March 2025 arXiv papers — page 19

Hilda Hadan, Reza Hadi Mogavi, Leah Zhang-Kennedy, Lennart E. Nacke

The rapid growth of artificial intelligence (AI) technologies has raised major privacy and ethical concerns. However, existing AI incident taxonomies and guidelines lack grounding in real-world cases, limiting their effectiveness for prevention and mitigation. We analyzed 202 real-world AI privacy and ethical incidents to develop a taxonomy that classifies t

Owen Medeiros, Matteo Castellani, Valentin Karam, Reed Foster

Developing ultra-low-energy superconducting computing and fault-tolerant quantum computing will require scalable superconducting memory. While conventional superconducting logic-based memory cells have facilitated early demonstrations, their large footprint poses a significant barrier to scaling. Nanowire-based superconducting memory cells offer a compact al

Declan Jagt, Sergei Chernyshenko, Matthew Peet

PDEs with periodic boundary conditions are frequently used to model processes in large spatial environments, assuming solutions to extend periodically beyond some bounded interval. However, solutions to these PDEs often do not converge to a unique equilibrium, but instead converge to non-stationary trajectories existing in the nullspace of the spatial differ

Arian Joharian, Frank Vallentin, Marc Christian Zimmermannn

We discuss the local analysis of Gaussian potential energy of modular lattices. We present examples of $2$-modular lattices -- such as the $16$-dimensional Barnes-Wall lattice -- and $3$-modular lattices -- such as the $12$-dimensional Coxeter-Todd lattice -- that are locally universally optimal among lattices (in the sense of Cohn and Kumar). We also provid

W. Brian Lane

The last two years have seen significant changes in the divine pantheon of the Lost Omens campaign setting of the Pathfinder Tabletop Roleplaying Game. First, the Pathfinder Remaster, necessitated by the Open Game License debacle, prompted the removal of alignment and an enrichment of divine identities and relationships. Second, the War of Immortals, kicked

Md Fazle Rabbi, Arifa Islam Champa, Rajshakhar Paul, Minhaz F. Zibran

This study investigates the software vulnerability resolution time in the Maven ecosystem, focusing on the influence of CVE severity, library popularity as measured by the number of dependents, and version release frequency. The results suggest that critical vulnerabilities are addressed slightly faster compared to lower-severity ones. Library popularity sho

Anna M. Limbach, Martin Winter

We investigate for which classes of (potentially infinite) graphs the clique dynamics is cover stable, i. e., when clique convergence/divergence is preserved under triangular covering maps. We first present an instructive counterexample: a clique convergent graph which covers a clique divergent graph and which is covered by a clique divergent graph. Based on

Hilda Hadan, Lydia Choong, Leah Zhang-Kennedy, Lennart E. Nacke

The well-established deceptive design literature has focused on conventional user interfaces. With the rise of extended reality (XR), understanding deceptive design's unique manifestations in this immersive domain is crucial. However, existing research lacks a full, cross-disciplinary analysis that analyzes how XR technologies enable new forms of deceptive d

Tomohisa Kawashima, Katsuaki Asano

The high-energy particle production in the accretion flow onto black holes can be a key physics to explain the high-energy neutrino background. While the single-zone approximation has been commonly adopted in studies of the high-energy neutrino emission around black holes, the effects of the global plasma structure may be non-negligible. We carry out the fir

Ke Zhang, Vishal M. Patel

Curating large-scale fully annotated datasets is expensive, laborious, and cumbersome, especially for medical images. Several methods have been proposed in the literature that make use of weak annotations in the form of scribbles. However, these approaches require large amounts of scribble annotations, and are only applied to the segmentation of regular orga

Maria Alejandra Ramirez, George Datseris, Arne Traulsen

Evolutionary game theory has traditionally employed deterministic models to describe population dynamics. These models, due to their inherent nonlinearities, can exhibit deterministic chaos, where population fluctuations follow complex, aperiodic patterns. Recently, the focus has shifted towards stochastic models, quantifying fixation probabilities and analy

Jonathan Monsalve, Kumar Vijay Mishra

Accurate target parameter estimation of range, velocity, and angle is essential for vehicle safety in advanced driver assistance systems (ADAS) and autonomous vehicles. To enable spectrum sharing, ADAS may employ integrated sensing and communications (ISAC). This paper examines a dual-deconvolution automotive ISAC scenario where the radar waveform is known b

Haoran Lin, Christopher L. Jacobs, Chenhui Yan, Gillian M. Nolan

A topological superconductor, characterized by either a chiral order parameter or a chiral topological surface state in proximity to bulk superconductivity, is foundational to topological quantum computing. As in other topological phases of matter, electronic correlations can tune topological superconductivity via modifications of the low-energy Fermiology.

