August 2022 arXiv papers — page 51

Shiwen He, Yeyu Ou, Liangpeng Wang, Hang Zhan

With the application of the fifth-generation wireless communication technologies, more smart terminals are being used and generating huge amounts of data, which has prompted extensive research on how to handle and utilize these wireless data. Researchers currently focus on the research on the upper-layer application data or studying the intelligent transmiss

Ivor Krešić, Gordon R. M. Robb, Gian-Luca Oppo, Thorsten Ackemann

We describe a mechanism for guiding the dynamical evolution of ultracold atomic motional degrees of freedom toward multiparticle entangled Dicke-squeezed states, via nonlinear self-organization under external driving. Two examples of many-body models are investigated. In the first model, the external drive is a temporally oscillating magnetic field leading t

Yubo Sun, Yiwei Zhang, Gennian Ge

Permutation codes and multi-permutation codes have been widely considered due to their various applications, especially in flash memory. In this paper, we consider permutation codes and multi-permutation codes against a burst of stable deletions. In particular, we propose a construction of permutation codes correcting a burst stable deletion of length $s$, w

Olivia Mallick, Muktish Acharyya

The three-dimensional anisotropic classical XY ferromagnet has been investigated by extensive Monte Carlo simulation using the Metropolis single spin flip algorithm. The magnetization ($M$) and the susceptibility ($\chi$) are measured and studied as functions of the temperature of the system. For constant anisotropy, the ferro-para phase transition has been

Sourin Chatterjee, Sayantan Nag Chowdhury, Dibakar Ghosh, Chittaranjan Hens

The persistence of biodiversity of species is a challenging proposition in ecological communities in the face of Darwinian selection. The present article investigates beyond the pairwise competitive interactions and provides a novel perspective for understanding the influence of higher-order interactions on the evolution of social phenotypes. Our simple mode

Meltem Tolunay, Ieva Liepuoniute, Mariya Vyushkova, Barbara A. Jones

Quantum dynamics of the radical pair mechanism is a major driving force in quantum biology, materials science, and spin chemistry. The rich quantum physical underpinnings of the mechanism are determined by a coherent oscillation (quantum beats) between the singlet and triplet spin states and their interactions with the environment, which is challenging to ex

Dietrich Stoyan, Sung Nok Chiu

In a recent prominent study Worobey et al.\ (2022, Science, 377, pp.\ 951--9) purported to demonstrate statistically that the Huanan Seafood Wholesale Market was the epicenter of the early COVID-19 epidemic. We show that this statistical conclusion is invalid on two grounds: (1) The assumption that a centroid of early case locations or another simply constru

Xiang-Xiang Sun, Shan-Gui Zhou

Pairing effects manifests themselves in many aspects in nuclear systems ranging from finite nuclei to nuclear matter and compact stars. Although with some specific features for nuclear systems, the mechanism of pairing between nucleons in these systems resembles that of electrons in superconductors. The Bardeen-Cooper-Schrieffer (BCS) theory, the first succe

Hubing Xiao, Junhui Fan, Zhihao Ouyang, Liangjun Hu

It is known that the blazar jet emissions are dominated by non-thermal radiation while the accretion disk jets are normally dominated by thermal emission. In this work, our aim is to study the connection between the two types of emission by investigating the correlation between the blazar emission line intensity property, which embodies the nature of accreti

Simon Scherrer, Markus Legner, Adrian Perrig, Stefan Schmid

Google's BBR is the most prominent result of the recently revived quest for efficient, fair, and flexible congestion-control algorithms (CCAs). While the performance of BBR has been investigated by numerous studies, previous work still leaves gaps in the understanding of BBR performance: Experiment-based studies generally only consider network settings that

Siwen Luo, Yihao Ding, Siqu Long, Josiah Poon

Recognizing the layout of unstructured digital documents is crucial when parsing the documents into the structured, machine-readable format for downstream applications. Recent studies in Document Layout Analysis usually rely on computer vision models to understand documents while ignoring other information, such as context information or relation of document

Issei Sakai, Takuma Akimoto

We investigate the current properties in the totally asymmetric simple exclusion process (TASEP) on a quenched random energy landscape. In low- and high-density regimes, the properties are characterized by single-particle dynamics. In the intermediate one, the current becomes constant and is maximized. Based on the renewal theory, we derive accurate results

