November 2024 arXiv papers — page 85

M. N'Diaye, A. Vigan, B. Engler, M. Kasper

Over the past decade, the high-contrast observation of disks and gas giant planets around nearby stars has been made possible on ground-based instruments using extreme adaptive optics (XAO). While these facilities produce images with a Strehl ratio larger than 90% in H-band in median observing conditions and high-flux regime, the correction leaves AO residua

Vinh Tran, Xuejian Shen, Mark Vogelsberger, Daniel Gilman

We present a novel analytic density profile for halos in self-interacting dark matter (SIDM) models, which accurately captures the isothermal-core configuration, i.e. where both the density and velocity dispersion profiles exhibit central plateaus in the halo innermost region. Importantly, the profile retains a simple and tractable functional form. We demons

Bjoern Hassfeld, Arthur Hebecker, Alexander Westphal

Making cosmological predictions in a multiverse is a fundamental theoretical challenge. Assuming that (quasi-)de Sitter vacua are quantum mechanically described by a finite-dimensional Hilbert space, we develop a detailed framework for making explicit anthropic predictions. A key challenge which we attempt to overcome arises because, almost unavoidably, cosm

Mathias Driesse, Gustav Uhre Jakobsen, Albrecht Klemm, Gustav Mogull

Using the worldline quantum field theory formalism, we compute the radiation-reacted impulse, scattering angle, radiated energy and recoil of a classical black hole (or neutron star) scattering event at fifth post-Minkowskian and sub-leading self-force orders (5PM-1SF). This state-of-the-art four-loop computation employs advanced integration-by-parts and dif

Menghe Zhang, Joonyeoup Kim, Yangwen Liang, Shuangquan Wang

Accurate hand motion capture and standardized 3D representation are essential for various hand-related tasks. Collecting keypoints-only data, while efficient and cost-effective, results in low-fidelity representations and lacks surface information. Furthermore, data inconsistencies across sources challenge their integration and use. We present UniHands, a no

Taiming Lu, Tianmin Shu, Alan Yuille, Daniel Khashabi

Planning with partial observation is a central challenge in embodied AI. A majority of prior works have tackled this challenge by developing agents that physically explore their environment to update their beliefs about the world state. In contrast, humans can $\textit{imagine}$ unseen parts of the world through a mental exploration and $\textit{revise}$ the

Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun

The typical Selective State-Space Model (SSM) used in Mamba addresses several limitations of Transformers, such as the quadratic computational complexity with respect to sequence length and the significant memory requirements during inference due to the key-value (KV) cache. However, the increasing size of Mamba models continues to pose challenges for traini

Maria Chudnovsky, Sepehr Hajebi, Sophie Spirkl

Two sets $X, Y$ of vertices in a graph $G$ are "anticomplete" if $X\cap Y=\varnothing$ and there is no edge in $G$ with an end in $X$ and an end in $Y$. We prove that every graph $G$ of sufficiently large treewidth contains two anticomplete sets of vertices each inducing a subgraph of large treewidth unless $G$ contains, as an induced subgraph, a highly stru

Gabriel Fernandes

We prove new instances of Halin's end degree conjecture (HC) in ZFC. In particular, we show that there is a proper class of cardinals kappa for which Halin's conjecture holds, answering two questions posed by Geschke, Kurkofka, Melcher, and Pitz (2023). We also investigate the relationship between HC and the Singular Cardinal Hypothesis, deriving consistency

Kyle Akira Rocha, Rachel Hur, Vicky Kalogera, Seth Gossage

We investigate Roche lobe overflow mass transfer (MT) in eccentric binary systems between stars and compact objects (COs), modeling the coupled evolution of both the star and the orbit due to eccentric MT (eMT) in a self-consistent framework. We implement the analytic expressions for secular rates of change of the orbital semi-major axis and eccentricity, as

Xinhai Li, Jialin Li, Ziheng Zhang, Rui Zhang

Efficient acquisition of real-world embodied data has been increasingly critical. However, large-scale demonstrations captured by remote operation tend to take extremely high costs and fail to scale up the data size in an efficient manner. Sampling the episodes under a simulated environment is a promising way for large-scale collection while existing simulat

Elie Azeraf

The Pairwise Markov Chain (PMC) is a probabilistic graphical model extending the well-known Hidden Markov Model. This model, although highly effective for many tasks, has been scarcely utilized for continuous value prediction. This is mainly due to the issue of modeling observations inherent in generative probabilistic models. In this paper, we introduce a n