Emil Graf, Alex Townsend

We present a novel, global algorithm for solving polynomial multiparameter eigenvalue problems (PMEPs) by leveraging a hidden variable tensor Dixon resultant framework. Our method transforms a PMEP into one or more univariate polynomial eigenvalue problems, which are solved as generalized eigenvalue problems. Our general approach avoids the need for custom l

Ron Vainshtein, Zohar Rimon, Shie Mannor, Chen Tessler

Recent advancements in imitation learning have led to transformer-based behavior foundation models (BFMs) that enable multi-modal, human-like control for humanoid agents. While excelling at zero-shot generation of robust behaviors, BFMs often require meticulous prompt engineering for specific tasks, potentially yielding suboptimal results. We introduce "Task

Lukas Rapp, Muriel Médard, Ken R. Duffy

Proposals have been made to reduce the guesswork of Guessing Random Additive Noise Decoding (GRAND) for binary linear codes by leveraging codebook structure at the expense of degraded block error rate (BLER). We establish one can preserve guesswork reduction while eliminating BLER degradation through dynamic list decoding terminated based on Soft Output GRAN

Yi-Ting Shen, Sungmin Eum, Doheon Lee, Rohit Shete

Composed pose retrieval (CPR) enables users to search for human poses by specifying a reference pose and a transition description, but progress in this field is hindered by the scarcity and inconsistency of annotated pose transitions. Existing CPR datasets rely on costly human annotations or heuristic-based rule generation, both of which limit scalability an

Jishnu Bose, Tien Chih, Hannah Housden, Legrand Jones

We initiate the combinatorial study of factorization systems on finite lattices, paying special attention to the role that reflective and coreflective factorization systems play in partitioning the poset of factorization systems on a fixed lattice. We ultimately uncover an intricate web of relations with such diverse combinatorial structures as submonoids, m

Mohsen Yarmohammadi, Peter M. Oppeneer, James K. Freericks

We propose a N\'eel magnetization switching mechanism in a hybrid magnon-phonon optical cavity system. A terahertz-pumped single-mode cavity photon couples to a spin-phonon chain, while the system dissipates energy via different baths. Our mean-field analysis reveals that the photon induces magnetization switching by generating strongly entangled magnon pair

Lauren Shrack, Timm Haucke, Antoine Salaün, Arjun Subramonian

The differences between images belonging to fine-grained categories are often subtle and highly localized, and existing explainability techniques for deep learning models are often too diffuse to provide useful and interpretable explanations. We propose a new explainability method (PAIR-X) that leverages both intermediate model activations and backpropagated

Matias Valdenegro-Toro, Deepan Chakravarthi Padmanabhan, Deepak Singh, Bilal Wehbe

Sonar sensing is fundamental for underwater robotics, but limited by capabilities of AI systems, which need large training datasets. Public data in sonar modalities is lacking. This paper presents the Marine Debris Forward-Looking Sonar datasets, with three different settings (watertank, turntable, flooded quarry) increasing dataset diversity and multiple co

Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu

State Space Models (SSMs) are emerging as a compelling alternative to Transformers because of their consistent memory usage and high performance. Despite this, scaling up SSMs on cloud services or limited-resource devices is challenging due to their storage requirements and computational power. To overcome this, quantizing SSMs with low bit-width data format

William K. Peria, Shengzhi Zhang, Sangyun Lee, Vivien S. Zapf

Capacitance measurements are crucial for probing the electrical properties of materials. In this study, we develop and implement a capacitance measurement technique optimized for pulsed magnetic fields. Our approach employs an auto-balancing bridge method, leveraging a high-bandwidth transimpedance amplifier to mitigate parasitic contributions from coaxial c

Bruno Coelho, Shujaat Mirza, Yuyuan Cui, Christina Pöpper

Fact-checking is a potentially useful application of Large Language Models (LLMs) to combat the growing dissemination of disinformation. However, the performance of LLMs varies across geographic regions. In this paper, we evaluate the factual accuracy of open and private models across a diverse set of regions and scenarios. Using a dataset containing 600 fac

Kushagra Srivastava, Rutwik Kulkarni, Manoj Velmurugan, Nitin J. Sanket

Autonomous aerial robots are becoming commonplace in our lives. Hands-on aerial robotics courses are pivotal in training the next-generation workforce to meet the growing market demands. Such an efficient and compelling course depends on a reliable testbed. In this paper, we present VizFlyt, an open-source perception-centric Hardware-In-The-Loop (HITL) photo

