arXiv papers from April 2025

Peter Yichen Chen, Pingchuan Ma, Niklas Hagemann, John Romanishin

The development of novel autonomous underwater gliders has been hindered by limited shape diversity, primarily due to the reliance on traditional design tools that depend heavily on manual trial and error. Building an automated design framework is challenging due to the complexities of representing glider shapes and the high computational costs associated wi

Fatih Selim Aktas, Christian Kroer

We study the convergence properties of the 'greedy' Frank-Wolfe algorithm with a unit step size, for a convex maximization problem over a compact set. We assume the function satisfies smoothness and strong convexity. These assumptions together with the Kurdyka-{\L}ojasiewicz (KL) property, allow us to derive global asymptotic convergence for the sequence gen

Ankit Amrutkar, Björn Kampa, Volkmar Schulz, Johannes Stegmaier

Computer-generated holography (CGH) enables applications in holographic augmented reality (AR), 3D displays, systems neuroscience, and optical trapping. The fundamental challenge in CGH is solving the inverse problem of phase retrieval from intensity measurements. Physics-inspired neural networks (PINNs), especially Gerchberg-Saxton-based PINNs (GS-PINNs), h

Ivan R. Kennedy, John Runcie, Angus N. Crossan, Ray Ritchie

Why do atmospheric carbon dioxide levels rise and fall seasonally measured on Mauna Loa? This study explores the thermal acid-calcification (TAC) hypothesis, suggesting that seasonal temperature shifts in surface seawater trigger acid pH-driven CO2 emissions caused by calcification. Using oceanographic data, we modeled how temperature affects dissolved inorg

Jeffrey Lim, Po T. Wang, Won Joon Sohn, Derrick Lin

Invasive brain-computer interface (BCI) technology has demonstrated the possibility of restoring brain-controlled walking in paraplegic spinal cord injury patients. However, current implementations of BCI-controlled walking still have significant drawbacks. In particular, prior systems are unidirectional and lack sensory feedback for insensate patients, have

Jiajun Liu, Ke Zhu, Shu Yang, Xiaofei Wang

Hybrid controlled trials (HCTs), which augment randomized controlled trials (RCTs) with external controls (ECs), are increasingly receiving attention as a way to address limited power, slow accrual, and ethical concerns in clinical research. However, borrowing from ECs raises critical statistical challenges in estimation and inference, especially for binary

Xuwei Yang, Fatemeh Tavakoli, David B. Emerson, Anastasis Kratsios

Most industry-standard generative AIs and feature encoders are proprietary, offering only black-box access: their outputs are observable, but their internal parameters and architectures remain hidden from the end-user. This black-box access is especially limiting when constructing mixture-of-expert type ensemble models since the user cannot optimize each pro

Cole Gigliotti, Elina Robeva

In this paper we study the space of second- and third-order moment tensors of random vectors which satisfy a Linear Non-Gaussian Acyclic Model (LiNGAM). In such a causal model each entry $X_i$ of the random vector $X$ corresponds to a vertex $i$ of a directed acyclic graph $G$ and can be expressed as a linear combination of its direct causes $\{X_j: j\to i\}

Thomas M. Sangy, Tibério de Paula Netto, Ilya L. Shapiro

We report on the calculation of the total derivative $\cx R$ term in the divergence of vacuum effective action for the nonminimal vector field operator in a curved space background. This term led to an interesting discussions in the literature, in particular because it defines the local part of anomaly-induced effective action in conformal quantum gravity an

Tianyu Qiu, Eric Ouano, Fernando Palafox, Christian Ellis

While game-theoretic planning frameworks are effective at modeling multi-agent interactions, they require solving large optimization problems where the number of variables increases with the number of agents, resulting in long computation times that limit their use in large-scale, real-time systems. To address this issue, we propose 1) PSN Game-a learning-ba

Shaokun Zhang, Ming Yin, Jieyu Zhang, Jiale Liu

Failure attribution in LLM multi-agent systems-identifying the agent and step responsible for task failures-provides crucial clues for systems debugging but remains underexplored and labor-intensive. In this paper, we propose and formulate a new research area: automated failure attribution for LLM multi-agent systems. To support this initiative, we introduce

Vladan Gecin, Mihailo Čubrović

We study the hydrodynamic response of the AdS electron star in the vector sector, and compute the correlation functions and the transverse conductivity of the dual field theory. The system exhibits hydrodynamic behavior at low temperatures and near the critical temperature where the electron star undergoes the phase transition to the RN black hole. However,

