July 2023 arXiv papers — page 12

Rafał Filipów, Adam Kwela

Let $\mathcal{I}$ be an ideal on $\omega$. For $f,g\in\omega^\omega$ we write $f \leq_{\mathcal{I}} g$ if $f(n) \leq g(n)$ for all $n\in\omega\setminus A$ with some $A\in\mathcal{I}$. Moreover, we denote $\mathcal{D}_{\mathcal{I}}=\{f\in\omega^\omega: f^{-1}[\{n\}]\in\mathcal{I} \text{ for every $n\in \omega$}\}$ (in particular, $\mathcal{D}_{Fin}$ denotes t

Kamiel Janssens, Michiko Ueda

Large-scale international scientific collaborations are increasingly common in the field of STEM (Science, Technology, Engineering, and Mathematics). However, little is known about the well-being of the members participating in these `big science' collaborations, which can present unique challenges due to the scale of their work. We conducted a survey among

László Székelyhidi

In our former paper we introduced the concept of localisation of ideals in the Fourier algebra of a locally compact Abelian group. It turns out that localisability of a closed ideal in the Fourier algebra is equivalent to the synthesisability of the annihilator of that closed ideal which corresponds to this ideal in the measure algebra. This equivalence prov

Maria C. Schutte, Leslie Hebb, John P. Wisniewski, Caleb I. Canas

Using simultaneous multi-filter observations during the transit of an exoplanet around a K dwarf star, we determine the temperature of a starspot through modeling the radius and position with wavelength-dependent spot contrasts. We model the spot using the starspot modeling program STarSPot (STSP), which uses the transiting companion as a knife-edge probe of

Rajendra Bhatia, Tanvi Jain

This article has two interpenetrating motifs. One is an exposition of some major ideas and techniques behind the use of block matrices, and especially their positivity properties. This is done by focussing on one major problem: characterisation of operators whose numerical radius is bounded by one. So, the article could serve as an introduction to that topic

Yuanfeng Song, Xuefang Zhao, Raymond Chi-Wing Wong

Data visualization (DV) has become the prevailing tool in the market due to its effectiveness into illustrating insights in vast amounts of data. To lower the barrier of using DVs, automatic DV tasks, such as natural language question (NLQ) to visualization translation (formally called text-to-vis), have been investigated in the research community. However,

Shun Lei, Yixuan Zhou, Liyang Chen, Zhiyong Wu

Expressive speech synthesis is crucial for many human-computer interaction scenarios, such as audiobooks, podcasts, and voice assistants. Previous works focus on predicting the style embeddings at one single scale from the information within the current sentence. Whereas, context information in neighboring sentences and multi-scale nature of style in human s

Laura Shou, Ramon van Handel

We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization transition near the edge of the spectrum: when $d\gg\log N$ the random matrix possesses a delocalized approximate top eigenvect

Guillermo Abramson

I perform a simple analysis of a random sample of Gaia satellite ERD3 sources in an attempt to answer the question posed sincerely by a visual artist: What color is the universe?

Tetsuro Kubo, Hiroshi Yasuoka, Balázs Dóra, Deepa Kasinathan

Based on our first detailed $^{181}$Ta nuclear quadrupole resonance (NQR) studies from 2017 on the Weyl semimetal TaP, we now extended our NQR studies to another Ta-based monopnictide TaAs. In the present work, we have determined the temperature-dependent $^{181}$Ta-NQR spectra, the spin-lattice relaxation time $T_{1}$, and the spin-spin relaxation time $T_{

Daniel T. Schussheim, Kurt Gibble

We describe a many-channel experiment control system based on a field-programmable gate array (FPGA). The system has 16 bit resolution on 10 analog 100 MS/s input channels, 14 analog 100 MS/s output channels, 16 slow analog input and output channels, dozens of digital inputs and outputs, and a touchscreen display for experiment control and monitoring. The sy

Rajendra Bhatia, Tanvi Jain

Let $r$ be any real number and for any $n$ let $p_1,\ldots,p_n$ be distinct positive numbers. A Kwong matrix is the $n\times n$ matrix whose $(i,j)$ entry is $(p_i^r+p_j^r)/(p_i+p_j).$ We determine the signatures of eigenvalues of all such matrices. The corresponding problem for the family of Loewner matrices $\begin{bmatrix}(p_i^r-p_j^r)/(p_i-p_j)\end{bmatr

