January 2022 arXiv papers — page 29

Taouba Jouini

An islanded inverter-based microgrid is a collection of heterogeneous DC energy resources, e.g., photovoltaic arrays, fuel cells, and energy-storage devices, interfaced to an AC distribution network and operated independently from the bulk power system. Energy conversion is typically managed by power electronics in voltage source inverters. Drawing from the

Guy Andre Boy

This position paper introduces and coins the term socioergonomics, considered as a sociological, ontological, and methodological support to human systems integration (HSI). It describes the evolution of ergonomics from early physiological to psychological to contemporary social sciences approaches supporting Industry 4.0 sociotechnical systems engineering. I

Siyao Liu, Tong Wu, Yong Wang

In this paper, we give Lichnerowicz type formulas for the perturbation of the de Rham Hodge operator. We prove the Kastler-Kalau-Walze type theorems for the perturbation of the de Rham Hodge operator on 4-dimensional and 6-dimensional compact manifolds with (resp.without) boundary. Some concrete examples of the perturbation of the de Rham Hodge operator are

Zhao Yang, Dianwen Ng, Xiao Fu, Liping Han

End-to-end automatic speech recognition (ASR) has achieved promising results. However, most existing end-to-end ASR methods neglect the use of specific language characteristics. For Mandarin Chinese ASR tasks, there exist mutual promotion relationship between Pinyin and Character where Chinese characters can be romanized by Pinyin. Based on the above intuiti

Hui Gao, Daqing Yang

The fractional arboricity of a digraph $D$, denoted by $\gamma(D)$, is defined as $\gamma(D)= \max_{H \subseteq D, |V(H)| >1} \frac {|A(H)|} {|V(H)|-1}$. Frank in [Covering branching, Acta Scientiarum Mathematicarum (Szeged) 41 (1979), 77-81] proved that a digraph $D$ decomposes into $k$ branchings, if and only if $\Delta^{-}(D) \leq k$ and $\gamma(D) \leq k

Rongbo Wu, Lang Gao, Youting Liang, Yong Zheng

Integrated thin-film lithium niobate (LN) electro-optic (EO) modulators of broad bandwidth, low insertion loss, low cost and high production rate are essential elements in contemporary inter-connection industries and disruptive applications. Here, we demonstrated the design and fabri-cation of a high performance thin-film LN EO modulator using photolithograp

Yufei Liu, Rao Ma, Haihua Xu, Yi He

An end-to-end (E2E) ASR model implicitly learns a prior Internal Language Model (ILM) from the training transcripts. To fuse an external LM using Bayes posterior theory, the log likelihood produced by the ILM has to be accurately estimated and subtracted. In this paper we propose two novel approaches to estimate the ILM based on Listen-Attend-Spell (LAS) fra

Y. Soeda, K. Asaga, T. Fukui

It is widely known that the twisted bilayer graphene (TBG) shows flat bands at magic angles, which can be well described by the effective continuum model derived by Bistritzer and MacDonald (BM). We propose in this paper a similar twisted bilayer system but defined on the square lattice with $\pi$-flux per plaquette, and study its spectrum using the BM Hamil

Sinan Tan, Mengmeng Ge, Di Guo, Huaping Liu

In the Vision-and-Language Navigation task, the embodied agent follows linguistic instructions and navigates to a specific goal. It is important in many practical scenarios and has attracted extensive attention from both computer vision and robotics communities. However, most existing works only use RGB images but neglect the 3D semantic information of the s

Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti

Given the ubiquity of deep neural networks, it is important that these models do not reveal information about sensitive data that they have been trained on. In model inversion attacks, a malicious user attempts to recover the private dataset used to train a supervised neural network. A successful model inversion attack should generate realistic and diverse s

Taras Banakh, Olena Hryniv

Given two elements $x,y$ of a semigroup $X$ we write $x\lesssim y$ if for every homomorphism $\chi:X\to\{0,1\}$ we have $\chi(x)\le\chi(y)$. The quasiorder $\lesssim$ is called the $binary$ $quasiorder$ on $X$. It induces the equivalence relation $\Updownarrow$ that coincides with the least semilattice congruence on $X$. In the paper we discuss some known an

Qi Zhao, Huanhao Li, Zhipeng Yu, Chi Man Woo

Face recognition has recently become ubiquitous in many scenes for authentication or security purposes. Meanwhile, there are increasing concerns about the privacy of face images, which are sensitive biometric data that should be carefully protected. Software-based cryptosystems are widely adopted nowadays to encrypt face images, but the security level is lim

Mostafa Goodarzi, Qifeng Li

Water and power systems are increasingly interdependent due to the growing number of electricity-driven water facilities. The security of one system can be affected by a contingency in the other system. This paper investigates a security-constrained operation problem of the energy-water nexus (EWN), which is a computationally challenging optimization problem

V. A. Zolotarev

Direct and inverse scattering problem for an operator with non-local potential is solved in the paper. The method is based on the Riemann boundary value problem on a bundle of three straight lines. Description of scattering problem data is given.

