August 2022 arXiv papers — page 77

Yinghui Shi, Xiaobin Sun, Liqiong Wang, Yingchao Xie

In this paper, we study the asymptotic behavior for multi-scale stochastic differential equations driven by L\'evy processes. The optimal strong convergence order 1/2 is obtained by studying the regularity estimates for the solution of Poisson equation with polynomial growth coefficients, and the optimal weak convergence order 1 is got by using the technique

Giovanni Naldi, Giuseppe Patane'

This work is concerned with epidemiological models defined on networks, which highlight the prominent role of the social contact network of a given population in the spread of infectious diseases. In particular, we address the modelling and analysis of very large networks. As a basic epidemiological model, we focus on a SEIR (Susceptible-Exposed-Infective-Re

Srimanta Pakhira, Shrish Nath Upadhyay

Recently, 2D JTMDs with asymmetric electronic structures are inviting an intense research interest in modern science and technology. Using the first principles-based periodic hybrid dispersion-corrected Density Functional Theory (DFT-D) method, we have investigated the equilibrium structure, geometry, and electronic properties of the 2D monolayer MoSSe JTMD

Kun Qiu, Harry Chang, Ying Wang, Xiahui Yu

Sophisticated traffic analytics, such as the encrypted traffic analytics and unknown malware detection, emphasizes the need for advanced methods to analyze the network traffic. Traditional methods of using fixed patterns, signature matching, and rules to detect known patterns in network traffic are being replaced with AI (Artificial Intelligence) driven algo

Petar Djapić, Petar Marković, Ralph McKenzie, Aleksandar Prokić

We begin the investigation of the variety of semilattices of Mal'cev blocks, which we call SMB algebras.

Srimanta Pakhira, Vikash Kumar

H$_2$ evolution reaction (HER) requires an electrocatalyst to reduce the reaction barriers for the efficient production of H$_2$. Platinum-group metal (PGM) elements such as Pt, Pd, etc. and their derivatives show excellent electrocatalytic activity for HER. The high cost and lack of availability of PGM elements bring constraints over their wide commercial a

Judith Sáinz-Pardo Díaz, Álvaro López García

Openly sharing data with sensitive attributes and privacy restrictions is a challenging task. In this document we present the implementation of pyCANON, a Python library and command line interface (CLI) to check and assess the level of anonymity of a dataset through some of the most common anonymization techniques: k-anonymity, ($\alpha$,k)-anonymity, $\ell$

Pei-Ling Huang, Chao Ma, Xiang-Long Yu, Jiansheng Wu

The measurement of topological number is crucial in the research of topological systems. Recently, the relations between the topological number and the dynamics are built. But a direct method to read out the topological number via the dynamics is still lacking. In this work, we propose a new dynamical protocol to directly measure the topological number of an

Hamid Shabani, Amir Hadi Ziaie, Hooman Moradpour

The Einstein static (ES) state is a good candidate for describing the very early universe in terms of a regular cosmological model in which the Big Bang singularity is avoided. In the present study we propose an ES solution in the framework of generalized Rastall gravity (GRG), a modified version of original Rastall theory in which the coupling parameter is

Yousef Bisabr

We argue that most advances in science and technology during the past and the present centuries rely on modern physics concepts developed in the early $20$th century. The reliance is so profound that any improvement of literacy of science and technology falters in the absence of those concepts in physics education. Despite this important role, there are some

Ali Can Demiralp, Dirk Norbert Helmrich, Joachim Protze, Torsten Wolfgang Kuhlen

Particle advection is the approach for extraction of integral curves from vector fields. Efficient parallelization of particle advection is a challenging task due to the problem of load imbalance, in which processes are assigned unequal workloads, causing some of them to idle as the others are performing compute. Various approaches to load balancing exist, y

Tomoharu Iwata, Yoshinobu Kawahara

We propose a data-driven method for controlling the frequency and convergence rate of black-box nonlinear dynamical systems based on the Koopman operator theory. With the proposed method, a policy network is trained such that the eigenvalues of a Koopman operator of controlled dynamics are close to the target eigenvalues. The policy network consists of a neu

Juhyung Park, Dongwon Park, Sooyeon Ji, Hyeong-Geol Shin

Deep learning-based denoising methods have shown powerful results for improving the signal-to-noise ratio of magnetic resonance (MR) images, mostly by leveraging supervised learning with clean ground truth. However, acquiring clean ground truth images is often expensive and time-consuming. Self supervised methods have been widely investigated to mitigate the

Yinhe Peng, Liuzhen Wu

We construct in ZFC an L topological vector space -- a topological vector space that is an L space -- and an L field -- a topological field that is an L space. This generalizes results in [5] and [8].