B. Mojaveri, R. Jafarzadeh Bahrbeig, M. A. Fasihi, S. Babanzadeh

The performance of open quantum batteries (QBs) is severely limited by decoherence due to the interaction with the surrounding environment. So, protecting the charging processes against decoherence is of great importance for realizing QBs. In this work we address this issue by developing a charging process of a qubit-based open QB composed of a qubit-battery

Zahra Ziran, Francesco Leotta, Massimo Mecella

The study of ancient documents provides a glimpse into our past. However, the low image quality and intricate details commonly found in these documents present significant challenges for accurate object detection. The objective of this research is to enhance object detection in ancient documents by reducing false positives and improving precision. To achieve

C. Anzivino, A. Zaccone

In many colloidal suspensions, the dispersed colloidal particles are amorphous solids resulting from vitrification. A crucial open problem is understanding how colloidal stability is affected by the intra-particle glass transition. By dealing with the latter process from a solid-state perspective, we estabilish a proportionality relation between the intra-pa

Andrew C. Burgess, Edward Linscott, David D. O'Regan

The piecewise linearity condition on the total energy with respect to the total magnetization of finite quantum systems is derived, using the infinite-separation-limit technique. This generalizes the well-known constancy condition, related to static correlation error, in approximate density functional theory (DFT). The magnetic analog of the DFT Koopmans' th

Ming-Cheng Tsai, Muhammad Salman Bashir, Mohamed-Slim Alouini

Due to the narrow beamwidths of laser Gaussian beams, accurate tracking of laser beam's angle-of-arrival is an important problem in mobile free-space optical communications. In most optical receivers today, fine tracking of angle-of-arrival involves estimating the location of the focused beam spot projected onto a focal plane array. However, for very thin Ga

Cleverson Filgueiras, Moises Rojas, Edilberto O. Silva, Carlos Romero

In this paper, we analyze the operation of an Otto cycle heat machine driven by a non-interacting two-dimensional electron gas on a twisted geometry. We show that due to both the energy quantization on this structure and the adiabatic transformation of the number of complete twists per unit length of a helicoid, the machine performance in terms of output wor

S. Rijal, R. Neupane, S. P. Mainali, S. K. Regmi

Cocktail party problem is the scenario where it is difficult to separate or distinguish individual speaker from a mixed speech from several speakers. There have been several researches going on in this field but the size and complexity of the model is being traded off with the accuracy and robustness of speech separation. "Monaural multi-speaker speech separ

Yu-Hang Chien, Fang Yu

Sports professionals constantly under pressure to perform at the highest level can benefit from sports analysis, which allows coaches and players to reduce manual efforts and systematically evaluate their performance using automated tools. This research aims to advance sports analysis in badminton, systematically detecting hit-frames automatically from match

Kristy Hecht, Nacer Chahat, Goutam Chattopadhyay, Enrica Martini

We present a new strategy for the design of dual-band planar antennas based on metasurfaces (MTSs) in the microwave and millimeter-wave regimes. It is based on a double layer structure obtained by cascading two subwavelength patterned metallic claddings supported by a grounded dielectric slab. Each metallic layer is responsible for controlling radiation at o

Wing Keung Cheung, Jeremy Kalindjian, Robert Bell, Arjun Nair

Early detection and diagnosis of coronary artery disease (CAD) could save lives and reduce healthcare costs. The current clinical practice is to perform CAD diagnosis through analysing medical images from computed tomography coronary angiography (CTCA). Most current approaches utilise deep learning methods but require centerline extraction and multi-planar r

Wing Keung Cheung, Ashkan Pakzad, Nesrin Mogulkoc, Sarah Needleman

The morphology and distribution of airway tree abnormalities enables diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airway segmentation plays a critical role in the production of the outline of the entire airway tree to enable estimation of disease extent and severity. In this study, we propose a da

Nazul Merino Negrete, Cesar Maldonado, Raúl Salgado-García

In this work we introduce the lag irreversibility function as a method to assess time-irreversibility in discrete time series. It quantifies the degree of time-asymmetry for the joint probability function of the state variable under study and the state variable lagged in time. We test its performance in a time-irreversible Markov chain model for which theore

Ming Wang, Wenfang Wu, Chongyun Gao, Daling Wang

Large language models (LLMs) have received increasing attention. However, due to the complexity of its capabilities, how to rationally evaluate the capabilities of LLMs is still a task to be solved. We propose the RoCar method, which utilizes the defined basic schemas to randomly construct a task graph and generates natural language evaluation tasks based on

