November 2024 arXiv papers — page 29

Tianyi Lou

We study the property $P_{\text {naive }}$ of mapping class groups of surfaces of infinite type, that is, for any finite collection of non-trivial elements $h_{1},h_{2}, \cdots, h_{n}$, there exists another element $g\neq 1$ of infinite order such that for all $i$, $\langle g, h_{i}\rangle \cong \langle g \rangle * \langle h_{i} \rangle$.

Jordan J. Bird

The integration of new literature into the English curriculum remains a challenge since educators often lack scalable tools to rapidly evaluate readability and adapt texts for diverse classroom needs. This study proposes to address this gap through a multimodal approach that combines transformer-based text classification with linguistic feature analysis to a

Yukun Wang, Longguang Wang, Zhiyuan Ma, Qibin Hu

Despite the typical inversion-then-editing paradigm using text-to-image (T2I) models has demonstrated promising results, directly extending it to text-to-video (T2V) models still suffers severe artifacts such as color flickering and content distortion. Consequently, current video editing methods primarily rely on T2I models, which inherently lack temporal-co

Zong-Zhe Du

We derive soft theorems for on-shell scattering amplitudes from non-linearly realised global space-time symmetries, arising from the flat space and decoupling limits of the effective field theories (EFTs) of inflation, while taking particular care of on-shell limits, soft limits, time-ordered correlations, momentum derivatives, energy-momentum conserving del

Max Schneider, Hendrik Nicolai, Vinzenz Schuh, Matthias Steinhausen

Hydrogen combustion systems operated under fuel-lean conditions offer great potential for low emissions. However, these operating conditions are also susceptible to intrinsic thermodiffusive combustion instabilities. Even though technical combustors are enclosed by walls that significantly influence the combustion process, intrinsic flame instabilities have

Julia Ive, Vishal Yadav, Mariia Ignashina, Matthew Rand

Introduction: The use of chatbots is becoming increasingly important across various aspects of daily life. However, the privacy concerns associated with these communications have not yet been thoroughly addressed. The aim of this study was to investigate user awareness of privacy risks in chatbot interactions, the privacy-preserving behaviours users practice

Qi Dai, Haixing Miao, Yiqiu Ma

Quantum mechanics, which governs all microscopic phenomena, encounters challenges when applied to macroscopic objects that exhibit classical behavior. To address this micro-macro disparity, collapse models such as the Continuous Spontaneous Localization (CSL) and Diosi-Penrose (DP) models have been proposed. These models phenomenologically modify quantum the

E. Emanuel Rapsch

A general theory of stochastic extensive forms is developed to bridge two concepts of information flow: decision trees and refined partitions on the one side, filtrations from probability theory on the other. Instead of the traditional "nature" agent, this framework uses a single lottery draw to select a tree of a given decision forest. Each "personal" agent

Paramjeet Banger, Rajat, Sandeep Gautam

We present a theoretical study of the collective excitations of the supersolid annular stripe phase of a spin-orbital-angular-momentum-coupled (SOAM-coupled) spin-1 Bose-Einstein condensate. The annular stripe phase simultaneously breaks two continuous symmetries, namely rotational and $U(1)$ gauge symmetry, and is more probable in the condensates with a lar

Ross O'Driscoll, Claudia Hagen, Joe Bater, James M. Adams

Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civilian critical national infrastructure. The use of artificial intelligence and autonomous agents in these attacks increases the scale, range, and complexity of this threat and the subsequent disruption they cause

Davyd Svyezhentsev, George Retsinas, Petros Maragos

In recent years, interest in synthetic data has grown, particularly in the context of pre-training the image modality to support a range of computer vision tasks, including object classification, medical imaging etc. Previous work has demonstrated that synthetic samples, automatically produced by various generative processes, can replace real counterparts an

Sezen Ece Kayacik, Albert H. Schrotenboer, Iris F. A. Vis, Beste Basciftci

Green hydrogen is a critical component for achieving the European Union's 2050 net-zero emissions goal. However, ensuring a reliable and stable supply is challenging, particularly when local production of green hydrogen is subject to high variability due to fluctuating renewable energy output. Although importing from regions with stable renewable resources m

Cynthia Dwork, Chris Hays, Nicole Immorlica, Juan C. Perdomo

Professional networks provide invaluable entree to opportunity through referrals and introductions. A rich literature shows they also serve to entrench and even exacerbate a status quo of privilege and disadvantage. Hiring platforms, equipped with the ability to nudge link formation, provide a tantalizing opening for beneficial structural change. We anticipa

