December 2024 arXiv papers — page 176

Hendrik Weichel, Aleksandr Zinovev, Heikki Haario, Martin Simon

We present a novel Bayesian framework for quantifying uncertainty in portfolio temperature alignment models, leveraging the X-Degree Compatibility (XDC) approach with the scientifically validated Finite Amplitude Impulse Response (FaIR) climate model. This framework significantly advances the widely adopted linear approaches that use the Transient Climate Re

K. Scherer, K. Herbst, N. E. Engelbrecht, S. E. S. Ferreira

The cosmic ray (CR) flux, as well as the hydrogen flux into the atmosphere of an exoplanet, can change the composition of the atmosphere. Here, we present the CR and hydrogen flux on top of the atmosphere. To do so, we have to study the 3D multifluid MHD structure of astrospheres. We discuss the shock structure of the stellar wind of LHS 1140 using four diff

Noam Soker

I examine images of 50 planetary nebulae (PNe) with observable post-common envelope evolution (CEE) binary central stars and find that jets are about 40 percent more common than dense equatorial outflows. Because, in some cases, energetic jets can compress an equatorial outflow and because fast jets might disperse early in the PN evolution and avoid detectio

Tatsuya Gima, Yuni Iwamasa, Yasuaki Kobayashi, Kazuhiro Kurita

In many decision-making processes, one may prefer multiple solutions to a single solution, which allows us to choose an appropriate solution from the set of promising solutions that are found by algorithms. Given this, finding a set of \emph{diverse} solutions plays an indispensable role in enhancing human decision-making. In this paper, we investigate the p

Tadahisa Funaki, Claudio Landim, Sunder Sethuraman

In this article, we find a scaling limit of the space-time mass fluctuation field of Glauber + Kawasaki particle dynamics around its hydrodynamic mean curvature interface limit. Here, the Glauber rates are scaled by $K=K_N$, the Kawasaki rates by $N^2$ and space by $1/N$. We start the process so that the interface $\Gamma_t$ formed is stationary that is, $\G

Filipo Sharevski, Jennifer Vander Loop, Bill Evans, Alexander Ponticello

This paper reports on a study exploring how two groups of individuals, legally blind (n=36) and sighted ones (n=36), react to aural telephone scam warnings in naturalistic settings. As spoofing a CallerID is trivial, communicating the context of an incoming call instead offers a better possibility to warn a receiver about a potential scam. Usually, such warn

Miklos Rasonyi

We present a Fourier-analytic method for estimating convergence rates in total variation distance in terms of various metrics related to weak convergence. Applications are provided in the areas of Malliavin calculus, normal approximation and stochastic dynamical systems with memory.

Tim S. Lyon

Propositional dynamic logic (PDL) is an important modal logic used to specify and reason about the behavior of software. A challenging problem in the context of PDL is solving fixed-point equations, i.e., formulae of the form $x \equiv \phi(x)$ such that $x$ is a propositional variable and $\phi(x)$ is a formula containing $x$. A solution to such an equation

Tuğçe Gökdemir, Jakub Rydzewski

In molecular dynamics (MD) simulations, transitions between states are often rare events due to energy barriers that exceed the thermal temperature. Because of their infrequent occurrence and the huge number of degrees of freedom in molecular systems, understanding the physical properties that drive rare events is immensely difficult. A common approach to th

Xinyuan Zhou, Ziqiang Wang, Hua Chen

The Dirac fermion with linear dispersion in the kagom\'e lattice governs the low-energy physics of different valleys at two inequivalent corners of hexagonal Brillouin zone. The effective Hamiltonian based on the cyclic permutation symmetry of sublattices is constructed to show that the topology of Dirac fermions at these two valleys is characterized by oppo

Zhi-Hao Huang, Kou-Han Ma, Bao-Zong Wang, W. Vincent Liu

Spin and orbital are two basic degrees of freedom that play significant roles in exploring exotic quantum phases in optical lattices with synthetic spin-orbit coupling (SOC) and high orbital bands, respectively. Here, we combine these two crucial ingredients for the first time by proposing a completely new orbital optical Raman lattice scheme to explore exot

Vlad C. Andrei, Alexandru P. Drăguţoiu, Gabriel Béna, Mahmoud Akl

This paper explores the potential of conversion-based neuromorphic algorithms for highly accurate and energy-efficient single-snapshot multidimensional harmonic retrieval (MHR). By casting the MHR problem as a sparse recovery problem, we devise the currently proposed, deep-unrolling-based Structured Learned Iterative Shrinkage and Thresholding (S-LISTA) algo

