math
math
11-25 00:00
arXiv:2511.17503v1 Announce Type: new Abstract: In this paper, we show how to expand Euclidean/Hermitian self-orthogonal code preserving their orthogonal property. Our results show that every $k$-dimension Hermitian self-orthogonal code is contained in a $(k+1)$-dimensional Hermitian self-orthogonal code. Also, for $k< n/2-1$, every $[n,k]$ Euclidean self-orthogonal code is contained in an $[n,k+1]$ Euclidean self-orthogonal code. Moreover, for $k=n/2-1$ and $p=2$, we can also fulfill the expanding process. But for $k=n/2-1$ and $p$ odd prime, the expanding process can be fulfilled if and only if an extra condition must be satisfied. We also propose two feasible algorithms on these expanding procedures.
cs.itmath.comath.it
math
math
11-25 00:00
arXiv:2511.17504v1 Announce Type: new Abstract: We study covert communication and covert secret key generation with positive rates over quantum state-dependent channels. Specifically, we consider fully quantum state-dependent channels when the transmitter shares an entangled state with the channel. We study this problem setting under two security metrics. For the first security metric, the transmitter aims to communicate covertly with the receiver while simultaneously generating a covert secret key, and for the second security metric, the transmitter aims to transmit a secure message covertly and generate a covert secret key with the receiver simultaneously. Our main results include one-shot and asymptotic achievable positive covert-secret key rate pairs for both security metrics. Our results recover as a special case the best-known results for covert communication over state-dependent classical channels. To the best of our knowledge, our results are the first instance of achieving a positive rate for covert secret key generation and the first instance of achieving a positive covert rate over a quantum channel. Additionally, we show that our results are optimal when the channel is classical and the state is available non-causally at both the transmitter and the receiver.
cs.itmath.it
math
math
11-25 00:00
arXiv:2511.17530v1 Announce Type: new Abstract: In this paper, we present different characterizations of tripotent orthogonal matrices (i.e., A^3 = A = A^* ) in terms of matrix equations, integer powers of AA^* and A^*A, average of A, A^*, and A^{\dagger}, rank of matrices, and trace of matrices. We study certain properties of this class of matrices.
math.oamath.ra
math
math
11-25 00:00
arXiv:2511.17536v1 Announce Type: new Abstract: We prove that Rado's graph admits no quantum symmetries.
math.oamath.qa
math
math
11-25 00:00
arXiv:2511.17650v1 Announce Type: new Abstract: Two evolution models based on the generalized Collatz operator are introduced. These models are characterized by coefficients $\alpha$ and $\beta$ in the Collatz dynamics, and are suitably defined. Here, $\alpha=\beta=1$, and $\alpha=3$, $\beta=1$ correspond to the Nollatz and classical Collatz operators, respectively. In general, the first evolution model is a continuum, Fourier side based, motivated by the Cubic Szeg\H{o} operator of G\'erard and Grellier. The second evolution considers discrete time derivatives of the Collatz orbits. In this paper we describe the evolution of both models, with particular emphasis on dynamical properties. For the first one, it is proved local and global existence in the space $L^2(\mathbb T)$, and a one-to-one characterization of the existence of nontrivial periodic and unbounded orbits of the Collatz mapping in terms of particular set of solutions of this continuous Collatz flow. For the discrete part, a sort of discrete energy is introduced. This energy has the property of being conserved by the discrete flow. An estimate of each term in this energy is given, proving suitable growth bounds. Finally, the meaning of the discrete time derivative for the generalized Collatz orbits is discussed. It is proved that, except for the Nollatz and Collatz operators, the sum of coefficients related to this discrete time derivative is an increasing sequence in $n$ as the iteration parameter $n$ evolves.
math.apmath.ds
math
math
11-25 00:00
arXiv:2511.17718v1 Announce Type: new Abstract: We consider a two-user random access system in which each user independently selects a coding scheme from a finite set for every message, without sharing these choices with the other user or with the receiver. The receiver aims to decode only user 1 message but may also decode user 2 message when beneficial. In the synchronous setting, the receiver employs two parallel sub-decoders: one dedicated to decoding user 1 message and another that jointly decodes both users messages. Their outputs are synthesized to produce the final decoding or collision decision. For the asynchronous setting, we examine a time interval containing $L$ consecutive codewords from each user. The receiver deploys $2^{2L}$ parallel sub-decoders, each responsible for decoding a subset of the message-code index pairs. In both synchronous and asynchronous cases, every sub-decoder partitions the coding space into three disjoint regions: operation, margin, and collision, and outputs either decoded messages or a collision report according to the region in which the estimated code index vector lies. Error events are defined for each sub-decoder and for the overall receiver whenever the expected output is not produced. We derive achievable upper bounds on the generalized error performance, defined as a weighted sum of incorrect-decoding, collision, and miss-detection probabilities, for both synchronous and asynchronous scenarios.
cs.itmath.it
math
math
11-25 00:00
arXiv:2511.17719v1 Announce Type: new Abstract: Let $G$ be a finite group and $K$ a field containing an element of multiplicative order $|G|$. It is shown that if $G$ has a cyclic subgroup of index at most $2$, then the separating Noether number over $K$ of $G$ coincides with the Noether number over $K$ of $G$. The same conclusion holds when $G$ is the direct product of a dihedral group and the $2$-element group. On the other hand, the smallest non-abelian groups $G$ are found for which the separating Noether number over $K$ is strictly less than the Noether number over $K$. Along the way the exact value of the separating Noether number is determined for all groups of order at most $16$. The results show in particular that unlike the ordinary Noether number, the separating Noether number of a non-abelian finite group may well be equal to the separating Noether number of a proper direct factor of the group.
math.acmath.rtmath.gr
math
math
11-25 00:00
arXiv:2511.17723v1 Announce Type: new Abstract: In the space of equioriented type $A$ quiver representations, placing strict rank conditions on the maps cuts out subvarieties that we call "open quiver loci." Their closures are the quiver loci, whose equivariant cohomology classes are the quiver polynomials of Buch and Fulton. We present a geometric and a combinatorial formula to compute equivariant Chern--Schwartz--MacPherson (CSM) classes of open quiver loci. These classes naturally associate an element of equivariant cohomology to each open quiver locus, and they include the data of the quiver polynomials, along with additional data about Euler characteristic. The combinatorial formula is in terms of "chained generic pipe dreams," which modify the pipe dreams of Fomin and Kirillov to more strongly resemble the lacing diagrams developed by Knutson-Miller-Shimozono. We also present three new formulas for quiver polynomials, two of which are combinatorial; these are streamlined versions of the previously known Knutson-Miller-Shimozono formulas, in the sense that they contain fewer terms.
math.agmath.co
cs
cs
11-25 00:00
arXiv:2511.17503v1 Announce Type: new Abstract: In this paper, we show how to expand Euclidean/Hermitian self-orthogonal code preserving their orthogonal property. Our results show that every $k$-dimension Hermitian self-orthogonal code is contained in a $(k+1)$-dimensional Hermitian self-orthogonal code. Also, for $k< n/2-1$, every $[n,k]$ Euclidean self-orthogonal code is contained in an $[n,k+1]$ Euclidean self-orthogonal code. Moreover, for $k=n/2-1$ and $p=2$, we can also fulfill the expanding process. But for $k=n/2-1$ and $p$ odd prime, the expanding process can be fulfilled if and only if an extra condition must be satisfied. We also propose two feasible algorithms on these expanding procedures.
cs.itmath.comath.it
cs
cs
11-25 00:00
arXiv:2511.17504v1 Announce Type: new Abstract: We study covert communication and covert secret key generation with positive rates over quantum state-dependent channels. Specifically, we consider fully quantum state-dependent channels when the transmitter shares an entangled state with the channel. We study this problem setting under two security metrics. For the first security metric, the transmitter aims to communicate covertly with the receiver while simultaneously generating a covert secret key, and for the second security metric, the transmitter aims to transmit a secure message covertly and generate a covert secret key with the receiver simultaneously. Our main results include one-shot and asymptotic achievable positive covert-secret key rate pairs for both security metrics. Our results recover as a special case the best-known results for covert communication over state-dependent classical channels. To the best of our knowledge, our results are the first instance of achieving a positive rate for covert secret key generation and the first instance of achieving a positive covert rate over a quantum channel. Additionally, we show that our results are optimal when the channel is classical and the state is available non-causally at both the transmitter and the receiver.
cs.itmath.it
cs
cs
11-25 00:00
arXiv:2511.17505v1 Announce Type: new Abstract: To keep modern Radio Access Networks (RAN) running smoothly, operators need to spot the real-world triggers behind Service-Level Agreement (SLA) breaches well before customers feel them. We introduce an AI/ML pipeline that does two things most tools miss: (1) finds the likely root-cause indicators and (2) reveals the exact order in which those events unfold. We start by labeling network data: records linked to past SLA breaches are marked `abnormal', and everything else `normal'. Our model then learns the causal chain that turns normal behavior into a fault. In Monte Carlo tests the approach pinpoints the correct trigger sequence with high precision and scales to millions of data points without loss of speed. These results show that high-resolution, causally ordered insights can move fault management from reactive troubleshooting to proactive prevention.
cs.nics.lg
cs
cs
11-25 00:00
arXiv:2511.17506v1 Announce Type: new Abstract: Next-generation (NextG) cellular networks are expected to manage dynamic traffic while sustaining high performance. Large language models (LLMs) provide strategic reasoning for 6G planning, but their computational cost and latency limit real-time use. Multi-agent reinforcement learning (MARL) supports localized adaptation, yet coordination at scale remains challenging. We present AURA, a framework that integrates cloud-based LLMs for high-level planning with base stations modeled as MARL agents for local decision-making. The LLM generates objectives and subgoals from its understanding of the environment and reasoning capabilities, while agents at base stations execute these objectives autonomously, guided by a trust mechanism that balances local learning with external input. To reduce latency, AURA employs batched communication so that agents update the LLM's view of the environment and receive improved feedback. In a simulated 6G scenario, AURA improves resilience, reducing dropped handoff requests by more than half under normal and high traffic and lowering system failures. Agents use LLM input in fewer than 60\% of cases, showing that guidance augments rather than replaces local adaptability, thereby mitigating latency and hallucination risks. These results highlight the promise of combining LLM reasoning with MARL adaptability for scalable, real-time NextG network management.
cs.nics.ai
cs
cs
11-25 00:00
arXiv:2511.17507v1 Announce Type: new Abstract: By observing the activities and relationships of musicians and sound designers to the activities of creation, performance, publishing and dissemination with artificial intelligence (AI), from two specialized forums between 2022 and 2024, this article proposes a lexicometric analysis of the representations linked to their use. Indeed, the machine, now equipped with artificial intelligences requiring new appropriations and enabling new mediations, constitutes new challenges for artists. To study these confrontations and new mediations, our approach mobilizes the theoretical framework of the Human-AI Musicking Framework, based on a lexicometric analysis of content. The aim is to clarify the present and future uses of AI from the interfaces, in the creation of sound and musical content, and to identify the obstacles, obstacles, brakes and limits to appropriation ``in the fact of making the content one's own and integrating it as a part of oneself'' (Bachimont and Crozat, 2004) in the context of a collaboration between musician and machine.
cs.hccs.ai
cs
cs
11-25 00:00
arXiv:2511.17508v1 Announce Type: new Abstract: Augmented Reality (AR) applications often require robust real-time tracking of objects in the user's environment to correctly overlay virtual content. Recent advances in computer vision have produced highly accurate deep learning-based object trackers, but these models are typically too heavy in computation and memory for wearable AR devices. In this paper, we present a lightweight RGB object tracking algorithm designed specifically for resource-constrained AR platforms. The proposed tracker employs a compact Siamese neural network architecture and incorporates optimization techniques such as model pruning, quantization, and knowledge distillation to drastically reduce model size and inference cost while maintaining high tracking accuracy. We train the tracker offline on large video datasets using deep convolutional neural networks and then deploy it on-device for real-time tracking. Experimental results on standard tracking benchmarks show that our approach achieves comparable accuracy to state-of-the-art trackers, yet runs in real-time on a mobile AR headset at around 30 FPS -- more than an order of magnitude faster than prior high-performance trackers on the same hardware. This work enables practical, robust object tracking for AR use-cases, opening the door to more interactive and dynamic AR experiences on lightweight devices.
cs.hccs.cv
cs
cs
11-25 00:00
arXiv:2511.17509v1 Announce Type: new Abstract: Human-AI collaboration outcomes depend strongly on human self-confidence calibration, which drives reliance or resistance toward AI's suggestions. This work presents two studies examining whether calibration of self-confidence before decision tasks, low versus high levels of Need for Cognition (NFC), and Actively Open-Minded Thinking (AOT), leads to differences in decision accuracy, self-confidence appropriateness during the tasks, and metacognitive perceptions (global and affective). The first study presents strategies to identify well-calibrated users, also comparing decision accuracy and the appropriateness of self-confidence across NFC and AOT levels. The second study investigates the effects of calibrated self-confidence in AI-assisted decision-making (no AI, two-stage AI, and personalized AI), also considering different NFC and AOT levels. Our results show the importance of human self-confidence calibration and psychological traits when designing AI-assisted decision systems. We further propose design recommendations to address the challenge of calibrating self-confidence and supporting tailored, user-centric AI that accounts for individual traits.
cs.hccs.ai
cs
cs
11-25 00:00
arXiv:2511.17511v1 Announce Type: new Abstract: To accelerate mechanical design and enhance design quality and innovation, we present a Multidisciplinary Design and Optimization (MDO) Agent driven by Large Language Models (LLMs). The agent semi-automates the end-to-end workflow by orchestrating three core capabilities: (i) natural-language-driven parametric modeling, (ii) retrieval-augmented generation (RAG) for knowledge-grounded conceptualization, and (iii) intelligent orchestration of engineering software for performance verification and optimization. Working in tandem, these capabilities interpret high-level, unstructured intent, translate it into structured design representations, automatically construct parametric 3D CAD models, generate reliable concept variants using external knowledge bases, and conduct evaluation with iterative optimization via tool calls such as finite-element analysis (FEA). Validation on three representative cases - a gas-turbine blade, a machine-tool column, and a fractal heat sink - shows that the agent completes the pipeline from natural-language intent to verified and optimized designs with reduced manual scripting and setup effort, while promoting innovative design exploration. This work points to a practical path toward human-AI collaborative mechanical engineering and lays a foundation for more dependable, vertically customized MDO systems.
cs.hccs.ai
cs
cs
11-25 00:00
arXiv:2511.17512v1 Announce Type: new Abstract: Mobile games have gained immense popularity due to their accessibility, allowing people to play anywhere, anytime. Dark patterns and deceptive designs (DPs) have been found in these and other gaming platforms within certain cultural contexts. Here, we explored DPs in the onboarding experiences of free-to-play mobile games from China and Japan. We identified several unique patterns and mapped their relative prevalence. We also found that game developers often employ combinations of DPs as a strategy ("DP Combos") and use elements that, while not inherently manipulative, can enhance the impact of known patterns ("DP Enhancers"). Guided by these findings, we then developed an enriched ontology for categorizing deceptive game design patterns into classes and subclasses. This research contributes to understanding deceptive game design patterns and offers insights for future studies on cultural dimensions and ethical game design in general.
cs.hccs.cy
cs
cs
11-25 00:00
arXiv:2511.17513v1 Announce Type: new Abstract: The study explores the effects of motivational climate on communication features, emotional states, collective efficacy, and performance in collaborative gaming environments. Forty participants with no prior gaming experience were randomly assigned to 20 gender-matched teams of three (including one confederate) across two motivational climates: positive-supportive (PS) or neutral-unsupported (NU) (10 teams per condition). Team members completed three progressively difficult levels of Overcooked! 2 during which communication contents, emotional responses, collective efficacy, and performance outcomes were observed and coded. Mixed-design MANOVAs and ANOVAs were employed to examine the effects of motivational climate and task difficulty on communication patterns, emotions, collective efficacy, and performance. Chi-square analyses were performed to test communication content differences between conditions. Results revealed that PS team members significantly outperformed NU teams at lower task difficulty level, but this advantage diminished as task complexity increased. Communication analysis revealed that PS team members utilized significantly more action-oriented, factual, and emotional/motivational statements, while NU team members used more statements of uncertainty and non-task-related communication. The percentage of the talk time increased with difficulty across both climate conditions. PS team members maintained more positive emotional profiles throughout, with higher excitement and happiness scores and lower anxiety, dejection, and anger compared to NU team members. Furthermore, PS team members reported consistently higher collective efficacy beliefs across all difficulty levels. These findings reveal that positive motivational climate enhances team communication effectiveness, emotional resilience, and performance outcomes in challenging collaborative environments.
cs.hccs.si
cs
cs
11-25 00:00
arXiv:2511.17514v1 Announce Type: new Abstract: Artificial intelligence (AI)-native radio access networks (RANs) will serve vertical industries with stringent requirements: smart grids, autonomous vehicles, remote healthcare, industrial automation, etc. To achieve these requirements, modern 5G/6G design increasingly leverage AI for network optimization, but the opacity of AI decisions poses risks in mission-critical domains. These use cases are often delivered via non-public networks (NPNs) or dedicated network slices, where reliability and safety are vital. In this paper, we motivate the need for transparent and trustworthy AI in high-stakes communications (e.g., healthcare, industrial automation, and robotics) by drawing on 3rd generation partnership project (3GPP)'s vision for non-public networks. We design a mathematical framework to model the trade-offs between transparency (explanation fidelity and fairness), latency, and graphics processing unit (GPU) utilization in deploying explainable AI (XAI) models. Empirical evaluations demonstrate that our proposed hybrid XAI model xAI-Native, consistently surpasses conventional baseline models in performance.
cs.nics.ai
cs
cs
11-25 00:00
arXiv:2511.17515v1 Announce Type: new Abstract: Systems analysis students increasingly use Generative AI, yet current pedagogy lacks systematic approaches for teaching responsible AI orchestration that fosters critical thinking whilst meeting educational outcomes. Students risk accepting AI suggestions blindly or uncritically without assessing alignment with user needs or contextual appropriateness. SAGE (Structured AI-Guided Education) addresses this gap by embedding GenAI into curriculum design, training students when to accept, modify, or reject AI contributions. Implementation with 18 student groups across four Australian universities revealed how orchestration skills develop. Most groups (84\%) moved beyond passive acceptance, showing selective judgment, yet none proactively identified gaps overlooked by both human and AI analysis, indicating a competency ceiling. Students strong at explaining decisions also performed well at integrating sources, and those with deep domain understanding consistently considered accessibility considerations. Accessibility awareness proved fragile. When writing requirements, 85\% of groups explicitly considered elderly users and cultural needs. Notably, 55\% of groups struggled identifying when AI misclassified system boundaries (what belongs inside versus outside the system), 45\% missed data management errors (how information is stored and updated), and 55\% overlooked missing exception handling. Three implications emerge for educators: (i) require students to document why they accepted, modified, or rejected each AI suggestion, making reasoning explicit; (ii) embed accessibility prompts at each development stage because awareness collapses without continuous scaffolding; and (iii) have students create their own specifications before using AI, then compare versions, and anchor to research or standards to identify gaps.
