November 2025 arXiv papers — page 127

Tina Behzad, Siddartha Devic, Vatsal Sharan, Aleksandra Korolova

We conduct an independent, third-party audit for bias of LinkedIn's Talent Search ranking system, focusing on potential ranking bias across two attributes: gender and race. To do so, we first construct a dataset of rankings produced by the system, collecting extensive Talent Search results across a diverse set of occupational queries. We then develop a robus

K. Z. Nanjo, J. Yazbeck, I. T. Baughman, J. B. Rundle

The 2025 M8.8 Kamchatka earthquake in the Kamchatka-Kuril subduction system provides a unique opportunity to investigate the preparatory processes of a great subduction event. Despite Kamchatka's high seismic activity, the long-term evolution of seismicity preceding major ruptures has been poorly documented. Identifying temporal patterns-such as multiyea

Inés García-Redondo, Claudia Landi, Sarah Percival, Anda Skeja

The concept of effective resistance, originally introduced in electrical circuit theory, has been extended to the setting of graphs by interpreting each edge as a resistor. In this context, the effective resistance between two vertices quantifies the total opposition to current flow when a unit current is injected at one vertex and extracted at the other. Be

Alptuğ Ulugöl, Frank Smallenburg, Laura Filion

Nearest-neighbor identification is central to the analysis of local structure in condensed matter systems. The solid-angle-based nearest-neighbor (SANN) algorithm is widely used offering a parameter-free and computationally efficient alternative to cutoff- or Voronoi-based methods. Unfortunately, however, in systems with low coordination numbers, SANN tends

Peter K. Blanchard, Edo Berger, Sebastian Gomez, Matt Nicholl

We present a large sample of 39 nebular-phase optical spectra of 25 hydrogen-poor superluminous supernovae (SLSNe-I) and jointly analyze them with previously published spectra of 12 events. We measure the properties of key emission features, namely those at 6300, 7300, and 7774 angstroms (associated with [O I], [Ca II]/[O II], and O I, respectively), and fin

Paweł Pielasa

We prove two dual recursive decompositions as a graded $\underline{\mathrm{CH}}(M)\otimes \underline{\mathrm{CH}}(N)$-module of the Chow ring $\underline{\mathrm{CH}}(M\oplus N)$ of the direct sum of matroids. We use this to obtain a decomposition of $\underline{\mathrm{CH}}(M\oplus N)$ into irreducible $\underline{\mathrm{CH}}(M) \otimes \underline{\mathrm{

Roman R. Rafikov, Nicolas P. Cimerman, Callum W. Fairbairn, Alexander J. Dittmann

Gravitational coupling between a protoplanetary disc and an embedded planet is often studied in a frame attached to a central star. This frame is non-inertial because of the stellar reflex motion, leading to indirect forces arising in the star-planet-disc system. Here we examine the impact produced by these forces on several aspects of disc-planet coupling u

Ferdinand, W. V. Jacobson-Galán, M. M. Kasliwal, Erez A. Zimmerman

X-ray observations of Type II supernovae (SNe II) probe the physics of supernova (SN) shocks and the mass-loss histories of their progenitor stars. We present multi-epoch, X-ray observations of SN II 2024ggi ($D \approx 7.2 \ \rm Mpc$) from ${\it Swift}$-XRT, ${\it Chandra}$ and ${\it XMM}$, which cover $\sim 1 - 344$ days since first light. We analyze these

Lena Komarova, Mauro Stefanon, Andres Laza-Ramos, Hiddo S. Algera

Measuring the ionizing photon production efficiency $\xi_{\mathrm{ion,0}}$ -- the ratio of ionizing photon output rate $Q_{\rm H^0}$ to UV continuum luminosity $L_{\rm UV}$ -- in galaxies at $z > 6$ is crucial for constraining their contribution to cosmic reionization. We present integrated and spatially resolved measurements of $\xi_{\mathrm{ion,0}}$ for 12

Paweł Pielasa

We study the Quot scheme of points $\mathrm{Quot}_d(\mathcal{O}_{\mathbb{A}^{n}}^{\oplus r})$. We exhibit and compute the cohomology of explicit loci in $\mathrm{Quot}_d(\mathcal{O}_{\mathbb{A}^{n}}^{\oplus r})$, whose complement has codimension diverging to infinity as $n\rightarrow \infty$. In the case $1<r<\frac{d+1}{2}$ this loci is an irreducible compon

R. Fisher, R. A. A. Bowler, R. K. Cochrane, L. E. Rowland

Reliable star formation rate (SFR) measurements are essential for understanding early galaxy evolution, yet derived values rely on several assumptions. To address this problem, we investigate the SFRs of 12 massive ($9~<~\log(M_{\star}/{\rm M}_{\odot})~<~10$) Lyman-break galaxies at $z=6.5-7.7$, drawn from the Atacama Large Millimeter/submillimeter Array (AL

