July 2023 arXiv papers — page 39

Romy Müller, Marcel Dürschmidt, Julian Ullrich, Carsten Knoll

Deep Learning models like Convolutional Neural Networks (CNN) are powerful image classifiers, but what factors determine whether they attend to similar image areas as humans do? While previous studies have focused on technological factors, little is known about the role of factors that affect human attention. In the present study, we investigated how the tas

Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc Van Gool

The local road network information is essential for autonomous navigation. This information is commonly obtained from offline HD-Maps in terms of lane graphs. However, the local road network at a given moment can be drastically different than the one given in the offline maps; due to construction works, accidents etc. Moreover, the autonomous vehicle might b

Md Asif Jalal, Pablo Peso Parada, Jisi Zhang, Karthikeyan Saravanan

Smart devices serviced by large-scale AI models necessitates user data transfer to the cloud for inference. For speech applications, this means transferring private user information, e.g., speaker identity. Our paper proposes a privacy-enhancing framework that targets speaker identity anonymization while preserving speech recognition accuracy for our downstr

Sunil Malik, Ka Ho Yuen, Huirong Yan

Magnetic fields are ubiquitous in the interstellar medium, including extended objects such as supernova remnants and diffuse halos around Pulsars. Its turbulent characteristics govern the diffusion of cosmic rays and the multi-wavelength emission from PWNe. However, the geometry and turbulence nature of the magnetic fields in the ambient region of PWN is sti

Donato Farina, Bilal Benazout, Federico Centrone, Antonio Acin

We discuss exchange scenario's thermodynamic uncertainty relations for the work done on a two-qubit entangled nonequilibrium steady state obtained by coupling the two qubits and putting each of them in weak contact with a thermal bath. In this way we investigate the use of entangled nonequilibrium steady states as end-points of thermodynamic cycles. In this

Sajjad Mohammadi

Let $a$ and $b$ be two positive integers such that $a, b < n$. We denote the inclusion $\Sigma \mathbb{C}P^a\rightarrow SU(n)$ by $\varepsilon_{a,n}$. Also, let $m$ and $n$ be two positive integers such that $m < n$. This article has two parts. In the first part, we will study the order of the Samelson product $\langle \varepsilon_{a,n}, \varepsilon_{b,n}\ra

Skyler Wu, Eric Meng Shen, Charumathi Badrinath, Jiaqi Ma

Chain-of-thought (CoT) prompting has been shown to empirically improve the accuracy of large language models (LLMs) on various question answering tasks. While understanding why CoT prompting is effective is crucial to ensuring that this phenomenon is a consequence of desired model behavior, little work has addressed this; nonetheless, such an understanding i

F. Malara, S. Perri, J. Giacalone, G. Zimbardo

Context. Recent spacecraft observations in the inner heliosphere have revealed the presence of local Alfvenic reversals of the magnetic field, while the field magnitude remains almost constant. They are called magnetic switchbacks and are very common in the plasma environment close to the Sun explored by the Parker Solar Probe satellite. Aims. A simple numer

Cheeun Hong, Kyoung Mu Lee

Although quantization has emerged as a promising approach to reducing computational complexity across various high-level vision tasks, it inevitably leads to accuracy loss in image super-resolution (SR) networks. This is due to the significantly divergent feature distributions across different channels and input images of the SR networks, which complicates t

Andrzej Biborski, Michał Zegrodnik, Paweł Wójcik, Michał P. Nowak

We study theoretically the electronic properties of the artificial quantum dot honeycomb lattice defined in a two-dimensional electron gas, focusing on the possibility of achieving a regime in which electronic correlations play a dominant role. At first we establish a non-interacting model compatible with recently studied experimentally devices. According to

Andrei V. Faminskii

An initial-boundary value problem with one boundary condition is considered for the higher order nonlinear Schr\"odinger equation. It is assumed that either the boundary condition is homogeneous or the nonlinearity in the equation is quadratic. Results on existence, uniqueness and continuous dependence on input data of global weak solutions are obtained.

