Tootfinder

Path-dependent, ESG-valued, option pricing in the Bachelier-Black-Scholes-Merton model
Bhathiya Divelgama, Nancy Asare Nyarko, W. Brent Lindquist, Svetlozar T. Rachev, Blessing Omotade
https://arxiv.org/abs/2509.18099

Magnetic penetration depth in topological superconductors: Effect of Majorana surface states and application for UTe$_2$
Kazuki Akuzawa, Jushin Tei, Ryoi Ohashi, Satoshi Fujimoto, Takeshi Mizushima
https://arxiv.org/abs/2509.18441

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
Jie Hao, Rui Yu, Wei Zhang, Huixia Wang, Jie Xu, Mingrui Liu
https://arxiv.org/abs/2510.06048

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
Effective data selection is essential for pretraining large language models (LLMs), enhancing efficiency and improving generalization to downstream tasks. However, existing approaches often require leveraging external pretrained models, making it difficult to disentangle the effects of data selection from those of the external pretrained models. In addition, they often overlook the long-term impact of selected data if the model is trained to convergence, primarily due to the prohibitive cost of…

Understanding the Influence of Rheological Properties of Shear-Thinning Liquids on Segmented Flow in Microchannel using CLSVOF Based CFD Model
Somasekhara Goud Sontti, Pankaj G. Pallewar, Amritendu Bhuson Ghosh, Arnab Atta
https://arxiv.org/abs/2510.08651

Understanding the Influence of Rheological Properties of Shear-Thinning Liquids on Segmented Flow in Microchannel using CLSVOF Based CFD Model
In this study, two phase gas-shear-thinning liquid flow in a square microchannel is numerically investigated using the coupled level set and volume of fluid (CLSVOF) methods. A systematic investigation is carried out to explore the influence of polyacrylamide (PAM) concentration, surface tension, velocity ratios, and contact angle on the gas slug length, volume, unit cell length, and pressure drop. Three different concentrations of PAM solutions, which exhibit shear-thinning behaviour are consi…

Combining Blotto Networks and Voter Models to Simulate Voter Behavior in Response to Competitive Election Spending
Renee Jerome
https://arxiv.org/abs/2510.09697 https://

Combining Blotto Networks and Voter Models to Simulate Voter Behavior in Response to Competitive Election Spending
In the past, the Voter Model has been explicitly used to model the impact of propaganda on a dynamic, interconnected population, and certain factors have been identified that influence the behavior of voters when under outside influence. The Blotto Game has also been explicitly used to study information wars between two opposing parties, whether in regards to a political issue or advertising war. Both the graph theory behind the Voter Model and the game theory aspects of the Blotto Game are rel…

Rotation of Polarization Angle in Gamma-Ray Burst Prompt Phase. III. The Influence of the Magnetic Field Orientation
Xing-Yao Wang, Jia-Sheng Li, Mi-Xiang Lan
https://arxiv.org/abs/2510.11971

Rotation of Polarization Angle in Gamma-Ray Burst Prompt Phase. III. The Influence of the Magnetic Field Orientation
Polarization is very sensitive to the configuration of the magnetic field in the radiation region. In addition to polarization curve and polarization spectrum, studies of polarization angle (PA) rotation spectrum is also crucial. In this paper, we use a simple parametric magnetic reconnection model with a large-scale aligned magnetic field in the radiation region to study the effects of field orientation on the PA rotations. Under different field orientations, variations of the PA rotation with…

Non-exotic wormholes in $f(R,L_m)$ gravity
Sara Rastgoo, Foad Parsaei
https://arxiv.org/abs/2510.11487 https://arxiv.org/pdf/2510.11487

Non-exotic wormholes in $f(R,L_m)$ gravity
In the present analysis, we examine the potential existence of generalized wormhole models within the framework of newly developed extended $f(R,L_m)$ gravity. We investigate both a linear model, $f(R,L_m)=αR+βL_m$, and a non-linear model, $f(R,L_m)=\frac{R}{2}+ L^α_m$, to analyze traversable wormholes. By employing the variational approach, we derive modified versions of the field equations under the influence of an anisotropic matter source. A power-law shape function is applied, resulting…

Adversarial Social Influence: Modeling Persuasion in Contested Social Networks
Renukanandan Tumu, Cristian Ioan Vasile, Victor Preciado, Rahul Mangharam
https://arxiv.org/abs/2510.01481

Adversarial Social Influence: Modeling Persuasion in Contested Social Networks
We present the Social Influence Game (SIG), a framework for modeling adversarial persuasion in social networks with an arbitrary number of competing players. Our goal is to provide a tractable and interpretable model of contested influence that scales to large systems while capturing the structural leverage points of networks. Each player allocates influence from a fixed budget to steer opinions that evolve under DeGroot dynamics, and we prove that the resulting optimization problem is a differ…

Nonuniform water distribution in Jupiter’s midlatitudes - influence of precipitation and planetary rotation: #Jupiter

Efficient Differentiable Contact Model with Long-range Influence
Xiaohan Ye, Kui Wu, Zherong Pan, Taku Komura
https://arxiv.org/abs/2509.20917 https://arxi…