cs.hccs.ai
cs
cs
11-25 00:00
arXiv:2511.17519v1 Announce Type: new Abstract: The open radio access network (O-RAN) enables modular, intelligent, and programmable 5G network architectures through the adoption of software-defined networking (SDN), network function virtualization (NFV), and implementation of standardized open interfaces. It also facilitates closed loop control and (non/near) real-time optimization of radio access network (RAN) through the integration of non-real-time applications (rApps) and near-real-time applications (xApps). However, one of the security concerns for O-RAN that can severely undermine network performance and subject it to a prominent threat to the security & reliability of O-RAN networks is jamming attacks. To address this, we introduce SAJD-a self-adaptive jammer detection framework that autonomously detects jamming attacks in artificial intelligence (AI) / machine learning (ML)-integrated O-RAN environments. The SAJD framework forms a closed-loop system that includes near-real-time inference of radio signal jamming interference via our developed ML-based xApp, as well as continuous monitoring and retraining pipelines through rApps. Specifically, a labeler rApp is developed that uses live telemetry (i.e., KPIs) to detect model drift, triggers unsupervised data labeling, executes model training/retraining using the integrated & open-source ClearML framework, and updates deployed models on the fly, without service disruption. Experiments on O-RAN-compliant testbed demonstrate that the SAJD framework outperforms state-of-the-art (offline-trained with manual labels) jamming detection approach in accuracy and adaptability under various dynamic and previously unseen interference scenarios.
cs.nics.ai
cs
cs
11-25 00:00
arXiv:2511.17520v1 Announce Type: new Abstract: One of the main problems for farmers is the protection of their crops, before and after harvesting, from animals and birds. To overcome this problem, this paper proposes a model of safe farming in which the crops will be protected from vertebrates attack through a prevention system that is based on Wirelesses Sensors Networks. Different sensor nodes are placed around the field that detect animals or birds existence and generate required signals and information. This information is passed to the Repelling and Notifying System (RNS) that is installed at the field through a short range wireless technology, ZigBee. As RNS receives the information, it generates ultrasonic sounds that are unbearable for animals and birds, which causes them to run away from the field. These ultrasonic sounds are generated in a frequency range that only animals and birds can hear, while humans cannot notice the sound. The paper also proposes a notifying system. It will inform the farmer about animals or birds intrusion in the field through SMS, but doesn't need any action from the farmer. The low cost and power efficiency of the proposed system is a key advantage for developing countries where cost and power are major players in any system feasibility.
cs.nics.etcs.ai
cs
cs
11-25 00:00
arXiv:2511.17523v1 Announce Type: new Abstract: Distributed peer-to-peer (P2P) networking delivers the new blocks and transactions and is critical for the cryptocurrency blockchain system operations. Having poor P2P connectivity reduces the financial rewards from the mining consensus protocol. Previous research defines beneficalness of each Bitcoin peer connection and estimates the beneficialness based on the observations of the blocks and transactions delivery, which are after they are delivered. However, due to the infrequent block arrivals and the sporadic and unstable peer connections, the peers do not stay connected long enough to have the beneficialness score to converge to its expected beneficialness. We design and build Dynamic Peer Beneficialness Prediction (DyPBP) which predicts a peer's beneficialness by using networking behavior observations beyond just the block and transaction arrivals. DyPBP advances the previous research by estimating the beneficialness of a peer connection before it delivers new blocks and transactions. To achieve such goal, DyPBP introduces a new feature for remembrance to address the dynamic connectivity issue, as Bitcoin's peers using distributed networking often disconnect and re-connect. We implement DyPBP on an active Bitcoin node connected to the Mainnet and use machine learning for the beneficialness prediction. Our experimental results validate and evaluate the effectiveness of DyPBP; for example, the error performance improves by 2 to 13 orders of magnitude depending on the machine-learning model selection. DyPBP's use of the remembrance feature also informs our model selection. DyPBP enables the P2P connection's beneficialness estimation from the connection start before a new block arrives.
cs.nics.lg
cs
cs
11-25 00:00
arXiv:2511.17526v1 Announce Type: new Abstract: Radio maps (RMs), which provide location-based pathloss estimations, are fundamental to enabling proactive, environment-aware communication in 6G networks. However, existing deep learning-based methods for RM construction often model dynamic environments as a series of independent static snapshots, thereby omitting the temporal continuity inherent in signal propagation changes caused by the motion of dynamic entities. To address this limitation, we propose the task of spatio-temporal RM prediction, which involves forecasting a sequence of future maps from historical observations. A key barrier to this predictive approach has been the lack of datasets capturing continuous environmental evolution. To fill this gap, we introduce RadioMapMotion, the first large-scale public dataset of continuous RM sequences generated from physically consistent vehicle trajectories. As a baseline for this task, we propose RadioLSTM, a UNet architecture based on Convolutional Long Short-Term Memory (ConvLSTM) and designed for multi-step sequence forecasting. Experimental evaluations show that RadioLSTM achieves higher prediction accuracy and structural fidelity compared to representative baseline methods. Furthermore, the model exhibits a low inference latency, indicating its potential suitability for real-time network operations. Our project will be publicly released at: https://github.com/UNIC-Lab/RadioMapMotion upon paper acceptance.
cs.nics.ai
cs
cs
11-25 00:00
arXiv:2511.17528v1 Announce Type: new Abstract: Industrial automation in the energy sector requires AI systems that can operate autonomously regardless of network availability, a requirement that cloud-centric architectures cannot meet. This paper evaluates the application of Device-First Continuum AI (DFC-AI) to critical energy sector operations. DFC-AI, a specialized architecture within the Hybrid Edge Cloud paradigm, implements intelligent agents using a microservices architecture that originates at end devices and extends across the computational continuum. Through comprehensive simulations of energy sector scenarios including drone inspections, sensor networks, and worker safety systems, we demonstrate that DFC-AI maintains full operational capability during network outages while cloud and gateway-based systems experience complete or partial failure. Our analysis reveals that zero-configuration GPU discovery and heterogeneous device clustering are particularly well-suited for energy sector deployments, where specialized nodes can handle intensive AI workloads for entire fleets of inspection drones or sensor networks. The evaluation shows that DFC-AI achieves significant latency reduction and energy savings compared to cloud architectures. Additionally, we find that gateway based edge solutions can paradoxically cost more than cloud solutions for certain energy sector workloads due to infrastructure overhead, while DFC-AI can consistently provide cost savings by leveraging enterprise-owned devices. These findings, validated through rigorous statistical analysis, establish that DFC-AI addresses the unique challenges of energy sector operations, ensuring intelligent agents remain available and functional in remote oil fields, offshore platforms, and other challenging environments characteristic of the industry.
cs.nics.ai
q-bio
q-bio
11-25 00:00
arXiv:2511.17627v1 Announce Type: new Abstract: Benthic habitat is challenging due to the environmental complexity of the seafloor, technological limitations, and elevated operational costs, especially in under-explored regions. This generates knowledge gaps for the sustainable management of hydrobiological resources and their nexus with society. We developed ECOSAIC (Ecological Compression via Orthogonal Specialized Autoencoders for Interpretable Classification), an Artificial Intelligence framework for automatic classification of benthic habitats through interpretable latent representations using a customizable autoencoder. ECOSAIC compresses n-dimensional feature space by optimizing specialization and orthogonality between domain-informed features. We employed two domain-informed categories: biogeochemical and hydrogeomorphological, that together integrate biological, physicochemical, hydrological and geomorphological, features, whose constraints on habitats have been recognized in ecology for a century. We applied the model to the Colombian Pacific Ocean and the results revealed 16 benthic habitats, expanding from mangroves to deep rocky areas up to 1000 m depth. The candidate habitats exhibited a strong correspondence between their environmental constraints, represented in latent space, and their expected species composition. This correspondence reflected meaningful ecological associations rather than purely statistical correlations, where the habitat's environmental offerings align semantically with the species' requirements. This approach could improve the management and conservation of benthic habitats, facilitating the development of functional maps that support marine planning, biodiversity conservation and fish stock assessment. We also hope it provides new insights into how ecological principles can inform AI frameworks, particularly given the substantial data limitations that characterize ecological research.
cs.lgq-bio.pe
q-bio
q-bio
11-25 00:00
arXiv:2511.17641v1 Announce Type: new Abstract: Consider a population of organisms that harvest free energy from their environment to reproduce. This paper shows that if the organisms' reproductive rates are proportional to the amount of physical free energy that they can convert into reproductive work, then the implicit probabilities that the organisms assign to environmental states are updated according to Bayes' rule.
cond-mat.stat-mechq-bio.pe
q-bio
q-bio
11-25 00:00
arXiv:2511.17652v1 Announce Type: new Abstract: Advances in AI have introduced several strong models in computational pathology to usher it into the era of multi-modal diagnosis, analysis, and interpretation. However, the current pathology-specific visual language models still lack capacities in making diagnosis with rigorous reasoning paths as well as handling divergent tasks, and thus challenges of building AI Copilots for real scenarios still exist. Here we introduce TeamPath, an AI system powered by reinforcement learning and router-enhanced solutions based on large-scale histopathology multimodal datasets, to work as a virtual assistant for expert-level disease diagnosis, patch-level information summarization, and cross-modality generation to integrate transcriptomic information for the clinical usage. We also collaborate with pathologists from Yale School of Medicine to demonstrate that TeamPath can assist them in working more efficiently by identifying and correcting expert conclusions and reasoning paths. Overall, TeamPath can flexibly choose the best settings according to the needs, and serve as an innovative and reliable system for information communication across different modalities and experts.
cs.cvq-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.17685v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) is a technology that measures gene expression profiles within tissue sections while retaining spatial context. It reveals localized gene expression patterns and tissue heterogeneity, both of which are essential for understanding disease etiology. However, its high cost has driven efforts to predict spatial gene expression from whole slide images. Despite recent advancements, current methods still face significant limitations, such as under-exploitation of high-level biological context, over-reliance on exemplar retrievals, and inadequate alignment of heterogeneous modalities. To address these challenges, we propose DKAN, a novel Dual-path Knowledge-Augmented contrastive alignment Network that predicts spatially resolved gene expression by integrating histopathological images and gene expression profiles through a biologically informed approach. Specifically, we introduce an effective gene semantic representation module that leverages the external gene database to provide additional biological insights, thereby enhancing gene expression prediction. Further, we adopt a unified, one-stage contrastive learning paradigm, seamlessly combining contrastive learning and supervised learning to eliminate reliance on exemplars, complemented with an adaptive weighting mechanism. Additionally, we propose a dual-path contrastive alignment module that employs gene semantic features as dynamic cross-modal coordinators to enable effective heterogeneous feature integration. Through extensive experiments across three public ST datasets, DKAN demonstrates superior performance over state-of-the-art models, establishing a new benchmark for spatial gene expression prediction and offering a powerful tool for advancing biological and clinical research.
q-bio.qmcs.ai
q-bio
q-bio
11-25 00:00
arXiv:2511.17794v1 Announce Type: new Abstract: Understanding how cooperation emerges and persists is a central challenge in evolutionary game theory. Existing models often rely on restricted, hand-picked strategy sets, which can overlook critical behavioural pathways. A recent four-strategy framework showed that cheap talk can promote cooperation through local interactions, yet it remained unclear whether modelled strategies might alter these conclusions. Here, we extend this framework to the complete set of eight strategies that naturally arise from communication and decision-making rules. We show that incorporating the full strategy space dramatically changes the evolutionary landscape. Cooperation becomes both more robust and more versatile, driven by novel pathways absent in the restricted model. In particular, we uncover a previously overlooked mechanism in which suspicious cooperation catalyses a cyclic dynamic that sustains cooperation. Conversely, the assumed role of strategic defection in the biased model is fragile, acting mainly as a spoiler rather than a genuine evolutionary attractor. The complete model further reveals a rich spectrum of long-term behaviours, including stable coexistence among up to seven strategies and time-varying patterns of partial coexistence. These results demonstrate that the full strategy space unlocks hidden routes to cooperative behaviour and highlight the importance of comprehensive modelling when explaining the emergence of cooperation.
cs.gtq-bio.pe
q-bio
q-bio
11-25 00:00
arXiv:2511.17905v1 Announce Type: new Abstract: Gene regulatory networks exhibit remarkable stability, maintaining functional phenotypes despite genetic and environmental perturbations. Discrete dynamical models, such as Boolean networks, provide systems biologists with a tractable framework to explore the mathematical underpinnings of this robustness. A key mechanism conferring stability is canalization. This perspective synthesizes historical insights, formal definitions of canalization in discrete dynamical models, quantitative measures of stability, illustrative applications, and emerging challenges at the interface of theory and experiment.
q-bio.mnmath.dscs.dm
q-bio
q-bio
11-25 00:00
arXiv:2511.17996v1 Announce Type: new Abstract: Collapse Lineage Tree (CLTree) is a software tool that annotates, roots, and evaluates phylogenetic trees by using lineages. A recursive algorithm was designed to annotate the branches by the common taxonomic lineage of its descendants in a rooted tree. For an unrooted tree, it determines the root that best conforms to the taxonomic system based on the aforementioned lineage annotations. Based on the lineage annotations of notes, CLTree infers the monophyly of taxonomic units and quantifies the concordance between the phylogenetic tree and the taxonomic system base on Shannon entropy. The core algorithm of CLTree is highly efficient with linear complexity, capable of processing phylogenetic trees with 17,955 terminal nodes within one second. We believe that CLTree will serve as a powerful tool for study of evolution and taxonomy.
q-bio.peq-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.18010v1 Announce Type: new Abstract: Deep learning has emerged as a powerful framework for analyzing biomolecular dynamics trajectories, enabling efficient representations that capture essential system dynamics and facilitate mechanistic studies. We propose a neural network architecture incorporating Fourier Transform analysis to process trajectory data, achieving dual objectives: eliminating high-frequency noise while preserving biologically critical slow conformational dynamics, and establishing an isotropic representation space through the last hidden layer for enhanced dynamical quantification. Comparative protein simulations demonstrate our approach generates more uniform feature distributions than linear regression methods, evidenced by smoother state similarity matrices and clearer classification boundaries. Moreover, by using saliency score, we identified key structural determinants linked to effective energy landscapes governing system dynamics. We believe that the fusion of neural network features with physical order parameters creates a robust analytical framework for advancing biomolecular trajectory analysis.
q-bio.qmq-bio.bm
q-bio
q-bio
11-25 00:00
arXiv:2511.18057v1 Announce Type: new Abstract: Current models treat physiological signals as noise corrupting neural computation. Previously, we showed that removing these "artifacts" eliminates 70% of predictive correlation, suggesting body signals functionally drive cognition. Here, we investigate the mechanism using high-density EEG (64 channels, 10 subjects, 500+ trials) during P300 target recognition. Phase Slope Index revealed zero-lag synchrony (PSI=0.000044, p=0.061) with high coherence (0.316, p<0.0001). Ridge-regularized Granger causality showed massive bidirectional coupling (F=100.53 brain-to-body, F=62.76 body-to-brain) peaking simultaneously at 78.1ms, consistent with mutually coupled resonance pairs. Time-resolved entropy analysis (200ms windows, 25ms steps) revealed triphasic dynamics: (1) constraint accumulation (0-78ms) building causal drive without entropy change (delta-S=-0.002 bits, p=0.75); (2) supercritical transition (100-600ms) triggering state expansion (58% directional increase, binomial p=0.002); (3) sustained metastability. Critically, transition magnitude was uncorrelated with resonance strength (r=-0.044, p=0.327), indicating binary threshold dynamics. Understanding emerges through a thermodynamic sequence: brain-body resonance acts as a discrete gate triggering non-linear information integration. This architecture may fundamentally distinguish biological from artificial intelligence. Keywords: embodied cognition, phase transitions, Granger causality, thermodynamics, neuromorphic computing, resonance dynamics, EEG artifacts
eess.spq-bio.nc
q-bio
q-bio
11-25 00:00
arXiv:2511.18142v1 Announce Type: new Abstract: Population heterogeneity is a key factor in epidemic dynamics, influencing both transmission and final epidemic size. While heterogeneity is often modeled through age structure, spatial location, or contact patterns, differences in host susceptibility have recently gained attention, particularly during the COVID-19 pandemic. Building on the framework of Diekmann and Inaba (Journal of Mathematical Biology, 2023), we focus on the special case of SEIR-models, which are widely used for influenza and other respiratory infections. We derive the model equations under two distinct assumptions linking susceptibility and infectiousness. Analytical results show that heterogeneity in susceptibility reduces the epidemic final size compared to homogeneous models with the same basic reproduction number $\Ro$. In the case of gamma-distributed susceptibility, we obtain stronger results on the epidemic final size. The resulting model captures population heterogeneity through a single parameter, which makes it practical for fitting epidemic data. We illustrate its use by applying it to seasonal influenza in Italy.
q-bio.pemath.ds
q-bio
q-bio
11-25 00:00
arXiv:2511.18325v1 Announce Type: new Abstract: Psychedelics, such as psilocybin, reorganise large-scale brain connectivity, yet how these changes are reflected across electrophysiological (electroencephalogram, EEG) and haemodynamic (functional magnetic resonance imaging, fMRI) networks remains unclear. We present Brain-MGF, a multimodal graph fusion network for joint EEG-fMRI connectivity analysis. For each modality, we construct graphs with partial-correlation edges and Pearson-profile node features, and learn subject-level embeddings via graph convolution. An adaptive softmax gate then fuses modalities with sample-specific weights to capture context-dependent contributions. Using the world's largest single-site psilocybin dataset, PsiConnect, Brain-MGF distinguishes psilocybin from no-psilocybin conditions in meditation and rest. Fusion improves over unimodal and non-adaptive variants, achieving 74.0% accuracy and 76.5% F1 score on meditation, and 76.0% accuracy with 85.8% ROC-AUC on rest. UMAP visualisations reveal clearer class separation for fused embeddings. These results indicate that adaptive graph fusion effectively integrates complementary EEG-fMRI information, providing an interpretable framework for characterising psilocybin-induced alterations in large-scale neural organisation.
