May 2022 arXiv papers — page 90

Md Arafat Sultan, Avirup Sil, Radu Florian

Machine learning models are prone to overfitting their training (source) domains, which is commonly believed to be the reason why they falter in novel target domains. Here we examine the contrasting view that multi-source domain generalization (DG) is first and foremost a problem of mitigating source domain underfitting: models not adequately learning the si

Victor Olkhov

The random values and volumes of consecutive trades made at the exchange with shares of security determine its mean, variance, and higher statistical moments. The volume weighted average price (VWAP) is the simplest example of such a dependence. We derive the dependence of the market-based variance and 3rd statistical moment of prices on the means, variances

Jan Harms

New concepts were recently proposed for gravitational-wave (GW) detectors on the Moon. These include laser-interferometric detectors, proposed as free-range or optical-fiber interferometers, and inertial acceleration sensors. Some of them exploit the response of the Moon to GWs, others follow the design of current laser-interferometric GW detectors, which di

Jiri Podolsky, Roland Steinbauer

Impulsive gravitational waves in Minkowski space were introduced by Roger Penrose at the end of the 1960s, and have been widely studied over the decades. Here we focus on nonexpanding waves which later have been generalized to impulses traveling in all constant-curvature backgrounds, i.e., the (anti-)de Sitter universe. While Penrose's original construction

Jian Ma

Independence and Conditional Independence (CI) are two fundamental concepts in probability and statistics, which can be applied to solve many central problems of statistical inference. There are many existing independence and CI measures defined from diverse principles and concepts. In this paper, the 16 independence measures and 16 CI measures were reviewed

Stefano Rinaldi, Walter Del Pozzo

The copious scientific literature produced after the detection of GW170817 electromagnetic counterpart demonstrated the importance of a prompt and accurate localization of the gravitational wave within the co-moving volume. In this letter, we present FIGARO, a ready to use and publicly available software that relies on Bayesian non-parametrics. FIGARO is des

Meir Shimon

A `bouncing' cosmological model is proposed in the context of a Weyl-invariant scalar-tensor (WIST) theory of gravity. In addition to being Weyl-invariant the theory is U(1)-symmetric and has a conserved global charge. The entire cosmic background evolution is accounted for by a complex scalar field that evolves in the static `comoving' frame. Its (dimension

Cheng Feng

This study focuses on two important problems related to applying offline model-based optimization to real-world industrial control problems. The first problem is how to create a reliable probabilistic model that accurately captures the dynamics present in noisy industrial data. The second problem is how to reliably optimize control parameters without activel

Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie

Deep generative models have achieved tremendous success in designing novel drug molecules in recent years. A new thread of works have shown the great potential in advancing the specificity and success rate of in silico drug design by considering the structure of protein pockets. This setting posts fundamental computational challenges in sampling new chemical

Marcel Herzog, Patrizia Longobardi, Mercede Maj

In this paper we shall deal with periodic groups, in which each element has a prime power order. A group $G$ will be called a $BCP$-group if each element of $G$ has a prime power order and for each $p\in \pi(G)$ there exists a positive integer $u_p$ such that each $p$-element of $G$ is of order $p^i\leq p^{u_p}$. A group $G$ will be called a $BSP$-group if e

Sen Guo, Guan-Ru Li, En-Wei Liang

The observable characteristics of the charged black hole (BH) surrounded by a thin disk accretion are investigated in the Rastall gravity. We found that the radii of the direct emission, lensing ring, and photon ring dramatically increased as the radiation field parameter increases, but they only weakly depend on the BH charge. Three positions of the radiati

Graham W. Pulford

Expectation maximisation (EM) is an unsupervised learning method for estimating the parameters of a finite mixture distribution. It works by introducing "hidden" or "latent" variables via Baum's auxiliary function $Q$ that allow the joint data likelihood to be expressed as a product of simple factors. The relevance of EM has increased since the introduction

Haoran Chen, Junren Shi

We develop a stochastic path-integral approach for predicting the superconducting transition temperatures of anharmonic solids. By defining generalized Bloch basis, we generalize the formalism of the stochastic path-integral approach, which is originally developed for liquid systems. We implement the formalism for ab initio calculations using the projector a

Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou

Semi-supervised Learning (SSL) has witnessed great success owing to the impressive performances brought by various methods based on pseudo labeling and consistency regularization. However, we argue that existing methods might fail to utilize the unlabeled data more effectively since they either use a pre-defined / fixed threshold or an ad-hoc threshold adjus

Adnan A. E. Hajomer, Nitin Jain, Hossein Mani, Hou-Man Chin

Distributing cryptographic keys over public channels in a way that can provide information-theoretic security is the holy grail for secure communication. This can be achieved by exploiting quantum mechanical principles in so-called quantum key distribution (QKD). Continuous-variable (CV) QKD based on coherent states, in particular, is an attractive scheme fo

Lilia Mehidi, Abdelghani Zeghib

Brinkmann Lorentz manifolds are those admitting an isotropic parallel vector field. We prove geodesic completeness of the compact and also compactly homogeneous Brinkmann spaces. We also prove, partially, that their parallel vector field generates an equicontinuous flow.

