November 2024 arXiv papers — page 20

Mayank Pathak, Banibrata Mukhopadhyay

Ultraluminous X-ray sources (ULXs) have been objects of great interest for the past few decades due to their unusually high luminosities and spectral properties. A few of these sources exhibit super-Eddington luminosities assuming them to be centering around stellar mass objects, even in their hard state. It has been shown via numerical steady state calculat

Julia E. Bergner

We give an introduction to the theory of 2-Segal sets, and two of the main applications of them: Hall algebras and a discrete version of Waldhausen's $S_\bullet$-construction. We present several combinatorial examples and how these constructions can be applied to them.

Y. Alexanian, A. de la Torre, S. McKweon Walker, M. Straub

The fate of the Fermi surface in bulk electron-doped Sr$_{2}$IrO$_{4}$ remains elusive, as does the origin and extension of its pseudogap phase. Here, we use high-resolution angle-resolved photoelectron spectroscopy (ARPES) to investigate the electronic structure of Sr$_{2-x}$La$_{x}$IrO$_{4}$ up to $x=0.2$, a factor of two higher than in previous work. We f

Piero Mazzarisi, Alessio Muscillo, Claudio Pacati, Paolo Pin

In the dynamic landscape of contemporary society, the popularity of ideas, opinions, and interests fluctuates rapidly. Traditional dynamical models in social sciences often fail to capture this inherent volatility, attributing changes to exogenous shocks rather than intrinsic features of the system. This paper introduces a novel, tractable model that simulat

A. Howell, M. Songvilay, J. A. Rodriguez-Rivera, Ch. Niedermayer

By tuning superconductivity with an applied magnetic field, we use neutrons to compare the magnetic ordered phases in superconducting and normal states of CeCo$_{0.5}$Rh$_{0.5}$In$_{5}$. At zero field, CeCo$_{0.5}$Rh$_{0.5}$In$_{5}$ displays both superconductivity ($T_{c}$=1.3 K) and spatially long-ranged commensurate $\uparrow\downarrow\uparrow\downarrow$ a

Jinyuan Qu, Hongyang Li, Shilong Liu, Tianhe Ren

In this paper, built upon TAPTRv2, we present TAPTRv3. TAPTRv2 is a simple yet effective DETR-like point tracking framework that works fine in regular videos but tends to fail in long videos. TAPTRv3 improves TAPTRv2 by addressing its shortcomings in querying high-quality features from long videos, where the target tracking points normally undergo increasing

Dillon Loh, Tomasz Bednarz, Xinxing Xia, Frank Guan

Visual Language Navigation is a task that challenges robots to navigate in realistic environments based on natural language instructions. While previous research has largely focused on static settings, real-world navigation must often contend with dynamic human obstacles. Hence, we propose an extension to the task, termed Adaptive Visual Language Navigation

Liang Guo, Qin Wang, Jianchao Wu, Guoliang Yu

The equivariant coarse Novikov conjectures stand among a handful profound $K$-theoretic conjectures in noncommutative geometry. Motivated by the quest to verify Novikov-type conjectures for groups of diffeomorphisms, we study in this paper the equivariant coarse Novikov conjectures for spaces that equivariantly and coarsely embed into admissible Hilbert-Hada

Nutth Tuchinda, Malik Wagih, Christopher A. Schuh

At very fine grain sizes, grain boundary segregation can deviate from conventional behavior due to triple junction effects. While this issue has been addressed in prior work for substitutional alloys, here we develop a framework that accounts for interstitial sites in the grains, grain boundaries, and triple junctions of model Pd(H) polycrystals. This approa

F. Henssler, K. Willa, M. Frachet, T. Lacmann

$\mathrm{Ba}\mathrm{Ni}_{2}\mathrm{As}_{2}$, a structural-analogue to the iron-based parent compound $\mathrm{Ba}\mathrm{Fe}_{2}\mathrm{As}_{2}$, offers a unique platform to study the interplay between superconductivity, charge density waves and, possibly, electronic nematicity. Here, we report on the growth and characterization of $\mathrm{Ba}_{1-x}\mathrm{

Thilo R. Müller, Manuel Geiger, Christian B. Mendl

Quantum computing holds immense promise for simulating quantum systems, a critical task for advancing our understanding of complex quantum phenomena. One of the primary goals in this domain is to accurately approximate the ground state of quantum systems. The Fermi-Hubbard model, particularly, is of profound interest due to its implications for high-temperat

