March 2025 arXiv papers — page 135

O Sauter, R. Hong, A. Marinoni, F. Scotti

The density limit in strongly-shaped negative triangularity (NT) discharges is studied experimentally in the DIII-D tokamak. Record-high Greenwald fractions $f_G$ are obtained, using gas puff injection only, with values up to near 2, where $f_G$ is defined as the ratio of the line-averaged density over $n_G=I_p/(\pi\,a^2)$, with $I_p$[MA] the plasma current

Benjamin Wong, Ryan H. Lee, Tyler M. Paine, Santosh Devasia

Ergodic exploration has spawned a lot of interest in mobile robotics due to its ability to design time trajectories that match desired spatial coverage statistics. However, current ergodic approaches are for continuous spaces, which require detailed sensory information at each point and can lead to fractal-like trajectories that cannot be tracked easily. Thi

Indrajit Paul, Ashok Kumar Das

In this article, we present two new characterizations of circular-arc bigraphs based on their vertex ordering. Also, we provide a characterization of circular-arc bigraphs in terms of forbidden patterns with respect to a particular ordering of their vertices.

Yuehao Bai, Xun Huang, Joseph P. Romano, Azeem M. Shaikh

This paper considers the problem of design-based inference for the average treatment effect in finely stratified experiments. Here, by "design-based'' we mean that the only source of uncertainty stems from the randomness in treatment assignment; by "finely stratified'' we mean that units are stratified into groups of a fixed size according to baseline covari

V. I. Zhdanov

Static spherically symmetric (SSS) solutions of f(R) gravity are studied in the Einstein frame. The solutions involve SSS configuration mass M and scalaron mass $\mu$ (in geometrized units); for typical astrophysical masses, the dimensionless parameter $M\mu$ has very large value. We found analytic solutions on a finite interval for $M\mu\to \infty$ in case

Thomas Thévenet, Axel Dian, Alexis Markovits, Sandro Scandolo

The chemical behavior of water under extreme pressures and temperatures lies at the heart of processes shaping planetary interiors, influences the deep carbon cycle, and underpins innovative high-temperature, high-pressure synthesis of materials. Recent experiments reveal that hydrocarbons immersed in ionized water under extreme conditions transform into hea

Marat Siddikov, Ivan Zemlyakov

In this manuscript we study the exclusive photoproduction of $\chi_{c}\gamma$ pairs in the collinear factorization framework. We found the coefficient functions for all possible spins and helicity projections of $\chi_{c}$ mesons and final-state photons in the leading order in the strong coupling $\alpha_{s}$. In our analysis we focused on the contribution o

Samantha M. Lawler, Mark Comte, Rosemary E. Pike, Mike Alexandersen

We present a publicly available, high-resolution, filled-parameter-space synthetic distribution of the Plutinos, trans-Neptunian Objects (TNOs) librating in the 3:2 mean-motion resonance with Neptune, with particular focus on the Plutinos simultaneously Kozai-librating. This synthetic distribution was built in preparation for results from the Large inclinati

Seyed Ali Akhavani, Bahruz Jabiyev, Ben Kallus, Cem Topcuoglu

Web Application Firewalls (WAFs) have been introduced as essential and popular security gates that inspect incoming HTTP traffic to filter out malicious requests and provide defenses against a diverse array of web-based threats. Evading WAFs can compromise these defenses, potentially harming Internet users. In recent years, parsing discrepancies have plagued

Leonard Waldmann, Ando Shah, Yi Wang, Nils Lehmann

Earth observation (EO) data features diverse sensing platforms with varying spectral bands, spatial resolutions, and sensing modalities. While most prior work has constrained inputs to fixed sensors, a new class of any-sensor foundation models able to process arbitrary sensors has recently emerged. Contributing to this line of work, we propose Panopticon, an

Peng Wang, Xiao-Xiao Tang, Hao-Da Wang, Noam I. Libeskind

Observational studies have reported that cosmic filaments on the megaparsec scale exhibit rotational motion. Subsequent simulation studies have shown qualitative agreement with these findings, but quantitative discrepancies remain due to differences in data and methods, which require verification. To address this issue, we adopt the same methodology as used

Evangelos Psomiadis, Ali Reza Pedram, Dipankar Maity, Panagiotis Tsiotras

This paper addresses the problem of optimizing communicated information among heterogeneous, resource-aware robot teams to facilitate their navigation. In such operations, a mobile robot compresses its local map to assist another robot in reaching a target within an uncharted environment. The primary challenge lies in ensuring that the map compression step b