Ishfaq Ahmad Rather, Kauan D. Marquez, Betânia C. Backes, Grigoris Panotopoulos

This study investigates the radial oscillations of hybrid neutron stars, characterized by a composition of hadronic external layers and a quark matter core. Utilizing a density-dependent relativistic mean-field model that incorporates hyperons and baryons for describing hadronic matter, and a density-dependent quark model for quark matter, we analyze the ten

Shangqing Wang, Christopher Lehmann, Rico Radeke, Frank H. P. Fitzek

This paper examines the role of 5G communication in the Mobilities for EU project, a collaborative initiative involving 29 partners and 11 pilots aimed at revolutionizing urban mobility through electrification, automation, and connectivity. Focusing on Dresden as a Lead City, we explore the integration of 27 innovative solutions, including autonomous freight

Shangqing Wang, Juan A. Cabrera, Frank H. P. Fitzek

This paper explores the potential of Vehicle-to-Everything (V2X) technology to enhance grid stability and support sustainable mobility in Dresden's Ostra district. By enabling electric vehicles to serve as mobile energy storage units, V2X offers grid stabilization and new business opportunities. We examine pilot projects and business use cases, focusing on B

Konstantinos Kavvadias, Jason Miller

We study the relationship between certain SLE$_\kappa(\rho)$ processes, which are variants of the Schramm-Loewner evolution with parameter $\kappa$ in which one keeps track of an extra marked point, and Liouville quantum gravity (LQG). These processes are defined whenever $\rho > -2-\kappa/2$ and in this work we will focus on the light cone regime, meaning t

Mohsen Khalili, Yicheng Wang, Stephan Winnerl, Clara J. Saraceno

We report high average power THz emission from a GaAs-based large-area photoconductive emitter, excited by a commercial Yb-laser amplifier without any compression schemes, doubled to the green. The LAE is pumped at 11.4 W of green average power (515 nm) and 310 fs pulse duration at 400-kHz repetition rate. We obtain a maximum THz power of 6.7 mW with a spect

Lingfeng Ming, Bo Zeng, Chenyang Lyu, Tianqi Shi

Large Language Models (LLMs) have achieved remarkable progress in recent years; however, their excellent performance is still largely limited to major world languages, primarily English. Many LLMs continue to face challenges with multilingual tasks, especially when it comes to low-resource languages. To address this issue, we introduced Marco-LLM: Massive mu

Yinyu Wu, Xuhui Zhang, Yingchao Jiao, Jinke Ren

Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and better energy efficiency. However, the resource competition among users will lead to uneven allocation, increased latency, and lower throughput. Fortunately, the rate-splitting multip

Yang-hao Chan, Jonah B. Haber, Mit H. Naik, Steven G. Louie

Understanding exciton thermalization is critical for optimizing optoelectronic and photocatalytic processes in many materials. However, it is hard to access the dynamics of such processes experimentally, especially on systems such as monolayer transition metal dichalcogenides, where various low-energy excitations pathways can compete for exciton thermalizati

C. C. Hsu, P. R. Raickwade, K. C. Sivakumar

Let $T\colon M_n\rightarrow M_n$ preserve Hadamard circulant majorization. In this note, we show that this property is inherited by the three most popular generalized inverses, viz. the Moore-Penrose inverse, the group inverse and the Drazin inverse.

Sejong Yang, Seoung Wug Oh, Yang Zhou, Seon Joo Kim

We introduce a novel approach for high-resolution talking head generation from a single image and audio input. Prior methods using explicit face models, like 3D morphable models (3DMM) and facial landmarks, often fall short in generating high-fidelity videos due to their lack of appearance-aware motion representation. While generative approaches such as vide

Yuji Kunisada, Ryotaro Sano, Norihito Sakaguchi

It has been reported that the {\alpha}-Al2O3, a promising tritium permeation barrier material for a fusion reactor, can be grown at low temperatures on the {\alpha}-Cr2O3 template, and that {\alpha}-Al2O3/{\alpha}-Cr2O3 composite films have more efficiently suppress the hydrogen isotope permeation than the single {\alpha}-Al2O3 film. In this study, we invest

Guangyi Hong, Zhi-An Wang

This paper establishes the convergence of boundary-layer solutions of the consumption type Keller-Segel model with non-degenerate initial data subject to physical boundary conditions, which is a sequel of \cite{Corrillo-Hong-Wang-vanishing} on the case of degenerate initial data. Specifically, we justify that the solution with positive chemical diffusion rat