Beong-woo Kwak, Youngwook Kim, Yu Jin Kim, Seung-won Hwang

Active learning can be defined as iterations of data labeling, model training, and data acquisition, until sufficient labels are acquired. A traditional view of data acquisition is that, through iterations, knowledge from human labels and models is implicitly distilled to monotonically increase the accuracy and label consistency. Under this assumption, the m

Ning Zhang, Yunlong Xiao, Wenjian Liu

The near-exact iCIPT2 approach for strongly correlated systems of electrons, which stems from the combination of iterative configuration interaction (iCI, an exact solver of full CI) with configuration selection for static correlation and second-order perturbation theory (PT2) for dynamic correlation, is extended to the relativistic domain. In the spirit of

Huizi Wu, Cong Geng, Hui Fang

Session-based recommendation which has been witnessed a booming interest recently, focuses on predicting a user's next interested item(s) based on an anonymous session. Most existing studies adopt complex deep learning techniques (e.g., graph neural networks) for effective session-based recommendation. However, they merely address co-occurrence between items

Jian Li, Bin Zhang, Yabiao Wang, Ying Tai

Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection. However, these hand-crafted FAE modules show inconsistent improvements on face detection, which is mainly due to the significant distribution difference between its training and applying co

Tianyu Wang

We study Hessian estimators for functions defined over an $n$-dimensional complete analytic Riemannian manifold. We introduce new stochastic zeroth-order Hessian estimators using $O (1)$ function evaluations. We show that, for an analytic real-valued function $f$, our estimator achieves a bias bound of order $ O \left( \gamma \delta^2 \right) $, where $ \gam

S. A. De La Motte, S. E. Hollitt, R. Horsley, P. D. Jackson

We present updates from QCDSF/UKQCD/CSSM on the $SU(3)_f$ breaking in $B$ meson decay constants. The $b$-quarks are generated with an anisotropic clover-improved action, and are tuned to match properties of the physical $B$ and $B^*$ mesons. Configurations are generated with $\overline{m}=(1/3)(2m_l+m_s)$ kept constant to control symmetry breaking effects. V

Ai-Chao Wang, Neng-Chang Wei, Fei Huang

In our previous work [Phys. Rev. D $\bf{101}$, 074025 (2020)], the photoproduction $\gamma p \to K^+ \Sigma^0(1385)$ has been investigated within an effective Lagrangian approach. There, the reaction amplitudes were constructed by considering the $t$-channel $K$ and $K^\ast(892)$ exchanges, $s$-channel $N$ contribution, $u$-channel $\Lambda$ exchange, genera

Kenneth Stewart, Emre Neftci

Adaptive "life-long" learning at the edge and during online task performance is an aspirational goal of AI research. Neuromorphic hardware implementing Spiking Neural Networks (SNNs) are particularly attractive in this regard, as their real-time, event-based, local computing paradigm makes them suitable for edge implementations and fast learning. However, th

Bo Zhou, Neel Dey, Jo Schlemper, Seyed Sadegh Mohseni Salehi

Multi-contrast MRI (MC-MRI) captures multiple complementary imaging modalities to aid in radiological decision-making. Given the need for lowering the time cost of multiple acquisitions, current deep accelerated MRI reconstruction networks focus on exploiting the redundancy between multiple contrasts. However, existing works are largely supervised with paire

Gokaran Shukla, Stefano Sanvito, Geunsik Lee

AlN and ZnO, two wide band-gap semiconductors extensively used in the display industry, crystallise in the wurtzite structure, which can favour the formation of epitaxial interfaces to close-packed common ferromagnets. Here we explore these semiconductors as material for insulating barriers in magnetic tunnel junctions. In particular, the {\it ab initio} qua

Yongchan Kwon, Antonio Ginart, James Zou

As machine learning (ML) is deployed by many competing service providers, the underlying ML predictors also compete against each other, and it is increasingly important to understand the impacts and biases from such competition. In this paper, we study what happens when the competing predictors can acquire additional labeled data to improve their prediction

