December 2024 arXiv papers — page 18

Tomasz Dębiec, Markus Schmidtchen

Localisation limits and nonlocal approximations of degenerate parabolic systems have experienced a renaissance in recent years. However, only few results cover anisotropic systems. This work addresses this gap by establishing the nonlocal-to-limit for a specific anisotropic cross-diffusion system encountered in population dynamics featuring phase-separation

Yuanzhen Shao, Gieri Simonett, Mathias Wilke

We consider the motion of an incompressible viscous fluid on a sphere, incorporating the effects of the Coriolis force. We demonstrate that global solutions exist for any divergence-free initial condition with finite kinetic energy. Furthermore, we show that each solution converges at an exponential rate to a state that is aligned with the rotation of the sp

Mikhail Maslyaev, Alexander Hvatov

Equation discovery methods hold promise for extracting knowledge from physics-related data. However, existing approaches often require substantial prior information that significantly reduces the amount of knowledge extracted. In this paper, we enhance the EPDE algorithm -- an evolutionary optimization-based discovery framework. In contrast to methods like S

Jose Soto Garcia, Natalia Chepiga

Quantum phase transitions are characterised by the universal scaling laws in the critical region surrounding the transitions. This universality is also manifested in the critical real-time dynamics through the quantum Kibble-Zurek mechanism. In recent experiments on a Rydberg atom quantum simulator, the Kibble-Zurek mechanism has been used to probe the natur

Yeonhong Park, Jake Hyun, Hojoon Kim, Jae W. Lee

Quantization of Large Language Models (LLMs) has recently gained popularity, particularly for on-device settings with limited hardware resources. While efficient, quantization inevitably degrades model quality, especially in aggressive low-bit settings such as 3-bit and 4-bit precision. In this paper, we propose DecDEC, an inference scheme that improves the

Linbo Shang, Zhichao Zhang

Vertex-frequency analysis, particularly the windowed graph Fourier transform (WGFT), is a significant challenge in graph signal processing. Tight frame theories is known for its low computational complexity in signal reconstruction, while fractional order methods shine at unveil more detailed structural characteristics of graph signals. In the graph fraction

Zhilin You, Zhenli Xu, Wei Cai

In this paper, a multi-scale Fourier neural operator (MscaleFNO) is proposed to reduce the spectral bias of the FNO in learning the mapping between highly oscillatory functions, with application to the nonlinear mapping between the coefficient of the Helmholtz equation and its solution. The MscaleFNO consists of a series of parallel normal FNOs with scaled i

Antonio M. García-García, Chang Liu, Lucas Sá, Jacobus J. M. Verbaarschot

The growth of information scrambling, captured by out-of-time-order correlation functions (OTOCs), is a central indicator of the nature of many-body quantum dynamics. Here, we compute analytically the complete time dependence of the OTOC for an integrable Sachdev-Ye-Kitaev (SYK) model, $N$ Majoranas with random two-body interactions of infinite range, couple

Rhoslyn Coles, Myfanwy E. Evans

Helices are the quintessential geometric motif of the microscale, from alpha-helices in proteins to double helices in DNA. Assembly of the helical geometry of biopolymers is a foundational step in a hierarchy of structure that eventually leads to biological activity. By simulating folding in a simplified setting we probe the role of the solvent in the collab

Mehran Hosseinzadeh Dizaj

This study delves into the effects of doping Spiro-OMeTAD, a widely employed hole transport material (HTM) in perovskite solar cells, with three distinct impurities: lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI), FK209, and tertbutylpyridine (tBP). The focus lies on their influence on critical photovoltaic parameters, including Fill Factor (FF), power

Lukas Trümper, Philipp Schaad, Berke Ates, Alexandru Calotoiu

The same computations are often expressed differently across software projects and programming languages. In particular, how computations involving loops are expressed varies due to the many possibilities to permute and compose loops. Since each variant may have unique performance properties, automatic approaches to loop scheduling must support many differen

Zhicheng Chen, Yifeng Ding

Let $n$-Medvedev's logic $\mathbf{ML}_n$ be the intuitionistic logic of Medvedev frames based on the non-empty subsets of a set of size $n$, which we call $n$-Medvedev frames. While these are tabular logics, after characterizing $n$-Medvedev frames using the property of having at least $n$ maximal points, we offer a uniform axiomatization of them through a G

Yijun Bei, Teng Ma, Dongxiang Zhang, Sai Wu

Discovering co-movement patterns from urban-scale video data sources has emerged as an attractive topic. This task aims to identify groups of objects that travel together along a common route, which offers effective support for government agencies in enhancing smart city management. However, the previous work has made a strong assumption on the accuracy of r

