March 2025 arXiv papers — page 46

Somnath Basu Roy Chowdhury, Avinava Dubey, Ahmad Beirami, Rahul Kidambi

Concept erasure is the task of erasing information about a concept (e.g., gender or race) from a representation set while retaining the maximum possible utility -- information from original representations. Concept erasure is useful in several applications, such as removing sensitive concepts to achieve fairness and interpreting the impact of specific concep

Robert de Mello Koch, Antal Jevicki

The space of invariants for a single matrix is generated by traces containing at most $N$ matrices per trace. We extend this analysis to multi-matrix models at finite $N$. Using the Molien-Weyl formula, we compute partition functions for various multi-matrix models at different $N$ and interpret them through trace relations. This allows us to identify a comp

Zachary Mullaghy

This work introduces a novel and general class of continuous transforms based on hierarchical Voronoi based refinement schemes. The resulting transform space generalizes classical approaches such as wavelets and Radon transforms by incorporating parameters of refinement multiplicity, dispersion, and rotation. We rigorously establish key properties of the tra

Stanislav Semenov

All constructive methods employed in modern mathematics produce only countable sets, even when designed to transcend countability. We show that any constructive argument for uncountability -- excluding diagonalization techniques -- effectively generates only countable fragments within a closed formal system. We formalize this limitation as the "fractal bound

Tom Benhamou, Gabriel Goldberg

A simple \(P_\lambda\)-point on a regular cardinal \(\kappa\) is a uniform ultrafilter on \(\kappa\) with a mod-bounded decreasing generating sequence of length \(\lambda\). We prove that if there is a simple $P_\lambda$-point ultrafilter over $\kappa>\omega$, then $\lambda=\mathfrak{d}_\kappa=\mathfrak{b}_\kappa=\mathfrak{u}_\kappa=\mathfrak{r}_\kappa=\math

Nimesha Wickramasinghe, Arash Shaghaghi, Gene Tsudik, Sanjay Jha

The adoption of modern encryption protocols such as TLS 1.3 has significantly challenged traditional network traffic classification (NTC) methods. As a consequence, researchers are increasingly turning to machine learning (ML) approaches to overcome these obstacles. In this paper, we comprehensively analyze ML-based NTC studies, developing a taxonomy of thei

Sergio Santos, Zakari Kujala, Sungyon Lee, Stefano Gonella

Drops on a vibrating substrate can experience a variety of motion regimes, including directional motion and climbing. The key ingredient to elicit these regimes is simultaneously activating the in-plane and out-of-plane degrees of freedom of the substrate with the proper phase difference. This is typically achieved by using a rigid substrate and two independ

Michael Suleymanov, Avishy Carmi, Eliahu Cohen

Viewing frames of reference as physical systems, subject to the same laws as the systems they describe, is central to the relational approach in physics. Under the assumption that quantum mechanics universally governs all physical entities, this perspective naturally leads to the concept of quantum reference frames (QRFs). We investigate the perspective-depe

Kai Nylund, Jennifer Mankoff, Venkatesh Potluri

We present MatplotAlt, an open-source Python package for easily adding alternative text to Matplotlib figures. MatplotAlt equips Jupyter notebook authors to automatically generate and surface chart descriptions with a single line of code or command, and supports a range of options that allow users to customize the generation and display of captions based on

Sophie Hao

Chesi's (forthcoming) target paper depicts a generative linguistics in crisis, foreboded by Piantadosi's (2023) declaration that "modern language models refute Chomsky's approach to language." In order to survive, Chesi warns, generativists must hold themselves to higher standards of formal and empirical rigor. This response argues that the crisis described

Dmitry B. Rokhlin, Olga V. Gurtovaya

We introduce a novel multi-kernel learning algorithm, VAW$^2$, for online least squares regression in reproducing kernel Hilbert spaces (RKHS). VAW$^2$ leverages random Fourier feature-based functional approximation and the Vovk-Azoury-Warmuth (VAW) method in a two-level procedure: VAW is used to construct expert strategies from random features generated for

Sarah A. MacQueen, Clara F. Hardy, W. John Braun, Rebecca C. Tyson

Foraging site constancy, or repeated return to the same foraging location, is a foraging strategy used by many species to decrease uncertainty, but it is often unclear exactly how the foraging site is identified. Here we focus on the context where food harvesting is first preceded by a separate exploration period. Foraging then consists of three distinct ste

Soumaya Elkantassi, Valérie Chavez-Demoulin, Anthony C. Davison, Matthew D. Hejduk