Hanlin Sun, Ivan Kryven, Ginestra Bianconi

During the COVID pandemic, periods of exponential growth of the disease have been mitigated by containment measures that in different occasions have resulted in a power-law growth of the number of cases. The first observation of such behaviour has been obtained from 2020 late spring data coming from China by Ziff and Ziff in Ref. [1]. After this important ob

Shyam Das, Bikram Keshari Parida, Koushik Chakraborty, Saibal Ray

We present a model of compact astrophysical object under General Theory of Relativity using the anisotropic extension of Tolman IV solution. The anisotropy function, derived from the model, remains well behaved throughout the interior of the star. The model satisfies several necessary conditions for a physically realistic compact star. Physical viability of

Aleksander Simonič

Assuming the Generalized Riemann Hypothesis, we provide explicit upper bounds for moduli of $\log{\mathcal{L}(s)}$ and $\mathcal{L}'(s)/\mathcal{L}(s)$ in the neighbourhood of the 1-line when $\mathcal{L}(s)$ are the Riemann, Dirichlet and Dedekind zeta-functions. To do this, we generalize Littlewood's well known conditional result to functions in the Selber

Min Woo Sun, Robert Tibshirani

Cross-validation (CV) is one of the most widely used techniques in statistical learning for estimating the test error of a model, but its behavior is not yet fully understood. It has been shown that standard confidence intervals for test error using estimates from CV may have coverage below nominal levels. This phenomenon occurs because each sample is used i

Viktor Krapivin, Mingqiang Gu, D. Hickox-Young, S. W. Teitelbaum

We use an x-ray free-electron laser to study the ultrafast lattice dynamics following above band-gap photoexcitation of the incipient ferroelectric potassium-tantalate, \kto. % We use ultrafast near-UV (central wavelength 266\,nm and 50 fs pulse duration) laser light to photoexcite charge carriers across the gap and probe the ultrafast lattice dynamics by re

Xuefeng Shen, Khoa Tran, Melvin Leok

A variational integrator of arbitrarily high-order on the special orthogonal group $SO(n)$ is constructed using the polar decomposition and the constrained Galerkin method. It has the advantage of avoiding the second-order derivative of the exponential map that arises in traditional Lie group variational methods. In addition, a reduced Lie--Poisson integrato

Abhik Digar, Rafael Espínola García, G. Sankara Raju Kosuru

The aim of this paper is to address an open problem given in [Kirk, W. A., Shahzad, Naseer, Normal structure and orbital fixed point conditions, J. Math. Anal. Appl. {\bf{vol 463(2)}}, (2018) 461--476]. We give a characterization of weak proximal normal structure using best proximity pair property. We also introduce a notion of pointwise cyclic contraction w

Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi

While datasets with single-label supervision have propelled rapid advances in image classification, additional annotations are necessary in order to quantitatively assess how models make predictions. To this end, for a subset of ImageNet samples, we collect segmentation masks for the entire object and $18$ informative attributes. We call this dataset RIVAL10

Yongle Jiang

Drimbe and Vaes proved an orbit equivalence superrigidity theorem for left-right wreath product actions in the measurable setting. We establish the counterpart result in the topological setting for continuous orbit equivalence. This gives us minimal, topologically free actions that are continuous orbit equivalence superrigid. One main ingredient for the proo

Zahra Ghasemi, Hadi Akbarzadeh Khorshidi, Uwe Aickelin

This study concentrates on clustering problems and aims to find compact clusters that are informative regarding the outcome variable. The main goal is partitioning data points so that observations in each cluster are similar and the outcome variable can be predicated using these clusters simultaneously. We model this semi-supervised clustering problem as a m

Qingnan An, Zhichao Liu

In this paper, we show that for unital, separable $C^*$-algebras of stable rank one and real rank zero, the unitary Cuntz semigroup functor and the functor ${\rm K}_*$ are naturallly equivalent. Then we introduce a refinement of the unitary Cuntz semigroup, say the total Cuntz semigroup, which is a new invariant for separable $C^*$-algebras of stable rank on

Chenchen Mou, Jianfeng Zhang

It is well known that the monotonicity condition, either in Lasry-Lions sense or in displacement sense, is crucial for the global well-posedness of mean field game master equations, as well as for the uniqueness of mean field equilibria and solutions to mean field game systems. In the literature, the monotonicity conditions are always taken in a fixed direct

Houpu Yao, Jiazhou Wang, Peng Dai, Liefeng Bo

As there is a growing interest in utilizing data across multiple resources to build better machine learning models, many vertically federated learning algorithms have been proposed to preserve the data privacy of the participating organizations. However, the efficiency of existing vertically federated learning algorithms remains to be a big problem, especial