Sen Guo, Ke-Jian He, Guan-Ru Li, Guo-Ping Li

Considering a charged black hole (BH) surrounded by a perfect fluid radiation field (PFRF) in Rastall gravity, we investigate this BH shadow and photon sphere on different spherical accretions backgrounds. The effect of the PFRF parameter/BH charge on the critical impact parameter is studied by investigating the light deflection near this BH. The luminosity

Andreas Ekstedt, Oliver Gould, Johan Löfgren

We develop new perturbative tools to accurately study radiatively-induced first-order phase transitions. Previous perturbative methods have suffered internal inconsistencies and been unsuccessful in reproducing lattice data, which is often attributed to infrared divergences of massless modes (the Linde problem). We employ a consistent power counting scheme t

Jingke Zhang, Jianwen Luo

Synthetic transmit aperture (STA) imaging can achieve optimal lateral resolution in the full field of view, at the cost of low frame rate (FR) and low signal-to-noise ratio (SNR). In our previous studies, compressed sensing based synthetic transmit aperture (CS-STA) and minimal l2-norm least squares (LS-STA) methods were proposed to recover the complete STA

E. Klempt, A. V. Sarantsev, I. Denisenko, K. V. Nikonov

The tensor glueball is searched for in BESIII data on radiative $J/\psi$ decays into $\pi^0\pi^0$ and $K_sK_s$. The $\pi\pi$ invariant mass distribution exhibits an enhancement that can be described by a pole at $(2210\pm 60) -i(180\pm 60)$\,MeV. We speculate if the tensor glueball could be distributed among high-mass tensor mesons.

Oliver Gould, Sinan Güyer, Kari Rummukainen

We study first-order electroweak phase transitions nonperturbatively, assuming any particles beyond the Standard Model are sufficiently heavy to be integrated out at the phase transition. Utilising high temperature dimensional reduction, we perform lattice Monte-Carlo simulations to calculate the main quantities characterising the transition: the critical te

Fahim Dalvi, Abdul Rafae Khan, Firoj Alam, Nadir Durrani

A large number of studies that analyze deep neural network models and their ability to encode various linguistic and non-linguistic concepts provide an interpretation of the inner mechanics of these models. The scope of the analyses is limited to pre-defined concepts that reinforce the traditional linguistic knowledge and do not reflect on how novel concepts

Hazrat Ali, Zubair Shah

This review presents a comprehensive study on the role of GANs in addressing the challenges related to COVID-19 data scarcity and diagnosis. It is the first review that summarizes the different GANs methods and the lungs images datasets for COVID-19. It attempts to answer the questions related to applications of GANs, popular GAN architectures, frequently us

Masaya Nakagawa, Hosho Katsura, Masahito Ueda

We construct exact eigenstates of multicomponent Hubbard models in arbitrary dimensions by generalizing the $\eta$-pairing mechanism. Our models include the SU($N$) Hubbard model as a special case. Unlike the conventional two-component case, the generalized $\eta$-pairing mechanism permits the construction of eigenstates that feature off-diagonal long-range

Yikuan Li, Mohammad Mamouei, Shishir Rao, Abdelaali Hassaine

Most machine learning (ML) models are developed for prediction only; offering no option for causal interpretation of their predictions or parameters/properties. This can hamper the health systems' ability to employ ML models in clinical decision-making processes, where the need and desire for predicting outcomes under hypothetical investigations (i.e., count

Allison Lahnala, Charles Welch, Béla Neuendorf, Lucie Flek

Large pre-trained neural language models have supported the effectiveness of many NLP tasks, yet are still prone to generating toxic language hindering the safety of their use. Using empathetic data, we improve over recent work on controllable text generation that aims to reduce the toxicity of generated text. We find we are able to dramatically reduce the s