Shrey Aryan, Lauro Silini

We study the isoperimetric problem with a potential energy $g$ in $\mathbb{R}^n$ weighted by a radial density $f$ and analyze the geometric properties of minimizers. Notably, we construct two counterexamples demonstrating that, in contrast to the classical isoperimetric case $g = 0$, the condition $\ln(f)'' + g' \geq 0$ does not generally guarantee the globa

Tomoaki Abuku, Masanori Fukui, Shin-ichi Katayama, Koki Suetsugu

In combinatorial game theory, there are two famous winning conventions, normal play and mis\`ere play. Under normal play convention, the winner is the player who moves last and under mis\`ere play convention, the loser is the player who moves last. The difference makes these conventions completely different, and usually, games under mis\`ere play convention

Ozer Can Devecioglu, Serkan Kiranyaz, Turker Ince, Moncef Gabbouj

The exploration of underwater environments is essential for applications such as biological research, archaeology, and infrastructure maintenanceHowever, underwater imaging is challenging due to the waters unique properties, including scattering, absorption, color distortion, and reduced visibility. To address such visual degradations, a variety of approache

Andreas Costa, Jaroslav Fabian

Spin-orbit coupling (SOC) emerging at the interfaces of superconducting magnetic tunnel junctions is at the heart of multiple unprecedented physical phenomena, covering triplet proximity effects induced by unconventional (spin-flip) Andreev reflections, giant transport magnetoanisotropies, sizable tunneling anomalous Hall effects, and electrically controlled

Yongjie Xu, Guangke Chen, Fu Song, Yuqi Chen

Backdoor attacks embed hidden associations between triggers and targets in deep neural networks (DNNs), causing them to predict the target when a trigger is present while maintaining normal behavior otherwise. Physical backdoor attacks, which use physical objects as triggers, are feasible but lack remote control, temporal stealthiness, flexibility, and mobil

Lei Chai, Hailong Sun, Jing Zhang

Crowdsourcing provides a flexible approach for leveraging human intelligence to solve large-scale problems, gaining widespread acceptance in domains like intelligent information processing, social decision-making, and crowd ideation. However, the uncertainty of participants significantly compromises the answer quality, sparking substantial research interest.

Juan Fernández-Gracia, Jorge P. Rodríguez, Lauren R. Peel, Konstantin Klemm

Social interactions are fundamental in animal groups, including humans, and can take various forms, such as competition, cooperation, or kinship. Understanding these interactions in marine environments has been historically challenging due to data collection difficulties. However, advancements in acoustic telemetry now enable remote analysis of such behavior

Edoardo Catenaro, Giulio Panzani, Davide Sette, Sergio M. Savaresi

This brief addresses the gearshifting problem for Semi-Automated Manual Transmissions (S-AMT) in powered two-wheelers, a powertrain setup that allows fast and smooth gear shifts with minimal modifications to the traditional manual powertrain layout. We show that with a proper synchronization between the electronic clutch and engine torque, excellent gearshif

I. D. Karachentsev, A. A. Popova

We consider the kinematic distances to nearby galaxies obtained by the Numerical Action Method (NAM) based on the Cosmic-flow-3 survey data. NAM distances are compared with 418 high-precision distances measured by the Tip of the Red Giant Branch (TRGB) method using the Hubble Space Telescope. We estimated the average difference <D_NAM - D_TRGB> = -0.30 +- 0.

Changcheng Li, Xiangyu Wang, Qiuju Chen, Xiren Zhou

Large language models (LLMs) have shown limitations in tasks requiring complex logical reasoning and multi-step problem-solving. To address these challenges, researchers have employed carefully designed prompts and flowcharts, simulating human cognitive processes to enhance LLM performance, such as the Chain of Thought approach. In this paper, we introduce M

Lars Schmarje, Kaspar Sakman, Reinhard Koch, Dan Zhang

Autonomous driving (AD) operates in open-world scenarios, where encountering unknown objects is inevitable. However, standard object detectors trained on a limited number of base classes tend to ignore any unknown objects, posing potential risks on the road. To address this, it is important to learn a generic rather than a class specific objectness from obje

Giuseppe Milazzo, Simon Lemerle, Giorgio Grioli, Antonio Bicchi

Intuitively, prostheses with user-controllable stiffness could mimic the intrinsic behavior of the human musculoskeletal system, promoting safe and natural interactions and task adaptability in real-world scenarios. However, prosthetic design often disregards compliance because of the additional complexity, weight, and needed control channels. This paper foc

Nikolaos Dimitrakopoulos

We discuss the results for the four-top quark production process at the LHC at NLO accuracy in perturbative QCD for the $3\ell$ decay channel. The QCD corrections are applied in both the production and the decay stages of the four top quarks by employing the narrow-width approximation. The spin correlations are therefore preserved at NLO accuracy in QCD with