Seonghoon Yoo, Seongah Jeong, Joonhyuk Kang

Unmanned aerial vehicles (UAVs) have been actively studied as moving cloudlets to provide application offloading opportunities and to enhance the security level of user equipments (UEs). In this correspondence, we propose a hybrid UAV-aided secure offloading system in which a UAV serves as a helper by switching the mode between jamming and relaying to maximi

Taekyun Kim, Dae San Kim, Hye Kyung Kim

We introduce the generalized degenerate Euler-Genocchi polynomials as a degenerate version of the Euler-Genocchi polynomials. In addition, we introduce their higher-order version, namely the generalized degenerate Euler-Genocchi polynomials of order {\alpha}, as a degenerate version of the generalized Euler-Genocchi polynomials of order {\alpha}. The aim of

Yunqi Liu, Cheng-Yong Zhang, Qian Chen, Zhoujian Cao

We study the critical dynamics in the scalarization and descalarization in the fully nonlinear dynamical evolution in a general theory with scalar field coupling with both Gauss-Bonnet invariant and Ricci scalar. We explore how the Gauss-Bonnet term triggers the black hole scalarization. A typical type I critical phenomenon is observed, where an unstable cri

Songpengcheng Xia, Lei Chu, Ling Pei, Wenxian Yu

Human activity recognition (HAR) with wearables is promising research that can be widely adopted in many smart healthcare applications. In recent years, the deep learning-based HAR models have achieved impressive recognition performance. However, most HAR algorithms are susceptible to the multi-class windows problem that is essential yet rarely exploited. In

Xiaolong Li, Kui Wang, Haotian Wu

In this paper, we prove a quantitative spectral inequality for the second Robin eigenvalue in non-compact rank-1 symmetric spaces. In particular, this shows that for bounded domains in non-compact rank-1 symmetric spaces, the geodesic ball maximises the second Robin eigenvalue among domains of the same volume, with negative Robin parameter in the regime conn

Norio Iwase

We are trying to look over the Lusternik-Schnirelmann theory (L-S theory, for short) and the Topological Complexity (TC, for short) as a natural extension of the L-S theory. In particular, we focus on the impact of the ideas originated from E. Fadell and S. Husseini on both theories. More precisely, we see how their ideas on a category weight and a relative

Robin Kothari, Ryan O'Donnell

Suppose $\boldsymbol{y}$ is a real random variable, and one is given access to ``the code'' that generates it (for example, a randomized or quantum circuit whose output is $\boldsymbol{y}$). We give a quantum procedure that runs the code $O(n)$ times and returns an estimate $\widehat{\boldsymbol{\mu}}$ for $\mu = \mathrm{E}[\boldsymbol{y}]$ that with high pr

István Zoltán Kiss, Péter L. Simon

Many models in mathematical epidemiology are developed with the aim to provide a framework for parameter estimation and then prediction. It is well-known that parameters are not always uniquely identifiable. In this paper we consider network-based mean-field models and explore the problem of parameter identifiability when observations about an epidemic are a

Hyeokjoo Park, Do Y. Kwak

In this paper we present an immersed weak Galerkin method for solving second-order elliptic interface problems on polygonal meshes, where the meshes do not need to be aligned with the interface. The discrete space consists of constants on each edge and broken linear polynomials satisfying the interface conditions in each element. For triangular meshes, such

Wenshuo Wang, Letian Wang, Chengyuan Zhang, Changliu Liu

No human drives a car in a vacuum; she/he must negotiate with other road users to achieve their goals in social traffic scenes. A rational human driver can interact with other road users in a socially-compatible way through implicit communications to complete their driving tasks smoothly in interaction-intensive, safety-critical environments. This paper aims

Nicat Aliyev, Emre Mengi

This work concerns the minimization of the pseudospectral abscissa of a matrix-valued function dependent on parameters analytically. The problem is motivated by robust stability and transient behavior considerations for a linear control system that has optimization parameters. We describe a subspace procedure to cope with the setting when the matrix-valued f

Sushil Mahavir Varma, Francisco Castro, Siva Theja Maguluri

We consider the load balancing system under Poisson arrivals, exponential services, and homogeneous servers. Upon arrival, a job is to be routed to one of the servers, where it is queued until service. We consider the Power-of-$d$ choices routing algorithm, which chooses the queue with minimum length among $d$ randomly sampled queues. We study this system in