cs.lgq-bio.nc
q-bio
q-bio
11-25 00:00
arXiv:2511.18626v1 Announce Type: new Abstract: T cells are central to the adaptive immune response, capable of detecting pathogenic antigens while ignoring healthy tissues with remarkable specificity and sensitivity. Quantitatively understanding how T cell receptors (TCRs) discriminate among antigens requires biophysical models and theoretical analysis of signaling networks. Here, we review current theoretical frameworks of antigen recognition in the context of modern experimental and computational advances. Antigen potency spans a continuum and exhibits nonlinear effects within complex mixtures, challenging discrete classification and simple threshold-based models. This complexity motivates the development of models such as adaptive kinetic proofreading, which integrate both activating and inhibitory signals. Advances in high-throughput technologies now generate large-scale, quantitative datasets, enabling the refinement of such models through statistical and machine learning approaches. This convergence of theory, data, and computation promises deeper insights into immune decision-making and opens new avenues for rational immunotherapy design.
q-bio.mnq-bio.cbq-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.18745v1 Announce Type: new Abstract: Cell migration often exhibits long-range temporal correlations and anomalous diffusion, even in the absence of external guidance cues such as chemical gradients or topographical constraints. These observations raise a fundamental question: do such correlations simply reflect internal cellular processes, or do they enhance a cell's ability to navigate complex environments? In this work, we explore how temporally correlated noise (modeled using fractional Brownian motion) influences chemotactic search dynamics. Through computational experiments, we show that superdiffusive motion, when combined with gradient-driven migration, enables robust exploration of the chemoattractant landscape. Cells reliably reach the global maximum of the concentration field, even in the presence of spatial noise, secondary cues, or irregular signal geometry. We quantify this behavior by analyzing the distribution of first hitting times under varying degrees of temporal correlation. Notably, our results are consistent across diverse conditions, including flat and curved substrates, and scenarios involving both primary and self-generated chemotactic signals. Beyond biological implications, these findings also offer insight into the design of optimization and sampling algorithms that benefit from structured stochasticity.
stat.apcs.ceq-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.18883v1 Announce Type: new Abstract: Autocatalysis is an important feature of metabolic networks, contributing crucially to the self-maintenance of organisms. Autocatalytic subsystems of chemical reaction networks (CRNs) are characterized in terms of algebraic conditions on submatrices of the stoichiometric matrix. Here, we derive sufficient conditions for subgraphs supporting irreducible autocatalytic systems in the bipartite K\"onig representation of the CRN. On this basis, we develop an efficient algorithm to enumerate autocatalytic subnetworks and, as a special case, autocatalytic cores, i.e., minimal autocatalytic subnetworks, in full-size metabolic networks. The same algorithmic approach can also be used to determine autocatalytic cores only. As a showcase application, we provide a complete analysis of autocatalysis in the core metabolism of E. coli and enumerate irreducible autocatalytic subsystems of limited size in full-fledged metabolic networks of E. coli, human erythrocytes, and Methanosarcina barkeri (Archea). The mathematical and algorithmic results are accompanied by software enabling the routine analysis of autocatalysis in large CRNs.
q-bio.mnq-bio.cbmath.co
q-bio
q-bio
11-25 00:00
arXiv:2511.19068v1 Announce Type: new Abstract: Modern genomic analyses increasingly rely on pangenomes, that is, representations of the genome of entire populations. The simplest representation of a pangenome is a set of individual genome sequences. Compared to e.g. sequence graphs, this has the advantage that efficient exact search via indexes based on the Burrows-Wheeler Transform (BWT) is possible, that no chimeric sequences are created, and that the results are not influenced by heuristics. However, such an index may report a match in thousands of positions even if these all correspond to the same locus, making downstream analysis unnecessarily expensive. For sufficiently similar sequences (e.g. human chromosomes), a multiple sequence alignment (MSA) can be computed. Since an MSA tends to group similar strings in the same columns, it is likely that a string occurring thousands of times in the pangenome can be described by very few columns in the MSA. We describe a method to tag entries in the BWT with the corresponding column in the MSA and develop an index that can map matches in the BWT to columns in the MSA in time proportional to the output. As a by-product, we can efficiently project a match to a designated reference genome, a capability that current pangenome aligners based on the BWT lack.
cs.dsq-bio.gn
q-bio
q-bio
11-25 00:00
arXiv:2511.19093v1 Announce Type: new Abstract: Collective vigilance describes how animals in groups benefit from the predator detection efforts of others. Empirical observations typically find either a many-eyes strategy with all (or many) group members maintaining a low level of individual vigilance, or a sentinel strategy with one (or a few) individuals maintaining a high level of individual vigilance while others do not. With a general analytical treatment that makes minimal assumptions, we show that these two strategies are alternate solutions to the same adaptive problem of balancing the costs of predation and vigilance. Which strategy is preferred depends on how costs scale with the level of individual vigilance: many-eyes strategies are preferred where costs of vigilance rise gently at low levels but become steeper at higher levels (convex; e.g. an open field); sentinel strategies are preferred where costs of vigilance rise steeply at low levels and then flatten out (concave; e.g. environments with vantage points). This same dichotomy emerges whether individuals act selfishly to optimise their own fitness or cooperatively to optimise group fitness. The model is extended to explain discrete behavioural switching between strategies and differential levels of vigilance such as edge effects.
q-bio.pecs.maphysics.bio-ph
q-bio
q-bio
11-25 00:00
arXiv:2511.19184v1 Announce Type: new Abstract: Designing new protein structures is fundamental to computational biology, enabling advances in therapeutic molecule discovery and enzyme engineering. Existing diffusion-based generative models typically operate in Cartesian coordinate space, where adding noise disrupts strict geometric constraints such as fixed bond lengths and angles, often producing physically invalid structures. To address this limitation, we propose a Torsion-Space Diffusion Model that generates protein backbones by denoising torsion angles, ensuring perfect local geometry by construction. A differentiable forward-kinematics module reconstructs 3D coordinates with fixed 3.8 Angstrom backbone bond lengths while a constrained post-processing refinement optimizes global compactness via Radius of Gyration (Rg) correction, without violating bond constraints. Experiments on standard PDB proteins demonstrate 100% bond-length accuracy and significantly improved structural compactness, reducing Rg error from 70% to 18.6% compared to Cartesian diffusion baselines. Overall, this hybrid torsion-diffusion plus geometric-refinement framework generates physically valid and compact protein backbones, providing a promising path toward full-atom protein generation.
cs.aiq-bio.bm
q-bio
q-bio
11-25 00:00
arXiv:2511.19423v1 Announce Type: new Abstract: We present Genie-CAT, a tool-augmented large-language-model (LLM) system designed to accelerate scientific hypothesis generation in protein design. Using metalloproteins (e.g., ferredoxins) as a case study, Genie-CAT integrates four capabilities -- literature-grounded reasoning through retrieval-augmented generation (RAG), structural parsing of Protein Data Bank files, electrostatic potential calculations, and machine-learning prediction of redox properties -- into a unified agentic workflow. By coupling natural-language reasoning with data-driven and physics-based computation, the system generates mechanistically interpretable, testable hypotheses linking sequence, structure, and function. In proof-of-concept demonstrations, Genie-CAT autonomously identifies residue-level modifications near [Fe--S] clusters that affect redox tuning, reproducing expert-derived hypotheses in a fraction of the time. The framework highlights how AI agents combining language models with domain-specific tools can bridge symbolic reasoning and numerical simulation, transforming LLMs from conversational assistants into partners for computational discovery.
q-bio.qmcs.ai
q-bio
q-bio
11-25 00:00
arXiv:2511.12135v2 Announce Type: cross Abstract: Aligning molecular sequence representations (e.g., SMILES notations) with textual descriptions is critical for applications spanning drug discovery, materials design, and automated chemical literature analysis. Existing methodologies typically treat molecular captioning (molecule-to-text) and text-based molecular design (text-to-molecule) as separate tasks, relying on supervised fine-tuning or contrastive learning pipelines. These approaches face three key limitations: (i) conventional metrics like BLEU prioritize linguistic fluency over chemical accuracy, (ii) training datasets frequently contain chemically ambiguous narratives with incomplete specifications, and (iii) independent optimization of generation directions leads to bidirectional inconsistency. To address these issues, we propose RTMol, a bidirectional alignment framework that unifies molecular captioning and text-to-SMILES generation through self-supervised round-trip learning. The framework introduces novel round-trip evaluation metrics and enables unsupervised training for molecular captioning without requiring paired molecule-text corpora. Experiments demonstrate that RTMol enhances bidirectional alignment performance by up to 47% across various LLMs, establishing an effective paradigm for joint molecule-text understanding and generation.
cs.lgcs.aiq-bio.bm
physics
physics
11-25 00:00
arXiv:2511.17542v1 Announce Type: new Abstract: Networks of radiation detectors provide a platform for real-time radioactive source detection and identification in urban environments. Detection algorithms in these systems must adapt to naturally-occurring changes in background, which requires well-characterized relationships between precipitation events and their corresponding radiological signature. We present a description of rain-induced radon progeny deposition events occurring in Chicago from September 2023 through February 2024. We measure ambient gamma radiation levels, precipitation rate, temperature, pressure and relative humidity in a network of sensor nodes. For each identified precipitation period, we decompose spectra into static- and radon-associated components as defined by a non-negative matrix factorization (NMF) algorithm. We find a consistent power-law relationship between a precipitation-dependent peak of the radon progeny proxy (RPP) and the peak strength of radon-associated NMF component for most precipitation events. We conduct a case study of a rainfall period with abnormally high levels of implied radon progeny concentration and describe its temporal and spatial evolution. We hypothesize this phenomenon is due to the air mass path that intersects a uranium-rich region of Wyoming. Finally, we cluster precipitation events into three distinct categories. One category roughly corresponds to events with deep low-pressure systems and high relative radon concentration, while another is characteristic of light stratiform rain with slightly higher temperatures and intermediate relative radon concentration. The third category contains a weak-gradient or lake breeze convection showers with intermittent precipitation and low relative radon concentration. These findings suggest that radiological anomaly detection could be improved by training unique background models corresponding to each category of meteorological event.
physics.geo-phphysics.ao-ph
physics
physics
11-25 00:00
arXiv:2511.17546v1 Announce Type: new Abstract: We present a novel method for accurately measuring the absolute electric quadrupole moments of light transition elements $(23 \leq Z \leq 30 )$. Our approach is based on performing precision muonic x-ray spectroscopy of the $2s-2p$ manifold, which is also referred to as the Lamb shift. These transitions are too weak to be detected with dispersive methods and too overlapping to be resolved by solid-state detectors. Here, we propose the use of cryogenic microcalorimeters, which possess high efficiency and excellent energy resolution in the relevant energy regime, coupled with state-of-the-art theoretical calculations. We demonstrate the feasibility of this approach by performing extensive calculations and realistic simulations. In this way, we establish that the uncertainty in the absolute moment, which is transferred to the quadrupole moments of all isotopes in the chain, could be reduced by up to an order of magnitude within a day of measurement. These precise reference quadrupole moments serve as valuable inputs for nuclear structure studies and for benchmarking state-of-the-art quantum chemistry calculations in open-shell elements.
physics.atom-phnucl-ex
physics
physics
11-25 00:00
arXiv:2511.17551v1 Announce Type: new Abstract: We have developed a hypersonic high-order, high-performance code (H$^3$PC) utilizing the ``Trixi.jl" framework in order to simulate both non-reactive and chemically reactive compressible Euler and Navier-Stokes equations for complex three-dimensional geometries. H$^3$PC is parallel on CPU platforms and can perform exascale parallel computations of hypersonic turbulent flows. The numerical approach is based on the discontinuous Galerkin spectral element method, satisfying the entropy and energy stability conditions for the Euler equations. H$^3$PC can perform simulations of high-speed flows from subsonic to hypersonic speeds based on frozen, equilibrium, and non-equilibrium chemistry modeling of the gas mixture, using the \texttt{Mutation.jl} , which is a Julia package developed to wrap the C++-based Mutation++ library. H$^3$PC can also perform parallel adaptive mesh refinement for two- and three-dimensional Euler and Navier-Stokes discretizations with non-conforming elements. In this study, we first demonstrate the successful integration of Mutation++ into the H$^3$PC solver, and then verify its accuracy through simulations of Taylor-Green vortex flow, supersonic flow past a square and circular cylinder, and hypersonic P8-inlet.
physics.comp-phphysics.flu-dyn
physics
physics
11-25 00:00
arXiv:2511.17570v1 Announce Type: new Abstract: Novel oral nicotine products, particularly nicotine pouches, have rapidly gained popularity among adolescents. Among U.S. high school students, nicotine pouch use has doubled since 2021, with 2.4% reporting current use in 2024. We analyzed Florida Youth Tobacco Survey data from 2022-2024 to assess prevalence trends and developed a grade-structured compartmental model to project future trajectories and evaluate intervention strategies. The model accurately captured observed trends across all high school grades and projected continued growth without intervention. We evaluated single and multi-parameter intervention strategies. Single-parameter interventions demonstrated limited effectiveness while multi-parameter strategies showed substantial effects. These findings underscore the need for comprehensive, multi-faceted interventions incorporating prevention education, cessation support, policy enforcement, and peer influence modification. Grade-specific targeting can enhance overall program effectiveness. School-based interventions should be implemented rapidly to address the accelerating epidemic of oral nicotine use among adolescents.
physics.soc-phcs.cy
physics
physics
11-25 00:00
arXiv:2511.17658v1 Announce Type: new Abstract: As digital communication grows in importance when connecting with healthcare providers, traditional behavioral and content message features are imbued with renewed significance. If one is to meaningfully connect with them, it is crucial to understand what drives them to engage and respond. In this study, the authors analyzed several million text messages sent through the Impiricus platform to learn which factors influenced whether or not a doctor clicked on a link in a message. Several key insights came to light through the use of logistic regression, random forest, and neural network models, the details of which the authors discuss in this paper.
cs.lgstat.mlphysics.soc-phcs.cycs.ai
physics
physics
11-25 00:00
arXiv:2511.17691v1 Announce Type: new Abstract: I will discuss how the concept of basho, introduced by Nishida Kitaro nearly a century ago, can give an interesting insight to understand the concept of a point in modern quantum gravity. A quantum spacetime, necessary for the quantization of gravity, requires a whole rethinking of geometry, starting from the primitive concepts, like that of a point. I argue that the local vision of what becomes of classical points in quantum gravity, and in particular in noncommutative geometry, shows several similarities with Nishida's basho.
hep-thphysics.hist-phgr-qc
physics
physics
11-25 00:00
arXiv:2511.17753v1 Announce Type: new Abstract: Ab initio quantum chemical methods for accurately computing interactions between molecules have a wide range of applications but are often computationally expensive. Hence, selecting an appropriate method based on accuracy and computational cost remains a significant challenge due to varying performance of methods. In this work, we propose a framework based on an ensemble of $\Delta$-ML models trained on features extracted from a pre-trained atom-pairwise neural network to predict the error of each method relative to all other methods including the ``gold standard'' coupled cluster with single, double, and perturbative triple excitations at the estimated complete basis set limit [CCSD(T)/CBS]. Our proposed approach provides error estimates across various levels of theories and identifies the computationally efficient approach for a given error range utilizing only a subset of the dataset. Further, this approach allows comparison between various theories. We demonstrate the effectiveness of our approach using an extended BioFragment dataset, which includes the interaction energies for common biomolecular fragments and small organic dimers. Our results show that the proposed framework achieves very small mean-absolute-errors below 0.1 kcal/mol regardless of the given method. Furthermore, by analyzing all-to-all $\Delta$-ML models for present levels of theory, we identify method groupings that align with theoretical hypotheses, providing evidence that $\Delta$-ML models can easily learn corrections from any level of theory to any other level of theory.
cs.aiphysics.chem-ph
physics
physics
11-25 00:00
arXiv:2511.17788v1 Announce Type: new Abstract: The IceCube Neutrino Observatory is a cubic-kilometer Cherenkov detector embedded in the Antarctic ice at the South Pole. Its densely instrumented sub-array and dedicated low-energy analyses provide sensitivity to neutrinos in the 5-100 GeV range, enabling precision studies of neutrino oscillations and searches for new physics. This work focuses specifically on this low-energy regime, where sparse hit patterns limit the performance of topology-based reconstruction and classification methods. We introduce Waveform-based Particle Identification (WavePID), a statistically rigorous and interpretable likelihood-ratio discriminator for track-cascade separation, built from Monte Carlo templates in timing-aware, physics-motivated observables and validated through dedicated simulations. Applied to both Monte Carlo and 11.1 years of IceCube data, WavePID suggests improved cascade purity by about 5 percentage points at a fixed 20% down-selection rate relative to the current leading cascade selection, while maintaining Data-MC agreement within detector systematics. The approach is compact and robust to sparse observations, demonstrating the value of waveform-level timing for low-energy reconstruction.
astro-ph.hephysics.ins-dethep-ex
physics
physics
11-25 00:00
arXiv:2511.17831v1 Announce Type: new Abstract: Free energy landscapes encode the kinetics, intermediates, and transition states that govern molecular processes and are thus a key target of single biomolecule research. Typical approaches to deriving optimal, error-minimizing, non-equilibrium driving protocols for estimating these landscapes require a priori knowledge of the landscape. Here, we present an alternative: an iterative algorithm for optimizing full free energy landscape reconstructions which can be used alongside experiments on unknown landscapes. Our approach (i) takes experimental or simulated trajectory data; (ii) reconstructs an `approximate' energy landscape; (iii) derives optimal control protocols from low-dimensional differentiable Brownian dynamics simulations on the candidate landscape using automatic differentiation; (iv) re-runs the experiment or simulation using the updated protocol; and (v) iterates until convergence. Using this approach, we recover known benchmarks from the literature and probe far-from-equilibrium regimes for symmetric, asymmetric, and triple-well energy landscapes under both 1- and 2-dimensional control. Our control protocols -- derived with no a priori knowledge of the energy landscape -- yield substantially reduced variance and bias in free energy landscape reconstructions compared to naive linear protocols.