Efficient Differentiable Contact Model with Long-range Influence
With the maturation of differentiable physics, its role in various downstream applications: such as model predictive control, robotic design optimization, and neural PDE solvers, has become increasingly important. However, the derivative information provided by differentiable simulators can exhibit abrupt changes or vanish altogether, impeding the convergence of gradient-based optimizers. In this work, we demonstrate that such erratic gradient behavior is closely tied to the design of contact m…

Fibration Symmetries and Cluster Synchronization in Multi-Body Systems
Margherita Bert\`e, Tommaso Gili
https://arxiv.org/abs/2510.11207 https://arxiv.org/…

Fibration Symmetries and Cluster Synchronization in Multi-Body Systems
Based on recent advances in fibration symmetry theory, we investigate how structural symmetries influence synchronization in systems with higher-order interactions (HOI). Using bipartite graph representations, we identify a node partition in fibres, based on equivalent incidence relations in hypergraphs. We study how identical nodes with an isomorphic input set can synchronize due to structural properties under our specific model assumptions, examining the dynamical model of Kuramoto with highe…

Inverse magnetic catalysis in the linear sigma model: a beyond mean field approach
Gabriela Fern\'andez, Luis A. Hern\'andez, Ana Mizher
https://arxiv.org/abs/2510.02747

Inverse magnetic catalysis in the linear sigma model: a beyond mean field approach
We explore the restoration of chiral symmetry in the linear sigma model coupled to quarks under the influence of strong magnetic fields and finite temperature, incorporating screening effects through ring diagrams. While previous studies using tree-level thermal masses lead to magnetic catalysis across all temperature ranges, in tension with lattice QCD results, we go beyond this limitation by computing the bosonic masses self-consistently within the lowest Landau level (LLL) approximation. The…

Influence-Guided Concolic Testing of Transformer Robustness
Chih-Duo Hong, Yu Wang, Yao-Chen Chang, Fang Yu
https://arxiv.org/abs/2509.23806 https://arxiv.…

Influence-Guided Concolic Testing of Transformer Robustness
Concolic testing for deep neural networks alternates concrete execution with constraint solving to search for inputs that flip decisions. We present an {influence-guided} concolic tester for Transformer classifiers that ranks path predicates by SHAP-based estimates of their impact on the model output. To enable SMT solving on modern architectures, we prototype a solver-compatible, pure-Python semantics for multi-head self-attention and introduce practical scheduling heuristics that temper const…

Beyond Revenue and Welfare: Counterfactual Analysis of Spectrum Auctions with Application to Canada's 3800MHz Allocation
Sara Jalili Shani, Kris Joseph, Michael B. McNally, James R. Wright
https://arxiv.org/abs/2512.08106 https://arxiv.org/pdf/2512.08106 https://arxiv.org/html/2512.08106
arXiv:2512.08106v1 Announce Type: new
Abstract: Spectrum auctions are the primary mechanism through which governments allocate scarce radio frequencies, with outcomes that shape competition, coverage, and innovation in telecommunications markets. While traditional models of spectrum auctions often rely on strong equilibrium assumptions, we take a more parsimonious approach by modeling bidders as myopic and straightforward: in each round, firms simply demand the bundle that maximizes their utility given current prices. Despite its simplicity, this model proves effective in predicting the outcomes of Canada's 2023 auction of 3800 MHz spectrum licenses. Using detailed round-by-round bidding data, we estimate bidders' valuations through a linear programming framework and validate that our model reproduces key features of the observed allocation and price evolution. We then use these estimated valuations to simulate a counterfactual auction under an alternative mechanism that incentivizes deployment in rural and remote regions, aligning with one of the key objectives set out in the Canadian Telecommunications Act. The results show that the proposed mechanism substantially improves population coverage in underserved areas. These findings demonstrate that a behavioral model with minimal assumptions is sufficient to generate reliable counterfactual predictions, making it a practical tool for policymakers to evaluate how alternative auction designs may influence future outcomes. In particular, our study demonstrates a method for counterfactual mechanism design, providing a framework to evaluate how alternative auction rules could advance policy goals such as equitable deployment across Canada.
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The Influence of Central Body Tides on Catastrophic Disruptions of Close-in Planetary Satellites
Harrison Agrusa, Patrick Michel
https://arxiv.org/abs/2510.06044 https://…

The Influence of Central Body Tides on Catastrophic Disruptions of Close-in Planetary Satellites
We model the outcomes of catastrophic disruptions on small, gravity-dominated natural satellites, accounting for the tidal potential of the central body, which is neglected in classical disruption scaling laws. We introduce the concept of $Q^\star_\text{TD}$, the specific energy required to disperse half of the total mass involved in a collision, accounting for the tidal potential of a central body. We derive a simple scaling relation for $Q^\star_\text{TD}$ and demonstrate that for close-in pl…

Markov Decision Processing Networks
Sanidhay Bhambay, Thirupathaiah Vasantam, Neil Walton
https://arxiv.org/abs/2509.24541 https://arxiv.org/pdf/2509.24541…