Satellite conjunctions involving near misses of space objects are increasingly common, especially with the growth of satellite constellations and space debris. Accurate risk analysis for these events is essential to prevent collisions and manage space traffic. Traditional methods for assessing collision risk, such as calculating the so-called collision proba

Tianze Chen, Ricardo Frumento, Giulia Pagnanelli, Gianmarco Cei

In this work, we describe a multi-object grasping benchmark to evaluate the grasping and manipulation capabilities of robotic systems in both pile and surface scenarios. The benchmark introduces three robot multi-object grasping benchmarking protocols designed to challenge different aspects of robotic manipulation. These protocols are: 1) the Only-Pick-Once

Simiao Ren, Yao Yao, Kidus Zewde, Zisheng Liang

Deepfake detection remains a critical challenge in the era of advanced generative models, particularly as synthetic media becomes more sophisticated. In this study, we explore the potential of state of the art multi-modal (reasoning) large language models (LLMs) for deepfake image detection such as (OpenAI O1/4o, Gemini thinking Flash 2, Deepseek Janus, Grok

Benjamin Minixhofer, Ivan Vulić, Edoardo Maria Ponti

Distillation has shown remarkable success in transferring knowledge from a Large Language Model (LLM) teacher to a student LLM. However, current distillation methods require similar tokenizers between the teacher and the student, restricting their applicability to only a small subset of teacher-student pairs. In this work, we develop a principled cross-token

Henry D. van Eijk, Sujit K. Ghosh

Forecasting revenues by aggregating analyst forecasts is a fundamental problem in financial research and practice. A key objective in this context is to improve the accuracy of the forecast by optimizing two performance metrics: the hit rate, which measures the proportion of correctly classified revenue surprise signs, and the win rate, which quantifies the

Anna Ciurlo, Mark R. Morris

This chapter provides a detailed overview of Sagittarius A* (Sgr A*), the supermassive black hole at the center of the Milky Way, located in the dense Galactic Center region approximately 8 kpc from Earth. Despite its relatively low activity compared to more luminous active galactic nuclei, Sgr A* has provided invaluable insights into black hole physics due

Durvudkhan Suragan, Muhammad Asad Zaighum

This paper introduces the concept of grand net spaces, a new framework that provides a unified setting for studying various function spaces. Building on the seminal works of [8] and [15], we define grand net spaces and establish their key properties, including embedding results, norm equivalences, and interpolation theorems. We prove that these spaces coinci

Mohomed Thariq, Indrajith Ekanayake

Distributed systems widely adopt microservice architecture to handle growing complexity and scale. This approach breaks applications into independent, loosely coupled services. Kubernetes has become the de facto standard for managing microservices, and automating complex, multi-step workflows is a common requirement in Kubernetes. Argo Workflows is a Kuberne

Volkan Ustun, Soham Hans, Rajay Kumar, Yunzhe Wang

Multi-agent reinforcement learning (MARL) is increasingly ubiquitous in training dynamic and adaptive synthetic characters for interactive simulations on geo-specific terrains. Frameworks such as Unity's ML-Agents help to make such reinforcement learning experiments more accessible to the simulation community. Military training simulations also benefit from

Arwa Bukhari, Daniel Hodgson, Sara Kanzi, Robert Purdy

To enhance the consistency between the quantum descriptions of waves and particles, we quantise mechanical point particles in this paper in the same physically-motivated way as we previously quantised light in quantum electrodynamics [Bennett et al., Eur. J. Phys. 37, 014001 (2016)]. To identify the relevant Hilbert space, we notice that mechanical particles

Ajitesh Srivastava, Aryan Shetty, Eric Rice

Studying peer relationships is crucial in solving complex challenges underserved communities face and designing interventions. The effectiveness of such peer-based interventions relies on accurate network data regarding individual attributes and social influences. However, these datasets are often collected through self-reported surveys, introducing ambiguit

Zdzisław Brzeźniak, Mikhail Neklyudov, Evelina Shamarova

We prove the existence of solution to the following $\mathbb{C}^3$-valued singular SPDE on the 2D torus $\mathbb{T}^2$: \begin{align} \label{CR} \partial_{\bar z} r = r \times \overline{r} + i \, \gamma \, {\mathscr W}, \tag{CR} \end{align} where $\partial_{\bar z}: = \frac12(\partial_x + i \partial_y)$ is the Cauchy-Riemann operator on $\mathbb{T}^2$, ${\ma