cond-mat.stat-mechphysics.bio-phphysics.comp-ph
physics
physics
11-25 00:00
arXiv:2511.17850v1 Announce Type: new Abstract: We demonstrate that multipoint Bayesian algorithm execution can overcome fundamental computational challenges in storage ring design optimization. Dynamic (DA) and momentum (MA) optimization is a multipoint, multiobjective design task for storage rings, ultimately informing the flux of x-ray sources and luminosity of colliders. Current state-of-art black-box optimization methods require extensive particle-tracking simulations for each trial configuration; the high computational cost restricts the extent of the search to $\sim 10^3$ configurations, and therefore limits the quality of the final design. We remove this bottleneck using multipointBAX, which selects, simulates, and models each trial configuration at the single particle level. We demonstrate our approach on a novel design for a fourth-generation light source, with neural-network powered multipointBAX achieving equivalent Pareto front results using more than two orders of magnitude fewer tracking computations compared to genetic algorithms. The significant reduction in cost positions multipointBAX as a promising alternative to black-box optimization, and we anticipate multipointBAX will be instrumental in the design of future light sources, colliders, and large-scale scientific facilities.
cs.lgphysics.acc-ph
physics
physics
11-25 00:00
arXiv:2511.17859v1 Announce Type: new Abstract: Natural hyperbolic materials have attracted significant interest in the field of photonics due to their unique optical properties. Based on the initial successful explorations on layered crystalline materials, hyperbolic dispersion was associated with extreme structural anisotropy, despite the rarity of natural materials exhibiting this property. Here we show that non cubic electrides are generally promising natural hyperbolic materials owing to charge localization in interstitial sites. This includes elemental and binary electrides, as well as some two-dimensional materials that show prominent in-plane hyperbolic dispersion. They exhibit low plasma frequencies and a broad hyperbolic window spanning the infrared to the ultraviolet. In semiconductor electrides, anisotropic interband transitions provide an additional mechanism for hyperbolic behaviour. These findings remove the previously held prerequisite of structural anisotropy for natural hyperbolic materials, and open up new opportunities, which might change the current strategy for searching and design photonic materials.
physics.opticscond-mat.mtrl-sciquant-phphysics.app-phphysics.comp-ph
physics
physics
11-25 00:00
arXiv:2511.17863v1 Announce Type: new Abstract: High-fidelity shock experiments were performed on copper powders with controlled porosity via improved target fabrication and assembly. Optical velocimetry and multi-channel pyrometry were used to obtain Hugoniot data, isentropic release paths, and interface temperature histories. The results validate a modified two-phase equation of state (EOS) for copper based on the framework of Greeff et al. The measured Hugoniot shows good agreement with the present model but exhibits significant softening above ~156 GPa relative to the original Greeff EOS, indicating that reduction in lattice specific heat becomes essential when shock temperatures exceed three times the melting point (T > 3Tm). Unloading behavior matches hydrodynamic simulations incorporating the recalibrated EOS, confirming its accuracy for off-Hugoniot states. Theoretical analysis of temperature release profiles suggests that the thermal conductivity of shocked copper powders may be considerably higher than first-principles predictions. Crucially, despite heterogeneity in shock heating, the macroscopic dynamic response of copper powders with a porosity of ~1.7 is well captured by an average-density EOS model, supporting the use of porous material experiments for EOS validation under extreme conditions.
cond-mat.mtrl-scicond-mat.mes-hallphysics.app-ph
econ
econ
11-25 00:00
arXiv:2511.17866v1 Announce Type: new Abstract: This study evaluates large language models as estimable classifiers and clarifies how modeling choices shape downstream measurement error. Revisiting the Economic Policy Uncertainty index, we show that contemporary classifiers substantially outperform dictionary rules, better track human audit assessments, and extend naturally to noisy historical and multilingual news. We use these tools to construct a new nineteenth-century U.S. index from more than 360 million newspaper articles and exploratory cross-country indices with a single multilingual model. Taken together, our results show that LLMs can systematically improve text-derived measures and should be integrated as explicit measurement tools in empirical economics.
q-fin.ececon.gn
econ
econ
11-25 00:00
arXiv:2511.17928v1 Announce Type: new Abstract: This paper develops limit theorems for random variables with network dependence, without requiring that individuals in the network to be located in a Euclidean or metric space. This distinguishes our approach from most existing limit theorems in network econometrics, which are based on weak dependence concepts such as strong mixing, near-epoch dependence, and $\psi$-dependence. By relaxing the assumption of an underlying metric space, our theorems can be applied to a broader range of network data, including financial and social networks. To derive the limit theorems, we generalize the concept of functional dependence (also known as physical dependence) from time series to random variables with network dependence. Using this framework, we establish several inequalities, a law of large numbers, and central limit theorems. Furthermore, we verify the conditions for these limit theorems based on primitive assumptions for spatial autoregressive models, which are widely used in network data analysis.
stat.thmath.stecon.em
econ
econ
11-25 00:00
arXiv:2511.18550v1 Announce Type: new Abstract: This paper presents robust inference methods for general linear hypotheses in linear panel data models with latent group structure in the coefficients. We employ a selective conditional inference approach, deriving the conditional distribution of coefficient estimates given the group structure estimated from the data. Our procedure provides valid inference under possible violations of group separation, where distributional properties of group-specific coefficients remain unestablished. Furthermore, even when group separation does hold, our method demonstrates superior finite-sample properties compared to traditional asymptotic approaches. This improvement stems from our procedure's ability to account for statistical uncertainty in the estimation of group structure. We demonstrate the effectiveness of our approach through Monte Carlo simulations and apply the methods to two datasets on: (i) the relationship between income and democracy, and (ii) the cyclicality of firm-level R&D investment.
stat.mlstat.meecon.em
econ
econ
11-25 00:00
arXiv:2511.18576v1 Announce Type: new Abstract: Access to finance is vital for improving food security, particularly in developing nations where agricultural production is crucial. Despite several financial interventions targeted at increasing agricultural production, smallholder farmers continue to lack access to reasonable, timely, and sufficient financing, limiting their ability to invest in improved technology and inputs, lowering productivity and food supply. This study examines the relationship between access to finance and food security among smallholder farmers in Ogun State, employing institutional theory as a theoretical framework. The study takes a quantitative method, with a survey for the research design and a population of 37,200 agricultural smallholder farmers. A sample size of 380 was chosen using probability sampling and simple random techniques. The data were analysed via Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings demonstrate a favourable relationship between access to finance and food security, with an R2-value of 0.615 indicating a robust link. These findings underline the need of improving financial institutions and implementing enabling policies to enable farmers have access to the financial resources they need to achieve food security outcomes.
q-fin.ececon.gn
econ
econ
11-25 00:00
arXiv:2511.18582v1 Announce Type: new Abstract: Concerns about how workers are perceived can deter effective collaboration with artificial intelligence (AI). In a field experiment on a large online labor market, I hired 450 U.S.-based remote workers to complete an image-categorization job assisted by AI recommendations. Workers were incentivized by the prospect of a contract extension based on an HR evaluator's feedback. I find that workers adopt AI recommendations at lower rates when their reliance on AI is visible to the evaluator, resulting in a measurable decline in task performance. The effects are present despite a conservative design in which workers know that the evaluator is explicitly instructed to assess expected accuracy on the same AI-assisted task. This reduction in AI reliance persists even when the evaluator is reassured about workers' strong performance history on the platform, underscoring how difficult these concerns are to alleviate. Leveraging the platform's public feedback feature, I introduce a novel incentive-compatible elicitation method showing that workers fear heavy reliance on AI signals a lack of confidence in their own judgment, a trait they view as essential when collaborating with AI.
cs.hcq-fin.ececon.gncs.ai
econ
econ
11-25 00:00
arXiv:2511.18647v1 Announce Type: new Abstract: This paper introduces a prior-free framework for information design based on partial identification and applies it to robust causal inference. The decision maker observes the distribution of signals generated by an information structure and ranks alternatives by their worst-case payoff over the state distributions consistent with those signals. We characterize the set of robustly implementable actions and show that each can be implemented by an information structure that withholds at most one dimension of information from the decision maker. In the potential outcomes model, every treatment is implementable via an experiment that is almost fully informative.
econ.thecon.em
econ
econ
11-25 00:00
arXiv:2511.18738v1 Announce Type: new Abstract: Mutual trust is a key determinant of decision-making in economic interactions, yet actual behavior often diverges from equilibrium predictions. This study investigates how emotional arousal, indexed by skin conductance responses,SCR, relates to trust behavior in a modified centipede game. To examine the impact of uncertainty, the game incorporated both fixed and random termination conditions. SCRs were recorded alongside self-reported measures of mutual and general trust and individual risk-taking propensity. Phasic SCRs were significantly higher under random termination, particularly following the opponent take actions, indicating increased emotional arousal under uncertainty. Mutual trust scores correlated positively with risk propensity but not with general trust. Behaviorally, higher mutual trust was associated with extended cooperative play, but only in the fixed-turn condition. These findings suggest that physiological arousal reflects emotional engagement in trust-related decisions and that uncertainty amplifies both arousal and strategic caution. Mutual trust appears context-dependent, shaped by emotional and physiological states that influence deviations from equilibrium behavior.
q-fin.ececon.gn
econ
econ
11-25 00:00
arXiv:2511.18944v1 Announce Type: new Abstract: We revisit Esteban and Ray's (1994) seminal model of polarization. Their main result (unnecessarily) relies on the assumption that individuals are infinitely divisible, which imposes strong restrictions on admissible polarization indices. We show that relaxing this assumption yields a broader family of indices consistent with the original axioms. The resulting indices avoid counter-intuitive rankings that arise when using results on the original paper and provide greater flexibility for empirical applications.
q-fin.ececon.gn
econ
econ
11-25 00:00
arXiv:2511.19121v1 Announce Type: new Abstract: We propose a new formulation of the maximum score estimator that uses compositions of rectified linear unit (ReLU) functions, instead of indicator functions as in Manski (1975,1985), to encode the sign alignment restrictions. Since the ReLU function is Lipschitz, our new ReLU-based maximum score criterion function is substantially easier to optimize using standard gradient-based optimization pacakges. We also show that our ReLU-based maximum score (RMS) estimator can be generalized to an umbrella framework defined by multi-index single-crossing (MISC) conditions, while the original maximum score estimator cannot be applied. We establish the $n^{-s/(2s+1)}$ convergence rate and asymptotic normality for the RMS estimator under order-$s$ Holder smoothness. In addition, we propose an alternative estimator using a further reformulation of RMS as a special layer in a deep neural network (DNN) architecture, which allows the estimation procedure to be implemented via state-of-the-art software and hardware for DNN.
stat.mlecon.em
econ
econ
11-25 00:00
arXiv:2511.17646v1 Announce Type: cross Abstract: This study explores Bitcoin's value formation through the Granular Interaction Thinking Theory-Value Theory (GITT-VT). Rather than stemming from material utility or cash flows, Bitcoin's value arises from informational attributes and interactions of multiple factors, including cryptographic order, decentralization-enabled autonomy, trust embedded in the consensus mechanism, and socio-narrative coherence that reduce entropy within decentralized value-exchange processes. To empirically assess this perspective, a Bayesian linear model was estimated using daily data from 2022 to 2025, operationalizing four informational value dimensions: Store-of-Value (SOV), Autonomy (AUT), Social-Signal Value (SSV), and Hedonic-Sentiment Value (HSV). Results indicate that only SSV exerts a highly credible positive effect on next-day returns, highlighting the dominant role of high-entropy social information in short-term pricing dynamics. In contrast, SOV and AUT show moderately reliable positive associations, reflecting their roles as low-entropy structural anchors of long-term value. HSV displays no credible predictive effect. The study advances interdisciplinary value theory and demonstrates Bitcoin as a dual-layer entropy-regulating socio-technological ecosystem. The findings offer implications for digital asset valuation, investment education, and future research on entropy dynamics across non-cash-flow digital assets.
q-fin.eccs.cyecon.gn
econ
econ
11-25 00:00
arXiv:2511.18614v1 Announce Type: cross Abstract: Debt recycling is a leveraged equity management strategy in which homeowners use accumulated home equity to finance investments, applying the resulting returns to accelerate mortgage repayment. We propose a novel framework to model equity and mortgage dynamics in presence of mortgage interest rates, borrowing costs on equity-backed credit lines, and tax shields arising from interest deductibility. The model is calibrated on three jurisdictions -- Australia, Germany, and Switzerland -- representing diverse interest rate environments and fiscal regimes. Results demonstrate that introducing positive interest rates without tax shields contracts success regions and lengthens repayment times, while tax shields partially reverse these effects by reducing effective borrowing costs and adding equity boosts from mortgage interest deductibility. Country-specific outcomes vary systematically, and rental properties consistently outperform owner-occupied housing due to mortgage interest deductibility provisions.
cond-mat.stat-mechq-fin.ececon.gnq-fin.rm
econ
econ
11-25 00:00
arXiv:2511.18641v1 Announce Type: cross Abstract: High-dimensional vector autoregressive (VAR) models have numerous applications in fields such as econometrics, biology, climatology, among others. While prior research has mainly focused on linear VAR models, these approaches can be restrictive in practice. To address this, we introduce a high-dimensional non-parametric sparse additive model, providing a more flexible framework. Our method employs basis expansions to construct high-dimensional nonlinear VAR models. We derive convergence rates and model selection consistency for least squared estimators, considering dependence measures of the processes, error moment conditions, sparsity, and basis expansions. Our theory significantly extends prior linear VAR models by incorporating both non-Gaussianity and non-linearity. As a key contribution, we derive sharp Bernstein-type inequalities for tail probabilities in both non-sub-Gaussian linear and nonlinear VAR processes, which match the classical Bernstein inequality for independent random variables. Additionally, we present numerical experiments that support our theoretical findings and demonstrate the advantages of the nonlinear VAR model for a gene expression time series dataset.
stat.thmath.ststat.meecon.em
econ
econ
11-25 00:00
arXiv:2511.18733v1 Announce Type: cross Abstract: Information transmitted across modern communication platforms is degraded not only by intentional manipulation (disinformation) but also by intrinsic cognitive decay and topology-dependent social averaging (misinformation). We develop a continuous-fidelity field theory on multiplex networks with distinct layers representing private chats, group interactions, and broadcast channels. Our analytic solutions reveal three universal mechanisms controlling information quality: (i) groupthink blending, where dense group coupling drives fidelity to the initial group mean; (ii) bridge-node bottlenecks, where cross-community flow produces irreversible dilution; and (iii) a network-wide fidelity landscape set by a competition between broadcast truth-injection and structural degradation pathways. These results demonstrate that connectivity can reduce information integrity and establish quantitative control strategies to enhance fidelity in large-scale communication systems.
cs.itecon.thhep-thphysics.soc-phmath.it
econ
econ
11-25 00:00
arXiv:2511.19225v1 Announce Type: cross Abstract: We consider a bipartite network of buyers and sellers, where the sellers run locally independent Progressive Second-Price (PSP) auctions, and buyers may participate in multiple auctions, forming a multi-auction market with perfect substitute. The paper develops a projection-based influence framework for decentralized PSP auctions. We formalize primary and expanded influence sets using projections on the active bid index set and show how partial orders on bid prices govern allocation, market shifts, and the emergence of saturated one-hop shells. Our results highlight the robustness of PSP auctions in decentralized environments by introducing saturated components and a structured framework for phase transitions in multi-auction dynamics. This structure ensures deterministic coverage of the strategy space, enabling stable and truthful embedding in the larger game. We further model intra-round dynamics using an index to capture coordinated asynchronous seller updates coupled through buyers' joint constraints. Together, these constructions explain how local interactions propagate across auctions and gives premise for coherent equilibria--without requiring global information or centralized control.
econ.thcs.gtcs.ds
econ
econ
11-25 00:00
arXiv:2003.08421v5 Announce Type: replace Abstract: This paper studies how to design two-wave experiments in the presence of spillovers for precise inference on treatment effects. We consider units connected through a single network, local dependence among individuals, and a general class of estimands encompassing average treatment and average spillover effects. We introduce a statistical framework for designing two-wave experiments with networks, where the researcher optimizes over participants and treatment assignments to minimize the variance of the estimators of interest, using a first-wave (pilot) experiment to estimate the variance. We derive guarantees for inference on treatment effects and regret guarantees on the variance obtained from the proposed design mechanism. Our results illustrate the existence of a trade-off in the choice of the pilot study and formally characterize the pilot's size relative to the main experiment. Simulations using simulated and real-world networks illustrate the advantages of the method.
stat.meecon.em
econ
econ
11-25 00:00
arXiv:2309.13766v3 Announce Type: replace Abstract: We develop a general framework for reserve systems that allocate scarce resources such as vaccines to unit-demand agents under prioritization and eligibility constraints, along with a computationally efficient mechanism. Reserve systems allocate scarce resources --such as vaccines, medical units, school seats, or government positions-- to essential groups by creating categories with prioritized beneficiaries. Prior work typically assumed a common baseline priority ordering and featured either hard or soft reserves. The threshold reserve model we introduce supports independent priority orderings, mixtures of hard and soft reserves, and overlapping categories, thereby capturing both beneficiary designations and eligibility constraints while offering policymakers greater flexibility. Our Iterative Max-in-Max Assignment Mechanism (IMMAM) satisfies all desirable properties in this domain: it respects priorities within categories, maximizes resource utilization, and then lexicographically maximizes beneficiary assignments. IMMAM is path independent and therefore well-behaved in settings with multiple institutions making simultaneous allocation decisions. We leverage path independence to obtain comparative statics and to significantly improve the mechanism's computational efficiency. We outline applications of our framework in the context of vaccine allocation.
econ.thcs.ds
econ
econ
11-25 00:00
arXiv:2309.17216v4 Announce Type: replace Abstract: Despite the widespread implementation of conditional cash transfers in low- and middle-income countries, evidence on their long-term effects remains limited. This paper evaluates the impact of Ecuador's Human Development Grant on the formal labour market outcomes of children from eligible households. The programme, one of the first of its kind, was characterised by weak enforcement of its eligibility criteria. Using a regression discontinuity design, we find that the grant increased the probability of working in the formal sector by almost 13\% around 15 years after exposure, thereby helping to curb the intergenerational transmission of poverty. This positive effect is most likely to operate through human capital accumulation.