Soojin Cho, JiSun Huh, Seonjeong Park

A \emph{Hessenberg Schubert variety} is an irreducible component of the intersection of a Schubert variety and a Hessenberg variety, defined as the closure of a Schubert cell intersected with the Hessenberg variety. We consider the smoothness of Hessenberg Schubert varieties of regular semisimple Hessenberg varieties of type $A$ in this paper. We consider th

Chao Huang, Diptesh Das, Koji Tsuda

Random forest is effective for prediction tasks but the randomness of tree generation hinders interpretability in feature importance analysis. To address this, we proposed DT-Sampler, a SAT-based method for measuring feature importance in tree-based model. Our method has fewer parameters than random forest and provides higher interpretability and stability f

Philip Amortila, Nan Jiang, Csaba Szepesvári

Theoretical guarantees in reinforcement learning (RL) are known to suffer multiplicative blow-up factors with respect to the misspecification error of function approximation. Yet, the nature of such \emph{approximation factors} -- especially their optimal form in a given learning problem -- is poorly understood. In this paper we study this question in linear

Rajarshi Roy, Kaustav Bhattacharjee, Satya Prakash Pati, Korak Biswas

The observation of room temperature ferromagnetism along with a low temperature paramagnetic counterpart in undoped Cu-Cu2O-rGO nanocomposite was demonstrated. A phenomenological approach was taken to explain the observations based on 3D Ising model for arbitrary spins generated due to Cu vacancy in the Cu2O system preferably at the interface.

R. Alarcon, R. Beck, J. C. Bernauer, M. Broering

We propose a new measurement of the ratio of positron-proton to electron-proton elastic scattering at DESY. The purpose is to determine the contributions beyond single-photon exchange, which are essential for the Quantum Electrodynamic (QED) description of the most fundamental process in hadronic physics. By utilizing a 20 cm long liquid hydrogen target in c

Ryo Ikehata, Xiaoyan Li

We consider the Cauchy problems in the whole space for wave equations with higher derivative terms. We derive sharp growth estimates of the $L^2$-norm of the solution itself in the case of the space 1, 2 dimensions. By imposing the weighted $L^1$-initial velocity, we can get the lower and upper bound estimates of the solution itself. In three or more dimensi

Martin Waltz, Niklas Paulig, Ostap Okhrin

This paper proposes a realistic modularized framework for controlling autonomous surface vehicles (ASVs) on inland waterways (IWs) based on deep reinforcement learning (DRL). The framework improves operational safety and comprises two levels: a high-level local path planning (LPP) unit and a low-level path following (PF) unit, each consisting of a DRL agent.

Martin W. Liebeck, Gary M. Seitz, Donna M. Testerman

We continue our work (started in ``Multiplicity-free representations of algebraic groups", arXiv:2101.04476), on the program of classifying triples $(X,Y,V)$, where $X,Y$ are simple algebraic groups over an algebraically closed field of characteristic zero with $X<Y$, and $V$ is an irreducible module for $Y$ such that the restriction $V\downarrow X$ is multi

Alerksandr A. Kurilovich, Vladimir N. Mantsevich, Aleksey V. Chechkin, Vladimir V. Palyulin

We show how two different mobile-immobile type models explain the observation of negative diffusion of excitons reported in experimental studies in quasi-two-dimensional semiconductor systems. The main reason for the effect is the initial trapping and a delayed release of free excitons in the area close to the original excitation spot. The density of trapped

Humian Zhou, Chui-Zhen Chen, Qing-Feng Sun, X. C. Xie

The quantum Hall effect (QHE), which was observed in 2D electron gas under an external magnetic field, stands out as one of the most remarkable transport phenomena in condensed matter. However, a long standing puzzle remains regarding the observation of the relativistic quantum Hall effect (RQHE). This effect, predicted for a single 2D Dirac cone immersed in

Stefanie Zbinden

We provide examples of classical small-cancellation groups which have non-sigma-compact Morse boundary. These are first known examples of groups with non-sigma-compact Morse boundary. Some small-cancellation groups do have sigma-compact Morse boundary, so this property distinguishes quasi-isometry types of small-cancellation groups. In fact, we give a comple

Alberto Richtsfeld

We carry the index theory for manifolds with boundary of B\"ar and Ballmann over to first order differential operators on metric graphs. This approach results in a short proof for the index of such operators. Then the self-adjoint extensions and the spectrum of the Dirac operator on the complex line bundle are studied. We also introduce two types of boundary

Xutian Deng, Junnan Jiang, Wen Cheng, Miao Li

As medical ultrasound is becoming a prevailing examination approach nowadays, robotic ultrasound systems can facilitate the scanning process and prevent professional sonographers from repetitive and tedious work. Despite the recent progress, it is still a challenge to enable robots to autonomously accomplish the ultrasound examination, which is largely due t