T. M. Stanton, F. Cullen, A. C. Carnall, D. Scholte

We present an analysis of eight star-forming galaxies with $\langle z \rangle = 4.0$ from the JWST EXCELS survey for which we obtain robust chemical abundance estimates for the $\alpha$-elements O, Ne and Ar. The $\alpha$-elements are primarily produced via core-collapse supernovae (CCSNe) which should result in $\alpha$-element abundance ratios that do not

Ziqiang Feng

We consider the class of partially hyperbolic diffeomorphisms on a closed 3-manifold with quasi-isometric center. Under the non-wandering condition, we prove that the diffeomorphisms are accessible if there is no $su$-torus. As a consequence, volume-preserving diffeomorphisms in this context are ergodic in the absence of $su$-tori, thereby confirming the Her

Maryam Cheema, Hasti Seifi, Pooyan Fazli

Audio descriptions (AD) make videos accessible for blind and low vision (BLV) users by describing visual elements that cannot be understood from the main audio track. AD created by professionals or novice describers is time-consuming and offers little customization or control to BLV viewers on description length and content and when they receive it. To addre

Guanming Zhang, Stefano Martiniani

Stochastic gradient descent (SGD) is a fundamental tool for training deep neural networks across a variety of tasks. In self-supervised learning, different input categories map to distinct manifolds in the embedded neural state space. Accurate classification is achieved by separating these manifolds during learning, akin to a packing problem. We investigate

William Shen, Caelan Garrett, Nishanth Kumar, Ankit Goyal

Planning long-horizon robot manipulation requires making discrete decisions about which objects to interact with and continuous decisions about how to interact with them. A robot planner must select grasps, placements, and motions that are feasible and safe. This class of problems falls under Task and Motion Planning (TAMP) and poses significant computationa

Gabrielle Adams, Katharina Lodders

From transmission electron microscopy and other laboratory studies of presolar grains, the implicit condensation sequence of carbon-bearing condensates in circumstellar envelopes of carbon stars is (from first to last) TiC-graphite-SiC. We use thermochemical equilibrium condensation calculations and show that the condensation sequence of TiC, graphite, and S

Matthew R. Mumpower, Tsung-Shung H. Lee, Nicole Lloyd-Ronning, Brandon L. Barker

We propose that neutrons may be generated in high-energy, high-flux photon environments via photo-induced reactions on pre-existing baryons. These photohadronic interactions are expected to occur in astrophysical jets and surrounding material. Historically, these reactions have been attributed to the production of high-energy cosmic rays and neutrinos. We es

Sara Ortega-Martinez, Sergio Contreras, Raul E. Angulo, Jonas Chaves-Montero

The Dark Energy Spectroscopic Instrument (DESI) survey is mapping the large-scale distribution of millions of Emission Line Galaxies (ELGs) over vast cosmic volumes to measure the growth history of the Universe. However, compared to Luminous Red Galaxies (LRGs), very little is known about the connection of ELGs with the underlying matter field. In this paper

Marek Wydmuch, Łukasz Borchmann, Filip Graliński

Though large language models (LLMs) have demonstrated exceptional performance across numerous problems, their application to predictive tasks in relational databases remains largely unexplored. In this work, we address the notion that LLMs cannot yield satisfactory results on relational databases due to their interconnected tables, complex relationships, and

Conrad Kosowsky

I model a rational agent who experiences endogenous deadline pressure in the face of a fixed future deadline. The agent holds a resource stock, and opportunities to spend resources arise randomly according to a Poisson process. When the deadline is far away, the agent smooths consumption, but as the deadline approaches, the agent prioritizes current spending

Arnab Seth, Joseph C. Prestigiacomo, Aini Xu, Zhenyuan Zeng

The search for new quantum spin liquid materials relies on systems with strong frustration such as spins on an ideal kagome lattice. However, lattice imperfections can have substantial effects which are as yet not well understood. In recent work, the two-dimensional kagome system YCu$_3$(OH)$_6$[(Cl$_x$Br$_{(1-x)}$)$_{3-y}$(OH)$_y$] has emerged as a leading

Günel Jabbarlı, Murat Kurt

Accurate and fast recognition of forgeries is an issue of great importance in the fields of artificial intelligence, image processing and object detection. Recognition of forgeries of facial imagery is the process of classifying and defining the faces in it by analyzing real-world facial images. This process is usually accomplished by extracting features fro

