March 2025 arXiv papers — page 11

June Young Kim

Accurate determination of the electron energy probability function (EEPF) is vital for understanding electron kinetics and energy distributions in plasmas. However, interpreting Langmuir probe current-voltage (I-V) characteristics is often hindered by nonlinear sheath dynamics, plasma instabilities, and diagnostic noise. These factors introduce fluctuations

Guillaume Braun, Minh Ha Quang, Masaaki Imaizumi

We investigate the problem of learning a Single Index Model (SIM)- a popular model for studying the ability of neural networks to learn features - from anisotropic Gaussian inputs by training a neuron using vanilla Stochastic Gradient Descent (SGD). While the isotropic case has been extensively studied, the anisotropic case has received less attention and th

Arthur Castello B. de Oliveira, Leilei Cui, Eduardo D. Sontag

This work explores generalizations of the Polyak-Lojasiewicz inequality (PLI) and their implications for the convergence behavior of gradient flows in optimization problems. Motivated by the continuous-time linear quadratic regulator (CT-LQR) policy optimization problem -- where only a weaker version of the PLI is characterized in the literature -- this work

Shunsuke Suzuki, Haruto Sonoda, Yusuke Sakai, Yuken Ohshiro

Supernova remnants (SNRs) provide crucial information of yet poorly understood mechanism of supernova explosion. Here we present XRISM high-resolution spectroscopy of the intermediate-mass-element (IME) ejecta in the SNR Cas A to determine their velocity distribution and thermal properties. The XRISM/Resolve spectrum in the 1.75-2.95 keV band extracted from

Ralph Howard

We prove the following version generalization of the Gronwall inequality: Let $\mathbf X$ be a Banach space and $U\subset \mathbf X$ an open convex set in $\mathbf X$. Let $f,g\colon [a,b]\times U\to \mathbf X$ be continuous functions and let $y,z\colon [a,b]\to U$ satisfy the initial value problems \begin{align*} y'(t)&=f(t,y(t)),\quad y(a)=y_0,\\ z'(t)&=g(

Mohamed BenSalah, Salih Tatar, Suleyman Ulusoy

This study investigates an inverse problem associated with a time-fractional HIV infection model incorporating nonlinear diffusion. The model describes the dynamics of uninfected target cells, infected cells, and free virus particles, where the diffusion terms are nonlinear density functions. The primary objective is to recover the unknown diffusion function

Li Yang, Dongbo Wang

How DNA-binding proteins locate specific genomic targets remains a central challenge in molecular biology. Traditional protein-centric approaches, which rely on wet-lab experiments and visualization techniques, often lack genome-wide resolution and fail to capture physiological dynamics in living cells. Here, we introduce a DNA-centric strategy that leverage

Christopher Herbig

In [3, Theorem 6.7B], the authors use the Main Theorems of Brauer to give a proof of Burnside's Normal $p$-complement Theorem. Unfortunately, the proof contains an error. We take this opportunity to give a proof along similar lines, circumventing the error by means of a well-known result on traces of totally positive cyclotomic integers.

In Hak Moon

This study presents a comprehensive evaluation of five leading large language models (LLMs) - Chat GPT 4o, Copilot Pro, Gemini Advanced, Claude Pro, and Meta AI - on their performance in solving calculus differentiation problems. The investigation assessed these models across 13 fundamental problem types, employing a systematic cross-evaluation framework whe

Peter Crooks, Xiang Gao, Mitchell Pound, Casen Thompson

In this expository note, we give a self-contained introduction to some modern incarnations of Hamiltonian reduction. Particular emphasis is placed on applications to symplectic geometry and geometric representation theory. We thereby discuss abelianization in Hamiltonian geometry, reduction by symplectic groupoids, and the Moore--Tachikawa conjecture.

Anas Saleh

Calculating the von Neumann entanglement entropy from experimental data is challenging due to its dependence on the complete wavefunction, forcing reliance on approximations such as classical mutual information (MI). We propose a machine learning approach using a graph neural network to predict the von Neumann entropy directly from experimentally accessible

Amit Seta, N. M. McClure-Griffiths

Magnetic fields are an important component of the interstellar medium (ISM) of galaxies. The thermal gas in the ISM has a multiphase structure, broadly divided into ionised, atomic, and molecular phases. The connection between the multiphase ISM gas and magnetic field is not known and this makes it difficult to account for their impact on star formation and

