January 2022 arXiv papers — page 78

Rui Yang, Ercai Chen, Xiaoyao Zhou

Firstly, we introduce a new notion called induced upper metric mean dimension with potential, which naturally generalizes the definition of upper metric mean dimension with potential given by Tsukamoto to more general cases, then we establish variational principles for it in terms of upper and lower rate distortion dimensions and show there exists a Bowen's

Anindya Goswami, Kuldip Singh Patel

The fully discrete problem for convection-diffusion equation is considered. It comprises compact approximations for spatial discretization, and Crank-Nicolson scheme for temporal discretization. The expressions for the entries of inverse of tridiagonal Toeplitz matrix, and Gerschgorin circle theorem have been applied to locate the eigenvalues of the amplific

Pai Li, Xiongzhi Zeng, Zhenyu Li

Chemical reactions on metal surfaces are important in various processes such as heterogeneous catalysis and nanostructure growth. At moderate or lower temperatures, these reactions generally follow the minimum energy path and temperature effects can be reasonably described by a harmonic oscillator model. At a high temperature approaching the melting point of

Rogerio Rossi

Data and Science has stood out in the generation of results, whether in the projects of the scientific domain or business domain. CERN Project, Scientific Institutes, companies like Walmart, Google, Apple, among others, need data to present their results and make predictions in the competitive data world. Data and Science are words that together culminated i

Liang-Liang Liu, Su-Jun Cui, Jing Xu, Xin-Heng Guo

Using the Bethe-Salpeter equation (BSE) we investigate the forward-backward asymmetries $( A_{FB}) $ in $\Lambda_b \rightarrow \Lambda l^+ l^-(l=e,\mu,\tau)$ in the quark-diquark model. This approach provides precise form factors that are different from those of QCD sum rules. We calculate the rare decay form factors for $\Lambda_b \rightarrow \Lambda l^+ l^

Shuang Tang, Lucy Dow, Emmanuel Ojukwu

There are many applications involving the use of bismuth antimony thin films. However, due to the low crystalline symmetry and strong coupling between the electronic band edges, it has always been challenging to infer the electronic phase of such a material. Fortunately, with the development of pattern recognition technology, scientists can build many black-

Shuang Tang, Jenna Jean-Baptiste, Schuyler Vecchiano, Adam Lukasiewicz

With the development of modern nanoscience and nanotechnology, Bi1-xSbx can be synthesized into different nanoscale and nanostructured forms, including thin films, nanowires, nanotubes, nanoribbons, and many others. However, due to the strong correlation between electrons and holes at the L-point in the Brillouin zone, the direct band evolves in an anomalous

Florian Meier

Recent research has shown how strongly Wikipedia and other web services or platforms are connected. For example, search engines rely heavily on surfacing Wikipedia links to satisfy their users' information needs and volunteer-created Wikipedia content frequently gets re-used on other social media platforms like Reddit. However, publicly accessible datasets t

Shuang Tang, Andy Juan, David Drysdale, Joseph Duarte Menjivar

With the technology of artificial defects creating, we can tune the band structure and transport properties of many two-dimensional (2D) layered materials. One prototype materials system is the antidoted graphene sheet, where periodical pores are made using focuses ion or electron beams in the nanoscale. We here study the electrical conductivity, thermopower

G. Alestas, L. Perivolaropoulos, K. Tanidis

It has recently been pointed out that a gravitational transition taking place at a recent redshift $z_t$, reducing the effective gravitational constant $G_{\rm eff}$ by about $10\%$ for $z>z_t$, has the potential to lead to a resolution of the Hubble tension if $z_t\lesssim 0.01$. Since $H(z)^2\sim G_{\rm eff}$, such a transition would also lead to sharp cha

Shansong Liu, Mengzhe Geng, Shoukang Hu, Xurong Xie

Despite the rapid progress of automatic speech recognition (ASR) technologies in the past few decades, recognition of disordered speech remains a highly challenging task to date. Disordered speech presents a wide spectrum of challenges to current data intensive deep neural networks (DNNs) based ASR technologies that predominantly target normal speech. This p

Haddi Ahmadi, Amin Khavasi

In this work, we prove a theorem that states the electromagnetic (EM) duality correspondence between eigenmodes of complementary structures, induces counterpropagating spin-polarized states in different types of waveguides where mirror reflection symmetries are preserved around one (or more) arbitrary plane(s). Similar to photonic topological insulators (PTI

