August 2022 arXiv papers — page 66

Jiamo Jiang, Mingfeng Xu, Zhongyuan Zhao, Kaifeng Han

Integrated sensing and communications (ISAC) is an essential technology for the 6G communication system, which enables the conventional wireless communication network capable of sensing targets around. The shared use of pilots is a promising strategy to achieve ISAC. It brings a trade-off between communication and sensing, which is still unclear under the im

Nibedita Ghosh, Hari Shankar Mahato

A system of diffusion-reaction equations coupled with a dissolution-precipitation model is discussed. We start by introducing a microscale model together with its homogenized version. In the present paper, we first derive the corrector result to justify the obtained theoretical results. Furthermore, we perform the numerical computations to compare the outcom

Minsu Ghim, Cheol-Hwan Park

Many physical quantities in solid-state physics are calculated from k-space summation. For spectral functions, the frequency-dependent factor can be decomposed into the energy-conserving delta function part and the nondissipative principal value part. A very useful scheme for this k-space summation is the tetrahedron method. Tetrahedron methods have been wid

Johan Engström, Shu-Yuan Liu, Azadeh Dinparastdjadid, Camelia Simoiu

There is currently no established method for evaluating human response timing across a range of naturalistic traffic conflict types. Traditional notions derived from controlled experiments, such as perception-response time, fail to account for the situation-dependency of human responses and offer no clear way to define the stimulus in many common traffic con

Deepak Vaid, Devadharshini Suresh

Quantum field theory provides us with the means to calculate scattering amplitudes. In recent years a dramatic new development has lead to great simplification of such calculations. This is based on the discovery of the``amplituhedron'' in the context of scattering of massless gauge bosons in Yang-Mills theory. One of the main challenges facing Loop Quantum

Hana Salati, Narinder Singh, Mehrdad Khamooshi, Sara Vahaji

Purpose: Nasal saline irrigation is highly recommended in patients following functional endoscopic sinus surgery (FESS) to aid the postoperative recovery. Post-FESS patients have significantly altered anatomy leading to markedly different flow dynamics from those found in pre-op or non-diseased airways, resulting in unknown flow dynamics. Methods: This work

Kajal Kumari, Mayank Goswami

Different technical and physical factors may affect the image quality reconstructed using a Computed Tomography system. We have developed and designed a 2D Gamma Computed Tomography set up to study the effect of some physical parameters. One must decide the number of detectors and set CT geometry parameters or configuration like the fan-beam angle and number

Yu Liu, Resta A. Susilo, Yongbin Lee, A. M. Milinda Abeykoon

Two-dimensional magnetic materials (2DMM) are significant for studies on the nature of 2D long range magnetic order but also for future spintronic devices. Of particular interest are 2DMM where spins can be manipulated by electrical conduction. Whereas Cr$_2$Si$_2$Te$_6$ exhibits magnetic order in few-layer crystals, its large band gap inhibits electronic co

Yu Liu, Zhixiang Hu, Michael O. Ogunbunmi, Eli Stavitski

We report giant anisotropy in thermoelectric power factor ($S^2\sigma$) of marcasite structure-type PtSb$_{1.4}$Sn$_{0.6}$. PtSb$_{1.4}$Sn$_{0.6}$, synthesized using ambient pressure flux growth method upon mixing Sb and Sn on the same atomic site, is a new phase different from both PtSb$_2$ and PtSn$_2$ that crystallize in the cubic $Pa\bar{3}$ pyrite and $

Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu

Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels. In this AMS Notices article, we focus on the decision-making development for the intervention of COVID-19, aiming to provide mathematical models and efficient machine learning methods, and justifications for related p

Marco Omainska, Junya Yamauchi, Masayuki Fujita

This paper considers a scenario of pursuing a moving target that may switch behaviors due to external factors in a dynamic environment by motion estimation using visual sensors. First, we present an improved Visual Motion Observer with switched Gaussian Process models for an extended class of target motion profiles. We then propose a pursuit control law with

Shuai Sun, Zhen-Wu Nie, Yue-Gang Li, Hui-Zu Lin

Although optical aperture synthesis has been generally regarded as the only access to very large imager for over a century, the problem of phasing all the giant sub-apertures on the scale of wavelength is still prohibitive. Besides, the accompanied adaptive optics combatting the atmospheric turbulence is also bulky and complicated. We here propose a new para

