November 2024 arXiv papers — page 153

Kamalesh Jana, Amanda B. B. de Souza, Yonghao Mi, Shima Gholam-Mirzaei

Using optical technology for current injection and electromagnetic emission simplifies the comparison between materials. Here, we inject current into monolayer graphene and bulk gallium arsenide (GaAs) using two-color quantum interference and detect the emitted electric field by electro-optic sampling. We find the amplitude of emitted terahertz (THz) radiati

Panwen Hu, Nan Xiao, Feifei Li, Yongquan Chen

In this era of videos, automatic video editing techniques attract more and more attention from industry and academia since they can reduce workloads and lower the requirements for human editors. Existing automatic editing systems are mainly scene- or event-specific, e.g., soccer game broadcasting, yet the automatic systems for general editing, e.g., movie or

Jen-Ping Chu, Mitul Luhar, Partrick Lynett

This paper evaluates the experimental generation of internal solitary waves (ISWs) in a miscible two-layer system with a free surface using a jet-array wavemaker (JAW). Unlike traditional gate-release experiments, the JAW system generates ISWs by forcing a prescribed vertical distribution of mass flux. Experiments examine three different layer-depth ratios,

Cyrille Kone, Marc Jourdan, Emilie Kaufmann

The problem of identifying the best answer among a collection of items having real-valued distribution is well-understood. Despite its practical relevance for many applications, fewer works have studied its extension when multiple and potentially conflicting metrics are available to assess an item's quality. Pareto set identification (PSI) aims to identify t

Suzanne Boyd, Matthew Hoeppner

For the family of complex rational functions of the form $R_{n,c,a}(z) = z^n + \dfrac{a}{z^n}+c$, known as ``Generalized McMullen maps'', for $a\neq 0$ and $n \geq 3$ fixed, we study the boundedness locus in some one-dimensional slices of the $(a,c)$-parameter space, by fixing a parameter or imposing a relation. First, if we fix $c$ with $|c|\geq 6$ while al

Zetian Chen, Noa Mazurski, Jacob Engelberg, Uriel Levy

Active metasurfaces hold great promise for spatial light modulation, and electro-optic tuning using lithium niobate is particularly attractive due to its high transparency and well-established thin-film platform. In this work, we present a free-space transmissive light modulator based on a seemingly un-patterned thin-film lithium niobate-on-insulator platfor

Jiechao Gao, Yuangang Li, Syeda Faiza Ahmed

The rapid acceleration of global urbanization has introduced novel challenges in enhancing urban infrastructure and services. Spatio-temporal data, integrating spatial and temporal dimensions, has emerged as a critical tool for understanding urban phenomena and promoting sustainability. In this context, Federated Learning (FL) has gained prominence as a dist

D. A. Vásquez-Torres, J. A. Toalá, A. Sacchi, M. A. Guerrero

Multi-epoch Chandra and XMM-Newton observations of the symbiotic system R Aquarii (R Aqr) spanning 22 yr are analysed by means of a reflection model produced by an accretion disc. This methodology helps dissecting the contribution from different components in the X-ray spectra of R Aqr: the soft emission from the jet and extended emission, the heavily-exting

Amelie Piveteau, Alban Seguinard, Piotr Mironowicz, Mohamed Bourennane

Quantum technologies provide many applications for information processing tasks that are impossible to realize within classical physics. These capabilities include such fundamental resources as generating secure, i.e. private and unpredictable random values. Yet, the problem of quantifying the amount of generated randomness is still not fully solved. This wo

Tianyu Yang, Yiyang Nan, Lisen Dai, Zhenwen Liang

Audio-Visual Question Answering (AVQA) is a challenging task that involves answering questions based on both auditory and visual information in videos. A significant challenge is interpreting complex multi-modal scenes, which include both visual objects and sound sources, and connecting them to the given question. In this paper, we introduce the Source-aware

N. Cribiori, F. Farakos, N. Liatsos

We argue that scale-separated AdS$_2$ vacua with at least two preserved supercharges cannot arise from flux compactifications in a regime of computational control. We deduce this by showing that the AdS$_2$ scale is parametrically of the same order as the tension of a fundamental BPS domain wall, which provides an upper bound on the UV cutoff. Since the latt

David Rasmussen Lolck, Laura Mančinska, Manaswi Paraashar

This paper investigates the impact of noise in the quantum query model, a fundamental framework for quantum algorithms. We focus on the scenario where the oracle is subject to non-unitary (or irreversible) noise, specifically under the \textit{faulty oracle} model, where the oracle fails with a constant probability and acts as identity. Regev and Schiff (ICA