Natalia Gorobey, Alexander Lukyanenko, A. V. Goltsev

The statistical distribution for the case of an adiabatically isolated body was obtained in the framework of covariant quantum theory and Wick's rotation in the complex time plane. The covariant formulation of the mechanics of an isolated system lies in the rejection of absolute time and the introduction of proper time as an independent dynamic variable. The

Elmehdi Illi, Marwa K. Qaraqe, F. El Bouanani, Saif M. Al-Kuwari

In this paper, the physical layer security of a dual-hop unmanned aerial vehicle-based wireless network, subject to imperfect channel state information (CSI) and mobility effects, is analyzed. Specifically, a source node $(S)$ communicates with a destination node $(D)$ through a decode-and-forward relay $(R)$, in the presence of two wiretappers $\left(E_{1},

Liying Lu, Ruizheng Wu, Huaijia Lin, Jiangbo Lu

Video frame interpolation (VFI), which aims to synthesize intermediate frames of a video, has made remarkable progress with development of deep convolutional networks over past years. Existing methods built upon convolutional networks generally face challenges of handling large motion due to the locality of convolution operations. To overcome this limitation

Ziyuan Zhou, Guanjun Liu

Multi-agent deep reinforcement learning makes optimal decisions dependent on system states observed by agents, but any uncertainty on the observations may mislead agents to take wrong actions. The Mean-Field Actor-Critic reinforcement learning (MFAC) is well-known in the multi-agent field since it can effectively handle a scalability problem. However, it is

Hao Wu, Yuhang Gong, Xiaopeng Ke, Hanzhong Liang

Intelligent Apps (iApps), equipped with in-App deep learning (DL) models, are emerging to offer stable DL inference services. However, App marketplaces have trouble auto testing iApps because the in-App model is black-box and couples with ordinary codes. In this work, we propose an automated tool, ASTM, which can enable large-scale testing of in-App models.

Yining Chen

In this article we make the concept of a continuous family of triangles precise and prove the moduli functor classifying oriented triangles admits a fine moduli space but the functor classifying non-oriented triangles only admits a coarse moduli space. We hope moduli spaces of triangles can help understand stacks.

Lexing Ying

This note introduces the double flip move for accelerating the Swendsen-Wang algorithm for Ising models with mixed boundary conditions below the critical temperature. The double flip move consists of a geometric flip of the spin lattice followed by a spin value flip. Both the symmetric and approximately symmetric models are considered. We prove the detailed

Yihan Wang

We consider $k$ intervals on the real line whose images under a continuous map $f$ contain themselves. It's conjectured that there exists a periodic point of period not bigger than $k$ in these intervals. We prove the conjecture for $k=5$ in this paper. We also propose a discretization method in attempt to solve the problem.

Hui-Min Yang, Hua-Xing Chen, Er-Liang Cui, Qiang Mao

We study the $\Xi_b(6100)$ using the methods of QCD sum rules and light-cone sum rules within the framework of heavy quark effective theory. Our results suggest that the $\Xi_b(6100)$ can be well interpreted as the $P$-wave bottom baryon of $J^P=3/2^-$, belonging to the $SU(3)$ flavor $\mathbf{\bar 3}_F$ representation. It has a partner state of $J^P=1/2^-$,

Ziang Song, Song Mei, Yu Bai

Imperfect-Information Extensive-Form Games (IIEFGs) is a prevalent model for real-world games involving imperfect information and sequential plays. The Extensive-Form Correlated Equilibrium (EFCE) has been proposed as a natural solution concept for multi-player general-sum IIEFGs. However, existing algorithms for finding an EFCE require full feedback from th

Wenhai Gao, Kai Zheng, Yang Liao, Henglei Du

Femtosecond laser ablation has been demonstrated to be a versatile tool to produce micro/nanoscale features with high precision and accuracy. However, the use of high laser fluence to increase the ablation efficiency usually results in unwanted effects, such as redeposition of debris, formation of recast layer and heat-affected zone in or around the ablation

Yuanhong Wang, Ying Huang, Chang Guo, Min Jiang

Quantum sensing provides sensitive tabletop tools to search for exotic spin-dependent interactions beyond the Standard Model, which has attracted great attention in theories and experiments. Here we develop a technique based on quantum Spin Amplifier for Particle PHysIcs REsearch (SAPPHIRE) to resonantly search for exotic interactions, specifically parity-od

Michael Krivelevich

We present a short and self-contained proof of the choosability version of Brooks' theorem.