E. Gatuzz, J. Sanders, A. Liu, A. Fabian

The hot gas permeating galaxy clusters-the intracluster medium (ICM)-is a key tracer of their assembly history and internal dynamics. Understanding the motion of this gas provides critical insight into processes such as mergers, turbulence, and energy dissipation in the largest gravitationally bound structures in the Universe. The Coma cluster is a nearby, m

Naixin Liang, Damiano Caprioli

Supersonic flows are ubiquitous in warm and cool media; their dissipation leads to heating, generation of nonthermal particles, and amplification of background magnetic fields. We present 2D hybrid (kinetic ions - fluid electrons) simulations of decaying shear flows across the subsonic-to-supersonic transition, finding that the canonical Kelvin-Helmholtz ins

Jonathan Oppenheim, Emanuele Panella

Theories of gravity in which the metric is fundamentally classical predict stochastic fluctuations in the gravitational field. In this article, we study the stochastic Klein-Gordon equation as a starting point to understand the phenomenology of linearised classical-quantum hybrid gravity. In particular, we describe how to compute the non-equilibrium two poin

A. Mucciarelli, P. Bonifacio, C. Lardo

We present the KOALA database, a new set of LTE, line-blanketed model atmospheres calculated with the code ATLAS9, together with the corresponding Opacity Distribution Functions and emergent fluxes. The latter were used also to calculated G-band bolometric corrections and theoretical magnitudes and colours for several photometric systems, i.e. UBVRI, 2MASS,

Aristeidis Polychronakis, Ioannis Liodakis, Anastasia Glykopoulou, Dmitry Blinov

Blazars are known for their extreme variability across the electromagnetic spectrum. Variability at very short timescales can push the boundaries between competing models offering us much needed discriminating power. This is particularly true for polarization variability that allows us to probe particle acceleration and high-energy emission models in blazars

David Trestini

In the case of nonspinning compact binary systems on quasi-elliptic orbits, I obtain the conservative map between the constants of motion (energy and angular momentum) and the fundamental (radial and azimuthal) frequencies at the fourth post-Newtonian order, including both instantaneous and tail contributions. This map is expressed in terms of an enhancement

Madyson G. Barber, Andrew W. Mann, Andrew Vanderburg, Khalid Barkaoui

The discovery of infant (< 50 Myr), close-in (<30-day period) planets is vital in understanding the formation mechanisms that lead to the distribution of mature transiting planets as discovered by Kepler. Despite several discoveries in this age bin, the sample is still too small for a robust statistical comparison to older planets. Here we report the validat

Arsenii Titov

We release FeynRules and UFO model files for the $ν$SMEFT -- the effective field theory of the Standard Model extended with right-handed neutrinos, $N_R$. These model files include operators with $N_R$ up to dimension six. In particular, we provide a UFO implementation of four-fermion operators with Majorana $N$ compatible with MadGraph5_aMC@NLO. It relies o

Sam van Leuven, Kayleigh Mathieson, Pratik Roy

We study superconformal indices of four-dimensional $SU(N)$ gauge theories with $\mathcal{N}=1,2,4$ supersymmetry. The usual representation of a gauge theory index involves multiple contour integrals and reflects the BPS spectrum at zero Yang-Mills coupling. To find an alternative, closed form expression, it is natural to attempt an evaluation of the integra

Miguel Escudero, Thomas Hambye, Chandan Hati

Many asymmetric dark matter scenarios have been proposed to date. Among them, perhaps the most motivated ones are those in which the dark matter asymmetry is induced from the baryon/lepton asymmetries via chemical equilibration without any new sources of CP violation. However, most of the models put forward along these lines have been excluded by now and/or

Isac Barranco-Llorca, David Vallés-Pérez, Susana Planelles, Vicent Quilis

While galaxy cluster masses are fundamental cosmological observables, estimates based on intra-cluster medium observations rely on hydrostatic equilibrium, introducing a systematic bias. We investigate how mergers drive the time evolution of this hydrostatic mass bias, identifying the dominant physical mechanisms and their dependence on dynamical state and m

Hossein Hatamnia, Bahram Mobasher, Sina Taamoli, Jeyhan S. Kartaltepe

We present a reconstruction of the large-scale structure using the James Webb Space Telescope's (JWST) COSMOS-Web program to trace environmentally driven galaxy evolution up to $z\sim7$. We applied a weighted kernel density estimation method to 160,000 galaxies with robust photometric redshifts. We find that stellar mass has a positive correlation with densi

Eritas Yang, Yubo Su

A widely explored pathway for hot Jupiter (HJ) formation is high-eccentricity migration driven by von Zeipel-Lidov-Kozai cycles induced by an exterior companion. However, for a distant or low-mass companion, this mechanism typically demands that the planet's initial orbit be very nearly perpendicular to that of the companion. In previous work (Yang et al. 20