Jamie Tucker-Foltz

A locked $t$-omino tiling is a grid tiling by $t$-ominoes such that, if you remove any pair of tiles, the only way to fill in the remaining $2t$ grid cells with $t$-ominoes is to use the same two tiles in the exact same configuration as before. We exclude degenerate cases where there is only one tiling overall due to small dimensions. It is a classic (and st

Jaromír Křepelka

This paper presents two approaches to the precise design of maximally flat antireflection coatings reducing the reflectance of the substrate to near zero in a certain region around the central frequency. The first ideal case concerns coherent light interference, where it is required that for a chosen central frequency the maximum number of reflectance deriva

Muhammad Asim, Muhammad Ozair Iqbal, Waqas Aman, Muhammad Mahboob Ur Rahman

This paper reports the findings of an experimental study on the problem of line-of-sight (LOS)/non-line-of-sight (NLOS) classification in an indoor environment. Specifically, we deploy a pair of NI 2901 USRP software-defined radios (SDR) in a large hall. The transmit SDR emits an unmodulated tone of frequency 10 KHz, on a center frequency of 2.4 GHz, using t

Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li

Personalized federated learning has gained significant attention as a promising approach to address the challenge of data heterogeneity. In this paper, we address a relatively unexplored problem in federated learning. When a federated model has been trained and deployed, and an unlabeled new client joins, providing a personalized model for the new client bec

Taveena Lotey, Prateek Keserwani, Debi Prosad Dogra, Partha Pratim Roy

Classification of motor imagery (MI) using non-invasive electroencephalographic (EEG) signals is a critical objective as it is used to predict the intention of limb movements of a subject. In recent research, convolutional neural network (CNN) based methods have been widely utilized for MI-EEG classification. The challenges of training neural networks for MI

Ulrich D. Jentschura, Christopher Moore

We analyze the leading and higher-order quantum electrodynamic corrections to the energy levels for a single electron bound in a Penning trap, including the Bethe logarithm correction due to virtual excitations of the reference quantum cyclotron state. The effective coupling parameter alpha_c in the Penning trap is identified as the square root of the ratio

Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou

As large language models (LLMs) generate texts with increasing fluency and realism, there is a growing need to identify the source of texts to prevent the abuse of LLMs. Text watermarking techniques have proven reliable in distinguishing whether a text is generated by LLMs by injecting hidden patterns. However, we argue that existing LLM watermarking methods

Prateek Keserwani, Taveena Lotey, Rohit Keshari, Partha Pratim Roy

Text detection in the wild is a well-known problem that becomes more challenging while handling multiple scripts. In the last decade, some scripts have gained the attention of the research community and achieved good detection performance. However, many scripts are low-resourced for training deep learning-based scene text detectors. It raises a critical ques

Yuxin Zhang, Clément Huneau, Jérôme Idier, Diana Mateus

Ultrasound image reconstruction can be approximately cast as a linear inverse problem that has traditionally been solved with penalized optimization using the $l_1$ or $l_2$ norm, or wavelet-based terms. However, such regularization functions often struggle to balance the sparsity and the smoothness. A promising alternative is using learned priors to make th

Yi Feng, Ruge Zhang, Jiayuan Du, Qijun Chen

Optical flow and disparity are two informative visual features for autonomous driving perception. They have been used for a variety of applications, such as obstacle and lane detection. The concept of "U-V-Disparity" has been widely explored in the literature, while its counterpart in optical flow has received relatively little attention. Traditional motion

Sascha Kirch, Valeria Olyunina, Jan Ondřej, Rafael Pagés

We present RGB-D-Fusion, a multi-modal conditional denoising diffusion probabilistic model to generate high resolution depth maps from low-resolution monocular RGB images of humanoid subjects. RGB-D-Fusion first generates a low-resolution depth map using an image conditioned denoising diffusion probabilistic model and then upsamples the depth map using a sec

Zhongzheng Huang, Jiawei Wu, Tao Wang, Zuoyong Li

Despite the success of deep neural networks in medical image classification, the problem remains challenging as data annotation is time-consuming, and the class distribution is imbalanced due to the relative scarcity of diseases. To address this problem, we propose Class-Specific Distribution Alignment (CSDA), a semi-supervised learning framework based on se