M. Borghesi, C. Barone, S. Capelli, G. Carapella

DARTWARS (Detector Array Readout with Traveling Wave AmplifieRS) is a three years project that aims to develop high-performing innovative Traveling Wave Parametric Amplifiers (TWPAs) for low temperature detectors and qubit readout (C-band). The practical development follows two different promising approaches, one based on the Josephson junctions (TWJPA) and

Jonathan Fhima, Jan Van Eijgen, Moti Freiman, Ingeborg Stalmans

Introduction: For supervised deep learning (DL) tasks, researchers need a large annotated dataset. In medical data science, one of the major limitations to develop DL models is the lack of annotated examples in large quantity. This is most often due to the time and expertise required to annotate. We introduce Lirot. ai, a novel platform for facilitating and

Naihao Deng, Yulong Chen, Yue Zhang

Text-to-SQL has attracted attention from both the natural language processing and database communities because of its ability to convert the semantics in natural language into SQL queries and its practical application in building natural language interfaces to database systems. The major challenges in text-to-SQL lie in encoding the meaning of natural uttera

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

A measurement of the $C\!P$-even fraction of the decay $D^{0}\to\pi^{+}\pi^{-}\pi^{+}\pi^{-}$ is performed with a quantum-correlated $\psi(3770)\to D\bar{D}$ data sample collected by the BESIII experiment, corresponding to an integrated luminosity of 2.93 $\textrm{fb}^{-1}$. Using a combination of $C\!P$ eigenstates, $D \to \pi^+\pi^-\pi^0$ and $D \to K_{S,L

G. Niccoli, V. Terras

This paper is a continuation of [1], in which a set of matrix elements of local operators was computed for the XXZ spin-1/2 open chain with a particular case of unparallel boundary fields. Here, we extend these results to the more general case in which both fields are non-longitudinal and related by one constraint, allowing for a partial description of the s

Mathieu Baillif

An open chain cover $\{U_\alpha : \alpha\in\kappa\}$ ($\kappa$ a cardinal) of a space $X$ is a systematic cover if the closure of $U_\alpha$ is contained in $U_\beta$ when $\alpha<\beta$, and $X$ is Type I if $\kappa=\omega_1$ and the closure of each $U_\alpha$ is Lindel\"of. A closed subspace $D\subset X$ is narrow in $X$ if for each systematic cover $\{V_\

Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis

Center-based clustering (e.g., $k$-means, $k$-medians) and clustering using linear subspaces are two most popular techniques to partition real-world data into smaller clusters. However, when the data consists of sensitive demographic groups, significantly different clustering cost per point for different sensitive groups can lead to fairness-related harms (e

Marta Pita-Vidal, Arno Bargerbos, Rok Žitko, Lukas J. Splitthoff

Spin qubits in semiconductors are currently one of the most promising architectures for quantum computing. However, they face challenges in realizing multi-qubit interactions over extended distances. Superconducting spin qubits provide a promising alternative by encoding a qubit in the spin degree of freedom of an Andreev level. Such an Andreev spin qubit co

Hsien-chung Kao, Dingping Li, Baruch Rosenstein

A one band Hubbard model with intermediate coupling is shown to describe the two most important unusual features of a normal state: linear resistivity strange metal and the pseudogap. Both the spectroscopic and transport properties of the cuprates are considered on the same footing by employing a relatively simple postgaussian approximation valid for the int

Lei Xie, Shenghui Song

Perceptive mobile networks (PMNs) were proposed to integrate sensing capability into current cellular networks where multiple sensing nodes (SNs) can collaboratively sense the same targets. Besides the active sensing in traditional radar systems, passive sensing based on the uplink communication signals from mobile user equipment may play a more important ro

Sijie Shen, Xiang Zhu, Yihong Dong, Qizhi Guo

Code generation aims to generate a code snippet automatically from natural language descriptions. Generally, the mainstream code generation methods rely on a large amount of paired training data, including both the natural language description and the code. However, in some domain-specific scenarios, building such a large paired corpus for code generation is

Kazumasa Inaba

In this paper, we show a generalized Join theorem for real analytic singularities. For complex singularities, this theorem was proved by A. N\'emethi.