Shubham Gupta

In this paper, we study the asymptotic behaviour of the sharp constant in discrete Hardy and Rellich inequality on the lattice $\mathbb{Z}^d$ as $d \rightarrow \infty$. In the process, we proved some Hardy-type inequalities for the operators $\Delta^m$ and $\nabla(\Delta^m)$ for non-negative integers $m$ on a $d$ dimensional torus. It turns out that the shar

Pengfei Zhang, Tingting Chai, Yongdong Xu

In the field of natural language processing, sentiment analysis via deep learning has a excellent performance by using large labeled datasets. Meanwhile, labeled data are insufficient in many sentiment analysis, and obtaining these data is time-consuming and laborious. Prompt learning devotes to resolving the data deficiency by reformulating downstream tasks

Jianfeng Lin, Ruikang Xiao, Zhao Guo

Modulating the stiffness of soft actuators is crucial for improving the efficiency of interaction with the environment. However, current stiffness modulation mechanisms are hard to achieve high lateral stiffness and a wide range of bending stiffness simultaneously. Here, we draw inspiration from the anatomical structure of the finger and propose a bi-directi

Abhishek Raghav, Kenta Hongo, Ryo Maezono, Emila Panda

In this work, electronic structure of several doped TiO$_2$ anatase systems is computed using DFT+$U$. Effective masses of charge carriers are also computed to quantify how the dopant atoms perturb the bands of the host anatase material. $U$ is computed systematically for all the dopants using the linear response method rather than using fitting procedures t

Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael I. Jordan

Motivated by applications to online learning in sparse estimation and Bayesian optimization, we consider the problem of online unconstrained nonsubmodular minimization with delayed costs in both full information and bandit feedback settings. In contrast to previous works on online unconstrained submodular minimization, we focus on a class of nonsubmodular fu

Mohamed Elmahallawy, Tie Luo

Low Earth Orbit (LEO) satellite constellations have seen a surge in deployment over the past few years by virtue of their ability to provide broadband Internet access as well as to collect vast amounts of Earth observational data that can be utilized to develop AI on a global scale. As traditional machine learning (ML) approaches that train a model by downlo

Zhihao Ge, Hairun Li, Tingting Li

In this paper, we study the numerical algorithm for a nonlinear poroelasticity model with nonlinear stress-strain relations. By using variable substitution, the original problem can be reformulated to a new coupled fluid-fluid system, that is, a generalized nonlinear Stokes problem of displacement vector field related to pseudo pressure and a diffusion probl

Masanao Igarashi

We study the multiple definitions of the entropy production for discrete-time Markov processes in single systems and composite systems. These definitions have been studied in single systems, but less so in composite systems. With a clear distinction, we review the equivalence condition and the meaning of the multiple definitions and show that all definitions

Hai Yang, Yibin Liu, Junxiao Wang, Jun Yang

In this paper, an improved multi-step finite control set model predictive current control (FCS-MPCC) strategy with speed loop disturbance compensation is proposed for permanent magnet synchronous machine (PMSM) drives system. A multi-step prediction mechanism is beneficial to significantly improve the steady-state performance of the motor system. While the c

Drew Heard

We study the Picard group of Franke's category of quasi-periodic $E_0E$-comodules for $E$ a 2-periodic Landweber exact cohomology theory of height $n$ such as Morava $E$-theory, showing that for $2p-2 > n^2+n$, this group is infinite cyclic, generated by the suspension of the unit. This is analogous to, but independent of, the corresponding calculations by H

Rongjie Huang, Yi Ren, Jinglin Liu, Chenye Cui

Style transfer for out-of-domain (OOD) speech synthesis aims to generate speech samples with unseen style (e.g., speaker identity, emotion, and prosody) derived from an acoustic reference, while facing the following challenges: 1) The highly dynamic style features in expressive voice are difficult to model and transfer; and 2) the TTS models should be robust

Florian Schweiger, Ofer Zeitouni

We study the distribution of the maximum of a large class of Gaussian fields indexed by a box $V_N\subset Z^d$ and possessing logarithmic correlations up to local defects that are sufficiently rare. Under appropriate assumptions that generalize those in Ding, Roy and Zeitouni (Annals Probab. (45) 2017, 3886-3928), we show that asymptotically, the centered ma

Trung-Hieu Hoang, Mona Zehni, Huaijin Xu, George Heintz

The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as they compensate for a growing shortage of neurologists. Current neurological digital biomarker pipelines, however, are narrowed down to a specific neurological exam component or appli