Diego Herrero-Carrión, Daniele Spinoso, David Izquierdo-Villalba, Tong Su

The enigmatic Little Red Dots (LRDs) discovered by the James Webb Space Telescope (JWST) exhibit properties challenging their interpretation as common galaxies or Active Galactic Nuclei (AGN). Understanding their nature is key to placing them within our picture of early galaxy and massive black hole (MBH) evolution. To this aim, we build a realistic comparis

Miguel Crispim Romão, João Arruda Gonçalves, José Guilherme Milhano

The modification of jets by interaction with the Quark Gluon Plasma has been extensively established through the comparison of observables computed for samples of jets produced in nucleus-nucleus collisions and proton-proton collisions. The presence of vacuum-like jets, jets that experienced little interaction with the Quark Gluon Plasma, in the nucleus-nucl

Katya Leidig, Benedikt Diemer, Song Huang, Shuo Xu

The diffuse outskirts of brightest cluster galaxies (BCGs) encode valuable information about the assembly history and mass of their host dark matter halos. However, the low surface brightness of these stellar halos has historically made them difficult to observe. Recent deep imaging, particularly with Hyper Suprime-Cam (HSC), has shown that the stellar mass

Vicente Amado Olivo, Wolfgang Kerzendorf, Bangjing Lu, Joshua V. Shields

The ability to distinctly and properly collate an individual researcher's publications is crucial for ensuring appropriate recognition, guiding the allocation of research funding and informing hiring decisions. However, accurately grouping and linking a researcher's entire body of work with their individual identity is challenging because of widespread name

Jiahao Wang, Weiye Xu, Aijun Yang, Wengang Zhou

Outcome-reward reinforcement learning (RL) is a common and increasingly significant way to refine the step-by-step reasoning of multimodal large language models (MLLMs). In the multiple-choice setting - a dominant format for multimodal reasoning benchmarks - the paradigm faces a significant yet often overlooked obstacle: unfaithful trajectories that guess th

Haotong Lin, Sili Chen, Junhao Liew, Donny Y. Chen

We present Depth Anything 3 (DA3), a model that predicts spatially consistent geometry from an arbitrary number of visual inputs, with or without known camera poses. In pursuit of minimal modeling, DA3 yields two key insights: a single plain transformer (e.g., vanilla DINO encoder) is sufficient as a backbone without architectural specialization, and a singu

Sheng-Yu Wang, Aaron Hertzmann, Alexei A Efros, Richard Zhang

Data attribution for text-to-image models aims to identify the training images that most significantly influenced a generated output. Existing attribution methods involve considerable computational resources for each query, making them impractical for real-world applications. We propose a novel approach for scalable and efficient data attribution. Our key id

Aiden J. Mains, Jia-Xin Zhong, Yun Jing, Bitan Roy

In addition to topological lattice defects such as dislocations and disclinations, crystals are also accompanied by unavoidable ordinary defects, devoid of any non-trivial geometry or topology, among which vacancies, Schottky defects, substitutions, interstitials, and Frenkel pairs are the most common. In this work, we demonstrate that these ubiquitous ordin

Yesheng Liang, Haisheng Chen, Zihan Zhang, Song Han

Post-training quantization (PTQ) compresses the weights and activations of large language models (LLMs) into low-precision representations to reduce memory footprint and accelerate inference. However, the presence of outliers in weights and activations often leads to large quantization errors and severe accuracy degradation, especially in recent reasoning LL

Ezra Msolla, Ayngaran Thavanesan

We build upon previous analytical treatments of scalar perturbations in curved inflationary universes to obtain analytical templates for the primordial tensor power spectrum in models with non-zero primordial spatial curvature. These templates are derived without assuming a particular inflaton potential, within a background history consisting of an initial k

Tianzhu Ye, Li Dong, Zewen Chi, Xun Wu

Black-box distillation creates student large language models (LLMs) by learning from a proprietary teacher model's text outputs alone, without access to its internal logits or parameters. In this work, we introduce Generative Adversarial Distillation (GAD), which enables on-policy and black-box distillation. GAD frames the student LLM as a generator and trai

Dan Mao, Eun-Ah Kim

Quantum theory of geometrically frustrated systems is usually approached as a gauge theory where the local conservation law becomes the Gauss law. Here we show that it can do something fundamentally different: enforce a global conserved quantity via a non-perturbative tiling invariant, rigorously linking microscopic geometry to a new macroscopically phase-co

Marcelo Campos, Matthew Jenssen, Marcus Michelen, Florian Pfender

We give a polynomial improvement to the cycle-complete Ramsey numbers \[ r(C_{\ell},K_k) \geq k^{1+1/(\ell- 2) + \varepsilon_{\ell} + o(1)}, \] for all fixed odd $\ell > 7$ with $k \rightarrow \infty$, for some $\varepsilon_{\ell} > 0$.