Hang Liu, Junjie Li, Yinzhi Wang

This study explores the use of automatic BLAS offloading and INT8-based emulation for accelerating traditional HPC workloads on modern GPU architectures. Through the use of low-bitwidth integer units and cache-coherent Unified Memory Architecture, we emulate double-precision matrix multiplications in the MuST application without code changes. We find that ac

Sarira Sahu, R. de J. Pacheco-Aké, G. Sánchez-Colón, D. I. Páez-Sánchez

Between 2005 and 2015, the BL Lacertae object PG 1553+113 exhibited multiple very high-energy (VHE; > 100 GeV) gamma-ray flares, which were detected by the Cherenkov telescopes, High Energy Stereoscopic System (HESS), Major Atmospheric Gamma Imaging Cherenkov (MAGIC), and the Very Energetic Radiation Imaging Telescope Array System (VERITAS). Despite the unce

Senbei Du, Merav Opher, Marc Kornbleuth

The evolution of the velocity distribution of pickup ions is crucial for understanding the energetic neutral atom (ENA) fluxes observed by Interstellar Boundary Explorer (IBEX). Pickup ions in the heliosheath contain two main components: those transmitted across the heliospheric termination shock and those locally created within the heliosheath. In this work

Estefania Loayza-Romero, Lidiya Pryymak, Kathrin Welker

In this paper, we study the use of outer metrics, in particular Sobolev-type metrics on the diffeomorphism group in the context of PDE-constrained shape optimization. Leveraging the structure of the diffeomorphism group we analyze the connection between the push-forward of a smooth function defined on the diffeomorphism group and the classical shape derivati

Franco Ferrari, Marcin R. Piątek

The statistical mechanics of [2]catenanes in a solution with constrained number of maxima and minima along a special direction (the height) is discussed. The interest in this system comes from the fact that, in the homopolymer case, it has analogies with self-dual anyon field theory models and has conformations that minimize the static energy and bear partic

Mouaad Boughellaba, Soulaimane Berkane, Abdelhamid Tayebi

This paper addresses the distributed attitude synchronization problem for a network of rigid-body systems on the special orthogonal group SO(3). Each agent measures, in its body frame, its own angular velocity and a set of vectors whose corresponding directions in the inertial frame are unknown. Under an undirected, connected, and acyclic interaction graph t

Alexey Gavryushin, Alexandros Delitzas, Luc Van Gool, Marc Pollefeys

When humans grasp an object, they naturally form trajectories in their minds to manipulate it for specific tasks. Modeling hand-object interaction priors holds significant potential to advance robotic and embodied AI systems in learning to operate effectively within the physical world. We introduce SIGHT, a novel task focused on generating realistic and phys

Muhammad Ahmad, Rita Orji, Fida Ullah, Ildar Batyrshin

The opioid overdose epidemic remains a critical public health crisis, particularly in the United States, leading to significant mortality and societal costs. Social media platforms like Reddit provide vast amounts of unstructured data that offer insights into public perceptions, discussions, and experiences related to opioid use. This study leverages Natural

Yagya Woli, Bryson Krause, Thang Hoang

Random lasing occurs as the result of coherent optical feedback from random scattering centers. Plasmonic nanostructures, such as silver or gold nanoparticles, efficiently scatter light due to the formation of hot spots and optical confinement at the nanoscale. In this work, using silver nanocubes as highly efficient light scattering centers, a broad band pl

Huiwen Yan, Mushuang Liu

Markov games (MGs) provide a mathematical foundation for multi-agent reinforcement learning (MARL), enabling self-interested agents to learn their optimal policies while interacting with others in a shared environment. However, due to the complexities of an MG problem, seeking (Markov perfect) Nash equilibrium (NE) is often very challenging for a general-sum

Satoya Nakano, Kengo Tachihara

We present the three-dimensional kinematics of classical Cepheids (CCs) in the Small Magellanic Cloud (SMC) using Gaia DR3 data. By cross-matching the CCs obtained from the fourth phase of the Optical Gravitational Lensing Experiment with Gaia DR3, we obtain distances and proper motions (PMs) for 4,236 CCs. Among them, 91 stars with available radial velociti

Luis Bonah, Jean-Claude Guillemin, Arnaud Belloche, Sven Thorwirth

Broadband measurements of glycidaldehyde in the frequency ranges 75-170 and 500-750 GHz were recorded to extend previous analyses of its pure rotational spectrum in the microwave region. The rotational parameters of the ground vibrational states for the main isotopologue and the three singly 13C-substituted isotopologues were considerably improved, and addit