Shanqi Liu, Xin Liu

This paper studies online convex optimization with unknown linear budget constraints, where only the gradient information of the objective and the bandit feedback of constraint functions are observed. We propose a safe and efficient Lyapunov-optimization algorithm (SELO) that can achieve an $O(\sqrt{T})$ regret and zero cumulative constraint violation. The r

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

Advanced Driver Assistance Systems (ADAS) are designed with the main purpose of increasing the safety and comfort of vehicle occupants. Most of current computer vision-based ADAS perform detection and tracking tasks quite successfully under regular conditions, but are not completely reliable, particularly under adverse weather and changing lighting condition

Feijoo Colomine Durán, Carlos Cotta, Antonio J. Fernández-Leiva

We consider the issue of intensification/diversification balance in the context of a memetic algorithm for the multiobjective optimization of investment portfolios with cardinality constraints. We approach this issue in this work by considering the selective application of knowledge-augmented operators (local search and a memory of elite solutions) based on

Vakada Naveen, Arvind Krishna Sridhar, Yinyi Guo, Erik Visser

This paper presents a comprehensive chatbot system designed to handle a wide range of audio-related queries by integrating multiple specialized audio processing models. The proposed system uses an intent classifier, trained on a diverse audio query dataset, to route queries about audio content to expert models such as Automatic Speech Recognition (ASR), Spea

Omer Sen, Christoph Pohl, Immanuel Hacker, Markus Stroot

The transition to smart grids has increased the vulnerability of electrical power systems to advanced cyber threats. To safeguard these systems, comprehensive security measures-including preventive, detective, and reactive strategies-are necessary. As part of the critical infrastructure, securing these systems is a major research focus, particularly against

Jie Su, Wei Wu, Denis Patterson, Simon Asher Levin

Spatial patterns are widely observed in numerous nonequilibrium natural systems, often undergoing complex transitions and bifurcations, thereby exhibiting significant importance in many physical and biological systems such as embryonic development, ecosystem desertification, and turbulence. However, how spatial pattern formation emerges and how the spatial p

Lara Bohnenblust, Serena Giardino, Lavinia Heisenberg, Nadine Nussbaumer

It is notoriously difficult to construct a stable non-singular bouncing cosmology that avoids all possible instabilities throughout the entire evolution of the universe. In this work, we explore whether a non-singular bounce driven by a specific class of modifications of General Relativity, the vector-tensor generalized Proca theories, can be constructed wit

Bojun Zhang

Gesture tracking technology provides users with a hands free interactive experience without the need to hold or touch devices. However, current gesture tracking research has primarily focused on tracking accuracy while neglecting issues of user privacy protection and security. This study aims to develop a gesture tracking system based on frequency hopping RF

Yuzhou Hao, Junwei Che, Xiaoying Wang, Xuejie Li

Mixed anion halide-chalcogenide materials have attracted considerable attention due to their exceptional optoelectronic properties, making them promising candidates for various applications. Among these, CuBiSeCl_2 has recently been experimentally identified with remarkably low lattice thermal conductivity (k_L). In this study, we employ Wigner transport the

Christian Acal, Elena Contreras, Ismael Montero, Juan Eloy Ruiz-Castro

Phase-type distributions (PHDs), which are defined as the distribution of the lifetime up to the absorption in an absorbent Markov chain, are an appropriate candidate to model the lifetime of any system, since any non-negative probability distribution can be approximated by a PHD with sufficient precision. Despite PHD potential, friendly statistical programs

Vitalyy V. Chaban

A new computational method is herein discussed to systemize the development of new dielectric capacitor designs. The method predicts the identities and amounts of (1) gaseous products of decomposition, (2) the volume of the emerged solid phase, coined soot, (3) the band gaps of the soot samples, and (4) the electrical conductivity of the soot. The prediction

Omer Sen, Nathalie Bleser, Andreas Ulbig

As the integration of digital technologies and communication systems continues within distribution grids, new avenues emerge to tackle energy transition challenges. Nevertheless, this deeper technological immersion amplifies the necessity for resilience against threats, encompassing both systemic outages and targeted cyberattacks. To ensure the robustness an

Xiao-Yao Hou, Ze-Feng Gao, Peng-Jie Guo, Jian-Feng Zhang

Dirac nodal line semimetals with topologically protected drumhead surface states have attracted intense theoretical and experimental attention over a decade. However, the study of type-II Dirac nodal line semimetals is rare, especially the type-II nodal chain semimetals have not been confirmed by experiment due to the lack of ideal material platform. In this