Suk Ki Lee, Hyunwoong Ko

Dynamic manufacturing processes exhibit complex characteristics defined by time-varying parameters, nonlinear behaviors, and uncertainties. These characteristics require sophisticated in-situ monitoring techniques utilizing multimodal sensor data and adaptive control systems that can respond to real-time feedback while maintaining product quality. Recently,

Kelsey Allen, Carl Doersch, Guangyao Zhou, Mohammed Suhail

A current limitation of video generative video models is that they generate plausible looking frames, but poor motion -- an issue that is not well captured by FVD and other popular methods for evaluating generated videos. Here we go beyond FVD by developing a metric which better measures plausible object interactions and motion. Our novel approach is based o

Y. Myrzakulov, Alnadhief H. A. Alfedeel, M. Koussour, S. Muminov

In this letter, we investigate cosmology within the framework of modified $f(Q, L_m)$ gravity using the non-linear model $f(Q, L_m) = -Q + \alpha L_m^n + \beta$, where $\alpha$, $\beta$, and $n$ are free parameters. The modified Friedmann equations are derived for a matter-dominated universe, and an analytical solution is obtained. Using Hubble, Pantheon+, a

Roman J. Georgio, Caelum Forder, Suman Deb, Andri Rahimov

Coral Protocol is an open and decentralized collaboration infrastructure that enables communication, coordination, trust and payments for The Internet of Agents. It addresses the growing need for interoperability in a world where organizations are deploying multiple specialized AI agents that must work together across domains and vendors. As a foundational p

Barnabás Deme

There are several astrophysical configurations where one is interested only in the long-term dynamical evolution. Although the first-order version of this approximation is usually sufficient in applications, second-order corrections may be relevant, too. Here we use the Hamiltonian formalism to show how such higher-order terms lead to the long-term evolution

David Kühnemann, Adam Polak, Alon Rosen

In the $k$-Orthogonal Vectors ($k$-OV) problem we are given $k$ sets, each containing $n$ binary vectors of dimension $d=n^{o(1)}$, and our goal is to pick one vector from each set so that at each coordinate at least one vector has a zero. It is a central problem in fine-grained complexity, conjectured to require $n^{k-o(1)}$ time in the worst case. We propo

Cole Wittbrodt

Search and matching increasingly takes place on online platforms. These platforms have elements of centralized and decentralized matching; platforms can alter the search process for its users, but are unable to eliminate search frictions entirely. I study a model where platforms can change the distribution of potential partners that an agent searches over an

Sumit Verma, Pritam Prasun, Arpit Jaiswal, Pritish Kumar

As AI systems become embedded in real-world applications, ensuring they meet ethical standards is crucial. While existing AI ethics frameworks emphasize fairness, transparency, and accountability, they often lack actionable evaluation methods. This paper introduces a systematic approach using the Responsible AI Labs (RAIL) framework, which includes eight mea

Dorothea-Enrica von Criegern, Gabriele Grillo, Dario Monticelli

We establish conditions for nonexistence of global solutions for a class of quasilinear parabolic problems with a potential on complete, non-compact Riemannian manifolds, including the Porous Medium Equation and the p-Laplacian with a potential term. Our results reveal the interplay between the manifold's geometry, the power nonlinearity, and the potential's

Kathie Cameron, Chính T. Hoàng, Taite LaGrange

Given a family F of graphs, a graph G is F-free if it does not contain any graph in F as an induced subgraph. The problem of determining the complexity of colouring (claw, 4K1)- free graphs is a well-known open problem. In this paper we solve the colouring problem for a subclass of (claw, 4K1)-free graphs. We design a polynomial-time algorithm to colour (cla

Yasin Findik, Christopher Coco, Reza Azadeh

Assistive exoskeletons have shown great potential in enhancing mobility for individuals with motor impairments, yet their effectiveness relies on precise parameter tuning for personalized assistance. In this study, we investigate the potential of offline reinforcement learning for optimizing effort thresholds in upper-limb assistive exoskeletons, aiming to r

Ameya Salvi, Mark Brudnak, Jonathon M. Smereka, Matthias Schmid

Skid-steered wheel mobile robots (SSWMRs) are characterized by the unique domination of the tire-terrain skidding for the robot to move. The lack of reliable friction models cascade into unreliable motion models, especially the reduced ordered variants used for state estimation and robot control. Ensemble modeling is an emerging research direction where the

Peter R. Young, Andrew R. Inglis, Graham S. Kerr, Therese A. Kucera

The first simultaneous observations of the Fe XVIII 974.86 {\AA} and Fe XX 721.56 {\AA} forbidden lines from the Spectral Imaging of the Coronal Environment (SPICE) spectrograph on Solar Orbiter are presented. The lines were observed from the post-flare loops of an M2.5 class solar flare that peaked at 23:49 UT on 2024 March 23. The Fe XX/Fe XVIII ratio is u