Won Joon Yun, Soohyun Park, Joongheon Kim, MyungJae Shin

CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments. This paper creates a case where the UAVs with CCTV-cameras fly over the city area for flexible and reliable surveillance services. UAVs should be deployed to cover a large area while minimize overlapping and shadow areas for a

Igor Fedorov, Ramon Matas, Hokchhay Tann, Chuteng Zhou

Deploying TinyML models on low-cost IoT hardware is very challenging, due to limited device memory capacity. Neural processing unit (NPU) hardware address the memory challenge by using model compression to exploit weight quantization and sparsity to fit more parameters in the same footprint. However, designing compressible neural networks (NNs) is challengin

Qilin Wang, Rongfang Liu, Hong-Mei Zou, Dan Long

In this work, the entanglement dynamics of a moving-biparticle system driven by an external classical field are investigated, where the moving-biparticle system is coupled with a zero temperature common environment. The analytical expressions of the density operator and the entanglement can be obtained by using the dressed-state basis when the total excitati

Graham Manuell

We describe the congruence lattices of frames and $\kappa$-frames. We look at the role that congruence biframes play in the category of strictly zero-dimensional biframes and discuss some reflections and coreflections of congruence frames.

Egor Illarionov, Andrey Tlatov

Sunspot groups observed in white-light appear as complex structures. Analysis of these structures is usually based on simple morphological descriptors which capture only generic properties and miss information about fine details. We present a machine learning approach to introduce a complete yet compact description of sunspot groups. The idea is to map sunsp

H. E. S. S. Collaboration, F. Aharonian, F. Ait Benkhali, E. O. Anguner

Observations with imaging atmospheric Cherenkov telescopes (IACTs) have enhanced our knowledge of nearby supernova (SN) remnants with ages younger than 500 years by establishing Cassiopeia A and the remnant of Tycho's SN as very-high-energy (VHE) gamma-ray sources. The remnant of Kepler's SN, which is the product of the most recent naked-eye supernova in our

Faisal Nadeem, Yonghui Li, Branka Vucetic, Mahyar Shirvanimoghaddam

This paper analyzes wireless network control for remote estimation of linear time-invariant dynamical systems under various Hybrid Automatic Repeat Request (HARQ) packet retransmission schemes. In conventional HARQ, packet reliability increases gradually with additional packets; however, each retransmission maximally increases the Age of Information and caus

Supriyo Ghosh, J. P. Ninan, D. K. Ojha

We explored here the near-infrared $H$-band atmospheric window aiming to provide quantitative diagnostic tools for deriving stellar parameters, for instance, effective temperature ($T_{eff}$) and metallicity ([$Fe/H$]), of cool giants ($T_{eff}$ $<$ 5000 K) using low-resolution spectra. We obtained 177 cool giants from the X-shooter spectral library covering

Esmerando Escoto, Anne-Lise Viotti, Skirmantas Alisauskas, Henrik Tünnermann

Post-compression of ultra-short laser pulses via self-phase modulation is routinely employed for the generation of laser pulses with optical bandwidths reaching far beyond the laser gain limitations. While high compression factors can be routinely achieved, the compressed pulses typically suffer from temporal quality degradation. We numerically and experimen

Daoyi Dong, Ian R Petersen

The development of estimation and control theories for quantum systems is a fundamental task for practical quantum technology. This vision article presents a brief introduction to challenging problems and potential opportunities in the emerging areas of quantum estimation, control and learning. The topics cover quantum state estimation, quantum parameter ide

Yi Zhang, Mingyuan Chen, Jundong Shen, Chongjun Wang

Multi-modal Multi-label Emotion Recognition (MMER) aims to identify various human emotions from heterogeneous visual, audio and text modalities. Previous methods mainly focus on projecting multiple modalities into a common latent space and learning an identical representation for all labels, which neglects the diversity of each modality and fails to capture

L. Chen, L. Q. Zhou, Y. Zhou, C. Liu

Looking for new materials with Dirac points has been a fascinating subject of research. Here we report the growth, crystal structure, and band structure of HfGe0.92Te single crystals, featuring three different types of Dirac points. HfGe0.92Te crystalizes in a nonsymmorphic tetragonal space group P4/nmm (No. 129), having square Ge-atom plane with vacancies a

Xue-An Pan, Zhong-Ming Niu, Mao Song, Yu Zhang

In this work, we investigate the next-to-leading order (NLO) QCD correction to $J/\psi$ associated production with a bottom quark pair from the Higgs boson decay within the nonrelativistic QCD framework. From numerical results, {we find that the decay width of process $H \rightarrow b+ J/\psi+\bar{b}$ at leading order (LO) mainly comes from the contribution