Vikas N. Thakur, Ajay Kumar, Aakash Kaushik, Guru Dutt Gupt

We report the high temperature dielectric and {\it ac} impedance spectroscopy investigation of Nb substituted LaCo$_{0.7}$Nb$_{0.3}$O$_3$ polycrystalline sample. The maximum dielectric constant value was observed $\approx$1400 at around 400~K where the peak value shows a decreasing trend at higher temperatures and frequency. Similar variation was reflected i

Mi-Ran Choi, Young-Ran Lee

We consider the dispersion managed nonlinear Schr\"odinger equation with power-law nonlinearity and its discrete version of equations with step size $h\in(0,1]$. We prove that the solutions of the discrete equations strongly converge in $L^2(\mathbb{R})$ to the solution of the dispersion managed NLS as $h\to 0$ after showing the global well-posedness of the

Loc X. Nguyen, Yan Kyaw Tun, Tri Nguyen Dang, Yu Min Park

In recent years, unmanned aerial vehicles (UAVs) assisted mobile edge computing systems have been exploited by researchers as a promising solution for providing computation services to mobile users outside of terrestrial infrastructure coverage. However, it remains challenging for the standalone MEC-enabled UAVs in order to meet the computation requirement o

Shonosuke Sugasawa, Jae Kwang Kim, Kosuke Morikawa

This paper proposes a flexible Bayesian approach to multiple imputation using conditional Gaussian mixtures. We introduce novel shrinkage priors for covariate-dependent mixing proportions in the mixture models to automatically select the suitable number of components used in the imputation step. We develop an efficient sampling algorithm for posterior comput

Tatsuo Nishitani

In this note, we improve a previously proven non-solvability result of the Cauchy problem for the Cauchy problem in the Gevrey class for a homogeneous second-order differential operator mentioned in the title. We prove that the Cauchy problem for this operator is not locally solvable at the origin for any lower order term in the Gevrey class of order greater

Zhanyi Jiao, Steven Kou, Yang Liu, Ruodu Wang

We study an axiomatic framework for anonymized risk sharing. In contrast to traditional risk sharing settings, our framework requires no information on preferences, identities, private operations and realized losses from the individual agents, and thereby it is useful for modeling risk sharing in decentralized systems. Four axioms natural in such a framework

Harmanpreet Kaur, Doug Downey, Amanpreet Singh, Evie Yu-Yen Cheng

The vast scale and open-ended nature of knowledge graphs (KGs) make exploratory search over them cognitively demanding for users. We introduce a new technique, polymorphic lenses, that improves exploratory search over a KG by obtaining new leverage from the existing preference models that KG-based systems maintain for recommending content. The approach is ba

Zhenan Fan, Zirui Zhou, Jian Pei, Michael P. Friedlander

Federated learning is an emerging technique for training models from decentralized data sets. In many applications, data owners participating in the federated learning system hold not only the data but also a set of domain knowledge. Such knowledge includes human know-how and craftsmanship that can be extremely helpful to the federated learning task. In this

Jiaye Li, Minghao Li, Zikai Alex Wen, Wei Cai

First-person shooter (FPS) game tournaments take place across the globe. A growing number of people choose to watch FPS games online instead of attending the game events in person. However, live streaming might miss critical highlight moments in the game, including kills and tactics. We identify how and why the live streaming team fails to capture highlight

Yueshan Lin, Wei Feng, Ting Zhou, Yanmin Wang

The sixth-generation (6G) network will shift its focus to supporting everything including various machine-type devices (MTDs) in an everyone-centric manner. To ubiquitously cover the MTDs working in rural and disastrous areas, satellite communications become indispensable, while mobile edge computing (MEC) also plays an increasingly crucial role. Their sophi

G. Diguet, B. Ducharne, S. El Hog, F. Kato

Geometric confinement (GC) of skyrmions in nanodomains plays a crucial role in skyrmion stabilization. This confinement effect decreases the magnetic field necessary for skyrmion formation and is closely related to the applied mechanical stresses. However, the mechanism of GC is unclear and remains controversial. Here, we numerically study the effect of GC o

Xue Quan, Huajie Chen

The Wigner localization is an electron phase at low densities when the electrons are sharply localized around equilibrium positions. The simulation of the Wigner localization phenomenon requires careful treatment of the many-body correlations, as the electron-electron interaction dominates the system. This work proposes a numerical algorithm to study the ele