Dongzhou Huang, Guodong Pang, Izabella Stuhl, Yuri Suhov

We introduce and study some queueing models with random resetting, including Markovian and non--Markovian models. The Markovian models include M/M/$\infty$, M/M/r and M/M/1+M queues with random resetting, in which a continuous-time Markov chain is formulated, with transitions including a resetting to state zero in addition to arrivals and services. We explic

Aleksandar Aksentijević, Suzana Aleksić, Stevan Pilipović

We discuss some structural properties of finitely generated shift-invariant (FGSI) spaces and subspaces of Sobolev spaces, particularly those related to convolution and the product within these spaces. We find shift-invariant solutions in FGSI spaces for a class of differential-difference equations with constant coefficients. Additionally, we analyze the Fou

Eloy Geenjaar, Vince Calhoun

Mental and cognitive representations are believed to reside on low-dimensional, non-linear manifolds embedded within high-dimensional brain activity. Uncovering these manifolds is key to understanding individual differences in brain function, yet most existing machine learning methods either rely on population-level spatial alignment or assume data that is t

Aditya Karan, Nicholas Vincent, Karrie Karahalios, Hari Sundaram

Given that data-dependent algorithmic systems have become impactful in more domains of life, the need for individuals to promote their own interests and hold algorithms accountable has grown. To have meaningful influence, individuals must band together to engage in collective action. Groups that engage in such algorithmic collective action are likely to vary

Bao-An Li, Xavier Grundler, Wen-Jie Xie, Nai-Bo Zhang

Future high-precision X-ray and gravitational-wave observations of neutron stars (NSs) are expected to constrain NS radii with uncertainties as small as $\sigma \simeq 0.1$~km. Such unprecedented precision offers a unique opportunity to extract new information about the nature and equation of state (EOS) of supradense matter in NS cores. Using mock radius da

Karan Kakroo, Hamid Sadat

This study conducts a high-fidelity two-way coupled fluid-structure interaction simulations, focusing on a novel perforated elastic vortex generator that is wall-mounted in an open channel with an incoming flow. The response of a perforated elastic vortex generator is investigated across a wide range of dimensionless parameters including dimensionless rigidi

Mohammad Rahbar, Christopher J. Stein

We introduce a unified statistical framework for quantifying system-environment coupling by treating the interaction energy $V_\mathcal{SE}$ as a stochastic variable. Using a reference-particle decomposition, we derive exact, closed-form expressions for the mean and variance of $V_\mathcal{SE}$ in terms of the single-particle density and up to four-body corr

Yuyan Ge, Kwan Ho Ryan Chan, Pablo Messina, René Vidal

The development of AI-based methods to analyze radiology reports could lead to significant advances in medical diagnosis, from improving diagnostic accuracy to enhancing efficiency and reducing workload. However, the lack of interpretability of AI-based methods could hinder their adoption in clinical settings. In this paper, we propose an interpretable-by-de

Hans Peter, Anders Søgaard

Sparse autoencoders (SAEs) \citep{bricken2023monosemanticity,gao2024scalingevaluatingsparseautoencoders} rely on dictionary learning to extract interpretable features from neural networks at scale in an unsupervised manner, with applications to representation engineering and information retrieval. SAEs are, however, computationally expensive \citep{lieberum2

Houda Belhad, Asmae Bourbia, Salma Boughanja

Chronic diseases, such as cardiovascular disease, diabetes, chronic kidney disease, and thyroid disorders, are the leading causes of premature mortality worldwide. Early detection and intervention are crucial for improving patient outcomes, yet traditional diagnostic methods often fail due to the complex nature of these conditions. This study explores the ap

Mohammad Rahbar, Christopher J. Stein

In open systems with strong coupling, the interaction energy between the system and the environment is significant, so thermodynamic quantities cannot be reliably obtained by traditional statistical mechanics methods. The Hamiltonian of mean force $\mathcal{H}^{*}_{\beta}$ offers an in principle accurate theoretical basis by explicitly accounting for the int

Richard E. Zeebe, Ilja J. Kocken

State-of-the-art long-term solar system integrations include several second order effects such as the Sun's quadrupole moment J2 and a contribution from asteroids (plus the Moon and general relativity). We recently showed that including 10 asteroids and a reduced J2 in our astronomical solutions provides the best match with geologic data to -58 Myr. However,

Rafael C. Pinto, Anderson R. Tavares

Proto-objects - image regions that share common visual properties - offer a promising alternative to traditional attention mechanisms based on rectangular-shaped image patches in neural networks. Although previous work demonstrated that evolving a patch-based hard-attention module alongside a controller network could achieve state-of-the-art performance in v

