March 2025 arXiv papers — page 183

Jean Louis Fendji Kedieng Ebongue

This study explores the shift from community networks (CNs) to community data in rural areas, focusing on combining data pools and data cooperatives to achieve data justice and foster and a just AI ecosystem. With 2.7 billion people still offline, especially in the Global South, addressing data justice is critical. While discussions related to data justice h

Dominic Maggio, Luca Carlone

Open-set semantic mapping requires (i) determining the correct granularity to represent the scene (e.g., how should objects be defined), and (ii) fusing semantic knowledge across multiple 2D observations into an overall 3D reconstruction -ideally with a high-fidelity yet low-memory footprint. While most related works bypass the first issue by grouping togeth

Megha Hegde, Jean-Christophe Nebel, Farzana Rahman

Interpreting the effects of variants within the human genome and proteome is essential for analysing disease risk, predicting medication response, and developing personalised health interventions. Due to the intrinsic similarities between the structure of natural languages and genetic sequences, natural language processing techniques have demonstrated great

A. A. Tarusov, K. A. Ushakov, M. A. Vasiliev

A class of higher-spin gauge theories on $AdS_4$ associated with various Coxeter groups $\mathcal{C}$ is analyzed at the linear order. For a general $\mathcal{C}$, a solution corresponding to the $AdS_4$ space and the form of the free unfolded equations are established. A disentanglement criterion has been formulated for Coxeter HS modules. The shifted homot

Gillian D. Beltz-Mohrmann, Adrian Pope, Alex Alarcon, Michael Buehlmann

In this paper, we present the Discovery simulations: a new pair of high-resolution N-body simulations motivated by the DESI Y1 BAO cosmological constraints on dark energy. The Discovery simulations were run with identical initial conditions, and differ only in their cosmological parameters. The first simulation is based on a flat $\Lambda\mathrm{CDM}$ cosmol

Adamson Bryant

Despite growing evidence that neighborhoods play a critical role in shaping economic mobility and well-being, effective policies to address neighborhood disadvantage remain elusive. This study evaluates the impact of the Promise Zone program, which aims to revitalize disadvantaged neighborhoods through streamlined federal support and grant incentives. I use

Anastasios Antoniadis, Ilias Tsatiris, Nevill Grech, Yannis Smaragdakis

In this work, we present a simple, uniform, and elegant solution to the problem, with stunning practical effectiveness and application to virtually any Datalog-based analysis. The approach consists of leveraging the choice construct, supported natively in modern Datalog engines like Souffl\'e. The choice construct allows the definition of functional dependen

Julie Michelman, Nasrin Baratalipour, Matthew Abueg

We envision a continuous collaborative learning system where groups of LLM agents work together to solve reasoning problems, drawing on memory they collectively build to improve performance as they gain experience. This work establishes the foundations for such a system by studying the interoperability of chain-of-thought reasoning styles, multi-agent collab

Seth Merkel, Timothy Proctor, Samuele Ferracin, Jordan Hines

The goal of benchmarking is to determine how far the output of a noisy system is from its ideal behavior; this becomes exceedingly difficult for large quantum systems where classical simulations become intractable. A common approach is to turn to circuits comprised of elements of the Clifford group (e.g., CZ, CNOT, $\pi$ and $\pi/2$ gates), which probe quant

Amin Mamandipoor, Huy Dinh Tran, Mohammad Alian

Networking is considered a datacenter tax, and hyperscalers push hard to provide high-performance networking with minimal resource expenditure. To keep up with the ever-increasing network rates, many CPU cycles are spent on the networking tax. We make a key observation that network processing threads can be simultaneously executed on server CPUs with minimal

Avinash Kumar

This work proposes a new method to select the augmentation parameters in the operator splitting quadratic program (OSQP) algorithm so as to reduce the computation time of overall algorithm. The selection is based upon the information of conjugate directions of the coefficient matrix of a linear system of equations present in the algorithm. This selection mak

Sergey Mozgovoy

Proto-exact and parabelian categories serve as non-additive analogues of exact and quasi-abelian categories, respectively. They give rise to algebraic K-theory and Hall algebras similarly to the additive setting. We show that every parabelian category admits a canonical proto-exact structure and we study several classes of parabelian categories, including ca

A Gamage, V Donzella

Current research on automotive perception systems predominantly focusses on either improving the performance of sensor technology or enhancing the perception functions in isolation. High-level perception functions are increasingly based on deep learning (DL) models due to their improved performance and generalisability compared to traditional algorithms. Des