Matei P. Coiculescu

We prove two results that together strongly suggest that obtaining a positive answer to the Navier-Stokes global regularity question requires more than a refinement of partial regularity theory. First we prove that there exists a class of bilinear operators $\mathfrak{B}$, which contains the Euler bilinear operator $\mathcal{E}(u,v):=\frac{1}{2}\mathbb{P}(u\

Mukesh Kumar Nagar, Arbind Kumar Lal, Sivaramakrishnan Sivasubramanian

Let $T$ be a tree on $n$ vertices and let $L_q^T$ be the $q$-analogue of its Laplacian. For a partition $\lambda \vdash n$, let the normalized immanant of $L_q^T$ indexed by $\lambda$ be denoted as $d_{\lambda}(L_q^T)$. A string of inequalities among $d_{\lambda}(L_q^T)$ is known when $\lambda$ varies over hook partitions of $n$ as the size of the first part

Zhiyu Pang

360-degree video becomes increasingly popular among users. In the current network bandwidth, serving high resolution 360 degree video to users is quite difficult. Most of the work has been devoted to the prediction of user viewports or tile-based adaptive algorithms. However, it is difficult to predict user viewports more accurately using only information su

Chunjin Yang, Fanman Meng, Shuai Chen, Mingyu Liu

Large-scale vision-language models (LVLMs) pretrained on massive image-text pairs have achieved remarkable success in visual representations. However, existing paradigms to transfer LVLMs to downstream tasks encounter two primary challenges. Firstly, the text features remain fixed after being calculated and cannot be adjusted according to image features, whi

Auwal Tijjani Amshi

Predicting the price of used vehicles is a more interesting and needed problem by many users. Vehicle price prediction can be a challenging task due to the high number of attributes that should be considered for accurate prediction. The major step in the prediction process is the collection and pre-processing of the data. In this project, python scripts were

Yan Sun, Hu Long, Xueling Feng, Mark Nixon

Gait recognition is one of the most promising video-based biometric technologies. The edge of silhouettes and motion are the most informative feature and previous studies have explored them separately and achieved notable results. However, due to occlusions and variations in viewing angles, their gait recognition performance is often affected by the predefin

Samuel Pfrommer, Yatong Bai, Hyunin Lee, Somayeh Sojoudi

Imitation learning suffers from causal confusion. This phenomenon occurs when learned policies attend to features that do not causally influence the expert actions but are instead spuriously correlated. Causally confused agents produce low open-loop supervised loss but poor closed-loop performance upon deployment. We consider the problem of masking observed

Mukesh Kumar Nagar

Let $G$ be a bipartite graph on $n$ vertices with the Laplacian matrix $L_G$. When $G$ is a tree, inequalities involving coefficients of immanantal polynomials of $L_G$ are known as we go up $GTS_n$ poset of unlabelled trees with $n$ vertices. We extend $GTS$ operation on a tree to an arbitrary graph, we call it generalized graph shift (hencefourth $GGS$) op

Hor Dashti, Abbas Ali Saberi, S. H. E. Rahbari, Jürgen Kurths

Jammed granular media and glasses exhibit spatial long-range correlations as a result of mechanical equilibrium. However, the existence of such correlations in the flowing matter, where the mechanical equilibrium is unattainable, has remained elusive. Here, we investigate this problem in the context of the percolation of interparticle forces in flowing granu

Tianyun Yang, Juan Cao, Danding Wang, Chang Xu

Nowadays, generative models are shaping various fields such as art, design, and human-computer interaction, yet accompanied by challenges related to copyright infringement and content management. In response, existing research seeks to identify the unique fingerprints on the images they generate, which can be leveraged to attribute the generated images to th

M. Fayolle, D. Dirkx, P. N. A. M. Visser, V. Lainey

The apparent close encounters of two satellites in the plane of the sky, called mutual approximations, have been suggested as a different type of astrometric observation to refine the moons' ephemerides. The main observables are the central instants of the close encounters, which have the advantage of being free of any scaling and orientation errors. However

Jiawen Kang, Jinbo Wen, Dongdong Ye, Bingkun Lai

Given the revolutionary role of metaverses, healthcare metaverses are emerging as a transformative force, creating intelligent healthcare systems that offer immersive and personalized services. The healthcare metaverses allow for effective decision-making and data analytics for users. However, there still exist critical challenges in building healthcare meta

Akshansh Mishra

In this research, the application of the Physics-Informed Neural Network (PINN) model is explored to solve transport equation-based Partial Differential Equations (PDEs). The primary objective is to analyze the impact of different activation functions incorporated within the PINN model on its predictive performance, specifically assessing the Mean Squared Er