Yahav Biran, Imry Kissos

The surge in generative AI workloads has created a need for scalable inference systems that can flexibly harness both GPUs and specialized accelerators while containing operational costs. This paper proposes a hardware-agnostic control loop that adaptively allocates requests across heterogeneous accelerators based on real-time cost and capacity signals. The

Dunja Simicic, Katarzyna Pierzchala, Olivier Braissant, Dario Sessa

Background & Aims: Patients with type C hepatic encephalopathy (HE) present diverse symptoms indicating that various brain regions are affected. Understanding the distinct metabolic and cellular changes across these regions could help explain the clinical variability of HE. We analyzed, for the first time, the longitudinal in-vivo neurometabolic and morpholo

Philip Kennerberg, Ernst C. Wit

Statistical learning methods typically assume that the training and test data originate from the same distribution, enabling effective risk minimization. However, real-world applications frequently involve distributional shifts, leading to poor model generalization. To address this, recent advances in causal inference and robust learning have introduced stra

Abhibhav Garg, Rafael Oliveira, Nitin Saxena

A central question in mathematics and computer science is the question of determining whether a given ideal $I$ is prime, which geometrically corresponds to the zero set of $I$, denoted $Z(I)$, being irreducible. The case of principal ideals (i.e., $m=1$) corresponds to the more familiar absolute irreducibility testing of polynomials, where the seminal work

Shaun Baek, Shaun Esua-Mensah, Cyrus Tsui, Sejan Vigneswaralingam

Large Language Models (LLMs) are primarily trained on high-resource natural languages, limiting their effectiveness in low-resource settings and in tasks requiring deep logical reasoning. This research introduces Rosetta-PL, a benchmark designed to evaluate LLMs' logical reasoning and generalization capabilities in a controlled environment. We construct Rose

Yoav Mairovich, Ariel Matzliach, Idan S. Wallerstein, Himadri R. Dakua

The discovery of superconductivity in nickelates has generated significant interest in condensed matter physics. Nickelate superconductors, which are hole-doped within the layered structure of RNiO$_2$, share structural similarities with high-$T_c$ cuprate superconductors. However, despite similarities in formal valence and crystal symmetry, the fundamental

Allyson Bieryla, Jiayin Dong, George Zhou, Jason D. Eastman

We report the discovery and characterization of TOI-2005b, a warm Jupiter on an eccentric (e~0.59), 17.3-day orbit around a V_mag = 9.867 rapidly rotating F-star. The object was detected as a candidate by TESS and the planetary nature of TOI-2005b was then confirmed via a series of ground-based photometric, spectroscopic, and diffraction-limited imaging obse

Naitik Jain, Amogh Joshi, Mason Earles

Accurate identification of crop and weed species is critical for precision agriculture and sustainable farming. However, it remains a challenging task due to a variety of factors -- a high degree of visual similarity among species, environmental variability, and a continued lack of large, agriculture-specific image data. We introduce iNatAg, a large-scale im

Tim Maudlin

It is commonly remarked that contemporary physics faces a challenge in reconciling quantum theory with Relativity, specifically General Relativity as a theory of gravity. But "challenge" is too mild a descriptor. Once one understands both what John Bell proved and what Einstein himself demanded of Relativity it becomes clear that the predictions of quantum t

Raphael Pestourie

In electromagnetism, the model of Maxwell's equations yields accurate and trustworthy predictions. Numerical solvers can reach electromagnetic solutions far beyond the set of analytical closed-form solutions; this is crucial in metamaterials design where the goal is to find the geometry that generates an optimal electromagnetic solution for a desired propert

E. H. T. Poldi, R. Tartaglia, G. Fabbris, N. Nguyen

The search for Kitaev's quantum spin liquid (KQSL) state in real materials has recently expanded with the prediction that honeycomb lattices of divalent, high-spin cobalt ions could host the dominant bond-dependent exchange interactions required to stabilize the elusive entangled quantum state. The layered honeycomb Na$_3$Co$_2$SbO$_6$ has been singled out a

Vahid Azimi-Mousolou, Anna Delin, Erik Sjöqvist, Olle Eriksson

Shake-up phenomena, rooted in the sudden approximation and many-body quantum dynamics, unveil critical characteristics of quantum systems, with wide-ranging applications in molecular spectroscopy and electronic structure studies. Here, this principle is extended to magnetic systems, and magnon shake-up structures and their relevance in generating and sensing