Wenhan Wang, Kechi Zhang, Ge Li, Shangqing Liu

Learning vector representations for programs is a critical step in applying deep learning techniques for program understanding tasks. Various neural network models are proposed to learn from tree-structured program representations, e.g., abstract syntax tree (AST) and concrete syntax tree (CST). However, most neural architectures either fail to capture long-

Puspraj Singh Chauhan, Sandeep Kumar, Imran Shafique Ansari

The present work proposes analytical solutions for the integral of bivariate Fox H-function in combination with algebraic, exponential, and complementary error functions. In addition, the work also presents the derivative identities with respect to function arguments. Further, the suitability of the proposed mathematical solutions is verified with reference

Hanshang Jin, Weizhao Cai, Jared Coles, Jackson R. Badger

We combine structural and magnetic measurements to compare the different magnetic phase diagrams between the pressure and substitution studies in CeTiGe3. We report on the structural, magnetic, and electrical transport properties of single crystals of CeTi1-xVxGe3 (x = 0, 0.1, 0.2, 0.3, 0.4, 0.9, and 1), and of polycrystalline samples (x = 0.5, 0.6, 0.7, 0.8

Yun-Fan Zhou, Chandreyee Sengupta, Yogesh Chandola, O. Ivy Wong

We present results from an HI counterpart search using the HI Parkes All Sky Survey (HIPASS) for a sample of low surface brightness galaxies (LSBGs) and ultradiffuse galaxies (UDGs) identified from the Dark Energy Survey (DES). We aimed to establish the redshifts of the DES LSBGs to determine the UDG fraction and understand their properties. Out of 409 galax

Hong Ren, Zhenkun Zhang, Zhangjie Peng, Li Li

Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) systems offer significant advantages in coverage and deployment flexibility, but suffer from endurance limitations due to the limited onboard energy. This paper proposes to improve the energy efficiency of UAV-enabled WPT systems with multiple ground sensors by utilizing reconfigurable intel

Ayushi Saxena, Vince Lyzinski

Two-sample network hypothesis testing is an important inference task with applications across diverse fields such as medicine, neuroscience, and sociology. Many of these testing methodologies operate under the implicit assumption that the vertex correspondence across networks is a priori known. This assumption is often untrue, and the power of the subsequent

Bhavana Lalchand, Wen-Ping Chen, Beth A. Biller, Loic Albert

We report the discovery of substellar objects in the young star cluster IC 348 and the neighboring Barnard 5 dark cloud, both at the eastern end of the Perseus star-forming complex. The substellar candidates are selected using narrowband imaging, i.e., on and off photometric technique with a filter centered around the water absorption feature at 1.45 microns

Yichen Peng, Chunqi Zhao, Haoran Xie, Tsukasa Fukusato

Animating 3D characters using motion capture data requires basic expertise and manual labor. To support the creativity of animation design and make it easier for common users, we present a sketch-based interface DualMotion, with rough sketches as input for designing daily-life animations of characters, such as walking and jumping.Our approach enables to comb

Yifei Zong, QiZhi He, Alexandre M. Tartakovsky

In this paper, we develop a physics-informed neural network (PINN) model for parabolic problems with a sharply perturbed initial condition. As an example of a parabolic problem, we consider the advection-dispersion equation (ADE) with a point (Gaussian) source initial condition. In the $d$-dimensional ADE, perturbations in the initial condition decay with ti

Qizhi Li, Hsiao-Yu Huang, Tianshuang Ren, Eugen Weschke

The extremely overdoped cuprates are generally considered to be Fermi liquid metals without exotic orders, whereas the underdoped cuprates harbor intertwined states. Contrary to this conventional wisdom, using Cu $L_3$ edge and O $K$ edge resonant x-ray scattering, we reveal a charge order (CO) in overdoped La$_{2-x}$Sr$_x$CuO$_4$ (0.35 $\leq$ x $\leq$ 0.6)

Alan Stoneham

Well-bounded operators are linear operators on a Banach space $X$ that have an $AC[a,b]$ functional calculus for some interval $[a,b]$. A well-bounded operator is of type (B) if it can be written as an integral against a spectral family of projections, and this is always the case when $X$ is reflexive. There are many examples of well-bounded operators on non

Yang-Jun Lee, Cheol-Hwan Park, María A. H. Vozmediano

The collapse of Landau levels under an electric field perpendicular to the magnetic field is one of the distinctive features of Dirac materials. So is the coupling of lattice deformations to the electronic degrees of freedom in the form of gauge fields which allows the formation of pseudo-Landau levels from strain. We analyze the collapse of Landau levels in