Sergey Tridenski, Anelia Somekh-Baruch

For the discrete-time AWGN channel with a power constraint, we give an alternative derivation of Shannon's sphere-packing upper bound on the optimal block error exponent and prove for the first time an analogous lower bound on the optimal correct-decoding exponent. The derivations use the method of types with finite alphabets of sizes depending on the block

Zhenjie Yan, Jacquelyn Ho, Yue-Hui Lu, Stuart J. Masson

We realize collective enhancement and suppression of light scattered by an array of tweezer-trapped $^{87}$Rb atoms positioned within a strongly coupled Fabry-P\'{e}rot optical cavity. We illuminate the array with light directed transverse to the cavity axis, in the low saturation regime, and detect photons scattered into the cavity. For an array with intege

A. I. Agafonov

The invariant mass of free particles is used to derive a bound-state equation for the hydrogen atom at rest. This equation has the well-known solutions for the single-particle states. Existence of two-particle bound states, for which the electron and proton have different scales of intraatomic motions, is predicted. Two two-particle states are obtained numer

Chen Zheng, Huan Zhang, Yan Zhao, Yuxuan Lai

Coherence is a crucial aspect of evaluating text readability and can be assessed through two primary factors when evaluating an essay in a scoring scenario. The first factor is logical coherence, characterized by the appropriate use of discourse connectives and the establishment of logical relationships between sentences. The second factor is the appropriate

José Balduque, Rafael Sánchez

Three-terminal coherent conductors are able to perform as quantum thermocouples when the heat absorbed from one terminal is transformed into useful power in the other two. Allowing for a phase coherent coupling to the heat source, we introduce a way to control and improve the thermoelectric response via quantum interference. A simple setup composed of a scan

Jingyu Ke, Hongfei Fu, Hongming Liu, Zhouyue Sun

In the verification of loop programs, disjunctive invariants are essential to capture complex loop dynamics such as phase and mode changes. In this work, we develop a novel approach for the automated generation of affine disjunctive invariants for affine while loops via Farkas' Lemma, a fundamental theorem on linear inequalities. Our main contributions are t

Vesna Iršič, Sandi Klavžar, Elif Tan

In this paper, generalized Pell graphs $\Pi _{n,k}$, $k\ge 2$, are introduced. The special case of $k=2$ are the Pell graphs $\Pi _{n}$ defined earlier by Munarini. Several metric, enumerative, and structural properties of these graphs are established. The generating function of the number of edges of $\Pi _{n,k}$ and the generating function of its cube poly

Shyam Nandan Rai, Fabio Cermelli, Dario Fontanel, Carlo Masone

Anomaly segmentation is a critical task for driving applications, and it is approached traditionally as a per-pixel classification problem. However, reasoning individually about each pixel without considering their contextual semantics results in high uncertainty around the objects' boundaries and numerous false positives. We propose a paradigm change by shi

Shengyue Yao, Jingru Yu, Yi Yu, Jia Xu

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability sim

C. S. Dias, J. C. Neves, M. M. Telo da Gama, E. del Gado

Identifying the necessary conditions for the onset of rigidity in a gel remains a challenge. It has been suggested that local particle coordination could be used to establish such conditions, but rigid gels occur for various coordination numbers. Combining simulations, oscillatory rheology, and a percolation analysis, for particles where the valence can be c

Hong Huang, Xinyu Lei, Tao Xiang

Machine learning makes multimedia data (e.g., images) more attractive, however, multimedia data is usually distributed and privacy sensitive. Multiple distributed multimedia clients can resort to federated learning (FL) to jointly learn a global shared model without requiring to share their private samples with any third-party entities. In this paper, we sho

Dmitrii Semenok

In the last six years (2015-2021), many superconducting hydrides with critical temperatures $\textit{T}$$_C$ of up to 253 K, a record for today, have been discovered. Now, a special field of hydride superconductivity at ultrahigh pressures has developed. For the most part, the properties of superhydrides are well described by the Migdal-Eliashberg theory of

Ryota Nakai, Kentaro Nomura

Higher-order topological phases are gapped phases of matter that host gapless corner or hinge modes. For the case of superconductors, corner or hinge modes are gapless Majorana modes or Majorana zero modes. To construct 3d higher-order topological superconductors, we consider a topological-insulator/superconductor multilayer under in-plane Zeeman coupling. W

Ranjuna M K, Jayakumar Balakrishnan

Recent theoretical works on two-dimensional molybdenum disulfide, MoS$_2$, with sulfur vacancies predict that the suppression of thermal transport in MoS$_2$ by point defects is more prominent in monolayers and becomes negligible as layer number increases. Here, we investigate experimentally the thermal transport properties of two-dimensional molybdenum disu

