January 2022 arXiv papers — page 36

Qiang Du, Xin Yang Lu, Chong Wang

In this paper we consider the functional \begin{equation*} E_{p,\la}(\Omega):=\int_\Omega \dist^p(x,\pd \Omega )\d x+\la \frac{\H^1(\pd \Omega)}{\H^2(\Omega)}. \end{equation*} Here $p\geq 1$, $\la>0$ are given parameters, the unknown $\Omega$ varies among compact, convex, Hausdorff two-dimensional sets of $\R^2$, $\pd \Omega$ denotes the boundary of $\Omega$

Rupal Roy, MM Rashid, Md Manjurul Ahsan, Zahed Siddique

Over the years, the number of exoskeleton devices utilized for upper-limb rehabilitation has increased dramatically, each with its own set of pros and cons. Most exoskeletons are not portable, limiting their utility to daily use for house patients. Additionally, the huge size of some grounded exoskeletons consumes space while maintaining a sophisticated stru

Xiaofeng Xue

In this paper we are concerned with hydrodynamics of a class of $N$-urn linear systems, which include voter models, pair-symmetric exclusion processes and binary contact path processes on $N$ urns as special cases. We show that the hydrodynamic limit of our process is driven by a $\left(C[0,1]\right)^\prime$-valued linear ordinary differential equation and t

Pavel B. Dubovski, Jeffrey A. Slepoi

Numerical solving differential equations with fractional derivatives requires elimination of the singularity which is inherent in the standard definition of fractional derivatives. The method of integration by parts to eliminate this singularity is well known. It allows to solve some equations but increases the order of the equation and sometimes leads to wr

Qiang Du, Xin Yang Lu, Chong Wang

We consider the minimization of an average distance functional defined on a two-dimensional domain $\Omega$ with an Euler elastica penalization associated with $\pd \Omega$, the boundary of $\Omega$. The average distance is given by \begin{equation*} \int_{\Omega} \dist^p(x,\pd \Omega )\d x \end{equation*} where $p\geq 1$ is a given parameter, and $\dist(x,\

Shou-Shan Bao, Qi-Xuan Xu, Hong Zhang

The approximate solution of the Klein-Gordon equation for a real scalar field of mass $\mu$ in the geometry of a Kerr black hole obtained by Detweiler \cite{Detweiler:1980uk} is widely used in the analysis of the stability of black holes as well as the search of axion-like particles. In this work, we confirm a missing factor $1/2$ in this solution, which was

Zexi Song, Zhiqiang Tan

Generalized linear mixed models are useful in studying hierarchical data with possibly non-Gaussian responses. However, the intractability of likelihood functions poses challenges for estimation. We develop a new method suitable for this problem, called imputation maximization stochastic approximation (IMSA). For each iteration, IMSA first imputes latent var

Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis

We propose RecShard, a fine-grained embedding table (EMB) partitioning and placement technique for deep learning recommendation models (DLRMs). RecShard is designed based on two key observations. First, not all EMBs are equal, nor all rows within an EMB are equal in terms of access patterns. EMBs exhibit distinct memory characteristics, providing performance

Pavel B. Dubovski, Jeffrey A. Slepoi

In this paper we consider fractional quasi-Bessel equations $$\sum_{i=1}^{m}d_i x^{\alpha_i+p_i}D^{\alpha_i} u(x) + (x^\beta - \nu^2)u(x)=0$$ and construct their existence and uniqueness theory in the class of fractional series. Our methodology allows us to obtain new results for a broad class of fractional differential equations including Cauchy-Euler and c

Roufeh Asghari, Amin Hassan Zadeh

In this paper, the recurrent events that can occur more than one over the follow-up time have been modeled by phase-type distributions. We use the finite-state continuous-time Markov process with multi states for patients with recurrent events. The number of recurrences until time $t$, the time stay for every state and the time till death are of importances.

Yuchang Sun, Jiawei Shao, Songze Li, Yuyi Mao

Federated learning (FL) has attracted much attention as a privacy-preserving distributed machine learning framework, where many clients collaboratively train a machine learning model by exchanging model updates with a parameter server instead of sharing their raw data. Nevertheless, FL training suffers from slow convergence and unstable performance due to st

Tianling Jin, Jingang Xiong

We prove global H\"older gradient estimates for bounded positive weak solutions of fast diffusion equations in smooth bounded domains with the homogeneous Dirichlet boundary condition, which then lead us to establish their optimal global regularity. This solves a problem raised by Berryman and Holland in 1980.