Jiwon Kim, Youngjo Min, Daehwan Kim, Gyuseong Lee

We present a novel semi-supervised learning framework that intelligently leverages the consistency regularization between the model's predictions from two strongly-augmented views of an image, weighted by a confidence of pseudo-label, dubbed ConMatch. While the latest semi-supervised learning methods use weakly- and strongly-augmented views of an image to de

Jianming Liang, Guanglu Song, Biao Leng, Yu Liu

We present a conceptually simple, flexible, and universal visual perception head for variant visual tasks, e.g., classification, object detection, instance segmentation and pose estimation, and different frameworks, such as one-stage or two-stage pipelines. Our approach effectively identifies an object in an image while simultaneously generating a high-quali

Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang

Building dialogue generation systems in a zero-shot scenario remains a huge challenge, since the typical zero-shot approaches in dialogue generation rely heavily on large-scale pre-trained language generation models such as GPT-3 and T5. The research on zero-shot dialogue generation without cumbersome language models is limited due to lacking corresponding p

Seth Lazar

Increasingly secret, complex and inscrutable computational systems are being used to intensify existing power relations and to create new ones; in particular, they are being used to govern. To be all-things-considered morally permissible new, or newly intense, power relations must meet standards of procedural legitimacy and proper authority. This is necessar

Changqing Guo, Houbing Huang

Understanding the dynamic behavior of the domain structure is critical to the design and application of super-elastic freestanding ferroelectric thin films. The phase-field simulation is currently a powerful tool for observing, exploring, and revealing domain switching behavior and phase transition in ferroelectric materials at the mesoscopic scale. The pres

Zhikang Dong, Pawel Polak

We investigate the inverse problem for Partial Differential Equations (PDEs) in scenarios where the parameters of the given PDE dynamics may exhibit changepoints at random time. We employ Physics-Informed Neural Networks (PINNs) - universal approximators capable of estimating the solution of any physical law described by a system of PDEs, which serves as a r

Yi-Piao Wu, Ling-Zhi Tang, Guo-Qing Zhang, Dan-Wei Zhang

Thouless pump with quantized transports is topologically robust against small perturbations and disorders, while breaks down under sufficiently strong disorders. Here we propose counter-intuitive topological pumps induced by disorders in noninteracting and interacting systems. We first show an extrinsic topological pump driven by the on-site quasiperiodic po

Yuanpeng Tu

Recently unsupervised person re-identification (re-ID) has drawn much attention due to its open-world scenario settings where limited annotated data is available. Existing supervised methods often fail to generalize well on unseen domains, while the unsupervised methods, mostly lack multi-granularity information and are prone to suffer from confirmation bias

Dominykas Šeputis, Jevgenij Gamper, Remigijus Paulavičius

In this work, we identify open research opportunities in applying Neural Temporal Point Process (NTPP) models to industry scale customer behavior data by carefully reproducing NTPP models published up to date on known literature benchmarks as well as applying NTPP models to a novel, real world consumer behavior dataset that is twice as large as the largest p

Boyan Jiang, Xinlin Ren, Mingsong Dou, Xiangyang Xue

Recent progress in 4D implicit representation focuses on globally controlling the shape and motion with low dimensional latent vectors, which is prone to missing surface details and accumulating tracking error. While many deep local representations have shown promising results for 3D shape modeling, their 4D counterpart does not exist yet. In this paper, we

Yu-Huan Wu, Da Zhang, Le Zhang, Xin Zhan

Current efficient LiDAR-based detection frameworks are lacking in exploiting object relations, which naturally present in both spatial and temporal manners. To this end, we introduce a simple, efficient, and effective two-stage detector, termed as Ret3D. At the core of Ret3D is the utilization of novel intra-frame and inter-frame relation modules to capture

Yanli Liu, Jiming Zhao, Chu-Min Li, Hua Jiang

Maximum Common induced Subgraph (MCS) is an important NP-hard problem with wide real-world applications. Branch-and-Bound (BnB) is the basis of a class of efficient algorithms for MCS, consisting in successively selecting vertices to match and pruning when it is discovered that a solution better than the best solution found so far does not exist. The method

Heishun Zen, Ryoichi Hajima, Hideaki Ohgaki

The detailed structure of few-cycle superradiant pulses generated from a free-electron laser (FEL) oscillator was experimentally revealed for the first time. As predicted in numerical simulations, the obtained pulse structures have ringing, i.e., a train of subpulses following the main pulse. Owing to the phase retrieval with a combination of linear and nonl