Ibrahim Elsharkawy, Yonatan Kahn, Benjamin Hooberman

Quantifying the uncertainty from machine learning analyses is critical to their use in the physical sciences. In this work we focus on uncertainty inherited from the initialization distribution of neural networks. We compute the mean $\mu_{\mathcal{L}}$ and variance $\sigma_{\mathcal{L}}^2$ of the test loss $\mathcal{L}$ for an ensemble of multi-layer percep

Ian W. Eisenberg, Lucía Gamboa, Eli Sherman

The rapid adoption of AI systems presents enterprises with a dual challenge: accelerating innovation while ensuring responsible governance. Current AI governance approaches suffer from fragmentation, with risk management frameworks that focus on isolated domains, regulations that vary across jurisdictions despite conceptual alignment, and high-level standard

Mohsen Gholami, Mohammad Akbari, Kevin Cannons, Yong Zhang

In this work, we propose an extreme compression technique for Large Multimodal Models (LMMs). While previous studies have explored quantization as an efficient post-training compression method for Large Language Models (LLMs), low-bit compression for multimodal models remains under-explored. The redundant nature of inputs in multimodal models results in a hi

Yasir Khan, Xinlei Wu, Sangpil Youm, Justin Ho

Query-focused tabular summarization is an emerging task in table-to-text generation that synthesizes a summary response from tabular data based on user queries. Traditional transformer-based approaches face challenges due to token limitations and the complexity of reasoning over large tables. To address these challenges, we introduce DETQUS (Decomposition-En

Anas Gamal Aly, Anders E. Jensen, Hala ElAarag

Recent work by Google DeepMind introduced assembly-optimized sorting networks that achieve faster performance for small fixed-size arrays (3-8). In this research, we investigate the integration of these networks as base cases in classical divide-and-conquer sorting algorithms, specifically Merge Sort and Quick Sort, to leverage these efficient sorting networ

Piotr Żelasko, Kunal Dhawan, Daniel Galvez, Krishna C. Puvvada

Attention encoder-decoder model architecture is the backbone of several recent top performing foundation speech models: Whisper, Seamless, OWSM, and Canary-1B. However, the reported data and compute requirements for their training are prohibitive for many in the research community. In this work, we focus on the efficiency angle and ask the questions of wheth

Jianfeng Gu, Hao Wang, Xiaorang Guo, Martin Schulz

As FPGAs gain popularity for on-demand application acceleration in data center computing, dynamic partial reconfiguration (DPR) has become an effective fine-grained sharing technique for FPGA multiplexing. However, current FPGA sharing encounters partial reconfiguration contention and task execution blocking problems introduced by the DPR, which significantl

Youness Atif

This paper introduces a novel audio-to-image encoding framework that integrates multiple dimensions of voice characteristics into a single RGB image for speaker recognition. In this method, the green channel encodes raw audio data, the red channel embeds statistical descriptors of the voice signal (including key metrics such as median and mean values for fun

Mark L. Lewis, Abbas Mohammadian

We generalize the enhanced power graph by replacing elements with conjugacy classes. The main result of this paper is to determine when this graph is triangle-free.

Daria Zaremba, Kim Venn, Christian R. Hayes, Raphaël Errani

We present Gemini/GHOST high-resolution spectra of five stars observed in two low surface brightness Milky Way satellites, Sagittarius II (Sgr2) and Aquarius II (Aqu2). For Aqu2, the velocities and metallicities of the two stars are consistent with membership in a dark matter-dominated ultra faint dwarf galaxy (UFD). The chemical abundance ratios suggest ine

Elizabeth Anne Watkins, Emanuel Moss, Giuseppe Raffa, Lama Nachman

While human-AI collaboration has been a longstanding goal and topic of study for computational research, the emergence of increasingly naturalistic generative AI language models has greatly inflected the trajectory of such research. In this paper we identify how, given the language capabilities of generative AI, common features of human-human collaboration d

Greg d'Eon, Hala Murad, Kevin Leyton-Brown, James R. Wright

Behavioral game theory models serve two purposes: yielding insights into how human decision-making works, and predicting how people would behave in novel strategic settings. A system called GameNet represents the state of the art for predicting human behavior in the setting of unrepeated simultaneous-move games, combining a simple "level-k" model of strategi

Tanmay Tirpankar, Arnab Das, Ganesh Gopalakrishnan

Techniques that rigorously bound the overall rounding error exhibited by a numerical program are of significant interest for communities developing numerical software. However, there are few available tools today that can be used to rigorously bound errors in programs that employ conditional statements (a basic need) as well as mixed-precision arithmetic (a