Thomas Harvey, Christopher C. Lovell, Sophie Newman, Christopher J. Conselice

We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible forward-modelling of galaxy SEDs and integrates the LtU-ILI package to ensure best practices in model training and validation. In this work we demonstrate Synference by training a n

Vitor Gelsleichter Probst Curtarelli, Stephan Paul, Anderson Wedderhoff Spengler

We propose a joint estimation method for the Direction-of-Arrival (DoA) and the Noise Covariance Matrix (NCM) tailored for beamforming applications. Building upon an existing NCM framework, our approach simplifies the estimation procedure by deriving an quasi-linear solution, instead of the traditional exhaustive search. Additionally, we introduce a novel Do

Stefano De Angelis, Aidan Herderschee, Radu Roiban, Fei Teng

We investigate the fate of asymptotic simplicity in physically relevant settings of compact-object scattering. Using the stress tensor of a two-body system as a source, we compute the spacetime metric in General Relativity at finite observer distance in an asymptotic expansion. To do so, we relate the metric to the final-state graviton one-point function in

Runpeng Geng, Yanting Wang, Chenlong Yin, Minhao Cheng

Long context LLMs are vulnerable to prompt injection, where an attacker can inject an instruction in a long context to induce an LLM to generate an attacker-desired output. Existing prompt injection defenses are designed for short contexts. When extended to long-context scenarios, they have limited effectiveness. The reason is that an injected instruction co

Pascal Strauch, David Müller, Sammy Christen, Agon Serifi

Despite recent advances in robust locomotion, bipedal robots operating in the real world remain at risk of falling. While most research focuses on preventing such events, we instead concentrate on the phenomenon of falling itself. Specifically, we aim to reduce physical damage to the robot while providing users with control over a robot's end pose. To this e

Abdullah Khalid, Allyson Silva, Gebremedhin A. Dagnew, Tom Dvir

The speed of a fault-tolerant quantum computer depends in large part on the reaction time of its classical electronics, that is, the total time required by decoders and controllers to determine the outcome of a logical measurement and execute subsequent conditional logical operations. Despite its importance, the reaction time and its impact on the design of

Dily Duan Yi Ong, David Yallup, Will Handley

The DESI Collaboration reports a significant preference for a dynamic dark energy model ($w_0w_a$CDM) over the cosmological constant ($\Lambda$CDM) when their data are combined with other frontier cosmological probes. We present a direct Bayesian model comparison using nested sampling to compute the Bayesian evidence, revealing a contrasting conclusion: for

Ritesh Goenka, Jonathan Hermon, Dominik Schmid

We introduce a multi-colour multi-urn generalisation of the Bernoulli-Laplace urn model, consisting of $d$ urns, $m$ colours, and $dmn$ balls, with $dn$ balls of each colour and $mn$ balls in each urn. At each step, one ball is drawn uniformly at random from each urn, and the chosen balls are redistributed among the urns based on a permutation drawn from a d

Aleksandr Razin, Danil Kazantsev, Ilya Makarov

Diffusion models struggle to scale beyond their training resolutions, as direct high-resolution sampling is slow and costly, while post-hoc image super-resolution (ISR) introduces artifacts and additional latency by operating after decoding. We present the Latent Upscaler Adapter (LUA), a lightweight module that performs super-resolution directly on the gene

Jiang Liu, Jialian Wu, Xiaodong Yu, Yusheng Su

Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks, yet the majority of high-performing models remain closed-source or partially open, limiting transparency and reproducibility. In this work, we introduce Instella, a family of fully open three billion parameter language models trained entirely on openly availab

Edward Kim, Devan Shanker, Varun Bharadwaj, Hongbeen Park

Simulation-based testing has become a crucial complement to road testing for ensuring the safety of cyber physical systems (CPS). As a result, significant research efforts have been directed toward identifying failure scenarios within simulation environments. However, a critical question remains. Are the AV failure scenarios discovered in simulation reproduc

Ilyas Fatkhullin, Niao He, Guanghui Lan, Florian Wolf

Constrained non-convex optimization is fundamentally challenging, as global solutions are generally intractable and constraint qualifications may not hold. However, in many applications, including safe policy optimization in control and reinforcement learning, such problems possess hidden convexity, meaning they can be reformulated as convex programs via a n

Hassan H. Abdallah, Yigal Kamel

We show that the 2-local splitting of spin$^c$ bordism by Anderson--Brown--Peterson and Stong refines to a $C_2$-equivariant map in the category of spectra with $C_2$-action from Real spin bordism to a sum of (higher) connective covers of $\mathrm{ku}_{\mathbb{R}}$ and suspensions of mod 2 Eilenberg--Mac Lane spectra. We use this to deduce a corresponding 2-