Hideaki Sugawara, Yasutada Tanabe, Masaharu Kameda

A numerical simulation method of computational fluid dynamics (CFD) coupling with a trim analysis for coaxial rotor systems is described in this paper. The trim analysis is implemented using a rotorcraft flow solver, rFlow3D. Six target forces and moments, which are the thrust of the coaxial rotor system, the rolling and pitching moments for each upper and l

Yuefang Sun

In this paper, we study the complexity of two types of digraph packing problems: perfect out-forests problem and Steiner cycle packing problem. For the perfect out-forest problem, we prove that it is NP-hard to decide whether a given strong digraph contains a 1-perfect out-forest. However, when restricted to a semicomplete digraph $D$, the problem of decidin

Tsuyoshi Miezaki, Hiroyuki Nakasora

In the present paper, we give the Assmus--Mattson type theorem for near-extremal Type I and even formally self-dual codes. We show the existence of $1$-designs or $2$-designs for these codes. As a corollary, we prove the uniqueness of a self-orthogonal $2$-$(16,6,8)$ design.

Ahmed Khalifa, Ganpathy Murthy, Ribhu K. Kaul

We study the edge spectrum of twisted sheets of single layer and bilayer graphene in cases where the continuum model predicts a valley Chern insulator -- an insulating state in which the occupied moir\'e mini-bands from each valley have a net Chern number, but both valleys together have no net Chern number, as required by time reversal symmetry. In a simple

Tanaji Sen

We develop theoretical expressions for the luminosity and beam-beam tune shifts in the presence of both a crossing angle and hourglass effects for the present and next generation of symmetric e$^+$-e$^-$ colliders. The theory is applied to the design of the Fermilab site filler Higgs factory and to the FCC-ee collider.

Siyu Li, Milos Zefran, Igor Paprotny

An important problem in microrobotics is how to control a large group of microrobots with a global control signal. This paper focuses on controlling a large-scale swarm of MicroStressBots with on-board physical finite-state machines. We introduce the concept of group-based control, which makes it possible to scale up the swarm size while reducing the complex

Yuya Maruyama, Hiroshi Fukui, Tsubasa Hirakawa, Takayoshi Yamashita

Robot navigation with deep reinforcement learning (RL) achieves higher performance and performs well under complex environment. Meanwhile, the interpretation of the decision-making of deep RL models becomes a critical problem for more safety and reliability of autonomous robots. In this paper, we propose a visual explanation method based on an attention bran

Chen Yang, Yupeng Hou, Yang Song, Tao Zhang

Person-job fit is the core technique of online recruitment platforms, which can improve the efficiency of recruitment by accurately matching the job positions with the job seekers. Existing works mainly focus on modeling the unidirectional process or overall matching. However, recruitment is a two-way selection process, which means that both candidate and em

Jinxin Ding, Yuxin Huang, Keyang Ni, Xueyao Wang

Intellectual properties is increasingly important in the economic development. To solve the pain points by traditional methods in IP evaluation, we are developing a new technology with machine learning as the core. We have built an online platform and will expand our business in the Greater Bay Area with plans.

Mohammed Alaloul, Khalil As'ham, Haroldo T. Hattori, Andrey E. Miroshnichenko

The ultrafast response and broadband absorption of all-optical graphene switches are highly desirable features for on-chip photonic switching. However, because graphene is an atomically thin material, its absorption of guided optical modes is relatively low, resulting in high saturation thresholds and switching energies for these devices. To boost the absorp

Adrien Benamira, Tristan Guérand, Thomas Peyrin, Trevor Yap

We propose $\mathcal{T}$ruth $\mathcal{T}$able net ($\mathcal{TT}$net), a novel Convolutional Neural Network (CNN) architecture that addresses, by design, the open challenges of interpretability, formal verification, and logic gate conversion. $\mathcal{TT}$net is built using CNNs' filters that are equivalent to tractable truth tables and that we call Learni

Xiujun Shu, Wei Wen, Haoqian Wu, Keyu Chen

Text-based person retrieval aims to find the query person based on a textual description. The key is to learn a common latent space mapping between visual-textual modalities. To achieve this goal, existing works employ segmentation to obtain explicitly cross-modal alignments or utilize attention to explore salient alignments. These methods have two shortcomi

Ruizhe Jia, Steven Yin

We study the competition between blockchains in a \emph{multi-chain} environment, where a dominant EVM-compatible blockchain (e.g., Ethereum) co-exists with an alternative EVM-compatible (e.g., Avalanche) and an EVM-incompatible (e.g., Algorand) blockchain. While EVM compatibility allows existing Ethereum users and developers to migrate more easily over to t