Zhenlong Li, Huan Ning, Song Gao, Krzysztof Janowicz

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute g

Jianqi Liu

In this paper, we introduce a new induction functor $\mathrm{Ind}^V_U$ between module categories corresponding to an embedding of vertex operator algebras (VOAs) $U \hookrightarrow V$. This induction functor is essentially defined at the level of the finite (Zhu) algebras, which we call the \emph{finite induction functor}. Under suitable conditions on $U$ an

Stefan Forcey

Planes are familiar mathematical objects which lie at the subtle boundary between continuous geometry and discrete combinatorics. A plane is geometrical, certainly, but the ways that two planes can interact break cleanly into discrete sets: the planes can intersect or not. Here we review how oriented matroids can be used to try to capture the combinatorial a

Aly Lidayan, Yuqing Du, Eliza Kosoy, Maria Rufova

What drives exploration? Understanding intrinsic motivation is a long-standing challenge in both cognitive science and artificial intelligence; numerous objectives have been proposed and used to train agents, yet there remains a gap between human and agent exploration. We directly compare adults, children, and AI agents in a complex open-ended environment, C

Rahul Agarwal, Amit Jaspal, Saurabh Gupta, Omkar Vichare

Recommender systems operate in closed feedback loops, where user interactions reinforce popularity bias, leading to over-recommendation of already popular items while under-exposing niche or novel content. Existing bias mitigation methods, such as Inverse Propensity Scoring (IPS) and Off-Policy Correction (OPC), primarily operate at the ranking stage or duri

Cornelius Fritz, Riccardo Rastelli, Michael Fop, Alberto Caimo

Durable interactions are ubiquitous in social network analysis and are increasingly observed with precise time stamps. Phone and video calls, for example, are events to which a specific duration can be assigned. We term data encoding interactions with the start and end times ``durational event data''. Recent advances in data collection have enabled the obser

Dhrubajyoti Ghosh, William Boettcher, Rob Johnston, Soumendra Lahiri

Escalating proliferation of inorganic accounts, commonly known as bots, within the digital ecosystem represents an ongoing and multifaceted challenge to online security, trustworthiness, and user experience. These bots, often employed for the dissemination of malicious propaganda and manipulation of public opinion, wield significant influence in social media

Veronique Petit, Mary E. Oksala

Stellar Magnetism affects all spectral types and exists and varies throughout the evolution of stars. Magnetic fields can affect not only the interior of stars, but also their circumstellar environments. In this chapter, we concentrate on the magnetic fields that can be measured at the surface of stars through the influence of the Zeeman effect on their spec

Alfonso Artigue

This article is about the shadowing property of homeomorphisms on compact metric spaces and the map associating a point of the space to each pseudo-orbit, called 'shadowing map'. Based on some particular dynamical properties, as expansivity, we develop a brief theory and a hierarchy of such maps. We consider examples as odometers, shifts on infinite

Teresa Sinico, Giovanni Boschetti, Pedro Neto

Physical human-robot interaction (pHRI) remains a key challenge for achieving intuitive and safe interaction with robots. Current advancements often rely on external tactile sensors as interface, which increase the complexity of robotic systems. In this study, we leverage the intrinsic tactile sensing capabilities of collaborative robots to recognize digits

Mattia Scarpa, Francesco Pase, Ruggero Carli, Mattia Bruschetta

Digital twins for power electronics require accurate power losses whose direct measurements are often impractical or impossible in real-world applications. This paper presents a novel hybrid framework that combines physics-based thermal modeling with data-driven techniques to identify and correct power losses accurately using only temperature measurements. O

Kerem Bozkurt, Christoph Lohrmann, Felix Weinhardt, Daniel Hanke

Biofilms exposed to flow experience shear stress, which leads to a competitive interaction between the growth and development of a biofilm and shearing. In this study, Pseudonomas fluorescene biofilm was grown in a microfluidic channel and exposed to forced flow of an aqueous solution of variable velocity. It can be observed that under certain conditions pre

Karoliina Lehtinen, Keya Prakash

History-determinism is a restricted notion of nondeterminism in automata, where the nondeterminism can be successfully resolved based solely on the prefix read so far. History-deterministic automata still allow for exponential succinctness in automata over infinite words compared to deterministic automata (Kuperberg and Skrzypczak, 2015), allow for canonical

Lili Mu, Volkmar Welker

For a polynomial $f(t) = 1+f_0t+\cdots +f_{d-1}t^d$ with positive integer coefficients Bell and Skandera ask if real rootedness of f(t) implies that there is a simplicial complex with f-vector $(1,f_0 \ldots,f_{d-1})$. In this paper we discover properties implied by the real rootedness of f(t) in terms of the binomial representation $f_i = \binom{x_{i+1}}{i+