Neil Irwin Bernardo, Jingge Zhu, Yonina C. Eldar, Jamie Evans

Hardware-limited task-based quantization is a new design paradigm for data acquisition systems equipped with serial scalar analog-to-digital converters using a small number of bits. By taking into account the underlying system task, task-based quantizers can efficiently recover the desired parameters from the low-bit quantized observation. Current design and

Saurav Agarwal, Srinivas Akella

This paper introduces the correlated arc orienteering problem (CAOP), where the task is to find routes for a team of robots to maximize the collection of rewards associated with features in the environment. These features can be one-dimensional or points in the environment, and can have spatial correlation, i.e., visiting a feature in the environment may pro

Ravinder K. Banyal, Amirul Hasan, Reni Kupke, Hari Mohan Varshney

A next-generation instrument named, Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES), is being planned for the W. M. Keck Observatory. SCALES will have an integral field spectrograph (IFS) and a diffraction-limited imaging channel to discover and spectrally characterize the directly imaged exoplanets. Operating at thermal infrared w

Donghyun Son, Byounggyu Lew, Kwanghee Choi, Yongsu Baek

Social media platforms struggle to protect users from harmful content through content moderation. These platforms have recently leveraged machine learning models to cope with the vast amount of user-generated content daily. Since moderation policies vary depending on countries and types of products, it is common to train and deploy the models per policy. How

Wei Kou, Xiaopeng Wang, Xurong Chen

The partons model reveals the dynamical structure of nucleons (protons and neutrons). Studies related to thermodynamic quantities of nucleons are interesting and topical questions. In this work, for the first time we apply Page's theory of the studies of black hole to investigate the entropy of proton system. Inspired by the quantum entanglement entropy in b

Xuan Luo, Hai-Bing Fu, Hai-Jiang Tian

The $Z$-boson decay provides good opportunities for the research on $\Xi_{bQ'}$ baryon due to large quantity of $Z$ events that can be collected at the high-energy colliders. We performed a completed investigation of the indirect production of the $\Xi_{bc}$ and $\Xi_{bb}$ baryon via $Z$-boson decay $Z\to \Xi_{bQ'}+\bar b +\bar Q'$ with $Q'= (c, b)$ quark ac

Tongmu He

Any finite-dimensional $p$-adic representation of the absolute Galois group of a $p$-adic local field with imperfect residue field is characterized by its arithmetic and geometric Sen operators defined by Sen and Brinon. We generalize their construction to the fundamental group of a $p$-adic affine variety with a semi-stable chart, and prove that the module

Chenglong Bao, Chao Ding, Yuexin Zhou

This paper studies the robust isolated calmness property of the KKT solution mapping of a class of nonsmooth optimization problems on Riemannian manifolds. The manifold versions of the Robinson constraint qualification, the strict Robinson constraint qualification, and the second order conditions are defined and discussed. We show that the robust isolated ca

Jiayi Qin, Giovanni Guccione, Jinyong Ma, Chenyue Gu

Optical systems are often subject to parametric instability caused by the delayed response of the optical field to the system dynamics. In some cases, parasitic photothermal effects aggravate the instability by adding new interaction dynamics. This may lead to the possible insurgence or amplification of parametric gain that can further destabilize the system

Jianfeng Luo, Xiaojun Chen

In this paper, we investigate an optimal control problem with terminal stochastic linear complementarity constraints (SLCC), and its discrete approximation using the relaxation, the sample average approximation (SAA) and the implicit Euler time-stepping scheme. We show the existence of feasible solutions and optimal solutions to the optimal control problem a

Teo Banica

This is a joint introduction to classical and free probability, which are twin sisters. We first review the foundations of classical probability, notably with the main limiting theorems (CLT, CCLT, PLT, CPLT), and with a look into examples coming from Lie groups and random matrices. Then we present the foundations and main results of free probability, notabl

Yangjing Zhang, Ying Cui, Bodhisattva Sen, Kim-Chuan Toh

In this paper we study the computation of the nonparametric maximum likelihood estimator (NPMLE) in multivariate mixture models. Our first approach discretizes this infinite dimensional convex optimization problem by fixing the support points of the NPMLE and optimizing over the mixture proportions. In this context we propose, leveraging the sparsity of the

Phuong Ngo, Christan Thomas, Hieu Nguyen, Abdullah Eroglu

This paper aims to implement and evaluate the performance of quantum computing on solving combinatorial optimization problems arising from the operations of the power grid. To this end, we construct a novel mixed integer conic programming formulation for the reconfiguration of radial distribution network in response to faults in distribution lines. Comparing