Nikita Kisel, Illia Volkov, Katerina Hanzelkova, Klara Janouskova

Since its release, ImageNet-1k dataset has become a gold standard for evaluating model performance. It has served as the foundation for numerous other datasets and training tasks in computer vision. As models have improved in accuracy, issues related to label correctness have become increasingly apparent. In this blog post, we analyze the issues in the Image

Alejandro Argudin-Monroy, Daniel Bravo, Carlos E. Parra

We study the conditions under which a TTF class in a module category over a ring is silting. Using the correspondence between idempotent ideals over a ring and TTF classes in the module category, we focus on finding the necessary and sufficient conditions for $R/I$ to be a silting $R$-module, and hence for the TTF class $\mathbf{Gen}(R/I)$ to be silting, whe

Stuti Pathak, Prashant Kumar, Dheeraj Baiju, Nicholus Mboga

Point clouds acquired in constrained, challenging, uncontrolled, and multi-sensor real-world settings are noisy, incomplete, and non-uniformly sparse. This presents acute challenges for the vital task of point cloud completion. Using tools from Algebraic Topology and Persistent Homology (PH), we demonstrate that current benchmark object point clouds lack ric

Anne Frühbis-Krüger, Thiago da Silva

In this article, we provide an explicit description of the Lipschitz saturation $A^*_{B,R}$ of a subalgebra $A\subseteq R[[t^{\gamma_1},\ldots, t^{\gamma_n}]]$ over a ring $R$ in terms of the numerical semigroup $\Gamma = \langle\gamma_{1},\ldots,\gamma_{n}\rangle$ with mild conditions imposed on $R$.

Nimita Shinde, Yanan Zhu, Wei Wang, Wangyao Li

Objective: Proton spot-scanning arc therapy (ARC) is an emerging modality that can improve the high-dose conformity to targets compared with standard intensity-modulated proton therapy (IMPT). However, the efficient treatment delivery of ARC is challenging due to the required frequent energy changes during the continuous gantry rotation. This work proposes a

Niklas Miller

A complete characterization of the asymptotic singularity probability of random circulant Bernoulli matrices is given for all values of the probability parameter.

Jovana Videnovic, Alan Lukezic, Matej Kristan

Memory-based trackers are video object segmentation methods that form the target model by concatenating recently tracked frames into a memory buffer and localize the target by attending the current image to the buffered frames. While already achieving top performance on many benchmarks, it was the recent release of SAM2 that placed memory-based trackers into

Alexandre C. Ricardo, Gabriel P. L. M. Fernandes, Amanda G. Valério, Tiago de S. Farias

Warehouse optimization stands as a critical component for enhancing operational efficiency within the industrial sector. By strategically streamlining warehouse operations, organizations can achieve significant reductions in logistical costs such as the necessary footprint or traveled path, and markedly improve overall workflow efficiency including retrieval

DongSeon Hwang, Hiroshi Sato, Naoto Yotsutani

We show that there exists a toric Fano manifold of dimension $10$ that does not admit an extremal K\"ahler metric in the first Chern class, answering a question of Mabuchi. By taking a product with a suitable toric Fano manifold, one can also produce a toric Fano manifold of dimension $n$ admitting no extremal K\"ahler metric in the first Chern class for eac

Michal Hevessy

In this paper a construction of a metrizable zero-dimensional CDH space $X$ such that $X^2$ has exactly $\mathfrak{c}$ countable dense subsets is provided. Furthermore, it is shown that the space can be constructed consistently co-analytic. Thus answering an open question asked by Medini. To do so we use the notion of $\lambda$-sets.

Yairon Cid-Ruiz, Yupeng Li, Jacob P. Matherne

We study the equivariant cohomology classes of torus-equivariant subvarieties of the space of matrices. For a large class of torus actions, we prove that the polynomials representing these classes (up to suitably changing signs) are covolume polynomials in the sense of Aluffi. We study the cohomology rings of complex varieties in terms of Macaulay inverse sy

Ben Philps, Maria del C. Valdes Hernandez, Chen Qin, Una Clancy

White Matter Hyperintensities (WMH) are key neuroradiological markers of small vessel disease present in brain MRI. Assessment of WMH is important in research and clinics. However, WMH are challenging to segment due to their high variability in shape, location, size, poorly defined borders, and similar intensity profile to other pathologies (e.g stroke lesio