Alexander Gill, Aaron Buikema, Stephen Sirisky, Hannah Clevenson

We present a method for simultaneously measuring the phase fronts of three or more RF fields using thermal Rydberg atoms. We demonstrate this method using an all-dielectric atomic electrometer acting in a heterodyne configuration to detect three single tone continuous-wave microwave signals propagating in free space. We show that this method can be used to m

Valentina Cesare, Ugo Becciani, Alberto Vecchiato, Mario Gilberto Lattanzi

The solver module of the Astrometric Verification Unit - Global Sphere Reconstruction (AVU-GSR) pipeline aims to find the astrometric parameters of $\sim$$10^8$ stars in the Milky Way, besides the attitude and instrumental settings of the Gaia satellite and the parametrized post Newtonian parameter $\gamma$ with a resolution of 10-100 micro-arcseconds. To pe

Soumitri Chattopadhyay, Basar Demir, Marc Niethammer

Domain shift, caused by variations in imaging modalities and acquisition protocols, limits model generalization in medical image segmentation. While foundation models (FMs) trained on diverse large-scale data hold promise for zero-shot generalization, their application to volumetric medical data remains underexplored. In this study, we examine their ability

José J. M. Uliana, Renato A. Krohling

This study investigates the application of diffusion models in medical image classification (DiffMIC), focusing on skin and oral lesions. Utilizing the datasets PAD-UFES-20 for skin cancer and P-NDB-UFES for oral cancer, the diffusion model demonstrated competitive performance compared to state-of-the-art deep learning models like Convolutional Neural Networ

Tianyi Zhang, Andrey Krayev, Tilo H. Yang, Nannan Mao

Two-dimensional (2D) Janus transition metal dichalcogenides (TMDs) are promising candidates for various applications in non-linear optics, energy harvesting, and catalysis. These materials are usually synthesized via chemical conversion of pristine TMDs. Nanometer-scale characterization of the obtained Janus materials' morphology and local composition is cru

Nadav E. Rosenthal, Joseph Tabrikian

One-bit quantization has garnered significant attention in recent years for various signal processing and communication applications. Estimating model parameters from one bit quantized data can be challenging, particularly when the quantization process is explicitly accounted for in the estimator. In many cases, the estimator disregards quantization effects,

Adrien Clavel, Mathieu Salaun, Lionel Bastard, Christophe Lepoittevin

Twin photons and triple photons generations require pump laser intensities of several hundred Mega Watts per square centimeter. Micrometer sized crystalline waveguides allow such interactions to be achieved at relatively low energies by taking advantage of the confinement of light. The materials selected to achieve these phenomena in the present work are fro

T. A. Koryukova, S. A. Trushkin, I. N. Pashchenko, A. B. Pushkarev

We continue investigating the observed properties of the quasar 2005$+$403 seen through the highly turbulent plasma in the Cygnus region. Our earlier study Koryukova+2023 revealed a great influence of propagation effects on the observed data, e.g. numerous episodes of multiple imaging formation, angular broadening of the source size, and the detection of an

Baptiste Julien, Ian A. Leahy, Rebecca W. Smaha, John S. Mangum

Some ternary TM nitrides are predicted to adopt layered structures that make them interesting for thermoelectric conversion and quantum materials applications. Synthesis of TM ternary nitride films by physical vapor deposition often favors disordered 3D structures rather than the predicted 2D-like layered structure. In this study, we investigate the structur

Shanshan Bai, Anna Kruspe, Xiaoxiang Zhu

Tweets provides valuable semantic context for earth observation tasks and serves as a complementary modality to remote sensing imagery. In building function classification (BFC), tweets are often collected using geographic heuristics and labeled via external databases, an inherently weakly supervised process that introduces both label noise and sentence leve

Milad Bahrami-Fard, Majid Ghasemi Korrani, Babak Fahimi

This paper proposes a practical startup strategy for current source inverter (CSI)-fed Permanent Magnet Synchronous Motor (PMSM) drives in submersible pump applications, focusing on ensuring a seamless shift to sensorless field-oriented control (FOC). The method effectively manages the transition to sensorless operation without requiring precise current or a

Paulo M. Carvalho-Neto, Renato Fehlberg Júnior

The function spaces of continuously differentiable functions are extensively studied and appear in various mathematical settings. In this context, we investigate the spaces of continuously fractional differentiable functions of order $\alpha>0$, considering both the Riemann-Liouville and Caputo fractional derivatives. We explore several fundamental propertie