Sean J. Gunderson, David P. Huenemoerder, José M. Torrejón, Dustin K. Swarm

We investigated the temporal and spectral features of $\gamma$ Cassiopeiae's X-ray emission within the context of the white dwarf accretion hypothesis. We find that the variabilities present in the X-ray data show two different signals, one primarily due to absorption and the other due to flickering like in non-magnetic cataclysmic variables. We then use thi

Michael Griebel, Guanglian Li, Christian Rieger

In many applications, random fields reflect uncertain parameters, and often their moments are part of the modeling process and thus well known. However, there are practical situations where this is simply not the case. Therefore, we do not assume that we know moments or expansion terms of the random fields, but only have discretized samples of them. The main

Anastasios N. Angelopoulos, Rina Foygel Barber, Stephen Bates

This book is about conformal prediction and related inferential techniques that build on permutation tests and exchangeability. These techniques are useful in a diverse array of tasks, including hypothesis testing and providing uncertainty quantification guarantees for machine learning systems. Much of the current interest in conformal prediction is due to i

Thomas Speck

Inhomogeneous flows and shear banding are of interest for a range of applications but have been eluding a comprehensive theoretical understanding, mostly due to the lack of a framework comparable to equilibrium statistical mechanics. Here we revisit models of fluids that reach a stationary state obeying mechanical equilibrium. Starting from a non-local const

Ben W. Reichardt, Adam Paetznick, David Aasen, Ivan Basov

Quantum computing experiments are transitioning from running on physical qubits to using encoded, logical qubits. Fault-tolerant computation can identify and correct errors, and has the potential to enable the dramatically reduced logical error rates required for valuable algorithms. However, it requires flexible control of high-fidelity operations performed

Guillaume Jeanmairet, Maxime Labat, Emmanuel Giner

Combining classical density functional theory (cDFT) with quantum mechanics (QM) methods offers a computationally efficient alternative to traditional QM/molecular mechanics (MM) approaches for modeling mixed quantum-classical systems at finite temperatures. However, both QM/MM and QM/cDFT rely on somewhat ambiguous approximations, the two major ones being:

CMS Collaboration

A full set of optimized observables is measured in an angular analysis of the decay B$^0$ $\to$ K$^*$(892)$^0\mu^+\mu^-$ using a sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV, collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 140 fb$^{-1}$. The analysis is performed in six bins of the squared invariant mass

Axel Elaldi, Guido Gerig, Neel Dey

Each voxel in a diffusion MRI (dMRI) image contains a spherical signal corresponding to the direction and strength of water diffusion in the brain. This paper advances the analysis of such spatio-spherical data by developing convolutional network layers that are equivariant to the $\mathbf{E(3) \times SO(3)}$ group and account for the physical symmetries of

Xu Cao, Kaizhao Liang, Kuei-Da Liao, Tianren Gao

Modeling disease progression is crucial for improving the quality and efficacy of clinical diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image monitoring for individual patients. To address this challenge, we propose the first Medical Video Generation (MVG) framework that enables controlled manipulation of disease-relate

Junming Diao

This paper introduces an innovative approach to radio astronomy by utilizing the global network of Internet of Things (IoT) devices to form a distributed radio telescope. Leveraging existing IoT infrastructure with minimal modifications, the proposed system employs widely dispersed devices to simultaneously capture both astronomical and communication signals

Joshua Cheung, Kun-Chieh Chien, Peter Sokalski, Li Shi

Sapphire is an attractive material in photonic, optoelectronic, and transparent ceramic applications that stand to benefit from surface functionalization effects stemming from micro/nanostructures. Here we investigate the use of ultrafast lasers for fabricating nanostructures in sapphire by exploring the relationship between irradiation parameters, morpholog

Federico Bambozzi, Matteo Capoferri, Simone Murro

The goal of this paper is to define a notion of non-commutative Gelfand duality. Using techniques from derived algebraic geometry, we show that the category of rings is anti-equivalent to a subcategory of pre-ringed sites, inspired by Grothendieck's work on commutative rings. Our notion of spectrum, although formally reminiscent of the Grothendieck spectrum,

John H. Elton, John R. Elton

Differential equations are derived which show how generalized Euler vector representations of the Euler rotation axis and angle for a rigid body evolve in time; the Euler vector is also known as a rotation vector or axis-angle vector. The solutions can exhibit interesting rotational features in this non-abstract, visualizable setting, including spinor-like b

Beverly Xu, Nan Wang, Ricardo Sanfelice

This paper presents two implementations of the recently developed motion planning algorithms HyRRT arXiv:2210.1508(2) and HySST arXiv:2305.1864(9). Specifically, cHyRRT, an implementation of the HyRRT algorithm, generates solutions to motion planning problems for hybrid systems with a probabilistic completeness guarantee, while cHySST, an implementation of t