Luca Sabatini

Let $G$ be a permutation group on the finite set $\Omega$. We prove various results about partitions of $\Omega$ whose stabilizers have good properties. In particular, in every solvable permutation group there is a set-stabilizer whose orbits have length at most $6$, which is best possible and answers two questions of Babai. Every solvable maximal subgroup o

Qiyu Wei, Xun Xu, Zeng Zeng, Xulei Yang

The patterns on wafer maps play a crucial role in helping engineers identify the causes of production issues during semiconductor manufacturing. In order to reduce costs and improve accuracy, automation technology is essential, and recent developments in deep learning have led to impressive results in wafer map pattern recognition. In this context, inspired

Boris Shakarov

We consider a nonlinear parabolic model that forces solutions to stay on a $L^2$-sphere through a nonlocal term in the equation. We study the local and global well-posedness on a bounded domain and the whole Euclidean space in the energy space. Then, we consider the solutions' asymptotic behavior. We prove strong convergence to a stationary state and asympto

Shuaiqi Wang, Zinan Lin, Giulia Fanti

We introduce a privacy measure called statistic maximal leakage that quantifies how much a privacy mechanism leaks about a specific secret, relative to the adversary's prior information about that secret. Statistic maximal leakage is an extension of the well-known maximal leakage. Unlike maximal leakage, which protects an arbitrary, unknown secret, statistic

Minhyeok Lee

This paper introduces a mathematical framework for defining and quantifying self-identity in artificial intelligence (AI) systems, addressing a critical gap in the theoretical foundations of artificial consciousness. While existing approaches to artificial self-awareness often rely on heuristic implementations or philosophical abstractions, we present a form

Paolo Facchi, Marilena Ligabò, Vito Viesti

We investigate quantum symmetries in terms of their large-time stability with respect to perturbations of the Hamiltonian. We find a complete algebraic characterization of the set of symmetries robust against a single perturbation and we use such result to characterize their stability with respect to arbitrary sets of perturbations.

Alessio Bottini

We provide a modular construction of the Laza--Sacc\`a--Voisin compactification of the intermediate Jacobian fibration of a cubic fourfold. Additionally, we construct infinitely many $20$-dimensional families of polarized hyper-K\"ahler manifolds of type OG10, realized as moduli spaces of stable bundles on hyper-K\"ahler manifolds of type $\mathrm{K3}^{[2]}$

Krzysztof Suchecki, Kathakali Biswas, Janusz A. Hołyst, Parongama Sen

We consider a kinetic model of opinion dynamics known as the Biswas-Chatterjee-Sen model with a modular interaction structure. The system consists of two groups of agents that feature more frequent interactions within each group and rarer interactions between agents of different groups. We use the mean-field analytical approximation to determine that aside f

Patrick Mineault, Niccolò Zanichelli, Joanne Zichen Peng, Anton Arkhipov

As AI systems become increasingly powerful, the need for safe AI has become more pressing. Humans are an attractive model for AI safety: as the only known agents capable of general intelligence, they perform robustly even under conditions that deviate significantly from prior experiences, explore the world safely, understand pragmatics, and can cooperate to

Alessio Rocci, Franklin J. Lambert

The meeting patronized by Ernest Solvay in 1911, the first Solvay Council, marked the beginning of what can be called the first quantum revolution. Maurice de Broglie was one of the secretaries of the Council. He participated in the two following conferences and contributed to the third Council with his work. Louis de Broglie collaborated and discussed with

Ziang Liu, Hongyu Li, Bruno Clerckx

Reconfigurable intelligent surface (RIS) has been envisioned as a key technology in future wireless communication networks to enable smart radio environment. To further enhance the passive beamforming capability of RIS, beyond diagonal (BD)-RIS has been proposed considering reconfigurable interconnections among different RIS elements. BD-RIS has a unique fea

Denis Barkats

The CMB polarization is the Everest in the quest to characterize the earliest photons from the Universe. After a long list of ever-decreasing upper limits, a detection of polarization was made in 2002 by the DASI team at ell =~ 500. The experiment described in this thesis is designed to make a more detailed measurements at higher angular resolution. The E-mo

Demir Arikan, Peiyao Zhang, Michael Sommersperger, Shervin Dehghani

Exudative (wet) age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, typically treated with intravitreal injections. Emerging therapies, such as subretinal injections of stem cells, gene therapy, small molecules and RPE cells require precise delivery to avoid damaging delicate retinal structures. Robotic systems can poten