Elena Bortolato, Francesco Bertolino, Monica Musio, Laura Ventura

The aim of this paper is to discuss both higher-order asymptotic expansions and skewed approximations for the Bayesian Discrepancy Measure for testing precise statistical hypotheses. In particular, we derive results on third-order asymptotic approximations and skewed approximations for univariate posterior distributions, also in the presence of nuisance para

A. U. Abeysekara, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez

TeV halos are extended very-high-energy (VHE; 0.1-100 TeV) gamma-ray emission around middle-aged pulsars. So far they have only been found around isolated pulsars, but it has been suggested that they may also be powered by millisecond pulsars (MSPs). We searched for VHE gamma-ray emission from MSPs reported by radio and GeV gamma-ray observatories in 2565 da

Christiana Erba, Richard Ignace, Faith Simmons, Ben Davies

WR 31a (Hen 3-519) is likely a post-luminous blue variable (LBV) star that is evolving to become a classical Wolf-Rayet star. Multicolor (UBVR) photopolarimetric observations of WR 31a were obtained over nine nights in early 2007. The linear polarization data of WR 31a trace a "loop" structure in a Stokes Q-U diagram, which is similar in all four passbands.

Nathan Daly, Thomas Krauss, Julia Shapiro

The Quadratic Assignment Problem (QAP) is an NP-hard fundamental combinatorial optimization problem introduced by Koopmans and Beckmann in 1957. The problem is to assign $n$ facilities to $n$ different locations with the goal of minimizing the cost of the total distances between facilities weighted by the corresponding flows. We initiate the study of using R

Joel Daniel Andersson, Amir Yehudayoff

We study a discrete convolution streaming problem. An input arrives as a stream of numbers $z = (z_0,z_1,z_2,\ldots)$, and at time $t$ our goal is to output $(Tz)_t$ where $T$ is a lower-triangular Toeplitz matrix. We focus on space complexity; we define a model for studying the memory-size of online continuous algorithms. In this model, algorithms store a b

Paul Bruillard, Kathleen Nowak, Stephen J. Young

We present a correspondence between multiplicity-free, self-dual, fusion rings and a digraph, hypergraph pair $(D,H)$. This correspondence is used to provide a complete characterization of all fusion rings corresponding to graphical properties of $D$. Further, we exploit this correspondence to provide a complete list of all non-isomorphic, self-dual, multipl

Michele Mugnaine, Ricardo L. Viana, Alfredo M. Ozorio de Almeida, Yves Elskens

Some dynamical properties of nonlinear coupled systems can be described by the two-harmonic standard map, a two-dimensional area-preserving system with two parameters, where two distinct arbitrary resonant modes compete. Usually, the initial phase of the resonant modes is considered to be null. In this paper, we consider a non-null phase shift between the tw

Eric Palmerduca, Hong Qin

There has been an extended debate regarding the existence of a spin-orbital decomposition of the angular momentum of photons and other massless particles. It was recently shown that there are both geometric and topological obstructions preventing any such decomposition. Here we show that any geometric connection on a particle's state space induces a splittin

Chrysoula Markou

These proceedings are based on the author's invited talk reviewing the original published work [1,2] of the author with collaborators. The subject matter is a new, covariant and efficient technology of constructing entire trajectories of physical string states deeper inside the string spectrum than the leading Regge. The key observation behind the technology

Fatemeh Elhambakhsh, Suk Ki Lee, Hyunwoong Ko

The rising demand for high-value electronics necessitates advanced manufacturing techniques capable of meeting stringent specifications for precise, complex, and compact devices, driving the shift toward innovative additive manufacturing (AM) solutions. Aerosol Jet Printing (AJP) is a versatile AM technique that utilizes aerosolized functional materials to a

A. Albert, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez

Extended gamma-ray emission around isolated pulsars at TeV energies, also known as TeV halos, have been found around a handful of middle-aged pulsars. The halos are significantly more extended than their pulsar wind nebulae but much smaller than the particle diffusion length in the interstellar medium. The origin of TeV halos is unknown. Interpretations invo

Ilan Strauss, Isobel Moure, Tim O'Reilly, Sruly Rosenblat

Drawing on 1,178 safety and reliability papers from 9,439 generative AI papers (January 2020 - March 2025), we compare research outputs of leading AI companies (Anthropic, Google DeepMind, Meta, Microsoft, and OpenAI) and AI universities (CMU, MIT, NYU, Stanford, UC Berkeley, and University of Washington). We find that corporate AI research increasingly conc