Sangita Mondal, Ved Mahajan, Biman Bagchi

Dimerization and subsequent aggregation of polymers and biopolymers often occur under nonequilibrium conditions. When the initial state of the polymer is not collapsed or the final folded native state, the dynamics of dimerization can follow a course sensitive to both the initial conditions and the conformational dynamics. Here we study the dimerization proc

Valentin Maestracci, Paolo Pistone

In this paper we introduce several quantitative methods for the lambda-calculus based on partial metrics, a well-studied variant of standard metric spaces that have been used to metrize non-Hausdorff topologies, like those arising from Scott domains. First, we study quantitative variants, based on program distances, of sensible equational theories for the $\

Chen-Yu Yang, M. Israr Aslam, Xiao-Xiong Zeng, Rabia Saleem

This study investigates the astronomical implications of the Ghosh-Kumar rotating Black Hole (BH), particularly its behaviour on shadow images, illuminated by celestial light sources and equatorial thin accretion disks. Our research delineates a crucial correlation between dynamics of the shadow images and the parameters $a$,~ $q$ and the $\theta_{obs}$, whi

Jorge Fariña-Asategui

We introduce the concept of cyclicity and hypercyclicity in self-similar groups as an analogue of cyclic and hypercyclic vectors for an operator on a Banach space. We derive a sufficient condition for cyclicity of non-finitary automorphisms in contracting discrete automata groups. In the profinite setting we prove that fractal profinite groups may be regarde

Dmitriy Kunisky, Daniel A. Spielman, Alexander S. Wein, Xifan Yu

We study the problem of detecting or recovering a planted ranked subgraph from a directed graph, an analog for directed graphs of the well-studied planted dense subgraph model. We suppose that, among a set of $n$ items, there is a subset $S$ of $k$ items having a latent ranking in the form of a permutation $\pi$ of $S$, and that we observe a fraction $p$ of

Vojtěch Havlíček, Chinmay Nirkhe

The states accepted by a quantum circuit are known as the witnesses for the quantum circuit's satisfiability. The assumption BQP does not equal QMA implies that no efficient algorithm exists for constructing a witness for a quantum circuit from the circuit's classical description. However, a similar complexity-theoretic lower bound on the computational hardn

J. R. Distel, E. C. Dunton, J. M. Durham, A. C. Hayes

There is a growing realization that neutrinos can be used as a diagnostic tool to better understand the inner workings of a nuclear weapon. Robust estimates demonstrate that an Inverse Beta Decay (IBD) neutrino scintillation detector built at the Nevada Test Site of 1000-ton active target mass at a standoff distance of 500 m would detect thousands of neutrin

Frederik Baymler Mathiesen, Sofie Haesaert, Luca Laurenti

This paper introduces a novel abstraction-based framework for controller synthesis of nonlinear discrete-time stochastic systems. The focus is on probabilistic reach-avoid specifications. The framework is based on abstracting a stochastic system into a new class of robust Markov models, called orthogonally decoupled Interval Markov Decision Processes (odIMDP

Elena R. Alonso, Aran Insausti, Lucie Kolesniková, Iker León

This work aims to spectroscopically characterize and provide for the first time direct experimental frequencies of the ground vibrational state and two excited states of the simplest alkynyl thiocyanate (HCCSCN) for astrophysical use. Both microwave (8-16~GHz) and millimeter wave regions (50-120~GHz) of the spectrum have been measured and analyzed in terms o

Ashish Pal, Satish Nagarajaiah

Machine learning for scientific discovery is increasingly becoming popular because of its ability to extract and recognize the nonlinear characteristics from the data. The black-box nature of deep learning methods poses difficulties in interpreting the identified model. There is a dire need to interpret the machine learning models to develop a physical under

Nikita Karpenko, Guangzhao Zhu

We introduce and study on examples a notion of the Artin shape for a motive related to a projective homogenous variety. We apply it to the problem of finding the complete motivic decomposition of the variety. Our examples cover unitary involution varieties as well as some varieties given by a quadratic Weil transfer. Some of the decompositions obtained dispe

Meng Zhou, Yuxuan Zhang, Xiaolan Xu, Jiayi Wang

Multimodal medical image fusion is a crucial task that combines complementary information from different imaging modalities into a unified representation, thereby enhancing diagnostic accuracy and treatment planning. While deep learning methods, particularly Convolutional Neural Networks (CNNs) and Transformers, have significantly advanced fusion performance