Shrobona Bagchi

Quantum speed limit is a fundamental speed limit for the evolution of quantum states. It is the single-most important interpretation of the time energy uncertainty relation. Recently the speed limit of quantum correlations have been proposed like the concurrence for pure quantum states. In this direction, we derive a speed limit bound for a quantum correlati

Ali Kadhim Yaqoob, Ahmad Kadri Junoh

Increasing the complexity of solving budgetary allocation (NP-hardness problem) has led a wide range of methods to minimize the costs. Metaheuristics and Linear Programming (LP) are the most optimization in this fields. Therefore, this study provides insights and a deep understanding of the applicability of LP models in industry and how to formulate SM and a

Wenqiang Sun, Shuo Chen, Fangfu Liu, Zilong Chen

In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins with the insight that both the spatial structure of a 3D scene and the temporal evolution of a 4D scene can be effectively represented through sequences of video frames. While rec

Victor M. Bastidas, Nathan Fitzpatrick, K. J. Joven, Zane M. Rossi

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can results in significant overhead due to the exponentially growing size of some symmetry groups as the number of particles increases. Quantum computers hold the promise of achieving exponential speedup in

A. N. Kuchera, R. Shahid, J. Zhao, A. Edmondson

Background: $^{15}$Be is an unbound nuclide that has been observed to decay by one-neutron emission. Shell model calculations predict two low-lying states in its energy spectrum, however, only a single resonance has been observed from coincident measurements of $^{14}$Be+n. It has been suggested that the yet unobserved state may decay sequentially through th

Dario Francia, Federico Manzoni

We compute the surface charges associated to $p-$form gauge fields in arbitrary spacetime dimension for large values of the radial coordinate. In the critical dimension where radiation and Coulomb falloff coincide we find asymptotic charges involving asymptotic parameters, i.e. parameters with a component of order zero in the radial coordinate. However, in d

Panwen Hu, Jin Jiang, Jianqi Chen, Mingfei Han

The advent of AI-Generated Content (AIGC) has spurred research into automated video generation to streamline conventional processes. However, automating storytelling video production, particularly for customized narratives, remains challenging due to the complexity of maintaining subject consistency across shots. While existing approaches like Mora and Aesop

Yuedong Chen, Chuanxia Zheng, Haofei Xu, Bohan Zhuang

We introduce MVSplat360, a feed-forward approach for 360{\deg} novel view synthesis (NVS) of diverse real-world scenes, using only sparse observations. This setting is inherently ill-posed due to minimal overlap among input views and insufficient visual information provided, making it challenging for conventional methods to achieve high-quality results. Our

Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao

Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle basic conversations but struggle with precise pixel-level grounding in videos. To address this, we introduce VideoGLaMM, a LMM designed for fine-grained pixel-level grounding in video

Friedrich Hübner, Benjamin Doyon

The generalized hydrodynamics (GHD) equation is the equivalent of the Euler equations of hydrodynamics for integrable models. Systems of hyperbolic equations such as the Euler equations usually develop shocks and are plagued by problems of uniqueness. We establish for the first time the existence and uniqueness of solutions to the full GHD equation and the a

Andrea Egidio Monti

Let $S$ be a closed orientable surface of genus at least two. We introduce a bordification of the moduli space $\mathcal{PT}(S)$ of complex projective structures, with a boundary consisting of projective classes of half-translation surfaces. Thurston established an equivalence between complex projective structures and hyperbolic surfaces grafted along a meas

Yujia Hu, Tuan-Phong Nguyen, Shrestha Ghosh, Simon Razniewski

Large language models (LLMs) have majorly advanced NLP and AI, and next to their ability to perform a wide range of procedural tasks, a major success factor is their internalized factual knowledge. Since Petroni et al. (2019), analyzing this knowledge has gained attention. However, most approaches investigate one question at a time via modest-sized pre-defin

Kaizhe Hu, Zihang Rui, Yao He, Yuyao Liu

Visual imitation learning methods demonstrate strong performance, yet they lack generalization when faced with visual input perturbations, including variations in lighting and textures, impeding their real-world application. We propose Stem-OB that utilizes pretrained image diffusion models to suppress low-level visual differences while maintaining high-leve