Liam Pond, Ichiro Fujinaga

This study evaluates the baseline capabilities of Large Language Models (LLMs) like ChatGPT, Claude, and Gemini to learn concepts in music theory through in-context learning and chain-of-thought prompting. Using carefully designed prompts (in-context learning) and step-by-step worked examples (chain-of-thought prompting), we explore how LLMs can be taught in

Luca Micheletto, Dylan Moore, Daniel Reck, Joel Slemrod

Traditional optimal commodity tax analysis, dating back to Ramsey (1927), prescribes that to maximize welfare one should impose higher taxes on goods with lower demand elasticities. Yet policy makers do not stress minimizing efficiency costs as a desideratum. In this note we revisit the commodity tax problem, and show that the attractiveness of the Ramsey in

Feng Lin, Dong Jae Kim, Zhenhao Li, Jinqiu Yang

When using LLMs to address Non-Functional Requirements (NFRs), developers may behave differently (e.g., expressing the same NFR in different words). Robust LLMs should output consistent results across these variations; however, this aspect remains underexplored. We propose RobuNFR for evaluating the robustness of LLMs in NFR-aware code generation across four

Hassan Abdelraouf, Georgios Piliouras, Jeff S. Shamma

We investigate the interplay between passivity, no-regret, and convergence in contractive games for various learning dynamic models and their higher-order variants. Our setting is continuous time. Building on prior work for replicator dynamics, we show that if learning dynamics satisfy a passivity condition between the payoff vector and the difference betwee

Alberto Padoan, Jeremy Coulson

The paper introduces a class of distances for linear behaviors over finite time horizons. These distances allow for comparisons between finite-horizon linear behaviors represented by matrices of possibly different dimensions. They remain invariant under coordinate changes, rotations, and permutations, ensuring independence from input-output partitions. Moreo

David Harvey, Joris van der Hoeven

Working in the multitape Turing model, we show how to reduce the problem of matrix transposition to the problem of integer multiplication. If transposing an $n \times n$ binary matrix requires $\Omega(n^2 \log n)$ steps on a Turing machine, then our reduction implies that multiplying $n$-bit integers requires $\Omega(n \log n)$ steps. In other words, if matr

Abhishek Mohapatra

The discovery of XYZ exotic states in the hadronic sector with two heavy quarks constitute one of the most important open problems in particle theory. In this work, we demonstrate that the QCD derived Born-Oppenheimer effective field theory (BOEFT) framework, provides a systematic framework to describe exotic states of arbitrary composition. The BOEFT constr

Neha Sharma, Debanjan Bhattacharjee, Sunita Kumari, Sandip Paul Choudhury

Ammonia is a harmful chemical hazard known for its widespread industrial use. Exposure to ammonia can cause environmental damage, human health hazards, and huge economic losses. Therefore, ammonia gas sensors are essential for detecting ammonia leaks to avoid serious accidental injury and death. In this study, we synthesize a nanostructured (WO3) n-type meta

Himali Dabhi

For a linear operator $T$ bounded from $L^p(Y)$ to $L^q(X)$, the Christ-Kiselev theorem gives $L^p \to L^q$ bounds for the maximal function $T^{*}$ associated to filtrations on $Y$. This result has been extended by establishing bounds for the maximal function associated to a product of filtrations, also known as the multiparameter extension of the Christ-Kis

Andrew Osborne, Ciro Salcedo, Andrew A. Houck

Flat band physics is a central theme in modern condensed matter physics. By constructing a tight--binding single particle system that has vanishing momentum dispersion in one or more bands, and subsequently including more particles and interactions, it is possible to study physics in strongly interacting regimes. Inspired by the glued trees that first arose

Luca Cappelli, Giuseppe Murante, Stefano Borgani, Andrea Bulgarelli

The Vlasov-Poisson systems of equations (VP) describes the evolution of a distribution of collisionless particles under the effect of a collective-field potential. VP is at the basis of the study of the gravitational instability of cosmological density perturbations in Dark-Matter (DM), but its range of application extends to other fields, such as plasma phy

Yifan Wang, Xu Ma, Yitian Zhang, Zhongruo Wang

Gating mechanisms have emerged as an effective strategy integrated into model designs beyond recurrent neural networks for addressing long-range dependency problems. In a broad understanding, it provides adaptive control over the information flow while maintaining computational efficiency. However, there is a lack of theoretical analysis on how the gating me