Yichen Wang, Jie Wang, Fulin Wang, Xiang Li

In recent years, graph representation learning has undergone a paradigm shift, driven by the emergence and proliferation of graph neural networks (GNNs) and their heterogeneous counterparts. Heterogeneous GNNs have shown remarkable success in extracting low-dimensional embeddings from complex graphs that encompass diverse entity types and relationships. Whil

Prajit KrisshnaKumar, Steve Paul, Souma Chowdhury

Interesting and efficient collective behavior observed in multi-robot or swarm systems emerges from the individual behavior of the robots. The functional space of individual robot behaviors is in turn shaped or constrained by the robot's morphology or physical design. Thus the full potential of multi-robot systems can be realized by concurrently optimizing t

F. L. Pratt, D. Lopez-Alcala, V. Garcia-Lopez, M. Clemente-Leon

The metal-organic-framework (MOF) compound Cu$_3$(HOTP)$_2$, a.k.a. Cu$_3$(HHTP)$_2$, is a small-gap semiconductor containing a kagome lattice of antiferromagnetically coupled $S$=1/2 Cu$^\mathrm{II}$ spins with intra-layer nearest-neighbor exchange coupling $J \sim $ 2 K. The intra-layer $J$ value obtained from DFT+U calculations is shown to match with the

Xingjian Lyu, Kaifeng Bu

This work explores displaced fermionic Gaussian operators with nonzero linear terms. We first demonstrate equivalence between several characterizations of displaced Gaussian states. We also provide an efficient classical simulation protocol for displaced Gaussian circuits and demonstrate their computational equivalence to circuits composed of nearest-neighbo

Siddhant Gupta, Fred Lu, Andrew Barlow, Edward Raff

A strategy used by malicious actors is to "live off the land," where benign systems and tools already available on a victim's systems are used and repurposed for the malicious actor's intent. In this work, we ask if there is a way for anti-virus developers to similarly re-purpose existing work to improve their malware detection capability. We show that this

Hanno von Bergen, Reinhard Diestel

Using the recently developed mathematical theory of tangles, we re-assess the mathematical foundations for applications of the five factor model in personality tests by a new, mathematically rigorous, quantitative method. Our findings broadly confirm the validity of current tests, but also show that more detailed information can be extracted from existing da

Skandan Subramanian, Tom Berlijn, Lucas Lindsay, Randy S. Fishman

Motivated by the experimental identification of magnetic compounds consisting of zigzag chains, we analyze the band structure topology of magnons in ferromagnets on a zigzag lattice. We account for the general lattice geometry by including spatially anisotropic Heisenberg exchange interactions and by Dzyaloshinskii-Moriya interaction on inversion asymmetric

Mir Afrasiar, Jaydeep Kumar Basak, Dimitrios Giataganas

Timelike entanglement entropy is a complex measure of information that is holographically realized by an appropriate combination of spacelike and timelike extremal surfaces. This measure is highly sensitive to Lorentz invariance breaking. In this work, we study the timelike entanglement entropy in non-relativistic theories, focusing on theories with hypersca

Sourav Modak, Anthony Stein

Precise weed management is essential for sustaining crop productivity and ecological balance. Traditional herbicide applications face economic and environmental challenges, emphasizing the need for intelligent weed control systems powered by deep learning. These systems require vast amounts of high-quality training data. The reality of scarcity of well-annot

Vemund Falch, Arne Brataas, Alireza Qaiumzadeh

We investigate the second-order photon correlation function in cavity-magnon systems, focusing on ferromagnetic and antiferromagnetic cavities within the ultrastrong coupling regime, and extending beyond the rotating-wave approximation. By deriving exact integral solutions for the second-order correlation function, we demonstrate that counter-rotating magnon

Sofie Martins, Erik Kjellgren, Emiliano Molinaro, Claudio Pica

HiRep allows flexible simulations of higher representations of Wilson Fermions with various actions and gauge groups and a range of inverters and integrators. This is particularly important for enabling evaluations of observables relevant to phenomenological inputs for Beyond-the-Standard-Model physics from lattice field theory. We present progress on the GP

Lukas Peter Wagner, Lasse Matthias Reinpold, Maximilian Kilthau, Felix Gehlhoff

The increasing share of renewable energy sources and necessitate new concepts for energy flexible operation of industrial production resources. In this paper, we demonstrate the potential of mass storage to increase energy flexibility in industrial operations through the application of optimized operational planning based on market prices. A wastewater treat