Benoît Dubus, Tobias Haas, Nicolas J. Cerf

The Jordan-Schwinger map is widely employed to switch between bosonic or fermionic mode operators and spin observables, with numerous applications ranging from quantum field theories of magnetism and ultracold quantum gases to quantum optics. While the construction of observables obeying the algebra of spin operators across multiple modes is straightforward,

Nicolas Baradel, Quentin Cormier

We investigate an optimal control problem motivated by neuroscience, where the dynamics is driven by a Poisson process with a controlled stochastic intensity and an unknown parameter. Given a prior distribution for the unknown parameter, we describe its evolution using Bayes' rule. We reformulate the optimization problem by applying Girsanov's theorem and es

Henry Cohn, Anqi Li

We prove that the kissing numbers in 17, 18, 19, 20, and 21 dimensions are at least 5730, 7654, 11692, 19448, and 29768, respectively. The previous records were set by Leech in 1967, and we improve on them by 384, 256, 1024, 2048, and 2048. Unlike the previous constructions, the new configurations are not cross sections of the Leech lattice minimal vectors.

Bavo Lesy, Ali Anwar, Siegfried Mercelis

Recently, there has been growing interest in autonomous shipping due to its potential to improve maritime efficiency and safety. The use of advanced technologies, such as artificial intelligence, can address the current navigational and operational challenges in autonomous shipping. In particular, inland waterway transport (IWT) presents a unique set of chal

Manuel Frank, Haithem Afli

We propose a training-free approach to improve sentence embeddings leveraging test-time compute by applying generative text models for data augmentation at inference time. Unlike conventional data augmentation that utilises synthetic training data, our approach does not require access to model parameters or the computational resources typically required for

Sara Klein, Xiangyuan Zhang, Tamer Başar, Simon Weissmann

In this work, we study $\gamma$-discounted infinite-horizon tabular Markov decision processes (MDPs) and introduce a framework called dynamic policy gradient (DynPG). The framework directly integrates dynamic programming with (any) policy gradient method, explicitly leveraging the Markovian property of the environment. DynPG dynamically adjusts the problem h

Nipun Sandamal Ranasekara Pathiranage, Stefania Cristina, Kenneth P. Camilleri

In this research work, we address the problem of robust iris centre localisation in unconstrained conditions as a core component of our eye-gaze tracking platform. We investigate the application of U-Net variants for segmentation-based and regression-based approaches to improve our iris centre localisation, which was previously based on Bayes' classification

Zenon Jan Jabłoński, Il Bong Jung, Jan Stochel

We prove that a CPD unilateral weighted shift $W_{\lambda}$ of type III is a quasi-affine transform of the operator $M_z$ of multiplication by the independent variable on the $L^2(\rho)$-closure of analytic complex polynomials on the complex plane, where $\rho$ is a measure precisely determined by $W_{\lambda}$. By using this model, we provide necessary and

Nelson L. Santos Junior, João A. M. Gondim

In this paper, we study the optimal control for an SEIR model adapted to the vaccination strategy of susceptible individuals. There are factors associated with a vaccination campaign that make this strategy not only a public health issue but also an economic one. In this case, optimal control is important as it minimizes implementation costs. We consider the

Monica Munnangi

A large amount of information in today's world is now stored in knowledge bases. Named Entity Recognition (NER) is a process of extracting, disambiguation, and linking an entity from raw text to insightful and structured knowledge bases. More concretely, it is identifying and classifying entities in the text that are crucial for Information Extraction, Seman

Zhaoyang Zhang, Hongtu Zhu, Ziqi Chen, Yingjie Zhang

In this paper, we aim to address a significant challenge in the field of missing data imputation: identifying and leveraging the interdependencies among features to enhance missing data imputation for tabular data. We introduce a novel framework named the Bipartite and Complete Directed Graph Neural Network (BCGNN). Within BCGNN, observations and features ar

Kristin Sheridan, Shuchi Chawla

In this paper we study flow problems on temporal networks, where edge capacities and travel times change over time. We consider a network with $n$ nodes and $m$ edges where the capacity and length of each edge is a piecewise constant function, and use $\mu=\Omega(m)$ to denote the total number of pieces in all of the $2m$ functions. Our goal is to design exa

Siming Huang, Tianhao Cheng, J. K. Liu, Jiaran Hao

Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are increasingly approaching the performance levels of proprietary models, high-quality code LLMs suitable for rigorous scientific investigation, particularly those with reproducible dat

Panagiotis Tolias, Fotios Kalkavouras, Tobias Dornheim, Federico Lucco Castello

The recently derived Fourier--Matsubara expansion of imaginary--time correlation functions comprises an exact result of linear response theory for finite-temperature quantum many-body systems. In its density--density version, the expansion facilitates systematic comparisons between quasi-exact \emph{ab initio} path integral Monte Carlo simulations and approx