Zdeněk Mihula

We provide a complete characterization of compactness of Sobolev embeddings of radially symmetric functions on the entire space $\mathbb{R}^n$ in the general framework of rearrangement-invariant function spaces. We avoid any unnecessary restrictions and cover also embeddings of higher order, providing a complete picture within this framework. To achieve this

Can Yildirim, Aditya Shukla, Yubin Zhang, Nikolas Mavrikakis

Dark Field X-ray Microscopy (DFXM) has advanced 3D non-destructive, high-resolution imaging of strain and orientation in crystalline materials, enabling the study of embedded structures in bulk. However, the photon-intensive nature of monochromatic DFXM limits its applicability to highly deformed or weakly crystalline structures and constrains time-resolved

Yixiao Li, Xianzhi Du, Ajay Jaiswal, Tao Lei

Recent advancements in large language models have intensified the need for efficient and deployable models within limited inference budgets. Structured pruning pipelines have shown promise in token efficiency compared to training target-size models from scratch. In this paper, we advocate incorporating enlarged model pretraining, which is often ignored in pr

Eric Zhao, Pranjal Awasthi, Nika Haghtalab

Finetuning provides a scalable and cost-effective means of customizing language models for specific tasks or response styles, with greater reliability than prompting or in-context learning. In contrast, the conventional wisdom is that injecting knowledge via finetuning results in brittle performance and poor generalization. We argue that the dichotomy of "ta

Esteban Henriquez, Jeonghun J. Lee, Sander Rhebergen

Hybridizable discretizations allow for the elimination of local degrees-of-freedom leading to reduced linear systems. In this paper, we determine and analyse an approach to construct parameter-robust preconditioners for these reduced systems. Using the framework of Mardal and Winther (Numer. Linear Algebra Appl., 18(1):1--40, 2011) we first determine a param

Antonio Pich, Ignasi Rosell, Juan José Sanz-Cillero

Using a general (non-linear) effective field theory description of the Standard Model electroweak symmetry breaking, we analyse the impact on the electroweak oblique parameters of hypothetical heavy resonance states strongly coupled to the SM particles. We present a next-to-leading order calculation of $S$ and $T$ that updates and generalizes our previous re

Danielle L. Ferreira, Ahana Gangopadhyay, Hsi-Ming Chang, Ravi Soni

Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability in imaging conditions (e.g., probe position, patient anatomy, tissue characteristics and pathology). To address this, we introduce Segment Anything Small (SAS), a simple yet effective scale- and texture-aware data aug

Aja Sutton, Zack W. Almquist, Jon Wakefield

Multilevel regression and poststratification (MRP) is a computationally efficient indirect estimation method that can quickly produce improved population-adjusted estimates with limited data. Recent computational advancements allow efficient, relatively simple, and quick approximate Bayesian estimation for MRP. As population health outcomes of interest inclu

Chris Kouvaris, Dimitris Zavitsanos

A strongly self-interacting component of asymmetric dark matter can collapse and form compact objects, provided there is an efficient mechanism of energy evacuation. If the dark matter quantum number is not completely conserved but it is slightly violated due to some new physics e.g. at the Planck scale, dark matter particles can annihilate into Standard Mod

Yao Luo, Dhruv Mangtani, Shiyu Peng, Jia Yao

Phonon interactions from lattice anharmonicity govern thermal properties and heat transport in materials. These interactions are described by n-th order interatomic force constants (n-IFCs), which can be viewed as high-dimensional tensors correlating the motion of n atoms, or equivalently encoding n-phonon scattering processes in momentum space. Here, we int

Stefana-Lucia Anita, Luca Di Persio

This paper investigates the optimal control problem for a class of parabolic equations where the diffusion coefficient is influenced by a control function acting nonlocally. Specifically, we consider the optimization of a cost functional that incorporates a controlled probability density evolving under a Fokker-Planck equation with state-dependent drift and

Carson Sobolewski, Zhenjiang Mao, Kshitij Maruti Vejre, Ivan Ruchkin

Vision-based control relies on accurate perception to achieve robustness. However, image distribution changes caused by sensor noise, adverse weather, and dynamic lighting can degrade perception, leading to suboptimal control decisions. Existing approaches, including domain adaptation and adversarial training, improve robustness but struggle to generalize to

João Alberto de Oliveira Lima

When users formulate queries, they often include not only the information they seek, but also pragmatic markers such as interrogative phrasing or polite requests. Although these speech act indicators communicate the user\textquotesingle s intent -- whether it is asking a question, making a request, or stating a fact -- they do not necessarily add to the core

