March 2025 arXiv papers — page 56

Rosemary Barrass, Harsha Nagarajan, Carleton Coffrin

The recent advent of commercially available quantum annealing hardware (QAH) has expanded opportunities for research into quantum annealing-based algorithms. In the domain of power systems, this advancement has driven increased interest in applying such algorithms to mixed-integer problems (MIP) like Unit Commitment (UC). UC focuses on minimizing power gener

Nicolas Baron Perez, Marcus Brüggen, Gregor Kasieczka, Luisa Lucie-Smith

The morphology of radio galaxies is indicative of their interaction with their surroundings, among other effects. Since modern radio surveys contain a large number of radio sources that would be impossible to analyse and classify manually, it is important to develop automatic schemes. Unlike other fields, which benefit from established theoretical frameworks

Sina Feldmann, Juliane Adrian, Maik Boltes

Impulse propagation in crowds is a phenomenon that is crucial for understanding collective dynamics, but has been scarcely addressed so far. Therefore, we have carried out experiments in which persons standing in a crowd are pushed forward in a controlled manner. Variations of experimental parameters include (i) the intensity of the push, (ii) the initial in

Pietro Asinari, Nada Alghamdi, Paolo De Angelis, Giulio Barletta

This document explores the potential of quantum computing in Thermal Science. Conceived as a living document, it will be continuously updated with experimental findings and insights for the research community in Thermal Science. By experiments, we refer both to the search for the most effective algorithms and to the performance of real quantum hardware. Thos

Tommie Kerssies, Niccolò Cavagnero, Alexander Hermans, Narges Norouzi

Vision Transformers (ViTs) have shown remarkable performance and scalability across various computer vision tasks. To apply single-scale ViTs to image segmentation, existing methods adopt a convolutional adapter to generate multi-scale features, a pixel decoder to fuse these features, and a Transformer decoder that uses the fused features to make predictions

Nicholas W. Barendregt, Joshua I. Gold, Krešimir Josić, Zachary P. Kilpatrick

To survive in dynamic and uncertain environments, individuals must develop effective decision strategies that balance information gathering and decision commitment. Models of such strategies often prioritize either optimizing tangible payoffs, like reward rate, or gathering information to support a diversity of (possibly unknown) objectives. However, our und

Kwangjun Ahn, Alex Lamb, John Langford

In this short report, we introduce joint multi-token prediction (JTP), a lightweight modification of standard next-token prediction designed to enrich hidden state representations by jointly predicting multiple future tokens. Unlike previous multi-token prediction approaches, JTP strategically employs teacher forcing of future-tokens through a carefully desi

Martin Ulmer

We study an elliptic operator $L:=\mathrm{div}(A\nabla \cdot)$ on the upper half plane $\mathbb{R}^2_+$. There are several conditions on the behavior of the matrix $A$ in the transversal $t$-direction that yield $\omega\in A_\infty(\sigma)$. These include the $t$-independence condition, a mixed $L^1-L^\infty$ condition on $\partial_t A$, and Dini-type condit

Denis S. Grebenkov, Ralf Metzler, Gleb Oshanin

A common scenario in a variety of biological systems is that multiple particles are searching in parallel for an immobile target located in a bounded domain, and the fastest among them that arrives to the target first triggers a given desirable or detrimental process. The statistics of such extreme events -- the \textit{fastest\/} first-passage to the target

Sina Feldmann, Juliane Adrian

Security plays a crucial role when it comes to planning large events such as concerts, sporting tournaments, pilgrims, or demonstrations. Monitoring and controlling pedestrian dynamics can prevent dangerous situations from occurring. However, little is known about the specific factors that contribute to harmful situations. For example, the individual respons

Daniil Averkov, Gregory Emdin, Viktoriia Krivogornitsyna, Alexander S. Kulikov

The Boolean circuit simplification problem involves finding a smaller circuit that computes the same function as a given Boolean circuit. This problem is closely related to several key areas with both theoretical and practical applications, such as logic synthesis, satisfiability, and verification. In this paper, we present Simplifier, a new open source tool

Shahab Ataei, Dipankar Maity, Debdipta Goswami

Least-square system identification is widely used for data-driven model-predictive control (MPC) of unknown or partially known systems. This letter investigates how the system identification and subsequent MPC is affected when the state and input data is quantized. Specifically, we examine the fundamental connection between model error and quantization resol

Jairo Delgado, Haimer A. Trejos, Carlos Peñafiel

In this paper, we obtain the necessary equations in a conformal parameter induced by the first or second fundamental forms for a surface that is isometrically immersed in the warped product $\mathbb{R} \times_{f} \mathbb{M}^{2}(\kappa)$ where $\mathbb{M}^{2}(\kappa)$ denotes the complete, connected, simply connected, two-dimensional space form of constant cu