J. Kersten, E. Körding, P. A. Woudt, P. J. Groot

A program to search for radio emission from dwarf-novae-type cataclysmic variables was conducted with the South African MeerKAT radio telescope. The dwarf novae RU Pegasi, V426 Ophiuchi and IP Pegasi were detected during outburst at L-band (1284 MHz central frequency). Previously, only one cataclysmic variable was radio-detected at a frequency this low. We n

J. H. Pixley, Pavel A. Volkov

Recent proposals for the realization of time-reversal symmetry breaking and topological superconductivity in twisted nodal superconductors have led to a surge of theoretical and experimental studies of these systems, marking one of the newest entries in the rapidly growing field of moiré materials. The interplay between order parameters of the separate layer

Julian Willkomm, Kai Wulff, Johann Reger

We consider the set-point control problem for nonlinear systems with flat output that are subject to perturbations. The nonlinear dynamics as well as the perturbations are locally Lipschitz. We apply the model-following control (MFC) approach which consists of a model control loop (MCL) for a feedforward generation and a process control loop (PCL) that compe

Sharad Sharan, Amit Jain, Roshan T. Eapen, Puneet Singla

This paper employs an alternate dynamical model of the circular restricted three body problem to quantify uncertainties associated with spacecraft thrusting maneuvers. A non-product quadrature scheme known as Conjugate Unscented Transform (CUT) is employed to determine the higher order system sensitivities through a computationally efficient data driven appr

J. Polihronov

This article reviews the properties of the self-similar solutions of the Navier-Stokes equation for incompressible fluids. Since any smooth solution can be embedded into a self-similar solution at the identity scale, it follows that under standard flow conditions, the initial solution will remain smooth for all time as long as the self-similar solution is se

Vanessa Teague, Arash Mirzaei

We examine the security of a cloud storage service that makes very strong claims about the ``trustless'' nature of its security. We find that, although stored files are end-to-end encrypted, the encryption method allows for effective dictionary attacks by a malicious server when passwords only just meet the minimum length required. Furthermore, the file shar

Anirudh Satheesh, Keenan Powell

Traffic congestion in modern cities is exacerbated by the limitations of traditional fixed-time traffic signal systems, which fail to adapt to dynamic traffic patterns. Adaptive Traffic Signal Control (ATSC) algorithms have emerged as a solution by dynamically adjusting signal timing based on real-time traffic conditions. However, the main limitation of such

Zhifan Ye, Yonggan Fu, Jingqun Zhang, Leshu Li

The rapidly advancing field of Augmented and Virtual Reality (AR/VR) demands real-time, photorealistic rendering on resource-constrained platforms. 3D Gaussian Splatting, delivering state-of-the-art (SOTA) performance in rendering efficiency and quality, has emerged as a promising solution across a broad spectrum of AR/VR applications. However, despite its e

Cong Duy Vu Hoang, Gioacchino Tangari, Clemence Lanfranchi, Dalu Guo

The growing adoption of large language models (LLMs) in business applications has amplified interest in Natural Language to SQL (NL2SQL) solutions, in which there is competing demand for high performance and efficiency. Domain- and customer-specific requirements further complicate the problem. To address this conundrum, we introduce Distill-C, a distilled cu

Ufuk Beyaztas, Han Lin Shang, Semanur Saricam

We introduce a novel function-on-function linear quantile regression model to characterize the entire conditional distribution of a functional response for a given functional predictor. Tensor cubic $B$-splines expansion is used to represent the regression parameter functions, where a derivative-free optimization algorithm is used to obtain the estimates. Qu

Nils Friederich, Angelo Jovin Yamachui Sitcheu, Annika Nassal, Erenus Yildiz

Microfluidic Live-Cell Imaging (MLCI) yields data on microbial cell factories. However, continuous acquisition is challenging as high-throughput experiments often lack real-time insights, delaying responses to stochastic events. We introduce three components in the Experiment Automation Pipeline for Event-Driven Microscopy to Smart Microfluidic Single-Cell A

Zahra TehraniNasab, Amar Kumar, Tal Arbel

Text-to-image diffusion models have demonstrated a remarkable ability to generate photorealistic images from natural language prompts. These high-resolution, language-guided synthesized images are essential for the explainability of disease or exploring causal relationships. However, their potential for disentangling and controlling latent factors of variati