Jinsook Lee, AJ Alvero, Thorsten Joachims, René Kizilcec

People are increasingly using technologies equipped with large language models (LLM) to write texts for formal communication, which raises two important questions at the intersection of technology and society: Who do LLMs write like (model alignment); and can LLMs be prompted to change who they write like (model steerability). We investigate these questions

Alan Dow, István Juhász

In this note we prove several theorems that are related to some results and problems from [6]. We answer two of the main problems that were raised in [6]. First we give a ZFC example of a Hausdorff space in $C(\omega_1)$ that has uncountable net weight. Then we prove that after adding any number of Cohen reals to a model of CH, in the extension every regular

Kevin D. Stubbs, Michael Ragone, Allan H. MacDonald, Lin Lin

At a magic relative twist angle, magic angle twisted bilayer graphene (MATBG) has an octet of flat bands that can host strong correlation physics when partially filled. A key theoretical discovery in MATBG is the existence of ferromagnetic Slater determinants as exact ground states of the corresponding flat band interacting (FBI) Hamiltonian. The FBI Hamilto

Muhammad Rizwan Akram, Abbas Semnani

Cold atmospheric pressure plasmas are crucial for applications in medicine, agriculture, and material processing, where their interaction with ambient air generates reactive oxygen and nitrogen species for disinfection and treatment purposes. Additionally, their ability to alter carbon bonds makes them valuable for processing heat-sensitive materials and etc

Joyce A. Guzik, Brian Kloppenborg, Noel Richardson, Jason Jackiewicz

Deneb, the prototype Alpha Cygni variable, is a bright A2 Ia supergiant which shows irregular variability with a 12-day quasi-period, presumed to be caused by pulsations. At the 2023 AAVSO Annual Meeting we discussed radial velocity and photometry data from several sources showing that the 12-day variations begin abruptly at an arbitrary phase, damp out afte

Salim Janji

This paper addresses the deployment of a drone equipped with a reconfigurable intelligent surface (RIS), creating a drone relay station (DRS) to enhance the connectivity of vehicle-to-vehicle (V2V) pairs on the ground. The trajectory of the DRS is optimized to quickly reach the best location for maximizing throughput. Additionally, the presence of an interfe

Vahid Azimi-Mousolou, Prashant Singh

Variational quantum algorithms have emerged as a powerful tool for harnessing the potential of near-term quantum devices to address complex challenges across quantum science and technology. Yet, the robust and scalable quantification of entanglement in many-body quantum systems remains a significant challenge, crucial for both advancing theoretical understan

Bowei Tian, Xuntao Lyu, Meng Liu, Hongyi Wang

Representation Engineering (RepE) has emerged as a powerful paradigm for enhancing AI transparency by focusing on high-level representations rather than individual neurons or circuits. It has proven effective in improving interpretability and control, showing that representations can emerge, propagate, and shape final model outputs in large language models (

Paraskevi Valergaki, Antonis Argyros, Giorgos Giannakakis, Anastasios Roussos

Real-time 3D face manipulation has significant applications in virtual reality, social media and human-computer interaction. This paper introduces a novel system, which we call Mirror of Diversity (MOD), that combines Generative Adversarial Networks (GANs) for texture manipulation and 3D Morphable Models (3DMMs) for facial geometry to achieve realistic face

I. J. Dejter

Independently posed by Behzad and Vizing, the Total Coloring Conjecture asserts that the total chromatic number of a simple connected graph $G$ is either $Δ(G)+1$ or $Δ(G)+2$, where $Δ(G)$ is the largest degree of any vertex of $G$. To decide whether a cubic graph $G$ has total chromatic number $Δ(G)+1$, even for bipartite cubic graphs, is NP-hard. The resul

Sarah Martinson, Lingkai Kong, Cheol Woo Kim, Aparna Taneja

Agent-based simulation is crucial for modeling complex human behavior, yet traditional approaches require extensive domain knowledge and large datasets. In data-scarce healthcare settings where historic and counterfactual data are limited, large language models (LLMs) offer a promising alternative by leveraging broad world knowledge. This study examines an L

Bartosz Malman

The classical Korenblum-Roberts Theorem characterizes the cyclic singular inner functions in the Bergman spaces of the unit disk $\mathbb{D}$ as those for which the corresponding singular measure vanishes on Beurling-Carleson sets of Lebesgue measure zero. We solve the weighted variant of the problem in which the Bergman space is replaced by a $\mathcal{P}^t

Lucas Williams

The Pontryagin-Thom theorem gives an isomorphism from the cobordism group of framed $n$-manifolds to the $n$th stable homotopy group of the sphere spectrum. In this paper, we prove the generalization of the Pontryagin-Thom theorem for families of framed equivariant manifolds parameterized over a compact base space.