Yixun Kang, Ying Li

This paper investigates the extent to which China's economic growth and development influence poverty levels, focusing on the dichotomy between absolute and relative poverty. Leveraging data from sources like the World Bank, Statista, and Macrotrends, and employing economic frameworks such as the Lewis Model, Poverty Headcount Ratio, and Gini Coefficient, th

Lee Kennedy-Shaffer

The undergraduate curriculum in statistics and data science is undergoing changes to accommodate new methods, newly interested students, and the changing role of statistics in society. Because of this, it is more important than ever that students understand the role of study design and how to formulate meaningful scientific and statistical research questions

Christian Böhning, Hans-Christian Graf von Bothmer, David Hubbard

Suppose E_1, E_2 are elliptic curves (over the complex numbers) together with standard double coverings of the projective line identifying a point and its inverse on E_i. Bogomolov, Fu and Tschinkel have asked if the number of common images of torsion points on the elliptic curves under these double coverings is uniformly bounded in the case when the branch

Masahiro Kato

This study proposes a debiasing method for smooth nonparametric estimators. While machine learning techniques such as random forests and neural networks have demonstrated strong predictive performance, their theoretical properties remain relatively underexplored. In particular, many modern algorithms lack guarantees of pointwise and uniform risk convergence,

Dovile Juodelyte, Enzo Ferrante, Yucheng Lu, Prabhant Singh

Current transferability estimation methods designed for natural image datasets are often suboptimal in medical image classification. These methods primarily focus on estimating the suitability of pre-trained source model features for a target dataset, which can lead to unrealistic predictions, such as suggesting that the target dataset is the best source for

Guanglei Yang, Yongqiang Zhang, Wanlong Li, Yu Tang

Convolutional Neural Networks (CNNs) have significantly impacted various computer vision tasks, however, they inherently struggle to model long-range dependencies explicitly due to the localized nature of convolution operations. Although Transformers have addressed limitations in long-range dependencies for the spatial dimension, the temporal dimension remai

Seokho Ahn, Hyungjin Kim, Sungbok Shin, Young-Duk Seo

Precise measurements from sensors are crucial, but data is usually collected from low-cost, low-tech systems, which are often inaccurate. Thus, they require further calibrations. To that end, we first identify three requirements for effective calibration under practical low-tech sensor conditions. Based on the requirements, we develop a model called TESLA, T

Noah M. MacKay

We use effective field theory (EFT) to calculate the scattering amplitude of a LIGO-like graviton-scalar Compton interaction. We gauge the center-of-momentum energy $\sqrt{s}$ between one gravitational-wave (GW) graviton (one quantum of the coherent bulk of an astrophysical GW, with energy $E_g=\hbar\omega_\mathrm{GW}$) and a resting heavy target (a suspende

Debdas Ghosh, Ravi Raushan, Zai-Yun Peng, Jen-Chih Yao

This article presents nonlinear conjugate gradient methods for finding local weakly minimal points of set-valued optimization problems under a lower set less ordering relation. The set-valued objective function of the optimization problem under consideration is defined by finitely many continuously differentiable vector-valued functions. For such optimizatio

Roel Hulsman, Valentin Comte, Lorenzo Bertolini, Tobias Wiesenthal

Quantitative tools are increasingly appealing for decision support in healthcare, driven by the growing capabilities of advanced AI systems. However, understanding the predictive uncertainties surrounding a tool's output is crucial for decision-makers to ensure reliable and transparent decisions. In this paper, we present a case study on pulmonary nodule det

Hyucksung Kwon, Kyungmo Koo, Janghyeon Kim, Woongkyu Lee

The expansion of long-context Large Language Models (LLMs) creates significant memory system challenges. While Processing-in-Memory (PIM) is a promising accelerator, we identify that it suffers from critical inefficiencies when scaled to long contexts: severe channel underutilization, performance-limiting I/O bottlenecks, and massive memory waste from static

Manabu Machida

Albeit the past intensive research, the governing equation of anomalous diffusion which is observed for the transport of particles underground is still an open problem. In this paper, as a governing equation, the advection-diffusion equation with a time-fractional derivative term is derived from the radiative transport equation with an integral term for wait

Yi-Lun Du, Nan Su, Konrad Tywoniuk

By incorporating contributions from both the (chromo)electric scale $gT$ and (chromo)magnetic scale $g^2T$, we establish spectral sum rules of quarks for strongly coupled QCD that respect Fermi-Dirac statistics as required by quantum mechanics. In sharp contrast to QED and weakly coupled QCD whose spectral functions consist of discontinuous zero-dimensional

