December 2024 arXiv papers — page 191

İlter Onat Korkmaz, Yaşar Cahit Yıldırım, Çağın Ararat, Cem Tekin

We study black-box vector optimization with Gaussian process bandits, where there is an incomplete order relation on objective vectors described by a polyhedral convex cone. Existing black-box vector optimization approaches either suffer from high sample complexity or lack theoretical guarantees. We propose Vector Optimization with Gaussian Process (VOGP), a

Andreas C. Schneider, Valentin Neuhaus, David A. Ehrlich, Abdullah Makkeh

In modern deep neural networks, the learning dynamics of the individual neurons is often obscure, as the networks are trained via global optimization. Conversely, biological systems build on self-organized, local learning, achieving robustness and efficiency with limited global information. We here show how self-organization between individual artificial neu

A. V. Shanin, A. I. Korolkov, N. M. Artemov, R. C. Assier

A matrix formalism is proposed for computations based on Picard--Lefschetz theory in a 2D case. The formalism is essentially equivalent to the computation of the intersection indices necessary for the Picard--Lefschetz formula and enables one to prove non-trivial topological identities for integrals depending on parameters. We introduce the universal Riemann

Yuzhi Che, Long Chen, Jinfei Wu, Xinchou Lou

We demonstrate the feasibility of determining the strong coupling constant, $\alpha_s$, from the inclusive semileptonic decay width of $B$ mesons. We express the semileptonic $B$ decay width as a function of $\alpha_s(5\mathrm{\,GeV})$, the Cabibbo-Kobayashi-Maskawa matrix element $|V_{cb}|$, $b$- and $c$-quark masses in the $\overline{\mathrm{MS}}$ scheme.

Xuemin Shen, Xinyu Huang, Jianzhe Xue, Conghao Zhou

In this article, we present a digital agent (DA)-assisted network management framework for future sixth generation (6G) networks considering user quality of experience (QoE). A novel QoE metric is defined by incorporating the impact of user behavioral dynamics and environmental complexity on quality of service (QoS). A two-level DA architecture is proposed t

Caixin Kang, Yubo Chen, Shouwei Ruan, Shiji Zhao

With the rise of deep learning, facial recognition technology has seen extensive research and rapid development. Although facial recognition is considered a mature technology, we find that existing open-source models and commercial algorithms lack robustness in certain complex Out-of-Distribution (OOD) scenarios, raising concerns about the reliability of the

Federico Pegoraro, Philip Held, Jonas Lammers, Benjamin Brecht

The two-qubit controlled-not (C-NOT) gate is an essential component for gate-based quantum circuits. In fact, its operation, combined with single qubit rotations allows to realise any quantum circuit. Several strategies have been adopted in order to build quantum gates. Among them, photonics offers the dual advantage of excellent isolation from the environme

CMS Collaboration

The inclusive WZ production cross section is measured in proton-proton collisions at a centre-of-mass energy of 13.6 TeV, using data collected during 2022 with the CMS detector, corresponding to an integrated luminosity of 34.7 fb$^{-1}$. The measurement uses multileptonic final states and a simultaneous likelihood fit to the number of events in four differe

Yves Gabellini, Thierry Grandou, Ralf Hofmann

About twelve years ago the use of standard functional manipulations was demonstrated to imply an unexpected property satisfied by the fermionic Green's functions of QCD. This non-perturbative phenomenon is dubbed Effective Locality. In a much simpler way than in QCD, the most remarkable and intriguing aspects of Effective Locality have been presented in a re

John Erik Fornæss, Mi Hu, Tuyen Trung Truong

In this paper, we research more in depth properties of Backtracking New Q-Newton's method (recently designed by the third author), when used to find roots of meromorphic functions. If $f=P/Q$, where $P$ and $Q$ are polynomials in 1 complex variable z with $\deg (P)>\deg (Q)$, we show the existence of an exceptional set $\mathcal{E}\subset\mathbf{C}$, which i

Mathias Lamari, Pierre Kerfriden, Oguz Umut Salman, Vladislav Yastrebov

Plastic flow is conventionally treated as continuous in finite element (FE) codes, whether in isotropic, anisotropic plasticity, or crystal plasticity. This approach, derived from continuum mechanics, contradicts the intermittent nature of plasticity at the elementary scale. Understanding crystal plasticity at micro-scale opens the door to new engineering ap

Yi-Xiang Lu, Xiao-Bo Jin, Jian Chen, Dong-Jie Liu

With the development of society, time series anomaly detection plays an important role in network and IoT services. However, most existing anomaly detection methods directly analyze time series in the time domain and cannot distinguish some relatively hidden anomaly sequences. We attempt to analyze the impact of frequency on time series from a frequency doma