Nathan Rethwisch, Heike Hofmann

The current method for forensic analysis of bullet comparison relies on manual examination by forensic examiners to determine if bullets were discharged from the same firearm. This process is highly subjective, prompting the development of algorithmic methods to provide objective statistical support for comparisons. However, a gap exists between the technica

Bastian Ayala, Joseph P. Anderson, G. Pignata, Francisco Foerster

Type IIb supernovae (SNe IIb) often exhibit an early light curve excess (EE) preceding the main peak powered by radioactive nickel decay. The physical origin of this early emission remains an open question. Among the proposed scenarios, shock cooling emission-resulting from the interaction between the shockwave and extended envelopes-is considered the most p

Elke-Caroline Aschenauer, Varvara Batozskaya, Salvatore Fazio, Alexander Jentsch

This study presents the impact of future measurements of deeply virtual Compton scattering (DVCS) with the ePIC detector at the electron-ion collider (EIC), currently under construction at Brookhaven National Laboratory. The considered process is sensitive to generalized parton distributions (GPDs), the understanding of which is a cornerstone of the EIC phys

Thomas Foltz

This paper focuses on detecting anomalies in surveillance video using keywords by leveraging foundational models' feature representation generalization capabilities. We present a novel, lightweight pipeline for anomaly classification using keyword weights. Our pipeline employs a two-stage process: induction followed by deduction. In induction, descriptions a

Yuran Sun, James Spall, Wai Wong, Xilei Zhao

Accurate and reliable bus travel time prediction in real-time is essential for improving the operational efficiency of public transportation systems. However, this remains a challenging task due to the limitations of existing models and data sources. This study proposed a hybrid Markovian framework for real-time bus travel time prediction, incorporating unce

Michaël Fanuel, Rémi Bardenet

Given an $n\times r$ matrix $X$ of rank $r$, consider the problem of sampling $r$ integers $\mathtt{C}\subset \{1, \dots, n\}$ with probability proportional to the squared determinant of the rows of $X$ indexed by $\mathtt{C}$. The distribution of $\mathtt{C}$ is called a projection determinantal point process (DPP). The vanilla classical algorithm to sample

Yasir Zubayr Barlas, Kizito Salako

Recent developments in sequential experimental design look to construct a policy that can efficiently navigate the design space, in a way that maximises the expected information gain. Whilst there is work on achieving tractable policies for experimental design problems, there is significantly less work on obtaining policies that are able to generalise well -

Fabio Maresca, Arnau Romero, Carmen Delgado, Vincenzo Sciancalepore

Smart factories enhance production efficiency and sustainability, but emergencies like human errors, machinery failures and natural disasters pose significant risks. In critical situations, such as fires or earthquakes, collaborative robots can assist first-responders by entering damaged buildings and locating missing persons, mitigating potential losses. Un

Verena Bögelein, Frank Duzaar, Naian Liao, Kristian Moring

We consider local weak solutions to the fractional $p$-Poisson equation of order $s$, i.e. $\left( - \Delta_p\right)^s u = f$. In the range $p>1$ and $s\in \big(\frac{p-1}{p},1\big)$ we prove Calder\'on & Zygmund type estimates at the gradient level. More precisely, we show for any $q>1$ that \begin{equation*} f\in L^{\frac{qp}{p-1}}_{\rm loc} \quad\Longrigh

B. Arnold, J. Daligault, D. Saumon, Antoine Bédard

Nucleation in the supercooled Yukawa system is relevant for addressing current challenges in understanding a range of crystallizing systems including white dwarf (WD) stars. We use both brute force and seeded molecular dynamics simulations to study homogeneous nucleation of crystals from supercooled Yukawa liquids. With our improved approach to seeded simula

Ábris Nagy, Márk Oláh, Myroslav Stoika, Csaba Vincze

An equidistant set in the Euclidean space consists of points having equal distances to both members of a given pair of sets, called focal sets. Having no effective formulas to compute the distance of a point and a set, it is hard to determine the points of an equidistant set in general. Special classes of equidistant sets allow us to approximate the equidist

Hersh Singh

The Ginsparg-Wilson (GW) relation elegantly captures how the anomalous chiral symmetry of a Dirac fermion manifests on the lattice. In this talk, we discuss how the GW relation and its closed-form solution, the overlap operator, can be generalized to Majorana or Dirac fermions in any dimension for finite symmetry transformations (continuous or discrete). We

Ricardo E. Gonzalez Penuela, Ruiying Hu, Sharon Lin, Tanisha Shende

Blind and Low Vision (BLV) people have adopted AI-powered visual interpretation applications to address their daily needs. While these applications have been helpful, prior work has found that users remain unsatisfied by their frequent errors. Recently, multimodal large language models (MLLMs) have been integrated into visual interpretation applications, and