David Monroe, Mohammad Alidoust, Igor Žutić

Integrating conventional superconductors with common III-V semiconductors provides a versatile platform to implement tunable Josephson junctions (JJs) and their applications. We propose that with gate-controlled time-dependent spin-orbit coupling, it is possible to strongly modify the current-phase relations and Josephson energy and provide a mechanism to dr

Chow-Choong Ngeow, Anupam Bhardwaj, Daniel Reiley, Russ R. Laher

We present the first absolute calibration for the yellow post-asymptotic-giant-branch (PAGB) stars in the g- and r-band based on time-series observations from the Zwicky Transient Facility. These absolute magnitudes were calibrated using four yellow PAGB stars (one non-varying star and three Type II Cepheids) located in the globular clusters. We provide two

Ming-yan Gong, Bin Lyu

The expectation-maximization (EM) and space-alternating generalized EM (SAGE) algorithms have been applied to direction of arrival (DOA) estimation in known noise. In this work, the two algorithms are proposed for DOA estimation in unknown uniform noise. Both the deterministic and stochastic signal models are considered. Moreover, a modified EM (MEM) algorit

Seamus D. Clarke, Sarah E. Jaffa, Anthony P. Whitworth

The interstellar medium is highly structured, presenting a range of morphologies across spatial scales. The large data sets resulting from observational surveys and state-of-the-art simulations studying these hierarchical structures means that identification and classification must be done in an automated fashion to be efficient. Here we present RJ-plots, an

Iñaki García Etxebarria

$\mathcal{N}=4$ supersymmetric Yang-Mills theories with algebra $\mathfrak{so}(4N)$ and appropriate choices of global structure can have non-invertible symmetries. We identify the branes holographically dual to the non-invertible symmetries, and derive the fusion rules for the symmetries from the worldvolume dynamics on the branes.

Rebecca Centeno, Matthias Rempel, Roberto Casini, Tanausu del Pino Aleman

We study the effects of finite spectral resolution on the magnetic field values retrieved through the weak field approximation (WFA) from the cores of the Mg II h & k lines. The retrieval of the line-of-sight (LOS) component of the magnetic field, $B_{\rm LOS}$, from synthetic spectra generated in a uniformly magnetized FAL-C atmosphere are accurate when res

Weihua Guo, Xuepeng Chen, Jiancheng Feng, Li Sun

We present observations of $J$=1-0 transition lines of ${ }^{12} \mathrm{CO}$, ${ }^{13} \mathrm{CO}$, and $\mathrm{C}^{18} \mathrm{O}$ towards the Galactic region of $153.60^{\circ} \leqslant l \leqslant 156.50^{\circ}$ and $1.85^{\circ} \leqslant b \leqslant 3.50^{\circ}$, using the Purple Mountain Observatory (PMO) 13.7 m millimeter telescope. Based on th

Tong Jiang, Jiajun Ren, Zhigang Shuai

Exciton coherence length (ECL) is an essential concept to characterize the nature of exciton in molecular aggregates for photosynthesis, organic photovoltaics, and light-emitting diodes. ECL has been defined in a number of ways through the variance or purity of the electronic reduced density matrix. However, we find that these definitions fail to present a m

Daiki Saito, Chul-Moon Yoo

We study false vacuum decay in a black hole (BH) spacetime with an angular momentum. Considering the false vacuum region described by a Kerr-de Sitter geometry, under the thin wall approximation, we can obtain the stationary configuration of the vacuum bubble seen from the outside false vacuum region without specifying the geometry inside the domain wall. Th

Yunhong Li, Yuandong Bi, Weichuan Zhang, Jie Ren

In this paper, a color edge detection method is proposed where the multi-scale Gabor filter are used to obtain edges from input color images. The main advantage of the proposed method is that high edge detection accuracy is attained while maintaining good noise robustness. The proposed method consists of three aspects: First, the RGB color image is converted

Bo Lu, Yong-Pan Gao, Kai Wen, Chuan Wang

Spiking neural network is a kind of neuromorphic computing that is believed to improve the level of intelligence and provide advantages for quantum computing. In this work, we address this issue by designing an optical spiking neural network and find that it can be used to accelerate the speed of computation, especially on combinatorial optimization problems