Yin-Fa Shen, Jian-Nan Ding, Qin Qin

The existence of heavy neutrinos is the most prominent feature of type-I seesaw-like mechanisms, which naturally explain tiny masses of observed neutrinos. Various experiments have been conducted to search for heavy neutrinos, with meson decays sensitive to heavy neutrinos lighter than $B$ mesons and high energy collider experiments sensitive to the ones wit

Atmadev Rai, Bikash K. Behera

Here we demonstrate quantum teleportation through hypergraph states, which are the generalization of graph states, and due to their non-local entanglement properties, it allows us to perform quantum teleportation. Here we design some hypergraph states useful for quantum teleportation and process the schemes for quantum teleportation of single-qubit and two-q

Arash Mehrjou, Ashkan Soleymani, Stefan Bauer, Bernhard Schölkopf

Model-free and model-based reinforcement learning are two ends of a spectrum. Learning a good policy without a dynamic model can be prohibitively expensive. Learning the dynamic model of a system can reduce the cost of learning the policy, but it can also introduce bias if it is not accurate. We propose a middle ground where instead of the transition model,

Run-kun Lu, Jian-wei Liu, Si-ming Lian, Xin Zuo

Over recent decades have witnessed considerable progress in whether multi-task learning or multi-view learning, but the situation that consider both learning scenes simultaneously has received not too much attention. How to utilize multiple views latent representation of each single task to improve each learning task performance is a challenge problem. Based

Dennis Leung, Ninh Tran

In multiple hypothesis testing, it is well known that adaptive procedures can enhance power via incorporating information about the number of true nulls present. Under independence, we establish that two adaptive false discovery rate (FDR) methods, upon augmenting sign declarations, also offer directional false discovery rate (FDR$_\text{dir}$) control in th

Cristian Moreno-Pulido, Joan Sola Peracaula

The renormalization of the vacuum energy in quantum field theory (QFT) is usually plagued with theoretical conundrums related not only with the renormalization procedure itself, but also with the fact that the final result leads usually to very large (finite) contributions incompatible with the measured value of $\Lambda$ in cosmology. Herein, we compute the

A. Pierret, D. Mele, H. Graef, J. Palomo

In view of the extensive use of hexagonal boron nitride (hBN) in 2D material electronics, it becomes important to refine its dielectric characterization in terms of low-field permittivity and high-field strength and conductivity up to the breakdown voltage. The present study aims at filling this gap using DC and RF transport in two Au-hBN-Au capacitor series

Muhammad Waseem, Peng Liang, Aakash Ahmad, Mojtaba Shahin

Researchers and practitioners have recently proposed many Microservices Architecture (MSA) patterns and strategies covering various aspects of microservices system life cycle, such as service design and security. However, selecting and implementing these patterns and strategies can entail various challenges for microservices practitioners. To this end, this

Jiří Liška, Tomáš Krajňák, Peter Kepič, Martin Konečný

Phthalocyanines as organic semiconductors and molecular magnets provide plenty of industrial or high-tech applications from dyes and pigments up to gas sensors, molecular electronics, spintronics and quantum computing. Copper phthalocyanine (CuPc) belongs among the most used phthalocyanines, typically in the form of powder or films but self-grown nanowires a

K. Mizuyama, H. Dai Nghia, T. Dieu Thuy, N. Hoang Tung

In this study, we analyzed how the incident neutron current is affected by the pairing effect in the neutron-nucleus scattering described within the framework of Hartree-Fock-Bogoliubov theory by performing numerical calculations in terms of current, vorticity, and circulation of the incident neutron current. We found that the pairing effect on the incident

Volker W. Elling

It is shown that the $\gamma$-van der Waals equation of state (eos) permits shock polars with supersonic critical points, corresponding to critical or strong-type shock reflections that are supersonic, which is not possible for ideal gas. It is also shown that general van der Waals eos permit polars with multiple critical points, corresponding to four or mor

Keith Ball

This note contains a short proof of the functional equation for the zeta function.