Sharp C. Y. Lo, Alberto Zingaro, Jon W. S. McCullough, Xiao Xue

The circulatory system, comprising the heart and blood vessels, is vital for nutrient transport, waste removal, and homeostasis. Traditional computational models often treat cardiac electromechanics and blood flow dynamics separately, overlooking the integrated nature of the system. This paper presents an innovative approach that couples a 3D electromechanic

Andrew W. Appel, Philip B. Stark

The recently published "MERGE" protocol is designed to be used in the prototype CAC-vote system. The voting kiosk and protocol transmit votes over the internet and then transmit voter-verifiable paper ballots through the mail. In the MERGE protocol, the votes transmitted over the internet are used to tabulate the results and determine the winners, but audits

Egor Kovalev, Georgii Bychkov, Khaled Abud, Aleksandr Gushchin

Adversarial robustness of neural networks is an increasingly important area of research, combining studies on computer vision models, large language models (LLMs), and others. With the release of JPEG AI - the first standard for end-to-end neural image compression (NIC) methods - the question of its robustness has become critically significant. JPEG AI is am

Satush Parikh, Soumya Basu, Avishek Ghosh, Abishek Sankararaman

Sequential learning in a multi-agent resource constrained matching market has received significant interest in the past few years. We study decentralized learning in two-sided matching markets where the demand side (aka players or agents) competes for the supply side (aka arms) with potentially time-varying preferences to obtain a stable match. Motivated by

Adrian del Rio

It is known that an electric-magnetic duality transformation is a symmetry of the classical source-free Maxwell theory in generic spacetimes. This provides a conserved Noether charge, physically related to the polarization state of the electromagnetic field. We argue that this conservation law fails to hold at the quantum level in presence of a background cl

Richard Asiamah, Yuqi Zhou, Ahmed S. Zamzam

High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load delivery, reduced losses, and the operation between voltage limits. However, computations to decide the optim

Hanan Dery, Cedric Robert, Scott A. Crooker, Xavier Marie

Tuning the density of resident electrons or holes in semiconductors provides crucial insight into the composition of excitonic complexes that are observed as absorption or photoluminescence resonances in optical studies. Moreover, we can change the way these resonances shift and broaden in energy by controlling the quantum numbers of the resident carriers wi

Maryam Bahrani, Naveen Durvasula

Blockchain networks are facing increasingly heterogeneous computational demands, and in response, protocol designers have started building specialized infrastructure to supply that demand. This paper introduces Resonance: a new kind of transaction fee mechanism for the general two-sided market setting (with users on one side and nodes on the other), where bo

Kaushik Venkatesh Krishnamurthy, Eric Sihite, Chenghao Wang, Shreyansh Pitroda

Wing-assisted inclined running (WAIR) observed in some young birds, is an attractive maneuver that can be extended to legged aerial systems. This study proposes a control method using a modified Variable Length Inverted Pendulum (VLIP) by assuming a fixed zero moment point and thruster forces collocated at the center of mass of the pendulum. A QP MPC is used

Marius Beceanu, Hyun-Kyoung Kwon

In this paper we prove that Schr\"{o}dinger's equation with a Hamiltonian of the form $H=-\Delta+i(A \nabla + \nabla A) + V$, which includes a magnetic potential $A$, has the same dispersive and solution decay properties as the free Schr\"{o}dinger equation. In particular, we prove $L^1 \to L^\infty$ decay and some related estimates for the wave equation. Th

Jinwon Sohn, Qifan Song

A generative adversarial network (GAN) has been a representative backbone model in generative artificial intelligence (AI) because of its powerful performance in capturing intricate data-generating processes. However, the GAN training is well-known for its notorious training instability, usually characterized by the occurrence of mode collapse. Through the l

Debsoumya Chakraborti, Oliver Janzer, Abhishek Methuku, Richard Montgomery

In 1975, Erd\H{o}s and Sauer asked to estimate, for any constant $r$, the maximum number of edges an $n$-vertex graph can have without containing an $r$-regular subgraph. In a recent breakthrough, Janzer and Sudakov proved that any $n$-vertex graph with no $r$-regular subgraph has at most $C_r n \log \log n$ edges, matching an earlier lower bound by Pyber, R

Wan-Hsuan Lin, Daniel Bochen Tan, Jason Cong

Quantum computing architectures based on neutral atoms offer large scales and high-fidelity operations. They can be heterogeneous, with different zones for storage, entangling operations, and readout. Zoned architectures improve computation fidelity by shielding idling qubits in storage from side-effect noise, unlike monolithic architectures where all operat