Kui-Lu Yang, Yong Zhang, Jian-Jie Qiu, Yi-Na Ao

We present an unbiased molecular line survey toward the carbon-rich circumstellar envelope CIT 6 carried out between 90 and 116 GHz with the Arizona Radio Observatory 12 m telescope. A total of 42 lines assigned to 10 molecular species and 4 isotopologues are detected. Despite the absence of any newly identified circumstellar molecules, several transitions a

Bin Liu, Qin Luo, Bang Wang

Learning contrastive representations from pairwise comparisons has achieved remarkable success in various fields, such as natural language processing, computer vision, and information retrieval. Collaborative filtering algorithms based on pairwise learning also rooted in this paradigm. A significant concern is the absence of labels for negative instances in

Ruochen Tai, Liyong Lin, Rong Su

This work investigates the problem of synthesizing fortified supervisors against covert actuator attackers. For a non-resilient supervisor S, i.e., there exists at least a covert actuator attacker that is capable of inflicting damage w.r.t S, a fortified supervisor S' satisfies two requirements: 1) S' is resilient against any covert actuator attacker, and 2)

Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li

Existing research primarily focuses on backdoor attacks and defenses within the generic federated learning scenario, where all clients collaborate to train a single global model. A recent study conducted by Qin et al. (2023) marks the initial exploration of backdoor attacks within the personalized federated learning (pFL) scenario, where each client construc

Deng Wang

The Chinese Pulsar Timing Array (CPTA) collaboration has recently reported the observational evidence of a stochastic gravitational wave background. In light of the latest CPTA observation, we aim at exploring the ability of CPTA in probing new physics. Specifically, we constrain the first-order cosmological phase transitions with CPTA data, and find that th

Yugao Zhu, Shenghua Liu, Wenjie Feng, Xueqi Cheng

Densest Subgraph Problem (DSP) is an important primitive problem with a wide range of applications, including fraud detection, community detection and DNA motif discovery. Edge-based density is one of the most common metrics in DSP. Although a maximum flow algorithm can exactly solve it in polynomial time, the increasing amount of data and the high complexit

Bin Chen, Yuefeng Liu, Boyang Yu

We study holographic complexity for the rotating quantum BTZ black holes (quBTZ), the BTZ black holes with corrections from bulk quantum fields. Using double holography, the combined system of backreacted rotating BTZ black holes with conformal matters, can be holographically described by the rotating AdS4 C-metric with the BTZ black hole living on a codimen

Xinyi Gao, Tong Chen, Yilong Zang, Wentao Zhang

Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. To address this limitation, graph condensation has emerged as a promising technique, which constructs a small synthetic graph for efficiently training GNNs while retaining performan

M. Fayolle, A. Magnanini, V. Lainey, D. Dirkx

The upcoming JUICE and Europa Clipper missions to Jupiter's Galilean satellites will provide radio science tracking measurements of both spacecraft. Such data are expected to significantly help estimating the moons' ephemerides and related dynamical parameters. However, the two missions will yield an imbalanced dataset, with no flybys planned at Io, condense

Naoya Ando

Let $M$ be a Lorentz surface and $F:M\rightarrow N$ a time-like and conformal immersion of $M$ into a 4-dimensional neutral space form $N$ with zero mean curvature vector. We see that the curvature $K$ of the induced metric on $M$ by $F$ is identically equal to the constant sectional curvature $L_0$ of $N$ if and only if the covariant derivatives of both of

Ludovic Cesbron, Maxime Herda

In this paper we study a self-consistent Vlasov-Fokker-Planck equations which describes the longitudinal dynamics of an electron bunch in the storage ring of a synchrotron particle accelerator. We show existence and uniqueness of global classical solutions under physical hypotheses on the initial data. The proof relies on a mild formulation of the equation a

A. F. Borghesani, G. Carugno, G. Messineo, J. Pazzini

We report the first ever measurements of the thermalization length of low-energy electrons injected into solid para-hydrogen at a temperature \(T\approx 2.8\,\)K. The use of the pulsed Townsend photoinjection technique has allowed us to investigate the behavior of quasi-free electrons rather than of massive, slow negative charges as reported in all previous

Tania Robens

I give a short summary on scenarios with new physics scalars that could be investigated at future $e^+e^-$ colliders. I concentrate on cases where at least one of the additional scalar has a mass below 125 GeV, and discuss both models where this could be realized, as well as studies which focus on such scenarios. This work is based on arXiv:2205.09687, and p