Iñigo Liberal, J. Enrique Vázquez-Lozano, Victor Pacheco-Peña

We investigate the quantum optical response of antireflection temporal coatings, i.e., matching temporal layers that suppress the generation of backward waves in temporal boundaries. Our results reveal that quantum antireflection temporal coatings are characterized for inducing a frequency shift of the quantum state, while preserving all photon statistics in

Pia Andrews, Tim de Sousa, Bruce Haefele, Matt Beard

This paper identifies the current challenges of the mechanisation, digitisation and automation of public sector systems and processes, and proposes a modern and practical framework to ensure and assure ethical and high veracity Artificial Intelligence (AI) or Automated Decision Making (ADM) systems in public institutions. This framework is designed for the s

Yoshihiro Gunji, Koji Ishiwata, Takahiro Yoshida

We consider a supergravity model that has the modular $A_4$ symmetry and discuss the interplay between the neutrino mixing and inflation. The model contains right-handed neutrinos that have the Majorana masses and additional Yukawa couplings to the waterfall field. In the model an active neutrino is massless and we find that only the inverted hierarchy is al

Jay A. Berres, S. Ali Hassani Gangaraj, George W. Hanson

We investigate entanglement mediated by DC current induced nonreciprocal graphene plasmon polaritons. Nonreciprocal systems are ideal for the enhancement, control, and preservation of entanglement due to the potential for unidirectional beam-like wave propagation, i.e., efficiently transporting photons from one emitter to another. Using a quantum master equa

Lan Wang, Zheng Zheng, Cai-Na Hao, Rui Guo

A sample of 279 massive red spirals was selected optically by Guo et al. (2020), among which 166 galaxies have been observed by the ALFALFA survey. In this work, we observe HI content of the rest 113 massive red spiral galaxies using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). 75 of the 113 galaxies have HI detection with a signal-to-no

Kexin Chen, Guangyong Chen, Junyou Li, Yuansheng Huang

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with high-quality annotations, which seriously limits the wide usage of data-driven methods. In this paper, we focus on the reaction yield prediction problem,

Jialin Tang, Qi Wang, Jiongzhi Zheng, Lin Cheng

The highly anisotropic thermal conductivity in layered materials is crucial for a broad range of applications such as thermal management of electronic devices, thermal insulation, and thermoelectrics. Understanding of anisotropic thermal transport in layered materials largely depends on atomistic simulations based on density functional theory (DFT) or empiri

Xinyu Zuo, Haijin Liang, Ning Jing, Shuang Zeng

Fine-grained entity typing (FET) aims to deduce specific semantic types of the entity mentions in text. Modern methods for FET mainly focus on learning what a certain type looks like. And few works directly model the type differences, that is, let models know the extent that one type is different from others. To alleviate this problem, we propose a type-enri

Musavvir Ali, Ehtesham Akhter

We define w-invex set, w-preinvex, w-strictly preinvex, w-quasi preinvex, w-strictly quasi preinvex, w-semi-strictly quasi preinvex, and w-pre pseudo-invex functions in this context. And these form a class of real functions, which is the generalization of a family of preinvex functions. Here, we provide a thorough analysis of the core characteristics of thes

Takanori Ayano

A telescopic curve is a certain algebraic curve defined by $m-1$ equations in the affine space of dimension $m$, which can be a hyperelliptic curve and an $(n,s)$ curve as a special case. The sigma function $\sigma(u)$ associated with the telescopic curve of genus $g$ is a holomorphic function on $\mathbb{C}^g$. For a subring $R$ of $\mathbb{C}$ and variable

Zhizhang Wu, Ivan G. Graham, Dingjiong Ma, Zhiwen Zhang

In this paper, we combine the Smolyak technique for multi-dimensional interpolation with the Filon-Clenshaw-Curtis (FCC) rule for one-dimensional oscillatory integration, to obtain a new Filon-Clenshaw-Curtis-Smolyak (FCCS) rule for oscillatory integrals with linear phase over the $d-$dimensional cube $[-1,1]^d$. By combining stability and convergence estima

Stephen Su, Samuel Kwong, Qingyu Zhao, De-An Huang

There has been an increasing interest in multi-task learning for video understanding in recent years. In this work, we propose a generalized notion of multi-task learning by incorporating both auxiliary tasks that the model should perform well on and adversarial tasks that the model should not perform well on. We employ Necessary Condition Analysis (NCA) as