Ali Asgharpour, Bert Koopmans, Rembert A. Duine

Altermagnets, a distinct class of antiferromagnets with electronic structures resembling those of d-wave superconductors, exhibit intriguing properties that have gained significant attention in recent research. In this article, we propose synthetic altermagnets, composed of two anisotropic ferromagnetic layers arranged such that the total net magnetization i

A. M. Gavrilik, A. V. Nazarenko

For a quasi-two-dimensional nonlinear sigma model on the real Stiefel manifolds with a generalized (anisotropic) metric, the equations of a two-charge renormalization group (RG) for the homothety and anisotropy of the metric as effective couplings are obtained in a one-loop approximation. Normal coordinates and the curvature tensor are exploited for the reno

Haojie Wang, Zhe Zhang, Haotian Gao, Xiangying Zhang

Identifying the interaction targets of bioactive compounds is a foundational element for deciphering their pharmacological effects. Target prediction algorithms equip researchers with an effective tool to rapidly scope and explore potential targets. Here, we introduce the COMET, a multi-technological modular target prediction tool that provides comprehensive

Artem Averin

We provide a formulation and proof of the gravitational entropy bound. We use a recently given framework which expresses the measurable quantities of a quantum theory as a weighted sum over paths in the theory's phase space. If this framework is applied to a field theory on a spacetime foliated by a hypersurface $\Sigma,$ the choice of a codimension-2 surfac

Han-Xin Lou, Xing-Guo Ye, Xin Liao, Tong-Yang Zhao

We investigate the resistive anisotropy in CsV3Sb5 thin films within the charge density wave phase. Using a device structure with twelve electrodes symmetrically distributed in a circular shape, we measure the resistivity anisotropy by varying the current direction. A twofold resistivity anisotropy modulated by temperature is found, which is fully consistent

E. Abasov, E. Boos, V. Bunichev, L. Dudko

The paper describes the application of deep neural networks for the searchdeviations from the Standard Model predictions at the Wtb vertex in the processes of single and double resonant top quark production with identical final state tWb. Monte-Carlo events preliminary classified by first level neural network as corresponding to single or double resonant top

Tejumade Afonja, Hui-Po Wang, Raouf Kerkouche, Mario Fritz

Generating tabular data under differential privacy (DP) protection ensures theoretical privacy guarantees but poses challenges for training machine learning models, primarily due to the need to capture complex structures under noisy supervision signals. Recently, pre-trained Large Language Models (LLMs) -- even those at the scale of GPT-2 -- have demonstrate

Mohammed Q. Shormani

This study sets out to answer one major question: Can ChatGPT capture swearing nuances? It presents an empirical study on the ability of ChatGPT to translate Arabic oath expressions into English. 30 Arabic oath expressions were collected from the literature. These 30 oaths were first translated via ChatGPT and then analyzed and compared to the human translat

Fatima Aboud, François Jauberteau, Didier Robert

In this article we are interested for the numerical computation of spectra of non-self adjoint quadratic operators, in two and three spatial dimensions. Indeed, in the multidimensional case very few results are known on the location of the eignevalues. This leads to solve nonlinear eigenvalue problems. In introduction we begin with a review of theoretical re

Kai-Lei Wang, Juan Wang, Yu-Kuo Hsiao, Xian-Hui Zhong

We investigate the sextet $b$-baryon decay processes $\Omega_b\to J/\psi\Omega^{(*)}$,where $\Omega^*$ represents the $1P$-, $1D$- and $2S$-wave excited $\Omega$ hyperons in the spectroscopy. Using the constituent quark model, we obtain ${\cal B}(\Omega_b \to J/\psi\Omega)=8.8\times 10^{-4}$, which agrees with the previous studies to the order of magnitude.

Bowei Wu, Teng Wang, Shuanghuizhi Li, Tingfeng Ma

In this work, tunable acoustic energy concentrations are realized based on pseudo-spin locking waveguides and topological rainbow trappings. Firstly, a tunable pseudo-spin locking is proposed, and the broad acoustic energy transport and spin-locked one-way transport are verified. The results show that acoustic wave transports based on pseudo-spin locking wav

Alexey Kuznetsov

For $q \in (0, 1)$, the deformed exponential function $f(x) = \sum_{n \geq 1} x^n q^{n(n-1)/2}/n!$ is known to have infinitely many simple and negative zeros $\{x_k(q)\}_{k \geq 1}$. In this paper, we analyze the series expansions of $-x_k(q)/k$ and $k/x_k(q)$ in powers of $q$. We prove that the coefficients of these expansions are rational functions of the