Hideto Asashiba, Shengyong Pan

A diagram consisting of differential graded (dg for short) categories and dg functors is formulated in this paper as a colax functor $X$ from a small category $I$ to the 2-category $\mathbf{k}$-dgCat of small dg categories, dg functors and dg natural transformations over a fixed commutative ring $\mathbf{k}$. If $I$ is a group regarded as a category with onl

Chuan-Hung Chen, Cheng-Wei Chiang, Takaaki Nomura, Chun-Wei Su

We construct a scotogenic Majorana neutrino mass model in a gauged $U(1)_X$ extension of the standard model, where the mass of the gauge boson and the unbroken gauge symmetry, which leads to a stable dark matter (DM), can be achieved through the Stueckelberg mechanism. It is found that the simplest version of the extended model consists of the two inert-Higg

Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu

Learning and equilibrium computation in games are fundamental problems across computer science and economics, with applications ranging from politics to machine learning. Much of the work in this area revolves around a simple algorithm termed \emph{randomized weighted majority} (RWM), also known as "Hedge" or "Multiplicative Weights Update," which is well kn

Xufang Wang, Zihuai Lin, Feng Lin, Lajos Hanzo

Terahertz (THz) systems have the benefit of high bandwidth and hence are capable of supporting ultra-high data rates, albeit at the cost of high pathloss. Hence they tend to harness high-gain beamforming. Therefore a novel hybrid 3D beamformer relying on sophisticated sensor-based beam training and channel estimation is proposed for Reconfigurable Intelligen

Jun Muramatsu

This paper investigates the achievability of the interference channel coding. It is clarified that the rate-splitting technique is unnecessary to achieve Han-Kobayashi and Jian-Xin-Garg inner regions. Codes are constructed by using sparse matrices (with logarithmic column degree) and the constrained-random-number generators. By extending the problem, we can

Ryohei Oka, Yuta Nakahara, Toshiyasu Matsushima

This study deals with two-dimensional (2D) signal processing using the wavelet packet transform. When the basis is unknown the candidate of basis increases in exponential order with respect to the signal size. Previous studies do not consider the basis as a random vaiables. Therefore, the cost function needs to be used to select a basis. However, this method

Yinqiao Wang, Jin Shang, Yuliang Jin, Jie Zhang

Two drastically different theories predict the marginal criticality of jamming. The full replica symmetry breaking (fullRSB) theory [1-4] predicts the power-law distributions of weak contact forces and small inter-particle gaps in infinite-dimensional hard-sphere glass, with two nontrivial exponents $\theta_f=0.42311...$ and $\gamma=0.41269...$, respectively

Lili Shen, Hang Yang

We characterize injective objects, injective hulls and essential embeddings in the category of symmetric categories enriched in a small, integral and involutive quantaloid. In particular, injective partial metric spaces are precisely formulated.

Wangbo Yu, Jinhao Du, Ruixin Liu, Yixuan Li

Image inpainting approaches have achieved significant progress with the help of deep neural networks. However, existing approaches mainly focus on leveraging the priori distribution learned by neural networks to produce a single inpainting result or further yielding multiple solutions, where the controllability is not well studied. This paper develops a nove

Fatima Salahdine, Zakaria El Mrabet, Naima Kaabouch

Phishing attacks are one of the most common social engineering attacks targeting users emails to fraudulently steal confidential and sensitive information. They can be used as a part of more massive attacks launched to gain a foothold in corporate or government networks. Over the last decade, a number of anti-phishing techniques have been proposed to detect

Junfa Lin, Siyuan Chen, Jiahai Wang

Recommender systems based on graph neural networks receive increasing research interest due to their excellent ability to learn a variety of side information including social networks. However, previous works usually focus on modeling users, not much attention is paid to items. Moreover, the possible changes in the attraction of items over time, which is lik

Alistair McLeod, Daniel Jacobs, Chayan Chatterjee, Linqing Wen

Deep learning can be used to drastically decrease the processing time of parameter estimation for coalescing binaries of compact objects including black holes and neutron stars detected in gravitational waves (GWs). As a first step, we present two neural network models trained to rapidly estimate the posterior distributions of the chirp mass and mass ratio o

Quanlong Yang, Dongyang Wang, Sergey Kruk, Mingkai Liu

Terahertz waves offer a profound platform for next-generation sensing, imaging, and information communications. However, all conventional terahertz components and systems suffer from a bulky design, sensitivity to imperfections, and transmission losses. Here, we propose and experimentally demonstrate on-chip integration and miniaturization of topological dev