Mamdouh Alenezi

Software measurement is an essential management tool to develop robust and maintainable software systems. Software metrics can be used to control the inherent complexities in software design. To guarantee that the components of the software are inevitably testable, the testability attribute is used, which is a sub-characteristics of the software's maintabili

Juan-Juan Hao, Ming Zhang, Xian-Xin Wu, Fan Yang

We study the pairing symmetry and the topological properties of the hydrogen-doped ACr$_3$As$_3$ superconductors. Based on our first-principle band structure with spin-orbit-coupling (SOC), we construct tight binding model including the on-site SOC terms, equipped with the multi-orbital Hubbard interactions. Then using the random-phase-approximation (RPA) ap

Xiao-Cheng Bai, Wen-Feng Wu, Han-Yu Wang, Ya-Min Quan

Recently synthesized Kagome compounds AV$_3$Sb$_5$ attract great attention due to the unusual coexistence of the topology, charge density wave and superconductivity. In this {\it Letter}, based on the band structures for CsV$_3$Sb$_5$ in pristine phase, we fit an effective 6-band model for the low-energy processes; utilizing the random phase approximation (R

Shane Walsh, Alex Frost, William Anderson, Toby Digney

Free-space communications at optical wavelengths offers the potential for orders-of-magnitude improvement in data rates over conventional radio wavelengths, and this will be needed to meet the demand of future space-to-ground applications. Supporting this new paradigm necessitates a global network of optical ground stations. This paper describes the architec

Quan-Lin Li, Yan-Xia Chang, Chi Zhang

It is interesting but difficult and challenging to study Ethereum with multiple mining pools. One of the main difficulties comes from not only how to represent such a general tree with multiple block branches (or sub-chains) related to the multiple mining pools, but also how to analyze a multi-dimensional stochastic system due to the mining competition among

Feng Wu

In this work, we investigate a theory of linear Weyl gravity coupled to a scalar field and study the scenario in which Lorentz symmetry is broken by a non-vanishing vacuum expectation value of the Weyl field in the flat space limit after Weyl symmetry breaking. We show that a $CPT$-odd Lorentz-violating interaction is generated after symmetry breaking. Featu

Andrew Sosanya, Sam Greydanus

Understanding natural symmetries is key to making sense of our complex and ever-changing world. Recent work has shown that neural networks can learn such symmetries directly from data using Hamiltonian Neural Networks (HNNs). But HNNs struggle when trained on datasets where energy is not conserved. In this paper, we ask whether it is possible to identify and

Xiangyu He, Jian Cheng

Super-resolution as an ill-posed problem has many high-resolution candidates for a low-resolution input. However, the popular $\ell_1$ loss used to best fit the given HR image fails to consider this fundamental property of non-uniqueness in image restoration. In this work, we fix the missing piece in $\ell_1$ loss by formulating super-resolution with neural

Peng Wang, Zihuai Lin, Xucun Yan, Zijiao Chen

Cardiovascular disease has become one of the most significant threats endangering human life and health. Recently, Electrocardiogram (ECG) monitoring has been transformed into remote cardiac monitoring by Holter surveillance. However, the widely used Holter can bring a great deal of discomfort and inconvenience to the individuals who carry them. We developed

Dorsa Fathollahi, Marco Mondelli

We consider the problem of coded distributed computing using polar codes. The average execution time of a coded computing system is related to the error probability for transmission over the binary erasure channel in recent work by Soleymani, Jamali and Mahdavifar, where the performance of binary linear codes is investigated. In this paper, we focus on polar

Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Peide Huang

In this paper, we focus on a new method of data augmentation to solve the data imbalance problem within imbalanced ECG datasets to improve the robustness and accuracy of heart disease detection. By using Optimal Transport, we augment the ECG disease data from normal ECG beats to balance the data among different categories. We build a Multi-Feature Transforme

Blake Wulfe, Ashwin Balakrishna, Logan Ellis, Jean Mercat

The ability to learn reward functions plays an important role in enabling the deployment of intelligent agents in the real world. However, comparing reward functions, for example as a means of evaluating reward learning methods, presents a challenge. Reward functions are typically compared by considering the behavior of optimized policies, but this approach

Michele Peruzzi, David B. Dunson

Quantifying spatial and/or temporal associations in multivariate geolocated data of different types is achievable via spatial random effects in a Bayesian hierarchical model, but severe computational bottlenecks arise when spatial dependence is encoded as a latent Gaussian process (GP) in the increasingly common large scale data settings on which we focus. T

Jianwei Xu, Ran Zhao, Yizhou Yu, Qingwei Zhang

Automatic detection of polyps is challenging because different polyps vary greatly, while the changes between polyps and their analogues are small. The state-of-the-art methods are based on convolutional neural networks (CNNs). However, they may fail due to lack of training data, resulting in high rates of missed detection and false positives (FPs). In order