Bertram Düring, Oliver Wright

Voter demographics and socio-economic factors like age, sex, ethnicity, education level, income, and other measurable factors like behaviour in previous elections or referenda are of key importance in modelling opinion formation dynamics. Here, we revisit the kinetic opinion formation model from D\"uring and Wright (2022) and compare in more detail the influ

S. Yu. Orevkov

A rational function on a real algebraic curve $C$ is called separating if it takes real values only at real points. Such a function defines a covering $\mathbb R C\to\mathbb{RP}^1$. Let $c_1,\dots,c_r$ be connected components of $\mathbb R C$. M. Kummer and K. Shaw defined the separating semigroup of $C$ as the set of all sequences $(d_1(f),\dots,d_r(f))$ wh

Salvatore Chirumbolo, Antonio Vella

Life is fundamentally a scientific enigma. The interplay between chaos, entropy dynamics, and Prigogine's dissipative systems offers profound insights into the emergence, stabilization, and eventual collapse of far-from-equilibrium systems. This study proposes that, alongside thermodynamic dissipative systems as highlighted by Ilya Prigogine, informational d

Filippo Caleca, Simone Tibaldi, Elisa Ercolessi

The use of Neural Networks in quantum many-body theory has seen a formidable rise in recent years. Among the many possible applications, one surely is to make use of their pattern recognition power when dealing with the study of equilibrium phase diagram. Within this context, Learning by Confusion has emerged as an interesting, unbiased scheme. The idea behi

Khadija El Aadmi-Laamech, Patricia Santos, Davinia Hernández-Leo

This study explores the design and preliminary evaluation of the "Well-being Journey" (WB Journey), a digital tool aimed at enhancing student well-being within educational environments through tailored recommendations for students. The study examines the WB Journey prototype's user experience and its effectiveness in meeting learning analytics goals related

Jiaming Liu, Min Fang, Chao Liu, Xiaolong Wang

The Taurus region is one of the most extensively studied star-forming regions. Surveys indicate that the young stars in this region are comprised of Young Stellar Objects (YSOs) that cluster in groups associated with the molecular cloud (Grouped Young Stellar Objects, GYSOs), and some older ones that are sparsely distributed throughout the region (Distribute

Ruslan Nakibov, Andrey Ursulov

In this paper we present the results of a theoretical study of the trajectories of massive particles in the K\"ottler metric in view of the cosmological constant {\Lambda}. For both negative and positive signs of {\Lambda} a classification of trajectories is proposed, with entries based on different solutions of the trajectory equation, obtained by the expan

Patricia Silva de Camargo, Paulo Roberto Cabral-Passos, André Frazão Helene

Motor imagery corresponds to the mental practice of simulating visual and kinesthetic aspects of a given motor task. This practice shares a similar neural substrate and correlated temporal scale with motor execution. Besides that, it can lead to performance improvements in the actual execution of the imagined task. Therefore it is important to understand fun

Zongru Wu, Pengzhou Cheng, Lingyong Fang, Zhuosheng Zhang

Backdoor attacks remain significant security threats to generative large language models (LLMs). Since generative LLMs output sequences of high-dimensional token logits instead of low-dimensional classification logits, most existing backdoor defense methods designed for discriminative models like BERT are ineffective for generative LLMs. Inspired by the obse

Sulagna Bhattacharya

Galactic dark matter (DM) particles, having non-gravitational interactions with nucleons, can interact with stellar constituents and eventually become captured within stars. Over the lifetime of the celestial body, these non-annihilating, heavy DM particles may accumulate and eventually form a comparable stellar mass black hole (BH), referred to as a Transmu

Aman Saggu, Lennart Ante, Kaja Kopiec

This study employs an event study methodology to investigate the market impact of the U.S. Securities and Exchange Commission's (SEC) classification of crypto assets as securities. It explores how SEC interventions influence asset returns and trading volumes, focusing on explicitly named crypto assets. The empirical analysis highlights significant adverse ma

Xiang Yu, Yibin Fu

To facilitate the understanding of the mechanisms underlying the electric breakdown of dielectric elastomers, we derive a one-dimensional (1d) model for axisymmetric necking in a dielectric membrane subjected to equibiaxial stretching and an electric field, starting from the three-dimensional (3d) nonlinear electroelasticity theory. Our reduction is built on

Chenguang Huang, Shengchao Yan, Wolfram Burgard

Dynamic scene understanding remains a persistent challenge in robotic applications. Early dynamic mapping methods focused on mitigating the negative influence of short-term dynamic objects on camera motion estimation by masking or tracking specific categories, which often fall short in adapting to long-term scene changes. Recent efforts address object associ