I. Khayr, N. Somun, S. Hameed, Z. Van Fossan

The interplay of electronic and structural degrees of freedom is a prominent feature of many quantum materials and of particular interest in systems with strong ferroelectric fluctuations, such as SrTiO$_3$ (STO) and KTaO$_3$ (KTO). Both materials are close to a ferroelectric transition, but despite six decades of extensive research, pivotal questions regard

Rajiv Sambharya, Nikolai Matni, George Pappas

We introduce a verification framework to exactly verify the worst-case performance of sequential convex programming (SCP) algorithms for parametric non-convex optimization. The verification problem is formulated as an optimization problem that maximizes a performance metric (e.g., the suboptimality after a given number of iterations) over parameters constrai

Haizhou Shi, Ye Liu, Bo Pang, Zeyu Leo Liu

Large Language Models (LLMs) have demonstrated remarkable reasoning abilities, yet existing test-time frameworks often rely on coarse self-verification and self-correction, limiting their effectiveness on complex tasks. In this paper, we propose Socratic Self-Refine (SSR), a novel framework for fine-grained evaluation and precise refinement of LLM reasoning.

Irene Abril-Cabezas, Frank J. Qu, Joshua Kim, Mathew S. Madhavacheril

We present a cosmic microwave background (CMB) lensing power spectrum analysis using daytime data (11am-11pm UTC) gathered by the Atacama Cosmology Telescope (ACT) over the period 2017-2022 (ACT Data Release 6). This dataset is challenging to analyze because the Sun heats and deforms the telescope mirror, complicating the characterization of the telescope. W

Benjamin L. Badger, Matthew Neligeorge

Language prediction is constrained by informational entropy intrinsic to language, such that there exists a limit to how accurate any language model can become and equivalently a lower bound to language compression. The most efficient language compression algorithms today are causal (next token prediction) large language models, but the use of these models t

Zhiyu Lu, Théo Simon

We study the $(w_0, \, w_a)$ parametrization of the dark energy (DE) equation of state, with and without the effective field theory of dark energy (EFTofDE) framework to describe the DE perturbations, parametrized here by the braiding parameter $\alpha_B$ and the running of the Planck mass $\alpha_M$. We combine the EFTofLSS full-shape analysis of the power

Shruti Singh Baghel, Yash Pratap Singh Rathore, Sushovan Jena, Anurag Pradhan

Large Vision-Language Models (VLMs) excel at understanding and generating video descriptions but their high memory, computation, and deployment demands hinder practical use particularly for blind and low-vision (BLV) users who depend on detailed, context-aware descriptions. To study the effect of model size on accessibility-focused description quality, we ev

Fani Xerakia

The Diederich-Forn{\ae}ss worm domain, an important example of a smoothly bounded pseudoconvex domain without a Stein neighborhood basis, provides key counterexamples in the theory of Several Complex Variables. In this paper, we examine its automorphism group and observe that its boundary is locally spherical everywhere except at the exceptional locus and th

Ameya Chavda, Daniel McLoughlin, Sebastian Mizera, John Staunton

We set up a bootstrap problem for renormalization. Working in the massless four-dimensional O$(N)$ model and the $\lambda \phi^4$ theory, we prove that unitarity leads to all-loop recursion relations between coefficients of scattering amplitudes with different multiplicities. These turn out to be equivalent to the identities imposed by renormalization of the

Tânia Paulista

The general ideal of this paper is to answer the following question: given a numerical property of commuting graphs, a class of semigroups $\mathcal{C}$ and $n\in\mathbb{N}$, is it possible to find a semigroup in $\mathcal{C}$ such that the chosen property is equal to $n$? We study this question for the classes of Clifford semigroups, inverse semigroups and

Alagappan Ramanathan, Eunju Kang, Dongsu Han, Sangeetha Abdu Jyothi

Internet measurement research faces an accessibility crisis: complex analyses require custom integration of multiple specialized tools that demands specialized domain expertise. When network disruptions occur, operators need rapid diagnostic workflows spanning infrastructure mapping, routing analysis, and dependency modeling. However, developing these workfl

Youssef Djellouli, Pierre Yves Gaudreau Lamarre

We study the occurrence of number rigidity and deletion singularity in a class of point processes that we call {\it projected perturbed lattices}. These are generalizations of processes of the form $\Pi=\{\|z\|^\alpha+g_z\}_{z\in\mathbb{Z}^d}$ where $(g_z)_{z\in\mathbb{Z}^d}$ are jointly Gaussian, $\alpha>0$, $d\in\mathbb{N}$, and $\|\cdot\|$ is a norm. We d

Praneet Nandan, Beatriz Pascual-Escudero, Diego Rojas La Luz

Multistationarity, underlies biochemical switching and cellular decision-making. We study how multistationarity in the sequential n-site phosphorylation-dephosphorylation cycle is affected when only some species are open, meaning allowed to exchange with the environment (so-called semi-open networks). Working under mass action kinetics, we obtain two complem