Yi Yan, Ercan E. Kuruoglu, Mustafa A. Altinkaya

Efficient and robust online processing technique of irregularly structured data is crucial in the current era of data abundance. In this paper, we propose a graph/network version of the classical adaptive Sign algorithm for online graph signal estimation under impulsive noise. Recently introduced graph adaptive least mean squares algorithm is unstable under

David Banh, Alan Huang

Large information sizes in samples and features can be encoded to speed up the learning of statistical models based on linear algebra and remove unwanted signals. Encoding information can reduce both sample and feature dimension to a smaller representational set. Here two examples are shown on linear mixed models and mixture models speeding up the run time f

Menglin Wang, Jiachen Li, Baisheng Lai, Xiaojin Gong

Recently, unsupervised person re-identification (Re-ID) has received increasing research attention due to its potential for label-free applications. A promising way to address unsupervised Re-ID is clustering-based, which generates pseudo labels by clustering and uses the pseudo labels to train a Re-ID model iteratively. However, most clustering-based method

Yuefei Lyu, Xiaoyu Yang, Jiaxin Liu, Philip S. Yu

Social networks are frequently polluted by rumors, which can be detected by advanced models such as graph neural networks. However, the models are vulnerable to attacks and understanding the vulnerabilities is critical to rumor detection in practice. To discover subtle vulnerabilities, we design a powerful attacking algorithm to camouflage rumors in social n

Florian Ellsaesser, Guido Fioretti, Gail E. James

There are two reasons why uncertainty may not be adequately described by Probability Theory. The first one is due to unique or nearly-unique events, that either never realized or occurred too seldom for frequencies to be reliably measured. The second one arises when one fears that something may happen, that one is not even able to figure out, e.g., if one as

Matthew Deakin, Phil C. Taylor, Janusz Bialek, Wenlong Ming

Distribution systems will require new cost-effective solutions to provide network capacity and increased flexibility to accommodate Low Carbon Technologies. To address this need, we propose the Hybrid Multi-Terminal Soft Open Point (Hybrid MT-SOP) to efficiently provide distribution system interconnection capacity. Each leg of the Hybrid MT-SOP has an AC/DC

Meng Xu, Youchen Wang, Bin Xu, Jun Zhang

Camera, and associated with its objects within the field of view, localization could benefit many computer vision fields, such as autonomous driving, robot navigation, and augmented reality (AR). In this survey, we first introduce specific application areas and the evaluation metrics for camera localization pose according to different sub-tasks (learning-bas

Adrien Casejuane, Jean-Baptiste Meilhan

Welded knotted objects are a combinatorial extension of knot theory, which can be used as a tool for studying ribbon surfaces in $4$-space. A finite type invariant theory for ribbon knotted surfaces was developped by Kanenobu, Habiro and Shima, and this paper proposes a study of these invariants, using welded objects. Specifically, we study welded string lin

D. S. Delion, S. A. Ghinescu

The simultaneous emission of two protons is an exotic and complex three-body process. It is very important for experimental groups investigating the nuclear stability on the proton drip line to have a simple rule predicting the two-proton decay widths with a reasonable accuracy for transitions between ground as well as excited states in terms of relevant phy

Elisa Gorla, Alberto Ravagnani

We develop an algebraic theory of supports for $R$-linear codes of fixed length, where $R$ is a finite commutative unitary ring. A support naturally induces a notion of generalized weights and allows one to associate a monomial ideal to a code. Our main result states that, under suitable assumptions, the generalized weights of a code can be obtained from the

Maoran Zhu, Yuanxin Wu

In this paper, a new framework for continuous-time maximum a posteriori estimation based on the Chebyshev polynomial optimization (ChevOpt) is proposed, which transforms the nonlinear continuous-time state estimation into a problem of constant parameter optimization. Specifically, the time-varying system state is represented by a Chebyshev polynomial and the

Mridula Mundalia, S. Sivaprasad Kumar

We introduce and study a new Ma-Minda subclass of starlike functions $\mathcal{S}^*_{\varrho},$ defined as $$\mathcal{S}^{*}_{\varrho}:=\left\{f\in\mathcal{A}:\frac{zf'(z)}{f(z)} \prec \cosh \sqrt{z}=:\varrho(z), z\in\mathbb{D} \right\},$$ associated with an analytic univalent function $\cosh \sqrt{z},$ where we choose the branch of the square root function

Siming Zheng, Xiaoyu Yang, Xin Yuan

We consider the reconstruction problem of video compressive sensing (VCS) under the deep unfolding/rolling structure. Yet, we aim to build a flexible and concise model using minimum stages. Different from existing deep unfolding networks used for inverse problems, where more stages are used for higher performance but without flexibility to different masks an