M. Fayolle, V. Lainey, D. Dirkx, L. I. Gurvits

Stellar occultations currently provide the most accurate ground-based measurements of the positions of natural satellites (down to a few kilometres for the Galilean moons). However, when using these observations in the calculation of satellite ephemerides, the uncertainty in the planetary ephemerides dominates the error budget of the occultation. We quantify

Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu

Recommender systems are important for providing personalized services to users, but the vast amount of collected user data has raised concerns about privacy (e.g., sensitive data), security (e.g., malicious data) and utility (e.g., toxic data). To address these challenges, recommendation unlearning has emerged as a promising approach, which allows specific d

Marianna D'Amato, Lucien Belzane, Corentin Dabard, Mathieu Silly

Achieving pure single-photon emission is essential for a range of quantum technologies, from optical quantum computing to quantum key distribution to quantum metrology. Among solid-state quantum emitters, colloidal lead halide perovskite (LHP) nanocrystals (NCs) have garnered significant attention due to their interesting structural and optical properties, w

Maksym Bekuzarov, Ariana Bermudez, Joon-Young Lee, Hao Li

Despite advancements in user-guided video segmentation, extracting complex objects consistently for highly complex scenes is still a labor-intensive task, especially for production. It is not uncommon that a majority of frames need to be annotated. We introduce a novel semi-supervised video object segmentation (SSVOS) model, XMem++, that improves existing me

Mengni Li, You Li

The Monge-Amp\`ere type equations over bounded convex domains arise in a host of geometric applications. In this paper, we focus on the Dirichlet problem for a class of Monge-Amp\`ere type equations, which can be degenerate or singular near the boundary of convex domains. Viscosity subsolutions and viscosity supersolutions to the problem can be constructed v

Igor Cherepanov, David Sessler, Alex Ulmer, Hendrik Lücke-Tieke

Deep learning (DL) models achieve remarkable performance in classification tasks. However, models with high complexity can not be used in many risk-sensitive applications unless a comprehensible explanation is presented. Explainable artificial intelligence (xAI) focuses on the research to explain the decision-making of AI systems like DL. We extend a recent

Samyak Jain, Sarthak Johari, Radhakrishnan Delhibabu

Cryptocurrency is a form of digital currency using cryptographic techniques in a decentralized system for secure peer-to-peer transactions. It is gaining much popularity over traditional methods of payments because it facilitates a very fast, easy and secure way of transactions. However, it is very volatile and is influenced by a range of factors, with socia

Kaveh Eftekharinasab

We construct connection maps and linear symmetric connections on tangent and second-order tangent bundles for \fr manifolds using the notion of a spray. For these manifolds, we characterize linear symmetric connections on tangent bundles in terms of bilinear symmetric mappings associated with sprays. We also provide an alternative characterization of these c

Muhamed Borogovac

Given Krein and Hilbert spaces $\left( \mathcal{K},[.,.] \right)$ and $\left( \mathcal{H}, \left( .,. \right) \right)$, respectively, the concept of the boundary triple $\Pi =(\mathcal{H}, \Gamma _{0}, \Gamma_{1})$ is generalized through the abstract Green's identity for the isometric relation $\Gamma$ between Krein spaces $\left( \mathcal{K}^{2}, \left[ .,.

Akihiro Shibata, Kei-Ichi Kondo

The lattice SU(2) gauge-scalar model with the scalar field in the adjoint representation of the gauge group has two completely separated confinement and Higgs phases according to the preceding studies based on numerical simulations which have been performed in the specific gauge fixing based on the conventional understanding of the Brout-Englert-Higgs mechan

Y. Ikeda, G. I. Sharygin

We prove the conjecture that allows one extend the argument shifting procedure from symmetric algebra $S\mathfrak{gl}_d$ of the Lie algebra $\mathfrak{gl}_d$ to the universal enveloping algebra $U\mathfrak{gl}_d$. Namely, it turns out that the iterated quasi-derivations of the central elements in $U\mathfrak{gl}_d$ commute with each other. Here quasi-derivat

Xinfa Zhu, Yi Lei, Tao Li, Yongmao Zhang

Previous multilingual text-to-speech (TTS) approaches have considered leveraging monolingual speaker data to enable cross-lingual speech synthesis. However, such data-efficient approaches have ignored synthesizing emotional aspects of speech due to the challenges of cross-speaker cross-lingual emotion transfer - the heavy entanglement of speaker timbre, emot