Markov Decision Processing Networks
We introduce Markov Decision Processing Networks (MDPNs) as a multiclass queueing network model where service is a controlled, finite-state Markov process. The model exhibits a decision-dependent service process where actions taken influence future service availability. Viewed as a two-sided queueing model, this captures settings such as assemble-to-order systems, ride-hailing platforms, cross-skilled call centers, and quantum switches. We first characterize the capacity region of MDPNs. Unli…

Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
Om Dobariya, Akhil Kumar
https://arxiv.org/abs/2510.04950 https://ar…

Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
The wording of natural language prompts has been shown to influence the performance of large language models (LLMs), yet the role of politeness and tone remains underexplored. In this study, we investigate how varying levels of prompt politeness affect model accuracy on multiple-choice questions. We created a dataset of 50 base questions spanning mathematics, science, and history, each rewritten into five tone variants: Very Polite, Polite, Neutral, Rude, and Very Rude, yielding 250 unique prom…

Improved Radiative Transfer Corrections in Helium Emission Lines
Oleg Kurichin, Alexandre Ivanchik
https://arxiv.org/abs/2510.02045 https://arxiv.org/pdf/2…

Improved Radiative Transfer Corrections in Helium Emission Lines
We present a new detailed model of the He I collisional-recombination spectrum based on the most up-to-date atomic data. The model accounts for radiative transfer effects and the influence of a non-zero optical depth in He I lines arising from transitions to the metastable 2^3S state. The model reveals substantial deviations in the emissivities of the lambda3889 and lambda7065 lines in the case of a non-zero optical depth, with previous models systematically underestimating and overestimating t…

Zeeman: A Deep Learning Regional Atmospheric Chemistry Transport Model
Mijie Pang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Guoqiang Wang, Hong Liao, Wei Han
https://arxiv.org/abs/2510.06140

Zeeman: A Deep Learning Regional Atmospheric Chemistry Transport Model
Atmospheric chemistry encapsulates the emission of various pollutants, the complex chemistry reactions, and the meteorology dominant transport, which form a dynamic system that governs air quality. While deep learning (DL) models have shown promise in capturing intricate patterns for forecasting individual atmospheric component - such as PM2.5 and ozone - the critical interactions among multiple pollutants and the combined influence of emissions and meteorology are often overlook. This study in…

Towards Verifiable Federated Unlearning: Framework, Challenges, and The Road Ahead
Thanh Linh Nguyen, Marcela Tuler de Oliveira, An Braeken, Aaron Yi Ding, Quoc-Viet Pham
https://arxiv.org/abs/2510.00833

Towards Verifiable Federated Unlearning: Framework, Challenges, and The Road Ahead
Federated unlearning (FUL) enables removing the data influence from the model trained across distributed clients, upholding the right to be forgotten as mandated by privacy regulations. FUL facilitates a value exchange where clients gain privacy-preserving control over their data contributions, while service providers leverage decentralized computing and data freshness. However, this entire proposition is undermined because clients have no reliable way to verify that their data influence has be…

Efficient and accurate tensor network algorithm for Anderson impurity problems
Zhijie Sun, Zhenyu Li, Chu Guo
https://arxiv.org/abs/2510.11459 https://arxi…

Efficient and accurate tensor network algorithm for Anderson impurity problems
The Anderson impurity model (AIM) is of fundamental importance in condensed matter physics to study strongly correlated effects. However, accurately solving its long-time dynamics still remains a great numerical challenge. An emergent and rapidly developing numerical strategy to solve the AIM is to represent the Feynman-Vernon influence functional (IF), which encodes all the bath effects on the impurity dynamics, as a matrix product state (MPS) in the temporal domain. The computational cost of …

A Hybrid Agent-Based and System Dynamics Framework for Modelling Project Execution and Technology Maturity in Early-Stage R&D
R. W. S. Pessoa, M. H. N{\ae}ss, J. C. Bijos, C. M. Rebello, D. Colombo, L. Schnitman, I. B. R. Nogueira
https://arxiv.org/abs/2510.09688

A Hybrid Agent-Based and System Dynamics Framework for Modelling Project Execution and Technology Maturity in Early-Stage R&D
This paper presents a hybrid approach to predict the evolution of technological maturity in R and D projects, using the oil and gas sector as an example. Integrating System Dynamics (SD) and Agent Based Modelling (ABM) allows the proposed multi level framework to capture uncertainties in work effort, team size, and project duration, which influence technological progress. While AB SD hybrid models are established in other fields, their use in R and D remains limited. The model combines system l…

Autonomy Matters: A Study on Personalization-Privacy Dilemma in LLM Agents
Zhiping Zhang, Yi Evie Zhang, Freda Shi, Tianshi Li
https://arxiv.org/abs/2510.04465 https://

Autonomy Matters: A Study on Personalization-Privacy Dilemma in LLM Agents
Large Language Model (LLM) agents require personal information for personalization in order to better act on users' behalf in daily tasks, but this raises privacy concerns and a personalization-privacy dilemma. Agent's autonomy introduces both risks and opportunities, yet its effects remain unclear. To better understand this, we conducted a 3$\times$3 between-subjects experiment ($N=450$) to study how agent's autonomy level and personalization influence users' privacy concerns, trust and willin…