Qiushi Shi, Ponnuthurai Nagaratnam Suganthan, Rakesh Katuwal

In this paper, we first introduce batch normalization to the edRVFL network. This re-normalization method can help the network avoid divergence of the hidden features. Then we propose novel variants of Ensemble Deep Random Vector Functional Link (edRVFL). Weighted edRVFL (WedRVFL) uses weighting methods to give training samples different weights in different

Shagun Banga, S. Sivaprasad Kumar

Following the trend of coefficient bound problems in Geometric Function Theory, in the present paper, we obtain the sharp bound of $|H_3(1)|$ for the class $\mathcal{S}^*$, of starlike functions and $\mathcal{SL}_q^*$, of $q$- starlike functions related with lemniscate of Bernoulli. Bound on the initial class is also an improvement over the existing known bo

Armando Pezo, Diego Garcia Ovalle, Aurelien Manchon

The orbital Hall effect (OHE) designates the generation of a charge-neutral flow of orbital angular momentum transverse to an initial charge current. Recent theoretical investigations suggest that transition metals display sizable OHE, encouraging experimental search along this direction. Nonetheless, most of these theories assume that the orbital moment ori

Linjie Ding, Dongchao Yang, LiZhi Yi, Yunli Xu

The spin Seebeck effect (SSE) in ferrimagnetic insulators (FMI) provides a simple method of using heat to manipulate magnons, which could be used as carriers of information and energy conversion. However, a theory that can quantitively interpret experimental results is still lacking. In this paper, we develop a transport theory of magnons in FMI at low tempe

Gan Ren

ZrCo alloy is promising to substitute uranium for handling hydrogen isotope storage in thermonuclear reactor. The alloying substitution of Zr in ZrCo with Hf or Ti can enhance the ability of anti-disproportionation. In this work, Zr$_{0.75}$Hf$_{0.25}$Co and Zr$_{0.75}$Ti$_{0.25}$Co were considered in the framework of density functional theory, aimed to inve

Gan Ren

The effective hydrodynamic radius is usually assumed to be a constant in testing the Stokes-Einstein relation by its variants. We have performed molecular dynamics simulations with ortho-terphenyl and Kob-Andersen model to examine the assumption and found the effective hydrodynamic radius is not a constant but decreases with decreasing temperature. The varia

Surya Giri, S. Sivaprasad Kumar

\noindent In the present investigation, we find the sharp bound of fifth coefficient of analytic normalized function $f$ satisfying $z f'(z)/f(z) \prec \varphi(z)$ when coefficients of $\varphi$ satisfy certain conditions. For an appropriate choice of $\varphi$, the already known estimates for various other subclasses of starlike functions follow directly fr

Tianjiao Wang, Zengfu Wang, Bill Moran, Moshe Zukerman

This paper optimizes path planning for a trunkand-branch topology network in an irregular 2-dimensional manifold embedded in 3-dimensional Euclidean space with application to submarine cable network planning. We go beyond our earlier focus on the costs of cable construction (including labor, equipment and materials) together with additional cost to enhance c

Tong Yang, Jun Zhou, Xiaoyang Ma, Keda Ding

Inter-site interactions between single atom catalysts (SACs) in the high loading regime are critical to tuning the catalytic performance. However, the understanding on such interactions and their distance dependent effects remains elusive, especially for the heteronuclear SACs. In this study, we reveal the effects of the distance-dependent inter-site interac

Lea M. Versbach, Viktor Linders, Robert Klöfkorn, Philipp Birken

We discuss two approaches for the formulation and implementation of space-time discontinuous Galerkin spectral element methods (DG-SEM). In one, time is treated as an additional coordinate direction and a Galerkin procedure is applied to the entire problem. In the other, the method of lines is used with DG-SEM in space and the fully implicit Runge-Kutta meth

Antonio Jimeno Yepes

Deep learning methods minimise the empirical risk using loss functions such as the cross entropy loss. When minimising the empirical risk, the generalisation of the learnt function still depends on the performance on the training data, the Vapnik-Chervonenkis(VC)-dimension of the function and the number of training examples. Neural networks have a large numb

Shin Sano, Seiji Yamada

We propose an AI-assisted design concept exploration tool, the "Character Space Construction" ("CSC"). Concept designers explore and articulate the target product aesthetics and semantics in language, which is expressed using "Design Concept Phrases" ("DCPs"), that is, compound adjective phrases, and contrasting terms that convey what are not their target de