Xiaobin Xiong, Yuxiao Chen, Aaron Ames

We present a stepping stabilization control that addresses external push disturbances on bipedal walking robots. The stepping control is synthesized based on the step-to-step (S2S) dynamics of the robot that is controlled to have an approximately constant center of mass (COM) height. We first learn a linear S2S dynamics with bounded model discrepancy from th

Hong Guo, Yunqi Liu, Chao Zhang, Yungui Gong

We study extreme mass ratio inspirals occurring in modified gravity, for which the system is modeled by a small compact object with scalar charge spiraling into a supermassive Kerr black hole. Besides the tensorial gravitational waves arising from the metric perturbations, radiations are also induced by the scalar field. The relevant metric and scalar pertur

Sangyun Lee, Sewoong Ahn, Kwangjin Yoon

Unsupervised real world super resolution (USR) aims to restore high-resolution (HR) images given low-resolution (LR) inputs, and its difficulty stems from the absence of paired dataset. One of the most common approaches is synthesizing noisy LR images using GANs (i.e., degradation generators) and utilizing a synthetic dataset to train the model in a supervis

Zihao Sheng, Lin Liu, Shibei Xue, Dezong Zhao

Lane change for autonomous vehicles (AVs) is an important but challenging task in complex dynamic traffic environments. Due to difficulties in guarantee safety as well as a high efficiency, AVs are inclined to choose relatively conservative strategies for lane change. To avoid the conservatism, this paper presents a cooperation-aware lane change method utili

Hang Yang, Yuji Fujii, K. W. Wang, Alex A. Gorodetsky

We present a hybrid sampling-surrogate approach for reducing the computational expense of uncertainty quantification in nonlinear dynamical systems. Our motivation is to enable rapid uncertainty quantification in complex mechanical systems such as automotive propulsion systems. Our approach is to build upon ideas from multifidelity uncertainty quantification

Vladislav Dorofeev, Petro Trokhimchuk

The problem of synthesis in computer sciences, including cybernetics, artificial intelligence and system analysis, is analyzed. Main methods of realization this problem are discussed. Ways of search universal method of creation universal synthetic science are represented. As example of such universal method polymetric analysis is given. Perspective of furthe

Abhishek Gupta, Arkady Kurnosov, Tsampikos Kottos, Ramathasan Thevamaran

While boosting signals with amplification mechanisms is a well established approach, attenuation mechanisms are typically considered an anathema because they degrade the efficiency of the structures employed to perform useful operations on these signals. An emerging alternate viewpoint promotes losses as a novel design element by utilizing the notion of exce

AmirEmad Ghassami, Chang Liu, Alan Yang, David Richardson

We study identifying and estimating the causal effect of a treatment variable on a long-term outcome using data from an observational and an experimental domain. The observational data are subject to unobserved confounding. Furthermore, subjects in the experiment are only followed for a short period; thus, long-term effects are unobserved, though short-term

C. K. Safeer, Mohamed-Ali Nsibi, Jayshankar Nath, Mihai Sebastian Gabor

Friction plays an essential role in most physical processes that we experience in our everyday life. Examples range from our ability to walk or swim, to setting boundaries of speed and fuel efficiency of moving vehicles. In magnetic systems, the displacement of chiral domain walls (DW) and skyrmions (SK) by Spin Orbit Torques (SOT), is also prone to friction

Jorge David Castaño-Yepes, D. J. Nader, A. Martín-Ruiz

In this paper we study the effects of a topological Weyl semimetal (WSM) upon the ground state and polarization of an hydrogen-like atom near its surface. The WSM is assumed to be in the equilibrium state and at the neutrality point, such that the interaction between the atomic charges and the material is fully described (in the non retarded regime) by axion

Parand Akbari, Francis Ogoke, Ning-Yu Kao, Kazem Meidani

Characterizing meltpool shape and geometry is essential in metal Additive Manufacturing (MAM) to control the printing process and avoid defects. Predicting meltpool flaws based on process parameters and powder material is difficult due to the complex nature of MAM process. Machine learning (ML) techniques can be useful in connecting process parameters to the

Ajinkya Punjal, Shraddha Choudhary, Maneesha Narayanan, Ruta Kulkarni

We report the Terahertz optical properties of the Vanadium doped [100] \b{eta}-Ga2O3 using Terahertz Time-Domain Spectroscopy (THz-TDS). The V-doped \b{eta}-Ga2O3 crystal shows strong birefringence in the 0.2-2.4 THz range. Further, phase retardation by the V-doped \b{eta}-Ga2O3 has been measured over the whole THz range by Terahertz Time-Domain Polarimetry