Zhiwen Shao, Yuchen Su, Yong Zhou, Fanrong Meng

Contour based scene text detection methods have rapidly developed recently, but still suffer from inaccurate frontend contour initialization, multi-stage error accumulation, or deficient local information aggregation. To tackle these limitations, we propose a novel arbitrary-shaped scene text detection framework named CT-Net by progressive contour regression

Kinfung Ngan, Yuan Zhan, Constantin Dory, Jelena Vučković

Diamond has emerged as a leading host material for solid-state quantum emitters, quantum memories, and quantum sensors. However, the challenges in fabricating photonic devices in diamond have limited its potential for use in quantum technologies. While various hybrid integration approaches have been developed for coupling diamond color centers with photonic

Jan Hartman, Assaf Klein, Davorin Kopič, Natalia Silberstein

In this work, we introduce the notion of Context-Based Prediction Models. A Context-Based Prediction Model determines the probability of a user's action (such as a click or a conversion) solely by relying on user and contextual features, without considering any specific features of the item itself. We have identified numerous valuable applications for this m

Yael Naze, Jan Robrade

Massive stars are known X-ray emitters and those belonging to the Be category are no exception. One type of X-ray emission even appears specific to that category, the gamma Cas phenomenon. Its actual incidence has been particularly difficult to assess. Thanks to four semesters of sky survey data taken by SRG (Spectrum Roentgen Gamma)/eROSITA, we revisit the

François Hamel, Mingmin Zhang

This paper is concerned with the existence of transition fronts for a one-dimensional twopatch model with KPP reaction terms. Density and flux conditions are imposed at the interface between the two patches. We first construct a pair of suitable super-and subsolutions by making full use of information of the leading edges of two KPP fronts and gluing them th

Lorenzo Caprini, Umberto Marini Bettolo Marconi, Hartmut Löwen

We study the collective vibrational excitations of crystals under out-of-equilibrium steady conditions that give rise to entropy production. Their excitation spectrum comprises equilibrium-like phonons of thermal origin and additional collective excitations called entropons because each of them represents a mode of spectral entropy production. Entropons coex

Abhi Modak

Global observables such as the pseudorapidity distributions of particle multiplicities in the final state are crucial to shed light into the physics processes involved in hadronic collisions. In proton$-$lead (p$-$Pb) collisions at Large Hadron Collider (LHC) energies, such measurements provide an important baseline to understand lead$-$lead (Pb$-$Pb) result

Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa

This work studies post-training parameter quantization in large language models (LLMs). We introduce quantization with incoherence processing (QuIP), a new method based on the insight that quantization benefits from $\textit{incoherent}$ weight and Hessian matrices, i.e., from the weights being even in magnitude and the directions in which it is important to

Fuquan Fang, Wen Shen

Geometry of manifolds with positive sectional curvature has been a central object dates back to the beginning of Riemannian geometry. Up to homeomorphism, there are only finitely many examples of simply connected positively curved manifolds in all dimensions except in dimension 7 and 13, namely, the Aloff-Wallach spaces and the Eschenburg spaces in dimension

Nils A. Nilsson, Christophe Le-Poncin Lafitte

Current searches for signals of departures from the fundamental symmetries of General Relativity using gravitational waves are largely dominated by propagation effects like dispersion and birefringence from highly dynamic sources such as coalescing binary-black holes and neutron stars. In this paper we take steps towards probing the nature of spacetime symme

Claudia König, Axel Munk, Frank Werner

We develop a multiscale scanning method to find anomalies in a $d$-dimensional random field in the presence of nuisance parameters. This covers the common situation that either the baseline-level or additional parameters such as the variance are unknown and have to be estimated from the data. We argue that state of the art approaches to determine asymptotica

Chuanyu Luo, Nuo Cheng, Sikun Ma, Jun Xiang

Common deep learning models for 3D environment perception often use pillarization/voxelization methods to convert point cloud data into pillars/voxels and then process it with a 2D/3D convolutional neural network (CNN). The pioneer work PointNet has been widely applied as a local feature descriptor, a fundamental component in deep learning models for 3D perc

Helmi Hankimaa, Olli Herrala, Fabricio Oliveira, Jaan Tollander de Balsch

In this paper, we propose novel mixed-integer linear programming (MIP) formulations to model decision problems posed as influence diagrams. We also present a novel heuristic that can be employed to warm start the MIP solver, as well as provide heuristic solutions to more computationally challenging problems. We provide computational results showcasing the su