Defeng Zou, Youjian Song, Omri Gat, Minglie Hu

Optical soliton molecules in ultrafast lasers present striking analogies with their matter molecule counterparts, such as internal vibrations. However, the vibrations of soliton molecules are nonlinear, with frequencies that are sensitive to the system parameters, thus presenting an opportunity of control. Here, we experimentally demonstrate the synchronizat

Sheetal Punia, Suman Danani, Hitesh B. Pandya

Microstrip patch antennas are low-profile and robust when mounted on rigid surfaces of the devices making them suitable for communication and millimeter-wave applications. In this paper, an antenna is designed for the resonant frequency of 170 GHz using microstrip technology concerning its miniaturization and cost-effectiveness. The designed antenna is a par

Zdeněk Dvořák, David R. Wood

We investigate the product structure of hereditary graph classes admitting strongly sublinear separators. We characterise such classes as subgraphs of the strong product of a star and a complete graph of strongly sublinear size. In a more precise result, we show that if any hereditary graph class $\mathcal{G}$ admits $O(n^{1-\epsilon})$ separators, then for

Maxime Ferreira Da Costa, Yuejie Chi

Spike deconvolution is the problem of recovering the point sources from their convolution with a known point spread function, which plays a fundamental role in many sensing and imaging applications. In this paper, we investigate the local geometry of recovering the parameters of point sources$\unicode{x2014}$including both amplitudes and locations$\unicode{x

Asrar Ahmed Baktayan, Ibrahim Ahmed Al-Baltah

The Mobile Network Operator (MNO) must select how to delegate Mobile Device (MD) queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, hi

Daniel Levin, Alexander Zuevsky

Let $\mathfrak g$ be an infinite-dimensional Lie algebra and $G$ be the algebraic completion of its module. Using a geometric interpretation in terms of sewing two Riemann spheres with a number of marked points, we introduce a multiplication between elements of two spaces $\mathcal{M}^k_m(\mathfrak g, G)$ and $\mathcal{M}^n_{m'}(\mathfrak g, G)$ of meromorph

Haruki Ebina, Reijo Keskitalo, Julian Borrill, Steve K. Choi

We present new wide field survey strategies for Chilean Large Aperture Telescopes (LAT) measuring the Cosmic Microwave Background (CMB), which we call Sinusoidal Modulated High Cadence Survey Strategies. The strategies were developed during the process of optimizing LAT measurements for the CMB-S4, Simons Observatory, and CCAT-prime collaborations. Observing

J. Walker Orr

Programs are a kind of communication to both computers and people, hence as students are trained to write programs they need to learn to write well-designed, readable code rather than code that simply functions correctly. The difficulty in teaching good design practices that promote readability is the labor intensiveness of assessing student programs. Typica

Gaofei Zhang

Suppose $f$ and $g$ are two post-critically finite polynomials of degree $d_1$ and $d_2$ respectively and suppose both of them have a finite super-attracting fixed point of degree $d_0$. We prove that one can always construct a rational map $R$ of degree $$D = d_1 + d_2 - d_0$$ by gluing $f$ and $g$ along the Jordan curve boundaries of the immediate super-at

Wenye Lin, Yangning Li, Yifeng Ding, Hai-Tao Zheng

Traditional knowledge distillation adopts a two-stage training process in which a teacher model is pre-trained and then transfers the knowledge to a compact student model. To overcome the limitation, online knowledge distillation is proposed to perform one-stage distillation when the teacher is unavailable. Recent researches on online knowledge distillation

M. Jani, M. Mrózek, A. M. Nowakowska, P. Leszczenko

We present a photoluminescence (PL) and Raman spectroscopy study of various diamond samples that have high concentrations of nitrogen-vacancy (NV) color centers up to multiple parts per million (ppm). With green red, and near infrared (NIR) light excitation, we demonstrate that while for samples with a low density of NV centers the signals are primarily domi

Putian Yang, Shiqing Zhang

In this paper, we focus on the set of geodesics rays of the Newtonian N-body problem. We find that the limits of geodesic rays are also geodesic rays, hence they are not dense in the space of initial conditions. As a result, there are many motions whose domain is the half real line has non-negative total energy, and they are not geodesic rays, the set of suc

Beniamin Goldys, Chunxi Jiao, Kim Ngan Le

In this paper we are concerned with the stochastic Landau-Lifshitz-Slonczewski equation (LLS) that describes magnetisation of an inifnite nanowire evolving under current driven spin torque. The current brings into the system a multiplicative gradient noise that appears as a transport term in the equation. We prove the existence, uniqueness and regularity of