Xiaoqing Luo, Yuting Jiang, Anqi Wang, Zhancheng Zhang

The traditional two-state hidden Markov model divides the high frequency coefficients only into two states (large and small states). Such scheme is prone to produce an inaccurate statistical model for the high frequency subband and reduces the quality of fusion result. In this paper, a fine-grained multi-state contextual hidden Markov model (MCHMM) is propos

Debdulal Ghosh, Jayanta Paul, Jitendra Kumar

This article is devoted to the study of existence of a mass conserving global solution for the collision-induced nonlinear fragmentation model which arises in particulate processes, with the singular type of collision kernel. The above mentioned form includes many practical oriented kernels of both singular and non-singular types. The singularity of the unbo

Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong

Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from several disadvantages: (1) existing methods fail to capture the important features of the images due to the naive tokenization scheme; (2) the models suffer from information loss b

Zhancheng Zhang, Yuanhao Gao, Mengyu Xiong, Xiaoqing Luo

Background: Leaning redundant and complementary relationships is a critical step in the human visual system. Inspired by the infrared cognition ability of crotalinae animals, we design a joint convolution auto-encoder (JCAE) network for infrared and visible image fusion. Methods: Our key insight is to feed infrared and visible pair images into the network si

Hamed Hosseiny, Arman Farhang, Behrouz Farhang-Boroujeny

In this paper, a practical precoding method for the downlink of filter bank multicarrier-based (FBMC-based) massive multiple-input multiple-output (MIMO) is developed. The proposed method includes a two-stage precoder consisting of a fractionally spaced prefilter (FSP) per subcarrier for flattening/equalizing the channel across the subcarrier band, followed

Chengcheng Ma, Xingjia Pan, Qixiang Ye, Fan Tang

Semi-supervised object detection has recently achieved substantial progress. As a mainstream solution, the self-labeling-based methods train the detector on both labeled data and unlabeled data with pseudo labels predicted by the detector itself, but their performances are always limited. Through experimental analysis, we reveal the underlying reason is that

S. Posen, M. Checchin, O. S. Melnychuk, T. Ring

In dark matter searches using axion haloscopes, the search sensitivity depends on the quality factors ($Q_0$) of radiofrequency cavities immersed in multi-tesla magnetic fields. Increasing $Q_0$ would increase the scan rate through the parameter space of interest. Researchers developing superconducting radiofrequency cavities for particle accelerators have d

M. J. Luo

It is known that the conformal instability or bottomless problem rises in the path integral method in quantizing the general relativity. Does quantum spacetime itself really suffer from such conformal instability? If so, does the conformal instability cause the collapse of local spacetime region or even collapse the whole spacetime? The problems are studied

Minling Feng, Kunpeng Wu, Shaofeng Lu

In modern rail transportation, energy-efficient train control (EETC) is concerned with the optimal train speed trajectory or control strategies to achieve the minimum energy cost under various operation and traction constraints. This paper proposes an EETC model based on convex optimization so that the model can be rapidly solved by convex optimization algor

Zilong He, Yong Hu, Fei Xu

An integral quadratic lattice is called indefinite $k$-universal if it represents all integral quadratic lattices of rank $k$ for a given positive integer $k$. For $k\geq 3$, we prove that the indefinite $k$-universal property satisfies the local-global principle over number fields. For $k=2$, we show that a number field $F$ admits an integral quadratic latt

Alessandro Palmieri, Hiroyuki Takamura

In the present paper we prove the blow-up in finite time for local solutions of a semilinear Cauchy problem associated with a wave equation in anti-de Sitter spacetime in the critical case. According to this purpose, we combine an ODI result with an iteration argument, by using an explicit integral representation formula for the solution to a linear Cauchy p

Yun-Hao Cao, Hao Yu, Jianxin Wu

Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition. They achieve competitive results with CNNs but the lack of the typical convolutional inductive bias makes them more data-hungry than common CNNs. They are often pretrained on JFT-300M or at least ImageNet and few works study training ViTs

Yong-Gao Chen, Yuchen Ding

Let $\mathcal{P}$ denote the set of all primes. In 1950, P. Erd\H{o}s conjectured that if $c$ is an arbitrarily given constant, $x$ is sufficiently large and $a_1,\dots , a_t$ are positive integers with $a_1<a_2<\cdot\cdot\cdot<a_t\leqslant x$ and $t>\log x$, then there exists an integer $n$ so that the number of solutions of $n=p+a_i$ $(p\in \mathcal{P}, 1\