Peng Wang, Shuzhi Sam Ge, Xiaobing Zhang

This work deals with the event-triggered finite-time control for high-order systems based on an implicit Lyapunov function (ILF). With the construction of an inverse optimal problem, a novel expression of ILF is obtained. By designing the event-triggering mechanism elaborately, it is guaranteed that the trivial solution of the closed-loop system is globally

Jianhang Zhu, Rongpeng Li, Guoru Ding, Chan Wang

Along with the fast development of network technology and the rapid growth of network equipment, the data throughput is sharply increasing. To handle the problem of backhaul bottleneck in cellular network and satisfy people's requirements about latency, the network architecture like information-centric network (ICN) intends to proactively keep limited popula

Ran Gu, Jingyang Zhang, Guotai Wang, Wenhui Lei

Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance for medical image segmentation, yet need plenty of manual annotations for training. Semi-Supervised Learning (SSL) methods are promising to reduce the requirement of annotations, but their performance is still limited when the dataset size and the number of annotated images are s

Qiuliang Ye, Li-Wen Wang, Daniel Pak-Kong Lun

Phase retrieval (PR), a long-established challenge for recovering a complex-valued signal from its Fourier intensity-only measurements, has attracted considerable attention due to its widespread applications in digital imaging. Recently, deep learning-based approaches were developed that achieved some success in single-shot PR. These approaches require a sin

Sila Lertbanjongngam, Bodin Chinthanet, Takashi Ishio, Raula Gaikovina Kula

AlphaCode is a code generation system for assisting software developers in solving competitive programming problems using natural language problem descriptions. Despite the advantages of the code generating system, the open source community expressed concerns about practicality and data licensing. However, there is no research investigating generated codes i

Michal Praszalowicz

Chiral Quark Soliton Model has been successfully applied to describe heavy baryon spectrum, both for charm and bottom, leading to the conclusion that the heavy quark has no effect on the soliton. This suggests that replacing a heavy quark by a heavy anti-diquark $\bar{Q}\bar{Q}$ in color triplet should give a viable description of heavy tetraquarks. We follo

Ting Lan, Huazhong Lü

The balanced hypercube $BH_{n}$, a variant of the hypercube, is a novel interconnection network for massive parallel systems. It is known that the balanced hypercube remains Hamiltonian after deleting at most $4n-5$ faulty edges if each vertex is incident with at least two edges in the resulting graph for all $n\geq2$. In this paper, we show that there exist

Yiming Chen, Guohao Dai, Mufeng Zhou, Mingyen Lee

Graph convolutional network (GCN), an emerging algorithm for graph computing, has achieved promising performance in graphstructure tasks. To achieve acceleration for data-intensive and sparse graph computing, ASICs such as GCNAX have been proposed for efficient execution of aggregation and combination in GCN. GCNAX reducing 8x DRAM accesses compared with pre

Lianyu Hu, Shenglan Liu, Wei Feng

It's common for current methods in skeleton-based action recognition to mainly consider capturing long-term temporal dependencies as skeleton sequences are typically long (>128 frames), which forms a challenging problem for previous approaches. In such conditions, short-term dependencies are few formally considered, which are critical for classifying similar

Chancellor Johnstone, Dan Nettleton

The COVID-19 pandemic was responsible for the cancellation of both the men's and women's 2020 National Collegiate Athletic Association (NCAA) Division 1 basketball tournaments. Starting from the point at which the Division 1 tournaments and any unfinished conference tournaments were cancelled, we deliver closed-form probabilities for each team of making the

Hongming Luo, Fei Zhou, Kin-man Lam, Guoping Qiu

User videos shared on social media platforms usually suffer from degradations caused by unknown proprietary processing procedures, which means that their visual quality is poorer than that of the originals. This paper presents a new general video restoration framework for the restoration of user videos shared on social media platforms. In contrast to most de

Vitaly Bergelson, Younghwan Son

We introduce an ergodic approach to the study of {\em joint normality} of representations of numbers. For example, we show that for any integer $b \geq 2$ almost every number $x \in [0,1)$ is jointly normal with respect to the $b$-expansion and continued fraction expansion. This fact is a corollary of the following result which deals with {\em pointwise join

Di Wu, Fanghua Jiang, Hexi Baoyin

In this paper, the time- and propellant-optimal low-thrust rephasing problems in circular orbit are studied to depict their solution spaces in an atlas. The number of key parameters that settle the rephasing problems is reduced by developing a set of linearized equations of motion based on the Sundman transformation and by formulating two reduced shooting fu