Campaign-spending driven polarization transition in a double-random field model of elections
Jan Korbel, Remah Dahdoul, Stefan Thurner
https://arxiv.org/abs/2510.00612 https://

Campaign-spending driven polarization transition in a double-random field model of elections
We model bipartisan elections where voters are exposed to two forces: local homophilic interactions and external influence from two political campaigns. The model is mathematically equivalent to the random field Ising model with a bimodal field. When both parties exceed a critical campaign spending, the system undergoes a phase transition to a highly polarized state where homophilic influence becomes negligible, and election outcomes mirror the proportion of voters aligned with each campaign, i…

Stability and Robustness of Time-Varying Opinion Dynamics: A Graph-Theoretic Approach
M. Hossein Abedinzadeh, Emrah Akyol
https://arxiv.org/abs/2510.01580 https://

Stability and Robustness of Time-Varying Opinion Dynamics: A Graph-Theoretic Approach
We study the stability of opinion dynamics in the time-varying Friedkin-Johnsen (TVFJ) model, which captures both persistent individual biases and adaptive social influence. We introduce two temporal structures, defected temporal graphs (DTGs) and weakly defected temporal graphs (WDTGs), that serve as graph-theoretic certificates linking stubborn influence and temporal connectivity to contraction of the state-transition matrix. Using these tools, we prove asymptotic stability of TVFJ dynamics u…

Assessing the Influence of Locational Suitability on the Spatial Distribution of Household Wealth in Bernalillo County, NM
Onyedikachi J. Okeke, Uloma E. Nelson, Chukwudi Nwaogu, Olumide O. Oladoyin, Emmanuel Kubuafor, Dennis Baidoo, Titilope Akinyemi, Adedoyin S. Ajeyomi, Rekiya A. Idris, Isaac A. Fabunmi
https://arxiv.org/abs/2510.11048

Assessing the Influence of Locational Suitability on the Spatial Distribution of Household Wealth in Bernalillo County, NM
This study applies Multiscale Geographically Weighted Regression (MGWR) to examine the spatial determinants of household wealth in Bernalillo County, New Mexico. The model incorporates sociodemographic, environmental, and proximity-based variables to evaluate how locational suitability influences economic outcomes. Key factors considered include income, home value, elevation, PM2.5 concentration, and distances to essential services such as schools, markets, and hospitals. The MGWR model demonst…

Understanding How Network Geometry Influences Diffusion Processes in Complex Networks: A Focus on Cryptocurrency Blockchains and Critical Infrastructure Networks
S M Mustaquim, Asim K. Dey, Abhijit Mandal
https://arxiv.org/abs/2509.23450

Understanding How Network Geometry Influences Diffusion Processes in Complex Networks: A Focus on Cryptocurrency Blockchains and Critical Infrastructure Networks
This study provides essential insights into how diffusion processes unfold in complex networks, with a focus on cryptocurrency blockchains and infrastructure networks. The structural properties of these networks, such as hub-dominated, heavy-tailed topology, network motifs, and node centrality, significantly influence diffusion speed and reach. Using epidemic diffusion models, specifically the Kertesz threshold model and the Susceptible-Infected (SI) model, we analyze key factors affecting diff…

Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics
Jiajie Zhao, Tao Luo, Yaoyu Zhang
https://arxiv.org/abs/2510.09564 https://

Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics
While architecture is recognized as key to the performance of deep neural networks, its precise effect on training dynamics has been unclear due to the confounding influence of data and loss functions. This paper proposed an analytic framework based on the geometric control theory to characterize the dynamical properties intrinsic to a model's parameterization. We prove that the Structural Invariant Manifolds (SIMs) of an analytic model $F(\mathbfθ)(\mathbf{x})$--submanifolds that confine grad…

Enhancing work-extraction in quantum batteries via correlated reservoirs
Sejal Ahuja, Tanoy Kanti Konar, Aditi Sen De
https://arxiv.org/abs/2509.25109 https://

Enhancing work-extraction in quantum batteries via correlated reservoirs
Going beyond isolated system dynamics, we examine how local and spatially correlated reservoirs influence the work extraction in quantum batteries. By employing a one-dimensional spin-1/2 model coupled to baths via dephasing and amplitude-damping noise, we demonstrate that correlations in reservoirs can significantly enhance battery's performance compared to local noise. In the dephasing scenario, we prove that correlated reservoirs produce a finite amount of extractable work, or ergotropy, dur…

Holographic s p superconductors with axion induced translation symmetry breaking
Ru-Qing Chen, Hui Zeng, Zhang-Yu Nie, Xin Zhao
https://arxiv.org/abs/2510.01922 https://