S. Wang, J. I. Katz

The radiation of a Fast Radio Burst (FRB) reflects from the Moon and Sun. If a reflection is detected, the time interval between the direct and reflected signals constrains the source to a narrow arc on the sky. If both Lunar and Solar reflections are detected these two arcs intersect, narrowly confining the source location on the sky. A previous paper calcu

Peng-Hui Chen, Fei Niu, Xin-Xing Xu, Zu-Xing Yang

Within the framework of the dinuclear system model, the reaction mechanisms for synthesizing target-like isotopes from Bk to compound nuclei Lv are thoroughly investigated in complete and incomplete fusion reaction of $^{48}$Ca +$^{248}$Cm around Coulomb barrier energies. Production cross-section of $^{292,293}$Lv as a function of excitation energy in fusion

Daniel A. Torres-Ballesteros, Leonardo Castañeda

In this work we present relensing, a package written in python whose goal is to model galaxy clusters from gravitational lensing. With relensing we extend the amount of software available, which provides the scientific community with a wide range of models that help to compare and therefore validate the physical results that rely on them. We implement a free

Simon Niklaus, Ping Hu, Jiawen Chen

Frame interpolation is an essential video processing technique that adjusts the temporal resolution of an image sequence. While deep learning has brought great improvements to the area of video frame interpolation, techniques that make use of neural networks can typically not easily be deployed in practical applications like a video editor since they are eit

Yang Zhang, Fei Xue, Bo Wang, Jia-Mian Hu

The coexistence of different ferroelectric phases enables the tunability of the macroscopic properties and extensive applications from piezoelectric transducers to nonvolatile memories. Here we develop a thermodynamic model to predict the stability and low-energy orientations of boundaries between different phases in ferroelectrics. Taking lead zirconate tit

Thuong Nguyen

In this paper, we construct a robust adaptive central-upwind scheme on unstructured triangular grids for two-dimensional shallow water equations with variable density. The method is well-balanced, positivity-preserving, and oscillation-free at the curve where two types of fluid merge. The proposed approach is an extension of the adaptive well-balanced, posit

Ziang Chen, Jianfeng Lu, Yulong Lu, Shengxuan Zhou

Spectral Barron spaces have received considerable interest recently as it is the natural function space for approximation theory of two-layer neural networks with a dimension-free convergence rate. In this paper we study the regularity of solutions to the whole-space static Schr\"odinger equation in spectral Barron spaces. We prove that if the source of the

Yang Liu, Liu Yang, Yu-Xin Xie

We study the initiation and evolution of aneurysmal morphology in a pressurized soft tube where the elastic modulus is non-uniform in the radial direction. The primary deformation prior to instability is characterized within the framework of nonlinear elasticity for a general material constitution and a generic modulus gradient. To unravel the influence of m

Yihuan Mao, Chao Wang, Bin Wang, Chongjie Zhang

With the success of offline reinforcement learning (RL), offline trained RL policies have the potential to be further improved when deployed online. A smooth transfer of the policy matters in safe real-world deployment. Besides, fast adaptation of the policy plays a vital role in practical online performance improvement. To tackle these challenges, we propos

Daokun Zhang, Jie Yin, Philip S. Yu

Link prediction aims to infer the link existence between pairs of nodes in networks/graphs. Despite their wide application, the success of traditional link prediction algorithms is hindered by three major challenges -- link sparsity, node attribute noise and dynamic changes -- that are faced by many real-world networks. To address these challenges, we propos

Jinlian Hu, Huaqiang Li, Rong Song, Jingxu Bai

We demonstrate a continuous frequency electric field measurement based on the far off-resonant AC stark effect in a Rydberg atomic vapor cell. In this configuration, a strong far off-resonant field, denoted as a local oscillator (LO) field, acts as a gain shifting the Rydberg level to a high sensitivity region. An incident weak signal field with a few hundre

Nikos Sioulas, Marco Velli, Rohit Chhiber, Loukas Vlahos

We use data from the first six encounters of Parker Solar Probe and employ the Partial Variance of Increments ($PVI$) method to study the statistical properties of coherent structures in the inner heliosphere with the aim of exploring physical connections between magnetic field intermittency and observable consequences such as plasma heating and turbulence d

Angelina McMillan-Major, Zaid Alyafeai, Stella Biderman, Kimbo Chen

In recent years, large-scale data collection efforts have prioritized the amount of data collected in order to improve the modeling capabilities of large language models. This prioritization, however, has resulted in concerns with respect to the rights of data subjects represented in data collections, particularly when considering the difficulty in interroga