Ian Lizarraga, Robert Marangell

Reaction-nonlinear diffusion partial differential equations can exhibit shock-fronted travelling wave solutions. Prior work by Yi et. al. (2021) has demonstrated the existence of such waves for two classes of regularisations, including viscous relaxation. Their analysis uses geometric singular perturbation theory: for sufficiently small values of a parameter

Emily McMilin

In this paper we motivate the causal mechanisms behind sample selection induced collider bias (selection collider bias) that can cause Large Language Models (LLMs) to learn unconditional dependence between entities that are unconditionally independent in the real world. We show that selection collider bias can become amplified in underspecified learning task

Taylor Faucett, Shih-Chieh Hsu, Daniel Whiteson

We train a network to identify jets with fractional dark decay (semi-visible jets) using the pattern of their low-level jet constituents, and explore the nature of the information used by the network by mapping it to a space of jet substructure observables. Semi-visible jets arise from dark matter particles which decay into a mixture of dark sector (invisibl

Ding Zou, Wei Wei, Ziyang Wang, Xian-Ling Mao

Incorporating Knowledge Graphs (KG) into recommeder system has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop end-to-end models based on graph neural networks (GNNs). However, the extremely sparse user-item interactions significantly degrade the performance of the GNN-based models, as: 1)

Luyao Niu, Zhouchi Li, Andrew Clark

We study the problem of synthesizing a controller to satisfy a complex task in the presence of sensor faults and attacks. We model the task using Gaussian distribution temporal logic (GDTL), and propose a solution approach that does not rely on computing any finite abstraction to model the system. We decompose the GDTL specification into a sequence of reach-

Bin Zhu, Jiahao Liu, Zhengshou Lai, Tao Qian

Generating large-scale samples of stationary random fields is of great importance in the fields such as geomaterial modeling and uncertainty quantification. Traditional methodologies based on covariance matrix decomposition have the diffculty of being computationally expensive, which is even more serious when the dimension of the random field is large. This

Hyun Ho Lee

We introduce the notion of the weak tracial approximate representability of a discrete group action on a unital $C^*$-algebra which could have no projections like the Jiang-Su algebra $\mathcal{Z}$. Then we show a duality between the weak tracial Rokhlin property and the weak tracial approximate representability. More precisely, when $G$ is a finite abelian

Athira Unni, Mayank Narang, Thirupathi Sivarani, Manoj Puravankara

The correlation between host star iron abundance and the exoplanet occurrence rate is well-established and arrived at in several studies. Similar correlations may be present for the most abundant elements, such as carbon and oxygen, which also control the dust chemistry of the protoplanetary disk. In this paper, using a large number of stars in the Kepler fi

JunYoung Gwak, Silvio Savarese, Jeannette Bohg

Recent research in multi-task learning reveals the benefit of solving related problems in a single neural network. 3D object detection and multi-object tracking (MOT) are two heavily intertwined problems predicting and associating an object instance location across time. However, most previous works in 3D MOT treat the detector as a preceding separated pipel

Masaharu Ishikawa, Tat Thang Nguyen

Let $f$ be a polynomial map from $\mathbb R^m$ to $\mathbb R^n$ with $m>n>0$ and $t_0$ be a regular value of $f$. For a small open ball $D_{t_0}$ centered at $t_0$, we show that the map $f:f^{-1}(D_{t_0})\to D_{t_0}$ is a Serre fibration if and only if $f$ is a Serre fibration over a finite number of certain simple arcs starting at $t_0$. We characterize the

Michael C. H. Choi

Given a target Gibbs distribution $\pi^0_{\beta} \propto e^{-\beta \mathcal{H}}$ to sample from in the low-temperature regime on $\Sigma_N := \{-1,+1\}^N$, in this paper we propose and analyze Metropolis dynamics that instead target an alternative distribution $\pi^{f}_{\alpha,c,1/\beta} \propto e^{-\mathcal{H}^{f}_{\alpha,c,1/\beta}}$, where $\mathcal{H}^{f

Jun Lu, Christine P. Chai

We introduce a probabilistic model with implicit norm regularization for learning nonnegative matrix factorization (NMF) that is commonly used for predicting missing values and finding hidden patterns in the data, in which the matrix factors are latent variables associated with each data dimension. The nonnegativity constraint for the latent factors is handl