Isabelle Bloch, Enzo Bonnot, Pietro Gori, Giammarco La Barbera

This article deals with the description and recognition of fiber bundles, in particular nerves, in medical images, based on the anatomical description of the fiber trajectories. To this end, we propose a logical formalization of this anatomical knowledge. The intrinsically imprecise description of nerves, as found in anatomical textbooks, leads us to propose

Sarah Scherotzke, Nicolò Sibilla, Paolo Tomasini

This paper establishes a unifying framework for various forms of twisted Hochschild homology by comparing two definitions of elliptic Hochschild homology: one introduced by Moulinos--Robalo--To\"en and the other by Sibilla--Tomasini. Central to our approach is a new Fourier--Mukai duality for formal groups. We prove that when $\widehat{E}$ is the formal grou

Saram Abbas, Naeem Soomro, Rishad Shafik, Rakesh Heer

Non-muscle-invasive bladder cancer (NMIBC) is a relentless challenge in oncology, with recurrence rates soaring as high as 70-80%. Each recurrence triggers a cascade of invasive procedures, lifelong surveillance, and escalating healthcare costs - affecting 460,000 individuals worldwide. However, existing clinical prediction tools remain fundamentally flawed,

C. Kapahi, D. Sarenac, B. Heacock, D. G. Cory

The gravitational constant (G) is the least precisely known fundamental constant of nature, with persistent and significant discrepancies between measurement methods. New techniques for measuring G with systematic effects different from commonly applied pendulum methods are required. Neutrons are convenient probes of gravitational forces as they are both mas

Filipp Nikitin, Ian Dunn, David Ryan Koes, Olexandr Isayev

Deep generative models have shown significant promise in generating valid 3D molecular structures, with the GEOM-Drugs dataset serving as a key benchmark. However, current evaluation protocols suffer from critical flaws, including incorrect valency definitions, bugs in bond order calculations, and reliance on force fields inconsistent with the reference data

Michelle C. Almendrala, Kyle Adrienne T. Valenzuela, Steffany Marie Nina B. Santos, Louise Grace S. Avena-Ardeta

The anaerobic co-digestion of slaughterhouse wastewater and food waste offers a sustainable approach to waste treatment and biogas production. However, limited literature was found on the study of ferric oxide as conductive material in co-digestion of the two substrates. This study evaluates the effect of ferric oxide on biogas yield, organic matter removal,

Loïck Degorre, Emmanuel Delaleau, Cédric Join, Michel Fliess

This work presents a new approach to the guidance and control of marine craft via HEOL, i.e., a new way of combining flatness-based and model-free controllers. Its goal is to develop a general regulator for Unmanned Surface Vehicles (USV). To do so, the well-known USV maneuvering model is simplified into a nominal Hovercraft model which is flat. A flatness-b

Longteng Chen

We study the uniqueness problem for the K\"ahler-Ricci flow with a conical initial condition. Given a complete gradient expanding K\"ahler-Ricci soliton on a non compact manifold with quadratic curvature decay, including its derivatives, we establish that any complete solution to the Kahler-Ricci flow emerging from the soliton's tangent cone at infinity--app

Raphael de Omena, José Edson Sampaio, Emanoel Souza

We investigate sufficient conditions for the invariance of the real Milnor number under $\mathcal{R}$-bi-Lipschitz equivalence for function-germs $ f, g \colon (\mathbb{R}^n, 0) \to (\mathbb{R}, 0) $. More generally, we explore its invariance within the extended framework of $\mathcal{R}$-asymptotically Lipschitz equivalence. To this end, we introduce the $\

Matteo El Hariry, Andrea Cini, Giacomo Mellone, Alessandro Balossino

Autonomy is a key challenge for future space exploration endeavours. Deep Reinforcement Learning holds the promises for developing agents able to learn complex behaviours simply by interacting with their environment. This paper investigates the use of Reinforcement Learning for the satellite attitude control problem, namely the angular reorientation of a spa

Mahsa Derakhshan, Andisheh Ghasemi, Rajmohan Rajaraman

We study the communication complexity of the Minimum Vertex Cover (MVC) problem on general graphs within the \(k\)-party one-way communication model. Edges of an arbitrary \(n\)-vertex graph are distributed among \(k\) parties. The objective is for the parties to collectively find a small vertex cover of the graph while adhering to a communication protocol w

Éva Czabarka, Alec Helm, László Székely

A tanglegram of size n is a graph formed from two rooted binary trees with n leaves each and a perfect matching between their leaf sets. Tanglegrams are used to model co-evolution in various settings. A tanglegram layout is a straight line drawing where the two trees are drawn as plane trees with their leaf-sets on two parallel lines, and only the edges of t