Haode Zhang, Haowen Liang, Yuwei Zhang, Liming Zhan

It is challenging to train a good intent classifier for a task-oriented dialogue system with only a few annotations. Recent studies have shown that fine-tuning pre-trained language models with a small amount of labeled utterances from public benchmarks in a supervised manner is extremely helpful. However, we find that supervised pre-training yields an anisot

Di Wu

Recently, Vagnozzi and Visinelli's work [Phys. Rev. D 100, 024020 (2020)] reveals that M87*'s shadow establishes an upper limit of $l \lesssim 170$ AU, where $l$ is the AdS$_5$ curvature radius and 1 AU is one astronomical unit. The Event Horizon Telescope, on the other hand, just captured the first image of the shadow of Sagittarius A* (SgrA*), the Galactic

Yuri I. Yermolaev, Irina G. Lodkina, Aleksander A. Khokhlachev, Mikhail Yu. Yermolaev

Based on the data of the solar wind (SW) measurements of the OMNI base for the period 1976-2019, the behavior of SW types as well as plasma and interplanetary magnetic field (IMF) parameters for 21-24 solar cycles (SCs) is studied. It is shown that with the beginning of the Era of Solar Grand Minimum (SC 23), the proportion of magnetic storms initiated by CI

D. -S. Wang

Capacities of quantum channels are fundamental quantities in the theory of quantum information. A desirable property is the additivity for a capacity. However, this cannot be achieved for a few quantities that have been established as capacity measures. Asymptotic regularization is generically necessary making the study of capacities notoriously hard. In thi

Liuyue Jiang, Nguyen Khoi Tran, M. Ali Babar

The construction of an interactive dashboard involves deciding on what information to present and how to display it and implementing those design decisions to create an operational dashboard. Traditionally, a dashboard's design is implied in the deployed dashboard rather than captured explicitly as a digital artifact, preventing it from being backed up, vers

Mohamed Mohana, Prasanalakshmi B, Salem Alelyani, Mohammed Saleh Alsaqer

Recent period of pandemic has brought person identification even with occluded face image a great importance with increased number of mask usage. This paper aims to recognize the occlusion of one of four types in face images. Various transfer learning methods were tested, and the results show that MobileNet V2 with Gated Recurrent Unit(GRU) performs better t

Shoya Matsumori, Kohei Okuoka, Ryoichi Shibata, Minami Inoue

Open cloze questions have been attracting attention for both measuring the ability and facilitating the learning of L2 English learners. In spite of its benefits, the open cloze test has been introduced only sporadically on the educational front, largely because it is burdensome for teachers to manually create the questions. Unlike the more commonly used mul

Ruiqi Zha, Zhichao Lian, Qianmu Li, Siqi Gu

Most of previous deepfake detection researches bent their efforts to describe and discriminate artifacts in human perceptible ways, which leave a bias in the learned networks of ignoring some critical invariance features intra-class and underperforming the robustness of internet interference. Essentially, the target of deepfake detection problem is to repres

Tangyu Jiang, Haigang Li, Xiaoliang Li

In this paper, we consider the exterior Dirichlet problem for Hessian quotient equations with the right hand side $g$, where $g$ is a positive function and $g=1+O(|x|^{-\beta})$ near infinity, for some $\beta>2$. Under a prescribed generalized symmetric asymptotic behavior at infinity, we establish an existence and uniqueness theorem for viscosity solutions,

A. O. Sorokin

Using Monte Carlo simulations, we consider the lattice version of the $O(N)\otimes O(M)$ sigma model for $2\leq M\leq4$ and $M\leq N \leq8$. We find a continuous transition for $N\geq M+4$. Estimates of the critical exponents for cases of second-order and weak first-order transitions are found. For $M=2$ our estimates of the exponents and marginal dimensiona

Katsuaki Morisawa, Takiko Sasaki, Hiroyuki Takamura

In this paper, we show the so-called "combined effect" of two different kinds of nonlinear terms for semilinear wave equations in one space dimension. Such a special phenomenon appears only in the case that the total integral of the initial speed is zero. It is remarkable that, including the combined effect case, our results on the lifespan estimates are par

Grigory Solomadin

In this paper an example of a $k$-independent $(n,k)$-type GKM-graph without nontrivial extensions is constructed for any $n\geq k\geq 3$. It is shown that this example cannot be realized by a GKM-manifold for any $n=k=3$ or $n\geq k\geq 4$.