Nicolas Dirnegger, Moein Malekakhlagh, Vikesh Siddhu, Ashutosh Rao

A promising quantum computing architecture comprises modules of superconducting quantum processors linked via optical channels using quantum transducers. As quantum transducer hardware improves, a need has arisen to understand the quantitative relationship between transducer-device characteristics and the strength of the resulting remote entanglement. Using

Xiao-Xiao Tang, Peng Wang, Wei Wang, Ming-Jie Sheng

In the cosmic web, filaments play a crucial role in connecting walls to clusters and also act as an important stage for galaxy formation and evolution. Recent observational studies claim that filaments have spin. In this study, we examined the potential impact of diversity in filament identification algorithms and galaxy survey datasets on the quantification

Yuhao Zhang, Xiangru Xu

Feedforward neural networks are widely used in autonomous systems, particularly for control and perception tasks within the system loop. However, their vulnerability to adversarial attacks necessitates formal verification before deployment in safety-critical applications. Existing set propagation-based reachability analysis methods for feedforward neural net

C. Wessel

The SuperKEKB accelerator and the Belle II experiment constitute the second-generation asymmetric energy B-factory. SuperKEKB has recently set a new world record in instantaneous luminosity, which is anticipated to further increase during the upcoming run periods up to $6\cdot 10^{35}\,\mathrm{cm}^{-2}\mathrm{s}^{-1}$. An increase in luminosity is challengin

So Young Lee, Russell Scheinberg, Amber Shore, Ameeta Agrawal

This study explores how recent large language models (LLMs) navigate relative clause attachment {ambiguity} and use world knowledge biases for disambiguation in six typologically diverse languages: English, Chinese, Japanese, Korean, Russian, and Spanish. We describe the process of creating a novel dataset -- MultiWho -- for fine-grained evaluation of relati

Daniele Gorla, Shivam Kumar, Pietro Nicolaus Roselli Lorenzini, Alireza Alipourfaz

This paper presents an approach to automating JUnit test generation for Java applications using the Spring Boot framework, leveraging the LLaMA (Large Language Model Architecture) model to enhance the efficiency and accuracy of the testing process. The resulting tool, called CUBETESTERAI, includes a user-friendly web interface and the integration of a CI/CD

Shrutika Singh, Anton Alyakin, Daniel Alexander Alber, Jaden Stryker

The performance of Large Language Models (LLMs) on multiple-choice question (MCQ) benchmarks is frequently cited as proof of their medical capabilities. We hypothesized that LLM performance on medical MCQs may in part be illusory and driven by factors beyond medical content knowledge and reasoning capabilities. To assess this, we created a novel benchmark of

Nawaf Alampara, Mara Schilling-Wilhelmi, Kevin Maik Jablonka

Measurements are fundamental to knowledge creation in science, enabling consistent sharing of findings and serving as the foundation for scientific discovery. As machine learning systems increasingly transform scientific fields, the question of how to effectively evaluate these systems becomes crucial for ensuring reliable progress. In this review, we examin

Kevin Li, Eric Laber

The contextual bandit framework is widely used to solve sequential optimization problems where the reward of each decision depends on auxiliary context variables. In settings such as medicine, business, and engineering, the decision maker often possesses additional structural information on the generative model that can potentially be used to improve the eff

Mark Saroufim, Yotam Perlitz, Leshem Choshen, Luca Antiga

Our analysis of the NeurIPS 2023 large language model (LLM) fine-tuning competition revealed the following trend: top-performing models exhibit significant overfitting on benchmark datasets, mirroring the broader issue of benchmark overfitting on popular leaderboards and that data curation is essential in order to get a high performing LLM. The competition,

Eslam Badr, Elira Shaska, Tony Shaska

An explicit invariant-theoretic description of the moduli space $\mathcal{M}_3^1$ of degree-three rational maps on $\mathbb{P}^1$ is developed. A cubic map $\phi$ is represented, up to conjugation, by the pair of binary forms $(f, g) \in V_4 \oplus V_2$ arising from its Clebsch--Gordan decomposition. From this representation one constructs weighted projectiv

Xiusi Li, Sékou-Oumar Kaba, Siamak Ravanbakhsh

Causal representation learning (CRL) enhances machine learning models' robustness and generalizability by learning structural causal models associated with data-generating processes. We focus on a family of CRL methods that uses contrastive data pairs in the observable space, generated before and after a random, unknown intervention, to identify the latent c

Fangqing Xiao, Zunqi Li, Dirk Slock

Integrated Sensing and Communication (ISAC) systems combine sensing and communication functionalities within a unified framework, enhancing spectral efficiency and reducing costs by utilizing shared hardware components. This paper investigates multipath component power delay profile (MPCPDP)-based joint range and Doppler estimation for Affine Frequency Divis

Parisa Boodaghi Malidarreh, Jillur Rahman Saurav, Thuong Le Hoai Pham, Amir Hajighasemi