Andrzej Bedychaj, Jacek Tabor, Marek Śmieja

Deep conditional generative models are excellent tools for creating high-quality images and editing their attributes. However, training modern generative models from scratch is very expensive and requires large computational resources. In this paper, we introduce StyleAutoEncoder (StyleAE), a lightweight AutoEncoder module, which works as a plugin for pre-tr

Minhye Jeon, Seokho Ahn, Young-Duk Seo

The use of knowledge graphs in recommender systems has become one of the common approaches to addressing data sparsity and cold start problems. Recent advances in large language models (LLMs) offer new possibilities for processing side and context information within knowledge graphs. However, consistent integration across various systems remains challenging

Guanglei Yang, Rui Tian, Yongqiang Zhang, Zhun Zhong

The autonomous driving community is increasingly focused on addressing corner case problems, particularly those related to ensuring driving safety under adverse conditions (e.g., nighttime, fog, rain). To this end, the task of Adverse Condition Depth Estimation (ACDE) has gained significant attention. Previous approaches in ACDE have primarily relied on gene

Boran A. Kilic, Ozgur B. Akan

Molecular Communication (MC) leverages the power of diffusion to transmit molecules from a transmitter to a receiver. A wide variety of modulation techniques based on molecule concentration, type, and release time have been extensively studied in the literature. In this paper, we propose a novel modulation technique that encodes the information into the rela

Cheng-Yuan Lu, Xian-Hui Ge, Sang-Jin Sin

We investigate the fermionic properties of a dyonic Gubser-Rocha model in the context of gauge/gravity duality. This model incorporates both a magnetic field and momentum relaxation. We have derived this model's scaling exponent, revealing the influence of the magnetic field and momentum relaxation on low-energy physics. As the magnetic field strength and mo

Pedro Costa, Martim Ferreira, Lina Oliveira

We introduce a class of left ideals (and subalgebras) of nest algebras determined by totally ordered families of partial isometries on a complex Hilbert space $H$. Let $\mathcal{E}$ be a family of partial isometries that is totally ordered in the Halmos--McLaughlin ordering, and let $\mathcal{A}_{\mathcal{E}}$ be the subset of operators in $B(H)$ which, for

Marcos Oliveira, Leonie Neuhauser, Fariba Karimi

While homophily -- the tendency to link with similar others -- may nurture a sense of belonging and shared values, it can also hinder diversity and widen inequalities. Here, we unravel this trade-off analytically, revealing homophily traps for minority groups: scenarios where increased homophilic interaction among minorities negatively affects their structur

Jingbo Lin, Zhilu Zhang, Wenbo Li, Renjing Pei

Recently, considerable progress has been made in all-in-one image restoration. Generally, existing methods can be degradation-agnostic or degradation-aware. However, the former are limited in leveraging degradation-specific restoration, and the latter suffer from the inevitable error in degradation estimation. Consequently, the performance of existing method

Yaning Zhang, Qiufu Li, Zitong Yu, Linlin Shen

Face forgery detection (FFD) is devoted to detecting the authenticity of face images. Although current CNN-based works achieve outstanding performance in FFD, they are susceptible to capturing local forgery patterns generated by various manipulation methods. Though transformer-based detectors exhibit improvements in modeling global dependencies, they are not

Wooseok Han, Minki Kang, Changhun Kim, Eunho Yang

Speaker-adaptive Text-to-Speech (TTS) synthesis has attracted considerable attention due to its broad range of applications, such as personalized voice assistant services. While several approaches have been proposed, they often exhibit high sensitivity to either the quantity or the quality of target speech samples. To address these limitations, we introduce

Witold Wydmański, Ulvi Movsum-zada, Jacek Tabor, Marek Śmieja

Although deep learning models have had great success in natural language processing and computer vision, we do not observe comparable improvements in the case of tabular data, which is still the most common data type used in biological, industrial and financial applications. In particular, it is challenging to transfer large-scale pre-trained models to downs

Xinru Wen, Jinbo Wen, Ming Xiao, Jiawen Kang

Vehicular metaverses, blending traditional vehicular networks with metaverse technology, are expected to revolutionize fields such as autonomous driving. As virtual intelligent assistants in vehicular metaverses, Artificial Intelligence (AI) agents powered by large language models can create immersive 3D virtual spaces for passengers to enjoy on-broad vehicu