Jeremy Wilkinson

In this contribution, the latest results for measurements of charm baryons in proton--proton collisions at $\sqrt{s}=5.02$ and $13\,\mathrm{TeV}$ are presented. The production yields of $\Lambda_\mathrm{c}^{+}$, $\Xi_\mathrm{c}^{0,+}$, $\Omega_\mathrm{c}^{0}$, and $\Sigma_\mathrm{c}^{0,++}$ are shown along with their yield ratios to $\mathrm{D}^{0}$ mesons,

Jan Blechschmidt, Jan-Frederik Pietschman, Tom-Christian Riemer, Martin Stoll

In this paper we focus on comparing machine learning approaches for quantum graphs, which are metric graphs, i.e., graphs with dedicated edge lengths, and an associated differential operator. In our case the differential equation is a drift-diffusion model. Computational methods for quantum graphs require a careful discretization of the differential operator

Zu-Cheng Chen, Yu-Mei Wu, Qing-Guo Huang

We perform a direct search for an isotropic stochastic gravitational-wave background (SGWB) produced by cosmic strings in the Parkes Pulsar Timing Array second data release. We find no evidence for such an SGWB, and therefore place $95\%$ confidence level upper limits on the cosmic string tension, $G\mu$, as a function of the reconnection probability, $p$, w

Chen Wang, Katherine Price, Hengrui Cai, Weining Shen

In many sports, it is commonly believed that the home team has an advantage over the visiting team, known as the home field advantage. Yet its causal effect on team performance is largely unknown. In this paper, we propose a novel causal inference approach to study the causal effect of home field advantage in English Premier League. We develop a hierarchical

Sudip Pal, Kranti Kumar, A. Banerjee

A quantitative estimation of the effect of simultaneously applied external pressure (P) and magnetic field (H) on the phase coexistence has been presented for Pr0.5Ca0.5Mn0.975Al0.025O3 and La0.5Ca0.5MnO3, where the ferromagnetic (FM)-metal and antiferromagnetic (AFM)-insulator phases compete in real space. We found that the nonequilibrium dynamics across th

Rostam Mohamadian

A topological space $X$ is called submaximal if every dense subset of $X$ is open. In this paper, we show that if $\beta X$, the Stone-\v{C}ech compactification of $X$, is a submaximal space, then $X$ is a compact space and hence $\beta X=X$. We also prove that if $\upsilon X$, the Hewitt realcompactification of $X$, is submaximal and first countable and $X$

Lingyue Shen, Ping Lin, Zhiliang Xu, Shixin Xu

A thermodynamically consistent phase-field model is introduced for simulating multicellular deformation, and aggregation under flow conditions. In particular, a Lennard-Jones type potential is proposed under the phase-field framework for cell-cell, cell-wall interactions. A second-order accurate in both space and time $C^0$ finite element method is proposed

Mahsa Mozafari-Nia, Moharram N. Iradmusa

An $n$-subdivision of a graph $G$ is a graph constructed by replacing a path of length $n$ instead of each edge of $G$ and an $m$-power of $G$ is a graph with the same vertices as $G$ and any two vertices of $G$ at distance at most $m$ are adjacent. The graph $G^{\frac{m}{n}}$ is the $m$-power of the $n$-subdivision of $G$. In [M. N. Iradmusa, M. Mozafari-Ni

Nan Li, Lianzhong Yang

Given an entire function $f$ of finite order $\rho$, let $L(z,f)=\sum_{j=0}^{m}b_{j}(z)f^{(k_{j})}(z+c_{j})$ be a linear delay-differential polynomial of $f$ with small coefficients in the sense of $O(r^{\lambda+\varepsilon})+S(r,f)$, $\lambda<\rho$. Provided $\alpha$, $\beta$ be similar small functions, we consider the zero distribution of $L(z,f)-\alpha f^

Indrajit Tah, Sean A. Ridout, Andrea J. Liu

The rapid rise of viscosity or relaxation time upon supercooling is universal hallmark of glassy liquids. The temperature dependence of the viscosity, however, is quite non universal for glassy liquids and is characterized by the system's "fragility," with liquids with nearly Arrhenius temperature-dependent relaxation times referred to as strong liquids and

Yahong Yang, Luchan Zhang, Yang Xiang

High entropy alloys (HEAs) are a class of novel materials that exhibit superb engineering properties. It has been demonstrated by extensive experiments and first principles/atomistic simulations that short-range order in the atomic level randomness strongly influences the properties of HEAs. In this paper, we derive stochastic continuum models for HEAs with