Jingxuan Li, Feihu Liu, Guoce Xin

Inspired by Gansner's elegant $k$-trace generating function for rectangular plane partitions, we introduce two novel operators, $\varphi_{z}$ and $\psi_{z}$, along with their combinatorial interpretations. Through these operators, we derive a new formula for $P$-partitions of posets extended by two-rowed plane partitions. This formula allows us to compute ex

Xiangnan Yu, Hao Xu, Zhiping Mao, HongGuang Sun

In complex physical systems, conventional differential equations often fall short in capturing non-local and memory effects, as they are limited to local dynamics and integer-order interactions. This study introduces a stepwise data-driven framework for discovering fractional differential equations (FDEs) directly from data. FDEs, known for their capacity to

Zuo Zuo, Jiahao Dong, Yue Gao, Zongze Wu

In the manufacturing industry, defect detection is an essential but challenging task aiming to detect defects generated in the process of production. Though traditional YOLO models presents a good performance in defect detection, they still have limitations in capturing high-order feature interrelationships, which hurdles defect detection in the complex scen

Hao Zhu, Yan Zhu, Jiayu Xiao, Tianxiang Xiao

Automated crop mapping through Satellite Image Time Series (SITS) has emerged as a crucial avenue for agricultural monitoring and management. However, due to the low resolution and unclear parcel boundaries, annotating pixel-level masks is exceptionally complex and time-consuming in SITS. This paper embraces the weakly supervised paradigm (i.e., only image-l

Victoria Williamson, James Sunseri, Zachary Slepian, Jiamin Hou

In the Interstellar Medium (ISM), gas and dust evolve under magnetohydrodynamic (MHD) turbulence. This produces dense, non-linear structures that then seed star formation. Observationally and theoretically, turbulence is quantified by summary statistics such as the 2-Point Correlation Function (2PCF) or its Fourier-space analog the power spectrum. These cann

Xubin Wang, Jianfei Wu, Yichen Yuan, Deyu Cai

Diversity in demonstration selection is critical for enhancing model generalization by enabling broader coverage of structures and concepts. Constructing appropriate demonstration sets remains a key research challenge. This paper introduces the Relevance-Diversity Enhanced Selection (RDES), an innovative approach that leverages reinforcement learning (RL) fr

Bin Li, Huimin Shan

Traditional video transmission systems assisted by multiple Unmanned Aerial Vehicles (UAVs) are often limited by computing resources, making it challenging to meet the demands for efficient video processing. To solve this challenge, this paper presents a multi-UAV-assisted Device-to-Device (D2D) mobile edge computing system for the maximization of task offlo

Dongjie Fu

In the field of text-to-motion generation, Bert-type Masked Models (MoMask, MMM) currently produce higher-quality outputs compared to GPT-type autoregressive models (T2M-GPT). However, these Bert-type models often lack the streaming output capability required for applications in video game and multimedia environments, a feature inherent to GPT-type models. A

I. A. Karimjanov

In the paper, we describe $n$-dimensional naturally graded nilpotent associative algebras with the characteristic sequence $C(\mathcal{A})=(n-p,1,\dots,1)$ as called $p-$filiform algebras over the field of the complex numbers.

Meiling Huang, Ming Jin, Ning Li

Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications. This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of human capital in creative tasks. Through two random controlled experiments in flash fiction writing and song composition, we

Genki Osada, Makoto Shing, Takashi Nishide

The training of score-based diffusion models (SDMs) is based on score matching. The challenge of score matching is that it includes a computationally expensive Jacobian trace. While several methods have been proposed to avoid this computation, each has drawbacks, such as instability during training and approximating the learning as learning a denoising vecto

Huadong Pang, Li Zhou, Yiping Dong, Peiyuan Chen

In the healthcare sector, the application of deep learning technologies has revolutionized data analysis and disease forecasting. This is particularly evident in the field of diabetes, where the deep analysis of Electronic Health Records (EHR) has unlocked new opportunities for early detection and effective intervention strategies. Our research presents an i

Zhaowei Chang, Pan Tang, Jianhua Zhang, Hao Jiang

Terahertz (THz) integrated sensing and communication (ISAC) holds the potential to achieve high data rates and high-resolution sensing. Reconstructing the propagation environment is a vital step for THz ISAC, as it enhances the predictability of the communication channel to reduce communication overhead. In this letter, we propose an environment reconstructi