Yukio Kajihara, Masanori Inui, Kazuhiro Matsuda, Koji Ohara

We performed small-angle X-ray scattering measurements of liquid Te using a synchrotron radiation facility and observed the maximum scattering intensity near 620 K in the supercooled region (melting temperature 723 K). This result is an experimental observation of the ridge line of the critical density fluctuation associated with the liquid-liquid phase tran

Daniel Dalthorp, Manuela Huso, Mark Dalthorp, Jeff Mintz

In estimating bird and bat mortality at wind turbines, it is essential to account for carcasses that lie outside the searched area. In this manuscript we explore some of the difficulties and nuances involved in the spatial prediction of the number of carcasses that lie outside the searched area and provide extensive guidance and documentation for a new R pac

Xufei Wang, Bo Jiang, Jun S. Liu

The varying coefficient model has received broad attention from researchers as it is a powerful dimension reduction tool for non-parametric modeling. Most existing varying coefficient models fitted with polynomial spline assume equidistant knots and take the number of knots as the hyperparameter. However, imposing equidistant knots appears to be too rigid, a

Syed Ansari, Amit Acharya, Alankar Alankar

A continuum grain boundary model is developed that uses experimentally measured grain boundary energy data as a function of misorientation to simulate idealized grain boundary evolution in a 1-D grain array. The model uses a continuum representation of the misorientation in terms of spatial gradients of the orientation as a fundamental field. The grain bound

Sean Hon, Po Yin Fung, Jiamei Dong, Stefano Serra-Capizzano

In this work, we propose a simple yet generic preconditioned Krylov subspace method for a large class of nonsymmetric block Toeplitz all-at-once systems arising from discretizing evolutionary partial differential equations. Namely, our main result is to propose two novel symmetric positive definite preconditioners, which can be efficiently diagonalized by th

Xinhang Li, Yong Zhang, Chunxiao Xing

Entity alignment aims at integrating heterogeneous knowledge from different knowledge graphs. Recent studies employ embedding-based methods by first learning the representation of Knowledge Graphs and then performing entity alignment via measuring the similarity between entity embeddings. However, they failed to make good use of the relation semantic informa

Zijiao Chen, Zihuai Lin, Peng Wang, Ming Ding

With recently successful applications of deep learning in computer vision and general signal processing, deep learning has shown many unique advantages in medical signal processing. However, data labelling quality has become one of the most significant issues for AI applications, especially when it requires domain knowledge (e.g. medical image labelling). In

Mansooreh Montazerin, Soheil Zabihi, Elahe Rahimian, Arash Mohammadi

Recently, there has been a surge of significant interest on application of Deep Learning (DL) models to autonomously perform hand gesture recognition using surface Electromyogram (sEMG) signals. DL models are, however, mainly designed to be applied on sparse sEMG signals. Furthermore, due to their complex structure, typically, we are faced with memory constr

Marcel Nutz, Johannes Wiesel

We study the stability of entropically regularized optimal transport with respect to the marginals. Given marginals converging weakly, we establish a strong convergence for the Schr\"odinger potentials describing the density of the optimal couplings. When the marginals converge in total variation, the optimal couplings also converge in total variation. This

Simon L. Grimm, Joachim G. Stadel, Ramon Brasser, Matthias M. M. Meier

We present recent updates and improvements of the graphical processing unit (GPU) N-body code GENGA. Modern state-of-the-art simulations of planet formation require the use of a very high number of particles to accurately resolve planetary growth and to quantify the effect of dynamical friction. At present the practical upper limit is in the range of 30,000

Arman Sharififar, Parastoo Sadeghi, Neda Aboutorab

It has been known that the insufficiency of linear coding in achieving the optimal rate of the general index coding problem is rooted in its rate's dependency on the field size. However, this dependency has been described only through the two well-known matroid instances, namely the Fano and non-Fano matroids, which, in turn, limits its scope only to the fie

Oluwaseyi Onasami, Damilola Adesina, Lijun Qian

With the recent increase in the number of underwater activities, having effective underwater communication systems has become increasingly important. Underwater acoustic communication has been widely used but greatly impaired due to the complicated nature of the underwater environment. In a bid to better understand the underwater acoustic channel so as to he

Zayd Hammoudeh, Daniel Lowd

Targeted training-set attacks inject malicious instances into the training set to cause a trained model to mislabel one or more specific test instances. This work proposes the task of target identification, which determines whether a specific test instance is the target of a training-set attack. Target identification can be combined with adversarial-instance