Md. Barkat Ullah Tusher, Shartaz Khan Akash, Amirul Islam Showmik

This paper showcases an experimental study on anomaly detection using computer vision. The study focuses on class distinction and performance evaluation, combining OpenCV with deep learning techniques while employing a TensorFlow-based convolutional neural network for real-time face recognition and classification. The system effectively distinguishes among t

Kenneth Alperin, Rohan Leekha, Adaku Uchendu, Trang Nguyen

The increasing use of Artificial Intelligence (AI) technologies, such as Large Language Models (LLMs) has led to nontrivial improvements in various tasks, including accurate authorship identification of documents. However, while LLMs improve such defense techniques, they also simultaneously provide a vehicle for malicious actors to launch new attack vectors.

Axel de la Macorra, Jose Agustin Lozano Torres

Dark energy, the enigmatic force driving the accelerated cosmic expansion of the universe, is conventionally described as a cosmological constant in the standard $\Lambda$CDM model. However, measurements from the Dark Energy Spectroscopic Instrument (DESI) reports a $> 2.5\sigma$ preference for dynamical dark energy, with baryon acoustic oscillation (BAO) da

Xuanhao Luo, Zhiyuan Peng, Zhouyu Li, Ruozhou Yu

The rapid increase in networked systems and data transmission requires advanced data compression solutions to optimize bandwidth utilization and enhance network performance. This study introduces a novel byte-level predictive model using Transformer architecture, capable of handling the redundancy and diversity of data types in network traffic as byte sequen

Sina Ditzel, Achref Jaziri, Iuliia Pliushch, Visvanathan Ramesh

The robustness of image recognition algorithms remains a critical challenge, as current models often depend on large quantities of labeled data. In this paper, we propose a hybrid approach that combines the adaptability of neural networks with the interpretability, transparency, and robustness of domain-specific quasi-invariant operators. Our method decompos

Jiafeng Chen, Jiaying Gu, Soonwoo Kwon

In the value-added literature, it is often claimed that regressing on empirical Bayes shrinkage estimates corrects for the measurement error problem in linear regression. We clarify the conditions needed; we argue that these conditions are stronger than the those needed for classical measurement error correction, which we advocate for instead. Moreover, we s

Pavel Shvartsman

Let $F$ be a set-valued mapping from an $N$-element metric space $({\mathcal M},\rho)$ into the family of all closed half-planes in ${\bf R}^2$. In this paper, we provide an efficient algorithm for a Lipschitz selection of $F$, i.e., a Lipschitz mapping $f:{\mathcal M}\to{\bf R}^2$ such that $f(x)\in F(x)$ for all $x\in{\mathcal M}$. Given a constant $\lambd

Matthias Bentert, Fedor V. Fomin, Petr A. Golovach, M. S. Ramanujan

Distance geometry explores the properties of distance spaces that can be exactly represented as the pairwise Euclidean distances between points in $\mathbb{R}^d$ ($d \geq 1$), or equivalently, distance spaces that can be isometrically embedded in $\mathbb{R}^d$. In this work, we investigate whether a distance space can be isometrically embedded in $\mathbb{R

Krisztian Balog, Donald Metzler, Zhen Qin

Large language models (LLMs) are increasingly integral to information retrieval (IR), powering ranking, evaluation, and AI-assisted content creation. This widespread adoption necessitates a critical examination of potential biases arising from the interplay between these LLM-based components. This paper synthesizes existing research and presents novel experi

Yuchen Fang, Javad Lavaei, Sen Na

In this paper, we consider nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We propose a Trust-Region Stochastic Sequential Quadratic Programming (TR-SSQP) method and establish its high-probability iteration complexity bounds for identifying first- and second-order $\epsilon$-stationary points. In our algori

Varsha Embar, Ritvik Shrivastava, Vinay Damodaran, Travis Mehlinger

Large Language Models have transformed the Contact Center industry, manifesting in enhanced self-service tools, streamlined administrative processes, and augmented agent productivity. This paper delineates our system that automates call driver generation, which serves as the foundation for tasks such as topic modeling, incoming call classification, trend det

Lovedeep Gondara, Jonathan Simkin, Shebnum Devji, Gregory Arbour

Background: Population-based cancer registries (PBCRs) manually extract data from unstructured pathology reports, a labor-intensive process where assigning reports to tumor groups can consume 900 person-hours annually for approximately 100,000 reports at a medium-sized registry. Current automated rule-based systems fail to handle the linguistic complexity of