Anqi Liang, Pengcheng Zhang, Bin Yao, Zhongpu Chen

This paper presents an efficient and scalable framework for Range Filtered Approximate Nearest Neighbors Search (RF-ANNS) over high-dimensional vectors associated with attribute values. Given a query vector $q$ and a range $[l, h]$, RF-ANNS aims to find the approximate $k$ nearest neighbors of $q$ among data whose attribute values fall within $[l, h]$. Exist

Conghao Wong, Ziqian Zou, Beihao Xia, Xinge You

Learning to forecast trajectories of intelligent agents has caught much more attention recently. However, it remains a challenge to accurately account for agents' intentions and social behaviors when forecasting, and in particular, to simulate the unique randomness within each of those components in an explainable and decoupled way. Inspired by vibration sys

Zongxia Liang, Sheng Wang, Jianming Xia

This paper discusses a nonlinear integral equation arising from portfolio selection with a class of time-inconsistent preferences. We propose a unified framework requiring minimal assumptions, such as right-continuity of market coefficients and square-integrability of the market price of risk. Our main contribution is proving the existence and uniqueness of

Dennis Kudlacik, Evgeny A. Zhukov, Dmitri R. Yakovlev, Gang Qiang

The spin properties of charge carriers confined in CuCl semiconductor nanocrystals (NCs) of different sizes (radius from 1.8 nm up to 28 nm) crystallized in a glass matrix are studied experimentally and theoretically. By means of photoluminescence, spin-flip Raman scattering, time-resolved Faraday ellipticity, and time-resolved differential transmission perf

Amaury Micheli

This thesis is dedicated to analysing the generation and destruction of quantum correlations in the context of inflationary cosmology and an experiment of 'analogue' preheating. Inflation is a phase of accelerated expansion of the Universe, preceding the so-called Standard Model of Big Bang cosmology, introduced to solve some shortcomings of this model. It a

Malik Abdul Manan, Feng Jinchao, Muhammad Yaqub, Shahzad Ahmed

Colorectal polyps are structural abnormalities of the gastrointestinal tract that can potentially become cancerous in some cases. The study introduces a novel framework for colorectal polyp segmentation named the Multi-Scale and Multi-Path Cascaded Convolution Network (MMCC-Net), aimed at addressing the limitations of existing models, such as inadequate spat

Jonathan Conrad

Quantum error correction is an essential ingredient in the development of quantum technologies. Its subject is to investigate ways to embed quantum Hilbert spaces into a physical system such that this subspace is robust against small imperfections in the physical systems. This task is exceedingly complex: for one, this is due to the vast diversity of possibl

Shai Shalev-Shwartz, Amnon Shashua, Gal Beniamini, Yoav Levine

Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with critical, precise reasoning capabilities akin to those of top human experts. Existing AI systems often excel at predefined tasks but struggle with adaptability and precision in novel

Lotta Rüter, Melanie Schienle

We propose an adaption of the multiple imputation random lasso procedure tailored to longitudinal data with unobserved fixed effects which provides robust variable selection in the presence of complex missingness, high dimensionality and multicollinearity. We apply it to identify social and financial success factors of microfinance institutions (MFIs) in a d

Sunil Mucesh, William G. Hartley, Ciarán M. Gilligan-Lee, Ofer Lahav

Understanding how galaxies form and evolve is at the heart of modern astronomy. With the advent of large-scale surveys and simulations, remarkable progress has been made in the last few decades. Despite this, the physical processes behind the phenomena, and particularly their importance, remain far from known, as correlations have primarily been established

Yuka Fujiki, Stefan Junk

We numerically investigate the robustness of networks with degree-degree correlations between nodes separated by distance $l=2$ in terms of shortest path length. The degree-degree correlation between the $l$-th nearest neighbors can be quantified by Pearson's correlation coefficient $r_l$ for the degrees of two nodes at distance $l$. We introduce $l$-th near

Jakob Huhle, Jakob Kaiser, Eric Müller, Johannes Schemmel

The development of mechanistic models of physical systems is essential for understanding their behavior and formulating predictions that can be validated experimentally. Calibration of these models, especially for complex systems, requires automated optimization methods due to the impracticality of manual parameter tuning. In this study, we use an autoencode

Xiao-Bin Chen, Kai Wang, Yi-Yun Huang, Hai-Ming Zhang

The supersonic flow motions associated with infall of baryonic gas toward sheets and filaments, as well as cluster mergers, produces large-scale shock waves. The shocks associated with galaxy clusters can be classified mainly into two categories: internal shocks appear in the hot intracluster medium within the viral radius, and external accretion shocks form