Yunqiu Shao, Haitao Li, Yueyue Wu, Yiqun Liu

Legal case retrieval is a special Information Retrieval~(IR) task focusing on legal case documents. Depending on the downstream tasks of the retrieved case documents, users' information needs in legal case retrieval could be significantly different from those in Web search and traditional ad-hoc retrieval tasks. While there are several studies that retrieve

Zexian Guo, Bobo Liu, Yu Gao, Ang Yang

Quantum many-body scar is a recently discovered phenomenon weakly violating eigenstate thermalization hypothesis, and it has been extensively studied across various models. However, experimental realizations are mainly based on constrained models such as the $PXP$ model. Inspired by recent experimental observations on the superconducting platform in Refs.~[N

Tiansi Dong, Rafet Sifa

Word Sense Disambiguation (WSD) is one of the hardest tasks in natural language understanding and knowledge engineering. The glass ceiling of 80% F1 score is recently achieved through supervised deep-learning, enriched by a variety of knowledge graphs. Here, we propose a novel neurosymbolic methodology that is able to push the F1 score above 90%. The core of

Sascha Heußen, David F. Locher, Markus Müller

Logical qubits can be protected from decoherence by performing QEC cycles repeatedly. Algorithms for fault-tolerant QEC must be compiled to the specific hardware platform under consideration in order to practically realize a quantum memory that operates for in principle arbitrary long times. All circuit components must be assumed as noisy unless specific ass

Youqiang Zheng, Li Xiao, Weiping Tu, Yuhong Yang

Recently, speech codecs based on neural networks have proven to perform better than traditional methods. However, redundancy in traditional parameter quantization is visible within the codec architecture of combining the traditional codec with the neural vocoder. In this paper, we propose a novel framework named CQNV, which combines the coarsely quantized pa

Junbin Fang, Canjian Jiang, You Jiang, Puxi Lin

Although face recognition starts to play an important role in our daily life, we need to pay attention that data-driven face recognition vision systems are vulnerable to adversarial attacks. However, the current two categories of adversarial attacks, namely digital attacks and physical attacks both have drawbacks, with the former ones impractical and the lat

John P. Nelson, Justin B. Biddle, Philip Shapira

This paper undertakes a systematic review of relevant extant literature to consider the potential societal implications of the growth of AI in manufacturing. We analyze the extensive range of AI applications in this domain, such as interfirm logistics coordination, firm procurement management, predictive maintenance, and shop-floor monitoring and control of

Thomas Lang, Samuel T. Spencer, Alison M. W. Mitchell

The number of satellites launched into Earth's orbit has almost tripled in the last three years due to the increasing commercialisation of space. Multiple satellite constellations, consisting of over 400,000 individual satellites, have either been partially launched or are proposed for launch in the near future. Many of these satellites are highly reflective

Stella Civelli, Enrico Forestieri, Marco Secondini

Probabilistic shaping is a pragmatic approach to improve the performance of coherent optical fiber communication systems. In the nonlinear regime, the advantages offered by probabilistic shaping might increase thanks to the opportunity to obtain an additional nonlinear shaping gain. Unfortunately, the optimization of conventional shaping techniques, such as

Piotr Lebiedowicz, Otto Nachtmann, Antoni Szczurek

We investigate the photon emission in pion-pion and pion-proton scattering in the soft-photon limit where the photon energy $\omega \to 0$. The expansions of the $\pi^{-} \pi^{0} \to \pi^{-} \pi^{0} \gamma$ and the $\pi^{\pm} p \to \pi^{\pm} p \gamma$ amplitudes, satisfying the energy-momentum relations, to the orders $\omega^{-1}$ and $\omega^{0}$ are deriv

Yi Yu, Wenlian Lu, Boyu Chen

We propose theoretical analyses of a modified natural gradient descent method in the neural network function space based on the eigendecompositions of neural tangent kernel and Fisher information matrix. We firstly present analytical expression for the function learned by this modified natural gradient under the assumptions of Gaussian distribution and infin

Anirban Banerjee, Arpita Das

Here, we define a subdivision operation for a hypergraph and compute all the eigenvalues of the subdivision of regular and certain non-regular hypergraphs. In non-regular hypergraphs, we investigate the power of regular graphs, various types of hyperflowers, and the squid-like hypergraph. Using our subdivision operation, we also show how to construct non-reg