q-fin.ececon.gn
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17705v1 Announce Type: new Abstract: Primordial dark matter halos are well understood from cold dark matter-only simulations. Since they can contract significantly as baryons settle into their centers, direct comparisons with observed galaxies are complicated. We present an approach to reversing the halo contraction by numerically calculating the halo response to baryonic infall and iterating the initial condition. This allowed us to derive spherically averaged primordial dark matter halos for observed galaxies. We applied this approach to the Milky Way and found that the latest Gaia measurements for the rotation velocities imply an odd primordial Galactic halo: Its concentration and total mass differ by more than 3$\sigma$ from the predictions, and the density profile presents an inner core that is too shallow and an outer decline that is too steep to be compatible with the cold dark matter paradigm.
astro-ph.coastro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17706v1 Announce Type: new Abstract: Very long baseline interferometry (VLBI) achieves the highest angular resolution in astronomy. VLBI measures corrupted Fourier components, known as visibilities. Reconstructing on-sky images from these visibilities is a challenging inverse problem, particularly for sparse arrays such as the Event Horizon Telescope (EHT) and the Very Long Baseline Array (VLBA), where incomplete sampling and severe calibration errors introduce significant uncertainty in the image. To help guide convergence and control the uncertainty in image reconstructions, regularization on the space of images is utilized, such as enforcing smoothness or similarity to a fiducial image. Coupled with this regularization is the introduction of a new set of parameters that modulate its strength. We present a hierarchical Bayesian imaging approach (Hierarchical Interferometric Bayesian Imaging, HIBI) that enables the quantification of uncertainty for al parameters. Incorporating instrumental effects within HIBI is straightforward, allowing for simultaneous imaging and calibration of data. To showcase HIBI's effectiveness and flexibility, we build a simple imaging model based on Markov random fields and demonstrate how different physical components can be included, e.g., black hole shadow size, and their uncertainties can be inferred. For example, while the original EHT publications were unable to constrain the ring width of M87*, HIBI measures a width of $9.3\pm 1.3\,\mu{\rm as}$. We apply HIBI to image and calibrate EHT synthetic data, real EHT observations of M87*, and multifrequency observations of \oj287. Across these tests, HIBI accurately recovers a wide variety of image structures and quantifies their uncertainties. HIBI is publicly available in the Comrade.jl VLBI software repository.
astro-ph.heastro-ph.im
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17710v1 Announce Type: new Abstract: Entity is a new-generation, fully open-source particle-in-cell (PIC) code developed to overcome key limitations in astrophysical plasma modeling, particularly the extreme separation of scales and the performance challenges associated with evolving, GPU-centric computing infrastructures. It achieves hardware-agnostic performance portability across various GPU and CPU architectures using the Kokkos library. Crucially, Entity maintains a high standard for usability, clarity, and customizability, offering a robust and easy-to-use framework for developing new algorithms and grid geometries, which allows extensive control without requiring edits to the core source code. This paper details the core general-coordinate special-relativistic module. Entity is the first PIC code designed to solve the Vlasov-Maxwell system in general coordinates, enabling a coordinate-agnostic framework that provides the foundational structure for straightforward extension to arbitrary coordinate geometries. The core methodology achieves numerical stability by solving particle equations of motion in the global orthonormal Cartesian basis, despite using generalized coordinates like Cartesian, axisymmetric spherical, and quasi-spherical grids. Charge conservation is ensured via a specialized current deposition technique using conformal currents. The code exhibits robust scalability and performance portability on major GPU platforms (AMD MI250X, NVIDIA A100, and Intel Max Series), with the 3D particle pusher and the current deposition operating efficiently at about 2 nanoseconds per particle per timestep. Functionality is validated through a comprehensive suite of standard Cartesian plasma tests and the accurate modeling of relativistic magnetospheres in curvilinear axisymmetric geometries.
astro-ph.hephysics.plasm-ph
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17712v1 Announce Type: new Abstract: We analyze the H2 emission observed in the HH46 Class I system as part of PROJECT-J (Protostellar Jets Cradle Tested with JWST), to investigate the origin and excitation of the warm molecular outflow. We used NIRSpec and MIRI spectral maps (1.6-27.9 microns) to trace the structure and physical conditions of the outflow. By fitting the H2 rotational diagrams with a multi-temperature gas model, we derived key physical parameters including temperature, extinction, column densities, and the ortho-to-para ratio. This information is combined with a detailed kinematical analysis and comparison with irradiated shock models. We find no evidence of H2 temperature or velocity stratification from the axis to the edge of the outflow, as would be expected in MHD disk-wind models and as observed in other outflows. Instead, the observations suggest that the H2 emission arises from shock interactions between jet bow shocks and/or wide-angle winds with the ambient medium and cavity walls. NIRSpec emission and velocity maps reveal expanding molecular shells, likely driven by the less luminous source in the binary system. We infer an accretion rate of less than 10^-9 solar masses per year for the secondary source, approximately one order of magnitude lower than that of the primary. The H2 emission is consistent with excitation by low-velocity (approximately 10 km/s) J-type shocks, irradiated by an external UV field that may originate from strong dissociative shocks driven by the atomic jet. Future JWST observations will further constrain the evolution of the expanding shell and the mechanisms driving the outflow.
astro-ph.srastro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17717v1 Announce Type: new Abstract: The relationship between the composition of rocky exoplanets and their host stars is fundamental to understanding planetary formation and evolution. However, previous studies have been limited by inconsistent datasets, observational biases and methodological differences. This study investigates the compositional relationship between rocky exoplanets and their host stars, utilizing a self-consistent and homogeneous dataset of 21 exoplanets and their 20 host stars. By applying sophisticated interior structure modeling and comprehensive chemical analysis, we identify a potential 1:1 best-fit line between the iron-mass fraction of planets and their host stars equivalent with a slope of $m = 0.94^{+1.02}_{-1.07}$ and intercept of $c = -0.02^{+0.31}_{-0.29}$. This results are consistent at the 1$\sigma$ level with other homogeneous studies, but not with heterogeneous samples that suggest much steeper best-fit lines. Although, our results remain tentative due to sample size and data uncertainties, the updated dataset significantly reduces the number of super-Mercuries from four to one, but it remains that several high-density planets are beyond what a primordial origin would suggest. The planets in our sample have a wider range of compositions compared to stellar equivalent values, that could indicate formation pathways away from primordial or be the result of random scattering owing to current mass-radius uncertainties as we recover the observed outliers in mock population analysis $\sim15\%$ of the time. To truly determine whether the origin is primordial with a 1:1 true relation, we find that sample of at least 150 planets is needed and that stars that are iron enrich or depleted are high value targets.
astro-ph.srastro-ph.ep
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17763v1 Announce Type: new Abstract: We report a series of images of the Tycho supernova remnant at eight epochs extending over thirty years: 1986-2016. In addition to our H{\alpha} images, we have obtained matched continuum images which we subtract to reveal faint emission, including a far more extensive network of optical knots and filaments than reported previously. The deepest images also show an extremely faint, fairly diffuse arc of emission surrounding much of the circumference of Tycho to the southeast and south, coinciding with the rim of the radio/X-ray shell. We have measured proper motions for 46 filaments, including many fainter ones near the Tycho outer rim. Our measurements are generally consistent with previous ones by Kamper and vandenBergh (1978), but ours have far greater precision. Most optical filaments at the shell rim have expansion indices reasonably consistent with the Sedov value (0.40), while the interior filaments have somewhat smaller values, as expected. From the combination of proper motions of filaments at the shell rim and shock velocity at the same positions, one should be able to calculate the distance to Tycho by simple geometry. Determination of the shock velocity from broad Balmer-line profiles is subject to model uncertainties, but the availability of dozens of such filaments with a range of conditions offers the possibility to substantially improve the distance determination for Tycho.
astro-ph.heastro-ph.srastro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17769v1 Announce Type: new Abstract: There is clear observational evidence that the main Class 0/I stages of the star formation process are associated with powerful collimated outflows (jets), which sometimes propagate up to distances as large as $10^{4-5}$ au scales in molecular clouds. Additionally, intermediate high-mass and low-mass protostars have often been observed to form in crowded clusters, where the typical separation distance between any two cluster members is of the same order or smaller than the scale of the outflow length. Therefore, there must be an interaction between the molecular outflows of different protostars within the protostellar association. A good example of this is the case of Cepheus E-mm, which is a protostellar outflow extending over a few dozen au. At its core is a binary system consisting of two protostars, Cep E-A and Cep E-B, separated by about 1000 au. Both protostars eject molecular jets at velocities of ~100 km/s. The interaction between these molecular outflows provides an opportunity to study the effects of jet collisions in a clustered star-forming environment, as they may leave detectable imprints on the morphology of the main envelope of the system. Our work aims to study the effects of the collision of molecular jets associated with the components of the binary system Cep-A and Cep-E, analyzing the disruption or reduction of molecular emission in the main envelope of the system, which the molecular outflow { launched} by Cep-A presumably pushes. If we characterize the collision in this system, we can provide insights into the expected morphology and molecular emissions in collisions of molecular outflows { associated to star forming process.
astro-ph.srastro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17797v1 Announce Type: new Abstract: The High Time Resolution Universe (HTRU) survey is an all-sky survey looking for pulsars and other radio transients. A new single-pulse (SP) search pipeline is presented, tailored to the northern part of the HTRU survey collected with the 100m Effelsberg Radio Telescope. In a selection of this data, synthetic SPs are injected with frequency-time structures resembling those of the detected Fast Radio Burst (FRB) population and processed by the pipeline to characterize its performance. Therefore, several new software toolkits have been developed (FRBfaker and RFIbye) to enable the injection of SPs with complex frequency-time structures and cope with the Radio Frequency Interference (RFI) in the survey's data. The operation of these toolkits is described alongside the overall functionality of the SP pipeline. Qualification of the pipeline confirmed that it is ready to process all the HTRU-North data. Additionally, the survey's sensitivity to SPs, the impact of RFI thereon, the performance of the deep-learning classifier FETCH, and some insights that may be used to improve the pipeline's performance in the future are determined. Within the small data sample analysed, 21 known pulsars and a RRAT are detected. In addition, eight faint SP trains that might originate from yet undiscovered neutron stars and 141 isolated SP candidates were discovered.
astro-ph.heastro-ph.im
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17872v1 Announce Type: new Abstract: Earth-like exoplanets can create resonant structures in exozodiacal dust through mean motion resonances (MMRs). These structures not only suggest the presence of such planets, but also act as potential noise sources in future mid-infrared (MIR) nulling interferometry observations. We aim to investigate how resonant structures in exozodiacal dust vary across stellar spectral types (F4--M4), and to evaluate how stellar wind drag affects their morphology and brightness in mature planetary systems. We conducted numerical simulations of dust dynamics, extending earlier studies by including spectral type variation in stellar wind drag in addition to Poynting-Robertson (PR) drag. Our models represented systems of a few Gyr hosting an Earth-like exoplanet in the habitable zone (HZ). We produced spatially resolved maps of optical depth and thermal emission for different stellar spectral types. Our simulations showed that resonant ring structures were formed for all stellar spectral types considered. In particular, we found that stellar wind drag played a critical role in shaping dust dynamics around old M-type stars, where it could dominate over PR drag by a factor of approximately 44. This reduced the contrast of resonant rings relative to the background disk, compared to cases without spectral type variation in stellar wind. Across different spectral types, the optical depth contrast of the resonant ring increased for lower-mass stars, assuming a fixed background level. Asymmetric thermal emission distributions were derived across all spectral types, which peaked for K-type stars. Our findings highlight the importance of incorporating both resonant dynamics and stellar wind effects when modeling exozodiacal dust around stars of different spectral types.
astro-ph.srastro-ph.ep
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17884v1 Announce Type: new Abstract: We announce a recently detected outburst that is currently only a few months old, and probably of FU Orionis type. The progenitor to the outburst was an emission-line, flat-spectrum SED young stellar object located in the W5 region, though somewhat outside the main star formation action. We present optical, near-infrared, and mid-infrared lightcurves that illustrate the quiescent state of [KAG2008] 13656 and its subsequent$\Delta r \approx -4$ mag and $\Delta J\approx -3$ mag outburst over $\sim$75 days in late-2025. Follow-up optical and near-infrared spectroscopy confirms the expected features from an FU Ori disk and outflow.
astro-ph.srastro-ph.ga
econ
econ
11-26 00:00
arXiv:2511.18664v2 Announce Type: replace Abstract: By clarifying the bases for the Verizon Communications Inc. v. Law Offices of Curtis V. Trinko, LLP, 2004 opinion, we hope to reduce two distinct errors. The false positive error is citing Trinko as precedent when it is not. This error is so prevalent it has earned the nickname of Trinko Creep. The false negative error is not citing Trinko when it should be. We argue that this error will be growing in the future as Trinko should be precedent in cases involving regulated access rights to sensitive consumer data in electronic health records and Agentic AI Long Term Memory.
q-fin.ececon.gn
math
math
11-25 00:00
arXiv:2511.17510v1 Announce Type: new Abstract: In this research article, we formulate and prove multidimensional Widder--Arendt theorem and integrated form of multidimensional Widder--Arendt theorem for functions with values in sequentially complete locally convex spaces. Established results seem to be new even for scalar-valued functions.
math.fa
math
math
11-25 00:00
arXiv:2511.17521v1 Announce Type: new Abstract: In this note it is proven that an idempotent ring cannot be Morita equivalent to its idempotent proper ideal.
math.ra
math
math
11-25 00:00
arXiv:2511.17522v1 Announce Type: new Abstract: The concepts of derivations and right derivations for Leibniz algebras and $K$-B quasi-Jordan algebras naturally arise from the inner derivations determined by their algebraic structures. In this paper we introduce the corresponding analogues for dialgebras, which we call diderivations, and examine their properties in relation to antiderivations and right derivations. Our approach is based on the study of multiplicative operators and on the construction of the Leibniz algebra generated by biderivations, thereby providing a systematic framework that unifies several types of derivation-like operators. In addition to the general theory, we present a complete classification of the spaces of diderivations for dialgebras of dimensions two and three, obtained through explicit computations. These low-dimensional results not only exemplify the general constructions but also reveal structural patterns that inform possible extensions to higher dimensions and more intricate algebraic contexts.28
math.ra
math
math
11-25 00:00
arXiv:2511.17534v1 Announce Type: new Abstract: This paper is concerned with the Cauchy problem of the evolutionary Faddeev model, a system that maps from the Minkowski space $\mathbb{R}^{1+3}$ to the unit sphere $\mathbb{S}^2$. The model is a system of nonlinear wave equations whose nonlinearities exhibit a null structure and include semilinear terms, quasilinear terms, and the unknowns themselves. By considering a class of large initial data (in energy norm) of the short pulse type, we prove that the evolutionary Faddeev model admits a globally smooth solution via energy estimates. The main result is achieved through the selection of appropriate multipliers that are specially adapted to the geometry of the system.
math.ap
math
math
11-25 00:00
arXiv:2511.17538v1 Announce Type: new Abstract: This paper intends to develop a $q$-difference operator $\nabla^{(\gamma)}_q$ of fractional order $\gamma$, and give several intriguing properties of this new difference operator. Our main focus remains on the construction of sequence spaces $\ell_p(\nabla^{(\gamma)})$ and $\ell_\infty (\nabla^{(\gamma)})$, at the same time comparing these spaces with those already exist in the literature. Apart from obtaining Schauder basis, we determine $\alpha$-, $\beta$-, and $\gamma$-duals of the newly defined spaces. A section is also devoted for characterizing matrix classes $(\ell_p(\nabla^{(\gamma)}),\mathfrak X),$ where $\mathfrak X$ is any of the spaces $\ell_\infty,$ $c,$ $c_0$ and $\ell_1$.
math.fa
math
math
11-25 00:00
arXiv:2511.17539v1 Announce Type: new Abstract: In this work we study the following classical still challenging Calculus problem: {\it If $f:(0,\infty)\to\mathbb{R}$ is a continuous function, for which the sequence $\{f(nx)\}$ tends to zero, for every positive $x$, as $n$ tends to infinity, then $f(x)$ also tends to zero, as $x$ tends to infinity.}
math.fa
math
math
11-25 00:00
arXiv:2511.17544v1 Announce Type: new Abstract: This paper introduces the concept of distorted monoidal categories, a generalization of monoidal and braided monoidal categories that supports non-reversible and direction-sensitive tensor structures. Unlike the classical setting, where the braiding symmetry is required to be invertible, distorted monoidal categories admit non-invertible binary distortions and unit distortions while preserving coherent tensorial reasoning. We show that these structures naturally assemble into a strict 2-category whose composition and interchange laws hold on the nose, not merely up to isomorphism. Beyond the abstract 2-monad justification, our contribution is a fully constructive and type-safe calculus that enables formal reasoning about non-invertible interchange. We provide explicit construction schemes for such distortions, including idempotent twists of classical braidings and graded unit distortions arising from characters on monoidal gradings. This framework extends the expressive power of monoidal categories to model irreversible, resource-sensitive, and direction-dependent processes --such as those in directed homotopy theory, categorical quantum mechanics, and non-symmetric operadic structures--while remaining amenable to mechanization and formal verification.
math.ct
math
math
11-25 00:00
arXiv:2511.17548v1 Announce Type: new Abstract: This paper is devoted to the analysis of a focusing nonlinear biharmonic Schr\"odinger equation in the presence of an unbounded growing up inhomogeneous term. The first main contribution of this work is the derivation of an inhomogeneous Gagliardo-Nirenberg inequality adapted to the unbounded weight, which provides the necessary control over the nonlinear term in terms of Sobolev norms. Building on this inequality, we then investigate the long-time behavior of solutions and establish a sharp dichotomy: solutions with initial data below the ground state energy either exist globally in time or experience finite-time blow-up. A distinctive feature of our results is that the analysis of the unbounded inhomogeneous term requires the imposition of radial symmetry on the initial data, which allows us to exploit certain Strauss type Sobolev estimates that would not hold in the general non-radial case. This work complements previous studies on biharmonic Schr\"odinger equations with singular inhomogeneities, highlighting both the challenges and the new phenomena that arise when the nonlinearity is weighted by a growing up unbounded function, which broke the space translation invariance of the standard homogeneous associated equation.