Haris Aziz, Patrick Lederer, Xinhang Lu, Mashbat Suzuki

In approval-based budget division, a budget needs to be distributed to candidates based on the voters' approval ballots over these candidates. In the pursuit of a simple, consistent, and approximately fair rule for this setting, we introduce the maximum payment rule (MP). Under this rule, each voter controls a part of the budget and, in each step, the corres

Renyongkang Zhang, Ge Guo, Zeng-di Zhou

This paper proposes a distributed optimization algorithm with a convergence time that can be assigned in advance according to task requirements. To this end, a sliding manifold is introduced to achieve the sum of local gradients approaching zero, based on which a distributed protocol is derived to reach a consensus minimizing the global cost. A novel approac

Hanjo D. Boekhout, Frank W. Takes

Cliques, groups of fully connected nodes in a network, are often used to study group dynamics of complex systems. In real-world settings, group dynamics often have a temporal component. For example, conference attendees moving from one group conversation to another. Recently, maximal clique enumeration methods have been introduced that add temporal (and freq

Xudong Gao, Xiaoguang Gao, Jia Rong, Xiaolei Li

The Fuzzy General Grey Cognitive Map (FGGCM) and Fuzzy Grey Cognitive Map (FGCM) extend the Fuzzy Cognitive Map (FCM) by integrating uncertainty from multiple interval data or fuzzy numbers. Despite extensive studies on the convergence of FCM and FGCM, the convergence behavior of FGGCM under sigmoid activation functions remains underexplored. This paper addr

Cheng-Man Wang, Chao-Hsiang Hsu, Jing-Sen Yang, Ping-Chun Tsai

Emerging superionic conductors Li3InCl6 (LIC) and Li6PS5Cl (LPSC) are very promising for solid-state electrolytes (SSEs) in all-solid-state lithium batteries (ASSLBs). However, unstable lithium-anode interfaces in LIC and LPSC have been observed through experiments and ab initio calculations, while the interphases formed in determining interfacial stability

Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Georgios Kaissis, Daniel Rueckert

Machine unlearning refers to removing the influence of a specified subset of training data from a machine learning model, efficiently, after it has already been trained. This is important for key applications, including making the model more accurate by removing outdated, mislabeled, or poisoned data. In this work, we study localized unlearning, where the un

Victoria Leaker, Tristan Pitre, Eric Poisson

We define and calculate the mass multipole moments of a material body of mass $M$ and electric charge $Q$ tidally deformed by a particle of mass $m \ll M$ and charge $q \ll Q$ placed at a distance $r_0$ from the body. Given $Q/M$ and $r_0$, we choose $q/m$ so that the gravitational attraction between body and particle is balanced by the electrostatic repulsi

Carlo Danieli, Laura Pilozzi, Claudio Conti, Valentina Brosco

Non-Abelian gauge symmetries are cornerstones of modern theoretical physics, underlying fundamental interactions and the geometric structure of quantum mechanics. However, their potential to control quantum coherence, entangle- ment, and transport in engineered quantum systems remains to a large extent unexplored. In this work, we propose utilizing non-Abeli

Vaibhav Kumar Jena

In this article, we prove a variety of uniqueness results for ultrahyperbolic equations with general space and time dependent lower order terms. We address the problem of determining uniqueness of solutions from boundary data as well as when the data is prescribed on an interior subset. Furthermore, we also present the case when the domain may change with re

Sarah T. Bachinger, Christoph Unger, Robin Erd, Leila Feddoul

We apply NER to a particular sub-genre of legal texts in German: the genre of legal norms regulating administrative processes in public service administration. The analysis of such texts involves identifying stretches of text that instantiate one of ten classes identified by public service administration professionals. We investigate and compare three method

Anisa Bajkova, Anton Smirnov, Vadim Bobylev

The paper is devoted to the analysis of the influence of the galactic bar on the nature of the orbital motion (chaotic or regular) of globular clusters in the central region of the Galaxy with a radius of 3.5 kpc, which are subject to the greatest influence of the bar. The sample includes 45 globular clusters. To form the 6D phase space required for integrat

Corentin Bonte, Arne Bouillon, Giovanni Samaey, Karl Meerbergen

Recently, the ParaOpt algorithm was proposed as an extension of the time-parallel Parareal method to optimal control. ParaOpt uses quasi-Newton steps that each require solving a system of matching conditions iteratively. The state-of-the-art parallel preconditioner for linear problems leads to a set of independent smaller systems that are currently hard to s