B. N. Kausik

We argue that the recent growth in income inequality is driven by disparate growth in investment income rather than by disparate growth in wages. Specifically, we present evidence that real wages are flat across a range of professions, doctors, software engineers, auto mechanics and cashiers, while stock ownership favors higher education and income levels. A

Yoon-Jae Yeo, Min-Cheol Sagong, Seung Park, Sung-Jea Ko

Region-adaptive normalization (RAN) methods have been widely used in the generative adversarial network (GAN)-based image-to-image translation technique. However, since these approaches need a mask image to infer the pixel-wise affine transformation parameters, they cannot be applied to the general image generation models having no paired mask images. To res

Jingwei Guo, Xiangrong Zhu

We study the pseudo-differential operator \begin{equation*} T_a f\left(x\right)=\int_{\mathbb{R}^n}e^{ix\cdot\xi}a\left(x,\xi\right)\widehat{f}\left(\xi\right)\,\textrm{d}\xi, \end{equation*} where the symbol $a$ is in the H\"{o}rmander class $S^{m}_{\rho,1}$ or more generally in the rough H\"{o}rmander class $L^{\infty}S^{m}_{\rho}$ with $m\in\mathbb{R}$ an

Russell G. Walker, Wm. Bruce Weaver, W. W. Shane, Arthur Babcock

We present spectroscopic and high-precision photometric observations, spanning the optical UV to the far red, before, during, and after the NASA Deep Impact event of July 4, 2005. The inner 2000 km of the pre and post-impact coma was about 0.3 magnitude redder in B-R than in the outer coma. The pre-impact spectrum was a faint reflected solar spectrum dominat

Jeffrey Rable, Benjamin Piazza, Jyotirmay Dwivedi, Nitin Samarth

Nitrogen-vacancy centers in diamond have recently been established as effective sensors of the magnetization dynamics in vicinal ferromagnetic materials. We demonstrate sub-100 nm placement accuracy of nitrogen-vacancy-containing nanodiamonds and use these as local sensors that probe optically detected ferromagnetic resonance in mesoscopically patterned Perm

Y. Lei, Y. Lu

We optimize the matrix representation of the nucleon-pair approximation (NPA) of the nuclear shell model. The NPA is a widely adopted truncation approach of the nuclear shell model and proves to be effective in describing low-lying states of medium-heavy and heavy nuclei. Due to simplified (yet flexible) commutators and absolute elimination of angular moment

X. Wang, F. Maresca, P. Cao

High-entropy alloys (HEAs) with concentrated solid solutions are conceived to possess a rugged atomic and energy landscape in which dislocation motion necessarily proceeds to accommodate mechanical deformation. Fundamental questions remain as to how rough the energy landscape is and to what extent it can be influenced by the local ordering of their constitue

Xiao Zhang, Yang Chen, Jianxiong Fang, Tishuo Wang

Diffraction beams generated by an acousto-optic modulator (AOM) are widely used in various optical experiments, some of which require high angular stability with the temporal modulation of optical power. Usually, it is difficult to realize both angular stability and high-power modulation in a passive setup without a servo system of radio-frequency compensati

Ying Zhou, Long Chen, Gang Wang, Yuxin Wang

Mn-based superconductor is rare and recently reported in quasi-one-dimensional KMn$_6$Bi$_5$ with [Mn$_6$Bi$_5$]-columns under high pressure. Here we report the synthesis, magnetic properties, electrical resistivity, and specific heat capacity of the newly-discovered quasi-one-dimensional NaMn$_6$Bi$_5$ single crystal. Compared with other AMn$_6$Bi$_5$ (A =

R. Bandyopadhyay, W. H. Matthaeus, D. J. McComas, R. Chhiber

In the lower solar coronal regions where the magnetic field is dominant, the Alfven speed is much higher than the wind speed. In contrast, the near-Earth solar wind is strongly super-Alfvenic, i.e., the wind speed greatly exceeds the Alfven speed. The transition between these regimes is classically described as the "Alfven point" but may in fact occur in a d

Yang Cao

The \S 2 of our work "Sous-groupe de Brauer invariant et obstruction de descente it\'er\'ee" uses a statement about the degree two K\"unneth formula proved by Skorobogatov and Zarhin in their paper "The Brauer group and the Brauer-Manin set of products of varieties". Recently they find that this statement is not correct (see their Corrigendum). We correct \S

Lu Dong, Zhi-Qiang Guo, Chao-Hong Tan, Ya-Jun Hu

Neural network models have achieved state-of-the-art performance on grapheme-to-phoneme (G2P) conversion. However, their performance relies on large-scale pronunciation dictionaries, which may not be available for a lot of languages. Inspired by the success of the pre-trained language model BERT, this paper proposes a pre-trained grapheme model called graphe

Stefan Gille, Ivan Panin

We prove that the hermitian Gersten-Witt complex is exact for Azumaya algebras with involution of the first- or second kind over a regular local ring, which is essentially smooth over a field, or over a discrete valuation ring.