Yunyi Li, Yiqiu Jiang, Hengmin Zhang, Jianxun Liu

Compressive sensing (CS) based computed tomography (CT) image reconstruction aims at reducing the radiation risk through sparse-view projection data. It is usually challenging to achieve satisfying image quality from incomplete projections. Recently, the nonconvex ${{L_ {{1/2}}}} $-norm has achieved promising performance in sparse recovery, while the applica

Wei Xiong, Zhuanxia Li, Guo-Qiang Zhang, Mingfeng Wang

Higher-order exceptional points (EPs) in non-Hermitian systems have attracted great interest due to their advantages in sensitive enhancement and distinct topological features. However, realization of such EPs is still challenged because more fine-tuning parameters is generically required in quantum systems, compared to the second-order EP (EP2). Here, we pr

Theodore Weisman

We define a new family of discrete representations of relatively hyperbolic groups which unifies many existing definitions and examples of geometrically finite behavior in higher rank. The definition includes the relative Anosov representations defined by Kapovich-Leeb and Zhu, and Zhu-Zimmer, as well as holonomy representations of various different types of

Xianli Zeng, Edgar Dobriban, Guang Cheng

Increasing concerns about disparate effects of AI have motivated a great deal of work on fair machine learning. Existing works mainly focus on independence- and separation-based measures (e.g., demographic parity, equality of opportunity, equalized odds), while sufficiency-based measures such as predictive parity are much less studied. This paper considers p

Yu-Hung Lai, Zhiquan Yuan, Myoung-Gyun Suh, Yu-Kun Lu

Stimulated Brillouin scattering provides optical gain for efficient and narrow-linewidth lasers in high-Q microresonator systems. However, the thermal dependence of the Brillouin process, as well as the microresonator, impose strict temperature control requirements for long-term frequency-stable operation. Here, we study Brillouin back action and use it to b

Bowen Shi, Abdelrahman Mohamed, Wei-Ning Hsu

This paper investigates self-supervised pre-training for audio-visual speaker representation learning where a visual stream showing the speaker's mouth area is used alongside speech as inputs. Our study focuses on the Audio-Visual Hidden Unit BERT (AV-HuBERT) approach, a recently developed general-purpose audio-visual speech pre-training framework. We conduc

Wei Ji, Jingjing Li, Qi Bi, Chuan Guo

Growing interests in RGB-D salient object detection (RGB-D SOD) have been witnessed in recent years, owing partly to the popularity of depth sensors and the rapid progress of deep learning techniques. Unfortunately, existing RGB-D SOD methods typically demand large quantity of training images being thoroughly annotated at pixel-level. The laborious and time-

Jinkun Zhang, Yuezhou Liu, Edmund Yeh

Collaborative edge computing (CEC) is an emerging paradigm where heterogeneous edge devices collaborate to fulfill computation tasks, such as model training or video processing, by sharing communication and computation resources. Nevertheless, the optimal data/result routing and computation offloading strategy in CEC with arbitrary topology still remains an

Jinpeng Hu, Yaling Shen, Yang Liu, Xiang Wan

Named entity recognition (NER) is a fundamental and important task in NLP, aiming at identifying named entities (NEs) from free text. Recently, since the multi-head attention mechanism applied in the Transformer model can effectively capture longer contextual information, Transformer-based models have become the mainstream methods and have achieved significa

Z. Ovadyahu

A consequence of the disorder and Coulomb interaction competition is the electron-glass phase observed in several Anderson-insulators. The disorder in these systems, typically degenerate semiconductors, is stronger than the interaction, more so the higher is the carrier-concentration N of the system. Here we report on a new feature observed in the electron-g

Nashlen Govindasamy, Tuomas Hakoniemi, Iddo Tzameret

We prove super-polynomial lower bounds on the size of propositional proof systems operating with constant-depth algebraic circuits over fields of zero characteristic. Specifically, we show that the subset-sum variant $\sum_{i,j,k,\ell\in[n]} z_{ijk\ell}x_ix_j x_k x_\ell - \beta=0$, for Boolean variables, does not have polynomial-size IPS refutations where th

Xinyan Fan, Wei Lan, Tao Zou, Chih-Ling Tsai

For estimating the large covariance matrix with a limited sample size, we propose the covariance model with general linear structure (CMGL) by employing the general link function to connect the covariance of the continuous response vector to a linear combination of weight matrices. Without assuming the distribution of responses, and allowing the number of pa

Yuan Da Liao, Xiao Yan Xu, Zi Yang Meng, Yang Qi

At sufficiently low temperatures, interacting electron systems tend to develop orders. Exceptions are quantum critical point (QCP) and quantum spin liquid (QSL), where fluctuations prevent the highly entangled quantum matter to an ordered state down to the lowest temperature. While the ramification of these states may have appeared in high-temperature superc