Christopher Bouchard

Let $\mathcal{A}$ be a union-closed family of sets with universe $\bigcup_{A \in \mathcal{A}}A = [n] = \{1,\cdots,n\}$ and length $\ell$. We prove that $|\mathcal{A}| \leq \sum_{i=0}^{\ell} \binom{n}{i}$, with equality if and only if $\mathcal{A} = \bigcup_{i=0}^{\ell}\binom{[n]}{n-i}$. Additionally, by showing that $|\mathcal{A}| \leq \frac{\ell^p-1}{\ell-1

Trung Hoa Dinh, Nhat A. Nghiem

The development of quantum computation has resulted in many quantum algorithms for a wide array of tasks. Recently, there is a growing interest in using quantum computing techniques to estimate or compute quantum information-theoretic quantities such as Renyi entropy, Von Neumann entropy, matrix means, etc. Motivated by these results, we present quantum algo

Thomas Hartke, Botond Oreg, Chunhan Feng, Carter Turnbaugh

The tension between fermion pairing and magnetism affects numerous strongly correlated electron systems, from high-temperature cuprates to twisted bilayer graphene. Exotic forms of fermion pairing and superfluidity are predicted when attraction between fermions competes with spin doping. Here, we follow the evolution of fermion pairing and charge and spin or

Zack Dewis, Yimin Zhu, Zhengsen Xu, Mabel Heffring

Although Sentinel-2 based land use and land cover (LULC) classification is critical for various environmental monitoring applications, it is a very difficult task due to some key data challenges (e.g., spatial heterogeneity, context information, signature ambiguity). This paper presents a novel Multitask Glocal OBIA-Mamba (MSOM) for enhanced Sentinel-2 class

Ioana A. Stelea, Snezana Stanimirovic, Nickolas M. Pingel, Hongxing Chen

We present the first localized detections of the cold neutral medium (CNM) in IC10, offering a rare view of dense atomic gas in a low-metallicity (0.27 solar metallicity) dwarf galaxy. As a low-metallicity starburst, IC10's interstellar medium conditions could reflect small-scale physical conditions that mirror those of early galaxies, providing a unique win

Brianne Weaver, Brigg Trendler, Chris Groendyke, Brian Hartman

Accurate mortality modeling is central to actuarial science and public health, especially as mental health emerges as a significant factor in population outcomes. This paper develops and applies a Bayesian hierarchical model to analyze U.S. county-level mortality and suicide rates from 2010 to 2023. Applying a conditional autoregressive (CAR) structure to ea

Fatima Abbasi, Richard Nally, Washington Taylor

We carry out a complete analysis of the toric elliptic and genus-one fibrations of all 474 million reflexive polytopes in the Kreuzer-Skarke database. Earlier work with Huang showed that all but 29,223 of these polytopes have such a fibration. We identify 2,264,992,252 distinct fibrations, and determine the fiber and base structure in each case; after accoun

Maninder Kaur, Nicolas T. Sandino, Jason P. Terry, Mahdi Ghafariasl

Two-dimensional (2D) in-plane heterostructures including compositionally graded alloys and lateral heterostructures with defined interfaces display rich optoelectronic properties and offer versatile platforms to explore one-dimensional interface physics and many-body interaction effects. Graded \(\mathrm{Mo}_x\mathrm{W}_{1-x}\mathrm{S}_2\) alloys show smooth

Raghav Adhikari, Sachet Khatiwada, Suman Poudel

Post-disaster situations pose unique navigation challenges. One of those challenges is the unstructured nature of the environment, which makes it hard to layout paths for rescue vehicles. We propose the use of Uncrewed Aerial Vehicle (UAV) in such scenario to perform reconnaissance across the environment. To accomplish this, we propose an optimization-based

Yen Nhi Truong Vu, Dan Guo, Sripad Joshi, Harshit Kumar

Digital Breast Tomosynthesis (DBT) enhances finding visibility for breast cancer detection by providing volumetric information that reduces the impact of overlapping tissues; however, limited annotated data has constrained the development of deep learning models for DBT. To address data scarcity, existing methods attempt to reuse 2D full-field digital mammog

Ahmed Gamal Eldin

Current AI systems excel at pattern recognition but fail at causal reasoning. We argue this is not an engineering limitation but reveals something fundamental about the nature of understanding itself. We propose that causal cognition requires a specific physical architecture: stochastic, coupled oscillators with whole-system coordination. To test this, we an

Alan Sherry, Saptarshi Mandal, Sthitadhi Roy

The projected ensemble -- an ensemble of pure states on a subsystem conditioned on projective measurement outcomes on its complement -- provides a finer probe of ergodicity and information structure than the reduced density matrix of the subsystem in bipartite quantum states. This framework can be generalised to partial projected ensembles in tripartite sett