Justin R. David, Srijan Kumar

We develop a method to evaluate the partition function and energy density of a massive scalar on a 2-sphere of radius $r$ and at finite temperature $\beta$ as power series in $\frac{\beta}{r}$. Each term in the power series can be written in terms of polylogarithms. We use this result to obtain the gap equation for the large $N$, critical $O(N)$ model with a

Yiwei Liu, Yihu Yang

Let $(\Omega^{n+1},g)$ be an $(n + 1)$-dimensional smooth complete connected Riemannian manifold with compact boundary $\partial\Omega=\Sigma$ and $f$ a smooth function on $\Omega$ which satisfies the Obata type equation $\nabla^2 f -fg =0$ with Robin boundary condition $f_{\nu} = cf$, where $c=\coth{\theta}>1$. In this paper, we provide some rigidity result

Anway S. Pimpalkar, Ariel Slepyan, Nitish V. Thakor

Stiffness estimation is crucial for delicate object manipulation in robotic and prosthetic hands but remains challenging due to dependence on force and displacement measurement and real-time sensory integration. This study presents a piezoelectric sensing framework for stiffness estimation at first contact during pinch grasps, addressing the limitations of t

Xinye Chen, Erin Carson, Cheng Kang

The success of large language models (LLMs) for time series has been demonstrated in previous work. Utilizing a symbolic time series representation, one can efficiently bridge the gap between LLMs and time series. However, the remaining challenge is to exploit the semantic information hidden in time series by using symbols or existing tokens of LLMs, while a

R. Dhanya, Jacques Giacomoni, Ritabrata Jana

In this article, we examine the H\"older regularity of solutions to equations involving a mixed local-nonlocal nonlinear nonhomogeneous operator $\fp + \fqs$ with singular data, under the minimal assumption that $p> sq$. The regularity result is twofold: we establish interior gradient H\"older regularity for locally bounded data and boundary regularity for s

Sonja Hohloch, Federico Zadra

These lecture notes grew out of notes for courses around Integrable PDEs and the KdV equation given by the authors during the past five years at the University of Antwerp (Belgium). Comments and suggestions are welcome.

Julius Beerwerth, Hazem Ibrahim, Bianca Atodiresei, Lorenz Dörschel

This paper presents a novel graph-based method for adapting control system architectures at runtime. We use a service-oriented architecture as a basis for its formulation. In our method, adaptation is achieved by selecting the most suitable elements, such as filters and controllers, for a control system architecture to improve control systems objective based

Mahmoud Baroun, Said Boulite, Abdellatif Elgrou, Omar Oukdach

In this paper, we continue the study of some controllability issues for the forward stochastic heat equation with dynamic boundary conditions. The main novelty in the present paper consists of considering only one control without extra forces in the noise parts. Under a strong measurability condition, and using a spectral inequality, we first establish an ap

Stéphanie Carlier, Femke De Backere, Filip De Turck

Serious games and gamification (SGG) have shown to have positive effects on health outcomes of eHealth applications. However, research has shown that a shift towards a personalized approach is needed, considering the diversity of users. This introduces new challenges to the domain of SGG as research is needed on how such personalization is achieved. A litera

Pengfei Zhou, Xiaopeng Peng, Jiajun Song, Chuanhao Li

Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a challenge, which requires integrated multimodal understanding and generation abilities. While the progress in unified models offers new solutions, existing benchmarks are insufficien

Nicolas Coucke, Mary Katherine Heinrich, Axel Cleeremans, Marco Dorigo

Collective decision making using simple social interactions has been studied in many types of multi-agent systems, including robot swarms and human social networks. However, existing multi-agent studies have rarely modeled the neural dynamics that underlie sensorimotor coordination in embodied biological agents. In this study, we investigated collective deci

David Perera, François Derrida, Théo Mariotte, Gaël Richard

Training speech separation models in the supervised setting raises a permutation problem: finding the best assignation between the model predictions and the ground truth separated signals. This inherently ambiguous task is customarily solved using Permutation Invariant Training (PIT). In this article, we instead consider using the Multiple Choice Learning (M

Jacob M. Leedom, Margherita Putti, Nicole Righi, Alexander Westphal

Certain inflationary models can feature periods of preheating - an era preceding reheating during which parametric resonance triggers an exponential production of bosons. This non-perturbative process can have significant impact on the history of our universe, with consequences ranging from altered reheating channels to overproduction of dark radiation to ov

G. Lusztig

Let W be a Weyl group and let w be a Coxeter elememt of minimal length of W. In the early 1970's I.G.Macdonald stated that the trace of w on an irreducible representation of W is 0,1 or -1. In this paper we give a proof of this statement and of an Iwahori-Hecke algebra version of it.