Nicolas Chavarria

We study $\varepsilon$-stability in continuous logic. We first consider stability in a model, where we obtain a definability of types result with a better approximation than that in the literature. We also prove forking symmetry for $\varepsilon$-stability and briefly discuss finitely satisfiable types. We then do a short survey of $\varepsilon$-stability in

Romain Ruzziconi, Amartya Saha

We show that the Ward identities of a Carrollian CFT stress tensor at null infinity reproduce the leading and subleading soft graviton theorems for massless scattering in the bulk. We deduce the expressions of the stress tensor components in terms of the bulk radiative modes, and these components turn out to be local at $\mathscr{I}$ in terms of the twistor

Orlando Luongo, Marco Muccino

Cosmological parameters and dark energy (DE) behavior are generally constrained assuming \textit{a priori} models. We work out a model-independent reconstruction to bound the key cosmological quantities and the DE evolution. Through the model-independent \textit{B\'ezier interpolation} method, we reconstruct the Hubble rate from the observational Hubble data

Stephen F. King, Xin Wang, Ye-Ling Zhou

We discuss modular domain walls and gravitational waves in a class of supersymmetric models where quark and lepton flavour symmetry emerges from modular symmetry. In such models a single modulus field $\tau$ is often assumed to be stabilised at or near certain fixed point values such as $\tau = {\rm i}$ and $\tau = \omega$ (the cube root of unity), in its fu

Zhaoyang Zhang, Ziqi Chen, Qiao Liu, Jinhan Xie

In this paper, we propose a novel framework, the Sampling-guided Heterogeneous Graph Neural Network (SHT-GNN), to effectively tackle the challenge of missing data imputation in longitudinal studies. Unlike traditional methods, which often require extensive preprocessing to handle irregular or inconsistent missing data, our approach accommodates arbitrary mis

Linghang Kong, Zimu Li, Zi-Wen Liu

We consider quantum circuit models where the gates are drawn from arbitrary gate ensembles given by probabilistic distributions over certain gate sets and circuit architectures, which we call stochastic quantum circuits. Of main interest in this work is the speed of convergence of stochastic circuits with different gate ensembles and circuit architectures to

Xiaoyu Zhang

The core of the Taylor-Wiles and Taylor-Wiles-Kisin method in proving modularity lifting theorems is the construction of Taylor-Wiles primes satisfying certain conditions relating automorphic side and Galois side. In this article, we construct such primes and develop the automorphic side of Taylor-Wiles method for definite special orthogonal or symplectic gr

Dongxin Zhang, Aravind Raji, Luis M. Vicente-Arche, Alexandre Gloter

The recent discovery of superconductivity in infinite-layer (IL, ABO$_2$) nickelates has opened a new avenue to deepen the understanding of high-temperature superconductivity. However, progress in this field is slowed by significant challenges in material synthesis and the scarcity of research groups capable of producing high quality superconducting samples.

E. A. Coello Pérez, T. Papenbrock

Collective modes emerge as the relevant degrees of freedom that govern low-energy excitations of atomic nuclei. These modes - rotations, pairing rotations, and vibrations - are separated in energy from non-collective excitations, making it possible to describe them in the framework of effective field theory. Rotations and pairing rotations are the remnants o

Bhupali Sharma

The real nature of nucleon-hyperon and hyperon-hyperon interaction is best understood by theoretical study of single lambda hypernuclei. Variational Monte-Carlo calculations have been done on some light lambda hypernuclei using realistic NN, NNN ; phenomenological {\Lambda}N and {\Lambda}NN interactions. The results obtained for different interactions show t

Zimu Li, Han Zheng, Zi-Wen Liu

The efficiency of locally generating unitary designs, which capture statistical notions of quantum pseudorandomness, lies at the heart of wide-ranging areas in physics and quantum information technologies. While there are extensive potent methods and results for this problem, the evidently important setting where continuous symmetries or conservation laws (m

Ankit Jha

Large-scale foundation models like CLIP have shown strong zero-shot generalization but struggle with domain shifts, limiting their adaptability. In our work, we introduce \textsc{StyLIP}, a novel domain-agnostic prompt learning strategy for Domain Generalization (DG). StyLIP disentangles visual style and content in CLIP`s vision encoder by using style projec