Sani Biswas, Chaman Kumar, Neelima, Gonçalo dos Reis

We propose an explicit drift-randomised Milstein scheme for both McKean--Vlasov stochastic differential equations and associated high-dimensional interacting particle systems with common noise. By using a drift-randomisation step in space and measure, we establish the scheme's strong convergence rate of $1$ under reduced regularity assumptions on the drift c

Guojing Cong, Anshul Gupta, Rodrigo Neumann, Maira de Bayser

We investigate the graph-based convolutional neural network approach for predicting and ranking gas adsorption properties of crystalline Metal-Organic Framework (MOF) adsorbents for application in post-combustion capture of $\textrm{CO}_2$. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent materia

Ruonan Li, Yichen Zhang, Yutao Tang, Shurong Li

This paper addresses the leader-following consensus problem for discrete-time positive multi-agent systems over time-varying graphs. We assume that the followers may have mutually different positive dynamics which can also be different from the leader. Compared with most existing positive consensus works for homogeneous multi-agent systems, the formulated pr

Liuyuan Wen, Baoyi Chen

We employ the time-dependent Schr\"odinger equation with different complex potentials to study the bottomonium sequential suppression in Pb-Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV and 5.02 TeV and Au-Au collisions at $\sqrt{s_{NN}}=200$ GeV. Both color screening effect and the random scatterings with thermal partons are considered in the real and imaginary

Liang Wang, Ying Li, Jierui Zhang, Xianping Tao

The document provides the proof to properties of community evolution indices including community split and shrink in paper: Liang Wang, Ying Li, Jierui Zhang, and Xianping Tao. 2022. Quantifying Community Evolution in Developer Social Networks. In Proceedings of the30th ACM Joint European Software Engineering Conference and Symposiumon the Foundations of Sof

Israel Quiros

In this paper we discuss on the phenomenological footprints of gauge invariant theories of gravity where the gravitational effects are due not only to spacetime curvature, but also to vectorial nonmetricity. We explore the possibility that vectorial nonmetricity and gauge symmetry may survive after $SU(2)\times U(1)$ (electroweak) symmetry breaking, so that

Jie Gu, Yunfeng Jiang, Marcus Sperling

The rational $Q$-system is an efficient method to solve Bethe ansatz equations for quantum integrable spin chains. We construct the rational $Q$-systems for generic Bethe ansatz equations described by an $A_{\ell-1}$ quiver, which include models with multiple momentum carrying nodes, generic inhomogeneities, generic diagonal twists and $q$-deformation. The r

Siteng Huang, Qiyao Wei, Donglin Wang

Compositional zero-shot learning (CZSL) refers to recognizing unseen compositions of known visual primitives, which is an essential ability for artificial intelligence systems to learn and understand the world. While considerable progress has been made on existing benchmarks, we suspect whether popular CZSL methods can address the challenges of few-shot and

Yuxuan Li, Yaoyao Han, Wenfei Liang, Boyu Zhang

Coherent interaction between matter and periodic light field induces both optical Stark effect (OSE) and Bloch-Siegert shift (BSS). Observing the BSS has been historically challenging, not only because it is weak but it is often accompanied by a much stronger OSE. Herein, by controlling the light helicity, we can largely restrict the OSE and BSS to different

Lucas O. Lyra, Antonio Elias Fabris, Joao B. Florindo

Convolutional neural networks have shown successful results in image classification achieving real-time results superior to the human level. However, texture images still pose some challenge to these models due, for example, to the limited availability of data for training in several problems where these images appear, high inter-class similarity, the absenc

Hualiang Wang, Siming Fu, Xiaoxuan He, Hangxiang Fang

Long-tailed learning aims to tackle the crucial challenge that head classes dominate the training procedure under severe class imbalance in real-world scenarios. However, little attention has been given to how to quantify the dominance severity of head classes in the representation space. Motivated by this, we generalize the cosine-based classifiers to a von

Zhen Huan

We develop a systematic 2-representation theory for coherent Lie 2-groups and its geometric incarnation via 2-vector bundles. For any coherent Lie 2-group $\mathcal{G}_{\bullet}$, we construct a bicategory 2Rep$(\mathcal{G}_{\bullet})$ of 2-representations valued in $k$-prelinear categories, and prove that biequivalent 2-groups induce biequivalent 2-represen

Ryohei Urata, Hong Liu, Kevin Yasumura, Erji Mao

In this paper, we describe Apollo, to the best of our knowledge, the world's first large-scale production deployment of optical circuit switches (OCSes) for datacenter networking. We will first describe the infrastructure challenges and use cases that motivated optical switching inside datacenters. We then delve into the requirements of OCSes for datacenter

Lei Ni, Fangyang Zheng

We consider the class of compact Hermitian manifolds whose Chern connection is Ambrose-Singer, namely, it has parallel torsion and curvature. We prove structure theorems for such manifolds.