Holographic s+p superconductors with axion induced translation symmetry breaking
We construct a holographic model for an s+p superconductor with axion-induced translation symmetry breaking within the framework of gauge/gravity duality, working in the probe limit. The equations of motion are solved numerically to investigate the influence of the parameter $k/T$ on the competition and coexistence between the s-wave and p-wave orders. We find that increasing $k/T$ suppresses the thermodynamic stability of both the single condensate s-wave and p-wave solutions. With the $k-μ$ …

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Sibel \"Ortel, Mutlu Y{\i}ld{\i}z
https://arxiv.org/abs/2510.02931 https://arxiv…

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Red giant stars play a key role in advancing our understanding of stellar mass loss. However, its initial mass and the amount of mass lost during this phase remain uncertain. In this study, we investigate the asteroseismic signatures of mass loss and the parameters that influence it. We examine six stars identified as red giant branch (RGB) stars in the APOKASC-2 catalog. Assuming these stars are on their first ascent of the RGB, we construct interior models. The resulting model ages are signif…

Incoherent repumping scheme in the $^{88}$Sr$^{ }$ five-level manifold
Valentin Martimort, Sacha Guesne, Derwell Drapier, Vincent Tugaye, Lilay Gros-Desormeaux, Valentin Cambier, Albane Douillet, Luca Guidoni, Jean-Pierre Likforman
https://arxiv.org/abs/2512.08710 https://arxiv.org/pdf/2512.08710 https://arxiv.org/html/2512.08710
arXiv:2512.08710v1 Announce Type: new
Abstract: Laser-cooled trapped ions are at the heart of modern quantum technologies and their cooling dynamics often deviate from the simplified two-level atom model. Doppler cooling of the $^{88}$Sr$^{ }$ ion involves several electronic levels and repumping channels that strongly influence fluorescence.In this work, we study a repumping scheme for the $^{88}$Sr$^{ }$ ion by combining precision single-ion spectroscopy with comprehensive numerical modeling based on optical Bloch equations including 18 Zeeman sublevels. We show that, although the observed fluorescence spectra retain a Lorentzian lineshape, their width and amplitude cannot be explained by a two-level atom description. Moreover, we find the optimal repumping conditions for maximizing the photon scattering rate.
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The influence of grain crushing and pore collapse on the formation of faults
N. A. Collins-Craft, I. Stefanou, J. Sulem, I. Einav
https://arxiv.org/abs/2509.22477 https://

The influence of grain crushing and pore collapse on the formation of faults
During an earthquake, slip occurs in a localised shear zone that features a heavily granulated fault core that can be characterised as a shear band. We study the formation of this fault core in a granular rock such as sandstone by developing a model of crushable granular media within the framework of Breakage Mechanics. This model accounts for the evolution of the grain size distribution, while also accounting for the co-evolution of the solid fraction. An enrichment with the Cosserat continuum…

Introspection in Learned Semantic Scene Graph Localisation
Manshika Charvi Bissessur, Efimia Panagiotaki, Daniele De Martini
https://arxiv.org/abs/2510.07053 https://

Introspection in Learned Semantic Scene Graph Localisation
This work investigates how semantics influence localisation performance and robustness in a learned self-supervised, contrastive semantic localisation framework. After training a localisation network on both original and perturbed maps, we conduct a thorough post-hoc introspection analysis to probe whether the model filters environmental noise and prioritises distinctive landmarks over routine clutter. We validate various interpretability methods and present a comparative reliability analysis. …

Coupling free-surface geometry and localized ion dose for continuum models of radiation-induced nanopatterning
Tyler P. Evans, Scott A. Norris
https://arxiv.org/abs/2510.01503 h…

Coupling free-surface geometry and localized ion dose for continuum models of radiation-induced nanopatterning
A first-principles understanding of the self-organization of highly regular, nanometer-scale structures atop irradiated semiconductor surfaces has been sought for decades. While numerous models exist which explain certain aspects of this phenomenon, a unified, physical model capable of explaining all details of pattern formation has remained elusive. However, it is increasingly apparent that such a model will require understanding the dual influence of the collision cascade initiated by ion imp…

Recidivism and Peer Influence with LLM Text Embeddings in Low Security Correctional Facilities
Shanjukta Nath, Jiwon Hong, Jae Ho Chang, Keith Warren, Subhadeep Paul
https://arxiv.org/abs/2509.20634

Recidivism and Peer Influence with LLM Text Embeddings in Low Security Correctional Facilities
We find AI embeddings obtained using a pre-trained transformer-based Large Language Model (LLM) of 80,000-120,000 written affirmations and correction exchanges among residents in low-security correctional facilities to be highly predictive of recidivism. The prediction accuracy is 30\% higher with embedding vectors than with only pre-entry covariates. However, since the text embedding vectors are high-dimensional, we perform Zero-Shot classification of these texts to a low-dimensional vector of…

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Mohammad Tamim Kashifi
https://arxiv.org/abs/2510.09886

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Over the past decade, there has been a growing trend toward integrating human factors (HF) into traffic flow models to better understand the complexities of human behavior and its impact on traffic dynamics. This research seeks to advance this trend by bridging the gap between traditional car-following models and the inherent variability of human driving behavior. By incorporating these elements, our models provide valuable insights into how driver behavior adaptation and risk-taking influence …