Edgar Santamaria, Martin A. Guerrero, Gerardo Ramos-Larios, Jesus A. Toala

This work presents the first optical imaging catalogue of resolved Galactic nova remnants. It compiles images from proprietary observations carried out at the Nordic Optical Telescope and public archives using different telescopes and instruments. The catalogue includes images spanning from 1950 to 2024 of 66 novae out of the more than 550 novae detected to

John R. Klein

We exhibit a homotopy theoretic proof of the Fundamental Theorem of Poincar\'e surgery in the simply connected case. We also deduce the Poincar\'e transversality exact sequence.

S. Li, R. M. Ludlam, D. J. K. Buisson, M. Sudha

The Nuclear Spectroscopic Telescope Array (NuSTAR) enables detailed high-energy X-ray observations from 3--79 keV, but its performance can be constrained by telemetry saturation when observing bright sources, leading to reduced effective exposure times. In this study, we investigate the use of serendipitous stray light (SL) observations to infer properties o

Gabriel Bo, Justin Gu, Christopher Sun

We present a foundation modeling framework that leverages deep learning to uncover latent genetic signatures across the hematopoietic hierarchy. Our approach trains a fully connected autoencoder on multipotent progenitor cells, reducing over 20,000 gene features to a 256-dimensional latent space that captures predictive information for both progenitor and do

Yunlong Yu, Xiang-Bin Wang, Nic Shannon, Robert Joynt

In the search for quantum advantage in real--world problems, one promising avenue is to use a quantum algorithm to improve on the solution found using an efficient classical algorithm. The quantum approximate optimization algorithm (QAOA) is particularly well adapted for such a "warm start" approach, and can be combined with the powerful classical Goemans-Wi

Yu Xin, Gorkem Can Ates, Kuang Gong, Wei Shao

Vision-language models (VLMs) have shown promise in 2D medical image analysis, but extending them to 3D remains challenging due to the high computational demands of volumetric data and the difficulty of aligning 3D spatial features with clinical text. We present Med3DVLM, a 3D VLM designed to address these challenges through three key innovations: (1) DCForm

Matthew Belyakov, Michael E. Brown

We present the JWST NIRSpec PRISM 0.7-5.3 micron spectra of Albiorix and Siarnaq and the NIRSpec G235H/G395M 1.7-5.3 micron spectra of Phoebe, the three largest Saturnian irregular satellites. The irregular satellites of the giant planets are thought to be captured planetesimals from the same population as Kuiper belt objects. They are emplaced inside Saturn

Hidde Koerts, Benjamin Moore, Sophie Spirkl

We characterize all orientations of cycles $C$ for which for every fixed $\varepsilon > 0$ there exists a constant $c \geq 1$ such that every digraph $D$ without loops or parallel arcs with $\chi(D) \geq c$ and minimum out-degree at least $\varepsilon |V(D)|$ contains $C$ as a subdigraph. This generalizes a result of Thomassen.

A. Lozano, G. Silva, G. Caceres, S. Akhter

This MINERvA analysis is the first neutrino and antineutrino study of a shallow inelastic scattering region, which is the transition region between resonant production and deep inelastic scattering processes. This transition is explicitly included in this study by expanding the scope of shallow inelastic scattering to include not only the mainly lower-$Q^2$

Triet Ha, David Rupke, Shane Caraker, Jack Harper

The OVI 1032, 1038 A line is a key probe of cooling gas in the circumgalactic medium (CGM) of galaxies, but has been observed to date primarily in absorption along single sightlines. We present deep HST ACS-SBC observations of the compact, massive starburst Makani. Makani hosts a 100 kpc, [OII]-emitting galactic wind driven by two episodes of star formation

Dhammika Pieris

The Cognitive Data Model (CDM) is proposed. A novel approach to database design, inspired by the belief that the human brain operates with a logical data model independent of its anatomical structure. The study aims to identify and replicate this CDM to enhance database design, resolving limitations of the existing models in handling complex relationships, s

Gabriel Bo, Marc Bernardino, Justin Gu

We explore the potential of integrating learnable and interpretable modules--specifically Kolmogorov-Arnold Networks (KAN) and graph-based representations--within a pre-trained GPT-2 model to enhance multi-task learning accuracy. Motivated by the recent surge in using KAN and graph attention (GAT) architectures in chain-of-thought (CoT) models and debates ov

Tianming Liu, Jirong Yang, Yafeng Yin

Agent-based modeling approaches represent the state-of-art in modeling travel demand and transportation system dynamics and are valuable tools for transportation planning. However, established agent-based approaches in transportation rely on multi-hierarchical mathematical models to simulate travel behavior, which faces theoretical and practical limitations.