Marcos Caso-Huerta, Lili Bu, Shihua Chen, Stefano Trillo

We present the fascinating phenomena of resonant radiation emitted by transient rogue waves in cubic and quadratic nonlinear media, particularly those shed from Peregrine solitons, one of the main wavepackets used today to model real-world rogue waves. In cubic media, it turns out that the emission of radiation from a Peregrine soliton can be attributed to t

Shuai Wang, Weiwen Liu, Jingxuan Chen, Yuqi Zhou

Recent advances in foundation models, particularly Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs), have facilitated the development of intelligent agents capable of performing complex tasks. By leveraging the ability of (M)LLMs to process and interpret Graphical User Interfaces (GUIs), these agents can autonomously execute user ins

Francis Nimmo, Thorsten Kleine, Alessandro Morbidelli, David Nesvorny

The nucleosynthetic isotope signatures of meteorites and the bulk silicate Earth (BSE) indicate that Earth consists of a mixture of "carbonaceous" (CC) and "non-carbonaceous" (NC) materials. We show that the fration of CC material recorded in the isotopic composition of the BSE varies for different elements, and depends on the element's tendency to partition

Rômulo Damasclin Chaves dos Santos

This study investigates the dynamics of incompressible fluid flows through quaternionic variables integrated within Sobolev-Besov spaces. Traditional mathematical models for fluid dynamics often employ Sobolev spaces to analyze the regularity of the solution to the Navier-Stokes equations. However, with the unique ability of Besov spaces to provide localized

Yves Frémat

Hot stars, of spectral types O-, B-, and A-, represent a small fraction of the stars observed by the Gaia satellite. Their properties and the specifications of the on-board instruments make their identification challenging. In the Gaia DR3, 12, 104,577 targets have been assigned a temperature greater than 7500 K. It represents about 2.5 percent of the stars

Haru-Tada Sato

We introduce supersymmetric extensions of the Hom-Lie deformation of the Virasoro algebra, as realized in the GL(1,1) quantum superspace, for Bloch electron systems under Zeeman effects. The construction is achieved by defining generators through magnetic translations and spin matrix bases, specifically for the N=1 and N=2 supersymmetric deformed algebras. T

Cambyse Rouzé, Daniel Stilck França, Álvaro M. Alhambra

It is of great interest to understand the thermalization of open quantum many-body systems, and how quantum computers are able to efficiently simulate that process. A recently introduced disispative evolution, inspired by existing models of open system thermalization, has been shown to be efficiently implementable on a quantum computer. Here, we prove that,

A. Belhaj, S. E. Ennadifi

Inspired by an ontic view of the wavefunction in quantum mechanics and motivated by the universal interaction of gravity, we discuss a possible gravity implication in the state collapse mechanism. Concretely, we investigate the stability of the spatial superposition of a massive quantum state under the gravity effect. In this context, we argue that the stabi

Giorgia Marcelli, Tecla Bottinelli Montandon, Roya Ebrahimi Viand, Felix Höfling

Non-equilibrium molecular dynamics (NEMD) simulations of fluid flow have highlighted the peculiarities of nanoscale flows compared to classical fluid mechanics; in particular, boundary conditions can deviate from the no-slip behavior at macroscopic scales. For fluid flow in slit-shaped nanopores, we demonstrate that surface morphology provides an efficient c

Slobodan Filipovski, Darko Dimitrov, Martin Knor, Riste Škrekovski

The $\sigma_{t}$-irregularity (or sigma total index) is a graph invariant which is defined as $\sigma_{t}(G)=\sum_{\{u,v\}\subseteq V(G)}(d(u)-d(v))^{2},$ where $d(z)$ denotes the degree of $z$. This irregularity measure was proposed by R\' {e}ti [Appl. Math. Comput. 344-345 (2019) 107-115], and recently rediscovered by Dimitrov and Stevanovi\'c [Appl. Math.