HongShuai Zhou, JinHao Zhang, BenFeng Bai, XiRan Mei

The stability and emissivity of the online calibration blackbody used in high-precision infrared remote sensing detectors in extreme environments are the primary limiting factors for their measurement accuracy. Due to the limitations of microstructure size effects, traditional calibration extended area blackbody cannot achieve an optimal balance between emis

Mohammed Abdellaoui, Nour-Eddine Abouelkhir, Abdallah Slaoui, Rachid Ahl Laamara

In quantum parameter estimation, the quantum Cram\'er-Rao bound (QCRB) sets a fundamental limit on the precision achievable with unbiased estimators. It relates the uncertainty in estimating a parameter to the inverse of the quantum Fisher information (QFI). Both QCRB and QFI are valuable tools for analyzing interferometric phase sensitivity. This paper comp

Xinlei Ge, Yang Li, Xing Zhang, Yukun Sun

As an emerging computing paradigm, mobile edge computing (MEC) provides processing capabilities at the network edge, aiming to reduce latency and improve user experience. Meanwhile, the advancement of containerization technology facilitates the deployment of microservice-based applications via edge node collaboration, ensuring highly efficient service delive

Xuan-Heng Zhang, Sheng-Qi Zhang, Cong-Feng Qiao

Motivated by the observation of the $J^P = 1^+$ resonance $X(2085)$ in the $p\bar{\Lambda}$ system by the BESIII collaboration, we studied the molecular states of hexaquarks $p\bar{\Lambda}$ and $p\bar{\Sigma}$ with baryon-antibaryon structures within the framework of the QCD sum rules. Non-perturbative contributions up to dimension 13 were considered in our

Mo Zhou, F. A. Cárdenas-López, Sugny Dominique, Xi Chen

We propose a quantum optimal control framework based on the Pontryagin Maximum Principle to design energy- and time-efficient pulses for open quantum systems. By formulating the Langevin equation of a dissipative LC circuit as a linear control problem, we derive optimized pulses with exponential scaling in energy cost, outperforming conventional shortcut-to-

Kaijun Deng, Dezhi Zheng, Jindong Xie, Jinbao Wang

Accurately synthesizing talking face videos and capturing fine facial features for individuals with long hair presents a significant challenge. To tackle these challenges in existing methods, we propose a decomposed per-embedding Gaussian fields (DEGSTalk), a 3D Gaussian Splatting (3DGS)-based talking face synthesis method for generating realistic talking fa

Kazuya Fujimoto, Tomohiro Sasamoto

We theoretically study quantum spin transport in a one-dimensional folded XXZ model with an alternating domain-wall initial state via the Bethe ansatz technique, exactly demonstrating that a probability distribution of finding a left-most up-spin with an appropriate scaling variable converges to the Tracy-Widom distribution for the Gaussian unitary ensemble

Runwu Shi, Katsutoshi Itoyama, Kazuhiro Nakadai

This paper addresses the extraction of the bird vocalization embedding from the whole song level using disentangled representation learning (DRL). Bird vocalization embeddings are necessary for large-scale bioacoustic tasks, and self-supervised methods such as Variational Autoencoder (VAE) have shown their performance in extracting such low-dimensional embed

Wei Zhou, Mohsen Mesgar, Annemarie Friedrich, Heike Adel

Complex table question answering (TQA) aims to answer questions that require complex reasoning, such as multi-step or multi-category reasoning, over data represented in tabular form. Previous approaches demonstrated notable performance by leveraging either closed-source large language models (LLMs) or fine-tuned open-weight LLMs. However, fine-tuning LLMs re

Runwu Shi, Benjamin Yen, Kazuhiro Nakadai

This paper aims to achieve single-channel target speech extraction (TSE) in enclosures by solely utilizing distance information. This is the first work that utilizes only distance cues without using speaker physiological information for single-channel TSE. Inspired by recent single-channel Distance-based separation and extraction methods, we introduce a nove

Vuong Bui

Klarner and Rivest showed that the growth of the number of polyominoes, also known as Klarner's constant, is at most $2+2\sqrt{2}<4.83$ by viewing polyominoes as a sequence of twigs with appropriate weights given to each twig and studying the corresponding multivariate generating function. In this short note, we give a simpler proof by a recurrence on an upp

Sheng Lyu, Chenshu Wu

Passive human speed estimation plays a critical role in acoustic sensing. Despite extensive study, existing systems, however, suffer from various limitations: First, the channel measurement rate proves inadequate to estimate high moving speeds. Second, previous acoustic speed estimation exploits Doppler Frequency Shifts (DFS) created by moving targets and re