Uwe Peters, Benjamin Chin-Yee

Artificial intelligence chatbots driven by large language models (LLMs) have the potential to increase public science literacy and support scientific research, as they can quickly summarize complex scientific information in accessible terms. However, when summarizing scientific texts, LLMs may omit details that limit the scope of research conclusions, leadin

Can Onur Akyuz, Riccardo Penco

We introduce the concept of "ajar systems" as an intermediate case between closed and open systems, where the time scale for charge exchange with the environment is parametrically larger than all other characteristic time scales. The Schwinger-Keldysh effective action for such finite-temperature systems exhibits a symmetry group $G_1 \times G_2$ weakly broke

Shiyin Shen, Nan Li

The cosmological principle posits that the universe does not exhibit any specific preference for position or direction. However, it remains unclear whether the universe has a distinct preference for parity: whether certain properties are more likely to be classified as even or odd. In this study, we analyze the largest available galaxy group catalogs to expl

Blaž Rodič

This study presents a review of research on social media bot detection. Social media bots are used by political and criminal actors for mass distribution of political messages, as well as rumors, conspiracy theories, and other forms of false information. Through the spread of disinformation, bots are eroding the public trust in political and media institutio

Anni Li, Ting Bai, Yingqing Chen, Christos G. Cassandras

In mixed traffic environments, where Connected and Autonomed Vehicles (CAVs) coexist with potentially non-cooperative Human-Driven Vehicles (HDVs), the self-centered behavior of human drivers may compromise the efficiency, optimality, and safety of the overall traffic network. In this paper, we propose a Cooperative Compliance Control (CCC) framework for mix

J. Russell Carpenter, Anthony C. Davison, Soumaya Elkantassi, Matthew D. Hejduk

Over the last quarter-century, spacecraft conjunction assessment has focused on a quantity associated by its advocates with collision probability. This quantity has a well-known dilution feature, where it is small when uncertainty is large, giving rise to false confidence that a conjunction is safe when it is not. An alternative approach to conjunction asses

Stephen H. Lubow, Gordon I. Ogilvie

The classical Laplace surface defines the location of circular particle orbits that do not undergo nodal precession around a planet with some obliquity. Close to the planet the surface coincides with the equator of the planet, while far from the planet it coincides with the orbital plane of the planet. We determine the shape of the Laplace surface of a circu

Oz Amram, Grace Cummings

This document represents a contribution of the United States early career collider physics community to the 2025--2026 update to the European Strategy for Particle Physics. Preferences with regard to different future collider options and R&D priorities were assessed via a survey. The early career community was defined as anyone who is a graduate student, pos

Ignacio Bono Parisi

The Matrix Bochner Problem aims to classify weight matrices whose sequences of orthogonal polynomials are eigenfunctions of a second-order differential operator. A major breakthrough in this direction was achieved in [7], where it was shown that, under certain natural conditions on the algebra $\mathcal{D}(W)$, all solutions arise from Darboux transformation

Simeng Sun, Cheng-Ping Hsieh, Faisal Ladhak, Erik Arakelyan

Complex reasoning tasks often rely on the ability to consistently and accurately apply simple rules across incremental steps, a foundational capability which we term "level-0" reasoning. To systematically evaluate this capability, we introduce L0-Bench, a language model benchmark for testing procedural correctness -- the ability to generate correct reasoning

A. Anyiszonyan, Zs. Sándor

Context. Protoplanetary discs are formed due to the fragmentation and collapse of giant molecular cloud cores. The physical properties and structure of a formed disc are of great importance when studying the onset of planet formation processes. Aims. Starting from the isothermal collapse of a rotating Bonnor-Ebert sphere, and assuming the conservation of ang

Oscar F. Archila, Alain Vande Wouwer, Johannes Schiffer

Collision avoidance is a problem largely studied in robotics, particularly in unmanned aerial vehicle (UAV) applications. Among the main challenges in this area are hardware limitations, the need for rapid response, and the uncertainty associated with obstacle detection. Artificial potential functions (APOFs) are a prominent method to address these challenge

Zhen Lin, Hongyu Yuan, Richard Barcus, Qing Lyu

Non-human primates (NHPs) serve as critical models for understanding human brain function and neurological disorders due to their close evolutionary relationship with humans. Accurate brain tissue segmentation in NHPs is critical for understanding neurological disorders, but challenging due to the scarcity of annotated NHP brain MRI datasets, the small size