Vector Quantization (VQ) techniques face significant challenges in codebook utilization, limiting reconstruction fidelity in image modeling. We introduce a Dual Codebook mechanism that effectively addresses this limitation by partitioning the representation into complementary global and local components. The global codebook employs a lightweight transformer

Giulio Cordova, Elena Graverini, Daniele Passaro, Michael J. Morello

The increasing computing power and bandwidth of FPGAs opens new possibilities in the field of real-time processing of high-energy physics data. The LHCb experiment has implemented a cluster-finder FPGA architecture aimed at reconstructing hits in its innermost silicon-pixel detector on-the-fly during readout. In addition to accelerating the event reconstruct

Mustafa Cavus, Katarzyna Woźnica, Przemysław Biecek

This paper investigates the critical role of hyperparameters in predictive multiplicity, where different machine learning models trained on the same dataset yield divergent predictions for identical inputs. These inconsistencies can seriously impact high-stakes decisions such as credit assessments, hiring, and medical diagnoses. Focusing on six widely used m

Argyrios Deligkas, Eduard Eiben, Stavros D. Ioannidis, Dušan Knop

In the recently introduced model of fair partitioning of friends, there is a set of agents located on the vertices of an underlying graph that indicates the friendships between the agents. The task is to partition the graph into $k$ balanced-sized groups, keeping in mind that the value of an agent for a group equals the number of edges they have in that grou

Matthew D. Kvalheim

We study the topology of the space of all smooth asymptotically stable vector fields on $\mathbb{R}^n$, as well as the space of all proper smooth Lyapunov functions for such vector fields. We prove that both spaces are path-connected and simply connected when $n\neq 4,5$ and weakly contractible when $n\leq 3$. Moreover, both spaces have the weak homotopy typ

Martin Larsson, Jonghwa Park, Johannes Wiesel

Estimating a $d$-dimensional distribution $\mu$ by the empirical measure $\hat{\mu}_n$ of its samples is an important task in probability theory, statistics and machine learning. It is well known that $\mathbb{E}[\mathcal{W}_p(\hat{\mu}_n, \mu)]\lesssim n^{-1/d}$ for $d>2p$, where $\mathcal{W}_p$ denotes the $p$-Wasserstein metric. An effective tool to comba

Caleb M. Shor, Jae Hyung Sim

In 2008, Wang \& Wang showed that the set of gaps of a numerical semigroup generated by two coprime positive integers $a$ and $b$ is equidistributed modulo 2 precisely when $a$ and $b$ are both odd. Shor generalized this in 2022, showing that the set of gaps of such a numerical semigroup is equidistributed modulo $m$ when $a$ and $b$ are coprime to $m$ and a

Hridoy Debnath, Pavel Fileviez Perez

We discuss the predictions in the simplest theory for neutrino masses based on the spontaneous breaking of local lepton number. This theory provides a simple theoretical framework to understand the possible relation between the origin of neutrino masses and the nature of the dark matter. In this theory, one of the fields needed for anomaly cancellation is a

Leonidas Gkimisis, Igor Pontes Duff, Pawan Goyal, Peter Benner

In this work, we investigate a skew-symmetric parameterization for energy-preserving quadratic operators. Earlier, [Goyal et al., 2023] proposed this parameterization to enforce energy-preservation for quadratic terms in the context of dynamical system data-driven inference. We here prove that every energy-preserving quadratic term can be equivalently formul

Christos Argyropoulos, Hamza Mir, Maria-Eleni Roumelioti, Pablo Garcia

Analyses of time to event datasets have been invariably based on the Cox proportional hazards model (PHM). Reformulations of the PHM as a Poisson Generalized Additive Model (GAM) or as a Generalized Linear Mixed Model (GLMM) have been proposed in the literature, aiming to increase the flexibility of the PHM and allow its use in situations in which complex sp

Johannes Buchner

The aim of this paper is to discuss the potential of using methods from Reinforcement Learning for Life Cycle Assessment in a circular economy, and to present some new ideas in this direction. To give some context, we explain how Reinforcement Learning was successfully applied in computer chess (and beyond). As computer chess was historically called the "dro

Markus Dertwinkel-Kalt, Max R. P. Grossmann

When environmental regulations are unpopular, policymakers often attribute resistance to information frictions and poor communication. We test this idea in the context of a major climate policy: Germany's Heating Law of 2023, which mandates the phase-out of fossil fuel heating. Through a survey experiment with property owners, we examine whether providing co

C. L. Carilli, L. Torino, B. Nikolic, N. Thyagarajan

Wave front sensing of the surface of equal phase for a propagating electromagnetic wave is a vital technology in fields ranging from real time adaptive optics, to high accuracy metrology, to medical optometry. We have developed a new method of wavefront sensing that makes a direct measurement of the electromagnetic phase distribution, or path-length delay, a