Gustavo Boska, Matheus Duzi, Paulo Magalhães Júnior

Directions of graphs were originally introduced in the study of a cops-and-robbers kind of game, while the study of end spaces has been used to generalize classical graph-theoretical results to infinite graphs, such as Halin's generalization of Menger's theorem. An edge-analogue of end spaces, where finite sets of edges are used instead of vertices as separa

Marie-Julie Dalbe, Pierre Jodlowski, Nicolas Vandenberghe

Cohesive granular materials, like wet sand, retain their shape before yielding under stress. This solid-like behavior is associated with elasticity. As the loading increases, the material typically flows. However, cohesive materials can also develop cracks, similar to those observed in brittle materials. This study explores the formation of cracks during the

Liam Burke, Erin Carson, Yuxin Ma

We perform a backward stability analysis of preconditioned sketched GMRES [Nakatsukasa and Tropp, SIAM J. Matrix Anal. Appl, 2024] for solving linear systems $Ax=b$, and show that the backward stability at iteration $i$ depends on the conditioning of the Krylov basis $B_{1:i}$ as long as the condition number of $A B_{1:i}$ can be bounded by $1/O(u)$, where $

Ananda Chakrabarti, Indranil Nayak, Debdipta Goswami

This paper introduces the temporally-consistent bilinearly recurrent autoencoder (tcBLRAN), a Koopman operator based neural network architecture for modeling a control-affine nonlinear control system. The proposed method extends traditional Koopman autoencoders (KAE) by incorporating bilinear recurrent dynamics that are consistent across predictions, enablin

Nikolett Német, Tamás Kiss, Scott Parkins

An open non-degenerate parametric oscillator (NDPO) is studied below threshold in the undepleted pump regime with time-delayed coherent feedback (TDCF). The figure of merit is the two-mode squeezing spectrum measuring the strength of continuous-valued Einstein-Podolsky-Rosen-type (EPR-type) entanglement between the down-converted modes in the output field. E

Swati Sharma, Fabian A. Braeu, Thanadet Chuangsuwanich, Tin A. Tun

Purpose: To characterize the 3D structural phenotypes of the optic nerve head (ONH) in patients with glaucoma, high myopia, and concurrent high myopia and glaucoma, and to evaluate their variations across these conditions. Participants: A total of 685 optical coherence tomography (OCT) scans from 754 subjects of Singapore-Chinese ethnicity, including 256 hea

Felix Burt, Kuan-Cheng Chen, Kin K. Leung

Executing quantum algorithms over distributed quantum systems requires quantum circuits to be divided into sub-circuits which communicate via entanglement-based teleportation. Naively mapping circuits to qubits over multiple quantum processing units (QPUs) results in large communication overhead, increasing both execution time and noise. This can be minimise

Amin Totounferoush, Serge Kotchourko, Michael W. Mahoney, Steffen Staab

Partial differential equations (PDEs) govern a wide range of physical systems, but solving them efficiently remains a major challenge. The idea of a scientific foundation model (SciFM) is emerging as a promising tool for learning transferable representations across diverse domains. However, SciFMs require large amounts of solution data, which may be scarce o

Ruben A. Hidalgo

The Loch Ness monster (LNM) is, up to homeomorphisms, the unique orientable, connected, Hausdorff, second countable surface of infinite genus and with exactly one end. For each integer $k \geq 2$, we construct Riemann surface structures $S$ on the LNM admitting a group of conformal automorphisms $H \cong {\mathbb Z}_{k}^{\mathbb N}$ such that $S/H$ is planar

Bethany Terris

The concept of presence has been extensively explored in philosophy, yet the notion of particle presence within quantum theory remains under-examined. In this article, we explore particle presence through an analysis of a paradox arising from weak measurements. We show that the classical intuition about particle presence involves an erroneous logical combina

Shutonu Mitra, Tomas Neguyen, Qi Zhang, Hyungmin Kim

The rise of cyber threats on social media platforms necessitates advanced metrics to assess and mitigate social cyber vulnerabilities. This paper presents the Social Cyber Vulnerability Index (SCVI), a novel framework integrating individual-level factors (e.g., awareness, behavioral traits, psychological attributes) and attack-level characteristics (e.g., fr

Bren E. Backhaus, Allison Kirkpatrick, Guang Yang, Gregory Troiani

We present the MIRI EGS Galaxy and AGN (MEGA) survey, a four band MIRI survey with 25 pointing in the Extended Groth Strip (EGS) extragalactic field. Three of the pointings utilized only the three reddest bands (F1000W, F1500W, F2100W) while the remainder of the pointings also add a blue filter (F770W). MEGA builds upon the existing observations in the EGS f