Daniel Kang, Nikos Arechiga, Sudeep Pillai, Peter Bailis

ML is being deployed in complex, real-world scenarios where errors have impactful consequences. In these systems, thorough testing of the ML pipelines is critical. A key component in ML deployment pipelines is the curation of labeled training data. Common practice in the ML literature assumes that labels are the ground truth. However, in our experience in a

Margarita Safonova

Gravitational lensing is brightening of background objects due to deflection of light by foreground sources. Rich clusters of galaxies are very effective lenses because they are centrally concentrated. Such natural Gravitational Telescopes provide us with strongly magnified galaxies at high redshifts otherwise too faint to be detected or analyzed. With a len

F. Bosia, V. Dal Poggetto, A. S. Gliozzi, G. Greco

Nature has engineered complex designs to achieve advanced properties and functionalities through evolution, over millions of years. Many organisms have adapted to their living environment producing extremely efficient materials and structures exhibiting optimized mechanical, thermal, optical properties, which current technology is often unable to reproduce.

Arnaud Ducrot, Zhucheng Jin

We investigate the asymptotic speed of spread of the solutions of a non-autonomous Fisher-KPP equation with nonlocal diffusion, driven by a thin-tailed kernel. In this paper, we are concerned with both compactly supported and exponentially decaying initial data. For general time heterogeneity, we provide lower and upper estimates of the spreading speed of th

Tanusree Sharma, Zhixuan Zhou, Yun Huang, Yang Wang

NFTs (Non-Fungible Tokens) are blockchain-based cryptographic tokens to represent ownership of unique content such as images, videos, or 3D objects. Despite NFTs' increasing popularity and skyrocketing trading prices, little is known about people's perceptions of and experiences with NFTs. In this work, we focus on NFT creators and present results of an expl

Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal

Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily on generic multi-hop reasoning over explicit facts, largely ignoring other reasoning types such as temporal, spatial, and taxonomic reasoning. In this paper, we present a benchmark

Albi Kerbizi, Xavier Artru, Anna Martin

The recently developed quantum mechanical string+${}^3P_0$ model of polarized quark fragmentation with pseudoscalar and vector meson production has been implemented in a stand alone Monte Carlo program. The simulation enables the detailed study of the quark spin dependent effects in the fragmentation process such as the transverse spin asymmetries. In partic

Abdullah Al Hussain, Md. Akhtaruzzaman Emon, Toufiq Ahmed Tanna, Rasel Iqbal Emon

The spirit of "blockchain technology" is a distributed database in which saved data is transparent, accountable, public, immutable, and traceable. This base-level disruptive technology can boost the security and privacy-related efficiency of various domains. As Bangladesh is currently aiming for sustainable development, blockchain technology adoption by loca

Vanshaj Kerni, Jyothsna Rani Komaragiri

Understanding the physical world is a continuous process of trial and error. It requires theoretical background and tools to find out the theory's accuracy. Particles motion through matter, and their energy loss is one such process. Testing the energy loss requires the development of a tool capable of simulating and testing theoretical predictions using data

J. Ou aali, M. Ouali, M. Ouhammou, S. Taj

In the framework of Higgs triplet model (HTM), we study the pair production process of doubly charged Higgs bosons via $e^{+}e^{-}$ annihilation in the presence of a laser field with circular polarization . We begin our work by presenting the theoretical calculation of the differential cross section in the centre of mass frame including both $Z$ and $\gamma$

Naga Dileep Varikuti, Vaibhav Madhok

We study operator growth in a bipartite kicked coupled tops (KCT) system using out-of-time ordered correlators (OTOCs), which quantify ``information scrambling" due to chaotic dynamics and serve as a quantum analog of classical Lyapunov exponents. In the KCT system, chaos arises from the hyper-fine coupling between the spins. Due to a conservation law, the s

Luigi Montoro, Berardino Sciunzi

In this paper we derive the Pohozaev identity for quasilinear equations \begin{equation}\tag{$E$}\label{eq:p} -\operatorname{div}(B'(H(\nabla u))\nabla H(\nabla u))=g(x, u) \quad \text {in}\,\, \Omega, \end{equation} involving the anisotropic Finsler operator $-\operatorname{div}(B'(H(\nabla u))\nabla H(\nabla u))$. In particular, by means of fine regularity