Guanwen Xie, Jingzehua Xu, Ziqi Zhang, Xiangwang Hou

It is significant to employ multiple autonomous underwater vehicles (AUVs) to execute the underwater target tracking task collaboratively. However, it's pretty challenging to meet various prerequisites utilizing traditional control methods. Therefore, we propose an effective two-stage learning from demonstrations training framework, FISHER, to highlight the

E. Faraji, P. Kurian, R. Franzosi, S. Mancini

In the present paper we address the general problem of selective electrodynamic interactions between DNA and protein, which is motivated by decades of theoretical study and our very recent experimental findings (M. Lechelon et al, \textit{Sci Adv} \textbf{8,} eabl5855 (2022)). Inspired by the Davydov and Holstein-Fr\"{o}hlich models describing electron motio

G. Jackson, M. Laine

Interaction rates of neutrinos and antineutrinos within a QED plasma determine the dynamics of their decoupling in the early universe. We show how to define the relevant double-differential production, annihilation, and scattering rates at NLO. Integrating over these rates with specific weights, other quantities from the literature can be obtained, such as e

Yibin Liu, Jianyu Zhang, Li Zhang, Shijian Li

Text-to-image (T2I) generation aims at producing realistic images corresponding to text descriptions. Generative Adversarial Network (GAN) has proven to be successful in this task. Typical T2I GANs are 2 phase methods that first pretrain an inter-modal representation from aligned image-text pairs and then use GAN to train image generator on that basis. Howev

Wenying Wen, Ziye Yuan, Yushu Zhang, Tao Wang

Images serve as a crucial medium for communication, presenting information in a visually engaging format that facilitates rapid comprehension of key points. Meanwhile, during transmission and storage, they contain significant sensitive information. If not managed properly, this information may be vulnerable to exploitation for personal gain, potentially infr

Jiayu Liu, Kai Wan, Xinping Yi, Robert Caiming Qiu

Integrated sensing and communication (ISAC) systems provide significant enhancements in performance and resource efficiency compared to individual sensing and communication systems, primarily attributed to the collaborative use of wireless resources, radio waveforms, and hardware platforms. This paper focuses on the bistatic ISAC systems with dispersed multi

Michal Szczepanik, Emil Zak

We present a new method for state preparation using the Unitary Vibrational Coupled-Cluster (UVCC) technique. Our approach utilizes redundancies in the Hilbert space in the direct mapping of vibrational modes into qubits. By eliminating half of the qubit controls required in the Trotterized UVCC ansatz, our method achieves up to a 50% theoretical reduction i

I-Da Chiang, Hiroyuki Hirashita, Jeremy Chastenet, Karin M. Sandstrom

The CO-to-H$_2$ conversion factor ($\alpha_\mathrm{CO}$) is expected to vary with dust abundance and grain size distribution through the efficiency of shielding gas from CO-dissociation radiation. We present a comprehensive analysis of $\alpha_\mathrm{CO}$ and grain size distribution for nearby galaxies, using the PAH fraction ($q_\mathrm{PAH}$) as an observ

Mohamed Yousry Elkhashab, Cristiano Porciani, Daniele Bertacca

Our peculiar velocity imprints a dipole on galaxy density maps derived from redshift surveys. The dipole gives rise to an oscillatory signal in the multipole moments of the observed power spectrum which we indicate as the finger-of-the-observer (FOTO) effect. Using a suite of large mock catalogues mimicking ongoing and future $\textrm{H}\alpha$- and $\textrm

Junting Zhang, Yu Xie, Ke Ji, Xiaofan Shen

Two-dimensional (2D) ferroelectrics and multiferroics have attracted considerable scientific and technological interest in recent years due to the increasing demands for miniaturization and low energy consumption of electronic devices. At present, the research on 2D ferroelectrics and multiferroics is still focused on van der Waals materials, while the known

Yanxiang Jia, Xuyang Wang, Yizhuo Hou, Yu Zhang

Cascaded phase shifters (CPSs) based on silicon photonics integrated chips play important roles in quantum information processing tasks. Owing to an increase in the scale of silicon photonics chips, the time required to calibrate various CPSs has increased. We propose a pairwise scan method for rapidly calibrating CPSs by introducing equivalent Mach Zehnder

Zehao Ju, Tongquan Wei, Fuke Shen

Federated Learning (FL) is a privacy-preserving distributed learning paradigm designed to build a highly accurate global model. In Mobile Edge IoT (MEIoT), the training and communication processes can significantly deplete the limited battery resources of devices. Existing research primarily focuses on reducing overall energy consumption, but this may inadve