Orna Kupferman, Ofer Leshkowitz

In the synthesis problem, we are given a specification, and we automatically generate a system that satisfies the specification in all environments. We introduce and study {\em synthesis with guided environments} (SGE, for short), where the system may harness the knowledge and computational power of the environment during the interaction. The underlying idea

Robert F. Catuto, Hsing-Ta Chen

Strong light-matter interactions between molecules and quantized electromagnetic fields inside an optical cavity open up novel possibilities, though inevitably influenced by disorder, an inherent attribute of realistic molecular systems. Here, we explore the steady-state optical response of molecular emitters within a lossy cavity, with a focus on the combin

Gisya Abdi, Tomasz Mazur, Ewelina Kowalewska, Andrzej Sławek

This study explores the impact of organic cations in bismuth iodide complexes on their memristive behavior in metal-insulator-metal (MIM) type thin-layer devices. The presence of electron-donating and electron withdrawing functional groups (-CN, -CH3, -NH2, and -N(CH3)2) on pyridinium cations induces morphological alterations in crystals, thus influencing th

Earnest Akofor

Let $X$ be a metric space and $BCl(X)$ the collection of nonempty bounded closed subsets of $X$. We show that Hausdorff distance $d_H$ belongs to a specific family of real-valued distances on $BCl(X)$, each of which can be expressed as the composition $\mu\circ d_{sv}$ of a topology inducing set-valued function $d_{sv}:BCl(X)^2\rightarrow \mathcal{P}(Z)$ and

Mengqi Lou, Kabir Aladin Verchand, Sara Fridovich-Keil, Ashwin Pananjady

We consider the problem of signal reconstruction for computed tomography (CT) under a nonlinear forward model that accounts for exponential signal attenuation, a polychromatic X-ray source, general measurement noise (e.g., Poisson shot noise), and observations acquired over multiple wavelength windows. We develop a simple iterative algorithm for single-mater

Dibyanayan Bandyopadhyay, Soham Bhattacharjee, Asif Ekbal

Large Language Models (LLMs) are highly proficient in language-based tasks. Their language capabilities have positioned them at the forefront of the future AGI (Artificial General Intelligence) race. However, on closer inspection, Valmeekam et al. (2024); Zecevic et al. (2023); Wu et al. (2024) highlight a significant gap between their language proficiency a

J. W. Moffat

An approach is presented to resolve key paradoxes in black hole physics through the application of complex Riemannian spacetime. We extend the Schwarzschild metric into the complex domain, employing contour integration techniques to remove singularities while preserving essential features of the original solution. A new regularized radial coordinate is intro

Meriem Behiri, Elizabeth Mahony, Elaine Sadler, Emily Kerrison

This work investigates the multi-wavelength properties of 165 4FGL blazars from the Fermi-LAT fourth source catalogue, looking for with counterparts in the Australian SKA Pathfinder (ASKAP) First Large Absorption Survey in HI (FLASH) continuum. Using high-resolution data from FLASH and complementary radio datasets, combined with archival Atacama Large Millim

Robin van Bijleveld, Eric Laenen, Coenraad Marinissen, Leonardo Vernazza

We investigate the factorization properties of the massive fermion form factor in QED, to next-to-leading power in the fermion mass, and up to two-loop order. For this purpose we define new jet functions that have multiple connections to the hard part as operator matrix elements, and compute them to second order in the coupling. We test our factorization for

Lukas Aichberger, Alasdair Paren, Guohao Li, Philip Torr

Recent advances in operating system (OS) agents have enabled vision-language models (VLMs) to directly control a user's computer. Unlike conventional VLMs that passively output text, OS agents autonomously perform computer-based tasks in response to a single user prompt. OS agents do so by capturing, parsing, and analysing screenshots and executing low-level

Martina Nibbi, Luca Frediani, Evgueni Dinvay, Christian B. Mendl

The density matrix renormalization group (DMRG) is a powerful numerical technique to solve strongly correlated quantum systems: it deals well with systems which are not dominated by a single configuration (unlike Coupled Cluster) and it converges rapidly to the Full Configuration Interaction (FCI) limit (unlike truncated Configuration Interaction (CI) expans

Tianyi Zhou

In this paper, we will prove alternate conditions for a type-$III$ Bernoulli scheme to be of type-$III_0$, type-$III_{\lambda}$ and type-$III_1$, and then conclude an alternate definition of the asymptotic ratio set of a type-$III$ ITPFI factor.