Otávio Cury, Guilherme Avelino, Pedro Santos Neto, Ricardo Britto

In software development, the identification of source code file experts is an important task. Identifying these experts helps to improve software maintenance and evolution activities, such as developing new features, code reviews, and bug fixes. Although some studies have proposed repository mining techniques to automatically identify source code experts, th

Suzanne B. P. E. Timmermans, Alireza Ramezani, Toni Montalvo, Mark Nguyen

Cowpea chlorotic mottle virus (CCMV) is a widely used model for virus replication studies. A major challenge lies in distinguishing between the roles of the interaction between coat proteins and that between the coat proteins and the viral RNA in assembly and disassembly processes. Here, we report on the spontaneous and reversible size conversion of the empt

Na Huang, Yu-Hong Dai, Dominique Orban, Michael A. Saunders

We consider the generalized successive overrelaxation (GSOR) method for solving a class of block three-by-three saddle-point problems. Based on the necessary and sufficient conditions for all roots of a real cubic polynomial to have modulus less than one, we derive convergence results under reasonable assumptions. We also analyze a class of block lower trian

Changcun Huang

This paper provides a theoretical framework on the solution of feedforward ReLU networks for interpolations, in terms of what is called an interpolation matrix, which is the summary, extension and generalization of our three preceding works, with the expectation that the solution of engineering could be included in this framework and finally understood. To t

Michael Klamkin, Mathieu Tanneau, Terrence W. K. Mak, Pascal Van Hentenryck

This paper considers optimization proxies for Optimal Power Flow (OPF), i.e., machine-learning models that approximate the input/output relationship of OPF. Recent work has focused on showing that such proxies can be of high fidelity. However, their training requires significant data, each instance necessitating the (offline) solving of an OPF. To meet the r

Qing Song, Wenfeng Sun, Donghan Yang, Mengjie Hu

Human matting refers to extracting human parts from natural images with high quality, including human detail information such as hair, glasses, hat, etc. This technology plays an essential role in image synthesis and visual effects in the film industry. When the green screen is not available, the existing human matting methods need the help of additional inp

Mingjian He, Robert Malaney

Hybrid entanglement between discrete-variable (DV) and continuous-variable (CV) quantum systems is an essential resource for heterogeneous quantum networks. Our previous work showed that in lossy channels the teleportation of DV qubits, via CV-entangled states, can be significantly improved by a new protocol defined by a modified Bell state measurement at th

Robert Boltje, Benjamín García

In this article, we propose a concept of anti-involution for Green biset functors and we provide equivalent definitions. We present $\star$-Green biset functors and we study their orthogonal units and the orthogonal automorphisms in their associated categories.

Zan Gao, Xinglei Cui, Tao Zhuo, Zhiyong Cheng

Temporal action localization plays an important role in video analysis, which aims to localize and classify actions in untrimmed videos. The previous methods often predict actions on a feature space of a single-temporal scale. However, the temporal features of a low-level scale lack enough semantics for action classification while a high-level scale cannot p

Taro Sakurai, Norihide Tokushige

We show that the expected number of cliques in the Erd\H{o}s-R\'enyi random graph $G(n,p)$ is $n^{\frac1{-2\log p}(\log n-2\log\log n+O(1))}$.

Xumeng Wang, Wei Chen, Jiazhi Xia, Zhen Wen

Horizontal federated learning (HFL) enables distributed clients to train a shared model and keep their data privacy. In training high-quality HFL models, the data heterogeneity among clients is one of the major concerns. However, due to the security issue and the complexity of deep learning models, it is challenging to investigate data heterogeneity across d

M. I. Jimenez, R. Tojeiro

In the article [\emph{Deformations of hypersurfaces preserving the M\"obius metric and a reduction theorem}, Adv. Math. 256 (2014), 156--205], Li, Ma and Wang investigated the interesting class of Moebius deformable hypersurfaces, that is, the umbilic-free Euclidean hypersurfaces $f\colon M^n\to \mathbb{R}^{n+1}$ that admit non-trivial deformations preservin

William Holland, Olga Ohrimenko, Anthony Wirth

Access patterns to data stored remotely create a side channel that is known to leak information even if the content of the data is encrypted. To protect against access pattern leakage, Oblivious RAM is a cryptographic primitive that obscures the (actual) access trace at the expense of additional access and periodic shuffling of the server's contents. A class

Kamaludin Dingle

Why are simple, regular, and symmetric shapes common in nature? Many natural shapes arise as solutions to energy minimisation or other optimisation problems, but is there a general relation between optima and simple, regular shapes and geometries? Here we argue from algorithmic information theory that for objective functions common in nature -- based on phys