Alessandro Gnutti, Chia-Hao Kao, Wen-Hsiao Peng, Riccardo Leonardi

Linear block transform coding remains a fundamental component of image and video compression. Although the Discrete Cosine Transform (DCT) is widely employed in all current compression standards, its sub-optimality has sparked ongoing research into discovering more efficient alternative transforms even for fields where it represents a consolidated tool. In t

Juan Felipe Huan Lew-Yee, Jorge M. del Campo, Mario Piris

Natural orbital functional (NOF) theory offers a promising approach for studying strongly correlated systems at an affordable computational cost, with an accuracy comparable to highly demanding wavefunction-based methods. However, its widespread adoption in cases involving a large number of correlated electrons has been limited by the extensive iterations re

I. S. Rezvyakova

It is proved that the Epstein zeta-function corresponding to a binary positive definite quadratic form with integer coefficients has a positive proportion of its non-trivial zeros on the critical line.

Chenyang Lei, Liyi Chen, Jun Cen, Xiao Chen

Foundation models like ChatGPT and Sora that are trained on a huge scale of data have made a revolutionary social impact. However, it is extremely challenging for sensors in many different fields to collect similar scales of natural images to train strong foundation models. To this end, this work presents a simple and effective framework, SimCMF, to study an

Gabriele Fissore

We perform a mass constrained phase-field approximation for a model that describes the epitaxial growth of a two-dimensional thin film on a substrate in the context of linearised elasticity. The approximated model encodes a variable on the free surface of the film, that physically is interpreted as an adatom density.

Jannes Münchmeyer, Diego Molina, Mathilde Radiguet, David Marsan

Like earthquakes, slow slip events release elastic energy stored on faults. Yet, the mechanisms behind slow slip instability and its relationship with seismicity are debated. Here, we use a seismo-geodetic deployment to document a shallow slow slip event (SSE) in 2023 on the Chile subduction. We observe dense, migrating seismic swarms accompanying the SSE, c

Yongjoong Shin, Enrico Di Lucente, Nicola Marzari, Lorenzo Monacelli

The lower mantle of Earth, characterized by pressures of 24-127 GPa and temperatures of 1900-2600 K, is still inaccessible to direct observations. In this work, we investigate by first principles the stability, phase diagram, elastic properties, and thermal conductivity of CaSiO3, that constitutes a significant component of Earth's lower mantle. Notably, our

Rupam Karmakar, Rajib Sarkar

In this article, we investigate the existence of induced cycles in Levi graphs associated to line arrangements in $\mathbb{P}_{\mathbb{C}}^2$. We also look at the problem of finding the length of a longest induced cycle in Levi graphs associated to line arrangements.

Xinzhe Song, Guiying Yan, Qiang Zhou

The planar Tur\'an number of $H$, denoted by $ex_{\mathcal{P}}(n,H)$, is the maximum number of edges in an $n$-vertex $H$-free planar graph. The planar Tur\'an number of $k(k\geq 3)$ vertex-disjoint union of cycles is the trivial value $3n-6$. We determine the planar Tur\'an number of $C_{3}\text{-}C_{3}$ and $C_{3}\text{-}C_{4}$, where $C_{k}\text{-}C_{\ell

V. B. Jhansi, S. Thoudam, S. Buitink, A. Corstranje

{Measurements of cosmic-ray composition based on air-shower measurements rely mostly on the determination of the position of the shower maximum ($X_\mathrm{max}$). One efficient technique is to image the development of the air shower using fluorescence telescopes. An alternative technique that has made significant advances in the recent years is to measure t

Chen Xu, Qiang Wang, Lijun Sun

Accurate travel time estimation is essential for navigation and itinerary planning. While existing research employs probabilistic modeling to assess travel time uncertainty and account for correlations between multiple trips, modeling the temporal variability of multi-trip travel time distributions remains a significant challenge. Capturing the evolution of

Christian Hirsch, Martina Petráková

In this paper, we present a large-deviation theory developed for functionals of canonical Gibbs processes, i.e., Gibbs processes with respect to the binomial point process. We study the regime of a fixed intensity in a sequence of increasing windows. Our method relies on the traditional large-deviation result for local bounded functionals of Poisson point pr