J. François, L. Ravera

Relationality is the paradigmatic conceptual core of general-relativistic gauge field theory. It can be made manifest via the Dressing Field Method (DFM) of symmetry reduction, a systematic tool to achieve gauge-invariance by extracting the physical degrees of freedom representing relations among field variables. We review and further expand on some applicat

Hamid Arian Zad, Michal Jaščur, Asad Ali, Saif Al-Kuwari

We investigate the low-temperature magnetic and quantum properties of hexanuclear Fe$^ {3+}_6$ complexes under an external magnetic field. We primarily study the impact of competing exchange interactions and their asymmetries induced by the Jahn-Teller distortion on the quantum properties of the complexes. The inequality in exchange interactions lifts the gr

Rida Qadri, Mark Diaz, Ding Wang, Michael Madaio

Generative AI model outputs have been increasingly evaluated for their (in)ability to represent non-Western cultures. We argue that these evaluations often operate through reductive ideals of representation, abstracted from how people define their own representation and neglecting the inherently interpretive and contextual nature of cultural representation.

Osman Goni, Himadri Saha Arka, Mithun Halder, Mir Moynuddin Ahmed Shibly

Recent advances in Generative Adversarial Networks (GANs) have demonstrated their capability for producing high-quality images. However, a significant challenge remains mode collapse, which occurs when the generator produces a limited number of data patterns that do not reflect the diversity of the training dataset. This study addresses this issue by proposi

Hao-Qiao Li, Hai-Ning Yan, Jiayin Gu, Xiao-Ze Tan

A future $e^+e^-$ collider could run at the Z-pole to perform important electroweak (EW) precision measurements, while such a run may not be viable for a future muon collider. This however can be compensated by the measurements of other EW processes, taking advantage of the high energy and large luminosity of the muon collider. In this paper, we consider the

Pablo Guillermo Carmona Rufo, Ayush Kumar, Carlos Sabín, Anupam Mazumdar

Entanglement is solely a quantum property and it can be extremely helpful to test the physics beyond the Standard Model in tabletop experiments with the advent of future quantum technologies. In this work, we provide an entanglement-based partial positive transpose witness for Yukawa-type potentials in the infrared regime between pairs of neutral/charged par

Karl Bergson Hallberg, Erik Wegner Hodt, Jacob Linder

When a charge current is injected into an altermagnet along a suitable crystallographic direction, a transverse spin current can be generated. This so-called spin-splitter effect does not rely on spin-orbit coupling, and is thus distinct from the spin Hall effect. The spin-splitter effect was predicted by \textit{ab initio} calculations and has been experime

Jiazhu Dai, Yubing Lu

Graph neural networks (GNNs) are widely used for graph-structured data but are vulnerable to membership inference attacks (MIAs) in graph classification tasks, which determine if a graph was part of the training dataset, potentially causing data leakage. Existing MIAs rely on prediction probability vectors, but they become ineffective when only prediction la

Dor Elimelech, Wasim Huleihel

The problems of detecting and recovering planted structures/subgraphs in Erd\H{o}s-R\'{e}nyi random graphs, have received significant attention over the past three decades, leading to many exciting results and mathematical techniques. However, prior work has largely focused on specific ad hoc planted structures and inferential settings, while a general theor

Sacha Braun, Liviu Aolaritei, Michael I. Jordan, Francis Bach

Conformal prediction provides a principled framework for constructing predictive sets with finite-sample validity. While much of the focus has been on univariate response variables, existing multivariate methods either impose rigid geometric assumptions or rely on flexible but computationally expensive approaches that do not explicitly optimize prediction se

Axel Descamps, Sélène Forget, Aliénor Lahlou, Claire Lavergne

Grouping elements into families to analyse them separately is a standard analysis procedure in many areas of sciences. We propose herein a new algorithm based on the simple idea that members from a family look like each other, and don't resemble elements foreign to the family. After reordering the data according to the distance between elements, the analysis

Zhongyu Yang, Jun Chen, Dannong Xu, Junjie Fei

Knowledge discovery and collection are intelligence-intensive tasks that traditionally require significant human effort to ensure high-quality outputs. Recent research has explored multi-agent frameworks for automating Wikipedia-style article generation by retrieving and synthesizing information from the internet. However, these methods primarily focus on te

Eugene Lerman

We prove that a vector field on an affine $C^\infty$-scheme Spec(A) has a flow if the $C^\infty$-ring A is finitely generated. If the vector field is complete then the flow is the target map of a groupoid internal to the category of $C^\infty$-schemes.