Richard Fechner, Jens Dörpinghaus, Robert Rockenfeller, Jennifer Faber

Background: Biomedical data are usually collections of longitudinal data assessed at certain points in time. Clinical observations assess the presences and severity of symptoms, which are the basis for description and modeling of disease progression. Deciphering potential underlying unknowns solely from the distinct observation would substantially improve th

Xueli Bai, Dong-Hui Li, Lei Wu, Jiefeng Xu

The Perron-Frobenius theorem says that the spectral radius of an irreducible nonnegative tensor is the unique positive eigenvalue corresponding to a positive eigenvector. With this in mind, the purpose of this paper is to find the spectral radius and its corresponding positive eigenvector of an irreducible nonnegative symmetric tensor. By transferring the ei

Diana Riazi, Giacomo Livan

We develop a model of opinion dynamics where agents in a social network seek to learn a ground truth among a set of competing hypotheses. Agents in the network form private beliefs about such hypotheses by aggregating their neighbors' publicly stated beliefs, in an iterative fashion. This process allows us to keep track of scenarios where private and public

Gyuyeong Kim

Spawning duplicate requests, called cloning, is a powerful technique to reduce tail latency by masking service-time variability. However, traditional client-based cloning is static and harmful to performance under high load, while a recent coordinator-based approach is slow and not scalable. Both approaches are insufficient to serve modern microsecond-scale

Nghia T. Nguyen, Long Luu, Phuong L. Vo, Thi Thanh Sang Nguyen

Dynamic adaptive streaming over HTTP (DASH) has been widely used in video streaming recently. In DASH, the client downloads video chunks in order from a server. The rate adaptation function at the video client enhances the user's quality-of-experience (QoE) by choosing a suitable quality level for each video chunk to download based on the network condition.

Sindhu D G, Akhilesh Ranjan, Hemwati Nandan

In recent years, many tetraquarks and pentaquarks have been discovered by various experimental groups and X(3872), Zc(3900), X(4430), P + c (4312), P + c (4457) are some of the interesting observed tetraquark and pentaquark states. The Regge trajectories of some such states are studied in view of the flux tube model of hadrons with finite quark masses. The e

Jun-Sik Sin, Nam-Il Ri, Hyon-Chol Kim, Sin-Hyok Hyon

We theoretically study transient electroosmotic flow of general Maxwell fluids through polyelectrolyte grafted nanochannel with a layered distribution of charges. By applying the method of Laplace transform, we semi-analytically obtain transient electroosmotic flow from Cauchy momentum equation and Maxwell constitutive equation. For nanochannels grafted with

Sicong Tang, Guangyuan Wang, Qing Ran, Lingzhi Li

We present a novel method for reconstructing clothed humans from a sparse set of, e.g., 1 to 6 RGB images. Despite impressive results from recent works employing deep implicit representation, we revisit the volumetric approach and demonstrate that better performance can be achieved with proper system design. The volumetric representation offers significant a

Bruno Kahn

We study the injectivity of the cycle class map with values in Jannsen's continuous \'etale cohomology, by using refinements that go through \'etale motivic cohomology and the ``tame'' version of Jannsen's cohomology. In particular, we use this to show that the Tate and the Beilinson conjectures imply that its kernel is torsion in positive characteristic, an

Salvatore Capozziello, Vittorio De Falco, Carmen Ferrara

In the framework of metric-affine gravity, we consider the role of the boundary term in Symmetric Teleparallel Gravity assuming $f(Q,B)$ models where $f$ is a smooth function of the non-metricity scalar $Q$ and the related boundary term $B$. Starting from a variational approach, we derive the field equations and compare them with respect to those of $f(Q)$ g

Guillermo Díez, Laura Ares, Alfredo Luis

Beam splitters are not-free operations with regard to quantum coherence. As a consequence, they can create coherence from both coherent and incoherent states. We investigate the increase in coherence produced by cascades of beam splitters. To this end, we construct two different configurations and analyze different sequences of input states.