CURE: Centroid-guided Unsupervised Representation Erasure for Facial Recognition Systems
Fnu Shivam, Nima Najafzadeh, Yenumula Reddy, Prashnna Gyawali
https://arxiv.org/abs/2509.19562

CURE: Centroid-guided Unsupervised Representation Erasure for Facial Recognition Systems
In the current digital era, facial recognition systems offer significant utility and have been widely integrated into modern technological infrastructures; however, their widespread use has also raised serious privacy concerns, prompting regulations that mandate data removal upon request. Machine unlearning has emerged as a powerful solution to address this issue by selectively removing the influence of specific user data from trained models while preserving overall model performance. However, …

Slow-phonon control of spin Edelstein effect in Rashba $d$-wave altermagnets
Mohsen Yarmohammadi, Jacob Linder, James K. Freericks
https://arxiv.org/abs/2510.02451 https://

Slow-phonon control of spin Edelstein effect in Rashba $d$-wave altermagnets
Altermagnets have zero net magnetization yet feature spin-split bands that host spin-polarized states. Here, we investigate how slow lattice vibrations (phonons) influence both the intrinsic and externally induced spin polarizations in two-dimensional $d$-wave altermagnets. For the induced spin polarizations, we employ a Rashba continuum model with electron-phonon coupling (EPC) treated at the static-Holstein level and analyze the spin Edelstein effect using the Kubo linear-response formalism. …

Analysis of managerial behaviors in business management
Ernest G\'orka, Dariusz Baran, Micha{\l} \'Cwi\k{a}ka{\l}a, Gabriela Wojak, Robert Marszczuk, Katarzyna Olszy\'nska, Piotr Mrzyg{\l}\'od, Maciej Frasunkiewicz, Piotr R\k{e}czajski, Kamil Sa{\l}uga, Maciej \'Slusarczyk, Jan Piwnik
https://arxiv.org/abs/2510.07047

Analysis of managerial behaviors in business management
This study explores how different managerial behaviors influence team effectiveness and organizational outcomes, using Kenneth Blanchard's situational leadership model as a diagnostic tool. Conducted across ten companies, the research evaluates leadership adaptability through a scenario-based questionnaire identifying instructional, teaching, supportive, and delegating styles. Results show that the supportive (affiliative) style is dominant, present in 60 percent of surveyed companies, with del…

Laser-assisted {\alpha} decay of actinide nuclei in bichromatic fields
You-Tian Zou, Tong-Pu Yu
https://arxiv.org/abs/2510.10896 https://arxiv.org/pdf/2510…

Laser-assisted α decay of actinide nuclei in bichromatic fields
Actinide nuclei provide a suitable platform for studying the laser-assisted nuclear $α$ decay, with potential applications in nuclear transmutation, nuclear radiotherapy, and nuclear battery regulation. In the present work, we develop a deformed one-parameter model to quantitatively study the influence of ultra-intense laser fields on the $α$ decay of actinide nuclei. Our calculations show that the $α$-decay half-lives of these nuclei can be altered to some finite extent under laser intensit…

LLM Company Policies and Policy Implications in Software Organizations
Ranim Khojah, Mazen Mohamad, Linda Erlenhov, Francisco Gomes de Oliveira Neto, Philipp Leitner
https://arxiv.org/abs/2510.06718

LLM Company Policies and Policy Implications in Software Organizations
The risks associated with adopting large language model (LLM) chatbots in software organizations highlight the need for clear policies. We examine how 11 companies create these policies and the factors that influence them, aiming to help managers safely integrate chatbots into development workflows.

Ecosystem Recovery to Historical Targets Becomes Unattainable Under Modelled Fishing and Climate in the Barents Sea
Matthew Hatton, Jack H Laverick, Neil Banas, Michael Heath
https://arxiv.org/abs/2510.04806

Ecosystem Recovery to Historical Targets Becomes Unattainable Under Modelled Fishing and Climate in the Barents Sea
Climate change and fisheries jointly shape the resilience of the Barents Sea marine ecosystem, yet the recovery of key fish populations to climate and anthropogenic disturbances requires further investigation. This study examines how fishing pressure and climate change, driven by the NEMO-MEDUSA Earth system model, influence the recovery times of Demersal and Planktivorous fish in the Barents Sea. We used the StrathE2EPolar end-to-end ecosystem model to simulate transient dynamics under increas…

Projection-based model order reduction for residence time distribution analysis of an industrial-scale continuous casting tundish
Harshith Gowrachari, Mattia Giuseppe Barra, Moaad Khamlich, Giovanni Stabile, Gianluca Bazzaro, Gianluigi Rozza
https://arxiv.org/abs/2509.20366

Projection-based model order reduction for residence time distribution analysis of an industrial-scale continuous casting tundish
The flow behavior in the continuous casting tundish plays a critical role in steel quality and is typically characterized via residence time distribution (RTD) curves. This study investigates the fluid flow behaviour in a single-strand tundish using numerical and experimental approaches. Full-order model (FOM) steady-state simulations were conducted under both isothermal and non-isothermal conditions to assess the influence of thermal buoyancy on the flow characteristics. The results show that …

Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Zinan Zheng, Yang Liu, Jia Li
https://arxiv.org/abs/2509.20911 https://

Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Graph neural networks have shown promising results in weather forecasting, which is critical for human activity such as agriculture planning and extreme weather preparation. However, most studies focus on finite and local areas for training, overlooking the influence of broader areas and limiting their ability to generalize effectively. Thus, in this work, we study global weather forecasting that is irregularly distributed and dynamically varying in practice, requiring the model to generalize t…

Observational constraints on f(Q,T) gravity from the mass-radius relation and stability of compact stars
S. K. Maurya, Abdul Aziz, Ksh. Newton Singh, G. Mustafa, Y. Sekhmani, Saibal Ray
https://arxiv.org/abs/2510.06003

Observational constraints on f(Q,T) gravity from the mass-radius relation and stability of compact stars
In this investigation we examine the astrophysical consequences of the influence of pressure anisotropy on the physical properties of observed pulsars within the background of $f(Q,T)$ gravity by choosing a specific form $f(Q, T)=ψ_1\, Q + ψ_2 T$, where $ψ_1$ and $ψ_2$ are the model parameters. Initially, we solve the modified field equations for anisotropic stellar configurations by assuming the physically valid metric potential along with anisotropic function for the distribution of the i…

Effect of a Fine-Scale Layered Structure of the Atmosphere on Infrasound Signals from Fragmenting Meteoroids
Igor P. Chunchuzov, Oleg E. Popov, Elizabeth A. Silber, Segey N. Kulichkov
https://arxiv.org/abs/2510.03655

Effect of a Fine-Scale Layered Structure of the Atmosphere on Infrasound Signals from Fragmenting Meteoroids
We investigate the influence of a fine-scale (FS) layered structure in the atmosphere on the propagation of infrasound signals generated by fragmenting meteoroids. Using a pseudo-differential parabolic equation (PPE) approach, we model broadband acoustic signals from point sources at altitudes of 35-100 km. The presence of FS fluctuations in the stratosphere (37-45 km) and the lower thermosphere (100-120 km) modifies ray trajectories, causing multiple arrivals and prolonged signal durations at …

Learning Paths to Multi-Sector Equilibrium: Belief Dynamics Under Uncertain Returns to Scale
Stefano Nasini, Rabia Nessah, Bertrand Wigniolle
https://arxiv.org/abs/2512.07013 https://arxiv.org/pdf/2512.07013 https://arxiv.org/html/2512.07013
arXiv:2512.07013v1 Announce Type: new
Abstract: This paper explores the dynamics of learning in a multi-sector general equilibrium model where firms operate under incomplete information about their production returns to scale. Firms iteratively update their beliefs using maximum a-posteriori estimation, derived from observed production outcomes, to refine their knowledge of their returns to scale. The implications of these learning dynamics for market equilibrium and the conditions under which firms can effectively learn their true returns to scale are the key objects of this study. Our results shed light on how idiosyncratic shocks influence the learning process and demonstrate that input decisions encode all pertinent information for belief updates. Additionally, we show that a long-memory (path-dependent) learning which keeps track of all past estimations ends up having a worse performance than a short-memory (path-independent) approach.
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Threading the Magellanic Needle: Hypervelocity Stars Trace the Past Location of the LMC
Scott Lucchini, Jiwon Jesse Han
https://arxiv.org/abs/2510.03393 https://

Threading the Magellanic Needle: Hypervelocity Stars Trace the Past Location of the LMC
Recent discoveries have shown that a population of hypervelocity stars (HVSs) originate from the Large Magellanic Cloud (LMC). We use three such HVSs as dynamical tracers to constrain the past orbit of the LMC. Since each star was ejected at a finite time in the past, it must intersect the past position of the LMC's central black hole at its ejection time. We model the LMC's orbit under the influence of dynamical friction and extended mass distributions for both the LMC and the Milky Way, gener…

CafGa: Customizing Feature Attributions to Explain Language Models
Alan Boyle, Furui Cheng, Vil\'em Zouhar, Mennatallah El-Assady
https://arxiv.org/abs/2509.20901 https://…

CafGa: Customizing Feature Attributions to Explain Language Models
Feature attribution methods, such as SHAP and LIME, explain machine learning model predictions by quantifying the influence of each input component. When applying feature attributions to explain language models, a basic question is defining the interpretable components. Traditional feature attribution methods, commonly treat individual words as atomic units. This is highly computationally inefficient for long-form text and fails to capture semantic information that spans multiple words. To addr…

Bidding strategies for energy storage players in 100% renewable electricity market: A game-theoretical approach
Arega Getaneh Abate, Salim Hassi, Dogan Keles, Xiufeng Liu, Xiao-Bing Zhang
https://arxiv.org/abs/2509.26568