Amlan Chakraborty, Prolay K. Chanda, Subinoy Das, Koushik Dutta

We investigate a scenario where a dark energy quintessence field $\phi$ with positive kinetic energy is coupled with dark matter. With two different self-interaction potentials for the field and a particular choice of the coupling function, we show explicitly how the observable effective equation of state parameter $w_{\rm eff}$ for the dark energy field cro

Chiara Cecchini, Gabriele Franciolini, Mauro Pieroni

Pulsar Timing Arrays are playing a crucial role in the ongoing gravitational wave astronomy revolution. The current evidence for a stochastic gravitational wave background (SGWB) at nHz frequencies offers an opportunity to discover cosmological signals and threatens the observability of other subdominant GWs. We explore prospects to constrain second-order sc

A. J. Cooper, J. H. Matthews, F. Carotenuto, R. Fender

Black hole X-ray binaries in outburst launch discrete, large-scale jet ejections which can propagate to parsec scales. The kinematics of these ejecta appear to be well described by relativistic blast wave models original devised for gamma-ray burst afterglows. In previous kinematic-only modelling, a crucial degeneracy prevented the initial ejecta energy and

Earnest Akofor

Let $X$ be a (topological) space and $Cl(X)$ the collection of nonempty closed subsets of $X$. Given a topology on $Cl(X)$, making $Cl(X)$ a space, a (subset) hyperspace of $X$ is a subspace $\mathcal{J}\subset Cl(X)$ with an embedding $X\hookrightarrow\mathcal{J}$, $x\mapsto\{x\}$. In this note, we characterize certain hyperspaces $\mathcal{J}\subset Cl(X)$

James H. Matthews, Alex J. Cooper, Lauren Rhodes, Katherine Savard

Blast wave models are commonly used to model relativistic outflows from ultra-relativistic gamma-ray bursts (GRBs), but are also applied to lower Lorentz factor ejections from X-ray binaries (XRBs). Here we revisit the physics of blast waves and reverse shocks in these systems and explore the similarities and differences between the ultra-relativistic ($\Gam

Birte Ostermann, Taylor Garnowski, Fabian Henze, Vaibhavnath Jha

Quadratic unconstrained binary optimization problems (QUBOs) are intensively discussed in the realm of quantum computing and polynomial optimization. We provide a vast experimental study of semidefinite programming (SDP) relaxations of QUBOs using sums of squares methods and on Hamiltonian Updates. We test on QUBO reformulations of industry-based instances o

Nathalie A. Korhonen Cuestas, Allison L. Strom, Tim B. Miller, Charles C. Steidel

The metal enrichment of a galaxy is determined by the cycle of baryons in outflows, inflows, and star formation. The relative contribution and timescale of each process sets the relationship between stellar mass, metallicity, and the star formation rate (SFR). In the local universe, galaxies evolve in an equilibrium state where the timescales on which SFR an

Sajad Movahedi, Felix Sarnthein, Nicola Muca Cirone, Antonio Orvieto

Linear recurrent neural networks (RNNs) and state-space models (SSMs) such as Mamba have become promising alternatives to softmax-attention as sequence mixing layers in Transformer architectures. Current models, however, do not exhibit the full state-tracking expressivity of RNNs because they rely on channel-wise (i.e. diagonal) sequence mixing. In this pape

Simran K. Nerval, Erika Hornecker, Yilun Guan, Zeling Zhang

We present a new pipeline utilizing machine learning for classifying short-duration features in raw time-ordered data (TOD) of cosmic microwave background survey observations. The pipeline, specifically designed for the Atacama Cosmology Telescope, works in conjunction with the previous TOD preprocessing techniques that employ statistical thresholding to ind

Rodrigo Jaeschke-Ubiergo, Venkata-Krishna Bharadwaj, Warlley Campos, Ricardo Zarzuela

Altermagnetism has been recently experimentally verified by photoemission mapping of the spin order in momentum space in MnTe and CrSb, which feature two anisotropic sublattices with antiparallel magnetic dipole moments. In this work, we explicitly demonstrate the presence of an even-parity ferroically ordered non-dipolar spin density on the atomic sites, i.