Xun Qian, Li-Zhi Liao, Jie Sun

Interior point methods for solving linearly constrained convex programming involve a variable projection matrix at each iteration to deal with the linear constraints. This matrix often becomes ill-conditioned near the boundary of the feasible region that results in wrong search directions and extra computational cost. A matrix-free interior point augmented L

Igor G. Korepanov

A phenomenon of "algebraic self-similarity" on 3d cubic lattice, providing what can be called an algebraic analogue of Kadanoff--Wilson theory, is shown to possess a 4d version as well. Namely, if there is a $4\times 4$ matrix $A$ whose entries are indeterminates over the field $\mathbb F_2$, then the $2\times 2\times 2\times 2$ block made of sixteen copies

K. Gas, J. -Y. Yoon, Y. Sato, H. Kubota

Antiferromagnets with broken time-reversal symmetry, such as Mn3Sn, have emerged as promising platforms for exploring topological and correlated electron physics. Mn3Sn is known to show two magnetic phase transitions: a non-collinear inverse triangular antiferromagnetic (IT-AFM) spin configuration is formed below its Neel temperature, whereas at T1 that usua

Mohamed R. Ibrahim, Terry Lyons

Air pollution in cities, especially NO\textsubscript{2}, is linked to numerous health problems, ranging from mortality to mental health challenges and attention deficits in children. While cities globally have initiated policies to curtail emissions, real-time monitoring remains challenging due to limited environmental sensors and their inconsistent distribu

Yijia Xiao, Edward Sun, Di Luo, Wei Wang

Significant progress has been made in automated problem-solving using societies of agents powered by large language models (LLMs). In finance, efforts have largely focused on single-agent systems handling specific tasks or multi-agent frameworks independently gathering data. However, the multi-agent systems' potential to replicate real-world trading firms' c

Konstantin Bogdanov

The goal of this note is to generalize Thurston's Topological Characterization of Rational Functions to the setting when both the covering degree and the set of marked points are infinite. A relevant class of branched coverings are transcendental entire functions with finitely many singular values whose orbits escape to (or, more generally, accumulate ``near

Zeyu Li, Yulei Han, Zhenhua Qiao

Recently, the quantum anomalous Hall effect (QAHE) has been theoretically proposed in compensated antiferromagnetic systems by using the magnetic topological insulator model [see arXiv:2404.13305 (2024)]. However, the related and systematic study based on a realistic material system is still limited. As the only experimentally realized antiferromagnetic topo

Heerak Sharma, Dmitry Shirokov

Commutative analogues of Clifford algebras are algebras defined in the same way as Clifford algebras except that their generators commute with each other, in contrast to Clifford algebras in which the generators anticommute. In this paper, we solve the problem of finding multiplicative inverses in commutative analogues of Clifford algebras by introducing a m

Luis Guajardo, Julio Oliva

In this work, we construct novel asymptotically locally AdS$_5$ black hole solutions of Einstein-Gauss-Bonnet theory at the Chern-Simons point, supported by a scalar field that generates primary hair. The strength of the scalar field is governed by an independent integration constant; when this constant vanishes, the spacetime reduces to a black hole geometr

Martin O. Canullan-Pascual, German Lugones, Milva G. Orsaria, Ignacio F. Ranea-Sandoval

We investigate the radial stability of neutron stars under conditions where their composition may or may not remain in chemical equilibrium during oscillations. Using different equations of state that include nucleons, hyperons, and/or $\Delta$ resonances, we compute stellar configurations and examine their fundamental mode frequencies in two limiting scenar

Thi-Hoa Nguyen, Bruno A. Roccia, Dominik Schillinger, Cristian C. Gebhardt

In this work, we compare the nodal and isogeometric spatial discretization schemes for the nonlinear formulation of shear- and torsion-free rods introduced in [1]. We investigate the resulting discrete solution space, the accuracy, and the computational cost of these spatial discretization schemes. To fulfill the required C1 continuity of the rod formulation

Thang Xuan Duong, Roger Andrew Sauer

This work presents a shear elastoplasticity model for textile fabrics within the theoretical framework of anisotropic Kirchhoff-Love shells with bending of embedded fibers proposed by Duong et al. (2023). The plasticity model aims at capturing the rotational inter-ply frictional sliding between fiber families in textile composites undergoing large deformatio

Minjun J. Choi

Various methods for leveraging turbulent fluctuation measurements from fusion plasma experiments are introduced, along with selected application examples. These can be categorized into spectral methods, statistical methods, and physics informed neural network based methods, and they are most effective for two-dimensional turbulence measurements, which are no