Tianyi Yang, Yuxiang Zhai, Dengji Zhao, Xinwei Song

Mechanism design on social networks is a hot research direction recently, and we have seen many interesting results in auctions and matching. Compared to the traditional settings, the new goal of the network settings is that we need to design incentives to incentivize the participants of the game to invite their neighbors on the network to join the game. Thi

Kan He, Shusen Liu, Jinchuan Hou

Ying conceived of using two or more small-capacity quantum computers to produce a larger-capacity quantum computing system by quantum parallel programming ([M. S. Ying, Morgan-Kaufmann, 2016]). In doing so, the main obstacle is separating the quantum gates in the whole circuit to produce a tensor product of the local gates. It has been showed that there are

Xiaoxia Wang, Chang Xu

In this paper, a new $q$-supercongruence with two free parameters modulo the fourth power of a cyclotomic polynomial is obtained. Our main auxiliary tools are Watson's $_8\phi_7$ transformation formula for basic hypergeometric series, the `creative microscoping' method recently introduced by Guo and Zudilin and the Chinese remainder theorem for coprime polyn

Zihao Zhou, Maolin Li, Weipeng Guan

We proposed and experimentally demonstrated a new hybrid code structure based on the overlapping of two light sources to produce the effect of multi-voltage amplitudes. And we also proposed an efficient polarity reversal threshold (RRT) algorithm for multilevel based OCC system. Then taking the issue of SPO into account, a novel adaptive sampling method (ASM

Emmanouil Lardas, Evangelos Protopapas, Dimitrios M. Thilikos, Dimitris Zoros

A strict bramble of a graph $G$ is a collection of pairwise-intersecting connected subgraphs of $G.$ The order of a strict bramble ${\cal B}$ is the minimum size of a set of vertices intersecting all sets of ${\cal B}.$ The strict bramble number of $G,$ denoted by ${\sf sbn}(G),$ is the maximum order of a strict bramble in $G.$ The strict bramble number of $

Jibao Qiu, C. L. Philip Chen, Tong Zhang

Symbolic Music Emotion Recognition(SMER) is to predict music emotion from symbolic data, such as MIDI and MusicXML. Previous work mainly focused on learning better representation via (mask) language model pre-training but ignored the intrinsic structure of the music, which is extremely important to the emotional expression of music. In this paper, we present

Tong Zhang, Haohan Weng, Ke Yi, C. L. Philip Chen

Convolutional Neural Networks (CNNs) have exhibited their great power in a variety of vision tasks. However, the lack of transform-invariant property limits their further applications in complicated real-world scenarios. In this work, we proposed a novel generalized one dimension convolutional operator (OneDConv), which dynamically transforms the convolution

Yuting Yang, Wenqiang Lei, Pei Huang, Juan Cao

Dialogue state tracking (DST) module is an important component for task-oriented dialog systems to understand users' goals and needs. Collecting dialogue state labels including slots and values can be costly, especially with the wide application of dialogue systems in more and more new-rising domains. In this paper, we focus on how to utilize the language un

Fan Yang

We prove Anderson localization for all Diophantine frequencies and all non-resonant phases for a model that arises from 2D quantum walk model subject to an external magnetic field. This is the first localization result for all Diophantine frequencies in the magnetic quantum walk and the quasi-periodic CMV setting. We also obtain sharp asymptotics of the loca

Hao Chen, Yifan Zao, Liqin Liu, Song Chen

Contemporary transfer learning-based methods to alleviate the data insufficiency in change detection (CD) are mainly based on ImageNet pre-training. Self-supervised learning (SSL) has recently been introduced to remote sensing (RS) for learning in-domain representations. Here, we propose a semantic decoupled representation learning for RS image CD. Typically

Ralph Adrian E. Farrales, Herbert B. Domingo, Eric A. Galapon

A time operator is a Hermitian operator that is canonically conjugate to a given Hamiltonian. For a particle in 1-dimension, a Hamiltonian conjugate operator in position representation can be obtained by solving a hyperbolic second-order partial differential equation, known as the time kernel equation, with some boundary conditions. One possible solution is

Yu Geng, Zongbo Han, Changqing Zhang, Qinghua Hu

Learning from different data views by exploring the underlying complementary information among them can endow the representation with stronger expressive ability. However, high-dimensional features tend to contain noise, and furthermore, the quality of data usually varies for different samples (even for different views), i.e., one view may be informative for

Daniel Lundstrom, Alexander Huyen, Arya Mevada, Kyongsik Yun

Deep learning (DL) has proven to be an effective machine learning and computer vision technique. DL-based image segmentation, object recognition and classification will aid many in-situ Mars rover tasks such as path planning and artifact recognition/extraction. However, most of the Deep Neural Network (DNN) architectures are so complex that they are consider