Karan Vombatkere, Evimaria Terzi, Aristides Gionis

We study a new formulation of the team-formation problem, where the goal is to form teams to work on a given set of tasks requiring different skills. Deviating from the classic problem setting where one is asking to cover all skills of each given task, we aim to cover as many skills as possible while also trying to minimize the maximum workload among the exp

Nan Hu, Jonghyun Hwang, Tachin Ruangkriengsin, Howard A. Stone

We use experiments and theory to elucidate the size effect in capillary breakup rheometry, where pre-stretching in the visco-capillary stage causes the apparent relaxation time to be consistently smaller than the actual value. We propose a method accounting for both the experimental size and the finite extensibility of polymers to extract the actual relaxati

Diego Corro, Masoumeh Zarei, Adam Moreno

We show the existence of a solution to the Ricci flow with a compact length space of bounded curvature, i.e., a space that has curvature bounded above and below in the sense of Alexandrov, as its initial condition. We show that this flow converges in the $C^{1,\alpha}$-sense to a $C^{1,\alpha}$-continuous Riemannian manifold which is isometric to the origina

Claudio Carvalho Neto, Ana Karolinna Maia, Cláudia Linhares Sales, Jonas Costa Ferreira da Silva

A network $\mathcal{N}$ is formed by a (multi)digraph $D$ together with a \emph{capacity function} $u : A(D) \to R_+$, and it is denoted by $\mathcal{N} = (D,u)$. A flow on $\mathcal{N}$ is a function $x: A(D) \to R_+$ such that $x(a) \leq u(a)$ for all $a \in A(D)$, and it is said to be $k$-splittable if it can be decomposed into up to $k$ paths. We say tha

Márcia S. B. A. Cardoso, Edcarlos D. Silva, Marcos. L. M. Carvalho, Minbo Yang

In the present work, we establish the existence and multiplicity of positive solutions for the singular elliptic equations with a double weighted nonlocal interaction term defined in the whole space $\mathbb{R}^N$. The nonlocal term and the fact that the energy functional is not differentiable are the main difficulties for this kind of problem. We apply the

Ekaterina Redekop, Zichen Wang, Rushikesh Kulkarni, Mara Pleasure

Longitudinal data in electronic health records (EHRs) represent an individual`s clinical history through a sequence of codified concepts, including diagnoses, procedures, medications, and laboratory tests. Generative pre-trained transformers (GPT) can leverage this data to predict future events. While fine-tuning of these models can enhance task-specific per

Alexander M. Perez Reyes, Matthew J. Zahr

A mesh-based parametrization is a parametrization of a geometric object that is defined solely from a mesh of the object, e.g., without an analytical expression or computer-aided design (CAD) representation of the object. In this work, we propose a mesh-based parametrization of an arbitrary $d'$-dimensional object embedded in a $d$-dimensional space using to

Jonas Golde, Patrick Haller, Fabio Barth, Alan Akbik

Recent advancements in large language models (LLMs) have led to remarkable performance across a wide range of language understanding and mathematical tasks. As a result, increasing attention has been given to assessing the true reasoning capabilities of LLMs, driving research into commonsense, numerical, logical, and qualitative reasoning. However, with the

Harold Blas

This review paper explores the Riccati-type pseudo-potential formulation applied to the quasi-integrable sine-Gordon, KdV, and NLS models. The proposed framework provides a unified methodology for analyzing quasi-integrability properties across various integrable systems, including deformations of the sine-Gordon, Bullough-Dodd, Toda, KdV, pKdV, NLS and SUSY

Edcarlos D Silva, Elaine A. F. Leite, Maxwell L. Silva

In the present work, we establish the existence of two positive solutions for singular nonlocal elliptic systems. More precisely, we consider the following nonlocal elliptic problem: $$\left\{\begin{array}{lll} (-\Delta)^su +V_1(x)u = \lambda\frac{a(x)}{u^p} + \frac{\alpha}{\alpha+\beta}\theta |u|^{\alpha - 2}u|v|^{\beta}, \,\,\, \mbox{in} \,\,\, \mathbb{R}^

Bang Nguyen, Tingting Du, Mengxia Yu, Lawrence Angrave

While the Question Generation (QG) task has been increasingly adopted in educational assessments, its evaluation remains limited by approaches that lack a clear connection to the educational values of test items. In this work, we introduce test item analysis, a method frequently used by educators to assess test question quality, into QG evaluation. Specifica