Alexander Gurung, Mirella Lapata

Generating high-quality stories spanning thousands of tokens requires competency across a variety of skills, from tracking plot and character arcs to keeping a consistent and engaging style. Due to the difficulty of sourcing labeled datasets and precise quality measurements, most work using large language models (LLMs) for long-form story generation uses com

Yohann Trivino, Vincent Richefeu, Farhang Radjai, Komlanvi Lampoh

In this paper, we present a 2D numerical model developed to simulate the dynamics of soft, deformable particles. To accommodate significant particle deformations, the particle surface is represented as a narrow shell composed of mass points that interact through elasto-plastic force laws governing their linear and angular relative displacements. Particle sha

Frank E. Curtis, Lara Zebiane

NonOpt, a C++ software package for minimizing locally Lipschitz objective functions, is presented. The software is intended primarily for minimizing objective functions that are nonconvex and/or nonsmooth. The package has implementations of two main algorithmic strategies: a gradient-sampling and a proximal-bundle method. Each algorithmic strategy can employ

Alfred A. B. Mayaki

Prior literature on two-firm two-market and two-stage extended dynamic models has introduced what Guth (2016) succinctly terms a social dilemma. A state in which conglomerate firms competing in a Bertrand duopoly consider jointly optimizing profits under a tacit self-enforcing agreement to deter market entry. This theoretical article reinterprets the social

Pranav Kumar, Fritz Körmann, Blazej Grabowski, Yuji Ikeda

The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCr$_2$H$_x$ Laves phases is investigated for $0 < x \le 6$ with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). The MLIPs are trained with configurations generated through a series of active-learning schemes. Basin-hopping Monte Carlo (BHMC) simulation

G. Leckenby, M. Trassinelli, R. J. Chen, R. S. Sidhu

The measurement of the bound-state $\beta$ decay of $^{205}\mathrm{Tl}^{81+}$ at the Experimental Storage Ring at GSI, Darmstadt, has recently been reported with substantial impact on the use of $^{205}\mathrm{Pb}$ as an early Solar System chronometer and the low-energy measurement of the solar neutrino spectrum via the LOREX project. Due to the technical ch

Terry Yue Zhuo, Junda He, Jiamou Sun, Zhenchang Xing

API misuse in code generated by large language models (LLMs) presents a serious and growing challenge in software development, as although LLMs demonstrate impressive code generation capabilities, their interactions with complex library APIs are often error-prone and can lead to software failures and vulnerabilities. In this paper, we conduct a large-scale s

Dalton H Bermudez, Wesley Culberson

Background: Current mathematical quantification methods for beam symmetry are highly sensitive to noise, especially in beam profiles with significant variation. Purpose: This study evaluates the accuracy of standard radiotherapy beam symmetry metrics and compares them to a proposed cross-correlation-based metric called the Correlative Symmetric Index (CSI),

Filippo Bonchi, Cipriano Junior Cioffo, Alessandro Di Giorgio, Elena Di Lavore

Tape diagrams provide a graphical representation for arrows of rig categories, namely categories equipped with two monoidal structures, $\oplus$ and $\otimes$, where $\otimes$ distributes over $\oplus$. However, their applicability is limited to categories where $\oplus$ is a biproduct, i.e., both a categorical product and a coproduct. In this work, we exten

Maria Pilar Garcia del Moral, Camilo las Heras, Alvaro Restuccia

We determine the role of torsion in the local and global geometrical description of M2-branes with fluxes and parabolic monodromies. The monodromy corresponds to a representation of the fundamental group of the base manifold into the parabolic subgroup of $\mbox{SL}(2,\mathbb{Z})$, the group of isotopy classes of area-preserving diffeomorphisms. These are su

Joscelyn van der Veen, Daniel F. V. James

From the nonclassicality of photon superbunching to the basic property of intensity, we characterize light with correlation and coherence functions. The correlation functions for nonstationary sources, such as short pulses, depend deterministically on the time dependent shape of the field and change the probability of the ensemble in time. We start from the

Xun Tang, Lexing Ying

We introduce a novel numerical scheme for solving the Fokker-Planck equation of discretized Dean-Kawasaki models with a functional tensor network ansatz. The Dean-Kawasaki model describes density fluctuations of interacting particle systems, and it is a highly singular stochastic partial differential equation. By performing a finite-volume discretization of

Satyapreet Singh Yadav, Nirupam Roy, Chetan Singh Thakur

Conventional frame-based cameras often struggle with limited dynamic range, leading to saturation and loss of detail when capturing scenes with significant brightness variations. Neuromorphic cameras, inspired by human retina, offer a solution by providing an inherently high dynamic range. This capability enables them to capture both bright and faint celesti