Niles Armstrong, Jory Denny, Jeremy LeCrone

We investigate the structure of discontinuities in clearance (or minimum time) functions for nonlinear control systems with general, closed obstacles (or targets). We establish general results regarding interactions between admissible trajectories and clearance discontinuities: e.g. instantaneous increases in clearance when passing through a discontinuity, a

Finn Lasse Buessen, Dvira Segal, Ilia Khait

We study a variation of the Trotter-Suzuki decomposition, in which a Hamiltonian exponential is approximated by an ordered product of two-qubit operator exponentials such that the Trotter step size is enhanced for a small number of terms. Such decomposition directly reflects hardware constraints of distributed quantum computers, where operations on monolithi

N. V. Rao, V. Leelavathi, Ch. Yaswanth, S. V. B. Rao

In this study, we extracted the amplitudes of the gravity waves (GWs)from the neutral densities measured in situ by the neutral gas and ion mass spectrometer aboard the Mars atmosphere and volatile evolution mission. The spatial and temporal variabilities of the GWs show that solar activity (the F10.7 cm solar flux corrected for a heliocentric distance of 1.

Gabriele Pozzato, Aki Takahashi, Xueyan Li, Donghoon Lee

In this paper, a core-shell enhanced single particle model for iron-phosphate battery cells is formulated, implemented, and verified. Starting from the description of the positive and negative electrodes charge and mass transport dynamics, the positive electrode intercalation and deintercalation phenomena and associated phase transitions are described with t

Rey Anaya, Alvaro Belmonte, Nathan Shank, Elise Sinani

We investigate a generalization of the bondage number of a graph called the \textit{$k\,$-synchronous bondage number}. The $k\,$-synchronous bondage number of a graph is the smallest number of edges that, when removed, increases the dominating number by $k$. In this paper, we discuss the 2-synchronous bondage number and then generalize to $k\,$-synchronous b

Tung H. Nguyen

Fix $\varepsilon>0$ and a nonnull graph $H$. A well-known theorem of R\"odl from the 80s says that every graph $G$ with no induced copy of $H$ contains a linear-sized $\varepsilon$-restricted set $S\subseteq V(G)$, which means $S$ induces a subgraph with maximum degree at most $\varepsilon\vert S\vert$ in $G$ or its complement. There are two extensions of th

Hadi Keramati, Feridun Hamdullahpur

We present surrogate models for heat transfer and pressure drop prediction of complex fin geometries generated using composite Bezier curves. Thermal design process includes iterative high fidelity simulation which is complex, computationally expensive, and time-consuming. With the advancement in machine learning algorithms as well as Graphics Processing Uni

Hwanhui Yun, Dominique Gautreau, K. Andre Mkhoyan, Turan Birol

Ruddlesden-Popper (RP) oxides (A$_{n+1}$B$_n$O$_{3n+1}$) comprised of perovskite (ABO$_3$)$_n$ slabs can host a wider variety of structural distortions than their perovskite counterparts. This makes accurate structural determination of RP oxides more challenging. In this study, we investigate the structural phase diagram of $n=1$ RP Sr$_2$SnO$_4$, one of alk

Zhi-Cheng Yang

Conservation laws and the associated hydrodynamic modes have important consequences on the growth of higher R\'enyi entropies in isolated quantum systems. It has been shown in various random unitary circuits and Hamiltonian systems that the dynamics of the R\'enyi entropies in the presence of a U(1) symmetry obey $S^{(n\geq 2)}(t) \propto t^{1/z}$, where $z$

Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal

Efficient vision works maximize accuracy under a latency budget. These works evaluate accuracy offline, one image at a time. However, real-time vision applications like autonomous driving operate in streaming settings, where ground truth changes between inference start and finish. This results in a significant accuracy drop. Therefore, a recent work proposed

Katelyn Laughon, Jason M. Yu, Tianyu Zhu

We present an efficient implementation of coupled-cluster Green's function (CCGF) method for simulating photoemission spectra of periodic systems. We formulate the periodic CCGF approach with Brillouin zone sampling in Gaussian basis at the coupled-cluster singles and doubles (CCSD) level. To enable CCGF calculations of realistic solids, we propose an active

Jiawang Nie, Li Wang, Zequn Zheng

There exist linear relations among tensor entries of low rank tensors. These linear relations can be expressed by multi-linear polynomials, which are called generating polynomials. We use generating polynomials to compute tensor rank decompositions and low rank tensor approximations. We prove that this gives a quasi-optimal low rank tensor approximation if t