Yi Yu, Zongxin Huang, Hongsen He, Yuriy Zakharov

This paper proposes a unified sparsity-aware robust normalized subband adaptive filtering (SA-RNSAF) algorithm for identification of sparse systems under impulsive noise. The proposed SA-RNSAF algorithm generalizes different algorithms by defining the robust criterion and sparsity-aware penalty. Furthermore, by alternating optimization of the parameters (AOP

Wen Liu, Han-Wen Yin, Zhi-Rao Wang, Wen-Qin Fan

Estimating the overlap between two states is an important task with several applications in quantum information. However, the typical swap test circuit can only measure a sole pair of quantum states at a time. In this study we designed a recursive quantum circuit to measure overlaps of multiple quantum states $|\phi_1...\phi_n\rangle$ concurrently with $O(n\

Qianru Liu, Rui Wang, Yuesheng Xu, Mingsong Yan

We consider a regularization problem whose objective function consists of a convex fidelity term and a regularization term determined by the $\ell_1$ norm composed with a linear transform. Empirical results show that the regularization with the $\ell_1$ norm can promote sparsity of a regularized solution. It is the goal of this paper to understand theoretica

Xue-Chao Feng, Wei-Hao, li-Juan Liu

In this work, we calculate the mass spectrum of the bottom mesons with a modified nonrelativistic quark model by involving the screening effect, and explore their strong decay properties within the $^3P_0$ model. Our results suggest that the $B_1(5721)$, $B^*_2(5747)$, $B_J(5840)$, and $B_J(5970)$ could be reasonably assigned as the $B_1^\prime(1P)$, $B(1^3P

Do-Guk Kim, Heung-Chang Lee

Recently, Neural Architecture Search (NAS) methods have been introduced and show impressive performance on many benchmarks. Among those NAS studies, Neural Architecture Transformer (NAT) aims to adapt the given neural architecture to improve performance while maintaining computational costs. However, NAT lacks reproducibility and it requires an additional ar

Ruriko Yoshida, David Barnhill

It is well-known that computing a Markov basis for a discrete loglinear model is very hard in general. Thus, we focus on connecting tables in a fiber via a subset of a Markov basis and in this paper, we consider connecting tables if we allow cell counts in each tale to be $-1$. In this paper we show that if a subset of a Markov basis connects all tables in t

Nicholas Werby, Andrew S. Maxwell, Ruaridh Forbes, Carla Figueira de Morisson Faria

Attosecond dynamics in strong-field tunnel ionization are encoded in intricate holographic patterns in the photoelectron momentum distributions (PMDs). These patterns show the interference between two or more superposed quantum electron trajectories, which are defined by their ionization times and subsequent evolution in the laser field. We determine the ion

Bo-Hae Im, Hojin Kim, Khac Nhuan Le, Tuan Ngo Dac

Multiples zeta values and alternating multiple zeta values in positive characteristic were introduced by Thakur and Harada as analogues of classical multiple zeta values of Euler and Euler sums. In this paper we determine all linear relations among alternating multiple zeta values and settle the main goals of these theories. As a consequence we completely es

Jaron Mar, Jiamou Liu

Understanding, modelling and predicting human risky decision-making is challenging due to intrinsic individual differences and irrationality. Fuzzy trace theory (FTT) is a powerful paradigm that explains human decision-making by incorporating gists, i.e., fuzzy representations of information which capture only its quintessential meaning. Inspired by Broniato

Gergő Nemes

The Stokes phenomenon is the apparent discontinuous change in the form of the asymptotic expansion of a function across certain rays in the complex plane, known as Stokes lines, as additional expansions, pre-factored by exponentially small terms, appear in its representation. It was first observed by G. G. Stokes while studying the asymptotic behaviour of th

Zeyu Lu, Junjun Jiang, Junqin Huang, Gang Wu

The purpose of image inpainting is to recover scratches and damaged areas using context information from remaining parts. In recent years, thanks to the resurgence of convolutional neural networks (CNNs), image inpainting task has made great breakthroughs. However, most of the work consider insufficient types of mask, and their performance will drop dramatic

Nelson D. Rufus, Vikram Gavini

The enriched finite element basis -- wherein the finite element basis is enriched with atom-centered numerical functions -- has recently been shown to be a computationally efficient basis for systematically convergent all-electron DFT ground-state calculations. In this work, we present the expressions to compute variationally consistent ionic forces and stre