Bidding strategies for energy storage players in 100% renewable electricity market: A game-theoretical approach
The transition to electricity systems powered entirely by renewable energy sources makes energy storage indispensable for balancing intermittency and ensuring reliability. Since RES operate at near-zero marginal cost, storage operators can strongly influence electricity prices and energy security when renewable supply alone cannot meet demand. We develop a Cournot competition model in which storage operators strategically bid quantities to maximize their profits. We propose a MILP model with th…

CFD Analysis of Taylor Bubble in a Co-Flow Microchannel with Newtonian and Non-Newtonian Liquid
Somasekhara Goud Sontti, Arnab Atta
https://arxiv.org/abs/2510.06745 https://

CFD Analysis of Taylor Bubble in a Co-Flow Microchannel with Newtonian and Non-Newtonian Liquid
We present a CFD based model to understand the Taylor bubble behavior in Newtonian and non-Newtonian liquids flowing through a confined co-flow microchannel. Systematic investigation is carried out to explore the influence of surface tension, inlet velocities, and apparent viscosity on the bubble length, shape, velocity, and film thickness around the bubble. Aqueous solutions of carboxymethyl cellulose (CMC) with different concentrations are considered as power-law liquid to address the presenc…

SDSS-V Black Hole Mapper: The Index Diagram as a tool to disentangle the influence of the Host Galaxy in Quasar spectra
C. A. Negrete, R. Sandoval-Orozco, H. Ibarra-Medel, B. Tapia, R. J. Assef, D. Dultzin, I. Lacerna, S. Morrison, S. F. Anderson, P. Rodr\'iguez Hidalgo C. Aydar, F. E. Bauer, E. Benitez, D. Bizyaev, W. N. Brandt, J. R. Brownstein, J. Buchner, I. Cruz-Gonz\'alez, D. Gonz\'alez-Buitrago, H. Hern\'andez-Toledo, N. Jenaro-Ballesteros, A. Koekemoer, Y. Krong…

SDSS-V Black Hole Mapper: The Index Diagram as a tool to disentangle the influence of the Host Galaxy in Quasar spectra
We revisit the Quasar Main Sequence (QMS) by investigating the impact of the stellar component from the host galaxy (HG) on the emission line spectra of the active galactic nuclei (AGN). We first detect spectra with broad emission lines using a line ratio method for a sample of $\sim$3000 high SNR ($>$20) Black Hole Mapper objects (part of the fifth phase of the Sloan Digital Sky Survey). We then built the Index diagram, a novel diagnostic tool using the $z$-corrected spectra, model-free, desig…

Regulation of droplet size and flow regime by geometrical confinement in a microfluidic flow-focusing device
Somasekhara Goud Sontti, Arnab Atta
https://arxiv.org/abs/2510.06893

Regulation of droplet size and flow regime by geometrical confinement in a microfluidic flow-focusing device
We have developed a coupled level set and volume of fluid-based computational fluid dynamics model to analyze the droplet formation mechanism in a square flow-focusing microchannel. We demonstrate a flexible manipulation of droplet formation and flow regime based on the modified flow-focusing microchannel with a constricted orifice. Furthermore, we have systematically studied the influence of geometrical confinement, flow rate, and interfacial tension on the droplet formation regime, length, vo…

Luttinger surface and exchange splitting induced by ferromagnetic fluctuations
Motoharu Kitatani, Yusuke Nomura, Shiro Sakai, Ryotaro Arita
https://arxiv.org/abs/2509.21034 http…

Luttinger surface and exchange splitting induced by ferromagnetic fluctuations
Ferromagnetism in the single-orbital Hubbard model, which contains only local Coulomb repulsion and no explicit ferromagnetic exchange interactions, has been extensively studied. However, how the associated fluctuations influence the electronic properties near the transition remains a fundamental issue. Here, by applying the dynamical vertex approximation (D$Γ$A) to single-orbital systems with a partially flat band dispersion, we demonstrate that finite-correlation-length ferromagnetic fluctua…

Technology innovation in evolutionary green transition: environmental quality and economic sustainability
Fausto Cavalli, Alessandra Mainini, Enrico Moretto, Ahmad Naimzada
https://arxiv.org/abs/2509.25272

Technology innovation in evolutionary green transition: environmental quality and economic sustainability
We propose an evolutionary model to study the transition toward green technology under the influence of innovation. Clean and dirty technologies are selected according to their profitability under an environmental tax, which depends on the overall pollution level. Pollution itself evolves dynamically: it results from the emissions of the two types of producers, naturally decays, and is reduced through the implementation of the current abatement technology. The regulator collects tax revenues an…

Modeling Tennis In-Match Momentum Using Probability Method
Jackson Graves, Daniel X. Guo, Ridge Shepherd, Alexander Young
https://arxiv.org/abs/2509.22670 https://

Modeling Tennis In-Match Momentum Using Probability Method
This paper investigates the Tennis Momentum Model (TMM), which aims to enhance the understanding of match dynamics by integrating key factors such as efficiency, historical scoring probabilities, and real-time scoring data. The model is designed to explore how momentum affects player performance throughout a match and how it might influence overall match outcomes. By leveraging this model, players and coaches could gain valuable insights that may help them adjust their strategies in response to…