Johannes O. Ferstad, Emily B. Fox, David Scheinker, Ramesh Johari

Digital health interventions (DHIs) and remote patient monitoring (RPM) have shown great potential in improving chronic disease management through personalized care. However, barriers like limited efficacy and workload concerns hinder adoption of existing DHIs; while limited sample sizes and lack of interpretability limit the effectiveness and adoption of pu

Lakshmi Likhitha Mankali, Jitendra Bhandari, Manaar Alam, Ramesh Karri

Large language models (LLMs) have demonstrated remarkable potential with code generation/completion tasks for hardware design. In fact, LLM-based hardware description language (HDL) code generation has enabled the industry to realize complex designs more quickly, reducing the time and effort required in the development cycle. However, the increased reliance

Philipp Lücke

Motivated by recent work of Boney, Dimopoulos, Gitman and Magidor, we characterize the existence of weak compactness cardinals for all abstract logics through combinatorial properties of the class of ordinals. This analysis is then used to show that, in contrast to the existence of strong compactness cardinals, the existence of weak compactness cardinals for

Niklas Dexheimer, Johannes Schmidt-Hieber

Forward gradient descent (FGD) has been proposed as a biologically more plausible alternative of gradient descent as it can be computed without backward pass. Considering the linear model with $d$ parameters, previous work has found that the prediction error of FGD is, however, by a factor $d$ slower than the prediction error of stochastic gradient descent (

Pushpak Pandey, Kanak Saha

Estimating the true background in an astronomical image is fundamental to detecting faint sources. In a typical low-photon count astronomical image, such as in the far and near-ultraviolet wavelength range, conventional methods relying on the 3-sigma clipping and median or mode estimation often fail to capture the true background level accurately. As a conse

Förster, Julia Katheder, Giacomo Ortali

An \emph{outer-RAC drawing} of a graph is a straight-line drawing where all vertices are incident to the outer cell and all edge crossings occur at a right angle. If additionally, all crossing edges are either horizontal or vertical, we call the drawing \emph{outer-apRAC} (\emph{ap} for \emph{axis-parallel)}. A graph is outer-(ap)RAC if it admits an outer-(a

Arnaud Dumont, Andrew J. Morris

We obtain Riesz transform bounds and characterise operator-adapted Hardy spaces to solve boundary value problems for singular Schr\"odinger equations $-\mathrm{div}(A\nabla u)+aVu=0$ in the upper half-space $\mathbb{R}^{1+n}_{+}$ with boundary dimension $n\geq 3$. The coefficients $(A,a,V)$ are assumed to be independent of the transversal direction to the bo

Emily M. Boudreaux, Brian C. Chaboyer, Amanda Ash, Renata Edaes Hoh

The helium abundances in the multiple populations that are now known to comprise all closely studied Milky Way globular clusters are often inferred by fitting isochrones generated from stellar evolutionary models to globular cluster photometry. It is therefore important to build stellar models that are chemically self-consistent in terms of their structure,

Daniel Timmer, Christoph Lienau

This chapter discusses recent experimental work exploring the optical properties and quantum dynamics of organic semiconductor nanostructures based on squaraine dyes. Squaraines are prototypical quadrupolar charge-transfer chromophores of interest for solu-tion-processed photovoltaics and as aggregates with large circular dichroism. Here, we demonstrate and

Bernd Freytag, Susanne Höfner, Bernhard Aringer, Andrea Chiavassa

The dramatic dimming episode of the red supergiant Betelgeuse in 2019/2020, caused by a partial darkening of the stellar disk, has highlighted gaps in the understanding of the evolution of massive stars. We analyzed numerical models to investigate the processes behind the formation of dark surface patches and the associated reduction in the disk-integrated s

Abolfazl Changizi, Ali H. Abdollahi Bafghi, Mahtab Mirmohseni, Masoumeh Nasiri-Kenari

This paper studies cache-aided wireless networks in the presence of active intelligent reflecting surfaces (IRSs) from an information-theoretic perspective. Specifically, we investigate interference management in a cache-aided wireless network assisted by an active IRS to enhance the achievable degrees of freedom (DoF). To this end, we jointly design the con

Jiayi Kuang, Jingyou Xie, Haohao Luo, Ronghao Li

Visual Question Answering (VQA) is a challenge task that combines natural language processing and computer vision techniques and gradually becomes a benchmark test task in multimodal large language models (MLLMs). The goal of our survey is to provide an overview of the development of VQA and a detailed description of the latest models with high timeliness. T