Yian Wang, Bingjie Tang, Chuang Gan, Dieter Fox

Robotic assembly remains a significant challenge due to complexities in visual perception, functional grasping, contact-rich manipulation, and performing high-precision tasks. Simulation-based learning and sim-to-real transfer have led to recent success in solving assembly tasks in the presence of object pose variation, perception noise, and control error; h

Olga Movilla Miangolarra, Ralph Sabbagh, Tryphon T. Georgiou

Quantum counterparts of Schrodinger's classical bridge problem have been around for the better part of half a century. During that time, several quantum approaches to this multifaceted classical problem have been introduced. In the present work, we unify, extend, and interpret several such approaches through a classical large deviations perspective. To this

William Cooperman, Keefer Rowan

Batchelor predicted that a passive scalar $\psi^\nu$ with diffusivity $\nu$, advected by a smooth fluid velocity, should typically have Fourier mass distributed as $|\hat \psi^\nu|^2(k) \approx |k|^{-d}$ for $|k| \ll \nu^{-1/2}$. For a broad class of velocity fields, we give a quantitative lower bound for a version of this prediction summed over constant wid

Yujie Zhang, David Schmid, Yìlè Yīng, Robert W. Spekkens

There is a received wisdom about where to draw the boundary between classical and nonclassical for various types of quantum processes. For multipartite states, it is the divide between separable and entangled; for channels, the divide between entanglement-breaking and not; for sets of measurements, the divide between compatible and incompatible; for assembla

Ryan Low, Rakshak Adhikari, Jonah C. Rose, Stephanie O'Neil

We present hydrodynamic simulations of a flavour-mixed two-component dark matter (2cDM) model that utilize IllustrisTNG baryonic physics. The model parameters are explored for two sets of power laws of the velocity-dependent cross sections, favoured on the basis of previous studies. The model is shown to suppress the formation of structures at scales $k\gtrs

Xiaowei Ou, Lina Necib, Andrew Wetzel, Anna Frebel

Recent measurements of the Milky Way rotation curve found a sharp decline at around $15$-$20$ kpc from the center of the Galaxy, suggesting that the Galactic dark matter halo is much less massive than predicted by other dynamical tracers. To address this tension, we study the validity of the assumptions made in calculating the Milky Way's rotation curve. To

K. Antoniadis, E. Zapartas, A. Z. Bonanos, G. Maravelias

Red supergiants (RSGs) are cool and evolved massive stars exhibiting enhanced mass loss compared to their main sequence phase, affecting their evolution and fate. However, the theory of the wind-driving mechanism is not well-established and the metallicity dependence has not been determined. We aim to uniformly measure the mass-loss rates of large samples of

M. Villenave, G. Rosotti, M. Lambrechts, A. Ziampras

The level of dust vertical settling and radial dust concentration in disks is of critical importance for understanding the efficiency of planet formation. We present the first uniform analysis of the vertical extent of millimeter dust for a representative sample of 33disks. We used radiative transfer modeling of archival high-angular-resolution (<=0.1") ALMA

Javier Carballo, Christiana Pantelidou, Benjamin Withers

We study the non-modal stability of black hole spacetimes under linear perturbations. We show that large-amplitude growth can occur at finite time, despite asymptotic decay of linear perturbations. In the example presented, the physical mechanism is a transient form of superradiance, and is qualitatively similar to the transition to turbulence in Navier-Stok

Emile Pangburn, Anurag Banerjee, Catherine Pépin, Cristina Bena

We study the formation of subgap impurity states in strongly correlated Mott insulators. We use a composite operator method that gives us access to both the bulk Green's function, as well as to the real-space Green's function in the presence of an impurity. Similar to the non-interacting systems, we show that the formation of impurity subgap states at large

Kevin Falls

A new fundamental form of the path integral for theories with local symmetry is introduced. It is utilised to construct effective actions that generate correlation functions of dressed fields in Yang-Mills theories and quantum gravity. The construction entails a novel BRST symmetric gauge fixing which imposes that the on-shell correlation functions are those

Stefan Antusch, Kevin Hinze, Shaikh Saad

Metastable cosmic strings (MSCSs) are among the best-fitting explanations of the 2023 pulsar timing array (PTA) signal for gravitational waves at nanohertz frequencies. We propose the novel possibility that a network of MSCSs generating this signal originates from the multi-step spontaneous breaking of a gauged flavour symmetry. As a specific example, we con

Thomas W. Grimm, Arno Hoefnagels, Mick van Vliet

Cosmological correlators are fundamental observables in an expanding universe and are highly non-trivial functions even at tree-level. In this work, we uncover novel structures in the space of such tree-level correlators that enable us to develop a new recursive algorithm for their explicit computation. We begin by formulating cosmological correlators as sol