Lukas Johannes Breitwieser

Agent-based modeling is indispensable for studying complex systems across many domains. However, existing simulation platforms exhibit two major issues: performance and modularity. Low performance prevents simulations with a large number of agents, increases development time, limits parameter exploration, and raises computing costs. Inflexible software desig

Paul Simeon, Noémie Globus, Kirk S. S. Barrow, Roger Blandford

We propose that a hierarchical shock model$\unicode{x2014}$including supernova remnant shocks, galactic wind termination shocks, and accretion shocks around cosmic filaments and galaxy clusters$\unicode{x2014}$can naturally explain the cosmic ray spectrum from ~1 GeV up to ~200 EeV. While this framework applies to the entire cosmic ray spectrum, in this work

Ashley Suh, Isabelle Hurley, Nora Smith, Ho Chit Siu

This late-breaking work presents a large-scale analysis of explainable AI (XAI) literature to evaluate claims of human explainability. We collaborated with a professional librarian to identify 18,254 papers containing keywords related to explainability and interpretability. Of these, we find that only 253 papers included terms suggesting human involvement in

Yu Luo, Han Zhou, Mengtao Zhang, Dylan De La Rosa

As an emerging programming language, Rust has rapidly gained popularity and recognition among developers due to its strong emphasis on safety. It employs a unique ownership system and safe concurrency practices to ensure robust safety. Despite these safeguards, security in Rust still presents challenges. Since 2018, 442 Rust-related vulnerabilities have been

Esmail Gumaan

Training multi-billion to trillion-parameter language models efficiently on GPU clusters requires leveraging multiple parallelism strategies. We present Galvatron, a novel open-source framework (dubbed 'Optimus-Megatron' in the implementation) that dynamically combines data parallelism, tensor model parallelism, and pipeline parallelism to optimize training

Yufei Xia, Wenrui Yu, Qiongxiu Li

Byzantine attacks present a critical challenge to Federated Learning (FL), where malicious participants can disrupt the training process, degrade model accuracy, and compromise system reliability. Traditional FL frameworks typically rely on aggregation-based protocols for model updates, leaving them vulnerable to sophisticated adversarial strategies. In this

Jaewon Lee, Sung Hun Park, Jangwon Kim, Kyung Hun Rho

Superradiance, first proposed by Dicke in 1954, is a highly efficient quantum light source that differs from conventional spontaneous emission. Unlike typical spontaneous emission, where intensity scales linearly with the number of electric dipoles, superradiance exhibits an intensity that scales quadratically with the number of electric dipoles. Similarly,

Tom Ginsberg, Vyom Patel

Quantum error detection (QED) offers a promising pathway to fault tolerance in near-term quantum devices by balancing error suppression with minimal resource overhead. However, its practical utility hinges on optimizing design parameters-such as syndrome measurement frequency-to avoid diminishing returns from detection overhead. In this work, we present a co

Nicholas Deas, Blake Vente, Amith Ananthram, Jessica A. Grieser

With a combination of quantitative experiments, human judgments, and qualitative analyses, we evaluate the quantity and quality of African American Language (AAL) representation in 12 predominantly English, open-source pretraining corpora. We specifically focus on the sources, variation, and naturalness of included AAL texts representing the AAL-speaking com

Saptati Datta

Partial correlation coefficients are widely applied in the social sciences to evaluate the relationship between two variables after accounting for the influence of others. In this article, we present Bayes Factor Functions (BFFs) for assessing the presence of partial correlation. BFFs represent Bayes factors derived from test statistics and are expressed as

Yifeng Cai

This paper introduces a Delaunay triangulation algorithm based on the external incremental method. Unlike traditional random incremental methods, this approach uses convex hull and points as basic operational units instead of triangles. Since each newly added point is outside the convex hull, there is no need to search for which triangle contains the point,

Dylan Burke, Geoffrey Cuff-Chartrand, Malors Espinosa, Mateusz Kazimierczak

In this paper we study knots created by galleries in the affine Coxeter complex of type \widewedge{B3}. We bound the stick number by 40 and prove that the smallest length of threefold rotationally symmetric trefoils is 42. We construct explicit galleries that knot as 9_35, 9_40, 9_41 and 9_47 in a way that has threefold rotational symmetry. We explain the co

Norbert Tihanyi, Tamas Bisztray, Mohamed Amine Ferrag, Bilel Cherif

Software testing and verification are critical for ensuring the reliability and security of modern software systems. Traditionally, formal verification techniques, such as model checking and theorem proving, have provided rigorous frameworks for detecting bugs and vulnerabilities. However, these methods often face scalability challenges when applied to compl

Nils Marggraf-Turley, Martha Shiell, Niels Pontoppidan, Drew Cappotto

Sound source localization relies on spatial cues such as interaural time differences (ITD), interaural level differences (ILD), and monaural spectral cues. Individually measured Head-Related Transfer Functions (HRTFs) facilitate precise spatial hearing but are impractical to measure, necessitating non-individual HRTFs, which may compromise localization accur

Ashwin K Seshadri, S Lakshmivarahan

Coupled gyrostat low-order models (GLOMs) are energy-conserving cores of Galerkin-truncated fluid and geophysical systems, including Rayleigh-Benard convection and vorticity dynamics. A single gyrostat always possesses two quadratic invariants; when gyrostats are coupled, the number and geometry of invariants vary sensitively with model configuration, influe