Yi-Hung Chiu, Ung Hee Lee, Changseob Song, Manaen Hu

Virtual models of human gait, or digital twins, offer a promising solution for studying mobility without the need for labor-intensive data collection. However, challenges such as the sim-to-real gap and limited adaptability to diverse walking conditions persist. To address these, we developed and validated a framework to create a skeletal humanoid agent capa

Fabian Becker, Catherine L. Curtin, Sudip KC, Tim Schneider

We present a detailed spectroscopic study of the $^4\mathrm{I}_{13/2}$ and $^4\mathrm{I}_{15/2}$ Er$^{3+}$ multiplets of Er:CaWO$_4$ grown without a co-dopant. Using photoluminescence and photoluminescence excitation measurements, we find multiple environments into which the Erbium ions are incorporated in the crystal. For the four most prevalent environment

P. Parfenov, M. Mamaev, A. Taranenko

Studying the properties of strongly-interacting matter at high relative baryon densities is one of the key scientific goals of the MPD (Multi-Purpose Detector) experiment at the NICA accelerator complex. The performance of measuring the azimuthal collective flow of identified charged hadrons at the MPD facility in fixed-target mode is studied in this work.

Wansen Wang, Caichang Tu, Zhaoyi Meng, Wenchao Huang

WebAssembly (WASM) has emerged as a crucial technology in smart contract development for several blockchain platforms. Unfortunately, since their introduction, WASM smart contracts have been subject to several security incidents caused by contract vulnerabilities, resulting in substantial economic losses. However, existing tools for detecting WASM contract v

Lorenzo Iorio

Let two test particles A and B revolving about a spinning primary along ideally identical orbits in opposite directions be considered. From the general expressions of the precessions of the orbital inclination induced by the post-Newtonian gravitomagnetic and Newtonian quadrupolar fields of the central object, it turns out that the Lense-Thirring inclination

Hao Yang, Qianghua Zhao, Lei Li

Chain-of-Thought prompting has significantly enhanced the reasoning capabilities of large language models, with numerous studies exploring factors influencing its performance. However, the underlying mechanisms remain poorly understood. To further demystify the operational principles, this work examines three key aspects: decoding, projection, and activation

Fardin Kheirandish, Narges Cheraghpour, Adam Moradian

The Empemba effect (ME) is investigated in the context of ubiquitous quantum oscillating and two-level systems (TLS) using a novel approach (DOI 10.1088/1402-4896/ad97f1). Exact reduced density matrices for various initial states are derived. The temporal behavior of the trace distance for these initial states is calculated analytically and presented. For a

Diogo Oliveira e Silva, Błażej Wróbel

Let ${{\bf R}_{\mathbb{S}^{d-1}}}(p\to q)$ denote the best constant for the $L^p(\mathbb{R}^d)\to L^q(\mathbb{S}^{d-1})$ Fourier restriction inequality to the unit sphere $\mathbb{S}^{d-1}$, and let ${\bf R}_{\mathbb{S}^{d-1}} (p\to q;\textrm{rad})$ denote the corresponding constant for radial functions. We investigate the asymptotic behavior of the operator

Adrián Navas-Montilla, Cordula Reisch, Pablo Diaz, Ilhan Özgen-Xian

Anthropogenic climate change has increased the probability, severity, and duration of heat waves and droughts, subsequently escalating the risk of wildfires. Mathematical and computational models can enhance our understanding of wildfire propagation dynamics. In this work, we present a simplified Advection-Diffusion-Reaction (ADR) model that accounts for the

Shahran Rahman Alve

This project aims to develop a robust video surveillance system, which can segment videos into smaller clips based on the detection of activities. It uses CCTV footage, for example, to record only major events-like the appearance of a person or a thief-so that storage is optimized and digital searches are easier. It utilizes the latest techniques in object d

Tianyu Chen, Zhendong Wang, Mingyuan Zhou

Diffusion models have recently demonstrated notable success in solving inverse problems. However, current diffusion model-based solutions typically require a large number of function evaluations (NFEs) to generate high-quality images conditioned on measurements, as they incorporate only limited information at each step. To accelerate the diffusion-based inve

Wenhui Yi, Jiayi Zhang, Zhe Wang, Huahua Xiao

The rotary and movable antennas (ROMA) technology is efficient in enhancing wireless network capacity by adjusting both the antenna spacing and three-dimensional (3D) rotation of antenna surfaces, based on the spatial distribution of users and channel statistics. Applying ROMA to high-speed rail (HSR) wireless communications can significantly improve system