Matthieu Bettinger, Etienne Rivière, Sonia Ben Mokhtar, Anthony Simonet-Boulogne

Current marketplaces rely on search mechanisms with distributed systems but centralized governance, making them vulnerable to attacks, failures, censorship and biases. While search mechanisms with more decentralized governance (e.g., DeSearch) have been recently proposed, these are still exposed to information head-start attacks (IHS) despite the use of Trus

Maria Larchenko, Alexander Lobashev, Dmitry Guskov, Vladimir Vladimirovich Palyulin

In this work, we introduce Modulated Flows (ModFlows), a novel approach for color transfer between images based on rectified flows. The primary goal of the color transfer is to adjust the colors of a target image to match the color distribution of a reference image. Our technique is based on optimal transport and executes color transfer as an invertible tran

Matteo Califano, Ivan De Martino, Daniele Vernieri

We investigate the capability of constraining the mass and redshift distributions of binary black hole systems jointly with the underlying cosmological model using one year of observations of the Einstein Telescope. To this aim, we fixed the underlying cosmological model to a flat $\Lambda$CDM model, then we considered the mass distribution given by a smooth

C. Mac Cormack, S. B. Shaik, P. Hess, R. Colaninno

Coronal Mass Ejections (CMEs) are significant drivers of geomagnetic activity, and understanding these structures is critical to developing and improving forecasting tools for space weather. The Solar Orbiter (SolO) mission, with its comprehensive set of remote sensing and in-situ instruments, along with its unique orbit, is significantly advancing the study

Jordan Chipka, Chris Moyer, Clay Troyer, Tyler Fuelling

The rapid growth of big data and advancements in computational techniques have significantly transformed sports analytics. However, the diverse range of data sources -- including structured statistics, semi-structured formats like sensor data, and unstructured media such as written articles, audio, and video -- creates substantial challenges in extracting ac

Miwha Jin, Anthony J. Remijan, Robin T. Garrod, Giseon Baek

Despite the organic molecule inventory detected in Orion KL, acetaldehyde (CH3CHO) -- one of the most ubiquitous interstellar aldehydes -- has not been firmly identified with mm-wave interferometry. We analyze extensive ALMA archival datasets (142-355 GHz) to search for acetaldehyde, revealing two distinct acetaldehyde emission peaks and one component with m

Van Chung Nguyen, Hung Manh La

This study introduces a novel methodology for controlling Quadrotor Unmanned Aerial Vehicles, focusing on Hierarchical Sliding Mode Control strategies and an Extended Kalman Filter. Initially, an EKF is proposed to enhance robustness in estimating UAV states, thereby reducing the impact of measured noises and external disturbances. By locally linearizing UAV

Theodoros Apostolopoulos, Vasilios Koutsokostas, Nikolaos Totosis, Constantinos Patsakis

The continuous increase in malware samples, both in sophistication and number, presents many challenges for organizations and analysts, who must cope with thousands of new heterogeneous samples daily. This requires robust methods to quickly determine whether a file is malicious. Due to its speed and efficiency, static analysis is the first line of defense. I

Michał Kijaczko, Vivek Sahu

We investigate the sharp constant for weighted fractional Hardy inequalities with the singularity on a flat submanifold of codimension $k$, where $1\leq k<d$. We also prove a weighted fractional Hardy inequality with a remainder. Using this result, we extend and derive a weighted version of the fractional Hardy-Sobolev-Maz'ya inequality with singularities on

Shin'ichi Nojiri, Sergei D. Odintsov, Tanmoy Paul, Soumitra SenGupta

The present work reveals a direct correspondence between modified theories of gravity (cosmology) and entropic cosmology based on the thermodynamics of apparent horizon. It turns out that due to the total differentiable property of entropy, the usual thermodynamic law (used for Einstein gravity) needs to be generalized for modified gravity theories having mo

Henry Mont, Matthieu Bettinger, Sonia Ben Mokhtar, Anthony Simonet-Boulogne

In decentralized cloud computing marketplaces, ensuring fair and efficient interactions among asset providers and end-users is crucial. A key concern is meeting agreed-upon service-level objectives like the service's reliability. In this decentralized context, traditional mechanisms often fail to address the complexity of task failures, due to limited availa

K. Abe, S. Abe, J. Abhir, A. Abhishek

Among the blazars whose emission has been detected up to very-high-energy (VHE; 100 GeV < E < 100 TeV) gamma rays, intermediate synchrotron-peaked BL Lacs (IBLs) are quite rare. The IBL B2 1811+31 (z = 0.117) exhibited intense flaring activity in 2020. Detailed characterization of the source emissions from radio to gamma-ray energies was achieved with quasi-