Mengqian Dinga, Jun Liua, Yang Luo, Jinshan Tang

Caenorhabditis elegans (C. elegans) is an excellent model organism because of its short lifespan and high degree of homology with human genes, and it has been widely used in a variety of human health and disease models. However, the segmentation of C. elegans remains challenging due to the following reasons: 1) the activity trajectory of C. elegans is uncont

Tariq M Khan, Dawn Lin, Shahzaib Iqbal, Erik Meijering

Incorporating modern computer vision techniques into clinical protocols shows promise in improving skin lesion segmentation. The U-Net architecture has been a key model in this area, iteratively improved to address challenges arising from the heterogeneity of dermatologic images due to varying clinical settings, lighting, patient attributes, and hair density

Yichen Wang, Qing Yu, Yancun Song

Bike-sharing is an environmentally friendly shared mobility mode, but its self-loop phenomenon, where bikes are returned to the same station after several time usage, significantly impacts equity in accessing its services. Therefore, this study conducts a multiscale analysis with a spatial autoregressive model and double machine learning framework to assess

Yichen Wang, Hao Yin, Yifan Yang, Chenyang Zhao

Freight truck-related crashes pose significant challenges, leading to substantial economic losses, injuries, and fatalities, with pronounced spatial disparities across different regions. This study adopts a transport geography perspective to examine spatial justice concerns by employing deep counterfactual inference models to analyze how socioeconomic dispar

Yurij Salmaniw, Alexander P Browning

Parameter identifiability is often requisite to the effective application of mathematical models in the interpretation of biological data, however theory applicable to the study of partial differential equations remains limited. We present a new approach to structural identifiability analysis of fully observed parabolic equations that are linear in their par

Vladimir Dotsenko, Sergey Mozgovoy

The notion of Weyl modules, both local and global, goes back to Chari and Pressley in the case of affine Lie algebras, and has been extensively studied for various Lie algebras graded by root systems. We extend that definition to a certain class of Lie algebras graded by weight lattices and prove that if such a Lie algebra satisfies a natural "thinness" cond

Bruno Dewer

A result due to Cho, Miyaoka, Shepherd-Barron [CMSB] and Kebekus [Ke] provides a numerical characterization of projective spaces. More recently, Dedieu and H\"oring [DH] gave a characterization of smooth quadrics based on similar arguments. As a relative version of [CMSB] and [Ke], H\"oring and Novelli proved in [HN] that the locus covered by positive-dimens

Kaveh Shahedi, Heng Li, Maxime Lamothe, Foutse Khomh

Software performance modeling plays a crucial role in developing and maintaining software systems. A performance model analytically describes the relationship between the performance of a system and its runtime activities. This process typically examines various aspects of a system's runtime behavior, such as the execution frequency of functions or methods,

Sumit Chaudhary, Davide Li Calsi, JinHyeock Choi, Marc Geitz

Quantum Key Distribution (QKD) offers provably secure, information-theoretic key exchange, but in long-distance scenarios without quantum repeaters, Trusted Nodes (TNs) are commonly employed despite introducing critical security risks. We propose a redundant key management method for QKD network that combines Twin Field QKD (TF-QKD) (or Measurement-Device In

Noura Zenbaa, Fabian Majcen, Claas Abert, Florian Bruckner

Magnonic logic gates represent a crucial step toward realizing fully magnonic data processing systems without reliance on conventional electronic or photonic elements. Recently, a universal and reconfigurable inverse-design device has been developed, featuring a 7$\times$7 array of independent current loops that create local inhomogeneous magnetic fields to

Idrus Husin Belfaqih, Martin Bojowald, Suddhasattwa Brahma, Erick I. Duque

Most of the potential physical effects of loop quantum gravity have been derived in effective models that modify the constraints of canonical general relativity in specific forms. Emergent modified gravity evaluates important conditions that ensure the existence of a compatible geometrical space-time interpretation of canonical solutions, as well as phase-sp

Yichen Wang, Huanbo Zhang, Chunhong Yuan, Xiangyu Li

In the evolving digital landscape, network flow models have transcended traditional applications to become integral in diverse sectors, including supply chain management. This research develops a robust network flow model for semiconductor wafer supply chains, optimizing resource allocation and addressing maximum flow challenges in production and logistics.