Nuojin Cheng, Alireza Doostan, Stephen Becker

Efficient optimization remains a fundamental challenge across numerous scientific and engineering domains, especially when objective function and gradient evaluations are computationally expensive. While zeroth-order optimization methods offer effective approaches when gradients are inaccessible, their practical performance can be limited by the high cost as

Huazhi Dong, Sihao Teng, Xu Han, Xiaopeng Wu

Flexible electrical impedance tomography (EIT) offers a promising alternative to traditional tactile sensing approaches, enabling low-cost, scalable, and deformable sensor designs. Here, we propose an optimized lattice-structured flexible EIT tactile sensor incorporating a hydrogel-based conductive layer, systematically designed through three-dimensional cou

Emily J. King

We consider geometric and combinatorial characterizations of equiangular tight frames (ETFs), with the former concerning homogeneity of the vector and line symmetry groups and the latter the matroid structure. We introduce the concept of the bender of a frame, which is the collection of short circuits, which in turn are the dependent subsets of frame vectors

Neel Malvania, Garry Jacyna, Bonnie L. Schmittberger Marlow, Zachary N. Hardesty-Shaw

Over the past decade, Rydberg atom electric field sensors have been under investigation as potential alternatives or complements to conventional antenna-based receivers for select applications in RF communications, remote sensing, and precision metrology. To understand the potential utility of these devices for various use cases, it is crucial to develop mod

Jean Hélder Marques Ribeiro, Hugo Felippe da Silva Lui, William Roberto Wolf

We propose a sensor-restrained model for the shear viscosity term within the localized artificial diffusivity (LAD) scheme to stabilize compressible large-eddy simulations with low-pressure-core vortical structures. LAD methods are used in numerical solvers based on spectral-like compact finite-difference schemes. While high-order-accurate numerical schemes

J. L. Shaw, M. V. Ambat, K. G. Miller, R. Boni

Dephasingless laser wakefield acceleration (DLWFA), a novel laser wakefield acceleration concept based on the recently demonstrated "flying focus" technology, offers a new paradigm in laser-plasma acceleration that could advance the progress toward a TeV linear accelerator using a single-stage system without guiding structures. The recently proposed NSF OPAL

Jannik Lübberstedt, Esteban Rivera, Nico Uhlemann, Markus Lienkamp

Large Vision Language Models (LVLMs) have shown strong capabilities in understanding and analyzing visual scenes across various domains. However, in the context of autonomous driving, their limited comprehension of 3D environments restricts their effectiveness in achieving a complete and safe understanding of dynamic surroundings. To address this, we introdu

Will Burstein

Let $(\varphi_i)_{i=1}^n$ be mutually orthogonal functions on a probability space such that $\|\varphi_i\|_\infty \leq 1 $ for all $i \in [n]$. Let $\alpha > 0$. Let $\Phi(u) = u^2 \log^{\alpha}(u)$ for $u \geq u_{0}$, and $\Phi(u) = c(\alpha) u^2$ otherwise. $u_0 \geq e$ and $c(\alpha)$ are constants chosen so that $\Phi$ is a Young function, depending only

C. W. Lester, A. B. Murray, Orencio Duran, B. Andreotti

Periodic sediment patterns have been observed on Earth in riverbeds and sand and snow deserts, but also in other planetary environments. One of the most ubiquitous patterns, familiar wind or 'impact' ripples, adorns sand beaches and arid regions on Earth. The observation of aeolian impact ripples on Mars the same size as their terrestrial counterparts despit

Bhanuja Ainary

Visually impaired people face significant challenges when attempting to interact with and understand complex environments, and traditional assistive technologies often struggle to quickly provide necessary contextual understanding and interactive intelligence. This thesis presents Audo-Sight, a state-of-the-art assistive system that seamlessly integrates Mul

André de Gouvêa, Adrian Thompson

We investigate the sensitivity of a companion neutrino detector situated in the plane of a high-energy, high-intensity muon storage ring to elastic $\nu_{\mu}$ and $\nu_e$ scattering on electrons (E$\nu$ES). Assuming a muon collider with center-of-mass energies of up to 10~TeV, we report sensitivity to the weak couplings $g_V$ and $g_A$ up to around 0.05% re

Phuoc-Truong Huynh

In this work, we develop a Bayesian framework for solving inverse problems in which the unknown parameter belongs to a space of Radon measures taking values in a separable Hilbert space. The inherent ill-posedness of such problems is addressed by introducing suitable measure-valued priors that encode prior information and promote desired sparsity properties

Minh-Hao Van, Xintao Wu

The rapid evolution of social media has provided enhanced communication channels for individuals to create online content, enabling them to express their thoughts and opinions. Multimodal memes, often utilized for playful or humorous expressions with visual and textual elements, are sometimes misused to disseminate hate speech against individuals or groups.