Xuwen Zhang

We prove a compactness result for capillary hypersurfaces with mean curvature prescribed by ambient functions, which generalizes the results of Sch\"atzle and Bellettini to the capillary case. The proof relies on extending the definition of (unoriented) curvature varifolds with capillary boundary introduced by Wang-Zhang to the context of oriented integral v

Guofang Wang, Xuwen Zhang

In this paper we introduce and study a new class of varifolds in $\mathbf{R}^{n+1}$ of arbitrary dimensions and co-dimensions, which satisfy a Neumann-type boundary condition characterizing capillarity. The key idea is to introduce a Radon measure on a subspace of the trivial Grassmannian bundle over the supporting hypersurface as a generalized boundary with

Nathan Grieser, Federico Leo Redi, Eduardo Rodrigues, Niladri Sahoo

The LHCb collaboration continues to heavily utilize the Run 1 and Run 2 legacy datasets well into Run 3. As the operational focus shifts from the legacy data to the live Run 3 samples, it is vital that a sustainable and efficient system is in place to allow analysts to continue to profit from the legacy datasets. The LHCb Stripping project is the user-facing

Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su

Various parallelism, such as data, tensor, and pipeline parallelism, along with memory optimizations like activation checkpointing, redundancy elimination, and offloading, have been proposed to accelerate distributed training for Large Language Models. To find the best combination of these techniques, automatic distributed training systems are proposed. Howe

Vyacheslav M. Abramov

In this paper, we introduce new classes of functions that extend the known classes of functions of complex variable, such as entire functions, meromorphic functions, rational functions and polynomial functions and take values in the set of circulant matrices with complex entries. For these new classes of functions, we extend the recently obtained characteriz

Kyungsu Kim

This thesis studies the effectiveness of Long Short Term Memory model in forecasting future Job Openings and Labor Turnover Survey data in the United States. Drawing on multiple economic indicators from various sources, the data are fed directly into LSTM model to predict JOLT job openings in subsequent periods. The performance of the LSTM model is compared

A. O. Quiñones, Z. Abbas, C. W. Outhwaite, L. B. Bhuiyan

Experimentally determined empirical formulae for the concentration dependent relative permittivity of aqueous solutions of MgCl$_{2}$ and NiCl$_{2}$ are utilized to calculate the osmotic coefficient and the mean activity coefficient of these salts for a range of concentrations. The systems are modelled using the primitive model of electrolytes and analyzed u

Zhongze Zhang, Wei Yu

This paper explores the design of beamforming codebooks for the base station (BS) and for the reconfigurable intelligent surfaces (RISs) in an active sensing scheme for uplink localization, in which the mobile user transmits a sequence of pilots to the BS through reflection at the RISs, and the BS and the RISs are adaptively configured by carefully choosing

Richard Gumbel, Kyle Godbey

Quasifission, along with fusion-fission, represent the two most likely reaction outcomes to occur post-capture in collisions leading to superheavy nuclei. As such, understanding these mechanisms and how they relate to one another is key to understanding the intricate dynamics that drive the formation (or dissociation) of the nascent compound nuclei formed in

Yalong Yu, Yekai Ren, Nuo Chen, Tao Chu

Thin-film lithium niobate (TFLN) modulators, despite their superior electro-optic performance, face critical DC drift challenges under low-frequency or prolonged operation. In this work, we demonstrate a novel suppression strategy by exciting multiferroic skyrmions in TFLN, achieving drift-free square-wave modulation for voer 1 hour-the first solution elimin

J. -P. Bruneton

This paper presents QDSR, an advanced symbolic Regression (SR) system that integrates genetic programming (GP), a quality-diversity (QD) algorithm, and a dimensional analysis (DA) engine. Our method focuses on exact symbolic recovery of known expressions from datasets, with a particular emphasis on the Feynman-AI benchmark. On this widely used collection of

Paul Wiegert, Vanessa Tran, Cole Gregg, Denis Vida

Material arriving at our solar system from the Galaxy may be detected at Earth in the form of meteors ablating in our atmosphere. Here we report on a search for interstellar meteors within the highest-quality events in the Global Meteor Network (GMN) database. No events were detected that were conclusively hyperbolic with respect to the Sun; however, our sea

Kangwei Liu, Mengru Wang, Yujie Luo, Lin Yuan

Fine-tuning enables large language models (LLMs) to adapt to specific domains, but often compromises their previously established safety alignment. To mitigate the degradation of model safety during fine-tuning, we introduce LookAhead Tuning, a lightweight and effective data-driven approach that preserves safety during fine-tuning. The method introduces two

Luca Camuti, Se-Ho Kim, Filip Podjaski, Miquel Vega-Paredes

Active and reliable electrocatalysts are fundamental to renewable energy technologies. PdCoO2 has recently been recognized as a promising catalyst template for the hydrogen evolution reaction (HER) in acidic media thanks to the formation of active PdHx. In this article, we monitor the transformation of single PdCoO2 particles during HER, and confirm their al