Diego Guadagnoli, Axel Iohner, Cristina Lazzeroni, Diego Martinez Santos

We reinterpret publicly available $K^+ \to \pi^+ \nu \bar{\nu}$ data collected by NA62 from 2016 to 2024 to constrain the fundamental vectorial coupling of the QCD axion to down and strange quarks. Using a fully reproducible likelihood analysis and a complete renormalization-group evolution of the axion couplings from the Peccei-Quinn (PQ) scale to the kaon

Yuxuan Zhang, Maissam Barkeshli

Recently, it has been established that Chern insulators possess an intrinsic two-dimensional electric polarization, despite having gapless edge states and non-localizable Wannier orbitals. This polarization, $\vec{P}_{\text{o}}$, can be defined in a many-body setting from various physical quantities, including dislocation charges, boundary charge distributio

Daniele Guerci, Liang Fu

We present a theory of ferromagnetic superconductivity that emerges upon doping a correlated ferromagnetic insulator through the condensation of excitonic Cooper pairs, which are charge-$2e$ bosonic quasiparticles made of Cooper pairs strongly hybridized with excitons. By solving a model of spin-polarized electrons using the strong-coupling expansion to the

Puxin Lin, Alessandro Mininno, Gary Shiu

We propose a version of the Weak Gravity Conjecture that applies to AdS spacetime. We find that the condition on the charge-to-mass ratio of a charged particle in AdS$_D$ spacetime is corrected compared to the one in Minkowski spacetime by contributions that depends on the AdS scale and the horizon radius of the extremal Reissner-Nordstr\"om black hole charg

Timothée Goubault de Brugière, Nicolas Heurtel

Exactly computing the full output distribution of linear optical circuits remains a challenge, as existing methods are either time-efficient but memory-intensive or memory-efficient but slow. Moreover, any realistic simulation must account for noise, and any viable quantum computing scheme based on linear optics requires feedforward. In this paper, we propos

Jonathon Riddell, Katja Klobas, Bruno Bertini

Random many-body states are both a useful tool to model certain physical systems and an important asset for quantum computation. Realising them, however, generally requires an exponential (in system size) amount of resources. Recent research has presented a way out by showing that one can generate random states, or more precisely a controlled approximation o

Julian May-Mann, Tobias Helbig, Trithep Devakul

We investigate how the pairing mechanism influences topological superconductivity in valley-polarized systems with Berry curvature. We demonstrate that short-range attractive interactions, such as those mediated by phonons, favor superconducting states where the Bogoliubov-de Gennes (BdG) Chern number has the same sign as the Berry curvature. In contrast, ov

Xinjie Liu, Cyrus Neary, Kushagra Gupta, Wesley A. Suttle

Many reinforcement learning (RL) algorithms are impractical for training in operational systems or computationally expensive high-fidelity simulations, as they require large amounts of data. Meanwhile, low-fidelity simulators, e.g., reduced-order models, heuristic rewards, or learned world models, can cheaply provide useful data, even if they are too coarse

Vittorio Bilò, Martin Loebl, Cosimo Vinci

We revisit the setting of fair allocation of indivisible items among agents with heterogeneous, non-monotone valuations. We explore the existence and efficient computation of allocations that approximately satisfy either envy-freeness or equity constraints. Approximate envy-freeness ensures that each agent values her bundle at least as much as those given to

Bryce T. Bolin, Josef Hanuš, Larry Denneau, Roberto Bonamico

We describe observations and physical characteristics of Earth-crossing asteroid 2024 YR$_4$, discovered on 2024 December 27 by the Asteroid Terrestrial-impact Last Alert System. The asteroid has semi-major axis, $a$ = 2.52 au, eccentricity, $e$ = 0.66, inclination $i$ = 3.41$^{\circ}$, and a $\sim$0.003 au Earth minimum orbit intersection distance. We obtai

Alexey Cheskidov, Zirong Zeng, Deng Zhang

For any divergence free initial data in $H^\frac12$, we prove the existence of infinitely many dissipative solutions to both the 3D Navier-Stokes and MHD equations, whose energy profiles are continuous and decreasing on $[0,\infty)$. If the initial data is only $L^2$, our construction yields infinitely many solutions with continuous energy, but not necessari

Itamar J. Allali, Praniti Singh, JiJi Fan, Lingfeng Li

Recently, the James Webb Space Telescope (JWST) has found early galaxies producing photons from more efficient ionization than previously assumed. This may suggest a reionization process with a larger reionization optical depth, $\tau_{\rm reio}$, in some mild disagreement with that inferred from measurements of cosmic microwave background (CMB). Intriguingl