Souhir Ben Amor, Thomas Möbius, Felix Müsgens

This paper combines a techno-economic energy system model with an econometric model to maximise electricity price forecasting accuracy. The proposed combination model is tested on the German day-ahead wholesale electricity market. Our paper also benchmarks the results against several econometric alternatives. Lastly, we demonstrate the economic value of impr

James Binney

We revisit the dynamics of razor-thin, stone-cold, self-gravitating discs. By recasting the equations into standard cylindrical coordinates, the linearised vertical dynamics of an exponential disc can be followed for several gigayears on a laptop in a few minutes. An initially warped disc rapidly evolves into a flat inner region and an outward-propagating sp

Maria D. Kazachenko, Jorge Perez-Gallego, Jennifer Miller, Francisco Vielma

In this paper we share the experience of the U.S. National Science Foundation (NSF) National Solar Observatory (NSO) scientists, educators and public outreach officers organizing an eclipse viewing party at a sports complex stadium on the US/Mexico border in Eagle Pass, TX in collaboration with educators from Eagle Pass and Uvalde areas. We describe reasons

Anna Chiara Alfano, Orlando Luongo, Marco Muccino

Even though the Dark Energy Spectroscopic Instrument (DESI) mission does not exclude a dynamical dark energy evolution, the concordance paradigm, i.e., the $\Lambda$CDM model, remains statistically favored, as it depends on the fewest number of free parameters. In this respect, high redshift astrophysical sources, such as gamma-ray bursts, represent a formid

Fayez Abu-Ajamieh, Nobuchika Okada, Sudhir K. Vempati

We use the Weak Gravity Conjecture (WGC) to investigate the impact of charge dequantization arising from non-local QED on the scale of non-locality of neutrinos. We find this scale to be <= 87 TeV, which could be probed in future colliders. We also investigate the electric force and potential in non-local QED and use them to reformulate the Weak Gravity Conj

Roshni G. Iyer, Yewen Wang, Wei Wang, Yizhou Sun

It is largely agreed that social network links are formed due to either homophily or social influence. Inspired by this, we aim at understanding the generation of links via providing a novel embedding-based graph formation model. Different from existing graph representation learning, where link generation probabilities are defined as a simple function of the

Saikat Mahapatra, Riddhick Birbonshi, Arnab Patra

In this paper, several significant upper bounds for the numerical radius and $a$-numerical radius of an element in a $\mathcal{C}^*$-algebra are obtained using Orlicz functions. Many well-known results are obtained from our findings, depending on specific choices of Orlicz functions.

Sevag Gharibian, Carsten Hecht

After nearly two decades of research, the question of a quantum PCP theorem for quantum Constraint Satisfaction Problems (CSPs) remains wide open. As a result, proving QMA-hardness of approximation for ground state energy estimation has remained elusive. Recently, it was shown [Bittel, Gharibian, Kliesch, CCC 2023] that a natural problem involving variationa

Elliot Glazer, Ege Erdil, Tamay Besiroglu, Diego Chicharro

We introduce FrontierMath, a benchmark of hundreds of original, exceptionally challenging mathematics problems crafted and vetted by expert mathematicians. The questions cover most major branches of modern mathematics -- from computationally intensive problems in number theory and real analysis to abstract questions in algebraic geometry and category theory.

Junyi Li, Heng Huang

Bilevel Optimization has experienced significant advancements recently with the introduction of new efficient algorithms. Mirroring the success in single-level optimization, stochastic gradient-based algorithms are widely used in bilevel optimization. However, a common limitation in these algorithms is the presumption of independent sampling, which can lead

Rudra Dhara, Pritam Das, Sulagna Datta, Nilesh Kulkarni

Rare-earth diantimonides display intriguing ground states often associated with structural order, which can be manipulated in thin film geometries. In this study, we report epitaxial synthesis of one such compound, YbSb$_{2}$, on III-V substrates using molecular-beam epitaxy. The synthesized thin films exhibit large, non-saturating, linear magnetoresistance

Lukas Heidemann

We develop a graphical calculus of manifold diagrams which generalises string and surface diagrams to arbitrary dimensions. Manifold diagrams are pasting diagrams for $(\infty, n)$-categories that admit a semi-strict composition operation for which associativity and unitality is strict. The weak interchange law satisfied by composition of manifold diagrams i

I. N. Nikonorov, M. V. Barkov, M. Lyutikov

Bow shocks generated by pulsars moving through weakly ionized interstellar medium (ISM) produce emission dominated by non-equilibrium atomic transitions. These bow shocks are primarily observed as H$_\alpha$ nebulae. We developed a package, named Shu, that calculates non-LTE intensity maps in more than 150 spectral lines, taking into account geometrical prop

Andre Weiner, Janis Geise

Dynamic mode decomposition (DMD) is a popular approach to analyzing and modeling fluid flows. In practice, datasets are almost always corrupted to some degree by noise. The vanilla DMD is highly noise-sensitive, which is why many algorithmic extensions for improved robustness exist. We introduce a flexible optimization approach that merges available ideas fo