Yiqian Luo, Qiurong Chen, Fali Li, Liang Yi

Autism Spectrum Disorder (ASD) is a pervasive developmental disorder of the central nervous system, primarily manifesting in childhood. It is characterized by atypical and repetitive behaviors. Currently, diagnostic methods mainly rely on questionnaire surveys and behavioral observations, which are prone to misdiagnosis due to their subjective nature. With a

Sebastian Hirt, Lukas Theiner, Rolf Findeisen

Closed-loop performance of sequential decision making algorithms, such as model predictive control, depends strongly on the choice of controller parameters. Bayesian optimization allows learning of parameters from closed-loop experiments, but standard Bayesian optimization treats this as a black-box problem and ignores the temporal structure of closed-loop t

Eleonore Faber, Bernd Schober

We study the connection between Conway-Coxeter frieze patterns and the data of the minimal resolution of a complex curve singularity: using Popescu-Pampu's notion of the lotus of a singularity, we describe a bijection between the dual resolution graphs of Newton non-degenerate plane curve singularities and Conway-Coxeter friezes. We use representation theore

Dongwei Pan, Yang Li, Hongsheng Li, Kwan-Yee Lin

We present TimeWalker, a novel framework that models realistic, full-scale 3D head avatars of a person on lifelong scale. Unlike current human head avatar pipelines that capture identity at the momentary level(e.g., instant photography or short videos), TimeWalker constructs a person's comprehensive identity from unstructured data collection over his/her var

Kevin Atsou, Thierry Goudon, Pierre-Emmanuel Jabin

We analyse a Fokker-Planck like equation, driven by a scalar parameter in order to reach an integral constraint. We exhibit criteria guaranteeing existence-uniqueness of a solution. We also provide counter-examples. This problem is motivated by an application to the immune control of tumor growth.

Mingyi Shi, Dafei Qin, Leo Ho, Zhouyingcheng Liao

Conversational scenarios are very common in real-world settings, yet existing co-speech motion synthesis approaches often fall short in these contexts, where one person's audio and gestures will influence the other's responses. Additionally, most existing methods rely on offline sequence-to-sequence frameworks, which are unsuitable for online applications. I

Dror Yahav, Ariel Maniv, Daniel Potashnikov, Asaf Pesach

We uncover a high-field magnetic phase in i-MAX compounds exhibiting a canted antiferromagnetic (AFM) order with unprecedented properties, revealed through NMR and AC susceptibility. Intriguingly, as the atomic number of Rare Earth increases, the transition field of this canted AFM phase grows at the expense of the lower-field AFM state. Our findings point t

Richard Evan Schwartz

In my 1993 paper, "Pappus's Theorem and the Modular Group", I explained how the iteration of Pappus's Theorem gives rise to a $2$-parameter family of representations of the modular group into the group of projective automorphisms. In this paper we realize these representations as isometry groups of patterns of geodesics in the symmetric space $X=SL_3(\R)/SO(

Qingfeng Sun, Hui Wang

In this paper, we establish an asymptotic formula for the twisted second moment of $L$-functions associated with Hecke--Maass cusp forms for $\rm SL(3,\mathbb{Z})$, and further deduce a weighted zero-density estimate for these $L$-functions in the spectral aspect which may have important applications in other problems.

Jie Zou, Aixin Sun, Cheng Long, Evangelos Kanoulas

In conversational recommender systems (CRSs), conversations usually involve a set of items and item-related entities or attributes, e.g., director is a related entity of a movie. These items and item-related entities are often mentioned along the development of a dialog, leading to potential sequential dependencies among them. However, most of existing CRSs

Valentin Niess, Kinson Vernet, Luca Terray

Goupil is a software library designed for the Monte Carlo transport of low-energy gamma-rays, such as those emitted from radioactive isotopes. The library is distributed as a Python module. It implements a dedicated backward sampling algorithm that is highly effective for geometries where the source size largely exceeds the detector size. When used in conjun

Yi Zeng, Hui Zhu, Jinwei Li, Jianfeng Li

While passive acoustic mapping (PAM) has been advanced for monitoring acoustic cavitation activity in focused ultrasound (FUS) therapy, achieving both real-time and high-quality imaging capabilities is still challenging. The angular spectrum (AS) method presents the most efficient algorithm for PAM, but it suffers from artifacts and low resolution due to the

Tom White

We present VISTA (Visualization of Internal States and Their Associations), a novel pipeline for visually exploring and interpreting neural network representations. VISTA addresses the challenge of analyzing vast multidimensional spaces in modern machine learning models by mapping representations into a semantic 2D space. The resulting collages visually reve