Jiaqi Liu, Xiao Qi, Ying Ni, Jian Sun

One of the key factors determining whether autonomous vehicles (AVs) can be seamlessly integrated into existing traffic systems is their ability to interact smoothly and efficiently with human drivers and communicate their intentions. While many studies have focused on enhancing AVs' human-like interaction and communication capabilities at the behavioral dec

Jithin G. Krishnan, Harikrishnan K. J., Amit Kumar Pal

In a star-network of qubits interacting via Heisenberg interaction of XYZ-type, we demonstrate a logarithmic growth of the localizable bipartite peripheral entanglement with increasing periphery-size and vanishing xy-anisotropy. This feature disappears when xy-anisotropy becomes non-zero, exhibiting an anisotropy effect, which can be negated by taking the sy

Tianchun Zhou

Systematic iterative algorithms of supersymmetric quantum mechanics (SUSYQM) type for solving the eigenequation of principal hypergeometric-like differential operator (HLDO) and for generating the eigenequation of associated HLDO itself as well its solutions are developed, without any input from traditional methods. These are initiated by devising two types

Luigi Palmieri, Lorenzo Valerio, Chiara Boldrini, Andrea Passarella

In a decentralized machine learning system, data is typically partitioned among multiple devices or nodes, each of which trains a local model using its own data. These local models are then shared and combined to create a global model that can make accurate predictions on new data. In this paper, we start exploring the role of the network topology connecting

Hiroshi Iritani

Hodge-theoretic mirror symmetry for a Calabi-Yau mirror pair says that the variation of Hodge structure arising from quantum cohomology of a Calabi-Yau manifold and that arising from deformation of complex structures on the dual Calabi-Yau manifold can be identified with each other, and it has been conjectured (Gamma-conjecture) that the Gamma-integral struc

Palash Saha, Bala Murali Krishna Mariserla

Scattering dynamics influence the graphenes transport properties and inhibits the charge carrier deterministic behaviour. The intra or inter-band scattering mechanisms are vital for graphenes optical conductivity response under specific considerations of doping. Here, we investigated the influence of scattering systematically on optical conductivity using a

Shahab Nikkhoo, Zexin Li, Aritra Samanta, Yufei Li

Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas where robots face a trade-off between self-interests and collective benefits. However, environmental factors such as miscommunication and adversarial robots can impact cooperation, making it crucial to

Pavan Kumar Gadamsetty, K. V. S. Hari, Lajos Hanzo

In a transmit preprocessing aided frequency division duplex (FDD) massive multi-user (MU) multiple-input multiple-output (MIMO) scheme assisted orthogonal frequency-division multiplexing (OFDM) system, it is required to feed back the frequency domain channel transfer function (FDCHTF) of each subcarrier at the user equipment (UE) to the base station (BS). Th

Ruihao Xia, Chaoqiang Zhao, Meng Zheng, Ziyan Wu

Most nighttime semantic segmentation studies are based on domain adaptation approaches and image input. However, limited by the low dynamic range of conventional cameras, images fail to capture structural details and boundary information in low-light conditions. Event cameras, as a new form of vision sensors, are complementary to conventional cameras with th

Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang

Predictive Autoscaling is used to forecast the workloads of servers and prepare the resources in advance to ensure service level objectives (SLOs) in dynamic cloud environments. However, in practice, its prediction task often suffers from performance degradation under abnormal traffics caused by external events (such as sales promotional activities and appli

Hiroshi Iritani

The mirror symmetric Gamma conjecture roughly speaking says that the Gamma class of a manifold determines the asymptotics of (exponential) periods of the mirror. We recast the method in [Iri11] in a more general context and show that the mirror symmetric Gamma conjecture for a Fano manifold F implies, via Laplace transformation, that for the total space K_F

Francisco Orts, Manuel Maier, Matthias Fuchs, Gloria Ortega

The dynamics of a tracer particle in a bath of quasi-hard colloidal spheres is studied by Langevin dynamics simulations and mode coupling theory (MCT); the tracer radius is varied from equal to up to 7 times larger than the bath particles radius. In the simulations, two cases are considered: freely diffusing tracer (passive microrheology) and tracer pulled w