Satchit Chatterji, Erman Acar

Safe reinforcement learning (RL) is crucial for real-world applications, and multi-agent interactions introduce additional safety challenges. While Probabilistic Logic Shields (PLS) has been a powerful proposal to enforce safety in single-agent RL, their generalizability to multi-agent settings remains unexplored. In this paper, we address this gap by conduc

Yu Fu, Berndt Müller, Chathuranga Sirimanna

We compute medium corrections to the energy-energy correlator (EEC) for jets in electron-nucleus collisions at leading order in the QCD coupling and the interaction of the jet with the medium. We derive an analytical expression for the modification of the EEC as a function of the opening angle and show that the modification is strongest at large angles withi

Olaf Wysocki, Yue Tan, Thomas Froech, Yan Xia

Facade semantic segmentation is a long-standing challenge in photogrammetry and computer vision. Although the last decades have witnessed the influx of facade segmentation methods, there is a lack of comprehensive facade classes and data covering the architectural variability. In ZAHA, we introduce Level of Facade Generalization (LoFG), novel hierarchical fa

Han Zhang, Rui Liu, Yunwei, Li

Voltage support capability is critical for grid-forming (GFM) inverters with current-limiting control (CLC) during grid faults. Despite the findings on the voltage support for symmetrical grid faults, its applicability to more common but complex asymmetrical grid faults has yet to be verified rigorously. This letter fills the gap in the voltage support capab

Klemens Flöge, Srisruthi Udayakumar, Johanna Sommer, Marie Piraud

Recent advances in Artificial Intelligence have enabled multi-modal systems to model and translate diverse information spaces. Extending beyond text and vision, we introduce OneProt, a multi-modal AI for proteins that integrates structural, sequence, text, and binding site data. Using the ImageBind framework, OneProt aligns the latent spaces of protein modal

Chuqiao Song, Shunzhang Chen, Xinyi Cai, Hao Chen

Title: Sentiment Analysis of Spanish Political Party Communications on Twitter Using Pre-trained Language Models Authors: Chuqiao Song, Shunzhang Chen, Xinyi Cai, Hao Chen Comments: 21 pages, 6 figures Abstract: This study investigates sentiment patterns within Spanish political party communications on Twitter by leveraging BETO and RoBERTuito, two pre-train

Spyros Kamnis, Konstantinos Delibasis

This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited experimental data. By pre-training the transformer on extensive synthetic materials data and fine-tuning it with specific

Paweł Pietrzycki, Jan Stochel

We investigate the hyperrigidity of subsets of unital $C^*$-algebras annihilated by states (or, more generally, by completely positive maps). This is closely related to the concept of rigidity at $0$ introduced by G. Salomon, who studied hyperrigid subsets of Cuntz and Cuntz-Krieger algebras. The absence of the unit in a hyperrigid set allows for the existen

Panwen Hu, Rui Huang

Remote teaching has become popular recently due to its convenience and safety, especially under extreme circumstances like a pandemic. However, online students usually have a poor experience since the information acquired from the views provided by the broadcast platforms is limited. One potential solution is to show more camera views simultaneously, but it

Gereon Koßmann, René Schwonnek

This paper introduces a numerical framework for establishing lower bounds on the conditional von-Neumann entropy in device-independent quantum cryptography and randomness extraction scenarios. Leveraging a hierarchy of semidefinite programs derived from the Navascu\'es-Pironio-Acin (NPA) hierarchy, our tool enables efficient computation of entropy bounds bas

Aaron Hillman, Yu-tin Huang, Laurentiu Rodina, Justinas Rumbutis

In this letter, we consider effective field theories for light fields transforming under the fundamental or adjoint representation of a continuous group. We demonstrate that in the presence of gravity, crossing symmetry combined with two subtraction sum rules, leads to stringent constraints on the spectrum of its ultraviolet (UV) completion. Such constraints

Alejandro Gil-García, Paula Naomi Pilatus

We show that every Born Lie algebra can be obtained by the bicross product construction starting from two pseudo-Riemannian Lie algebras. We then obtain a classification of all Lie algebras up to dimension four and all six-dimensional nilpotent Lie algebras admitting an integrable Born structure. Finally, we study the curvature properties of the pseudo-Riema

T. E. Röber, R. Goedhart, S. İ. Birbil

Explainable AI (XAI) holds the promise of advancing the implementation and adoption of AI-based tools in practice, especially in high-stakes environments like healthcare. However, most of the current research lacks input from end users, and therefore their practical value is limited. To address this, we conducted semi-structured interviews with clinicians to