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe, Óscar Mata-Carballeira

The article discusses the use of low cost System-On-Module (SOM) platforms for the implementation of efficient hyperspectral imaging (HSI) processors for application in autonomous driving. The work addresses the challenges of shaping and deploying multiple layer fully convolutional networks (FCN) for low-latency, on-board image semantic segmentation using re

Ying Chen, Ziwei Xu, Kotaro Inoue, Ryutaro Ichise

Instrumental Variable (IV) provides a source of treatment randomization that is conditionally independent of the outcomes, responding to the challenges of counterfactual and confounding biases. In finance, IV construction typically relies on pre-designed synthetic IVs, with effectiveness measured by specific algorithms. This classic paradigm cannot be genera

Amir Reza Asadi, Mohamad Saraee, Azadeh Mohammadi

This study investigated the factors contributing to the failure of augmented reality (AR) and virtual reality (VR) startups in the emerging metaverse landscape. Through an in-depth analysis of 29 failed AR/VR startups from 2016 to 2022, key pitfalls were identified, such as a lack of scalability, poor usability, unclear value propositions, and the failure to

Megan E. Tracy, Benjamin J. Kasting, Cecilia Herrero, Ludovic Berthier

Physical vapor deposition can prepare organic glasses with high kinetic stability. When heated, these glassy solids slowly transform into the supercooled liquid in a process known as rejuvenation. In this study, we anneal vapor-deposited glasses of methyl-m-toluate (MMT) for six hours at 0.98Tg to observe rejuvenation using dielectric spectroscopy. Glasses o

Haitham S. Al-Sinani, Chris J. Mitchell

This study explores the application of generative AI (GenAI) within manual exploitation and privilege escalation tasks in Linux-based penetration testing environments, two areas critical to comprehensive cybersecurity assessments. Building on previous research into the role of GenAI in the ethical hacking lifecycle, this paper presents a hands-on experimenta

Andor Diera, Lukas Galke, Ansgar Scherp

Low isotropy in an embedding space impairs performance on tasks involving semantic inference. Our study investigates the impact of isotropy on semantic code search performance and explores post-processing techniques to mitigate this issue. We analyze various code language models, examine isotropy in their embedding spaces, and its influence on search effecti

Hyeonseung Lee, Ji Won Yoon, Sungsoo Kim, Nam Soo Kim

Transducer neural networks have emerged as the mainstream approach for streaming automatic speech recognition (ASR), offering state-of-the-art performance in balancing accuracy and latency. In the conventional framework, streaming transducer models are trained to maximize the likelihood function based on non-streaming recursion rules. However, this approach

Hoàng-Ân Lê, Paul Berg, Minh-Tan Pham

Object detection and semantic segmentation are both scene understanding tasks yet they differ in data structure and information level. Object detection requires box coordinates for object instances while semantic segmentation requires pixel-wise class labels. Making use of one task's information to train the other would be beneficial for multi-task partially

Anurag Shandilya, Swapnil Bhat, Akshat Gautam, Subhash Yadav

Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-tailed dataset augmentation, and scaling machine learning algorithms. For medical applications, the synthetically generated medical images by such models are still reasonable in qual

Serhii Svystun, Oleksandr Melnychenko, Pavlo Radiuk, Oleg Savenko

The research presents an automated method for determining the trajectory of an unmanned aerial vehicle (UAV) for wind turbine inspection. The proposed method enables efficient data collection from multiple wind installations using UAV optical sensors, considering the spatial positioning of blades and other components of the wind energy installation. It inclu

Alex Ocampo, Enrico Giudice, Dieter A. Häring, Baldur Magnusson

Mediation analysis for survival outcomes is challenging. Most existing methods quantify the treatment effect using the hazard ratio (HR) and attempt to decompose the HR into the direct effect of treatment plus an indirect, or mediated, effect. However, the HR is not expressible as an expectation, which complicates this decomposition, both in terms of estimat

Chengjian Li, Xiangbo Shu, Qiongjie Cui, Yazhou Yao

Diffusion models achieve impressive performance in human motion generation. However, current approaches typically ignore the significance of frequency-domain information in capturing fine-grained motions within the latent space (e.g., low frequencies correlate with static poses, and high frequencies align with fine-grained motions). Additionally, there is a

R. Maire, A. Plati, F. Smallenburg, G. Foffi

Non-equilibrium phase coexistence is commonly observed in both biological and artificial systems, yet understanding it remains a significant challenge. Unlike equilibrium systems, where free energy provides a unifying framework, the absence of such a quantity in non-equilibrium settings complicates their theoretical understanding. Granular materials, driven

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe, M. Victoria Martínez

We present the updated version of the HSI-Drive dataset aimed at developing automated driving systems (ADS) using hyperspectral imaging (HSI). The v2.0 version includes new annotated images from videos recorded during winter and fall in real driving scenarios. Added to the spring and summer images included in the previous v1.1 version, the new dataset contai