math.ap
math
math
11-25 00:00
arXiv:2511.17613v1 Announce Type: new Abstract: We are concerned with the Steiner chains consisting of four circles. More precisely, we deal with the invariants of chains introduced in the recent papers of J.Lagarias, C.Mallows, A.Wilks, R.Schwartz and S.Tabachnikov. We also establish certain algebraic relations between those invariants. To this end we use the invariance of certain moments of curvatures of poristic Steiner chains established by R.Schwartz and S.Tabachnikov, combined with the computation of these moments for the socalled symmetric Steiner 4-chains. We also present analogous results for Steiner 3-chains and give an application of our results to the feasibility problem for the radii of Steiner 4-chains. Keywords: Steiner chain, parent circles, Steiner porism, poristic Steiner chains, Descartes circle theorem, invariant moments of curvatures, algebraic relations between invariants
math.gm
math
math
11-25 00:00
arXiv:2511.17640v1 Announce Type: new Abstract: Type-2 fuzzy set (T2 FS) were introduced by Zadeh in 1965, and the membership degrees of T2 FSs are type-1 fuzzy sets (T1 FSs). Owing to the fuzziness of membership degrees, T2 FSs can better model the uncertainty of real life, and thus, type-2 rule-based fuzzy systems (T2 RFSs) become hot research topics in recent decades. In T2 RFS, the compositional rule of inference is based on triangular norms (t-norms) defined on complete lattice (L, \le ) ( L is the set of all convex normal functions from [0,1] to [0,1], and , \le is the so-called convolution order). Hence, the choice of t-norm on (L,\le) may influence the performance of T2 RFS. Therefore, it is significant to broad the set of t-norms among which domain experts can choose most suitable one. To construct t-norms on (L,\le), the mainstream method is convolution which is induced by two operators on the unit interval [0,1]. A key problem appears naturally, when convolution is a t-norm on (L,\le). This paper gives the necessary and sufficient conditions under which convolution is a t-norm on (L,\le). Moreover, note that the computational complexity of operators prevent the application of T2 RFSs. This paper also provides one kind of convolutions which are t-norms on (L,\le) and extremely easy to calculate.
math.gm
math
math
11-25 00:00
arXiv:2511.17642v1 Announce Type: new Abstract: This article examines the dynamic phase transitions and pattern formations attributed to binary systems modeled by the Cahn-Hilliard equation. In particular, we consider a two-dimensional lattice structure and determine how different choices of the spanning vectors influence the resulting dynamical tramsitions and pattern formations. As the basic steady-state loses its linear stability, the binary system undergoes a dynamic transition which is shown to be characterized by both the geometry of the domain and the choice of physical parameters of the model. Unlike rectangular domains, we are able to observe the emergence of hexagonally-packed circles, as well as the familiar rolls and square structures. We begin with the decomposition of our function space into a stable and unstable eigenspace before calculating the center manifold that maps the former to the later. In analyzing the resulting reduced equations, we consider the different multiplicities that the critical eigenvalue can have, which is shown to be geometry-dependent. We briefly consider the long-range interaction model and determine that it produces similar results to the original model.
math.ap
math
math
11-25 00:00
arXiv:2511.17653v1 Announce Type: new Abstract: Multi-Agent Reinforcement Learning (MARL) has emerged as a powerfulparadigm for cooperative decision-making in connected autonomous vehicles(CAVs); however, existing approaches often fail to guarantee stability, optimality,and interpretability in systems characterized by nonlinear dynamics,partial observability, and complex inter-agent coupling. This study addressesthese foundational challenges by introducing MARL-CC, a unified MathematicalFramework for Multi-Agent Reinforcement Learning with Control Coordination.The proposed framework integrates differential geometric control, Bayesian inference,and Shapley-value-based credit assignment within a coherent optimizationarchitecture, ensuring bounded policy updates, decentralized belief estimation,and equitable reward distribution. Theoretical analyses establish convergence andstability guarantees under stochastic disturbances and communication delays.Empirical evaluations across simulation and real-world testbeds demonstrate upto a 40% improvement in convergence rate and enhanced cooperative efficiencyover leading baselines, including PPO, DDPG, and QMIX.These results signify a decisive advance in control-oriented reinforcement learning,bridging the gap between mathematical rigor and practical autonomy.The MARL-CC framework provides a scalable foundation for intelligent transportation,UAV coordination, and distributed robotics, paving the way toward interpretable, safe, and adaptive multi-agent systems. All codes and experimentalconfigurations are publicly available on GitHub to support reproducibilityand future research.
math.gm
math
math
11-25 00:00
arXiv:2511.17679v1 Announce Type: new Abstract: Let $G$ be a connected graph, and let $b$ and $k$ be two positive integers with $b\equiv1$ (mod 2). A $[1,b]$-odd factor of $G$ is a spanning subgraph $F$ of $G$ with $d_F(v)\equiv1$ (mod 2) and $1\leq d_F(v)\leq b$ for every $v\in V(G)$. A graph $G$ is called $k$-critical with respect to $[1,b]$-odd factor if $G-X$ contains a $[1,b]$-odd factor for every $X\subseteq V(G)$ with $|X|=k$. Let $\mathcal{D}(G)$ denote the distance matrix of $G$. The largest eigenvalue of $\mathcal{D}(G)$, denoted by $\mu(G)$, is called the distance spectral radius of $G$. In this paper, we prove an upper bound for $\mu(G)$ in a connected graph $G$ which guarantees $G$ to be $k$-critical with respect to $[1,b]$-odd factor.
math.co
math
math
11-25 00:00
arXiv:2511.17686v1 Announce Type: new Abstract: Let $A$ be a dissipative operator on a Banach space with a dense domain. It is proved that $A$ has a quasi-dissipative extension (possibly in an enlarged Banach space) which generates a quasi-contractive $C_0$-semigroup. \par This gives a positive answer to the question posed by P.R.Chernoff and H.F.Trotter.
math.fa
math
math
11-25 00:00
arXiv:2511.17700v1 Announce Type: new Abstract: Given a closed immersion between arbitrary smooth complex projective varieties, we prove that the two operations: (1) taking the moduli space of stable sheaves, and (2) taking the deformation to the normal cone, commute in a precise sense. In the case of curves inside symplectic surfaces, previously studied by Donagi-Ein-Lazarsfeld, the corresponding deformation to the normal cone space is an open subset of the relative moduli space of sheaves. As an application, we show generalized Kummer varieties degenerate to natural symplectic subvarieties of the Hitchin system for curves of genus at least 2.
math.ag
math
math
11-25 00:00
arXiv:2511.17716v1 Announce Type: new Abstract: We consider the problem of representing the fraction $5/P$ as a sum of three distinct unit fractions $1/A+1/B+1/C$ with $A
math.nt
cs
cs
11-25 00:00
arXiv:2511.17516v1 Announce Type: new Abstract: On modern computers with graphical user interfaces, application windows are managed by a window manager, a core component of the desktop environment. Mainstream operating systems such as Microsoft Windows and Apple's macOS employ window managers, where users rely on a mouse or trackpad to manually resize, reposition, and switch between overlapping windows. This approach can become inefficient, particularly on smaller screens such as laptops, where frequent window adjustments disrupt workflow and increase task completion time. An alternative paradigm, dynamic window management, automatically arranges application windows into non-overlapping layouts. These systems reduce the need for manual manipulation by providing intelligent placement strategies and support for multiple workspaces. Despite their potential usability benefits, dynamic window managers remain niche, primarily available on Linux systems and rarely enabled by default. This study evaluates the usability of dynamic window managers in comparison to conventional floating window systems. We developed a prototype dynamic window manager that incorporates configurable layouts and workspace management, and we conducted both heuristic evaluation and statistical testing to assess its effectiveness. Our findings indicate that dynamic window managers significantly improve task completion time in multi-window workflows by 37.83%. By combining cognitive heuristics with empirical performance measures, this work highlights the potential of dynamic window management as a viable alternative to traditional floating window systems and contributes evidence-based insights to the broader field of human-computer interaction (HCI).
cs.hc
cs
cs
11-25 00:00
arXiv:2511.17517v1 Announce Type: new Abstract: Efficient energy provisioning is a fundamental requirement for modern transportation systems, making refueling path optimization a critical challenge. Existing solutions often focus either on inter-vehicle communication or intra-vehicle monitoring, leveraging Intelligent Transportation Systems, Digital Twins, and Software-Defined Internet of Vehicles with Cloud/Fog/Edge infrastructures. However, integrated frameworks that adapt dynamically to driver mobility patterns are still underdeveloped. Building on our previous PIENO framework, we present RI-PIENO (Revised and Improved Petrol-filling Itinerary Estimation aNd Optimization), a system that combines intra-vehicle sensor data with external geospatial and fuel price information, processed via IoT-enabled Cloud/Fog services. RI-PIENO models refueling as a dynamic, time-evolving directed acyclic graph that reflects both habitual daily trips and real-time vehicular inputs, transforming the system from a static recommendation tool into a continuously adaptive decision engine. We validate RI-PIENO in a daily-commute use case through realistic multi-driver, multi-week simulations, showing that it achieves significant cost savings and more efficient routing compared to previous approaches. The framework is designed to leverage emerging roadside infrastructure and V2X communication, supporting scalable deployment within next-generation IoT and vehicular networking ecosystems.
cs.ni
cs
cs
11-25 00:00
arXiv:2511.17518v1 Announce Type: new Abstract: The rapid adoption of serverless computing necessitates a deeper understanding of its underlying operational mechanics, particularly concerning request routing, cold starts, function scaling, and resource management. This paper presents Serv-Drishti, an interactive, open-source simulation tool designed to demystify these complex behaviours. Serv-Drishti simulates and visualises the journey of a request through a representative serverless platform, from the API Gateway and intelligent Request Dispatcher to dynamic Function Instances on resource-constrained Compute Nodes. Unlike simple simulators, Serv-Drishti provides a robust framework for comparative analysis. It features configurable platform parameters, multiple request routing and function placement strategies, and a comprehensive failure simulation module. This allows users to not only observe but also rigorously analyse system responses under various loads and fault conditions. The tool generates real-time performance graphs and provides detailed data exports, establishing it as a valuable resource for research, education, and the design analysis of serverless architectures.
cs.ni
cs
cs
11-25 00:00
arXiv:2511.17524v1 Announce Type: new Abstract: Mobile Edge Computing (MEC) is a promising approach for enhancing the quality-of-service (QoS) of AI-enabled applications in the B5G/6G era, by bringing computation capability closer to end-users at the network edge. In this work, we investigate the joint optimization of edge server (ES) deployment, service placement, and computation task offloading under the stochastic information scenario. Traditional approaches often treat these decisions as equal, disregarding the differences in information realization. However, in practice, the ES deployment decision must be made in advance and remain unchanged, prior to the complete realization of information, whereas the decisions regarding service placement and computation task offloading can be made and adjusted in real-time after information is fully realized. To address such temporal coupling between decisions and information realization, we introduce the stochastic programming (SP) framework, which involves a strategic-layer for deciding ES deployment based on (incomplete) stochastic information and a tactical-layer for deciding service placement and task offloading based on complete information realization. The problem is challenging due to the different timescales of two layers' decisions. To overcome this challenge, we propose a multi-timescale SP framework, which includes a large timescale (called period) for strategic-layer decision-making and a small timescale (called slot) for tactical-layer decision making. Moreover, we design a Lyapunov-based algorithm to solve the tactical-layer problem at each time slot, and a Markov approximation algorithm to solve the strategic-layer problem in every time period.
cs.ni
cs
cs
11-25 00:00
arXiv:2511.17525v1 Announce Type: new Abstract: The exponential growth of multimedia streaming services over the Internet emphasizes the increasing significance of ensuring a seamless and high-quality streaming experience for users. Dynamic Adaptive Streaming over HTTP (DASH) has emerged as a popular solution for delivering multimedia content over variable network conditions. However, challenges such as network congestion, intermittent packet losses, and varying network load continue to impact the Quality of Experience (QoE) perceived by the users. In this work, the main goal is to evaluate the effectiveness of using queue management and flow isolation techniques in terms of improving the overall QoE for DASH based multimedia streaming applications. Proportional Integral controller Enhanced (PIE) and Flow Queue PIE (FQ-PIE) are used as queue management and flow isolation mechanisms, respectively. The most distinctive aspect of this work is our assessment of QoE for multimedia streaming applications when multipath transport protocols, like Multipath TCP (MPTCP), are employed. Network Stack Tester (NeST), a Python based network emulator built on top of Linux network namespaces, has been used to perform the experiments. The parameters used for evaluating the QoE include bitrate, bitrate switches, throughput, Round Trip Time (RTT), and application buffer level. We observe that flow isolation techniques, combined with queue management and multipath transport, significantly improve the QoE for multimedia applications.
cs.ni
cs
cs
11-25 00:00
arXiv:2511.17527v1 Announce Type: new Abstract: This student paper introduces a novel methodology for the detection and analysis of multihop cross-chain arbitrage opportunities, wherein multihop denotes arbitrage sequences involving more than two transactional steps across distinct blockchain networks, executed using sequence-dependent strategies. Utilizing a comprehensive dataset comprising over 2.4 billion transactions recorded between September 2023 and August 2024 (encompassing 12 blockchain platforms and 45 cross-chain bridges) we design and implement an algorithm capable of identifying, sequence-dependent arbitrage paths spanning multiple ecosystems. Our empirical analysis demonstrates that such arbitrage opportunities are exceedingly infrequent, underscoring the inherent challenges associated with multihop execution in cross-chain environments.
cs.oh
cs
cs
11-25 00:00
arXiv:2511.17529v1 Announce Type: new Abstract: Accurate network-traffic forecasting enables proactive capacity planning and anomaly detection in Internet Service Provider (ISP) networks. Recent advances in time-series foundation models (TSFMs) have demonstrated strong zero-shot and few-shot generalization across diverse domains, yet their effectiveness for computer networking remains unexplored. This paper presents a systematic evaluation of a TSFM, IBM's Tiny Time Mixer (TTM), on the CESNET-TimeSeries24 dataset, a 40-week real-world ISP telemetry corpus. We assess TTM under zero-shot and few-shot settings across multiple forecasting horizons (hours to days), aggregation hierarchies (institutions, subnets, IPs), and temporal resolutions (10-minute and hourly). Results show that TTM achieves consistent accuracy (RMSE 0.026-0.057) and stable $R^2$ scores across horizons and context lengths, outperforming or matching fully trained deep learning baselines such as GRU and LSTM. Inference latency remains under 0.05s per 100 points on a single MacBook Pro using CPU-only computation, confirming deployability without dedicated GPU or MPS acceleration. These findings highlight the potential of pretrained TSFMs to enable scalable, efficient, and training-free forecasting for modern network monitoring and management systems.
cs.ni
q-bio
q-bio
11-25 00:00
arXiv:2511.17695v1 Announce Type: new Abstract: Motivation: Drug synergy is strongly influenced by cellular context. Variations in protein interaction landscapes and pathway activities across cell types can reshape how drugs act in combination. However, most existing models overlook this heterogeneity and rely on static or bulk level protein protein interaction networks that ignore cell specific molecular wiring. With the availability of single cell transcriptomic data, it is now possible to reconstruct cell line specific interactomes, offering a new foundation for contextualized drug synergy modeling. Results: We present SynCell, a contextualized drug synergy framework that integrates drug protein, protein protein, and protein cell line relations within a unified graph architecture. SynCell leverages single cell derived, cell line specific PPI networks to embed the molecular context in which drugs act, and employs graph convolutional learning to model how pharmacological effects propagate through cell specific signaling networks. This formulation treats synergy prediction as a cell line contextualized drug drug interaction problem. Across two large scale benchmarks (NCI ALMANAC and ONeil), SynCell consistently outperforms state of the art baselines including DeepDDS, HypergraphSynergy, and HERMES, especially in predicting synergies involving unseen drugs or novel cell lines. Ablation analyses show that contextualizing PPIs with single cell resolution yields substantial gains in generalization and biological interpretability.
q-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.18238v1 Announce Type: new Abstract: Alzheimer's disease (AD) emerges from a complex interplay of molecular, cellular, and network-level disturbances that are not easily captured by traditional reductionist frameworks. Conventional analyses of gene expression often rely on thresholded correlation networks or clustering-based module detection, approaches that may obscure nonlinear structure and higher-order organization. Here, we introduce a comparative topological framework that makes use of topological data analysis (TDA) and the Mapper algorithm to detect discontinuities - localized disruptions in the topology of gene co-expression space between healthy and AD brain tissue. Using gene expression data from 3 brain regions, we mapped how AD reshapes the global topology of gene-gene relationships. Discontinuity hotspots were identified via variability-based node scoring and subjected to Gene Ontology Biological Process enrichment analysis. This work illustrates the potential of TDA to uncover disease-relevant structure in high-dimensional transcriptomic data and motivates broader application of shape-based comparative methods in neurodegeneration research and other areas that benefit from comparative analysis.
q-bio.qm
q-bio
q-bio
11-25 00:00
arXiv:2511.18598v1 Announce Type: new Abstract: The urban habitat provides a landscape that increases the chances of human-animal interactions, which can lead to increased human-animal conflict, but also coexistence. Some species show high levels of socio-cognitive abilities that enable them to perceive communicational gestures of humans and use them for their own benefit. This study investigated the ability of Indian free-ranging dogs (Canis lupus familiaris) to utilise human social-referential cues (pointing and gazing) to locate hidden food, focusing on the relative effectiveness of unimodal versus multimodal cues. A total of 352 adult free-ranging dogs were tested in an object-choice task involving six different cue conditions: control (no cue), negative control (one baited bowl, no cue), combined pointing and gazing, pointing-only, gazing-only, and conflicting cues (pointing and gazing at opposite bowls). The dogs successfully chose the correct target only in the combined pointing and gazing condition, while performance under unimodal and conflicting cue conditions did not differ significantly from chance. This highlights the importance of signal redundancy and clarity in interspecific communication for this population. A dog's demeanor was a significant predictor of its willingness to engage: affiliative dogs were significantly more likely to succeed in the overall experiment and displayed a significantly shorter approach latency compared to anxious and neutral dogs. While demeanor affected the approach latency, it did not affect the accuracy of the choice, decoupling the dogs' personality from its cognitive ability to comprehend the clear cue. Neither the dogs' sex nor the experimental condition significantly predicted approach latency.