Ginevra Lautizi, Vittorio Di Trapani, Alain Studer, Marie-Christine Zdora

We demonstrate a robust signal extraction method for X-ray speckle-based tensor tomography. We validate the effectiveness of the method for several carbon fiber composites, highlighting its potential for industrial applications. The proposed method can be adapted to various acquisition schemes and wavefront-marking optical elements, making it a versatile and

Aneel Bhusal, Todd D. Little

We introduce Bhirkuti's Test of Bias Acceptance (BTBA), a standardized framework for evaluating estimator bias in Monte Carlo simulation studies. BTBA uses a simulation-specific standardized score (Z*) and a decision matrix to assess bias acceptability based on the mean and variance of Z* distributions. Under ideal conditions, Z* values should approximate a

Xiaohua Zhou, Tianyu Fang, Yijie Mao

Beyond-diagonal reconfigurable intelligent surface (BD-RIS) has garnered significant research interest recently due to its ability to generalize existing reconfigurable intelligent surface (RIS) architectures and provide enhanced performance through flexible inter-connection among RIS elements. However, current BD-RIS designs often face challenges related to

Xuandong Zhao, Sam Gunn, Miranda Christ, Jaiden Fairoze

As the outputs of generative AI (GenAI) techniques improve in quality, it becomes increasingly challenging to distinguish them from human-created content. Watermarking schemes are a promising approach to address the problem of distinguishing between AI and human-generated content. These schemes embed hidden signals within AI-generated content to enable relia

José Nicolás Orce, Boris Pritychenko, Tibor Kibédi, Jun Chen

Born in Punjab (India) in December 1941, Balraj Singh is not only the single most prolific nuclear data evaluator and disseminator of nuclear structure and decay data with 148 evaluations in Nuclear Data Sheets -- 85 as the first and often only author -- plus other journals, but his upmost curiosity and dedication brought him to be one of the finest nuclear

Jinyang Wu, Mingkuan Feng, Shuai Zhang, Feihu Che

In-context learning (ICL) enables large language models (LLMs) to perform downstream tasks through advanced prompting and high-quality demonstrations. However, traditional ICL paradigms encounter significant limitations in complex reasoning tasks, stemming primarily from their dependence on example quality and absence of explicit reasoning guidance. To addre

Michal Makowski, Wenzheng Ye, Dominik Kowal, Francesco Maddalena

Scintillators convert high-energy radiation into detectable photons and play a crucial role in medical imaging and security applications. The enhancement of scintillator performance through nanophotonics and nanoplasmonics, specifically using the Purcell effect, has shown promise but has so far been limited to ultrathin scintillator films because of the loca

Jiangtao Shuai, Martin Baerveldt, Manh Nguyen-Duc, Anh Le-Tuan

This paper presents a preliminary study of an efficient object tracking approach, comparing the performance of two different 3D point cloud sensory sources: LiDAR and stereo cameras, which have significant price differences. In this preliminary work, we focus on single object tracking. We first developed a fast heuristic object detector that utilizes prior i

Siyang Zhang, Ser-Nam Lim

Generating long-duration videos has always been a significant challenge due to the inherent complexity of spatio-temporal domain and the substantial GPU memory demands required to calculate huge size tensors. While diffusion based generative models achieve state-of-the-art performance in video generation task, they are typically trained with predefined video

Yuze Wang, Aoran Hu, Ji Qi, Yang Liu

Accurately mapping large-scale cropland is crucial for agricultural production management and planning. Currently, the combination of remote sensing data and deep learning techniques has shown outstanding performance in cropland mapping. However, those approaches require massive precise labels, which are labor-intensive. To reduce the label cost, this study

Hao Liu, Minglin Chen, Yanni Ma, Haihong Xiao

Pre-training on large-scale unlabeled datasets contribute to the model achieving powerful performance on 3D vision tasks, especially when annotations are limited. However, existing rendering-based self-supervised frameworks are computationally demanding and memory-intensive during pre-training due to the inherent nature of volume rendering. In this paper, we

Hao Liu, Yanni Ma, Yan Liu, Haihong Xiao

3D vision-language (VL) reasoning has gained significant attention due to its potential to bridge the 3D physical world with natural language descriptions. Existing approaches typically follow task-specific, highly specialized paradigms. Therefore, these methods focus on a limited range of reasoning sub-tasks and rely heavily on the hand-crafted modules and

Jim A. Enriquez, Rustam Balafendiev, Alexander J. Millar, Constantin Simovski

Wire media (WM) resonators have emerged as promising realization for plasma haloscopes -- devices designed to detect axions, a potential component of dark matter. Key factors influencing the detection probability include cavity volume, resonance quality factor, and form factor. While the form factor has been explored for resonant frequency tuning, its optimi