Muhammad Sajjad Akbar

The growing use of generative AI tools like ChatGPT has raised urgent concerns about their impact on student learning, particularly the potential erosion of critical thinking and creativity. As students increasingly turn to these tools to complete assessments, foundational cognitive skills are at risk of being bypassed, challenging the integrity of higher ed

Fan-Keng Sun, Yu-Cheng Wu, Duane S. Boning

Time series data are everywhere -- from finance to healthcare -- and each domain brings its own unique complexities and structures. While advanced models like Transformers and graph neural networks (GNNs) have gained popularity in time series forecasting, largely due to their success in tasks like language modeling, their added complexity is not always neces

Yasmine Amhis, Jeremy Andrea, Etienne Augé, Sara Bolognesi

In view of the European Strategy for Particle Physics process, the French HEP community has organized a national process of collecting written contributions and has pursued a series of workshops culminating with a national symposium held in Paris on January 20-21, 2025 that involved over 280 scientists https://indico.in2p3.fr/event/34662/. The present docume

Loris Belcastro, Cristian Cosentino, Fabrizio Marozzo, Merve Gündüz-Cüre

In recent years, social media has emerged as a primary channel for users to promptly share feedback and issues during disasters and emergencies, playing a key role in crisis management. While significant progress has been made in collecting and analyzing social media content, there remains a pressing need to enhance the automation, aggregation, and customiza

Maicol A. Ochoa

We formulate a semiclassical theory for electron transport in open quantum systems with electron-phonon interactions adequate for situations when the system's phonon dynamics is comparable with the electron transport timescale. Starting from the Keldysh non-equilibrium Green's function formalism we obtain equations of motion for the retarded and lesser elect

Alexandre Arbey, Jamie Boyd, Daniel Britzger, Concetta Cartaro

Data preservation significantly increases the scientific output of high-energy physics experiments during and after data acquisition. For new and ongoing experiments, the careful consideration of long-term data preservation in the experimental design contributes to improving computational efficiency and strengthening the scientific activity in HEP through Op

Amar Kumar, Anita Kriz, Barak Pertzov, Tal Arbel

Vision-language foundation models (VLMs) have shown impressive performance in guiding image generation through text, with emerging applications in medical imaging. In this work, we are the first to investigate the question: 'Can fine-tuned foundation models help identify critical, and possibly unknown, data properties?' By evaluating our proposed method on a

Nisal Ranasinghe, Damith Senanayake, Saman Halgamuge

The ability to discover meaningful, accurate, and concise mathematical equations that describe datasets is valuable across various domains. Equations offer explicit relationships between variables, enabling deeper insights into underlying data patterns. Most existing equation discovery methods rely on genetic programming, which iteratively searches the equat

Adrian Bermudez-Villalva, Maryam Mehrnezhad, Ehsan Toreini

Online hate speech can harmfully impact individuals and groups, specifically on non-moderated platforms such as 4chan where users can post anonymous content. This work focuses on analysing and measuring the prevalence of online hate on 4chan's politically incorrect board (/pol/) using state-of-the-art Natural Language Processing (NLP) models, specifically tr

Sebastian Johann Wetzel, Seungwoong Ha, Raban Iten, Miriam Klopotek

Machine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulations. As artificial intelligence (AI) continues to grow in capability, these algorithms will enable many scientific discoveries beyond human capabilities. Since the primary goal of s

Julien Soulé, Jean-Paul Jamont, Michel Occello, Louis-Marie Traonouez

Multi-Agent Reinforcement Learning can lead to the development of collaborative agent behaviors that show similarities with organizational concepts. Pushing forward this perspective, we introduce a novel framework that explicitly incorporates organizational roles and goals from the $\mathcal{M}OISE^+$ model into the MARL process, guiding agents to satisfy co

Michael B. Lund

For generations, people have complained that things used to be better in the past. In this paper, we investigate this change by specifically looking at creativity in astronomy. To do this,we explore if older constellations reflected a greater sense of creativity on the part of those designing them than more modern constellations do. We find that things reall

George Trivizas, Matthew D. Feinstein, Euclides Almeida

Light generation through optical harmonics plays a pivotal role in photonics, driving innovations in coherent light sources, biological imaging, and spectroscopy. Traditional methods for tuning optical harmonics, including electrostatic gating, are inherently slow, presenting a bottleneck for the performance of integrated photonic devices. While all-optical