A. A. Kudryashova, N. N. Bursov, S. A. Trushkin

The results of the analysis of 205 brightest sources ( $S>15$ mJy), which were found in the sky survey at the declination of the pulsar in the Crab Nebula, are presented. The survey was conducted at a frequency of 4.7~GHz using a three-beam radiometer complex installed in the focus of the Western Sector of the RATAN-600 radio telescope in 2018-2019. Based on

J. C Martínez, L. Soukup

We continue our investigation of cardinal sequences associated with locally Lindelof, scattered, Hausdorff P-spaces (abbreviated as LLSP spaces). We outline a method for constructing LLSP spaces from cone systems and partial orders with specific properties. Additionally, we establish limitations on the cardinal sequences of LLSP spaces. Finally, we present b

Kutalmış Coşkun, Borahan Tümer, Bjarne C. Hiller, Martin Becker

Markov chains are simple yet powerful mathematical structures to model temporally dependent processes. They generally assume stationary data, i.e., fixed transition probabilities between observations/states. However, live, real-world processes, like in the context of activity tracking, biological time series, or industrial monitoring, often switch behavior o

Divya Jyoti, Alex Fétida, Laurent Limot, Roberto Robles

We investigate the temperature-dependent deposition of nickelocene (NiCp$_2$) molecules on a single crystal Au(111) substrate, revealing distinct adsorption behaviors and structural formations. At low temperatures (4.2 K), individual NiCp$_2$ molecules adsorb on the herringbone elbows and step edges, forming ordered patterns as molecular coverage increases.

Victor Vinnikov, Hugo J. Woerdeman

We establish various certifying determinantal representation results for a polynomial that contains as a factor a prescribed multivariable polynomials that is strictly stable on a tube domain. The proofs use a Cayley transform in combination with the Matrix-valued Hermitian Positivstellensatz developed in ArXiv:1501.05527.

Vladimir Malinovskii, Andrei Panferov, Ivan Ilin, Han Guo

Quantizing large language models has become a standard way to reduce their memory and computational costs. Typically, existing methods focus on breaking down the problem into individual layer-wise sub-problems, and minimizing per-layer error, measured via various metrics. Yet, this approach currently lacks theoretical justification and the metrics employed m

Oriane Blondel

We study the stationary measures for variants of the Porous Medium Model in dimension 1. These are exclusion processes that belong to the class of kinetically constrained models, in which an exchange can occur between $x$ and $x+1$ only if there is a particle either at $x-1$ or $x+2$. We show that any stationary probability measure can be decomposed into a f

Nikos Frantzikinakis

Suppose we partition the integers into finitely many cells. Can we always find a solution of the equation $x^2+y^2=z^2$ with $x,y,z$ on the same cell? What about more general homogeneous quadratic equations in three variables? These are basic questions in arithmetic Ramsey theory, which have recently been partially answered using ideas inspired by ergodic th

Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang

We investigate the approximation and estimation rates of conditional diffusion transformers (DiTs) with classifier-free guidance. We present a comprehensive analysis for ``in-context'' conditional DiTs under four common data assumptions. We show that both conditional DiTs and their latent variants lead to the minimax optimality of unconditional DiTs under id

Wenliang Sheng, Hongxu Zhao, Lingpeng Chen, Guangyang Zeng

We consider the acoustic-n-point (AnP) problem, which estimates the pose of a 2D forward-looking sonar (FLS) according to n 3D-2D point correspondences. We explore the nature of the measured partial spherical coordinates and reveal their inherent relationships to translation and orientation. Based on this, we propose a bi-step efficient and statistically opt

Julia Bruner, Kyle Adams, Skylar Grey, Mahya Aghaee

Liver transplant can be a life-saving procedure for patients with end-stage liver disease. With the introduction of modern immunosuppressive therapies, short-term survival has significantly improved. However, long-term survival has not substantially improved in decades. Consequently, causes of death are now more likely to be due to the toxicities and side-ef

Jiahan Li, Chaoran Cheng, Jianzhu Ma, Ge Liu

Shape assembly, which aims to reassemble separate parts into a complete object, has gained significant interest in recent years. Existing methods primarily rely on networks to predict the poses of individual parts, but often fail to effectively capture the geometric interactions between the parts and their poses. In this paper, we present the Geometric Point

Christopher Irving, Benoît Van Vaerenbergh

We establish universality of the renormalised energy for mappings from a planar domain to a compact manifold, by approximating subquadratic polar convex functionals of the form $\int_\Omega f(|\mathrm{D} u|)\,\mathrm{d} x$. The analysis relies on the condition that the vortex map ${x}/{\lvert x\rvert}$ has finite energy and that $t\mapsto f (\sqrt{t})$ is co