Zhengtian Li, Zeyu Li, Zhenhua Qiao

We theoretically demonstrate that Chern number tunable quantum anomalous Hall effect (QAHE) and second-order topological insulators can be induced in the two-dimensional $\mathbb{Z}_2$ topological insulator (TI), i.e., Kane-Mele model, by applying $d$-wave altermagnetism. When the N\'eel vector of altermagentism lies in the $x-y$ plane, the $\mathbb{Z}_2$ TI

Jin Matsuda, Hikaru Watanabe, Ryotaro Arita

Altermagnets exhibit nonrelativistic spin splitting due to the breaking of time-reversal symmetry and have been garnering significant attention as promising materials for spintronic applications. In contrast, conventional antiferromagnets without spin splitting seem not to have any symmetry breaking and have drawn less attention. However, we show that conven

Zhaopeng Feng, Jiayuan Su, Jiamei Zheng, Jiahan Ren

Recent advancements in large language models (LLMs) have given rise to the LLM-as-a-judge paradigm, showcasing their potential to deliver human-like judgments. However, in the field of machine translation (MT) evaluation, current LLM-as-a-judge methods fall short of learned automatic metrics. In this paper, we propose Multidimensional Multi-Agent Debate (M-M

Yuan Liu, Ravishankar Ramanathan

Semi-device-independent (SDI) randomness generation protocols based on Kochen-Specker contextuality offer the attractive features of compact devices, high rates, and ease of experimental implementation over fully device-independent (DI) protocols. Here, we investigate this paradigm and derive four results to improve the state-of-art. Firstly, we introduce a

Hongjie Dong, Hyunwoo Kwon

We establish the spatial differentiability of weak solutions to nonstationary Stokes equations in divergence form with variable viscosity coefficients having $L_2$-Dini mean oscillations. As a corollary, we derive local spatial Schauder estimates for such equations if the viscosity coefficient belongs to $C^\alpha_x$. Similar results also hold for strong sol

Matthias Langer, Jakob Reiffenstein, Harald Woracek

In this paper we consider two-dimensional canonical systems with discrete spectrum and study their eigenvalue densities. We develop a formula that determines the Stieltjes transform of the eigenvalue counting function up to universal multiplicative constants. An explicit criterion is given for the resolvents of the model operator to belong to a Schatten-von

Kaitong Sun, Si Wu, Junchao Xia, Yinghao Zhu

Graphene stands as a promising material with vast potential across energy storage, electronics, etc. Here, we present a novel mechanical approach utilizing ultrasonic high-energy intercalation exfoliation to extract monolayer graphene from graphite, offering a simple yet efficient alternative to conventional methods. Through a comprehensive series of charact

T. Takebe, A. Zabrodin

We give a detailed account of the N -component Toda lattice hierarchy. This hierarchy is an extended version of the one introduced by Ueno and Takasaki. Our version contains N discrete variables rather than one. We start from the Lax formalism, deduce the bilinear relation for the wave functions from it and then, based on the latter, prove existence of the t

Sujit K. Ghosh, Usha Ananthakumar, Praveen D. Chougale, Adithya B. Somaraj

Malaria remains a significant public health challenge in many regions, necessitating robust predictive models to aid in its management and prevention. This study focuses on developing and evaluating time series models for forecasting malaria cases across eight Indian states: Jharkhand, Chhattisgarh, Maharashtra, Meghalaya, Mizoram, Odisha, Tripura, and Uttar

Dmitrii Taletskii

The Gamma-Theta Conjecture states that if the domination number of a graph is equal to its eternal domination number, then it is also equal to its clique covering number. This conjecture is known to be true for several graph classes, such as outerplanar graphs, subcubic graphs and $C_k$-free graphs, where $k \in \{3,4\}$. In this paper, we prove the Conjectu

Sergiu Klainerman, Dawei Shen, Jingbo Wan

Kerr stability for small angular momentum has been proved in the series of works by Klainerman-Szeftel, Giorgi-Klainerman-Szeftel and Shen. Some of the most basic conclusions of the result, concerning various physical quantities on the future null infinity are derived in the work of Klainerman-Szeftel. Further important conclusions were later derived in An-H

Francesco Pace, Alberto Rozas-Fernández, Özgen Tunç Türker

We present and examine a kinetically coupled tachyon dark energy model, where a tachyon scalar field interacts with the matter sector. More specifically, we deduce this cosmological setting from a generalised interacting dark energy model that allows for the kinetic term of the scalar field to couple to the matter species a priori in the action. A thorough d