q-bio.ot
q-bio
q-bio
11-25 00:00
arXiv:2511.18853v1 Announce Type: new Abstract: Stroke is a leading cause of disability and death worldwide, with ischemic strokes accounting for nearly 80% of cases. Fewer than 5% of patients receive the sole validated pharmacotherapy, intravenous thrombolysis, highlighting the urgent need for novel therapies. Within this landscape, the exploration of natural molecules emerges as a promising avenue, particularly as a means to address limitations associated with conventional drugs. Nutraceuticals, bioactive compounds derived from food sources, offer a compelling prospect for health and wellness. The term nutraceutical reflects their dual potential in nutrition and pharmacotherapy, emphasizing their relevance to both disease prevention and treatment. Interestingly, many were initially recognized as ''natural preconditioners'', substances that prime the body for protection against stress or damage. In fact, numerous nutraceuticals have been shown to activate protective pathways similar to those triggered by preconditioning across various organs. Among nutraceuticals, omega-3 polyunsaturated fatty acids sourced from plants or fish, along with polyphenols, have emerged as particularly promising. Their consumption has been associated with a reduced risk of ischemic stroke, supported by numerous preclinical studies demonstrating their beneficial effects on cellular components within the neurovascular unit. This review explores the shared protective mechanisms of various nutraceuticals against key drivers of ischemic injury, including excitotoxicity, oxidative stress, apoptosis, and inflammation. By delineating these actions, the review highlights the potential of nutraceuticals as brain preconditioners that enhance neuroprotection, thereby mitigating the impact of cerebral ischemia in both preventive and therapeutic contexts.
q-bio.nc
q-bio
q-bio
11-25 00:00
arXiv:2511.18893v1 Announce Type: new Abstract: Neurodegenerative diseases are driven by the accumulation of protein aggregates in the brain of affected individuals. The aggregation behaviour in vitro is well understood and driven by the equilibration of a super-saturated protein solution to its aggregated equilibrium state. However, the situation is altered fundamentally in living systems where active processes consume energy to remove aggregates. It remains unclear how and why cells transition from a state with predominantly monomeric protein, which is stable over decades, to one dominated by aggregates. Here, we develop a simple but universal theoretical framework to describe cellular systems that include both aggregate formation and removal. Using a two-dimensional phase-plane representation, we show that the interplay of aggregate formation and removal generates cell-level bistability, with a bifurcation structure that explains both the emergence of disease and the effects of therapeutic interventions. We explore a wide range of aggregate formation and removal mechanisms and show that phenomena such as seeding arise robustly when a minimal set of requirements on the mechanism are satisfied. By connecting in vitro aggregation mechanisms to changes in cell state, our framework provides a general conceptual link between molecular-level therapeutic interventions and their impact on disease progression.
q-bio.bm
physics
physics
11-25 00:00
arXiv:2511.17549v1 Announce Type: new Abstract: This paper is a continuation of a series of works, devoted to various aspects of the 1908 Tunguska event. This usually refers to an explosive phenomenon associated with the appearance of a forestfall, named nowadays as the Kulikovskii one. However, several other notable natural phenomena occurred in the Central Siberia on June 30, 1908. This paper considers geomorphological features, reports of substance discoveries, forestfalls, and earthquakes. The general conclusion is that the Tunguska event was a very complex phenomenon. Research of the Tunguska event requires the participation of experts in various fields.
physics.pop-ph
physics
physics
11-25 00:00
arXiv:2511.17620v1 Announce Type: new Abstract: Blind and Visually Impaired (BVI) Individuals face significant challenges in science due to the discipline's reliance on visual elements such as graphs, diagrams, and laboratory work. Traditional learning materials, such as Braille and large-print textbooks, are often scarce or delayed, while practical experiments are rarely adapted for accessibility. Additionally, mainstream educators lack the training to effectively support BVI students, and Teachers for the Visually Impaired (TVIs) often lack scientific expertise. As a result, BVI individuals remain underrepresented in scientific jobs, reinforcing a cycle of exclusion. However, technological advancements and inclusive initiatives are opening new opportunities. Outreach programs aim to make science engaging and accessible for BVI individuals through multi-sensory learning experiences. Hands-on involvement in these activities fosters confidence and interest in scientific careers. Beyond sparking interest, equipping BVI students with the right tools and skills is crucial for their academic success. Early exposure to assistive technologies enables BVI students to navigate scientific studies independently. Artificial Intelligence (AI) tools further enhance accessibility by converting visual data into descriptive text and providing interactive assistance. Several learning sessions demonstrated the effectiveness of these interventions, with participants successfully integrating into university-level science programs. Educating BVI and their teachers on these tools and good pratices is the aim of our project AccesSciencesDV. Research careers offer promising opportunities for BVI, especially in computational fields. By leveraging coding, data analysis, and AI-driven tools, BVI researchers can conduct high-level scientific work without relying on direct visual observations. The presence of BVI scientists enriches research environments.
physics.ed-ph
physics
physics
11-25 00:00
arXiv:2511.17713v1 Announce Type: new Abstract: The ability to address sub-picosecond events of weak optical signals is essential for progress in quantum science, nonlinear optics, and ultrafast spectroscopy. While up-conversion and optical Kerr gating (OKG) offer femtosecond resolution, they are generally limited to ensemble measurements, making ultrafast detection in nano-optics challenging. OKG, with its broadband response and high throughput without phase-matching, is especially promising when used at high repetition rates under focused illumination. Here, we demonstrate an ultrafast detection scheme using the third-order nonlinearity of graphene and thin graphite films, operating at 1 GHz with sub-nanojoule pulses and achieving 141 fs temporal resolution. Their exceptionally large nonlinear refractive index, orders of magnitude higher than conventional Kerr media, enhances detection efficiency at smaller thicknesses, enables sub-picosecond response, and supports broadband operation. Their atomic-scale thickness minimizes dispersion and simplifies integration with microscopy platforms, optical fibers, and nanophotonic circuits, making them a compact, practical material platform for nano-optical and on-chip ultrafast Kerr gating.
physics.optics
physics
physics
11-25 00:00
arXiv:2511.17767v1 Announce Type: new Abstract: Evolutionary algorithms for molecular design require computationally efficient yet accurate fitness functions. We systematically benchmark Hartree-Fock and density functional theory for predicting molecular first hyperpolarizability ($\beta$), evaluating five functionals (HF, PBE0, B3LYP, CAM-B3LYP, M06-2X) across six basis sets against experimental data from five organic push-pull chromophores. For this dataset, HF/3-21G achieves 45.5% mean absolute percentage error with perfect pairwise ranking in 7.4 minutes per molecule. All 30 tested combinations of functional and basis sets maintain perfect pairwise agreement, validating their use as evolutionary fitness functions despite moderate absolute errors. Larger basis sets yield a lower percentage error compared to the experimental values than the difference with the functional. The preservation of pairwise rankings across all combinations of functionals and basis sets provides crucial guidance for evolutionary optimization of nonlinear optical materials.
physics.chem-ph
physics
physics
11-25 00:00
arXiv:2511.17768v1 Announce Type: new Abstract: Production and manipulation of orbital angular momentum (OAM) of coherent soft x-ray beams is demonstrated utilizing consecutive diffractive optics. OAM addition is observed upon passing the beam through consecutive fork gratings. The OAM of the beam was found to be decoupled from its spin angular momentum (SAM). Practical implementation of angular momentum control by consecutive devices in the x-ray regime opens new experimental opportunities, such as direct measurement of OAM beams without resorting to phase sensitive techniques, including holography. OAM analyzers utilizing fork gratings can be used to characterize the beams produced by synchrotron and free electron lasers sources; they can also be used in scattering experiments.
physics.optics
physics
physics
11-25 00:00
arXiv:2511.17771v1 Announce Type: new Abstract: The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and operational assessment of Drift Tube Linac performance, scintillator-based loss monitors were previously installed along the exterior of the first two accelerating cavities to assess low energy beam losses. Here we present a recent upgrade to the loss monitor system, including significant improvements in analog signal processing to address baseline-interfering noise; digitization of the signals to enable regular operational use and tuning; and a new remote operation upgrade of the translating loss monitor with precise positioning of the loss monitor along its nine-foot track. Data from the fixed and translating detectors collected under varying beam conditions validate the utility of the upgrade.
physics.acc-ph
physics
physics
11-25 00:00
arXiv:2511.17785v1 Announce Type: new Abstract: Circular Rydberg states offer advantages for quantum information and quantum simulation platforms due to their long lifetimes and strong dipole-dipole interactions. Unfortunately, current techniques for the production of these states remain technically challenging. Here we investigate the ability of twisted electron collisions to produce circular Rydberg states. Twisted electrons carry quantized orbital angular momentum that can be transferred to the electronic state of the atom, potentially providing an efficient means to generate circular Rydberg states. Using a fully quantum mechanical framework, we compute total excitation cross sections for circular Rydberg states of hydrogen, rubidium, and cesium targets using Bessel electron beams. Our models account for the full Bessel-beam structure of the incident electron and incorporate macroscopic target effects to model experimentally-relevant conditions. Our results show that twisted electrons with large opening angles produce significant enhancements in the excitation probability relative to plane-wave electrons, particularly for large opening angles and low energies. We trace this enhancement to contributions from projectiles with large values of orbital angular momentum. These findings demonstrate that twisted-electron excitation may provide a feasible and potentially advantageous pathway for generating circular Rydberg states.
physics.atom-ph
physics
physics
11-25 00:00
arXiv:2511.17810v1 Announce Type: new Abstract: This study address the computational determination of catalytic reaction rates by moving beyond traditional Transition State Theory (TST), addressing its limitations in complex systems. The Hill relation framework, integrated with Adaptive Multilevel Splitting (AMS), offers exact rate constants for stochastic dynamics, overcoming TST's assumptions and limitations such as recrossings and post-transition state bifurcations. Two case studies validate the approach: water formation on {\gamma}-alumina and protonated isobutanol dehydration in the gas phase, demonstrating consistency with DFT results and highlighting the importance of dynamical effects. This framework provides a robust, computationally feasible methodology for studying complex catalytic processes.
physics.chem-ph
physics
physics
11-25 00:00
arXiv:2511.17837v1 Announce Type: new Abstract: Negative information often exerts a disproportionately strong impact on human decision-making, a phenomenon known as the negativity bias. In behavioral economics, this effect is formally captured by Prospect Theory, which posits that losses loom larger than equivalent gains. For example, a single negative product review can outweigh numerous positive ones, reflecting this principle of loss aversion in consumer behavior. While this psychological effect has been widely documented, its implications for collective opinion dynamics, critical for understanding market stability and reputation dynamics, remain poorly understood. Here, we generalize the $q$-voter model with independence by introducing opinion-dependent influence group sizes, $q_+$ and $q_-$, which represent the social reinforcement needed to change an opinion from negative to positive and from positive to negative, respectively. We study two versions of this asymmetric model: a baseline model that reduces to the standard $q$-voter model when $q_+ = q_- = q$, and an extended model that incorporates an additional asymmetry expressed as a preference for one opinion. In its reduced version, this represents a minimal model in terms of non-linearity within the $q$-voter framework that allows for discontinuous phase transitions and hysteresis. Using mean-field analysis and computer simulations, we show that these modifications lead to rich collective behaviors, including double hysteresis, one form of which is irreversible, providing a mechanism for path-dependence and the sustained, irrecoverable damage to collective sentiment, brand equity, or market confidence.
physics.soc-ph
physics
physics
11-25 00:00
arXiv:2511.17845v1 Announce Type: new Abstract: Extreme gust encounters by finite wings with disturbance velocity exceeding their cruise speed remain largely unexplored, while particularly relevant to miniature-scale aircraft. This study considers extreme aerodynamic flows around a square wing and the large, unsteady forces that result from gust encounters. We analyse the evolution of three-dimensional, large-scale vortical structures and their complex interactions with the wing by performing direct numerical simulations at a chord-based Reynolds number of 600. We find that a strong incoming positive gust vortex induces a prominent leading-edge vortex (LEV) on the upper surface of the wing, accompanied by tip vortices (TiVs) strengthened through the interaction. Conversely, a strong negative gust vortex induces an LEV on the lower surface of the wing and causes a reversal in TiV orientation. In both extreme vortex gust encounters, the wing experiences significant lift fluctuations. Furthermore, we identify two opposing effects of the TiVs on the large lift fluctuations. First, the enhanced or reversed TiVs contribute to significant lift surges or drops by generating large low-pressure cores near the wing. Second, the TiVs play a part in attenuating lift fluctuations through enhanced downwash or upwash, formation of an arch vortex, and distortion of vortical structure around the wing corners. The second effect outweighs the first, resulting in smaller transient lift changes on the finite wing compared to the 2D wing. We also show that flying above a positive gust vortex or flying below a negative one can mitigate lift fluctuations during encounters. The current findings provide potential guidance on how TiV dynamics and wing positions could be leveraged to alleviate large transient lift fluctuations experienced by finite wings in severe gust conditions.
physics.flu-dyn
physics
physics
11-25 00:00
arXiv:2511.17880v1 Announce Type: new Abstract: Optical kernel machines offer high throughput and low latency. A nonlinear optical kernel can handle complex nonlinear data, but power consumption is typically high with the conventional nonlinear optical approach. To overcome this issue, we present an optical kernel with structural nonlinearity that can be continuously tuned at low power. It is implemented in a linear optical scattering cavity with a reconfigurable micro-mirror array. By tuning the degree of nonlinearity with multiple scattering, we vary the kernel sensitivity and information capacity. We further optimize the kernel nonlinearity to best approximate the parity functions from first order to fifth order for binary inputs. Our scheme offers potential applicability across photonic platforms, providing programmable kernels with high performance and low power consumption.
physics.optics
physics
physics
11-25 00:00
arXiv:2511.17949v1 Announce Type: new Abstract: Growing energy demands of modern digital devices necessitate alternative, low-power computing mechanisms. When incident loads take the form of acoustic or vibrational waves, the ability to mechanically process information eliminates the need for transduction, paving the way for passive computing. Recent studies have proposed systems that learn and execute mechanical logic through buckling, bistability, and origami-inspired lattices. However, owing to the large timescales of shape morphing, such concepts suffer from slow operation or require active stimulation of adaptive materials. To address these limitations, we present a novel approach to mechanical logic, leveraging the rich dynamics of wave propagation in elastic structures. In lieu of traditional forward-design tools, such as band diagrams and transmission spectra, we employ a multi-faceted topology optimization approach, enabling us to identify candidate waveguide configurations within an extremely large design space. By incorporating voids within an otherwise uniform substrate, the optimized waveguides are able to precisely manipulate wave propagation paths, triggering desirable interferences of the scattered wavefield that culminate in energy localization at readouts corresponding to a given logic function. An experimental setup is used to demonstrate the efficacy of such logic gates and their resilience to non-uniform loading. By implementing these building blocks into a mechanical adder, we demonstrate the scalable deployment of more sophisticated mechanical computing circuits, opening up new avenues in mechanical signal processing and physical computing.
physics.app-ph
econ
econ
11-25 00:00
arXiv:2511.17981v1 Announce Type: new Abstract: We identify a distinct motive for search, termed catalytic exploration, where agents rationally explore alternatives they expect to reject to resolve uncertainty about the status quo. By decomposing option value into switching and catalytic components, we show that high exploration rates can coexist with bounded switching probabilities. This mechanism generates three insights. First, strong catalytic motives cause separating equilibria to collapse in signaling games as receivers explore indiscriminately. Second, agents optimally acquire more precise information about the status quo than about alternatives, reversing rational inattention intuitions. Third, catalytic exploration creates negative externalities: information technology improvements can paradoxically reduce welfare by encouraging excessive benchmarking.
econ.th
econ
econ
11-25 00:00
arXiv:2511.18476v1 Announce Type: new Abstract: This paper studies choice situations in which a decision maker can choose multiple alternatives. Given a menu of available options, the decision maker selects a subset of the menu with certain probabilities. We employ an axiomatic approach to characterize various parametric models in the literature. Our results elucidate the implications of the functional form assumptions and shed light on the distinctions between models. The behavioral postulates offer simple tools for testing and falsifying the choice procedures used by the decision maker and reveal a close connection between models that are seemingly unrelated.
econ.th
econ
econ
11-25 00:00
arXiv:2511.18662v1 Announce Type: new Abstract: We introduce a model of persuasion in which a sender without any commitment power privately gathers information about an unknown state of the world and then chooses what to verifiably disclose to a receiver. The receiver does not know how many experiments the sender is able to run, and may therefore be uncertain as to whether the sender disclosed all of her information. Despite this challenge, we show that, under general conditions, the sender is able to achieve the same payoff as in the full-commitment Bayesian persuasion case.
econ.th
econ
econ
11-25 00:00
arXiv:2511.19017v1 Announce Type: new Abstract: We set out to solve a dual puzzle regarding reproductive strategies: The "Ancient vs. Modern" Puzzle (why pre-modern elites adopted a "Survival" strategy while modern elites adopt an "Anxiety" strategy) and the "Class Divide" Puzzle (why modern involution manifests as a U-shaped fertility pattern). We develop a unified computational framework (DP + Monte Carlo) that introduces Cognitive Heterogeneity across classes. Our Hybrid Model (M-H) posits that the poor act as "Rational Survivors" (M1 utility, Reality parameters), while the middle/rich act as "Biased Strivers" (M4b utility, Belief parameters). Our simulations yield three core findings. First, we confirm that the "Survival" strategy is objectively rational whenever risk exceeds a low threshold ($\sigma > 0.45$). Given that real-world risk is massive ($\sigma_{Real} \approx 4.9$), the modern "Quality" strategy is objectively fragile. Second, the trap for the Middle/Rich ($B \ge 200$) is driven by a "Two-Stage Belief Error": they are first "baited" by a Causal Error (underestimating risk) to enter the status game, and then "trapped" by a Marginal Error (underestimating returns) which triggers a stop in fertility. Third, the U-shape is driven by the cognitive divide. The Poor escape the trap by retaining a "Rational Survival" strategy in the face of real high risk. Conversely, the Aspirational Middle Class ($HC \approx 12, B \ge 200$) is uniquely trapped by their Biased Beliefs. Their high competence raises their dynastic reference point ($R$) to a level where, under perceived low returns, restricting fertility to $N=1$ becomes the only rational choice within their biased belief system.
econ.th
econ
econ
11-25 00:00
arXiv:2511.19372v1 Announce Type: new Abstract: This paper proposes an identification inspired from the SVAR-IV literature that uses external instruments to identify PVARs, and discusses associated issues of identification, estimation, and inference. I introduce a form of local average treatment effect - the $\mu$-LATE - which arises when a continuous instrument targets a binary treatment. Under standard assumptions of independence, exclusion, and monotonicity, I show that externally instrumented PVARs estimate the $\mu$-LATE. Monte Carlo simulations illustrate that confidence sets based on the Anderson-Rubin statistics deliver reliable convergence for impulse responses. As an application, I instrument state-level military spending with the state's share of national spending to estimate the dynamic fiscal multiplier. I find multipliers above unity, with effects concentrated in the contemporaneous year and persisting into the following year.