Gan Zhang, Megha Rao, Janni Yuval, Ming Zhao

Machine learning (ML) models are successful with weather forecasting and have shown progress in climate simulations, yet leveraging them for useful climate predictions needs exploration. Here we show this feasibility using Neural General Circulation Model (NeuralGCM), a hybrid ML-physics atmospheric model developed by Google, for seasonal predictions of larg

Andreas Schachner

We review compactifications of type IIB string theory which produce de Sitter vacua to leading order in the $\alpha^\prime$ and $g_s$ expansions in line with the scenario proposed by Kachru, Kallosh, Linde, and Trivedi. We detail specific Calabi-Yau orientifold compactifications incorporating the non-perturbative superpotential from Euclidean D3-branes, the

Leah Schätzler, Christoph Scheven, Jarkko Siltakoski, Calvin Stanko

For $q \in (0, \infty)$, we consider the Cauchy-Dirichlet problem to doubly nonlinear systems of the form \begin{align*} \partial_t \big( |u|^{q-1}u \big) - \operatorname{div} \big( D_\xi f(x,u,Du) \big) = - D_u f(x,u,Du) \end{align*} in a bounded noncylindrical domain $E \subset \mathbb{R}^{n+1}$. We assume that $x \mapsto f(x,u,\xi)$ is integrable, that $(

Yinghui He, Abhishek Panigrahi, Yong Lin, Sanjeev Arora

In-context learning (ICL) allows a language model to improve its problem-solving capability when provided with suitable information in context. Since the choice of in-context information can be determined based on the problem itself, in-context learning is analogous to human learning from teachers in a classroom. Recent works (Didolkar et al., 2024a; 2024b)

Pedro Duarte, Marcelo Durães, Tomé Graxinha, Silvius Klein

Consider the space of two dimensional random linear cocycles over a shift in finitely many symbols, with at least one singular and one invertible matrix. We provide an explicit formula for the unique stationary measure associated to such cocycles and establish a Furstenberg-type formula characterizing the Lyapunov exponent. Using the spectral properties of t

Willie Aboumrad, Phani R V Marthi, Suman Debnath, Martin Roetteler

Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear problems. Quantum computing provides new avenues to approach these problems. We develop a hybrid quantum-classical algorithm for the Unit Commitment (UC) problem in power systems wh

Feifei Niu, Chuanyi Li, Kui Liu, Xin Xia

Bug localization is a crucial aspect of software maintenance, running through the entire software lifecycle. Information retrieval-based bug localization (IRBL) identifies buggy code based on bug reports, expediting the bug resolution process for developers. Recent years have witnessed significant achievements in IRBL, propelled by the widespread adoption of

Z. Meisel, W. -J. Ong, J. S. Randhawa

We performed astrophysics model calculations with updated nuclear data to identify a possible bypass of the $^{64}{\rm Ge}$ waiting-point, a defining feature of the rapid-proton capture (rp-) process that powers type-I x-ray bursts on accreting neutron stars. We find that the rp-process flow through the $^{64}{\rm Ge}$ bypass could be up to 36\% for astrophy

Benoît Assi, Christan Bierlich, Philip Ilten, Tony Menzo

We present a method for reweighting flavor selection in the Lund string fragmentation model. This is the process of calculating and applying event weights enabling fast and exact variation of hadronization parameters on pre-generated event samples. The procedure is post hoc, requiring only a small amount of additional information stored per event, and allowi

Sandeep Ramteke, Jordan Dehmel, Touvia Miloh, Jarrod Schiffbauer

Most active colloid experiments are quasi-2D. Here a 3D density-matched solution of active particles propelled and aligned with an AC electric field uniquely facilitates measurement of short and long-range particle-wall interactions. Near-wall mobility is reduced by Stokes drag and local electric-field distortion. Long-range attractions concentrate particles

Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya

We introduce a novel approach for calibrating uncertainty quantification (UQ) tailored for multi-modal large language models (LLMs). Existing state-of-the-art UQ methods rely on consistency among multiple responses generated by the LLM on an input query under diverse settings. However, these approaches often report higher confidence in scenarios where the LL

Philip Beltracchi, Camilo Posada

The equilibrium configurations of slowly rotating anisotropic self-gravitating fluids are computed using the extended Hartle structure equations, including anisotropic effects, derived in our previous paper. We focus on the so-called $\mathcal{C}$-star, whose anisotropic pressure follows a fully covariant equation of state (EoS), while a standard polytrope d