Shavika Rastogi, Nik Dennler, Michael Schmuker, André van Schaik

Natural odor environments present turbulent and dynamic conditions, causing chemical signals to fluctuate in space, time, and intensity. While many species have evolved highly adaptive behavioral responses to such variability, the emerging field of neuromorphic olfaction continues to grapple with the challenge of efficiently sampling and identifying odors in

Kalin Kopanov, Velizar Varbanov, Tatiana Atanasova

The integration of social media and artificial intelligence (AI) into disaster management, particularly for earthquake response, represents a profound evolution in emergency management practices. In the digital age, real-time information sharing has reached unprecedented levels, with social media platforms emerging as crucial communication channels during cr

Benedikt Valentin Meylahn

We study interpersonal trust by means of the all-or-nothing public goods game between agents on a network. The agents are endowed with the simple yet adaptive learning rule, exponential moving average, by which they estimate the behavior of their neighbors in the network. Theoretically we show that in the long-time limit this multi-agent reinforcement learni

Filip Nikolovski, Irena Stojkovska, Katerina Hadzi-Velkova Saneva, Zoran Hadzi-Velkov

Regularization is a widely recognized technique in mathematical optimization. It can be used to smooth out objective functions, refine the feasible solution set, or prevent overfitting in machine learning models. Due to its simplicity and robustness, the gradient descent (GD) method is one of the primary methods used for numerical optimization of differentia

Tuomas Hakoniemi, Nutan Limaye, Iddo Tzameret

Strong algebraic proof systems such as IPS (Ideal Proof System; Grochow-Pitassi [GP18]) offer a general model for deriving polynomials in an ideal and refuting unsatisfiable propositional formulas, subsuming most standard propositional proof systems. A major approach for lower bounding the size of IPS refutations is the Functional Lower Bound Method (Forbes,

Jacek Miekisz, Javad Mohamadichamgavi

We construct and analyze structured replicator dynamics of the Snowdrift game. In our model, the offspring is put in juvenile compartments and then mature and join adult compartments with strategy-dependent rates. This is augmented by death rates and hence the population size is bounded. In the corresponding birth-death Markov jump process, rates of leaving

Aashi Shrinate, Twinkle Tripathy

In this work, we consider a strongly connected group of individuals involved in decision-making. The opinions of the individuals evolve using the Friedkin-Johnsen (FJ) model. We consider that there are two competing `influencers' (stubborn agents) vying for control over the final opinion of the group. We investigate the impact of modifying the network intera

Simone Baldassarri, Alessandra Cipriani

The present overview and gentle introduction to Grassmannian calculus and some of its applications to probability collects the notes of a mini-course given by the authors at the Brazilian School of Probability, August 5-9, 2024, in Salvador, Bahia, Brazil. The content is by no means comprehensive, and is a personal summary and interpretation of results and a

Xi Yang, Pai Peng, Wulin Xie, Xiaohuan Lu

Few-shot image classification remains a critical challenge in the field of computer vision, particularly in data-scarce environments. Existing methods typically rely on pre-trained visual-language models, such as CLIP. However, due to the modality gap, which is the inconsistent distribution of image and text features in the joint embedding space, directly us

Zening Yan

We study the shadow of five-dimensional black strings immersed in dark matter environment. We show the influence of the momentum characteristic parameter $\widetilde{P_{y}}$ of the extra compact dimension on the shadow radius, and we provide the constraint range $0~\leq~\widetilde{P_{y}}~\lesssim~0.171215$ in the static Schwarzschild black string solution ba

S. Massabeau, O. Paull, A. Pezo, F. Miljevic

Spintronic Terahertz emitters, based on optically triggered spin-to-charge interconversion processes, have recently emerged as novel route towards compact and efficient THz sources. Yet, the next challenge for further technologically-relevant devices remains to modulate the emission, with low-energy consumption operation. To this aim, ferroelectric materials

Sergey V. Astashkin, Konstantin V. Lykov

We prove that both multiple Rademacher system and Rademacher chaos possess the property of random unconditional convergence in the space $L_\infty$. This fact combined with some intimate connections between $L_\infty$-norms of linear combinations of elements of these systems and some special norms of matrices of their coefficients allows us to establish shar

Micol Bassanini, Simone Deparis, Paolo Ricci

In wave propagation problems, finite difference methods implemented on staggered grids are commonly used to avoid checkerboard patterns and to improve accuracy in the approximation of short-wavelength components of the solutions. In this study, we develop a mimetic finite difference (MFD) method on staggered grids for transport operators with divergence-free