econ.em
econ
econ
11-25 00:00
arXiv:2306.04494v3 Announce Type: replace Abstract: Quantifying the impact of regulatory policies on social welfare generally requires the identification of counterfactual distributions. Many of these policies (e.g. minimum wages or minimum working time) generate mass points and/or discontinuities in the outcome distribution. Existing approaches in the difference-in-difference literature cannot accommodate these discontinuities while accounting for selection on unobservables and non-stationary outcome distributions. We provide a unifying partial identification result that can account for these features. Our main identifying assumption is the stability of the dependence (copula) between the distribution of the untreated potential outcome and group membership (treatment assignment) across time. Exploiting this copula stability assumption allows us to provide an identification result that is invariant to monotonic transformations. We provide sharp bounds on the counterfactual distribution of the treatment group suitable for any outcome, whether discrete, continuous, or mixed. Our bounds collapse to the point-identification result in Athey and Imbens (2006) for continuous outcomes with strictly increasing distribution functions. We illustrate our approach and the informativeness of our bounds by analyzing the impact of an increase in the legal minimum wage using data from a recent minimum wage study (Cengiz et al 2019).
econ.em
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17701v1 Announce Type: new Abstract: Black hole environments often host plasmas that are fully collisionless or contain intrinsically collisionless regions, including relativistic jets and coronae where particle energization is ubiquitous. Capturing the physics of these systems requires numerical methods capable of modeling relativistic, magnetized, collisionless plasmas in strong gravitational fields. In this work, we introduce the general-relativistic module for the Entity -- the first open-source, coordinate-agnostic performance-portable particle-in-cell code. The code enables fast axisymmetric simulations of collisionless plasmas around black holes on any modern high-performance computing architecture (both GPUs and CPUs).
astro-ph.he
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17702v1 Announce Type: new Abstract: Helium reionization is the most recent phase change of the intergalactic medium, yet its timing and main drivers remain uncertain. Among the probes to trace its unfolding, the 3.46 cm hyperfine line of singly-ionized helium opens the study of helium reionization to upcoming radio surveys. We aim to evaluate the detectability of the 3.46,cm signal with radio surveys and the possible constraints it can place on helium reionization, in particular whether it can distinguish between early and late helium reionization scenarios. Moreover, we perform a comprehensive study of the advantages of single-dish vs. interferometric setup. Using hydrodynamical simulations post-processed with radiative transfer, we construct mock data cubes for two models of helium reionization. We compute the power spectrum of the signal and forecast the signal-to-noise ratio for SKA-1 MID, DSA-2000, and a PUMA-like survey, in both observational setups. The two scenarios produce distinct power spectra, but the faintness of the signal, largely caused by weak coupling between the spin temperature and the kinetic temperature in low-density regions of the IGM, combined with high instrumental noise, makes detection very difficult within realistic integration times for current surveys. A PUMA-like survey operating in single-dish mode could, however, detect the 3.46 cm signal with an integrated signal-to-noise ratio of a few in < 1000 h in both scenarios. Distinguishing helium reionization scenarios with 3.46 cm line-intensity mapping therefore remains challenging for current facilities. Our results, however, indicate that next-generation, high-sensitivity surveys with optimized observing strategies, especially when combined with complementary probes of the IGM, could begin to place meaningful constraints on the timing and morphology of helium reionization.
astro-ph.co
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17709v1 Announce Type: new Abstract: It is relatively rare for gas giant planets to have resonant or near-resonant companions, but these systems are particularly useful for constraining planet formation and migration models. In this study, we examine Kepler-1624b, a sub-Saturn orbiting an M dwarf that was previously found to exhibit transit timing variations with an amplitude of approximately 2 minutes, suggesting the presence of a nearby non-transiting companion. We reanalyze the transits from archival Kepler data and extend the TTV baseline by 11 years by combining TESS data with three new ground-based transit observations from Palomar and Las Cumbres Observatories. We jointly fit these datasets and find that the TTV amplitude is significantly weaker in our updated analysis. We calculate the Bayes factor for a one-planet versus two-planet model and find that the one-planet model is preferred. Our results highlight the need for careful analysis of systems with relatively low amplitude TTV signals that are identified in large automated catalogs.
astro-ph.ep
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17732v1 Announce Type: new Abstract: Strong gravitational lensing is a powerful probe for studying the fundamental properties of dark matter on sub-galactic scales. Detailed analyses of galaxy-scale lenses have revealed localized gravitational perturbations beyond the smooth mass distribution of the main lens galaxy, largely attributed to dark matter subhalos and intervening line-of-sight halos. Recent studies suggest that, in contrast to subhalos, line-of-sight halos imprint distinct anisotropic features on the two-point correlation function of the effective lensing deflection field. These anisotropies are particularly sensitive to the collisional nature of dark matter, offering a potential means to test alternatives to the cold dark matter paradigm. In this study, we explore whether a neural density estimator can directly identify such anisotropic signatures from galaxy-galaxy strong lens images. We model the multipoles of the two-point function using a power-law parameterization and train a neural density estimator to predict the corresponding posterior distribution of lensing parameters, alongside parameter distributions for dark matter substructure. Our results show that recovering the dark matter substructure mass functions and mass-concentration parameters remains challenging, owing to difficulties in generating uniform training data set while using physically motivated priors. We also unveil an important degeneracy between the line-of-sight halo mass-function amplitude and the subhalo mass-function normalization. Furthermore, the network exhibits limited accuracy in predicting the two-point function multipole parameters, suggesting that both the training data and the adopted power-law fitting function may inadequately represent the true underlying structure of the anisotropic signal.
astro-ph.co
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17738v1 Announce Type: new Abstract: Low surface brightness galaxies (LSBs) are an important class of galaxies that allow us to broaden our understanding of galaxy formation and test various cosmological models. We present a survey of low surface brightness galaxies at $0.4 < z_{\rm phot} < 0.8$ in the GOODS-S field using JADES data. We model LSB surface brightness profiles, identifying those with $\bar{\mu}_{\rm eff} > 24$ mag arcsec$^{-2}$ in the F200W JWST/NIRCam filter. We study the spatial distribution, number density, S\'{e}rsic profile parameters, and rest-frame colours of these LSBs. We compare the photometrically-derived star formation histories, mass-weighted ages, and dust attenuations of these galaxies with a high surface brightness (HSB) sample at similar redshift and a lower redshift ($z_{\rm phot} < 0.4$) LSB sample, all of which have stellar masses $\lesssim 10^8 M_{\odot}$. We find that both the high and the low redshift LSB samples have low star formation (SFR$_{100} \lesssim 0.01$ $M_{\odot}$ yr$^{-1}$) compared with the HSB sample (SFR$_{100} \gtrsim 0.01$ $M_{\odot}$ yr$^{-1}$). The star formation histories show that the LSBs and HSBs possibly come from the same progenitors at $z \gtrsim 2$, though the histories are not well constrained for the LSB samples. The LSBs appear to have minimal dust, with most of our LSB samples showing $A_V < 1$ mag. JWST has pushed our understanding of LSBs beyond the local Universe.
astro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17800v1 Announce Type: new Abstract: We present X-ray observations of the periodic optical source ZTF J185139.81+171430.3 (hereafter ZTF J1851) by the XMM, NICER and NuSTAR telescopes. The source was initially speculated to be a white dwarf (WD) pulsar system due to its short period ($P\sim12$ min) and highly-modulated optical lightcurves. Our observations revealed a variable X-ray counterpart extending up to 40 keV with an X-ray luminosity of $L_X \sim 3\times10^{33}$ erg s$^{-1}$ (0.3--40 keV). Utilizing timing data from XMM and NICER, we detected a periodic signal at $P_{\rm spin}=12.2640(7)\pm0.0583$ min with $>6\sigma$ significance. The pulsed profile displays $\sim 25\%$ and $\sim10\%$ modulation in the 0.3--2 and 2--10 keV bands, respectively. Broadband X-ray spectra are best characterized by an absorbed optically-thin thermal plasma model with $kT \approx 25$ keV and a Fe K-$\alpha$ fluorescent line at 6.4 keV. The bright and hard X-ray emission rules out the possibility of a WD pulsar or ultra-compact X-ray binary. The high plasma temperature and Fe emission lines suggest that ZTF J1851 is an intermediate polar spinning at 12.264 min. We employed an X-ray spectral model composed of the accretion column emission and X-ray reflection to fit the broadband X-ray spectra. Assuming spin equilibrium between the WD and the inner accretion disk, we derived a WD mass range of $M_{\rm WD}=(1.07\rm{-}1.32)M_{\odot}$ exceeding the mean WD mass of IPs ($\langle M_{\rm WD} \rangle = 0.8 M_\odot)$. Our findings illustrate that follow-up broadband X-ray observations could provide unique diagnostics to elucidate the nature of periodic optical sources anticipated to be detected in the upcoming Rubin all-sky optical surveys.
astro-ph.he
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17814v1 Announce Type: new Abstract: Following the detection of a radio-loud Active Galactic Nucleus (AGN) in the z=4.3 protocluster SPT2349-56, we have obtained additional observations with MeerKAT in S-band (2.4 GHz) with the aim of further characterizing radio emission from amongst the ~30 submillimeter (submm) galaxies (SMGs) identified in the structure. We newly identify three of the protocluster SMGs individually at 2.4GHz as having a radio-excess, two of which are now known to be X-ray luminous AGN. Two additional members are also detected with radio emission consistent with their star formation rate (SFR). Archival MeerKAT UHF (816 MHz) observations further constrain luminosities and radio spectral indices of these five galaxies. The Australia Telescope Compact Array (ATCA) is used to detect and resolve the central two sources at 5.5 and 9.0 GHz finding elongated, jet-like morphologies. The excess radio luminosities range from L1.4,rest = (1-20)x10^25 W/Hz, ~10-100x higher than expected from the SFRs, assuming the usual far-infrared-radio correlation. Of the known cluster members, only the SMG `N1' shows signs of AGN in any other diagnostics, namely a large and compact excess in CO(11-10) line emission. We compare these results to field samples of radio sources and SMGs. The overdensity of radio-loud AGN in the compact core region of the cluster may be providing significant heating to the recently discovered nascent intra-cluster medium (ICM) in SPT2349-56.
astro-ph.ga
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17819v1 Announce Type: new Abstract: TIC 322208686 is known to be a detached binary that exhibits two types of variability: pulsation and eclipse. We present the physical properties of the target star using the short-cadence TESS data from sectors 24, 57, and 58, and our echelle spectra that show the presence of a tertiary companion. The spectral analysis led to the triple-lined radial velocities and the atmospheric parameters of the eclipsing components. Joint modeling of these observations reveals that the eclipsing pair contains two F-type stars with masses $1.564\pm0.012$ $M_\odot$ and $1.483\pm0.012$ $M_\odot$, radii $1.588\pm0.011$ $R_\odot$ and $1.500\pm0.012$ $R_\odot$, effective temperatures $7028\pm100$ K and $7020\pm110$ K, and luminosities $5.51\pm0.32$ $L_\odot$ and $4.90\pm0.32$ $L_\odot$. The light contributions of the three stars obtained from this modeling match well with those calculated from the observed spectra. The binary star parameters are in satisfactory agreement with evolutionary model predictions for age $t$ = 0.4 Gyr and metallicity $Z$ = 0.03. We extracted 11 significant frequencies from the TESS light residuals with the binary effects removed. Of these, five signals between 0.65 day$^{-1}$ and 1.89 day$^{-1}$ can be considered as $\gamma$ Dor pulsations originating mainly from the primary component, while the other frequencies are likely instrumental artifacts or combination terms. These results suggest that TIC 322208686 is a hierarchical triple, containing a pulsating eclipsing pair and a tertiary companion.
astro-ph.sr
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17832v1 Announce Type: new Abstract: It is usually assumed that mutual synchronisation of a tidal two-body system happens through tidal recession, assuming the reduced Hill sphere is not reached. However, synchronisation can be achieved also via tidal approach, provided the Roche limit is not crossed. For each of the two scenarios, hereafter referred to as Scenario 1 and Scenario 2, respectively, we derive the condition under which the evolving synchronicity radius catches up with the tidally evolving orbit. We consider these two scenarios for the Pluto-Charon system, examine the impact origin hypothesis of Charon's formation, and propose that capture is a likelier option. We investigate Scenario 2, both analytically and numerically, where the orbital evolution of Charon starts at a higher altitude than present and undergoes tidal descent. In Scenario 2, the greater initial orbital separation between the partners reduces tidally induced thermal processes and fracturing, as compared to Scenario 1. In several study cases, we also observe temporary locking of Charon into higher spin-orbit resonances (3:2 to 7:2) in the first 0.5Myr of the system's evolution.
astro-ph.ep
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17858v1 Announce Type: new Abstract: We forecast the detectability of the Doppler magnification dipole with a joint analysis of galaxy spectroscopic redshifts and size measurements. The Doppler magnification arises from an apparent size variation caused by galaxies' peculiar velocities when mapping them from redshift space to real space. This phenomenon is the dominant contribution to the convergence at low redshifts ($\lesssim$ 0.5). A practical observational strategy is to cross-correlate a galaxy number count tracer, e.g. from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey, with the convergence field reconstructed from galaxy size measurements obtained by the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). To assess the achievable precision of galaxy size measurements, we simulate LSST Y1-quality galaxy images with Galsim and measure them with the Galight profile fitting package. Our investigations, based on galaxy populations from LSST's synthetic galaxy catalogue cosmoDC2, show that the variance due to intrinsic galaxy size variation dominates over size measurement errors as expected, but may be lower than previous studies have suggested. Under our analysis assumptions, the Doppler magnification dipole would be detectable with a signal-to-noise ratio $\geq 10$ in multiple redshift bins between $0.1 \leq z \leq 0.5$ with DESI spectroscopic redshifts and LSST imaging.
astro-ph.co
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17900v1 Announce Type: new Abstract: PSR J2039-5617 is a redback millisecond pulsar binary system consisting of a compact star with a mass of 1.1-1.6 $M_\odot$ and a low-mass companion of 0.15-0.22 $M_\odot$. For this binary, we performed a timing analysis using 16 years of data from the Fermi Large Area Telescope, covering the period from 2008 August to 2024 October. Our analysis detected an orbital modulation with a period of 0.2279781 days at a significance level of $\sim4\sigma$, which is in good agreement with previous findings. However, unlike previous reports, we identified a transition in the orbital modulation around 2021 August, after which the orbital signal disappeared. We speculate that the system may be undergoing a transition from a rotation-powered to an accretion-powered state at this epoch. Additionally, we conducted the phase-resolved and spectral analyses, and in the phase-resolved results, we observed an anti-correlation between its $\gamma$-ray and X-ray emissions, which consistent with the predictions of high-energy radiation models for such systems. We provide some predictive discussions based on the results of $\gamma$-ray data analysis, and future Fermi-LAT observations will determine whether these predictions hold true.
astro-ph.he
astro-ph
astro-ph
11-25 00:00
arXiv:2511.17998v1 Announce Type: new Abstract: We report a constraint on the cosmological variation of the proton g-factor, $g_p$. By comparing the measured redshifts between \mbox{H\,{\sc i}} 21 cm and OH 18 cm lines observed with the newly commissioned Five-hundred-meter Aperture Spherical radio Telescope (FAST) toward PKS 1413+135 at $z$ = 0.24671, we obtain $\Delta g_{p}/g_{p} = (-4.3\pm2.5)\times10^{-5}$, which is more than two orders of magnitude more sensitive than previous constraints. In addition, we obtain sensitive constraints of $\Delta (\mu\alpha^{2})/(\mu\alpha^{2}) = (2.0\pm1.2)\times10^{-5}$ and $\Delta (\mu\alpha^{2}g_{p}^{0.64})/(\mu\alpha^{2}g_{p}^{0.64}) = (-4.7\pm1.9)\times10^{-6}$.
astro-ph.co
astro-ph
astro-ph
11-25 00:00
arXiv:2511.18008v1 Announce Type: new Abstract: AM CVn binaries are the most compact of accreting binaries having orbital periods in the range ~5-70 min. They consist of a white dwarf accreting hydrogen deficient material from a degenerate or semi-degenerate star and are predicted to be amongst the verification sources for future gravitational wave observatories such as LISA. Using the recent catalogue of Green et al (2025) I focus attention on the orbital period range in which outbursts are seen from AM CVn's. I examine in more detail the outburst properties of KL Dra which has an outburst every few months and has many sectors of TESS data as an open resource. Using observational data on the outbursting systems in general, I compare the outburst recurrence time, duration and amplitude as a function of orbital period with the predictions of the disc instability model. The recurrence time is well described, although there is some evidence that the amount of material in the disc at the end of the quiescence phase is less than earlier model assumptions. The distribution of the outburst duration appears to be dependent on the cadence of the observations and how it is defined. Similarly the amplitude distribution is dependent on cadence and the filter, which causes an apparent spread in distribution. Both of these features need to be systematically studied using consistent benchmarks. AM CVn binaries remain an excellent sources to test models which aim to predict the properties of disc accreting systems.
astro-ph.sr
astro-ph
astro-ph
11-25 00:00
arXiv:2511.18029v1 Announce Type: new Abstract: The Galactic Center (GC) is an extreme region of the Milky Way that is host to a complex set of thermal and non-thermal structures. In particular, the GC contains high-density gas and dust that is collectively referred to as the Central Molecular Zone (CMZ). In this work, we study a subset of HNCO filaments identified in band 3 ALMA observations of the GC obtained by the ALMA CMZ Exploration Survey (ACES) that are comparable to high density filaments identified in the Galactic Disk. We compare the orientation of the magnetic field derived from 214 um SOFIA and 850 um JCMT observations with the filament orientation to determine which mechanisms dominate the formation of these filaments. We observe a large range of magnetic orientations in our observed filaments indicating the complex environments the filaments are located in. We also compare the observational results to synthetic data sets created using an MHD model of the GC. Our analysis reveals that the dominant mechanisms local to the HNCO filaments vary throughout the GC with some filaments being dominated by supersonic turbulence and others by subsonic turbulence. The comparison to synthetic observations indicates that the observed filaments are in magnetically dominated environments that could be supporting these filaments against collapse. Our results on the CMZ filaments are also compared to results obtained on similar filaments located in the Galactic Disk, and we find that the filaments studied here are possible CMZ analogs to the dense filamentary "bones" observed previously in the Galactic Disk.
astro-ph.ga