Yongchun Xu, Zengtao Kuang, Qun Huang, Jie Yang

Quantum computing offers a promising avenue for advancing computational methods in science and engineering. In this work, we introduce the quantum asymptotic numerical method (qANM), a framework for solving nonlinear path-following problems using quantum computing. Based on the principle of high-order perturbation techniques, the proposed method uses Taylor

Wansen Wang, Pu Zhang, Renjie Ji, Wenchao Huang

Some smart contracts violate decentralization principles by defining privileged accounts that manage other users' assets without permission, introducing centralization risks that have caused financial losses. Existing methods, however, face challenges in accurately detecting diverse centralization risks due to their dependence on predefined behavior patterns

Kiyohiro Nakayama, Jan Ackermann, Timur Levent Kesdogan, Yang Zheng

Apparel is essential to human life, offering protection, mirroring cultural identities, and showcasing personal style. Yet, the creation of garments remains a time-consuming process, largely due to the manual work involved in designing them. To simplify this process, we introduce AIpparel, a multimodal foundation model for generating and editing sewing patte

Zhaokun Hu, Yindong Xiao, Houjun Wang, Jiayong Yu

As the scale and complexity of integrated circuits continue to increase, traditional modeling methods are struggling to address the nonlinear challenges in radio frequency (RF) chips. Deep learning has been increasingly applied to RF device modeling. This paper proposes a deep learning-based modeling method for RF devices using a uniform noise training set,

Sotirios Fragkos, Baptiste Fabre, Olena Tkach, Stéphane Petit

Driving quantum materials out-of-equilibrium makes it possible to generate states of matter inaccessible through standard equilibrium tuning methods. Upon time-periodic coherent driving of electrons using electromagnetic fields, the emergence of Floquet-Bloch states enables the creation and control of exotic quantum phases. In transition metal dichalcogenide

Yifan Lu, Xuanchi Ren, Jiawei Yang, Tianchang Shen

We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suffer from limited scales or lack geometric and appearance consistency along generated sequences. In contrast, we leverage the recent advancements in scalable 3D representation and v

Fnu Neha, Deepshikha Bhati, Deepak Kumar Shukla, Angela Guercio

The rapid development of Artificial Intelligence (AI) has led to the creation of powerful text generation models, such as large language models (LLMs), which are widely used for diverse applications. However, concerns surrounding AI-generated content, including issues of originality, bias, misinformation, and accountability, have become increasingly prominen

Arash Tavassoli, Stuart R. Hudson, Zhisong Qu, Matthew Hole

We investigate the solutions of the relaxed MHD model (RxMHD) of Dewar \& Qu [J. Plasma Phys. {\bf 88}, 835880101 (2022)]. This model generalizes Taylor relaxation by including the ideal Ohm's law constraint using an augmented Lagrangian method, providing a pathway to extend the multi-region relaxed MHD (MRxMHD) model. We present the first numerical solution

Yunhe Pang, Bo Chen, Fanjin Zhang, Yanghui Rao

Anomaly detection on text-rich graphs is widely prevalent in real life, such as detecting incorrectly assigned academic papers to authors and detecting bots in social networks. The remarkable capabilities of large language models (LLMs) pave a new revenue by utilizing rich-text information for effective anomaly detection. However, simply introducing rich tex

Wanli Cheng

In the fields of non-commutative geometry and string theory, quantum tori appear in different mathematical and physical contexts. Therefore, quantized theta functions defined on quantum tori are also studied (Yu. I. Manin, A. Schwartz; note that a comparison between the two definitions of quantum theta is still an open problem). One important application of

Mithun Parab, Pranay Lendave, Jiyoung Kim, Thi Quynh Dan Nguyen

In image-assisted minimally invasive surgeries (MIS), understanding surgical scenes is vital for real-time feedback to surgeons, skill evaluation, and improving outcomes through collaborative human-robot procedures. Within this context, the challenge lies in accurately detecting, segmenting, and estimating the depth of surgical scenes depicted in high-resolu

Ming-Chang Chiu, Shicheng Wen, Pin-Yu Chen, Xuezhe Ma

In vision-language models (VLMs), the ability to perceive and interpret color and physical environment is crucial for achieving contextually accurate understanding and interaction. However, despite advances in multimodal modeling, there remains a significant lack of specialized datasets that rigorously evaluate a model's capacity to discern subtle color vari

Ruicong Huang, Wencong Wang, Yuyang Liang, Dongmei Liu

Over the past decade, parity-time (PT) symmetry and anti-PT (APT) symmetry in various physical systems have been extensively studied, leading to significant experimental and theoretical advancements. However, physical systems that simultaneously exhibit both PT and APT symmetry have not yet been explored. In this study, we construct a phase-sensitive non-Her