H M Imran Kays, Arif Mohaimin Sadri

Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks i.e. robustness as well as to recover from the loss of functionality due to such disruptions i.e. rapidity. Therefore,

A. Shekhter, R. D. McDonald, B. J. Ramshaw, K. A. Modic

The magnetotropic susceptibility is the thermodynamic coefficient associated with the rotational anisotropy of the free energy in an external magnetic field, and is closely related to the magnetic susceptibility. It emerges naturally in frequency-shift measurements of oscillating mechanical cantilevers, which are becoming an increasingly important tool in th

Masoumah Al-Ali, Andrew R. Linshaw

The universal two-parameter ${\mathcal W}_{\infty}$-algebra is a classifying object for vertex algebras of type ${\mathcal W}(2,3,\dots, N)$ for some $N$. Gaiotto and Rap\v{c}\'ak recently introduced a large family of such vertex algebras called $Y$-algebras, which includes many known examples such as the principal ${\mathcal W}$-algebras of type $A$. These

Aizitiaili Abulikemu, Takumi Fukuda, Muneaki Hase

This study investigates the ultrafast dynamics of coherent phonons and phonon-polaritons in lithium niobate (LiNbO$_{3}$) crystals using reflective pump-probe spectroscopy with 25-fs time resolution. In addition to several coherent optical phonon modes, the electro-optic sampling measurements explored the coexistence of phonon-polariton E-modes near 3.8 and

Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu, Guan Huang

3D object detection with surrounding cameras has been a promising direction for autonomous driving. In this paper, we present SimMOD, a Simple baseline for Multi-camera Object Detection, to solve the problem. To incorporate multi-view information as well as build upon previous efforts on monocular 3D object detection, the framework is built on sample-wise ob

Kotaro Kawatani

Let $R$ be a commutative ring. We introduce the notion of support of objects in an $R$-linear triangulated category. As an application, we study the non-existence of Bridgeland stability conditions on $R$-linear triangulated categories.

Yihe Liu, Ziqi Yuan, Huisheng Mao, Zhiyun Liang

Multimodal sentiment analysis (MSA), which supposes to improve text-based sentiment analysis with associated acoustic and visual modalities, is an emerging research area due to its potential applications in Human-Computer Interaction (HCI). However, the existing researches observe that the acoustic and visual modalities contribute much less than the textual

Jay Bishnu, Andrew Gondoputro

Rapid development in deep learning model construction has prompted an increased need for appropriate training data. The popularity of large datasets - sometimes known as "big data" - has diverted attention from assessing their quality. Training on large datasets often requires excessive system resources and an infeasible amount of time. Furthermore, the supe

Shuai Wang, Xinkui He, Yueying Liang, Yabei Su

High harmonic generation in solids is becoming an important method for strong field solid state physics research. The power scale relationship between high harmonics and the driving laser is investigated both experimentally and theoretically. Results of the power scale dependence clearly divided the interaction into two regimes. The modification of the bandg

Christopher J. Crowley, Joshua L. Pughe-Sanford, Wesley Toler, Roman O. Grigoriev

Recent work suggests unstable recurrent solutions of the equations governing fluid flow can play an important role in structuring the dynamics of turbulence. Here we present a method for detecting intervals of time where turbulence "shadows" (spatially and temporally mimics) recurrent solutions. We find that shadowing occurs frequently and repeatedly in both

Andrey Baydin, Kenji Hayashida, Takuma Makihara, Fuyang Tay

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling tra

Fanxiaoyu Xia, Tongjiang Wang, Yang Su, Jie Zhao

We present a detailed analysis of a reflecting intensity perturbation in a large coronal loop that appeared as sloshing oscillation and lasted for at least one and a half periods. The perturbation is initiated by a microflare at one footpoint of the loop, propagates along the loop and is eventually reflected at the remote footpoint where significant brighten