R. Donagi, T. Pantev

We show that the natural nc-space attached to an intersection of three quadrics in P^7 is truly non-commutative. In particular, its associated numerical K-lattice is not isomorphic to the K-lattice of any smooth projective surface, so the relevant derived category is not equivalent to the derived category of any smooth projective surface. Using the new theor

Salim Janji, Paweł Sroka, Adrian Kliks

This paper addresses the crucial need for reliable wireless communication in vehicular networks, particularly vital for the safety and efficacy of (semi-)autonomous driving amid increasing traffic. We explore the use of Reconfigurable Intelligent Surfaces (RISes) mounted on Drone Relay Stations (DRS) to enhance communication reliability. Our study formulates

Jianren Wang, Yifan Su, Abhinav Gupta, Deepak Pathak

On-policy reinforcement learning (RL) algorithms are widely used for their strong asymptotic performance and training stability, but they struggle to scale with larger batch sizes, as additional parallel environments yield redundant data due to limited policy-induced diversity. In contrast, Evolutionary Algorithms (EAs) scale naturally and encourage explorat

Svante Janson, Mihai Nica, Simon Segert

In 2024, Daniel Litt posed a simple coinflip game pitting Alice's "Heads-Heads" vs Bob's "Heads-Tails": who is more likely to win if they score 1 point per occurrence of their substring in a sequence of n fair coinflips? This attracted over 1 million views on X and quickly spawned several articles explaining the counterintuitive solution. We study the genera

Alexander Lobashev, Maria Larchenko, Dmitry Guskov

We propose SW-Guidance, a training-free approach for image generation conditioned on the color distribution of a reference image. While it is possible to generate an image with fixed colors by first creating an image from a text prompt and then applying a color style transfer method, this approach often results in semantically meaningless colors in the gener

Lukas Rapp, Jiewei Feng, Muriel Médard, Ken R. Duffy

Guessing Random Additive Noise Decoding (GRAND) and its variants, known for their near-maximum likelihood performance, have been introduced in recent years. One such variant, Segmented GRAND, reduces decoding complexity by generating only noise patterns that meet specific constraints imposed by the linear code. In this paper, we introduce a new method to eff

Jiangchang Zheng, Caiyun Chen, Xu Zhang, Daniel J. Schultz

Hidden ordered states--characterized by order parameters that elude conventional probes--pose a fundamental challenge for their identification in quantum materials. Recent experiments report evidence for time-reversal symmetry breaking orbital magnetic order and anomalous transport signatures in the $2a\times2a$ charge density wave state of the kagome metal

Arshi Ali, Biny Sebastian, Darshan Kakkad, Sasikumar Silpa

NGC 5972, a Voorwerp galaxy, features a helical-shaped extended emission-line region (EELR) with a radius > 10 kpc and a S-shaped radio structure spanning about 470 kpc. We use VLT MUSE, GMRT, and VLA to study the stellar and ionized gas kinematics and how the radio jet influences the gas in the galaxy. Our sensitive radio observations detect the southern je

Alvi Jawad, Jason Jaskolka, Ashraf Matrawy, Mohamed Ibnkahla

Microsoft's STRIDE methodology is at the forefront of threat modeling, supporting the increasingly critical quality attribute of security in software-intensive systems. However, in a comprehensive security evaluation process, the general consensus is that the STRIDE classification is only useful for threat elicitation, isolating threat modeling from the othe

Zhihao Liu, Zhong Fang, Hongming Weng, Quansheng Wu

Colossal magnetoresistance (CMR) is commonly observed in magnetic semiconductors when an external magnetic field is applied, usually accompanied by anomalous resistivity peaks or humps which were previously considered as evidence of a metal-insulator transition (MIT). Previous research efforts primarily focused on elucidating the CMR effect in ferromagnetic

Xiyuan Gao

In these proceedings, we summarize our recent findings on a minimal renormalizable $SO(10)$ grand unified theory. With the assumption of spontaneous $CP$ violation, the low-energy theory becomes a constrained two-Higgs-doublet model, whose mass spectrum has an upper bound of 545 GeV. High-luminosity collider experiments may find its flavor violating signals

Wen-Tao Xu, Michael Knap, Frank Pollmann

Within the confined phase of (2+1)D lattice gauge theories a roughening transition arises between a weakly confined regime with floppy string excitations and a strongly confined regime with stiff string excitations. In this work, we use an infinite Density Matrix Renormalization Group (iDMRG) algorithm to quantitatively characterize the properties of confine