Yosuke Ueno, Taku Saito, Teruo Tanimoto, Yasunari Suzuki

Due to the high error rate of a qubit, detecting and correcting errors on it is essential for fault-tolerant quantum computing (FTQC). Among several FTQC techniques, lattice surgery (LS) using surface code (SC) is currently promising. To demonstrate practical quantum advantage as early as possible, it is indispensable to propose a high-performance and low-ov

Richard J. Nowakowski, Ethan J. Saunders

Mis\`ere games in general have little algebraic structure, but if the games under consideration have properties then some algebraic structure re-appears. In 2023, the class of Blocking games was identified. Mis\`ere Cricket Pitch was suggested as a problem at the Games-at-Dal-2023 Workshop, and is the first game in this class to be studied. Normal play Crick

Óscar Amaro, Lucas I. Iñigo Gamiz, Marija Vranic

Near-future experiments with Petawatt class lasers are expected to produce a high flux of gamma-ray photons and electron-positron pairs through Strong Field Quantum Electrodynamical processes. Simulations of the expected regime of laser-matter interaction are computationally intensive due to the disparity of the spatial and temporal scales and because quantu

Xue Zhang, Yu Sang, Gabriel A. Hoerning, Filipe B. Abdalla

There are various surveys that will provide excellent data to search for and localize Fast Radio Bursts (FRBs). The BINGO project will be one such survey, and this collaboration has already estimated a FRB detection rate that the project will yield. We present a forecast of the future constraints on our current cosmological model that the BINGO FRB detection

Yijia Hong, Yuan-Chen Guo, Ran Yi, Yulong Chen

Decomposing physically-based materials from images into their constituent properties remains challenging, particularly when maintaining both computational efficiency and physical consistency. While recent diffusion-based approaches have shown promise, they face substantial computational overhead due to multiple denoising steps and separate models for differe

Jiahan Shi, Matthias Bartelmann, Hubert Klahr, Cornelis P. Dullemond

Planet formation in the solar system was started when the first planetesimals were formed from the gravitational collapse of pebble clouds. Numerical simulations of this process, especially in the framework of streaming instability, produce various power laws for the initial mass function for planetesimals. While recent advances have shed light on turbulence

Darya Apushkinskaya, Sergey Tikhomirov, Nina Uraltseva

We study solutions of parabolic equations with a discontinuous hysteresis operator, described by a free interface boundary. It is established that for spatially transverse initial data from the space $W^{2-2/q}_q$ with $q > 3$, there exists a solution in the space $W^{2,1}_q$, where the interface boundary exhibits Holder continuity with an exponent $1/2$. Fu

Atamert Rahma, Chinmay Datar, Felix Dietrich

Neural networks that synergistically integrate data and physical laws offer great promise in modeling dynamical systems. However, iterative gradient-based optimization of network parameters is often computationally expensive and suffers from slow convergence. In this work, we present a backpropagation-free algorithm to accelerate the training of neural netwo

Andreas Hagn, Jan Krause, Moritz Stargalla, Lorenza Moreno

This paper studies a variant of the Set Covering Routing Problem (SCRP) motivated by post-disaster humanitarian logistics. We consider a hybrid distribution concept in which the majority of transportation is performed by helicopters, while ground transport is limited to the last mile, addressing severe accessibility constraints in disaster-affected regions.

Konstantinos Efstathiou, Sonja Hohloch, Pedro Santos

Hypersemitoric systems are a class of integrable systems on $4$-dimensional symplectic manifolds which only have mildly degenerate singularities and where one of the integrals induces an effective Hamiltonian $S^1$-action and is proper. We introduce the affine invariant of hypersemitoric systems, which is a generalization of the Delzant polytope of toric sys

Onur Dikici, Edoardo Ghignone, Cheng Hu, Nicolas Baumann

Accurate tire modeling is crucial for optimizing autonomous racing vehicles, as state-of-the-art (SotA) model-based techniques rely on precise knowledge of the vehicle's parameters. Yet, system identification in dynamic racing conditions is challenging due to varying track and tire conditions. Traditional methods require extensive operational ranges, often i

Jabez J. McClelland, Evgheni Strelcov, Ami Chand

We present measurements comparing scanning thermal microscopy in air and vacuum. Signal levels are compared and resolution is probed by scanning over the edge of a nanofabricated Ag square embedded in SiO2. Signals measured in air were seen to be 2.5 to 40 times larger than in vacuum. Furthermore, the air signals were stable while the vacuum signals varied s