Limin Song, Shenyi Gao, Shiqi Xia, Yongsheng Liang

Topological entities based on bulk-boundary correspondence are ubiquitous, from conventional to higher-order topological insulators, where the protected states are typically localized at the outer boundaries (edges or corners). A less explored scenario involves protected states that are localized at the inner boundaries, sharing the same energy as the bulk s

Donghao Yang, Aolang Wu, Tianyi Zhang, Li Zhang

Among the programming languages for Programmable Logic Controllers (PLCs), Structured Text (ST) is widely adopted for industrial automation due to its expressiveness and flexibility. However, major vendors implement ST with proprietary extensions and hardware-specific libraries - Siemens' SCL and CODESYS' ST each differ in syntax and functionality. This frag

He Wang, Yunpeng Ge, Ivan Wang-Hei Ho

Wi-Fi sensing has been extensively explored for various applications, including vital sign monitoring, human activity recognition, indoor localization, and tracking. However, practical implementation in real-world scenarios is hindered by unstable sensing performance and limited knowledge of wireless sensing coverage. While previous works have aimed to addre

Yating Liu, Lulu Fan, Lei Hu, Junqiang Lu

Deep-learning-based methods have been favored in astrophysics owing to their adaptability and remarkable performance and have been applied to the task of the classification of real and bogus transients. Different from most existing approaches which necessitate massive yet expensive annotated data, We aim to leverage training samples with only 1000 labels ava

Shabnam Fazliani, Mohammad Mowlavi Sorond, Arsalan Masoudifard

The advent of smart contracts has enabled the rapid rise of Decentralized Finance (DeFi) on the Ethereum blockchain, offering substantial rewards in financial innovation and inclusivity. This growth, however, is accompanied by significant security risks such as illicit accounts engaged in fraud. Effective detection is further limited by the scarcity of label

Tanuj Gupta, Arun Kumar Sharma, Ankur Dwivedi, Vivek Gupta

On-demand vibration mitigation in a mechanical system needs the suitable design of multiscale metastructures, involving complex unit cells. In this study, immersing in the world of patterns and examining the structural details of some interesting motifs are extracted from the mechanical metastructure perspective. Nine interlaced metastructures are fabricated

Amir Ghiami, Hleb Fiadziushkin, Tianyishan Sun, Songyao Tang

A reliable and scalable transfer of 2D-TMDCs (two-dimensional transition metal dichalcogenides) from the growth substrate to a target substrate with high reproducibility and yield is a crucial step for device integration. In this work, we have introduced a scalable dry-transfer approach for 2D-TMDCs grown by MOCVD (metal-organic chemical vapor deposition) on

Alban Dutilleul, Hugo Pompougnac, Nicolas Derumigny, Gabriel Rodriguez

Modern Out-of-Order (OoO) CPUs are complex systems with many components interleaved in non-trivial ways. Pinpointing performance bottlenecks and understanding the underlying causes of program performance issues are critical tasks to fully exploit the performance offered by hardware resources. Current performance debugging approaches rely either on measuring

Alexis I. Aravanis, Thanh Tu Lam, Olga Muñoz, Antonio Pascual-Iserte

The employment of stochastic geometry for the analysis and design of ultra dense networks (UDNs) has provided significant insights into network densification. In addition to the characterization of the network performance and behavior, these tools can also be exploited toward solving complex optimization problems that could maximize the capacity benefits ari

Robert P. Cameron, Duncan McArthur, Alison M. Yao, Nick Vogeley

Inspired by a sea creature, we identify a robust chiral optical force that pushes the opposite enantiomers of a chiral molecule towards regions of orthogonal linear polarization in an optical field via electric dipole interactions. Our chiral optical force can be orders of magnitude stronger than others proposed to date and applies to essentially all chiral

Tau Hoshino, Tetsufumi Hirano

The initial conditions of one-dimensional expanding viscous fluids in relativistic heavy-ion collisions are scrutinized in terms of nonlinear causality of the relativistic hydrodynamic equations. Conventionally, it is believed that the matter generated in relativistic heavy-ion collisions starts to behave as a fluid all at once at some initial time. However,

Qing Qin, Yu Zhang, Yubei Wei, Jinnuo

In this study, we present a two-stage method for fabricating monodisperse alginate hydrogel microspheres using a symmetrically designed flow-focusing microfluidic device. One of the flow-focusing junctions generates alginate hydrogel droplets without the addition of surfactants, while the other junction introduces corn oil with acetic acid, which facilitates