Jehad Abed, Jiheon Kim, Muhammed Shuaibi, Brook Wander

The search for low-cost, durable, and effective catalysts is essential for green hydrogen production and carbon dioxide upcycling to help in the mitigation of climate change. Discovery of new catalysts is currently limited by the gap between what AI-accelerated computational models predict and what experimental studies produce. To make progress, large and di

João Barata, Zhong-Bo Kang, Xoán Mayo López, Jani Penttala

In this Letter, we study the collinear limit of the Energy-Energy Correlator (EEC) in single-inclusive jet production in proton-proton ($pp$) and proton-nucleus ($pA$) collisions. We introduce a non-perturbative model that allows us to describe the EEC in the entire angular region of the current experiments. Our results for $pp$ collisions show excellent agr

Quinten De Man, Laxman Dhulipala, Adam Karczmarz, Jakub Łącki

We study the problem of dynamically maintaining the connected components of an undirected graph subject to edge insertions and deletions. We give the first parallel algorithm for the problem which is work-efficient, supports batches of updates, runs in polylogarithmic depth, and uses only linear total space. The existing algorithms for the problem either use

Yong-Hoon Kim, Ryong-Gyu Lee

The continued miniaturization of semiconductor devices, represented by Moore's law, has reached the atomic scale limit, requiring nanoscale quantum mechanical effects to be included in device simulations without empirical parameters. For this purpose, a method that combines density functional theory (DFT) and non-equilibrium Green's function (NEGF) theory ha

Enshuo Hsu, Kirk Roberts

Objectives: Despite the recent adoption of large language models (LLMs) for biomedical information extraction, challenges in prompt engineering and algorithms persist, with no dedicated software available. To address this, we developed LLM-IE: a Python package for building complete information extraction pipelines. Our key innovation is an interactive LLM ag

Antonio López Rivera, Lucrezia Marcovaldi, Jesús Ramírez, Alex Cuenca

Optimizing space vehicle routing is crucial for critical applications such as on-orbit servicing, constellation deployment, and space debris de-orbiting. Multi-target Rendezvous presents a significant challenge in this domain. This problem involves determining the optimal sequence in which to visit a set of targets, and the corresponding optimal trajectories

Chunchu Zhu, Xunjie Chen, Jingang Yi

Human walkers traverse diverse environments and demonstrate different gait locomotion and energy cost on granular terrains compared to solid ground. We present a stiffness-based model predictive control approach of knee exoskeleton assistance on sand. The gait and locomotion comparison is first discussed for human walkers on sand and solid ground. A machine

James Cranch, Daniel Graves

Coloured partition algebras were introduced by Bloss and exhibit a Schur-Weyl duality with certain complex reflection groups. In this paper we show that these algebras exhibit homological stability by demonstrating that their homology groups are stably isomorphic to the homology groups of a wreath product, generalizing work of Boyd--Hepworth--Patzt and Boyde

Emma Radice, Marco Salvalaglio, Roberto Bergamaschini

We present a phase-field model for simulating the solid-state dewetting of anisotropic crystalline films on non-planar substrates. This model exploits two order parameters to trace implicitly the crystal free surface and the substrate profile in both two and three dimensions. First, we validate the model by comparing numerical simulation results for planar s

Jeffrey N. Clark, Matthew Wragg, Emily Nielsen, Miquel Perello-Nieto

There is a growing need to understand how digital systems can support clinical decision-making, particularly as artificial intelligence (AI) models become increasingly complex and less human-interpretable. This complexity raises concerns about trustworthiness, impacting safe and effective adoption of such technologies. Improved understanding of decision-maki

Michael C. Ogilvie, Moses A. Schindler, Stella T. Schindler

Lattice $\mathbb{Z}_3$ theories with complex actions share many key features with finite-density QCD including a sign problem and $CK$ symmetry. Complex $\mathbb{Z}_3$ spin and gauge models exhibit a generalized Kramers-Wannier duality mapping them onto chiral $\mathbb{Z}_3$ spin and gauge models, which are simulatable with standard lattice methods in large

Álvaro Fernández-Mora, Alex Haro, Josep-Maria Mondelo

In this work, we obtain an a-posteriori theorem for the existence of partly hyperbolic invariant tori in analytic Hamiltonian systems: autonomous, periodic, and quasi-periodic. The method of proof is based on the convergence of a KAM iterative scheme to solve the invariance equations of tori and their invariant bundles under the framework of the parameteriza