Evangelos Kazakos, Cordelia Schmid, Josef Sivic

We propose a novel approach for captioning and object grounding in video, where the objects in the caption are grounded in the video via temporally dense bounding boxes. We introduce the following contributions. First, we present a large-scale automatic annotation method that aggregates frame-level captions grounded with bounding boxes into temporally dense

James M. Shook, Isabel Beichl

For a digraph $G$, a set $F\subseteq V(G)$ is said to be a feedback vertex set (FVS) if $G-F$ is acyclic. The problem of finding a smallest FVS is NP-hard. We present a matrix scaling technique for finding feedback vertex sets in un-weighted directed graphs that runs in $O(|F|\log(|V|)|V|^{2})$ time. Our technique is empirically shown to produce smaller feed

Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal, James J. Little

Large-scale vision-language models (VLMs), trained on extensive datasets of image-text pairs, exhibit strong multimodal understanding capabilities by implicitly learning associations between textual descriptions and image regions. This emergent ability enables zero-shot object detection and segmentation, using techniques that rely on text-image attention map

Vignesh Jagathese

We introduce an analogue to Quasi-$F$-splittings, Quasi-$F$-purity, which is definable over rings that are not necessarily $F$-finite. We show that this property is equivalent to being Quasi-$F$-split in the complete local and $F$-finite case. We then exhibit that it is stable under completion, direct limit, and local/finite \'etale extension.

Zhang Zhang, Chao Sun, Chao Yue, Da Wen

Roadside vision centric 3D object detection has received increasing attention in recent years. It expands the perception range of autonomous vehicles, enhances the road safety. Previous methods focused on predicting per-pixel height rather than depth, making significant gains in roadside visual perception. While it is limited by the perspective property of n

Yang Dan, Dallas R. Trinkle

We use first-principles spin-polarized energy density method (EDM) to calculate the atomic energies in isolated $a_0[100](010)$ edge, $a_0[100](011)$ edge, $\frac{a_0}{2}[\bar1\bar11](1\bar10)$ edge and $\frac{a_0}{2}[111](1\bar10)$ $71^\circ$ mixed dislocations in body-centered cubic (BCC) Fe. The distribution of atomic energies shows the energetic effects

Scott A. Manifold, George B. Long, Jonathan J. Burnett

Large-scale cryogenic Input-Output (IO) infrastructure is a requirement for realising fault-tolerant quantum computing in solid-state modalities. Such IO scaling presents significant challenges in thermal modelling, hardware design and verification. Here we present a design tool for cryogenic platform development with applicability to quantum computing and o

Harald Garcke, Robert Nürnberg, Simon Praetorius, Ganghui Zhang

We propose higher-order isoparametric finite element approximations for mean curvature flow and surface diffusion. The methods are natural extensions of the piecewise linear finite element methods introduced by Barrett, Garcke, and N\"urnberg (BGN) in a series of papers in 2007 and 2008. The proposed schemes exhibit unconditional energy stability and inherit

Jet Lem, Yun Kai, Maxime Vassaux, Steven E. Kooi

Exploring shock-shock interactions has been limited by experimental constraints, particularly in laser-induced shock experiments due to specialized equipment requirements. Herein, we introduce a tabletop approach to systematically investigate the excitation and superposition of dual laser-induced shock waves in water. Utilizing two laser pulses, spatio-tempo

Yingqi Gao, Wenlu Xu, Jin J. Zhou, Hua Zhou

As data marketplaces become increasingly central to the digital economy, it is crucial to design efficient pricing mechanisms that optimize revenue while ensuring fair and adaptive pricing. We introduce the Maximum Auction-to-Posted Price (MAPP) mechanism, a novel two-stage approach that first estimates the bidders' value distribution through auctions and th

Ju He, Qihang Yu, Qihao Liu, Liang-Chieh Chen

Bridging different modalities lies at the heart of cross-modality generation. While conventional approaches treat the text modality as a conditioning signal that gradually guides the denoising process from Gaussian noise to the target image modality, we explore a much simpler paradigm-directly evolving between text and image modalities through flow matching.