Valentin Braeutigam, Vanessa Wirth, Ingrid Ullmann, Christian Schüßler

The 3D reconstruction of faces gains wide attention in computer vision and is used in many fields of application, for example, animation, virtual reality, and even forensics. This work is motivated by monitoring patients in sleep laboratories. Due to their unique characteristics, sensors from the radar domain have advantages compared to optical sensors, name

Changli Wu, Qi Chen, Jiayi Ji, Haowei Wang

3D Referring Expression Segmentation (3D-RES) aims to segment 3D objects by correlating referring expressions with point clouds. However, traditional approaches frequently encounter issues like over-segmentation or mis-segmentation, due to insufficient emphasis on spatial information of instances. In this paper, we introduce a Rule-Guided Spatial Awareness N

Peter Lowdon, Owe Philipsen

It has long been understood that the inclusion of temperature in the perturbative treatment of quantum field theories leads to complications that are not present at zero temperature. In these proceedings we report on the non-perturbative obstructions that arise, and how these lead to deviations in the predictions of lattice scalar correlation functions in ma

Houssam Razouk, Michael Leitner, Roman Kern

Urban blight is a problem of high interest for planning and policy making. Researchers frequently propose theories about the relationships between urban blight indicators, focusing on relationships reflecting causality. In this paper, we improve on the integration of domain knowledge in the analysis of urban blight by introducing four rules for effective mod

Adam Wróbel, Mikołaj Janusz, Bartosz Zieliński, Dawid Rymarczyk

Deep Learning (DL) models are often black boxes, making their decision-making processes difficult to interpret. This lack of transparency has driven advancements in eXplainable Artificial Intelligence (XAI), a field dedicated to clarifying the reasoning behind DL model predictions. Among these, attribution-based methods such as LRP and GradCAM are widely use

Alexander Valov, Baruch Meerson

The fractional Ornstein-Uhleneck (fOU) process is described by the overdamped Langevin equation $\dot{x}(t)+\gamma x=\sqrt{2 D}\xi(t)$, where $\xi(t)$ is the fractional Gaussian noise with the Hurst exponent $0<H<1$. For $H\neq 1/2$ the fOU process is non-Markovian but Gaussian, and it has either vanishing (for $H<1/2$), or divergent (for $H>1/2$) spectral d

Harshit Bajpai, Gaurav Mittal, Ankik Kumar Giri

Over the past decade, stochastic algorithms have emerged as scalable and efficient tools for solving large-scale ill-posed inverse problems by randomly selecting subsets of equations at each iteration. However, due to the ill-posedness and measurement noise, these methods often suffer from oscillations and semi-convergence behavior, posing challenges in achi

Kirill Boguslavski, Paul Hotzy, David I. Müller

Complex Langevin (CL) is a computational method to circumvent the numerical sign problem with applications in finite-density quantum chromodynamics and the real-time dynamics of quantum field theories. It has long been known that, depending on the simulated system, CL does not always converge correctly. In this work, we provide numerical evidence that the su

Ziqian Zou, Conghao Wong, Beihao Xia, Qinmu Peng

Understanding and anticipating human movement has become more critical and challenging in diverse applications such as autonomous driving and surveillance. The complex interactions brought by different relations between agents are a crucial reason that poses challenges to this task. Researchers have put much effort into designing a system using rule-based or

Peter Fischer, Michael Ritzert, Thomas Kerschenbauer

Modern PET scanners based on scintillating crystals use solid state photo detectors for light readout. The small area of these devices is beneficial for spatial resolution, but also leads to a large number of electronic channels to be read out, mostly by application specific integrated circuits (ASICs) containing amplification, noise reduction, hit finding,

Martin Křížek, Matouš Vrba, Antonella Barišić Kulaš, Stjepan Bogdan

We propose a new approach to visual perception for relative localization of agents within large-scale swarms of UAVs. Inspired by biological perception utilized by schools of sardines, swarms of bees, and other large groups of animals capable of moving in a decentralized yet coherent manner, our method does not rely on detecting individual neighbors by each

Osamu Fujino, Hiroshi Sato

For every complete toric variety, there exists a projective toric variety which is isomorphic to it in codimension one. In this paper, we show that every smooth non-projective complete toric threefold of Picard number at most five becomes projective after a finite succession of flops or anti-flips.

Junichiro Hagiwara, Toshihiko Nishimura, Takanori Sato, Yasutaka Ogawa

Multiple-input multiple-output (MIMO) technology is essential for the optimal functioning of next-generation wireless networks; however, enhancing its signal-detection performance for improved spectral efficiency is challenging. Here, we propose an approach that transforms the discrete MIMO detection problem into a continuous problem while leveraging the eff