Sreelakshmi M, Akhilesh Ranjan

In the past twenty years, hadron spectroscopy has made immense progress. Experimental facilities have observed different multiquark states during these years. There are different models and phenomenological potentials to study the nature of interquark interaction. In this work, we have reviewed different quark potentials and models used in hadron spectroscop

Albert Cabot, Federico Carollo, Igor Lesanovsky

A boundary time-crystal is a quantum many-body system whose dynamics is governed by the competition between coherent driving and collective dissipation. It is composed of $N$ two-level systems and features a transition between a stationary phase and an oscillatory one. The fact that the system is open allows to continuously monitor its quantum trajectories a

Wittaya Kanchanapusakit, Pattarapon Tanalikhit

We consider a heavy external object moving in an ideal gas of light particles. Collisions with the gas particles transfer momentum to the object, leading to a force that is proportional to the object's velocity but in the opposite direction. In an ideal classical gas at temperature $T$, the force acting on the object is proportional to $\sqrt{T}$. Quantum st

Yili Chen, Zhengyu Li, Zheng Wan, Hui Yu

AI-driven drug design relies significantly on predicting molecular properties, which is a complex task. In current approaches, the most commonly used feature representations for training deep neural network models are based on SMILES and molecular graphs. While these methods are concise and efficient, they have limitations in capturing complex spatial inform

Serena Landers, Arkady Kurnosov, William Tuxbury, Ilya Vitebskiy

A stationary inflection point (SIP) in the Bloch dispersion relation of a periodic waveguide is an exceptional point degeneracy where three Bloch eigenmodes coalesce forming the so-called frozen mode with a divergent amplitude and vanishing group velocity of its propagating component. We have developed a theoretical framework to study the time evolution of w

Kosuke Nishiwaki, Katsuaki Asano, Kohta Murase

A fraction of merging galaxy clusters host diffuse radio emission in their central region, termed as a giant radio halo (GRH). The most promising mechanism of GRHs is the re-acceleration of non-thermal electrons and positrons by merger-induced turbulence. However, the origin of these seed leptons has been under debate, and either protons or electrons can be

Chinmay Vilas Samak, Tanmay Vilas Samak, Venkat Krovi

The engineering community currently encounters significant challenges in the development of intelligent transportation algorithms that can be transferred from simulation to reality with minimal effort. This can be achieved by robustifying the algorithms using domain adaptation methods and/or by adopting cutting-edge tools that help support this objective sea

Andrés Carnero Bravo

Given a graph $G$, we define a filtration of simplicial complexes associated to $G$, $\mathcal{F}_0(G)\subseteq\mathcal{F}_1(G)\subseteq\cdots\subseteq\mathcal{F}_\infty(G)$ where the first complex is the independence complex and the last the complex is formed by the acyclic sets of vertices. We prove some properties of this filtration and we calculate the h

Stephen Chung

A biologically plausible method for training an Artificial Neural Network (ANN) involves treating each unit as a stochastic Reinforcement Learning (RL) agent, thereby considering the network as a team of agents. Consequently, all units can learn via REINFORCE, a local learning rule modulated by a global reward signal, which aligns more closely with biologica

Chengsong Huang, Qian Liu, Bill Yuchen Lin, Tianyu Pang

Low-rank adaptations (LoRA) are often employed to fine-tune large language models (LLMs) for new tasks. This paper investigates LoRA composability for cross-task generalization and introduces LoraHub, a simple framework devised for the purposive assembly of LoRA modules trained on diverse given tasks, with the objective of achieving adaptable performance on

Neeraj Jain, Jörg Büchner, Miroslav Bárta, Radoslav Bučík

Solar energetic particles (SEPs) in the energy range 10s KeV/nucleon-100s MeV/nucleon originate from Sun. Their high flux near Earth may damage the space borne electronics and generate secondary radiations harmful for the life on Earth and thus understanding their energization on Sun is important for space weather prediction. Impulsive (or ${}^{3}$He-rich) S

Vassilios Yfantis, Achim Wagner, Martin Ruskowski

The use of distributed optimization in machine learning can be motivated either by the resulting preservation of privacy or the increase in computational efficiency. On the one hand, training data might be stored across multiple devices. Training a global model within a network where each node only has access to its confidential data requires the use of dist

Praveen Joshi, Chandra Thapa, Mohammed Hasanuzzaman, Ted Scully

Distributed collaborative machine learning (DCML) is a promising method in the Internet of Things (IoT) domain for training deep learning models, as data is distributed across multiple devices. A key advantage of this approach is that it improves data privacy by removing the necessity for the centralized aggregation of raw data but also empowers IoT devices

V. Venkatesha, Chaitra Chooda Chalavadi, N. S. Kavya, P. K. Sahoo

In the present manuscript, we study traversable wormhole solutions in the background of extended symmetric teleparallel gravity with matter coupling. With the anisotropic matter distribution we probe the wormhole geometry for two different gravity models. Primarily, we consider the linear model $ f(Q,T) =Q + 2 \, \xi \,T$. Firstly, we presume a logarithmic f

Teng Fei

Generalized Calabi-Gray manifolds are non-K\"ahler complex manifolds with very explicit geometry yet not being homogeneous. In this note, we demonstrate that how generalized Calabi-Gray manifolds can be used to answer some questions in non-K\"ahler geometry.