Dong-Liang Fang, Amand Faessler

We develop the formalism for calculating the decay rate of neutrinoless double beta decay to the $2^+$ excited states within L-R symmetric model. We consider the effects from induced hadronic currents up to NLO. The QRPA method in a spherical basis is adopted for the nuclear many-body calculation and the corresponding nuclear matrix elements are given. Also,

Li Zhao, Chen-Song Zhang, Chun-Sheng Feng, Shi Shu

The compositional model is often used to describe multicomponent multiphase porous media flows in the petroleum industry. The fully implicit method with strong stability and weak constraints on time-step sizes is commonly used in the mainstream commercial reservoir simulators. In this paper, we develop an efficient multi-stage preconditioner for the fully im

Jia-Xiang Li, Song Wu, Li-Li Hao, Qun-Li Lei

Thermodynamic behavior of polymer chains out of equilibrium is a fundamental problem in both polymer physics and biological physics. By using molecular dynamics simulation, we discover a general non-equilibrium mechanism that controls the conformation and dynamics of polar active polymer, i.e., head activity commands the overall chain activity, resulting in

Colin Orion Chandler, William J. Oldroyd, Chadwick A. Trujillo

We report object 282P/(323137) 2003 BM80 is undergoing a sustained activity outburst, lasting over 15 months thus far. These findings stem in part from our NASA Partner Citizen Science project Active Asteroids (http://activeasteroids.net), which we introduce here. We acquired new observations of 282P via our observing campaign (Vatican Advanced Technology Te

Renke Huang, Chenyang Li, Francesco A. Evangelista

In this work, we propose a quantum unitary downfolding formalism based on the driven similarity renormalization group (QDSRG) that may be combined with quantum algorithms for both noisy and fault-tolerant hardware. The QDSRG is a classical polynomially-scaling downfolding method that avoids the evaluation of costly three- and higher-body reduced density matr

Alejandro Ayala, Bilgai Almeida Zamora, J. J. Cobos-Martínez, S. Hernández-Ortiz

In heavy-ion collisions, fluctuations of conserved charges are known to be sensitive observables to probe criticality for the QCD phase transition and to locate the position of the putative critical end point (CEP). In this work we seek to show that the Linear Sigma Model with quarks produces an effective description of the QCD phase diagram in which deviati

Min Sup Hur, Bernhard Ersfeld, Hyojeong Lee, Hyunseok Lee

We propose a new method for laser pulse compression that uses the spatially varying dispersion of a plasma plume with a density gradient. This novel scheme can be used to compress ultrahigh power lasers. A long, negatively frequency-chirped, laser pulse reflects off the plasma ramp of an over-dense plasma. As the density increases longitudinally the high fre

Luis A. Dupont, Humberto Muñoz-George, Rafael H. Villarreal

In this paper we study the normality of monomial ideals using linear programming and graph theory. We give normality criteria for monomial ideals, for ideals generated by monomials of degree two, and for edge ideals of graphs and clutters and their ideals of covers.

Shu-Min Wu, Hao-Sheng Zeng

Using two different types of quantification for quantum steering, we study the influence of Hawking radiation on quantum steering for fermionic fields in Schwarzschild spacetime. The degradation for the steering between physically accessible observers and the generation for the steering between physically accessible and inaccessible observers induced by Hawk

Yi-Xiang Wang, Fuxiang Li

The optical selection rules of an electron system under a magnetic field play key roles in determining its optical properties, from which the band structures and underlying symmetries can be derived. In this Letter, based on a three-dimensional strong topological insulator model describing ZrTe5,we study the Landau levels (LLs) and magneto-optical conductivi

Yi-Xiang Wang, Fuxiang Li

We use the Dirac cone model to explore the high Chern number (C) phases that are realized in the magnetic-doped topological insulator (TI) multilayer structures by Zhao et al. [Nature 588, 419 (2020)]. The Chern number is calculated by capturing the evolution of the phase boundaries with the parameters and then the Chern number phase diagrams of the TI multi

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si

The prevailing graph neural network models have achieved significant progress in graph representation learning. However, in this paper, we uncover an ever-overlooked phenomenon: the pre-trained graph representation learning model tested with full graphs underperforms the model tested with well-pruned graphs. This observation reveals that there exist confound