Jasmin Bedow, Dirk K. Morr

Executing quantum algorithms using Majorana zero modes - a major milestone for the field of topological quantum computing - requires a platform that can be scaled to large quantum registers, can be controlled in real time and space, and a braiding protocol that uses the unique properties of these exotic particles. Here, we demonstrate the first successful si

E. C. Schösser, V. Ramachandran, A. A. C. Sander, J. S. Gallagher

To study stars analogous to those in the early Universe with redshift z > 3, we need to probe environments with low metallicities. Until recently, massive O-type stars with metallicities lower than that of the Small Magellanic Cloud (SMC, Z < 20%Z_sol) were only known in compact dwarf galaxies. Observations of stars in such distant galaxies (> 1 Mpc) suffer

Ella Werre, David Robinson, Camille Avestruz, Nickolay Y. Gnedin

Quasar absorption lines provide a unique window to the relationship between galaxies and the intergalactic medium during the Epoch of Reionization. In particular, high redshift quasars enable measurements of the neutral hydrogen content of the universe. However, the limited sample size of observed quasar spectra, particularly at the highest redshifts, hamper

Norbert Schuch, Andras Molnar, David Perez-Garcia

Matrix Product States (MPS) and Tensor Networks provide a general framework for the construction of solvable models. The best-known example is the Affleck-Kennedy-Lieb-Tasaki (AKLT) model, which is the ground state of a 2-body nearest-neighbor parent Hamiltonian. We show that such simple parent Hamiltonians for MPS models are, in fact, much more prevalent th

Hyunsu Kong, Michael Boylan-Kolchin, James S. Bullock

Modern studies of galaxy formation rely heavily on numerical simulations, which in turn require tools to identify and track self-bound structures in stars and dark matter. In this paper, we present Bloodhound, a new halo tracking algorithm optimized to track and characterize substructure in cosmological simulations, a regime that is crucial for studies of th

Steve B. Howell, Clara E. Martínez-Vázquez, Elise Furlan, Nicholas J. Scott

Since its inception, speckle interferometry has revolutionized high-resolution astronomical imaging, overcoming atmospheric challenges to achieve the diffraction limits of telescopes. Almost a decade ago, in 2018, a pair of speckle cameras -- 'Alopeke and Zorro -- were installed at the twin 8.1-meter Gemini North and South telescopes, two of the largest aper

Shreya Vardhan, Bowen Shi, Isaac H. Kim, Yijian Zou

We introduce a notion of chirality for generic quantum states. A chiral state is defined as a state which cannot be transformed into its complex conjugate in a local product basis using local unitary operations. We introduce a number of quantitative measures of chirality which vanish for non-chiral states. A faithful measure called the "chiral log-distance"

Liang Mao, Fan Yang

Symmetry classification is crucial in understanding universal properties of quantum matter. Recently, the scope of symmetry classification has been extended to open quantum systems governed by the Lindblad master equation. However, the classification of Lindbladians and steady states remains largely separate. Because the former requires the non-Hermitian cla

Colburn Cobb-Bruno, Hendrik Utzat

We theoretically propose a new method in cavity- and surface-enhanced Raman spectroscopy (SERS) with improved temporal resolution in the measurement of stochastic Raman spectral fluctuations. Our approach combines Fourier spectroscopy and photon correlation to decouple the integration time from the temporal resolution. Using statistical optics simulations, w

Aiden Daniel, Tanmay Bhore, Jiannis K. Pachos, Chang Liu

The quantum description of a black hole predicts that quantum information hidden behind the event horizon can be teleported outside almost instantaneously. In this work, we demonstrate that a chiral spin-chain model, which naturally simulates a binary black hole system, can realise this teleportation process. Our system captures two essential components of t

Nico A. Hackner, Peizhi Mai, Philip W. Phillips

We show that the physics of the SU($N$) Hubbard model can be realistically simulated with the recently developed orbital Hatsugai-Kohmoto model. In this approach, the momentum mixing absent from the band Hatsugai-Kohmoto model is included by grouping $n$-Hubbard atoms into a cluster. We take advantage of the rapid convergence of this scheme ($1/n^2$) and sho

Asaf Joseph, Shmuel Peleg

Clothes-Changing Person Re-Identification (ReID) aims to recognize the same individual across different videos captured at various times and locations. This task is particularly challenging due to changes in appearance, such as clothing, hairstyle, and accessories. We propose a Clothes-Changing ReID method that uses only skeleton data and does not use appear

Mohamad Shalaby, Antoine Bret, Federico Fraschetti

Collisionless electron-ion shocks are fundamental to astrophysical plasmas, yet their behavior in strong magnetic fields remains poorly understood. Using Particle-in-Cell (PIC) simulations with the SHARP-1D3V code, we investigate the role of the ion magnetization parameter $\sigma_i$ in parallel shock transitions. Strongly magnetized converging flows ($\sigm

Nicolás Bernal, Quan-feng Wu, Xun-Jie Xu, Yong Xu

We investigate a novel gravitational wave (GW) production mechanism from gravitons generated during the pre-thermal phase of cosmic reheating, where the energy density is dominated by non-thermalized inflaton decay products, dubbed reheatons. We consider multiple production channels, including: $i)$ pure inflaton-inflaton annihilation, $ii)$ graviton Bremsst