T. Wang, H. X. Zhou, Q. Fang, Y. N. Han

Extreme events generated by complex systems have been intensively studied in many fields due to their great impact on scientific research and our daily lives. However, their prediction is still a challenge in spite of the tremendous progress that model-free machine learning has brought to the field. We experimentally generate, and theoretically model, extrem

Anirban Roy Chowdhury, Ashis Saha, Sunandan Gangopadhyay

Two different entanglement measures for mixed states, namely, the entanglement of purification and entanglement negativity has been holographically computed for the dipole deformed supersymmetric Yang-Mills (SYM) theory by considering its gravity dual. The dipole deformation induces non-locality in the SYM theory which is characterized by a length-scale $a=\

Payel Nandi, C. S. Stalin, D. J. Saikia, Rogemar A. Riffel

Black hole driven outflows in galaxies hosting active galactic nuclei (AGN) may interact with their interstellar medium (ISM) affecting star formation. Such feedback processes, reminiscent of those seen in massive galaxies, have been reported recently in some dwarf galaxies. However, such studies have usually been on kiloparsec and larger scales and our know

Emre Sen

In the derived category of mod-KQ for Dynkin quiver Q, we construct a full subcategory in a canonical way, so that its endomorphism algebra is a higher Auslander algebra of global dimension $3k+2$ for any $k\geq 1$. Furthermore, we extend this construction for higher analogues of representation finite and hereditary algebras. Specifically, if $M$ is an n-clu

Rishi Advani, Abolfazl Asudeh

The maximum independent set problem is a classical NP-hard problem in theoretical computer science. In this work, we study a special case where the family of graphs considered is restricted to intersection graphs of sets of axis-aligned hyperrectangles and the input is provided in an online fashion. We prove results for several adversary models, classes of h

Yuichiro Marui, Hiroshi Kori

Previous studies on oscillator populations with two-simplex interaction have reported novel phenomena such as discontinuous desynchronization transitions and multistability of synchronized states. However, the noise effect is not well understood. Here, we study a higher-order network of noisy oscillators with generic interactions consisting of one-simplex an

Qian Wu, Ruixuan Xiao, Kaixin Xu, Jingcheng Ni

Gait recognition aims to distinguish different walking patterns by analyzing video-level human silhouettes, rather than relying on appearance information. Previous research on gait recognition has primarily focused on extracting local or global spatial-temporal representations, while overlooking the intrinsic periodic features of gait sequences, which, when

Nikolai Lebovka, Mykhaylo Petryk, Mykhailo Tatochenko, Nikolai Vygornitskii

The different variants of two-stage random sequential adsorption (RSA) models for packing of disks and discorectangles on a two-dimensional (2D) surface were investigated. In the SD model, the discorectangles were first deposited and then the disks were added. In the DS model, the disks were first deposited and then discorectangles were added. At the first s

Abdul Basit, Alexander Clifton, Paul Horn

Motivated by classical work of Alon and F\"uredi, we introduce and address the following problem: determine the minimum number of affine hyperplanes in $\mathbb{R}^d$ needed to cover every point of the triangular grid $T_d(n) := \{(x_1,\dots,x_d)\in\mathbb{Z}_{\ge 0}^d\mid x_1+\dots+x_d\le n-1\}$ at least $k$ times. For $d = 2$, we solve the problem exactly

Stephen Chung

A biologically plausible method for training an Artificial Neural Network (ANN) involves treating each unit as a stochastic Reinforcement Learning (RL) agent, thereby considering the network as a team of agents. Consequently, all units can learn via REINFORCE, a local learning rule modulated by a global reward signal, which aligns more closely with biologica

Omar. Mustafa, Faizuddin Ahmed

We revisit and discuss the KG-oscillator in the $(1+2)$-dimensional G\"{u}rses space-time studied in (F. Ahmed, Ann. Phys. (N. Y.) 404 (2019) 1). The modified oscillator frequency {\it i.e.,} $\tilde{\omega}^{2}=(\Omega^{2}\,E^{2}+\eta^{2})$ appeared in the eigenvalue equation is an energy-dependent parameter, and consequently, the results are accurately rep