Chuyen Nguyen, Caleb Morgan, Sudip Mittal

As the practicality of Artificial Intelligence (AI) and Machine Learning (ML) based techniques grow, there is an ever increasing threat of adversarial attacks. There is a need to red team this ecosystem to identify system vulnerabilities, potential threats, characterize properties that will enhance system robustness, and encourage the creation of effective d

Wei-Bin Yan, Zhong-Xiao Man, Ying-Jie Zhang, Heng Fan

We investigate the heat conduction between two one-dimension waveguides intermediated by a Laser-driving atom. The Laser provides the optical control on the heat conduction. The tunable asymmetric conduction of the heat against the temperature gradient is realized. Assisted by the modulated Laser, the heat conduction from either waveguide to the other wavegu

Bo Leng, Vien Van

Hopf insulators are topological insulators whose topological behavior arises from the nontrivial mapping from a 3D sphere to a 2D sphere, known as the Hopf map. The Hopf map, typically encountered in the study of spinor and skyrmion systems, is classified topologically by an integer invariant called the Hopf index. Here we show that due to the periodic circu

Tokura Willian, Barboza Marcelo, Batista Elismar, Menezes Ilton

In this paper we take a look at conditions that make a Riemann soliton trivial, compacity being one of them. We also show that the behaviour at infinity of the gradient field of a non-compact gradient Riemann soliton might cause the soliton to be an Einstein manifold. Finally, we obtain scalar curvature estimates for complete shrinking or steady gradient Rie

Yunge Cui, Xieyuanli Chen, Yinlong Zhang, Jiahua Dong

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great success in loop closure. The BoW features for loop searching can also be used in the subsequent 6-DoF loop correction. However, for 3D LiDAR SLAM, the state-of-the-art methods may

Saba Akhyani, Mehryar Abbasi Boroujeni, Mo Chen, Angelica Lim

Robots and artificial agents that interact with humans should be able to do so without bias and inequity, but facial perception systems have notoriously been found to work more poorly for certain groups of people than others. In our work, we aim to build a system that can perceive humans in a more transparent and inclusive manner. Specifically, we focus on d

Giammaria Giordano, Gerardo Festa, Gemma Catolino, Fabio Palomba

Context. Software reusability mechanisms, like inheritance and delegation in Object-Oriented programming, are widely recognized as key instruments of software design. These are used to reduce the risks of source code being affected by defects, other than to reduce the effort required to maintain and evolve source code. Previous work has traditionally employe

C. A. Walsh, D. S. Clark

The growth rate of the non-linear ablative Rayleigh-Taylor (RT) instability is enhanced by magnetic fields self-generated by the Biermann battery mechanism; a scaling for this effect with perturbation height and wavelength is proposed and validated with extended-magnetohydrodynamic simulations. The magnetic flux generation rate around a single RT spike is fo

Baturalp Yalcin, Ziye Ma, Javad Lavaei, Somayeh Sojoudi

Many fundamental low-rank optimization problems, such as matrix completion, phase synchronization/retrieval, power system state estimation, and robust PCA, can be formulated as the matrix sensing problem. Two main approaches for solving matrix sensing are based on semidefinite programming (SDP) and Burer-Monteiro (B-M) factorization. The SDP method suffers f

Prasanna Date, Shruti Kulkarni, Aaron Young, Catherine Schuman

Neuromorphic computers perform computations by emulating the human brain, and use extremely low power. They are expected to be indispensable for energy-efficient computing in the future. While they are primarily used in spiking neural network-based machine learning applications, neuromorphic computers are known to be Turing-complete, and thus, capable of gen

Jarle Brinchmann

I present an analysis of the JWST NIRSpec data of SMACS 0723 released as Early Release Observations. As part of this three new redshifts are provided, bringing the total of reliable redshifts to 14. I propose a modification to the direct abundance determination method that reduces sensitivity to flux calibration uncertainties by a factor of ~3 and show that

A. Cummings, J. Eser, G. Filippatos, A. V. Olinto

The next generation of ultra-high energy cosmic ray (UHECR) and very-high energy neutrino observatories will address the challenge of the extremely low fluxes of these particles at the highest energies. EUSO-SPB2 (Extreme Universe Space Observatory on a Super Pressure Balloon2) is designed to prepare space missions to address this challenge. EUSO-SPB2 is equ