Lei Liu, Zhenghao Chen, Wei Jiang, Wei Wang

In this work, we propose a novel compression framework for 3D Gaussian Splatting (3DGS) data. Building on anchor-based 3DGS methodologies, our approach compresses all attributes within each anchor by introducing a novel Hybrid Entropy Model for 3D Gaussian Splatting (HEMGS) to achieve hybrid lossy-lossless compression. It consists of three main components: a

Javier Huertas-Tato, Adrián Girón-Jiménez, Alejandro Martín, David Camacho

Authorship has entangled style and content inside. Authors frequently write about the same topics in the same style, so when different authors write about the exact same topic the easiest way out to distinguish them is by understanding the nuances of their style. Modern neural models for authorship can pick up these features using contrastive learning, howev

Daniel Arean, David Garcia-Fariña, Karl Landsteiner

Non-Hermitian quantum field theories are a promising tool to study open quantum systems. These theories preserve unitarity if PT-symmetry is respected, and in that case an equivalent Hermitian description exists via the so-called Dyson map. Generically, PT-symmetric non-Hermitian theories can also feature phases where PT-symmetry is broken and unitarity is l

Frédéric Fortier-Chouinard, Zitian Zhang, Louis-Etienne Messier, Mathieu Garon

Recent work has shown that diffusion models can serve as powerful neural rendering engines that can be leveraged for inserting virtual objects into images. However, unlike typical physics-based renderers, these neural rendering engines are limited by the lack of manual control over the lighting, which is often essential for improving or personalizing the des

Henri M. J. Boffin, David Jones

Stars are mostly found in binary and multiple systems, as at least 50% of all solar-like stars have companions - a fraction that goes up to 100% for the most massive stars. Moreover, a large fraction of them will interact in some way or another over the course of their lives. Such interactions can, and often will, alter the structure and evolution of both co

Sergio E. Jorás

This series of three lectures was presented at ``Escola de Cosmologia e Gravita\c{c}\~ao" \url{https://cosmosecontexto.org.br/ecg-inscricoes} and webcast at \url{https://shorturl.at/2ZSI7} -- in Portuguese, but slides in English. We will go through a brief review on $f(R)$ theories (in the metric approach) and the usual requirements for successful modificati

Dominique Labbé, Jacques Savoy

En plus de soixante ans, huit pr\'esidents se sont succ\'ed\'e \`a la t\^ete de la Ve R\'epublique fran\c{c}aise (de Gaulle, Pompidou, Giscard d'Estaing, Mitterrand, Chirac, Sarkozy, Hollande, Macron). Apr\`es avoir pr\'esent\'e le corpus de leurs discours -- soit 9202 textes et plus de 20 millions de mots \'etiquet\'es -- le style de chacun des pr\'esidents

Osama A. Marzouk, E. David Huckaby

We apply several weighted sum of gray gases models (WSGGMs) to calculate the radiative absorption coefficient for gas mixtures containing H2O and CO2. Our main objectives are to analyze and compare four WSGGMs which have been recently developed for oxy-fuel combustion. The models are compared with the widely-used air-fuel WSGGM of Smith et al. In addition to

Junha Hyung, Kinam Kim, Susung Hong, Min-Jung Kim

Diffusion models have emerged as a powerful tool for generating high-quality images, videos, and 3D content. While sampling guidance techniques like CFG improve quality, they reduce diversity and motion. Autoguidance mitigates these issues but demands extra weak model training, limiting its practicality for large-scale models. In this work, we introduce Spat

Eduard Zamfir, Zongwei Wu, Nancy Mehta, Yuedong Tan

Recent advancements in all-in-one image restoration models have revolutionized the ability to address diverse degradations through a unified framework. However, parameters tied to specific tasks often remain inactive for other tasks, making mixture-of-experts (MoE) architectures a natural extension. Despite this, MoEs often show inconsistent behavior, with s

Péter Mester, Ádám Timár

We construct a unimodular random rooted graph with maximal degree $d\geq 3$ and upper growth rate $d-1$, which does not have a growth rate. Ab\'ert, Fraczyk and Hayes showed that for a unimodular random tree, if the upper growth rate is at least $\sqrt{d-1}$, then the growth rate exists, and asked with some scepticism if this may hold for more general graphs

Molly Lynch, Michael Weselcouch

In this article we will use Minecraft to experimentally approximate the values of four different mathematical constants. The mathematical constants that we will approximate are $\sqrt{2}, \pi$, Euler's number $e$, and Ap\'{e}ry's constant $\zeta(3)$. We will begin each section with a brief history of the number being approximated and describe where it appear

Piotr Zenczykowski

We use experiment-supported dimensional analysis to further bolster our arguments that crucial information on the emergence and/or nature of space could be extracted from the combination of the properties of gravitational and strong interactions.