Franco Vargas Pallete, Yilin Wang, Catherine Wolfram

We apply Epstein's construction of hypersurfaces in the hyperbolic disk $\mathbb D$ to prove identities between the Schwarzian action on $\operatorname{PSL}_2(\mathbb R)\backslash \mathrm{Diff}^3 (\mathbb S^1)$, the length of the corresponding Epstein curve in $\mathbb D$, and the area enclosed by the Epstein curve. These results are inspired by the holograp

Zebin Xing, Xingyu Zhang, Yang Hu, Bo Jiang

We propose GoalFlow, an end-to-end autonomous driving method for generating high-quality multimodal trajectories. In autonomous driving scenarios, there is rarely a single suitable trajectory. Recent methods have increasingly focused on modeling multimodal trajectory distributions. However, they suffer from trajectory selection complexity and reduced traject

Darragh Glynn

Let $\mathcal{H}$ be a Hurwitz space that parametrises holomorphic maps to $\mathbb{P}^1$. Abramovich, Corti and Vistoli, building on work of Harris and Mumford, describe a compactification $\overline{\mathcal{H}}$ with a natural boundary stratification. We show that the irreducible strata of $\overline{\mathcal{H}}$ are in bijection with combinatorial objec

Jirayu Mongkolkiattichai, Liyu Liu, Sohail Dasgupta, Kaden R. A. Hazzard

Hubbard systems are paradigmatic realizations of strongly correlated many-body systems. Introducing additional species breaks the SU(2) symmetry of the Hubbard model and leads to a wide variety of novel exotic quantum phases. Three-component fermionic systems are at the heart of model systems for quantum chromodynamics where the three components reflect the

Edgar Assing, Yingkun Li, Tian Wang, Jiacheng Xia

Given two CM elliptic curves over a number field and a natural number $m$, we establish a polynomial lower bound (in terms of $m$) for the number of rational primes $p$ such that the reductions of these elliptic curves modulo a prime above $p$ are $m$-isogenous. The proof relies on higher Green functions and theorems of Gross-Zagier and Gross-Kohnen-Zagier.

Parameswaran Kamalaruban, Mark Anderson, Stuart Burrell, Maeve Madigan

Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of these adapted classifiers remain underexplored. Existing fairness-aware fine-tuning methods assume that sensitive attribute labels are available alongside downstream task labels, which often fails in practice due to use

Christian Jorgensen, Arthur Y. Lin, Rhushil Vasavada, Rose K. Cersonsky

How do classification models "see" our data? Based on their success in delineating behaviors, there must be some lens through which it is easy to see the boundary between classes; however, our current set of visualization techniques makes this prospect difficult. In this work, we propose a hybrid supervised-unsupervised technique distinctly suited to visuali

Lukas Thede, Karsten Roth, Matthias Bethge, Zeynep Akata

Keeping large language models factually up-to-date is crucial for deployment, yet costly retraining remains a challenge. Knowledge editing offers a promising alternative, but methods are only tested on small-scale or synthetic edit benchmarks. In this work, we aim to bridge research into lifelong knowledge editing to real-world edits at a practically relevan

Zhenxuan Zhang, Hongjie Wu, Jiahao Huang, Baihong Xie

Multi-contrast magnetic resonance imaging (MRI) plays a vital role in brain tumor segmentation and diagnosis by leveraging complementary information from different contrasts. Each contrast highlights specific tumor characteristics, enabling a comprehensive understanding of tumor morphology, edema, and pathological heterogeneity. However, existing methods sti

Roham Koohestani, Philippe de Bekker, Begüm Koç, Maliheh Izadi

Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for tasks such as code generation and bug repair. However, this proliferation has led to major challenges: (1) fragmented knowledge across tasks, (2) difficulty in selecting contextua

V. I. Yukalov, E. P. Yukalova

Quantum statistical systems, composed of atoms or molecules interacting with each other through highly singular non-integrable potentials, are considered. The treatment of such systems cannot start with the standard approximations such as Hartree, Hartree-Fock or Hartree-Fock-Bogolubov approximations because of non-integrability of the interaction potentials

Hans Halvorson, JB Manchak, James Owen Weatherall

Determinism is (roughly) the thesis that the past determines the future. But efforts to define it precisely have exposed deep methodological disagreements. Standard possible-worlds formulations of determinism presuppose an "agreement" relation between worlds,but this relation can be understood in multiple ways, none of which is particularly clear. We critica