Samuel Belkadi, Steve Hong, Marian Chen, Miruna Cretu

Autoregressive models excel in efficiency and plug directly into the transformer ecosystem, delivering robust generalization, predictable scalability, and seamless workflows such as fine-tuning and parallelized training. However, they require an explicit sequence order, which contradicts the unordered nature of graphs. In contrast, diffusion models maintain

Yuhong Zhong, Daniel S. Berger, Pantea Zardoshti, Enrique Saurez

Pooling PCIe devices across multiple hosts offers a promising solution to mitigate stranded I/O resources, enhance device utilization, address device failures, and reduce total cost of ownership. The only viable option today are PCIe switches, which decouple PCIe devices from hosts by connecting them through a hardware switch. However, the high cost and limi

Yaniv Kurman, Kieran Hymas, Arkady Fedorov, William J. Munro

Executing quantum logic in cryogenic quantum computers requires a continuous energy supply from room-temperature control electronics. This dependence on external energy sources creates scalability limitations due to control channel density and heat dissipation. Here, we propose quantum batteries (QBs) as intrinsic quantum energy sources for quantum computati

Yuing Sun, Sam Addison Ankenbauer, Zhifan Guo, Yuchen Chen

Aging in place refers to the enabling of individuals to age comfortably and securely within their own homes and communities. Aging in place relies on robust infrastructure, prompting the development and implementation of both human-led care services and information and communication technologies to provide support. Through a long-term ethnographic study that

Pentti Kanerva

We model human and animal learning by computing with high-dimensional vectors (H = 10,000 for example). The architecture resembles traditional (von Neumann) computing with numbers, but the instructions refer to vectors and operate on them in superposition. The architecture includes a high-capacity memory for vectors, analogue of the random-access memory (RAM

Xu-Hong Ye, Ranieri D. Baldi, Yong-Yun Chen, Denis Bastieri

Radio galaxies (RGs) are a subclass of active galactic nuclei, which are suggested to be the parent populations of blazars. According to the accretion-ejection paragram, RGs can be classified into low-excitation or high-excitation radio galaxies (LERGs or HERGs). In this paper, we compiled a distance-limited ($z<0.15$) sample of 431 LERGs (Fanaroff-Riley, or

Wei Xu, Charles James Wagner, Junjie Luo, Qi Guo

Extracting depth information from photon-limited, defocused images is challenging because depth from defocus (DfD) relies on accurate estimation of defocus blur, which is fundamentally sensitive to image noise. We present a novel approach to robustly measure object depths from photon-limited images along the defocused boundaries. It is based on a new image p

Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim

A fundamental task in AI is providing performance guarantees for predictions made in unseen domains. In practice, there can be substantial uncertainty about the distribution of new data, and corresponding variability in the performance of existing predictors. Building on the theory of partial identification and transportability, this paper introduces new res

J. Dunsmore, L. M. Arthur, R. S. Kemp

Conventional feasibility studies of deep decarbonisation are often limited in their temporal scope, and are thus unable to draw conclusions about grid reliability over multi-decadal time periods. To address this problem, we introduce RESCORE, a fast and transparent model that uses 43 years of hourly weather data to evaluate both the cost and reliability char

Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia

Hashtag recommendation systems have emerged as a key tool for automatically suggesting relevant hashtags and enhancing content categorization and search. However, existing static models struggle to adapt to the highly dynamic nature of social media conversations, where new hashtags constantly emerge and existing ones undergo semantic shifts. To address these

Amit Jain, Roshan T. Eapen, Puneet Singla

This paper introduces a novel methodology that leverages the Hamilton-Jacobi solution to enhance non-linear model predictive control (MPC) in scenarios affected by navigational uncertainty. Using Hamilton-Jacobi-Theoretic approach, a methodology to improve trajectory tracking accuracy among uncertainties and non-linearities is formulated. This paper seeks to

Marco Caputo, Michele Russo, Emanuela Merelli

This work seeks to tackle the inherent complexity of dataspaces by introducing a novel data structure that can represent datasets across multiple levels of abstraction, ranging from local to global. We propose the concept of a multilevel graph, which is equipped with two fundamental operations: contraction and expansion of its topology. This multilevel graph

Thomas O'Brien, Ysobel Sims

We explore the use of GPT-4 on a humanoid robot in simulation and the real world as proof of concept of a novel large language model (LLM) driven behaviour method. LLMs have shown the ability to perform various tasks, including robotic agent behaviour. The problem involves prompting the LLM with a goal, and the LLM outputs the sub-tasks to complete to achiev