Ramkishor Sharma, Axel Brandenburg, Kandaswamy Subramanian, Alexander Vikman

We numerically study axion-U(1) inflation, focusing on the regime where the coupling between axions and gauge fields results in significant backreaction from the amplified gauge fields during inflation. These amplified gauge fields not only generate high-frequency gravitational waves (GWs), but also enhance spatial inhomogeneities in the axion field. GWs ser

Sum Kiu Law, Nok To Omega Tong

To a graph $\Gamma$, one can associate a hypertoric variety $\mathcal{M}(\Gamma)$ and its multiplicative version $\mathcal{M}^{\mathrm{mul}}(\Gamma)$. It was shown in [DMS24] that the cohomology of $\mathcal{M}^{\mathrm{mul}}(\Gamma)$ is computed by the CKS complex, which is a finite dimensional complex attached to $\Gamma$. The multiplicative hypertoric var

Michele Caprio, David Stutz, Shuo Li, Arnaud Doucet

An open question in \emph{Imprecise Probabilistic Machine Learning} is how to empirically derive a credal region (i.e., a closed and convex family of probabilities on the output space) from the available data, without any prior knowledge or assumption. In classification problems, credal regions are a tool that is able to provide provable guarantees under rea

Jack Gegenberg, Gabor Kunstatter

We consider a Yang-Mills type gauge theory of gravity based on the conformal group SO(4,2) coupled to a conformally invariant real scalar field. The goal is to generate fundamental dimensional constants via spontaneous breakdown of the conformal symmetry. In the absence of other matter couplings the resulting theory resembles Weyl-Einstein gravity, {with the

E. Panetier, S. N. Breton, R. A. García, A. Jiménez

Magnetic cycles of solar-like stars influence their internal physics. Thus, the frequency, amplitude, excitation rate, and damping of the acoustic oscillation modes (p-modes) vary with the cycle over time. We need to understand the impact of magnetic activity on p-modes in order to characterise precisely stars that will be observed by the ESA PLATO mission,

Meer Ashwinkumar, Mir Faizal, Arshid Shabir, Douglas J. Smith

We study twisted M-theory in a general conifold background, and describe it in terms of a 5d non-commutative Chern-Simons-matter theory, which is equivalent to 5d non-commutative Chern-Simons theory for a supergroup. In an equivalent description as twisted type IIA string theory, the matter degrees of freedom arise from topological strings stretched between

Pietro Bonfà, Francis Pratt, Diego Valenti, Ifeanyi John Onuorah

Kagome superconductors AV$_{3}$Sb$_{5}$ provide a unique platform for studying the interplay between a variety of electronic orders, including superconductivity, charge density waves, nematic phases and more. Understanding the evolution of the electronic state from the charge density wave to the superconducting transition is essential for unraveling the inte

Fujie Zhang, Peiqi Yu, Biao Yi, Baolei Zhang

Large Language Models (LLMs) have demonstrated remarkable capabilities across a variety of tasks in different domains. However, they sometimes generate responses that are logically coherent but factually incorrect or misleading, which is known as LLM hallucinations. Data-driven supervised methods train hallucination detectors by leveraging the internal state

Faisal N. Abu-Khzam, Tom Davot, Lucas Isenmann, Sergio Thoumi

Editing a graph to obtain a disjoint union of s-clubs is one of the models for correlation clustering, which seeks a partition of the vertex set of a graph so that elements of each resulting set are close enough according to some given criterion. For example, in the case of editing into s-clubs, the criterion is proximity since any pair of vertices (in an s-

Nicholas Pischke, Thomas Powell

We provide abstract, general and highly uniform rates of asymptotic regularity for a generalized stochastic Halpern-style iteration, which incorporates a second mapping in the style of a Krasnoselskii-Mann iteration. This iteration is general in two ways: First, it incorporates stochasticity completely abstractly, rather than fixing a sampling method; second

Shaokai Wu, Yuxiang Lu, Yapan Guo, Wei Ji

Computed Tomography (CT) enables detailed cross-sectional imaging but continues to face challenges in balancing reconstruction quality and computational efficiency. While deep learning-based methods have significantly improved image quality and noise reduction, they typically require large-scale training data and intensive computation. Recent advances in sce

Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus, Raunak Kumar

In many repeated auction settings, participants care not only about how frequently they win but also how their winnings are distributed over time. This problem arises in various practical domains where avoiding congested demand is crucial, such as online retail sales and compute services, as well as in advertising campaigns that require sustained visibility