Arnaud Ducrot, Pierre Magal

In this work, we develop a mathematical model to describe the local movement of individuals by taking into account their return to home after a period of travel. We provide a suitable functional framework to handle this system and study the large-time behavior of the solutions. We extend our model by incorporating a colonization process and applying the retu

Jiqing Wu, Nanda Horeweg, Marco de Bruyn, Remi A. Nout

Randomized controlled trials (RCTs) are considered as the gold standard for testing causal hypotheses in the clinical domain. However, the investigation of prognostic variables of patient outcome in a hypothesized cause-effect route is not feasible using standard statistical methods. Here, we propose a new automated causal inference method (AutoCI) built upo

Weiwei Song, Zhi Gao, Renwei Dian, Pedram Ghamisi

Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing learning as the current mainstream method has achieved satisfactory retrieval performance. On one hand, various deep neural networks are used to extract semantic features of remote

Saida Mussakhojayeva, Yerbolat Khassanov, Huseyin Atakan Varol

We present an expanded version of our previously released Kazakh text-to-speech (KazakhTTS) synthesis corpus. In the new KazakhTTS2 corpus, the overall size has increased from 93 hours to 271 hours, the number of speakers has risen from two to five (three females and two males), and the topic coverage has been diversified with the help of new sources, includ

Yang Zhong, Hongyu Yu, Xingao Gong, Hongjun Xiang

Message-passing neural networks (MPNN) have shown extremely high efficiency and accuracy in predicting the physical properties of molecules and crystals, and are expected to become the next-generation material simulation tool after the density functional theory (DFT). However, there is currently a lack of a general MPNN framework for directly predicting the

J. Zhu, N. M. Lockmann, M. K. Czwalinna, H. Schlarb

Longitudinal properties of electron bunches are critical for the performance of a wide range of scientific facilities. In a free-electron laser, for example, the existing diagnostics only provide very limited longitudinal information of the electron bunch during online tuning and optimization. We leverage the power of artificial intelligence to build a neura

Nitish Yadav, S. A. Hashmi

We present a novel tin based flexible, gel polymer negative electrode for use in sodium-ion devices. The electrodes have been prepared by trapping tin micro-particles in a porous electrolyte membrane formed by immersion precipitation phase-inversion and soaking in a sodium-ion conducting liquid electrolyte. The tin particles are the active electrode material

Lishun Wang, Zongliang Wu, Yong Zhong, Xin Yuan

Spectral compressive imaging (SCI) is able to encode the high-dimensional hyperspectral image to a 2D measurement, and then uses algorithms to reconstruct the spatio-spectral data-cube. At present, the main bottleneck of SCI is the reconstruction algorithm, and the state-of-the-art (SOTA) reconstruction methods generally face the problem of long reconstructi

Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti

Large transformer models can highly improve Answer Sentence Selection (AS2) tasks, but their high computational costs prevent their use in many real-world applications. In this paper, we explore the following research question: How can we make the AS2 models more accurate without significantly increasing their model complexity? To address the question, we pr

Zhen Gao, Ziwei Wan, Dezhi Zheng, Shufeng Tan

Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for realizing future wireless systems. In this paper, we propose an ISAC processing framework relying on millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Specifically, we provide a compressed sampling (CS) perspective to facilitate IS

Sebastian Wallkotter, Mohamed Chetouani, Ginevra Castellano

Robots that share an environment with humans may communicate their intent using a variety of different channels. Movement is one of these channels and, particularly in manipulation tasks, intent communication via movement is called legibility. It alters a robot's trajectory to make it intent expressive. Here we propose a novel evaluation method that improves

Diab W. Abueidda, Seid Koric, Rashid Abu Al-Rub, Corey M. Parrott

The potential energy formulation and deep learning are merged to solve partial differential equations governing the deformation in hyperelastic and viscoelastic materials. The presented deep energy method (DEM) is self-contained and meshfree. It can accurately capture the three-dimensional (3D) mechanical response without requiring any time-consuming trainin

Wei-Chang Yeh

The Monte Carlo simulation (MCS) is a statistical methodology used in a large number of applications. It uses repeated random sampling to solve problems with a probability interpretation to obtain high-quality numerical results. The MCS is simple and easy to develop, implement, and apply. However, its computational cost and total runtime can be quite high as