Yilin Ma

This paper studies quantum three-body scattering within a modern microlocal framework. We show that the three-body Helmholtz operator at positive energy gives rise to a pair of Fredholm maps between suitable anisotropic Hilbert spaces. Notably, we consider decay at various faces of spatial infinity separately, made precise via a compactification. Despite the

Zishuo Feng, Feng Cao

The task of converting Hanyu Pinyin abbreviations to Chinese characters is a significant branch within the domain of Chinese Spelling Correction (CSC). It plays an important role in many downstream applications such as named entity recognition and sentiment analysis. This task typically involves text-length alignment and seems easy to solve; however, due to

José R. C. Andrade, Martin Kretschmar, Rostyslav Danylo, Stefanos Carlström

In the last few decades the development of ultrafast lasers has revolutionized our ability to gain insight into light-matter interactions. The appearance of few-cycle light sources available from the visible to the mid-infrared spectral range and the development of attosecond extreme ultraviolet and x-ray technologies provide for the first time the possibili

Nicholas Chow, Bo Fu

This paper showcases AdaptLIL, a real-time adaptive link-indented list ontology mapping visualization that uses eye gaze as the primary input source. Through a multimodal combination of real-time systems, deep learning, and web development applications, this system uniquely curtails graphical overlays (adaptations) to pairwise mappings of link-indented list

Mathew Jacob, Erik Lindgren, Matei Zaharia, Michael Carbin

Rerankers, typically cross-encoders, are computationally intensive but are frequently used because they are widely assumed to outperform cheaper initial IR systems. We challenge this assumption by measuring reranker performance for full retrieval, not just re-scoring first-stage retrieval. To provide a more robust evaluation, we prioritize strong first-stage

Marc Aiguier, Romain Pascual

Los's theorem, also known as the fundamental result of ultraproducts, states that the ultraproduct over a family of structures for the same language satisfies a first-order formula if and only if the set of indices for which the structures satisfy the formula belongs to the underlying ultrafilter. The associated notion of satisfaction is the Tarskian one

R. Rácz, S. T. S. Kovács, G. Lakatos, K. K. Rahul

The detection of various molecular species, including complex organic molecules relevant to biochemical and geochemical processes, in astronomical settings such as the interstellar medium or the outer Solar System has led to the increased need for a better understanding of the chemistry occurring in these cold regions of space. In this context, the chemistry

Shovito Barua Soumma, S M Raihanul Alam, Rudmila Rahman, Umme Niraj Mahi

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease that impairs mobility and safety by increasing the risk of falls. An effective FOG detection system must be accurate, real-time, and deployable in free-living environments to enable timely interventions. However, existing detection methods face challenges due to (1) intra- and inter-pati

Lorenzo Traldi

Motivated by knot theory, it is natural to define the orientation-reversal of a quandle orbit by inverting all the translations given by elements of that orbit. In this short note we observe that this natural notion is unsuited to medial quandles.

Shiyue Zhao, Junzhi Zhang, Neda Masoud, Yuhong Jiang

Executing drift maneuvers during high-speed cornering presents significant challenges for autonomous vehicles, yet offers the potential to minimize turning time and enhance driving dynamics. While reinforcement learning (RL) has shown promising results in simulated environments, discrepancies between simulations and real-world conditions have limited its pra

Yannick Metz, David Lindner, Raphaël Baur, Mennatallah El-Assady

Reinforcement Learning from Human feedback (RLHF) has become a powerful tool to fine-tune or train agentic machine learning models. Similar to how humans interact in social contexts, we can use many types of feedback to communicate our preferences, intentions, and knowledge to an RL agent. However, applications of human feedback in RL are often limited in sc

Alan Sherry, Cedric Bernardin, Abhishek Dhar, Aritra Kundu

We consider the dynamics of a continuously monitored qubit in the limit of strong measurement rate where the quantum trajectory is described by a stochastic master equation with Poisson noise. Such limits are expected to give rise to quantum jumps between the pointer states associated with the non-demolition measurement. A surprising discovery in earlier wor

Sani Biswas, Chaman Kumar, Christoph Reisinger, Verena Schwarz

In this work, we present a general Milstein-type scheme for McKean-Vlasov stochastic differential equations (SDEs) driven by Brownian motion and Poisson random measure and the associated system of interacting particles where drift, diffusion and jump coefficients may grow super-linearly in the state variable and linearly in the measure component. The strong