K. Wakamatsu, Y. Suzuki, T. Fujii, K. Miyagawa

Quantum spin liquid is a nontrivial magnetic state of longstanding interest, in which spins are strongly correlated and entangled but do not order1, 2; further intriguing is its doped version, which possibly hosts strange metal and unconventional superconductivity3. Promising and currently the only candidate of the doped spin liquid is a triangular-lattice o

Naoki Masuyama, Narito Amako, Yuna Yamada, Yusuke Nojima

Adaptive Resonance Theory (ART) is considered as an effective approach for realizing continual learning thanks to its ability to handle the plasticity-stability dilemma. In general, however, the clustering performance of ART-based algorithms strongly depends on the specification of a similarity threshold, i.e., a vigilance parameter, which is data-dependent

Shyam Venkatasubramanian, Chayut Wongkamthong, Mohammadreza Soltani, Bosung Kang

Using an amalgamation of techniques from classical radar, computer vision, and deep learning, we characterize our ongoing data-driven approach to space-time adaptive processing (STAP) radar. We generate a rich example dataset of received radar signals by randomly placing targets of variable strengths in a predetermined region using RFView, a site-specific ra

Aksheshkumar Ajaykumar Shah, Hemanth Venkateswara

Recently, Generative Adversarial Networks (GANs) have been applied to the problem of Cold-Start Recommendation, but the training performance of these models is hampered by the extreme sparsity in warm user purchase behavior. In this paper we introduce a novel representation for user-vectors by combining user demographics and user preferences, making the mode

Zhihua Wang, Gongxiang Liu, Libin Li

For a finite-dimensional Hopf algebra $A$ with a nonzero left integral $\Lambda$, we investigate a relationship between $P_n(\Lambda)$ and $P_n^J(\Lambda)$, where $P_n$ and $P_n^J$ are respectively the $n$-th Sweedler power maps of $A$ and the twisted Hopf algebra $A^J$. We use this relation to give several invariants of the representation category Rep$(A)$

Léia Sousa de Sousa, André Costa Drummond

Metropolitan optical networks are undergoing major transformations to continue being able to provide services that meet the requirements of the applications of the future. The arrival of the $5G$ will expand the possibilities for offering IoT applications, autonomous vehicles, and smart cities services while imposing strong pressure on the physical infrastru

Timothée Vaillant, Alexandre C. M. Correia

The motion of a satellite can experience secular resonances between the precession frequencies of its orbit and the mean motion of the host planet around the star. Some of these resonances can significantly modify the eccentricity (evection resonance) and the inclination (eviction resonance) of the satellite. In this paper, we study in detail the secular res

Xin Sun, Tao Ge, Shuming Ma, Jingjing Li

Synthetic data construction of Grammatical Error Correction (GEC) for non-English languages relies heavily on human-designed and language-specific rules, which produce limited error-corrected patterns. In this paper, we propose a generic and language-independent strategy for multilingual GEC, which can train a GEC system effectively for a new non-English lan

David García-Peláez, César Simón López-Monsalvo

In this work, we use the fact that kinematics of light propagation in a non-dispersive medium associated with a bi-metric spacetime is expressed by means of a 1-parameter family of contact transformations. We present a general technique to find such transformations and explore some explicit examples for Minkowski and anti-deSitter spacetimes geometries.

Thomas Y. Chen

Mentorship in the AI community is crucial to maintaining and increasing diversity, especially with respect to fostering the academic growth of underserved students. While the research process itself is important, there is not sufficient emphasis on the submission, presentation, and publication process, which is a cause for concern given the meteoric rise of

Gaobiao Xiao

The magnetic Aharonov-Bohm effect shows that charged particles may be affected by the vector potential in regions without any electric or magnetic fields [1]. The Aharonov-Bohm effect was experimentally confirmed [2-3] and has been found in many situations [4-6]. A common explanation is based on quantum mechanics, which states that the wavefunctions associat