Pinghui Huang, Fangyuan Yu, Eve J. Lee, Ruobing Dong

From the survival of dust disks for a few Myr to the establishment of chemical dichotomy, dust traps are expected to play a pivotal role in sculpting protoplanetary disks and the early planet formation process. These traps however may not be perfect as evidenced by the detection of gas and dust inside the gaps and cavities of structured disks. Using two-flui

Patrick D. Bolton, Svjetlana Fajfer, Jernej F. Kamenik, Martín Novoa-Brunet

Motivated by a recent Belle~II measurement that suggests an excess in the rare decay $B \to K\, E_{\rm miss}$, and building upon our recent differential decay rate likelihood analysis of the existing experimental information, we investigate possible new physics (NP) scenarios in which light invisible states participate in flavour-changing $b \to s$ transitio

Kohki Uno, Keiichi Maeda, Takashi Nagao, Giorgos Leloudas

AT2023clx, which occurred in NGC3799 with a Low-Ionization Nuclear Emission-Line Region (LINER), is one of the most nearby nuclear transients classified as a tidal disruption event (TDE). We present three-epoch spectropolarimetric follow-up observations of AT2023clx. We detected two polarization components; one is a constant polarization of $\sim 1\%$ origin

Daisuke Fujii, Akihiro Iwanaka, Masakiyo Kitazawa, Daiki Suenaga

We investigate the thermodynamic behavior and phase diagram of $SU(3)$ Yang-Mills theory on $\mathbb{T}^2 \times \mathbb{R}^2$ in Euclidean spacetime using an effective model. In our approach, the Polyakov loops along the compactified directions are treated as dynamic variables, and the model is calibrated to match lattice simulation results for thermodynami

Mario De Marco, Shani Nadir Meynet

In this work we consider the relation between finite isometries of the internal space and symmetries of the transverse field theory in Geometric Engineering. On top of the established relation between branes wrapping torsional cycles and topological defects, we study other symmetries of the field theory that are not captured by branes wrapped at infinity. Is

Marcel Augusto Pinto, Giovanni Luca Sferrazza, Daniele De Bernardis, Francesco Ciccarello

We investigate the emission of a qubit weakly coupled to a one-band coupled-cavity array where, due to an engineered gradient in the cavity frequencies, photons are effectively accelerated by a synthetic force F. For strong F, a reversible emission described by an effective Jaynes-Cummings model occurs, causing a chiral time-periodic excitation of an extensi

Abby Mintz, O. Grace Telford, Evan N. Kirby, John Chisholm

As JWST uncovers increasingly strong evidence that metal-poor, massive stars in early galaxies dominated reionization, observational constraints on the properties of such stars are more relevant than ever before. However, spectra of individual O- and B-type stars are rare at the relevant metallicities ($\lesssim 0.2$ $Z_\odot$), leaving models of stellar evo

David I. Dunsky, Gordan Krnjaic, Elena Pinetti

Since dark matter is only known to have gravitational interactions, it may plausibly decay to gravitons on cosmological timescales. Although such a scenario can be easily realized, there are currently no known limits on this possibility based on indirect detection searches. We find that the gravitons produced in dark matter decays can convert to photons in l

Eric R. Coughlin, C. J. Nixon

Stars partially destroyed by a supermassive black hole (SMBH) in a partial tidal disruption event (TDE) can be ejected from the SMBH. Previous investigations attributed this positive-energy/velocity kick to asymmetries in the mass lost by the star near pericenter. We propose that asymmetric mass loss is not predominantly responsible for "kicking" the star, a

Bo Yang

We introduce a universal formulation of the generalized real space interactions with translational invariance, when projected into a single Landau level, can be equivalent to density-density interaction projected into any Chern bands (e.g. Landau levels, continuous moire Chern bands and discrete lattice Chern bands). By constructing a complete basis of gener

Juan A. Sanchez, Vishnu Reddy, Lucille Le Corre, Neil Pearson

Impacts are the most ubiquitous processes on planetary bodies in our solar system. During these impact events, shock waves can deposit enough energy to produce shock-induced darkening in the target material, resulting in an alteration of its spectral properties. This spectral alteration can lead to an ambiguous taxonomic classification of asteroids and an in

Seval Taşdemir, Deniz Cennet Çınar, Remziye Canbay, Serkan Taştan

We conducted an in-depth analysis of NGC 6793 open cluster via Gaia DR3 data, including astrometric, spectroscopic, and photometric measurements. Selection of 147 stars, which show membership probabilities $P\geq0.5$ were classified as likely members. The mean trigonometric parallaxes and proper-motion components of the cluster were found to be $\varpi = 1.6