Luke Snow, Vikram Krishnamurthy, Brian M. Sadler

In mathematical psychology, recent models for human decision-making use Quantum Decision Theory to capture important human-centric features such as order effects and violation of the sure-thing principle (total probability law). We construct and analyze a human-sensor system where a quickest detector aims to detect a change in an underlying state by observin

Nelson Velandia SJ, Alfonso Leyva, Javier Alexander Cano-Arango

We describe the trajectories of circular orbits of spinless and spinning test particles around of rotating bodies in equatorial and non-equatorial planes via the Mathisson-Papapetrou-Dixon equations which include the Ricci rotation coefficients with the purpose of describing not only the curvature of space time, but also the rotation of the spinning test par

Ted Tao Yuan, Zezhong Zhang

To recommend relevant merchandises for seasonal retail events, we rely on item retrieval from marketplace inventory. With feedback to expand query scope, we discuss keyword expansion candidate selection using word embedding similarity, and an enhanced tf-idf formula for expanded words in search ranking.

Gopal Sharma, Kangxue Yin, Subhransu Maji, Evangelos Kalogerakis

We propose to utilize self-supervised techniques in the 2D domain for fine-grained 3D shape segmentation tasks. This is inspired by the observation that view-based surface representations are more effective at modeling high-resolution surface details and texture than their 3D counterparts based on point clouds or voxel occupancy. Specifically, given a 3D sha

Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath

Conditional randomization tests (CRTs) assess whether a variable $x$ is predictive of another variable $y$, having observed covariates $z$. CRTs require fitting a large number of predictive models, which is often computationally intractable. Existing solutions to reduce the cost of CRTs typically split the dataset into a train and test portion, or rely on he

Li Xu, Cuiling Fan, Dongchun Han

The singleton defect of an $[n,k,d]$ linear code ${\cal C}$ is defined as $s({\cal C})=n-k+1-d$. Codes with $S({\cal C})=0$ are called maximum distance separable (MDS) codes, and codes with $S(\cal C)=S(\cal C ^{\bot})=1$ are called near maximum distance separable (NMDS) codes. Both MDS codes and NMDS codes have good representations in finite projective geom

Maxwell C. Siegel

This paper gives an overview of $\left(p,q\right)$-adic Fourier theory - the Fourier theory of functions from the $p$-adic numbers to the $q$-adic numbers, where $p$ and $q$ are distinct primes - which we then use to prove a novel $\left(p,q\right)$-adic generalization of Norbert Wiener's celebrated Tauberian Theorem. Letting $K$ be a metrically complete, al

Ryo Hanai

Active systems are comprised of constituents with interactions that are generically non-reciprocal in nature. Such non-reciprocity often gives rise to situations where conflicting objectives exist, such as in the case of a predator pursuing its prey, while the prey attempts to evade capture. This situation is somewhat reminiscent of those encountered in geom

Rei Murakami

In this paper, we prove that there exists a solution of the $J$-equation on the total space of a holomorphic submersion if there exist solutions of the $J$-equation on the fibers and the base. The method is an adiabatic limit technique. We also partially prove the converse implication. More precisely, if the total space is $J$-nef, then each fiber is $J$-nef

Surajit Basak, Andrzej Ptok

Topological properties of systems lead to the emergence of surface states which can be observed experimentally within the angle-resolved photoemission spectroscopy (ARPES) measurements. Recently, the topological properties of Pb$_{2}$Pd were reported. In this paper, we discuss the role of the surface termination on the realized surface states. We discuss the

Amir Akbary, Alia Hamieh

Let $d\in\mathbb{N}$, and let $\pi$ be a fixed cuspidal automorphic representation of $\mathrm{GL}_{d}(\mathbb{A}_{\mathbb{Q}})$ with unitary central character. We determine the limiting distribution of the family of values $-\frac{L'}{L}(1+it,\pi\otimes\chi_D)$ as $D$ varies over fundamental discriminants. Here, $t$ is a fixed real number and $\chi_D$ is th

Belle II Collaboration, F. Abudinén, I. Adachi, L. Aggarwal

We report on a measurement of the $\Omega_c^0$ lifetime using $\Omega_c^0 \to \Omega^-\pi^+$ decays reconstructed in $e^+e^-\to c\bar{c}$ data collected by the Belle II experiment and corresponding to $207~{\rm fb^{-1}}$ of integrated luminosity. The result, $\rm\tau(\Omega_c^0)=243\pm48( stat)\pm11(syst)~fs$, agrees with recent measurements indicating that