Xiaoyi Gu, Santanu S. Dey, Álinson S. Xavier, Feng Qiu

In many operational applications, it is necessary to routinely find, within a very limited time window, provably good solutions to challenging mixed-integer linear programming (MILP) problems. An example is the Security-Constrained Unit Commitment (SCUC) problem, solved daily to clear the day-ahead electricity markets. Previous research demonstrated that mac

Kang Du, Yu Xiang

It has become increasingly common nowadays to collect observations of feature and response pairs from different environments. As a consequence, one has to apply learned predictors to data with a different distribution due to distribution shifts. One principled approach is to adopt the structural causal models to describe training and test models, following t

Olivier Martin, Charles Vial

A conjecture of Voisin states that two points on a smooth projective complex variety whose algebra of holomorphic forms is generated in degree 2 are rationally equivalent to each other if and only if their difference lies in the third step of the Bloch-Beilinson filtration. In this note, we formulate a generalization that allows for rational equivalence of e

Hyungjun Lee, Sejoon Lim

Recently, research using point clouds has been increasing with the development of 3D scanner technology. According to this trend, the demand for high-quality point clouds is increasing, but there is still a problem with the high cost of obtaining high-quality point clouds. Therefore, with the recent remarkable development of deep learning, point cloud up-sam

Zhize Li, Jian Li

We propose and analyze several stochastic gradient algorithms for finding stationary points or local minimum in nonconvex, possibly with nonsmooth regularizer, finite-sum and online optimization problems. First, we propose a simple proximal stochastic gradient algorithm based on variance reduction called ProxSVRG+. We provide a clean and tight analysis of Pr

Gilhyun Nam, Gyeongjae Choi, Kyungmin Lee

Training a deep learning model with artificially generated data can be an alternative when training data are scarce, yet it suffers from poor generalization performance due to a large domain gap. In this paper, we characterize the domain gap by using a causal framework for data generation. We assume that the real and synthetic data have common content variab

Bangwei Guo, Xingyu Li, Jitendra Jonnagaddala, Hong Zhang

Artificial intelligence (AI) models have been developed for predicting clinically relevant biomarkers, including microsatellite instability (MSI), for colorectal cancers (CRC). However, the current deep-learning networks are data-hungry and require large training datasets, which are often lacking in the medical domain. In this study, based on the latest Hier

Jianhui Li, Tingting Tang, Shimin Yu, Peng Yu

Porous materials are used in many fields, including energy industry, agriculture, medical industry, etc. The generation of digital porous media facilitates the fabrication of real porous media and the analysis of their properties. The past random digital porous media generation methods are unable to generate a porous medium with a specific permeability. A ne

Cole Foster, Berk Sevilmis, Benjamin Kimia

Similarity search is a fundamental building block for information retrieval on a variety of datasets. The notion of a neighbor is often based on binary considerations, such as the k nearest neighbors. However, considering that data is often organized as a manifold with low intrinsic dimension, the notion of a neighbor must recognize higher-order relationship

Jingcao Wu

In this paper we establish a Nadel-type vanishing theorem and a Kawamata--Viehweg-type vanishing theorem concerning the asymptotic multiplier ideal sheaf on a compact K\"{a}hler manifold $X$. After that, we provide a relative variant.

Rongli Huang, Yongmei Liang

In this paper, we study a class of special Lagrangian curvature potential equations and obtain the existence of smooth solutions for Dirichlet problem. The existence result is based on a priori estimates of global $C^{0}$, $C^{1}$ and $C^{2}$ norms of solutions under the assumption of existence of a subsolution.

Hsiao-Yi Chen, Takuya Nomoto, Ryotaro Arita

Exciton condensation indicating the spontaneous formation of electron-hole pair can cause the phase transition from a semimetal to an excitonic insulator by gap opening at the Fermi surface. While the idea of this excitonic insulator has been proposed for decades, current theoretical approaches can only provide qualitative descriptions, and a quantitative pr

Hirotsugu Suzui, Kazuharu Uchiyama, Kingo Uchida, Ryoichi Horisaki

Photochromic diarylethene is known to exhibit reversible photoisomerization under irradiation with ultraviolet (UV) and visible light. Besides reversible optical properties upon light irradiation, a variety of discontinuous morphological changes are reported in the literature, such as sudden crystal bending, cracking, and photosalient effects, which are caus