Fabian Jakob, Andrea Iannelli

We propose a novel approach for analyzing dynamic regret of first-order constrained online convex optimization algorithms for strongly convex and Lipschitz-smooth objectives. Crucially, we provide a general analysis that is applicable to a wide range of first-order algorithms that can be expressed as an interconnection of a linear dynamical system in feedbac

Michael Overton, Barrie Robison, Lucas Sheneman

The integration of Large Language Models (LLMs) into social science research presents transformative opportunities for advancing scientific inquiry, particularly in public administration (PA). However, the absence of standardized methodologies for using LLMs poses significant challenges for ensuring transparency, reproducibility, and replicability. This manu

Sophia Geris, Yvette Perrott

Galaxy cluster X-ray cavities are inflated by relativistic jets that are ejected into the intracluster medium by active galactic nuclei (AGN). AGN jets prevent predicted cooling flow establishment at the cluster centre, and while this process is not well understood in existing studies, simulations have shown that the heating mechanism will depend on the type

Kalliopi Basioti, Pritish Sahu, Qingze Tony Liu, Zihao Xu

Raven's Progressive Matrices (RPMs) is an established benchmark to examine the ability to perform high-level abstract visual reasoning (AVR). Despite the current success of algorithms that solve this task, humans can generalize beyond a given puzzle and create new puzzles given a set of rules, whereas machines remain locked in solving a fixed puzzle from a c

Tatsuyuki Hikita

By using level one polynomial representations of affine Hecke algebras of type $A$, we obtain a $(q,t)$-analogue of the chromatic symmetric functions of unit interval graphs which generalizes Syu Kato's formula for the chromatic symmetric functions of unit interval graphs. We show that at $q=1$, the $(q,t)$-chromatic symmetric functions essentially reduce to

Fatemeh Sarvi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke

In two-sided marketplaces, items compete for user attention, which translates to revenue for suppliers. Item exposure, indicated by the amount of attention items receive in a ranking, can be influenced by factors like position bias. Recent work suggests that inter-item dependencies, such as outlier items in a ranking, also affect item exposure. Outlier items

Thomas Bartz-Beielstein

The desirability-function approach is a widely adopted method for optimizing multiple-response processes. Kuhn (2016) implemented the packages desirability and desirability2 in the statistical programming language R, but no comparable packages exists for Python. The goal of this article is to provide an introduction to the desirability function approach usin

Oscar Dufour, Jakob Cordes, Alexandre Nicolas, Antoine Tordeux

Stop-and-go waves in vehicular traffic are commonly explained as a linear collective instability induced by e.g. response delays. We explore an alternative mechanism that more faithfully mirrors oscillation formation in dense single-file traffic. Stochastic noise plays a key role in this model; as it is increased, the base (uniform) flow abruptly switches to

Adrià Medeiros, Manuel Gundín, Dario A. Fioretto, Vincent Vinel

Polarization-encoded spin-photon interfaces constitute promising candidates for the development of stationary nodes used as photon receivers, for quantum communication and distributed quantum computing. Here we introduce a time-resolved tomography approach which allows observing the dynamics of an electron spin, in a semiconductor quantum dot, mapped onto th

Jian Tan

This paper establishes that multilinear Calder\'on--Zygmund operators and their maximal operators are bounded on Hardy spaces associated with ball quasi-Banach function spaces. Moreover, we also obtain the boundedness of multilinear pseudo-differential operators on local Hardy spaces associated with ball quasi-Banach function spaces. Since these (local) Hard

James Sarkies

The codegree Tur\'an density $\pi_{\text{co}}(F)$ of a $k$-uniform hypergraph (or $k$-graph) $F$ is the infimum over all $d$ such that a copy of $F$ is contained in any sufficiently large $n$-vertex $k$-graph $G$ with the property that any $(k-1)$-subset of $V(G)$ is contained in at least $dn$ edges. The problem of determining $\pi_{\text{co}}(F)$ for a $k$-

Jian Tan

In this paper, we prove the boundedness of multilinear fractional integral operators from products of Hardy spaces associated with ball quasi-Banach function spaces into their corresponding ball quasi-Banach function spaces. As applications, we establish the boundedness of these operators on various function spaces, including weighted Hardy spaces, variable

Nihat Ay, Lorenz J. Schwachhöfer

We study the torsion of the $\alpha$-connections defined on the density manifold in terms of a regular Riemannian metric. In the case of the Fisher-Rao metric our results confirm the fact that all $\alpha$-connections are torsion free. For the $\alpha$-connections obtained by the Otto metric, we show that, except for $\alpha = -1$, they are not torsion free.