Shaohuai Liu, Lin Dong, Chao Tian, Le Xie

Data scaling has revolutionized research fields like natural language processing, computer vision, and robotics control, providing foundation models with remarkable multi-task and generalization capabilities. In this paper, we investigate whether similar data scaling laws exist in developing foundation models for power systems, and whether appropriate data s

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

A search for the decay $B^+_c\rightarrow \chi_{c1}(3872)\pi^+$ is reported using proton-proton collision data collected with the LHCb detector between 2011 and 2018 at centre-of-mass energies of 7, 8, and 13 $TeV$, corresponding to an integrated luminosity of $9fb^{-1}$. No significant signal is observed. Using the decay $B^+_c\rightarrow \psi(2S)\pi^+$ as a

A. V. Shanin, A. Yu. Laptev

We consider a three-dimensional Fourier integral in which the exponent in the exponential factor is the product of some phase function and a large parameter. The asymptotics of this integral is sought when the large parameter tends to infinity. In the one-dimensional case, the asymptotics of such an integral is constructed by the points of stationary phase a

Nikolaus Z. Prusinski, Charles C. Steidel, Yuguang Chen

We present new results on the spatial structure and kinematics of the circumgalactic medium (CGM) of z ~ 2 star-forming galaxies drawn from the Keck Baryonic Structure Survey, using Lya and metallic ion absorption recorded in spectra of background galaxies whose sightlines are projected within ~ 30" (physical distances D_tran < 250 kpc) of the foreground gal

Eray Yapağcı, Yavuz Alp Sencer Öztürk, Eray Tüzün

Reproducing game bugs, particularly crash bugs in continuously evolving games like Minecraft, is a notoriously manual, time-consuming, and challenging process to automate; insights from a key decision maker from Minecraft we interviewed confirm this, highlighting that a substantial portion of crash reports necessitate manual scenario reconstruction. Despite

Zheng Bian, Erik M. Bollt

We study conditional mutual information (cMI) between a pair of variables $X,Y$ given a third one $Z$ and derived quantities including transfer entropy (TE) and causation entropy (CE) in the dynamically relevant context where $X=T(Y,Z)$ is determined by $Y,Z$ via a deterministic transformation $T$. Under mild continuity assumptions on their distributions, we

Adi Glücksam, Shira Tanny

In 1972, Cornalba and Shiffman showed that the number of zeros of an order zero holomorphic function in two or more variables can grow arbitrarily fast. We generalize this finding to the setting of complex dynamics, establishing that the number of isolated primitive periodic points of an order zero holomorphic function in two or more variables can grow arbit

CMS Collaboration

A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. In this search, a flavor-changing neutral current produces a single top quark or antiquark and

C. R. Nugent, J. M. Bauer, O. Benitez, M. Blain

We have created a new image analysis pipeline to reprocess images taken by the Near Earth Asteroid Tracking survey and have applied it to ten nights of observations. This work is the first large-scale reprocessing of images from an asteroid discovery survey in which thousands of archived images are re-calibrated, searched for minor planets, and resulting obs

Franck Cappello, Allison Baker, Ebru Bozda, Martin Burtscher

Increasing data volumes from scientific simulations and instruments (supercomputers, accelerators, telescopes) often exceed network, storage, and analysis capabilities. The scientific community's response to this challenge is scientific data reduction. Reduction can take many forms, such as triggering, sampling, filtering, quantization, and dimensionality re

Maleeha Masood, Shreya Kannan, Zikun Liu, Deepak Vasisht

Short video streaming systems such as TikTok, YouTube Shorts, Instagram Reels, etc., have reached billions of active users worldwide. At the core of such systems are (proprietary) recommendation algorithms which recommend a sequence of videos to each user, in a personalized way. We aim to understand the temporal evolution of recommendations made by such algo

Oksana Braganets

Let $(\xi_k, \eta_k)_{k\geq 1}$be independent identically distributed random vectors with arbitrarily dependent positive components and $T_k:=\xi_1+\ldots+\xi_{k-1}+\eta_k$for $k\in\mathbb{N}$. We call the random sequence {T_k, k=1,2...} a (globally) perturbed random walk. Consider a general branching process generated by {T_k, k=1,2...} and let Y_j(t) denot