Ziyin Zhang, Jiahao Xu, Tian Liang, Xingyu Chen

Conventional speculative decoding (SD) methods utilize a predefined length policy for proposing drafts, which implies the premise that the target model smoothly accepts the proposed draft tokens. However, reality deviates from this assumption: the oracle draft length varies significantly, and the fixed-length policy hardly satisfies such a requirement. Moreo

Joel Kariel, Anthony Savagar

We develop a theoretical framework to investigate the link between rising scale economies and stagnating productivity. Our model features heterogeneous firms, imperfect competition, and firm selection. We demonstrate that scale economies generated by fixed costs have distinct impacts on aggregate productivity compared to those driven by returns to scale (slo

Lucie Cros, Françoise Combes, Anne-Laure Melchior, Thomas Martin

The Andromeda galaxy (M31) is the most nearby giant spiral galaxy, an opportunity to study with high resolution dynamical phenomena occurring in nuclear disks and bulges, able to explain star formation quenching, and galaxy evolution through collisions and tides. Multi-wavelength data have revealed in the central kpc of M31 strong dynamical perturbations, wi

Nicolas Blumenroehr, Philipp-Joachim Ost, Felix Kraus, Achim Streit

The FAIR principles are globally accepted guidelines for improved data management practices with the potential to align data spaces on a global scale. In practice, this is only marginally achieved through the different ways in which organizations interpret and implement these principles. The concept of FAIR Digital Objects provides a way to realize a domain-

Emily Williams, Amanda Howard, Brek Meuris, Panos Stinis

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonst

Jun Geng, Ziyi Xu

In this paper we investigate the $L^p$ regularity, $L^p$ Neumann and $W^{1,p}$ problems for generalized Schr\"odinger operator $-\text{div}(A\nabla )+ V $ in the region above a Lipschitz graph under the assumption that $A$ is elliptic, symmetric and $x_d-$independent. Specifically, we prove that the $L^p$ regularity problem is uniquely solvable for $$1<p<2+\

Andrew J. Peterson

As large language models (LLMs) are increasingly used for work, personal, and therapeutic purposes, researchers have begun to investigate these models' implicit and explicit moral views. Previous work, however, focuses on asking LLMs to state opinions, or on other technical evaluations that do not reflect common user interactions. We propose a novel evaluati

Eric T. Sawyer

We compare the smooth Alpert testing condition for the paraboloid Fourier extension conjecture in <cite>RiSa3</cite> to the modulated testing condition for the Kakeya conjecture in <cite>RiSa2</cite>. To this end, the modulated testing condition is converted to a certain restricted smooth Alpert testing condition for the paraboloid Fourier extension conjectu

José Fernando Núñez, Jamie Arjona, Javier Béjar

Deep learning models need a sufficient amount of data in order to be able to find the hidden patterns in it. It is the purpose of generative modeling to learn the data distribution, thus allowing us to sample more data and augment the original dataset. In the context of physiological data, and more specifically electrocardiogram (ECG) data, given its sensiti

Fateme Gholami, Alexandre Landry

In this paper, we find several teleparallel $F(T,B)$ solutions for a Robertson--Walker (TRW) cosmological spacetime. We first set and solve the $F(T,B)$-type field equations for a linear perfect fluid. Using similar techniques, we then find new $F(T,B)$ solutions for non-linear perfect fluids with a weak quadratic correction term to the linear equation of st

Chelsea Walton, Harshit Yadav

Due to the work of Shimizu (2019), various nondegeneracy conditions for braided finite tensor categories are equivalent. This theory is partially extended to braided module categories here. We introduce when a braided module category is "nondegenerate" and "factorizable", and establish that these properties are equivalent. The proof involves a new monadicity

Feiyang Huang

In the field of image captioning, the phenomenon where missing or nonexistent objects are used to explain an image is referred to as object bias (or hallucination). To mitigate this issue, we propose a target-aware prompting strategy. This method first extracts object labels and their spatial information from the image using an object detector. Then, an attr