Moises Diaz, Miguel A. Ferrer, Jose Juan Quintana, Adam Wolniakowski

Online signature parameters, which are based on human characteristics, broaden the applicability of an automatic signature verifier. Although kinematic and dynamic features have previously been suggested, accurately measuring features such as arm and forearm torques remains challenging. We present two approaches for estimating angular velocities, angular pos

Mohd Norhakim Bin Hassan, Simon Watson, Cheng Zhang

This paper presents a wireless power transfer (WPT) for a mid-sized inspection mobile robot. The objective is to transmit 100 W of power over 1 meter of distance, achieved through lightweight Litz wire coils weighing 320 g held together with a coil structure of 3.54 kg. The Wireless Power Transfer System (WPTS) is mounted onto an unmanned ground vehicle (UGV

J. S. Kim, P. M. Dee, J. J. Hamlin, P. J. Hirschfeld

WBe2, which occurs in space group 194, with hexagonal symmetry P63/mmc, is prepared by arc-melting at temperatures above 2200 C, where Be vapor loss is significant. This study is motivated by recent work on MoB2 and WB2, both superconductors (Tc=32 and 17 K respectively) under high (~70 GPa) pressure. In order to avoid the known Be-rich superconducting phase

Bhavna Yadav, Ashutosh Kumar Alok

Neutrino oscillation experiments are gradually approaching an era of precision, where subleading effects can also be tested. One such subleading effect is Non-Standard Interactions (NSI), which can play a crucial role in neutrino oscillations. Various works have typically discussed vector NSI in the context of quantum correlations. Recently, there have been

Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng

Peptides, short chains of amino acids, interact with target proteins, making them a unique class of protein-based therapeutics for treating human diseases. Recently, deep generative models have shown great promise in peptide generation. However, several challenges remain in designing effective peptide binders. First, not all residues contribute equally to pe

Zigeng Chen, Xinyin Ma, Gongfan Fang, Xinchao Wang

In the rapidly advancing field of image generation, Visual Auto-Regressive (VAR) modeling has garnered considerable attention for its innovative next-scale prediction approach. This paradigm offers substantial improvements in efficiency, scalability, and zero-shot generalization. Yet, the inherently coarse-to-fine nature of VAR introduces a prolonged token s

Thomas Bruys, Reza Zandehshahvar, Amira Hijazi, Pascal Van Hentenryck

This study develops a deep learning-based approach to automate inbound load plan adjustments for a large transportation and logistics company. It addresses a critical challenge for the efficient and resilient planning of E-commerce operations in presence of increasing uncertainties. The paper introduces an innovative data-driven approach to inbound load plan

Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan

Recent research has generated hope that inference scaling, such as resampling solutions until they pass verifiers like unit tests, could allow weaker models to match stronger ones. Beyond inference, this approach also enables training reasoning models, where data is curated using rejection sampling against a verifier. However, we show that this approach is f

Luke R. Holden, Clive N. Tadhunter

To test the scenario that outflows accelerated by active galactic nuclei (AGN) have a major impact on galaxy-wide scales, we have analysed deep VLT/MUSE data for the type-2 quasar/ultraluminous infrared galaxy F13451+1232 - an object that represents the major mergers considered in models of galaxy evolution. After carefully accounting for the effects of atmo

Mojtaba A. Farahani, Fadi El Kalach, Austin Harper, M. R. McCormick

TSF is growing in various domains including manufacturing. Although numerous TSF algorithms have been developed recently, the validation and evaluation of algorithms hold substantial value for researchers and practitioners and are missing. This study aims to fill this gap by evaluating the SoTA TSF algorithms on thirteen manufacturing datasets, focusing on t

Louis Narmour, Ryan Job, Tomofumi Yuki, Sanjay Rajopadhye

Reductions combine collections of inputs with an associative (and here, also commutative) operator to produce collections of outputs. When the same value contributes to multiple outputs, there is an opportunity to reuse partial results, enabling reduction simplification. We provide the first complete push-button implementation of reduction simplification in

Daria Shvalyuk, Anton Nazarov

In this paper, we consider the formation of droplets in the dimer model on a triangular lattice. The droplets in the dimer model are superposition polygons formed as two overlapping configurations of dimers: constant and movable. We demonstrate that specific local energies of dimers and low temperatures lead to the emergence of a macroscopic droplet. The mot