Pengfei Du

The integration of Large Language Models (LLMs) with specialized tools presents new opportunities for intelligent automation systems. However, orchestrating multiple LLM-driven agents to tackle complex tasks remains challenging due to coordination difficulties, inefficient resource utilization, and inconsistent information flow. We present OmniNova, a modula

Paul Bertin, Joseph D. Viviano, Alejandro Tejada-Lapuerta, Weixu Wang

Single-cell data provide high-dimensional measurements of the transcriptional states of cells, but extracting insights into the regulatory functions of genes, particularly identifying transcriptional mechanisms affected by biological perturbations, remains a challenge. Many perturbations induce compensatory cellular responses, making it difficult to distingu

Andrew J. Sargent, Alexander J. van der Horst, Megan C. Johnson, Travis C. Fischer

We present $4-12$ GHz in-band spectral energy distributions with accompanying 6 GHz and 10 GHz imaging results for a volume-complete sample ($<40$ Mpc) of hard X-ray selected active galactic nuclei (AGNs) observed with the Karl G. Jansky Very Large Array (VLA) in its A-array configuration. Despite expectations, only 12 out of 25 of these targets have been de

Kostas I. Psaromiligkos, Simon Riche

We study the construction of a modular generalized Springer correspondence for a possibly disconnected complex reductive algebraic group.

Zhenya Zang, David A Dorward, Katherine E Quiohilag, Andrew DJ Wood

The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and prognosis. However, current clinical practice relies on multi-step staining and labelling processes that are time-intensive and costly, requiring highly specialised expertise. In this study, we propose a label-free met

Oleksandr Manzyuk

We show that state, reader, writer, and error monad transformers are instances of one general categorical construction: translation of a monad along an adjunction.

CMS Collaboration

A search for $t$-channel exchange of leptoquarks (LQs) is performed in dimuon and dielectron spectra using proton-proton collision data collected at $\sqrt{s}$ = 13 TeV with the CMS detector at the CERN LHC. The data correspond to an integrated luminosity of 138 fb$^{-1}$. Eight scenarios are considered, in which up or down quarks couple to muons or electron

Logan Howe, Bart van Zeghbroeck, David Olaya, John Biesecker

Measurement of signals generated by superconducting Josephson junction (JJ) circuits require ultra-fast components located in close proximity to the generating circuitry. We report a detailed study of optimal design criteria for a JJ-based sampler which balances the highest sampler bandwidth (shortest 10\%--90\% rise time) with minimal sampled waveform disto

Kevin Ingles, Jordi Salinas San Martín, Willian Serenone, Jacquelyn Noronha-Hostler

We present semi-analytical solutions for the evolution of both the temperature and chemical potentials for viscous Gubser flow with conserved charges. Such a solution can be especially useful in testing numerical codes intended to simulate relativistic fluids with large chemical potentials. The freeze-out hypersurface profiles for constant energy density are

Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie, Jean-Baptiste Alayrac

Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as robots remains a significant challenge. This report introduces a new family of AI models purposefully designed for robotics and built upon the foundation of Gemini 2.0. We present

Ankita Budhraja, Balbeer Singh

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general $\nu$-point projected energy correlators in heavy ion collisions. The $\nu$-point projected energy correlators (or, $\nu$-correlators) are an analytically continued family of the integer $N$-point projected energy correlators, which p

Jiuqi Wang, Rohan Chandra, Shangtong Zhang

Loss of plasticity is one of the main challenges in continual learning with deep neural networks, where neural networks trained via backpropagation gradually lose their ability to adapt to new tasks and perform significantly worse than their freshly initialized counterparts. The main contribution of this paper is to propose a new hypothesis that experience r

A. Abada, G. Arcadi, M. Lucente, S. Rosauro-Alcaraz

The presence of a dark matter component in the Universe, together with the discovery of neutrino masses from the observation of the oscillation phenomenon, represents one of the most important open questions in particle physics today. A concurrent solution arises when one of the right-handed neutrinos, necessary for the generation of light neutrino masses, i

Mikael Chala, Guilherme Guedes

We derive the one-loop effective 3-dimensional Lagrangian that describes the high-temperature limit of the electroweak theory, to order $\mathcal{O}(g^6)$ in coupling constants $g$, including corrections due to Matsubara modes of both fermionic and bosonic degrees of freedom. We clarify certain aspects of the gauge-independence of physical parameters. We als