Jiseong Kim, Kunjakanan Nath

Let $\{\lambda_f(n)\}_{n \geq 1}$ be the normalized Hecke eigenvalues of a given holomorphic cusp form $f$ of even weight $k$. We show under the assumption of the existence of Littlewood's type zero free region for $L(s, f, \chi)$, where $\chi$ is a Dirichlet character modulo $q$, that if $X^{2/3+\varepsilon} \ll H \ll X^{1-\varepsilon}$ with $\varepsilon>0$

Radosław Miernik, Marek Szykuła, Jakub Kowalski, Jakub Cieśluk

We propose a new General Game Playing (GGP) system called Regular Games (RG). The main goal of RG is to be both computationally efficient and convenient for game design. The system consists of several languages. The core component is a low-level language that defines the rules by a finite automaton. It is minimal with only a few mechanisms, which makes it ea

Allan Flower, Richard Mycroft

This paper presents two new results on the theory of maximal left-compressed intersecting families (MLCIFs). First, we answer a question raised by Barber by showing that the number of $k$-uniform MLCIFs on a ground set of size $n$ grows as a doubly-exponential function of $k$, which we identify up to a log factor in the exponent. Among these MLCIFs we identi

Bavana Durgapraveen, Sornaraj Sivasankaran, Abhinand Balachandran, Sriram Rajkumar

The rapid expansion of asynchronous remote care has intensified provider workload, creating demand for AI systems that can assist clinicians in managing patient queries more efficiently. The MEDIQA-WV 2025 shared task addresses this challenge by focusing on generating free-text responses to wound care queries paired with images. In this work, we present two

Miles Wang-Henderson, Benjamin Kaufman, Edward Williams, Ryan Pederson

Batched synthesis and testing of molecular designs is the key bottleneck of drug development. There has been great interest in leveraging biomolecular foundation models as surrogates to accelerate this process. In this work, we show how to obtain scalable probabilistic surrogates of binding affinity for use in Batch Bayesian Optimization (Batch BO). This dem

Agustín Lantero-Barreda, Carlos Centeno-Lorca, Bradley J. Kavanagh, Núria Castello-Mor

While Dark Matter (DM) is typically assumed to interact only very weakly with the particles of the Standard Model, many direct detection experiments are currently exploring regions of parameter space where DM can have a large scattering cross section. In this scenario, DM may scatter in the atmosphere and Earth before reaching the detector, leading to a dist

Sierra Cantway

Measurements of jet substructure observables in heavy-ion (HI) collisions provide powerful constraints on the microscopic mechanisms of interactions between energetic partons and the quark--gluon plasma (QGP). Although there has been remarkable progress in measuring inclusive jet substructure, a complete understanding of identified particle production inside

Valeria Olivares, Yuanyuan Su, Pasquale Temi, Ryan Eskenasy

Warm ionized gas is ubiquitous at the centers of X-ray bright elliptical galaxies. While it is believed to play a key role in the feeding and feedback processes of supermassive black holes, its origins remain under debate. Existing studies have primarily focused on the morphology and kinematics of warm ionized gas. This work aims to provide a new perspective

Omid Mirzaeedodangeh, Eliot Shekhtman, Nikolai Matni, Lars Lindemann

Safe planning of an autonomous agent in interactive environments -- such as the control of a self-driving vehicle among pedestrians -- poses a major challenge as the behavior of the environment is unknown and reactive to the behavior of the autonomous agent. This coupling gives rise to interaction-driven distribution shifts where the autonomous agent's contr

Raman Ebrahimi, Sean Fuhrman, Kendrick Nguyen, Harini Gurusankar

The WikiRace game, where players navigate between Wikipedia articles using only hyperlinks, serves as a compelling benchmark for goal-directed search in complex information networks. This paper presents a systematic evaluation of navigation strategies for this task, comparing agents guided by graph-theoretic structure (betweenness centrality), semantic meani

Mariana Navarro, Andrés González Lorente, Pablo V. Parellada, Carlos Pascual-García

Finite-size general security proofs for quantum key distribution based on R\'enyi entropies have recently been introduced. These approaches are more flexible and provide tighter bounds on the secret key rate than traditional formulations based on the von Neumann entropy. However, deploying them requires minimizing the conditional R\'enyi entropy, a difficult

Abhinand Balachandran, Bavana Durgapraveen, Gowsikkan Sikkan Sudhagar, Vidhya Varshany J S

The accurate extraction of medical orders from doctor-patient conversations is a critical task for reducing clinical documentation burdens and ensuring patient safety. This paper details our team submission to the MEDIQA-OE-2025 Shared Task. We investigate the performance of MedGemma, a new domain-specific open-source language model, for structured order ext