Andrew Wang, Wyatt Mayor, Ryan Smith, Gopal Nookula

Robust classification is essential in tasks like autonomous vehicle sign recognition, where the downsides of misclassification can be grave. Adversarial attacks threaten the robustness of neural network classifiers, causing them to consistently and confidently misidentify road signs. One such class of attack, shadow-based attacks, causes misidentifications b

P. Dingus, C. Zhu, C. Gonatas

Ensembles of random legislative districts are a valuable tool for assessing whether a proposed district plan is an outlier or gerrymander. Expert witnesses have presented these in litigation using various methods, and unsurprisingly, they often disagree. Recent open source methods now permit independent validation of expert witness testimony. Here, we compar

Nardo Giménez, Guillermo Matera, Mariana Pérez, Melina Privitelli

This paper deals with properties of the algebraic variety defined as the set of zeros of a "deficient" sequence of multivariate polynomials. We consider two types of varieties: ideal-theoretic complete intersections and absolutely irreducible varieties. For these types, we establish improved bounds on the dimension of the set of deficient systems of each typ

Tushar Pandey

Unitary Modular Tensor Categories(UMTC) have a one-to-one correspondence with Topological Quantum Field Theories (TQFT). Different identifications have been made so far associating different physical particle types (anyons) to different UMTCs. However, the area of anyon model transformations has not been discovered much, which correspond to topological phase

Chun-Hao Liu, Burhaneddin Yaman

We introduce a new type of autonomous vehicle - an autonomous dozer that is expected to complete construction site tasks in an efficient, robust, and safe manner. To better handle the path planning for the dozer and ensure construction site safety, object detection plays one of the most critical components among perception tasks. In this work, we first colle

Radim Pánis, Karel Adámek, Norbert Marwan

Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work we present a new strategy for an almost parameter-free RQA. The approach finally omits the choice of the threshold parameter by calculating the RQA measures for a range of thresholds (in fact recurrence rates). Specifically, we test the ability of t

Tong Zhou, Shaolei Ren, Xiaolin Xu

Malicious architecture extraction has been emerging as a crucial concern for deep neural network (DNN) security. As a defense, architecture obfuscation is proposed to remap the victim DNN to a different architecture. Nonetheless, we observe that, with only extracting an obfuscated DNN architecture, the adversary can still retrain a substitute model with high

P. V. Pyshkin, E. Ya. Sherman, A. Gábris, Lian-Ao Wu

Precise control of quantum systems with a moderate number of degrees of freedom, being of interest for application in quantum technologies, becomes experimentally feasible. Various types of quantum scenarios and protocols are being widely discussed in scientific literature. We propose, analyze, and optimize a protocol which allows fast simulation of properti

Daniela A. Parletta, Andrea Paudice, Massimiliano Pontil, Saverio Salzo

In this work we study high probability bounds for stochastic subgradient methods under heavy tailed noise. In this setting the noise is only assumed to have finite variance as opposed to a sub-Gaussian distribution for which it is known that standard subgradient methods enjoys high probability bounds. We analyzed a clipped version of the projected stochastic

Erik Peterson, Alexander Lavin

A ''technology lottery'' describes a research idea or technology succeeding over others because it is suited to the available software and hardware, not necessarily because it is superior to alternative directions--examples abound, from the synergies of deep learning and GPUs to the disconnect of urban design and autonomous vehicles. The nascent field of Sel

Eren Güvenilir, Fatih Ozaydin, Özgür E. Müstecaplıoğlu, Tuğrul Hakioğlu

We consider a semi-classical heat engine with a $q$-deformed quantum oscillator working substance and classical thermal baths. We investigate the influence of the quantum statistical deformation parameter $q$ on the work and efficiency of the engine. In usual heat engines, a Hamiltonian parameter is varied during the work injection and extraction stages whil

Rina Friedberg, Ryan Rogers

We study a new privacy model where users belong to certain sensitive groups and we would like to conduct statistical inference on whether there is significant differences in outcomes between the various groups. In particular we do not consider the outcome of users to be sensitive, rather only the membership to certain groups. This is in contrast to previous

Fatih Ecevit, Cem Yalçın Yıldırım

In this paper we are concerned with the asymptotic behavior of \[ \operatorname{tr}(\mathcal{L}^+_{\rm sq}) = \frac{1}{4} \sum_{j,k=0 \atop (j,k) \neq (0,0)}^{n-1} \frac{1}{1-\frac{1}{2} \big( \cos \frac{2\pi j}{n} + \cos \frac{2\pi k}{n} \big)}, \] the trace of the pseudoinverse of the Laplacian matrix related with the square lattice, as $n \to \infty$. The