Ben Johnsrude

We demonstrate two applications of Fourier decoupling theorems over non-Archimedean local fields to real-variable problems. These include short mean value estimates for exponential sums, canonical-scale mean value estimates for exponential sums arising from phase functions with coefficients arising from the traces of powers of algebraic numbers, and solution

Jiwoong Jang, Antoine Mellet

The Patlak-Keller-Segel system of equations (PKS) is a classical example of aggregation-diffusion equation. It describes the aggregation of some organisms via chemotaxis, limited by some nonlinear diffusion. It is known that for some choice of this nonlinear diffusion, the PKS model asymptotically leads to phase separation and mean-curvature driven free boun

Nuren Zhaksylyk, Ibrahim Almakky, Jay Paranjape, S. Swaroop Vedula

Accurate surgical instrument segmentation is essential in cataract surgery for tasks such as skill assessment and workflow optimization. However, limited annotated data makes it difficult to develop fully automatic models. Prompt-based methods like SAM2 offer flexibility yet remain highly sensitive to the point prompt placement, often leading to inconsistent

Michael P. Grehan, Tanisha Ghosal, James R. Beattie, Bart Ripperda

High-energy astrophysical systems and compact objects are frequently modeled using ideal relativistic magnetohydrodynamic (MHD) or force-free electrodynamic (FFE) simulations, with the underlying assumption that the discretisation from the numerical scheme introduces an effective (numerical) magnetic resistivity that adequately resembles an explicit resistiv

Luke Chen, Junyao Wang, Trier Mortlock, Pramod Khargonekar

Uncertainty Quantification (UQ) is crucial for ensuring the reliability of machine learning models deployed in real-world autonomous systems. However, existing approaches typically quantify task-level output prediction uncertainty without considering epistemic uncertainty at the multimodal feature fusion level, leading to sub-optimal outcomes. Additionally,

Seokho Jin, Seungki Kim

We study the statistical distribution of primitive sublattices in the space of lattices $\mathrm{SL}(n,\mathbb Z)\backslash\mathrm{SL}(n,\mathbb R)$. A central difficulty in this area is that the second moment of the counting function for rank $k$ sublattices, where $2 \le k \le n-2$, diverges. To overcome this, we analyze the inner product of truncated pseu

Oleg Lyubimtsev, Askar Tuganbaev

A ring $R$ is said to be centrally essential if for every its non-zero element $a$, there exist non-zero central elements $x$ and $y$ with $ax = y$. A ring $R$ is said to be completely centrally essential if all its factor rings are centrally essential rings. It is proved that completely centrally essential semiprimary rings are Lie nilpotent; noetherian com

Marcos Jardim, Jason Lo, Antony Maciocia, Cristian Martinez

We prove that the Gieseker moduli space of stable sheaves on a smooth projective threefold $X$ of Picard rank 1 is separated from the moduli space of PT stable objects by a single wall in the space of Bridgeland stability conditions on $X$, thus realizing the higher rank DT/PT correspondence as a wall-crossing phenomenon in the space of Bridgeland stability

Maksim Borisov, Zhanibek Kozhirbayev, Valentin Malykh

Machine translation for low resource language pairs is a challenging task. This task could become extremely difficult once a speaker uses code switching. We propose a method to build a machine translation model for code-switched Kazakh-Russian language pair with no labeled data. Our method is basing on generation of synthetic data. Additionally, we present t

Kaila E. Weflen, Megan R. Bentley, James H. Thorpe, Peter R. Franke

The fundamental non-Hermitian nature of the forms of coupled-cluster (CC) theory widely used in quantum chemistry has usually been viewed as a negative, but the present letter shows how this can be used to advantage. Specifically, the non-symmetric nature of the reduced one-particle density matrix (in the molecular orbital basis) is advocated as a diagnostic

Jason B. Gibson, Ajinkya C. Hire, Pawan Prakash, Philip M. Dee

The quest to identify new superconducting materials with enhanced properties is hindered by the prohibitive cost of computing electron-phonon spectral functions, severely limiting the materials space that can be explored. Here, we introduce a Bootstrapped Ensemble of Equivariant Graph Neural Networks (BEE-NET), a machine-learning model trained to predict the

Theodosis Alexandrou, Lin Zhou

We study the injectivity property of certain actions of higher Chow groups on refined unramified cohomology. As an application for every $p\geq1$ and for each $d\geq p+4$ and $n\geq2,$ we establish the first examples of smooth complex projective $d$-folds $X$ such that for all $p+3\leq c\leq d-1,$ the higher Chow group $\text{CH}^{c}(X,p)$ contains infinitel