Jiedong Zhuang, Lu Lu, Ming Dai, Rui Hu

Multimodal large language models (MLLMs) enhance their perceptual capabilities by integrating visual and textual information. However, processing the massive number of visual tokens incurs a significant computational cost. Existing analysis of the MLLM attention mechanisms remains shallow, leading to coarse-grain token pruning strategies that fail to effecti

Wenkun He, Yun Liu, Ruitao Liu, Li Yi

Synthesizing realistic human-object interaction motions is a critical problem in VR/AR and human animation. Unlike the commonly studied scenarios involving a single human or hand interacting with one object, we address a more generic multi-body setting with arbitrary numbers of humans, hands, and objects. This complexity introduces significant challenges in

Naoki Kimura, Tomoya Nakamura

A Koszul-Vinberg manifold is a generalization of a Hessian manifold, and their relation is similar to the relation between Poisson manifolds and symplectic manifolds. Koszul-Vinberg structures and Poisson structures on manifolds extend to the structures on algebroids. A Koszul-Vinberg structure on a left-symmetric algebroid is regarded as a symmetric analogu

Anji Dong, Nicolas Robles, Alexandru Zaharescu, Dirk Zeindler

Let $\mathfrak{p}_{\mathbb{P}_r}(n)$ denote the number of partitions of $n$ into $r$-full primes. We use the Hardy-Littlewood circle method to find the asymptotic of $\mathfrak{p}_{\mathbb{P}_r}(n)$ as $n \to \infty$. This extends previous results in the literature of partitions into primes. We also show an analogue result involving convolutions of von Mango

Anji Dong, Nicolas Robles, Alexandru Zaharescu, Dirk Zeindler

We examine exponential sums of the form $\sum_{n \le X} w(n) e^{2\pi i\alpha n^k}$, for $k=1,2$, where $\alpha$ satisfies a generalized Diophantine approximation and where $w$ are different arithmetic functions that might be multiplicative, additive, or neither. A strategy is shown on how to bound these sums for a wide class of functions $w$ belonging within

Shuyao Jiang, Ruiying Zeng, Yangfan Zhou, Michael R. Lyu

WebAssembly (Wasm) is a binary instruction format designed as a portable compilation target, which has been widely used on both the web and server sides in recent years. As high performance is a critical design goal of Wasm, it is essential to conduct performance testing for Wasm runtimes. However, existing research on Wasm runtime performance testing still

Alessandro Fazzari, Maxim Gerspach

We prove precise conditional estimates for the third moment of the logarithm of the Riemann zeta function, refining what is implied by the Selberg central limit theorem, both for the real and imaginary parts. These estimates match predictions made in work of Keating and Snaith. We require the Riemann Hypothesis, a conjecture for the triple correlation of Rie

Rongkun Xue, Jing Yang, Yuyang Jiang, Yiming Feng

Existing local dynamic route planning algorithms, when directly applied to terrain following/terrain avoidance, or dynamic obstacle avoidance for large and medium-sized fixed-wing aircraft, fail to simultaneously meet the requirements of real-time performance, long-distance planning, and the dynamic constraints of large and medium-sized aircraft. To deal wit

Gulsemay Yigit, Wakil Sarfaraz, Raquel Barreira, Anotida Madzvamuse

In this work, the influence of geometry and domain size on spatiotemporal pattern formation is investigated to establish parameter spaces for a cross-diffusive reaction-diffusion model on an annulus. By applying linear stability theory, we derive conditions which can give rise to Turing, Hopf and transcritical types of diffusion-driven instabilities. We expl

Ziyu Dong, Teng Ma, Chengjie Yang, Zizheng Zhou

We present a more efficient method for constructing the complete EFT operator basis for particles of any mass and spin, based on on-shell method and Young tableaux. By classifying the amplitude bases according to the polarization configurations of massive particles and using their high-energy limit, our approach can construct EFT basis in a straightforward w

Mina Hemmati Tirabadi, Ali Iranmanesh

In this paper, we prove that if G is a finite simple group with the same-size conjugacy class set U(G) = U(PSL(2, 11)), then G is isomorphic to PSL(2, 11).

Massimo Papa

The effects of the many-body correlations with respect the MF description characterizing the Constrained Molecular Dynamics are discussed in the case of finite and zero range effective microscopic interactions. In particular, for the system $^{64}Ni+^{48}Ca$ fusion-fission cross-sections, IMF production and transversal flow have been evaluated in the framewo