Longju Bai, Angana Borah, Oana Ignat, Rada Mihalcea

Large Multimodal Models (LMMs) exhibit impressive performance across various multimodal tasks. However, their effectiveness in cross-cultural contexts remains limited due to the predominantly Western-centric nature of most data and models. Conversely, multi-agent models have shown significant capability in solving complex tasks. Our study evaluates the colle

Ruizhi Liu, Weicheng Ye

Although it is long believed that vanishing of chiral central charges of a 2d conformal field theory (CFT) implies the existence of conformal boundary conditions, there are yet higher obstructions. In this paper, we focus on 2d rational CFTs, for which we identify a series of obstructions, known as higher central charges. We also discuss its implication for

Gabriel P. L. M. Fernandes, Matheus S. Fonseca, Amanda G. Valério, Alexandre C. Ricardo

Warehouses play a central role in industrial logistics, functioning as critical hubs for storing and organizing inventory to support efficient production. Optimizing item allocation within these facilities is essential for reducing operational costs and improving delivery times. In this work, we address the optimization of inventory allocation in warehouses

Eduardo Peixoto, Pedro Garcia Freitas, Mylene Christine Queiroz Farias, Edil Medeiros

In 2023 we have conducted extensive experiments on subjective video quality for the TV 3.0 project at University of Bras\'ilia. A full report on these tests is available at the F\'orum SBTVD website . These tests have evaluated the H.266/VVC codec and a hybrid codec formed by the H.266/VVC and the LCEVC (Low Complexity Enhancement Video Coding) with differen

Simon Garrigou, Hugo Lourenço-Martins

Phase-shaped electron energy-loss spectroscopy (PSEELS) measures the scattering probability of structured free electron beams by a target. Over the last decade, it was shown that this scheme can be employed to emulate polarized optical spectroscopies with electrons, and therefore to transpose macroscopic optical concepts - such as dichroism - down to the dee

Xu-Guang Huang

Spin polarization and spin transport are common phenomena in many quantum systems. Relativistic spin hydrodynamics provides an effective low-energy framework to describe these processes in quantum many-body systems. The fundamental symmetry underlying relativistic spin hydrodynamics is angular momentum conservation, which naturally leads to inter-conversion

Yunhao Xing, Que Liu, Jingwu Wang, Diego Gomez-Zara

In mixed reality (MR) environments, understanding space and creating virtual objects is crucial to providing an intuitive and rich user experience. This paper introduces sMoRe (Spatial Mapping and Object Rendering Environment), an MR application that combines Generative AI (GenAI) with large language models (LLMs) to assist users in creating, placing, and ma

Eliahu Friedman, Avraham Gal

This work is a sequel to our two 2023 publications [PLB 837 137669, NPA 1039 122725] where fitting 14 1$s_\Lambda$ and 1$p_\Lambda$ single-particle binding energies in hypernuclei across the periodic table led to a well-defined $\Lambda$-nucleus optical potential. The potential consists of a Pauli modified linear-density ($\Lambda N$) and a quadratic-density

Sauvik Roy, Nirmalya Ghosh, Ayan Banerjee, Subhasish Dutta Gupta

Coherent perfect absorption (CPA) has been a topic of considerable contemporary research interest. Most of the theoretical treatment of CPA with beams, to the best of our knowledge, relies on a scalar (in some cases coupled mode) theories with inadequate input about the polarization states of the incoming light. In view of the lack of a full vectorial theory

Valentina De Romeri, Dimitrios K. Papoulias, Christoph A. Ternes

Recently, two dark matter direct detection experiments have announced the first indications of nuclear recoils from solar $^8$B neutrinos via coherent elastic neutrino-nucleus scattering (CE$\nu$NS) with xenon nuclei. These results constitute a turning point, not only for dark matter searches that are now entering the \textit{neutrino fog}, but they also bri

Masahiro Kato

This study introduces a debiasing method for regression estimators, including high-dimensional and nonparametric regression estimators. For example, nonparametric regression methods allow for the estimation of regression functions in a data-driven manner with minimal assumptions; however, these methods typically fail to achieve $\sqrt{n}$-consistency in thei

Andrew Starnes, Guannan Zhang, Viktor Reshniak, Clayton Webster

This article introduces a novel family of optimization algorithms - Anisotropic Gaussian Smoothing Gradient Descent (AGS-GD), AGS-Stochastic Gradient Descent (AGS-SGD), and AGS-Adam - that employ anisotropic Gaussian smoothing to enhance traditional gradient-based methods, including GD, SGD, and Adam. The primary goal of these approaches is to address the ch