Joaquin Sureda, Shaun T. Brown, Azadeh Fattahi, Thales Gutcke

We use the extremely high-resolution ($m_{\rm bary}=4\rm{M}_\odot$) LYRA cosmological galaxy formation simulations of six dwarf galaxies with $M_{\rm 200c}\sim10^9\rm{M}_\odot$ at $z=0$ to investigate their stellar assembly histories. Based on the age of stars in these galaxies at $z=0$, $40-100\%$ of their stellar mass was formed by the time of reionization

Rodrigo Sasse, Rubens Costa, Adriel G. B Mocellin, Carlos H. Coimbra Araújo

The detection of high-energy astrophysical multimessengers establishes a connection between ultra-high-energy cosmic rays (UHECRs) and powerful cosmic accelerators. Interactions of UHECRs with radiation fields and interstellar matter generate very-high-energy (VHE) gamma rays and neutrinos, making them key components in the multimessenger framework. This stu

Tianhui Han, Shashwat Singh, Sarvesh Patil, Zeynep Temel

Origami-inspired mechanisms can transform flat sheets into functional three-dimensional dynamic structures that are lightweight, compact, and capable of complex motion. These properties make origami increasingly valuable in robotic and deployable systems. However, accurately simulating their folding behavior and interactions with the environment remains chal

Sören Arlt, Xuemei Gu, Mario Krenn

Artificial intelligence (AI) is used in numerous fields of science, yet the initial research questions and targets are still almost always provided by human researchers. AI-generated creative ideas in science are rare and often vague, so that it remains a human task to execute them. Automating idea generation and implementation in one coherent system would s

Chi Hin Chan, Magdalena Czubak, Padi Fuster Aguilera

In this paper we derive four new candidates for an intrinsic viscosity operator on an ellipsoid by using the heuristic of the thin shell limit along the scaling direction of the ellipsoid. We show that the general method of the thin shell limit through the asymptotic expansion depends on the averaging method used. We consider both the homogeneous Navier and

M. Haluk Seçuk, Özgür Delice

In this article, the behavior of a straight cosmic string is studied for the linearized version of Horndeski theory in cases where the scalar field is massless or massive. Several physical properties of such solutions are discussed in detail regarding the effects of the scalar field of this theory. The mass of the scalar field induces a screening effect such

Vishal Thenuwara, Nisansa de Silva

Fine-grained sentiment analysis faces ongoing challenges in Aspect Sentiment Triple Extraction (ASTE), particularly in accurately capturing the relationships between aspects, opinions, and sentiment polarities. While researchers have made progress using BERT and Graph Neural Networks, the full potential of advanced language models in understanding complex la

Yuval Shapira, Dana Drachsler-Cohen

Few-pixel attacks mislead a classifier by modifying a few pixels of an image. Their perturbation space is an $\ell_0$-ball, which is not convex, unlike $\ell_p$-balls for $p\geq1$. However, existing local robustness verifiers typically scale by relying on linear bound propagation, which captures convex perturbation spaces. We show that the convex hull of an

Sanchit Sinha, Guangzhi Xiong, Zhenghao He, Aidong Zhang

Modern vision-language models (VLMs) deliver impressive predictive accuracy yet offer little insight into 'why' a decision is reached, frequently hallucinating facts, particularly when encountering out-of-distribution data. Neurosymbolic frameworks address this by pairing black-box perception with interpretable symbolic reasoning, but current methods extract

Fengsheng Lin, Shengyi Yan, Trac Duy Tran

We present a semi-unified sparse dictionary learning framework that bridges the gap between classical sparse models and modern deep architectures. Specifically, the method integrates strict Top-$K$ LISTA and its convex FISTA-based variant (LISTAConv) into the discriminative LC-KSVD2 model, enabling co-evolution between the sparse encoder and the dictionary u

Francesco Gucci†, Andrea Iudica†, Andres Valladares Y Tacchi†, Andrea Schirato

Ultrafast chiro-optical spectroscopy provides unique access to the structural dynamics of molecules, spin-valley relaxation in semiconductors, and the non-equilibrium optical response of chiral nanophotonic systems. Yet, because chiral signals are intrinsically weak and time-resolved spectroscopy probes small photoinduced changes, transient chiro-optical res

Garapati Keerthana, Manik Gupta

Personalized decision systems in healthcare and behavioral support often rely on static rule-based or engagement-maximizing heuristics that overlook users' emotional context and ethical constraints. Such approaches risk recommending insensitive or unsafe interventions, especially in domains involving serious mental illness, substance use disorders, or depres

Mohammadsina Almasi, Hadis Anahideh

Equitably allocating limited resources in high-stakes domains-such as education, employment, and healthcare-requires balancing short-term utility with long-term impact, while accounting for delayed outcomes, hidden heterogeneity, and ethical constraints. However, most learning-based allocation frameworks either assume immediate feedback or ignore the complex