Hiroshi Iritani

The Gamma-class is a characteristic class for complex manifolds with transcendental coefficients. It defines an integral structure of quantum cohomology, or more precisely, an integral lattice in the space of flat sections of the quantum connection. We present several conjectures (the Gamma-conjectures) about this structure, particularly focusing on the Riem

Wieslaw Kubiś

Motivated by a recent work of Balcerzak and Kania [Proc. Amer. Math. Soc. 151 (2023) 3737--3742], we show that every countable monoid has a universal action on the free object over a countable infinite set. This is a general result concerning concrete categories with a left adjoint (free) functor. On the way, we introduce an abstract concept of ``being gener

Sanjeev Arora, Anirudh Goyal

A major driver of AI products today is the fact that new skills emerge in language models when their parameter set and training corpora are scaled up. This phenomenon is poorly understood, and a mechanistic explanation via mathematical analysis of gradient-based training seems difficult. The current paper takes a different approach, analysing emergence using

Hiroshi Iritani

We review mirror symmetry for the quantum cohomology D-module of a compact weak-Fano toric manifold. We also discuss the relationship to the GKZ system, the Stanley-Reisner ring, the Mellin-Barnes integrals, and the Gamma-integral structure.

Mingcai Chen, Yu Zhao, Zhonghuang Wang, Bing He

Immune repertoire classification, a typical multiple instance learning (MIL) problem, is a frontier research topic in computational biology that makes transformative contributions to new vaccines and immune therapies. However, the traditional instance-space MIL, directly assigning bag-level labels to instances, suffers from the massive amount of noisy labels

Soumyadeep Roy, Jonas Wallat, Sowmya S Sundaram, Wolfgang Nejdl

Large-scale language models such as DNABert and LOGO aim to learn optimal gene representations and are trained on the entire Human Reference Genome. However, standard tokenization schemes involve a simple sliding window of tokens like k-mers that do not leverage any gene-based semantics and thus may lead to (trivial) masking of easily predictable sequences a

Chuanbo Liu, Jin Wang

Master equations are of fundamental importance in modeling stochastic dynamical systems.However, solving master equations is challenging due to the exponential increase in the number of possible states or trajectories with the dimension of the state space. In this study, we propose repurposing language models as a machine learning approach to solve master eq

Andrey R. Chekhlov, Peter V. Danchev

A famous conjecture attributed to Dardano-Dikranjan-Rinauro-Salce states that any uniformly fully inert subgroup of a given group is commensurable with a fully invariant subgroup (see, respectively, [5] and [6]). In this short note, we completely settle this problem in the affirmative for an arbitrary Abelian group.

Bhoomeendra Singh Sisodiya, Narendra Babu Unnam, P. Krishna Reddy, Apala Das

Developing methods for extracting relevant legal information to aid legal practitioners is an active research area. In this regard, research efforts are being made by leveraging different kinds of information, such as meta-data, citations, keywords, sentences, paragraphs, etc. Similar to any text document, legal documents are composed of paragraphs. In this

Saki Omi, Hyo-Sang Shin, Namhoon Cho, Antonios Tsourdos

Recent studies have greatly improved reinforcement learning, and an increased interest in real-world implementation has emerged. In many cases, the implementation is challenged by time-varying disturbances as it introduces hidden states, which makes the problem best described with Partially Observable Markov Decision Processes. An effective approach to addre

Parosh Aziz Abdulla, Mohamed Faouzi Atig, Frederik Meyer Bønneland, Sarbojit Das

Event-driven multi-threaded programming is an important idiom for structuring concurrent computations. Stateless Model Checking (SMC) is an effective verification technique for multi-threaded programs, especially when coupled with Dynamic Partial Order Reduction (DPOR). Existing SMC techniques are often ineffective in handling event-driven programs, since th

Yongkang Li, Ziyang Song, Zheng Shi, Qingping Dou

Terahertz (THz) communication is one of the most promising candidates to accommodate high-speed mobile data services. This paper proposes a secure hybrid automatic repeat request with incremental redundancy (HARQ-IR) aided THz communication scheme, where the transmission secrecy is ensured by confusing the eavesdropper with dummy messages. The connection and

Souvik Das, Arnab Maity, Rajib Sarkar, Anirudha Menon

Considering the low-energy model of tilted Weyl semimetal, we study the electronic transmission through a periodically driven quantum well, oriented in the transverse direction with respect to the tilt. We adopt the formalism of Floquet scattering theory and investigate the emergence of Fano resonances as an outcome of matching between the Floquet sidebands