Martin Malenický, Martin Cífka, Médéric Fourmy, Louis Montaut

Accurate 6D object pose estimation from images is a key problem in object-centric scene understanding, enabling applications in robotics, augmented reality, and scene reconstruction. Despite recent advances, existing methods often produce physically inconsistent pose estimates, hindering their deployment in real-world scenarios. We introduce PhysPose, a nove

Guillaume Fuchs, Florin Ghido, Dominik Weckbecker, Oliver Thiergart

Directional Audio Coding (DirAC) is a proven method for parametrically representing a 3D audio scene in B-format and is capable of reproducing it on arbitrary loudspeaker layouts. Although such a method seems well suited for low bitrate Ambisonic transmission, little work has been done on the feasibility of building a real system upon it. In this paper, we p

Andrea Conti, Yolanda Lozano, Niall T. Macpherson

We perform a complete classification of AdS$_2$ solutions of Type II supergravity realising $\mathcal{N}=6$ supersymmetry and OSp$(6|2)$ superconformal symmetry on backgrounds that are foliations of AdS$_2 \times \mathbb{CP}^3$ over a Riemann surface $\Sigma_2$. Such solutions only exist in type IIB supergravity and are in 1 to 1 correspondence with a fourth

Nat Gopalswamy, Pertti Makela, Hong Xie, Sachiko Akiyama

We report on the observation of first, second, and third harmonic components during an interplanetary (IP) type II solar radio burst observed on 2024 September 14 by the radio instruments on board Wind, the Solar Terrestrial Relations Observatory (STEREO), and the Parker Solar Probe. The eruption resulted in an ultrafast coronal mass ejection (CME) that had

Naëmi Leo, Jonathan S. White, Michel Kenzelmann, Takashi Honda

Magnetoelectric multiferroics promise direct cross-control between coexisting ferroelectric and ferromagnetic orders, which is of interest for applications in magnetism and spintronics. A particularly interesting type of cross-control is found in spin-spiral multiferroic Mn$_2$GeO$_4$, where a ferroelectric multi-domain distribution can be globally inverted

Henry Bradford, Jacob Willis

For a finitely generated lawless group $\Gamma$ and $n \in \mathbb{N}$, let $\mathcal{A}_{\Gamma} (n)$ be the minimal positive integer $M_n$ such that for all nontrivial reduced words $w$ of length at most $n$ in the free group of fixed rank $k \geq 2$, there exists $\overline{g} \in \Gamma^k$ of word-length at most $M_n$ with $w(\overline{g}) \neq e$. For a

Anton O. Pokusinskyi, Oleksandr V. Dobrovolskiy

Two-band superconductors host vortices from superfluid condensates of different electron bands. These vortices carry a fractional flux quantum and attract each other, coalescing to form a composite vortex with the whole flux quantum $\phi_0$. However, due to the differences in viscosity and flux of the vortices across different bands, composite vortices may

Zheng-Peng Duan, Jiawei Zhang, Xin Jin, Ziheng Zhang

Large-scale pre-trained diffusion models are becoming increasingly popular in solving the Real-World Image Super-Resolution (Real-ISR) problem because of their rich generative priors. The recent development of diffusion transformer (DiT) has witnessed overwhelming performance over the traditional UNet-based architecture in image generation, which also raises

Shounak De, Shruti Paranjape, Andrzej Pokraka, Marcus Spradlin

Motivated by the recent discovery of hidden zeros in particle and string amplitudes, we characterize zeros of individual graph contributions to the cosmological wavefunction of a scalar field theory. We demonstrate that these contributions factorize near these zeros for all tree graphs and provide evidence that this extends to loop graphs as well. We explici

Jixuan Leng, Chengsong Huang, Langlin Huang, Bill Yuchen Lin

Existing reasoning evaluation frameworks for Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) predominantly assess either text-based reasoning or vision-language understanding capabilities, with limited dynamic interplay between textual and visual constraints. To address this limitation, we introduce CrossWordBench, a benchmark designed