Martin Haenggi

For a given set of transmitters such as cellular base stations or WiFi access points, is it possible to analytically characterize the set of locations that are "covered" in the sense that users at these locations experience a certain minimum quality of service? In this paper, we affirmatively answer this question, by providing explicit simple outer bounds an

Rushikesh Ubale, Sujan K. K., Sangram Deshpande, Gregory T. Byrd

We present a novel hybrid quantum-classical neural network architecture for fraud detection that integrates a classical Long Short-Term Memory (LSTM) network with a variational quantum circuit. By leveraging quantum phenomena such as superposition and entanglement, our model enhances the feature representation of sequential transaction data, capturing comple

Maksim Helmann, Alexander Strack, Dirk Pflüger

Python is the de-facto language for software development in artificial intelligence (AI). Commonly used libraries, such as PyTorch and TensorFlow, rely on parallelization built into their BLAS backends to achieve speedup on CPUs. However, only applying parallelization in a low-level backend can lead to performance and scaling degradation. In this work, we pr

Michal Geyer, Omer Tov, Linyi Jin, Richard Tucker

The rising popularity of immersive visual experiences has increased interest in stereoscopic 3D video generation. Despite significant advances in video synthesis, creating 3D videos remains challenging due to the relative scarcity of 3D video data. We propose a simple approach for transforming a text-to-video generator into a video-to-stereo generator. Given

Vasudev Sharma, Ahmed Alagha, Abdelhakim Khellaf, Vincent Quoc-Huy Trinh

Vision-language models (VLMs) have gained significant attention in computational pathology due to their multimodal learning capabilities that enhance big-data analytics of giga-pixel whole slide image (WSI). However, their sensitivity to large-scale clinical data, task formulations, and prompt design remains an open question, particularly in terms of diagnos

Hwihun Jeong, Hayeon Lee, Se Young Chun, Jongho Lee

Blind harmonization has emerged as a promising technique for MR image harmonization to achieve scale-invariant representations, requiring only target domain data (i.e., no source domain data necessary). However, existing methods face limitations such as inter-slice heterogeneity in 3D, moderate image quality, and limited performance for a large domain gap. T

József Balogh, Ce Chen, Ramon I. Garcia

Let $B(2d-1, d)$ be the subgraph of the hypercube $\mathcal{Q}_{2d-1}$ induced by its two largest layers. Duffus, Frankl and R\"odl proposed the problem of finding the asymptotics for the logarithm of the number of maximal independent sets in $B(2d-1, d)$. Ilinca and Kahn determined the logarithmic asymptotics and reiterated the question of what their order

Dalton Durant, Renato Zanetti

In this work, a kernel-based Ensemble Gaussian Mixture Probability Hypothesis Density (EnGM-PHD) filter is presented for multi-target filtering applications. The EnGM-PHD filter combines the Gaussian-mixture-based techniques of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter with the particle-based techniques of the Sequential Monte Carlo

Teegan Bailey, Isaiah Hollars, Yupei Li, Ruth Luo

A Berge cycle of length $\ell$ in a hypergraph $\mathcal{H}$ is a sequence of alternating vertices and edges $v_0e_0v_1e_1...v_\ell e_\ell v_0$ such that $\{v_i,v_{i+1}\}\subseteq e_i$ for all $i$, with indices taken modulo $\ell$. For $n$ sufficiently large and $r\geq \lfloor\frac{n-1}{2}\rfloor-1$ we prove exact minimum degree conditions for an $n$-vertex,

Yakov Berchenko-Kogan

Geometric decomposition is a widely used tool for constructing local bases for finite element spaces. For finite element spaces of differential forms on simplicial meshes, Arnold, Falk, and Winther showed that geometric decompositions can be constructed from extension operators satisfying certain properties. In this paper, we generalize their results to func

Joseph Cummings, Kyle J. -M. Dahlin, Elizabeth Gross, Jonathan D. Hauenstein

Changes in environmental or system parameters often drive major biological transitions, including ecosystem collapse, disease outbreaks, and tumor development. Analyzing the stability of steady states in dynamical systems provides critical insight into these transitions. This paper introduces an algebraic framework for analyzing the stability landscapes of e

Jinyan Su, Jennifer Healey, Preslav Nakov, Claire Cardie

Large language models (LLMs) are increasingly optimized for long reasoning, under the assumption that more reasoning leads to better performance. However, emerging evidence suggests that longer responses can sometimes degrade accuracy rather than improve it. In this paper, we conduct a systematic empirical study of the relationship between reasoning length a

Xinxian Chen, Ignacio Franco

We introduce an efficient method TTN-HEOM for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme to the bexcitonic generalization of the numerically-exact hierarchical equations of motion (HEOM). The method yields a series of