Kaibo Hu

Complexes and cohomology, traditionally central to topology, have emerged as fundamental tools across applied mathematics and the sciences. This survey explores their roles in diverse areas, from partial differential equations and continuum mechanics to reformulations of the Einstein equations and network theory. Motivated by advances in compatible and struc

Emily C. Hector, Leonardo Cella, Ryan Martin

Divide-and-conquer methods use large-sample approximations to provide frequentist guarantees when each block of data is both small enough to facilitate efficient computation and large enough to support approximately valid inferences. When the overall sample size is small or moderate, likely no suitable division of the data meets both requirements, hence the

Pei-Cheng Kuo, Roman G. Novikov

We consider the Schr\"odinger equation with a multipoint potential of the Bethe-Peierls-Thomas-Fermi type. We show that such a potential in dimension d=2 or d=3 is uniquely determined by its scattering amplitude at a fixed positive energy. Moreover, we show that there is no non-zero potential of this type with zero scattering amplitude at a fixed positive en

Jonathan Peters, Philippe Talatchian

Equilibrium Propagation (EP) is a supervised learning algorithm that trains network parameters using local neuronal activity. This is in stark contrast to backpropagation, where updating the parameters of the network requires significant data shuffling. Avoiding data movement makes EP particularly compelling as a learning framework for energy-efficient train

Uddhav Bhattarai, Rajkishan Arikapudi, Steven A. Fennimore, Frank N Martin

Manual fruit harvesting is common in agriculture, but the amount of time pickers spend on non-productive activities can make it very inefficient. Accurately identifying picking vs. non-picking activity is crucial for estimating picker efficiency and optimising labour management and harvest processes. In this study, a practical system was developed to calcula

Marcus J. Glennon, Catherine I. V. Bird, Prateek Yadav, Patrick Kleine

Setting up a psychedelic study can be a long, arduous, and kafkaesque process. This rapidly-developing field poses several unique challenges for researchers, necessitating a range of considerations that have not yet been standardised. Many of the complexities inherent to psychedelic research also challenge existing assumptions around, for example, approaches

Marie Michaelides, Mélina Mailhot, Yongkun Li

We introduce a novel forecasting model for crop yields that explicitly accounts for spatio-temporal dependence and the influence of extreme weather and climatic events. Our approach combines Bayesian Structural Time Series for modeling marginal crop yields, ensuring a more robust quantification of uncertainty given the typically short historical records. To

Atanu Bhatta, Arpit Maurya

We compute the greybody factor for scalar and photon radiations in AdS Schwarzschild black brane. We consider the linearized field equations satisfied by the minimally coupled massive scalar field and the transverse components of the Maxwell fields on the black brane background and recast them to the Heun's equations by appropriate change of variables and fi

A. Huss, L. Bonino, O. Braun-White, S. Caletti

The antenna subtraction method for NNLO QCD calculations is implemented in the NNLOJET parton-level event generator code to compute jet cross sections and related observables in electron-positron, lepton-hadron and hadron-hadron collisions. We describe the open-source NNLOJET code and its usage.

Suvankar Purkait, Tanmay Maiti, Pooja Agarwal, Suparna Sahoo

The edge structure of a gate-defined compressible quantum Hall fluids in the filling fraction range 2/3 to 1 is studied using the three reconstructed $e^2/3h$ fractional edge modes of unity filling integer quantum Hall state. We find that the individually excited partially resolved $e^2/3h$ edge modes of the bulk state equilibrate completely even at higher m

Pablo Corcho-Caballero, Yago Ascasibar, Daniel Jiménez-López

Stellar population synthesis is a crucial methodology in astrophysics, enabling the interpretation of the integrated light of galaxies and stellar clusters. By combining empirical and/or theoretical libraries of the spectral energy distribution emitted by simple stellar populations (SSPs) with models of the star formation history (SFH) and chemical evolution

Sergey Berezin, Eugene Strahov

We introduce and study a model of directed last-passage percolation in planar layered environment. This environment is represented by an array of random exponential clocks arranged in blocks, for each block the average waiting times depend only on the local coordinates within the block. The last-passage time, the total time needed to travel from the source t

Lu Li, Zhengyi Shao

Understanding our place in the universe is an eternal quest. Through the analysis of the 3D structures of 66 nearby open clusters using Gaia DR3 data, we discovered an intriguing pattern: most clusters show their elongation directions pointing at the Sun, suggesting that the Solar System might just be the universe's favorite spot, a cosmic feng shui hotspot!