Anna Margarethe Limbach, Robert Scheidweiler, Eberhard Triesch

Let $P(k,n)$ be the set of products of $k$ factors from the set $\{1,\ldots , n\}.$ In 1955, Erd\H{o}s posed the problem of determining the order of magnitude of $|P (2, n)|$ and proved that $|P (2, n)| = o(n^2 )$ for $n \to\infty$. In 2015, Darda and Hujdurovi\'c asked whether, for each fixed $n$, $|P (k, n)|$ is a polynomial in $k$ of degree $\pi(n)$ - the

Cameron Fiore, Hongyi Fan, Benjamin Kimia

The image retrieval (IR) approach to image localization has distinct advantages to the 3D and the deep learning (DNN) approaches: it is seen-agnostic, simpler to implement and use, has no privacy issues, and is computationally efficient. The main drawback of this approach is relatively poor localization in both position and orientation of the query camera wh

Injy Hamed, Ngoc Thang Vu, Nizar Habash

Code-switching, the act of alternating between languages, emerged as a prevalent global phenomenon that needs to be addressed for building user-friendly language technologies. A main bottleneck in this pursuit is data scarcity, motivating research in the direction of code-switched data augmentation. However, current literature lacks comprehensive studies tha

Stam Nicolis

There are two approaches towards supersymmetry: The ``conventional approach'', in which the fields appear in the classical action and the ``stochastic approach'', in which they emerge upon introducing in the action the contribution of a certain determinant. The second approach relies, in particular, on the so-called Nicolai map. The relation between the two

Ningjing Tang, Megan Li, Amy Winecoff, Michael Madaio

Model documentation plays a crucial role in promoting transparency and responsible development of AI systems. With the rise of Generative AI (GenAI), open-source platforms have increasingly become hubs for hosting and distributing these models, prompting platforms like Hugging Face to develop dedicated model documentation guidelines that align with responsib

Maximilian Augustin, Yannic Neuhaus, Matthias Hein

Vision-language models (VLMs) are prone to object hallucinations, where they erroneously indicate the presenceof certain objects in an image. Existing benchmarks quantify hallucinations using relatively small, labeled datasets. However, this approach is i) insufficient to assess hallucinations that arise in open-world settings, where VLMs are widely used, an

Agam Shah, Liqin Ye, Sebastian Jaskowski, Wei Xu

Large Language Models (LLMs) are frequently utilized as sources of knowledge for question-answering. While it is known that LLMs may lack access to real-time data or newer data produced after the model's cutoff date, it is less clear how their knowledge spans across historical information. In this study, we assess the breadth of LLMs' knowledge using financi

Nitesh Kumar Singh, Ion Necoara

This paper considers smooth convex optimization problems with many functional constraints. To solve this general class of problems we propose a new stochastic perturbed augmented Lagrangian method, called SGDPA, where a perturbation is introduced in the augmented Lagrangian function by multiplying the dual variables with a subunitary parameter. Essentially,

Shutong Jin, Axel Kaliff, Ruiyu Wang, Muhammad Zahid

Data scarcity presents a key bottleneck for imitation learning in robotic manipulation. In this paper, we focus on random exploration data-actions and video sequences produced autonomously via motions to randomly sampled positions in the workspace-to investigate their potential as a cost-effective data source. Our investigation follows two paradigms: (a) ran

J. M. Tanoh Dje, Benoît. F. Sehba

In this work, we propose an atomic decomposition of the Bergman-Orlicz spaces on the complex upper half-plane. Using this result, we characterize Carleson embeddings with loss between Bergman-Orlicz spaces and certain Orlicz spaces. We also leverage this last result to control the composition operator between two Bergman-Orlicz spaces.

N. J Juris, Marykutty James, Jincy Devasia

We present a comprehensive analysis of AstroSat/LAXPC data of the second spin-up and second spin-down phases of the persistent X-ray pulsar 4U 1626-67. Flares followed by a broad dip are detected in the spin-up observations. The pulse profiles changed from a shoulder-like structure to a broad sinusoidal shape as the source underwent a torque reversal from sp

Himanshu Garg, Fleurianne Bertrand, Subhashree Mohapatra

Here, we present a least-squares based spectral element formulation for one-dimensional eigenvalue problems with interface conditions. First we develop the method for without interface case, then we extend it to interface case. Convergence analysis for eigenvalues and eigenfunctions have been discussed. Numerical experiments with different jump conditions ha

Haein Kong, Seonghyeon Moon

Large language models (LLMs) have been actively applied in the mental health field. Recent research shows the promise of LLMs in applying psychotherapy, especially motivational interviewing (MI). However, there is a lack of studies investigating how language models understand MI ethics. Given the risks that malicious actors can use language models to apply M