N. V. Krylov

For solutions of a certain class of SPDEs in divergence form we present some estimates of their $L_{p}$-norms and the $L_{p}$-norms of their first-order derivatives. The main novelty is that the low-order coefficients are supposed to belong to certain Morrey classes instead of $L_{p}$-spaces. Our results are new even if there are no stochastic terms in the e

Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice

We study the problem of learning, from observational data, fair and interpretable policies that effectively match heterogeneous individuals to scarce resources of different types. We model this problem as a multi-class multi-server queuing system where both individuals and resources arrive stochastically over time. Each individual, upon arrival, is assigned

Abraham Chien, Lan Gao, Shu Zhang, Hantao Ji

Magnetic reconnection is a ubiquitous astrophysical process that rapidly converts magnetic energy into some combination of plasma flow energy, thermal energy, and non-thermal energetic particles, including energetic electrons. Various reconnection acceleration mechanisms in different low-$\beta$ (plasma-to-magnetic pressure ratio) and collisionless environme

Xiaobing Sun, Wenjie Feng, Shenghua Liu, Yuyang Xie

Given a stream of money transactions between accounts in a bank, how can we accurately detect money laundering agent accounts and suspected behaviors in real-time? Money laundering agents try to hide the origin of illegally obtained money by dispersive multiple small transactions and evade detection by smart strategies. Therefore, it is challenging to accura

Fanqing Liu, Jianfu Yang, Xiaohui Yu

In this paper, we investigate the existence of multiple solutions to the following multi-critical elliptic problem \begin{equation}\label{eq:0.1} \left\{\begin{aligned} -\Delta u & =\lambda |u|^{p-2}u +\sum_{i=1}^k(|x|^{-(N-\alpha_i)}*|u|^{2^*_i})|u|^{2^*_i-2}u\quad {\rm in}\quad \Omega,\\ &u\in H^1_0(\Omega)\\ \end{aligned}\right. \end{equation} in connecti

Yuxuan Wang, Jinyao Xie, Jiongzhi Zheng, Kun He

The Partitioning Min-Max Weighted Matching (PMMWM) problem is an NP-hard problem that combines the problem of partitioning a group of vertices of a bipartite graph into disjoint subsets with limited size and the classical Min-Max Weighted Matching (MMWM) problem. Kress et al. proposed this problem in 2015 and they also provided several algorithms, among whic

S. Redner

These notes are based on the lectures that I gave (virtually) at the Bruneck Summer School in 2021 on first-passage processes and some applications of the basic theory. I begin by defining what is a first-passage process and presenting the connection between the first-passage probability and the familiar occupation probability. Some basic features of first p

Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson

As facial recognition systems are deployed more widely, scholars and activists have studied their biases and harms. Audits are commonly used to accomplish this and compare the algorithmic facial recognition systems' performance against datasets with various metadata labels about the subjects of the images. Seminal works have found discrepancies in performanc

K. R. Rajagopal, Casey Rodriguez

We formulate and consider the problem of an inextensible, unshearable, viscoelastic rod, with evolving natural configuration, moving on a plane. We prove that the dynamic equations describing quasistatic motion of an Eulerian strut, an infinite dimensional dynamical system, are globally well-posed. For every value of the terminal thrust, these equations cont

Dipin S. Pillai, Jason R. Picardo, R. Narayanan

A consistent averaging technique, using the weighted residual integral boundary layer (WRIBL) method, is presented for flow through a thin-gap geometry wherein the fluid's viscosity varies across the gap. In such situations, the flow has a non-parabolic cross-gap velocity profile -- an effect that is ignored by Darcy models conventionally used for such Hele-

Sheng-Li Qin, Tie Liu, Xunchuan Liu, Paul F. Goldsmith

Hot cores characterized by rich lines of complex organic molecules are considered as ideal sites for investigating the physical and chemical environments of massive star formation. We present a search for hot cores by using typical nitrogen- and oxygen-bearing complex organic molecules (C$_2$H$_5$CN, CH$_3$OCHO and CH$_3$OH), based on ALMA Three-millimeter O

Lin Zhu, Xiao Wang, Yi Chang, Jianing Li

Neuromorphic vision sensor is a new bio-inspired imaging paradigm that reports asynchronous, continuously per-pixel brightness changes called `events' with high temporal resolution and high dynamic range. So far, the event-based image reconstruction methods are based on artificial neural networks (ANN) or hand-crafted spatiotemporal smoothing techniques. In

Li Ma, Yin Xia, Lexin Li

Two-sample multiple testing problems of sparse spatial data are frequently arising in a variety of scientific applications. In this article, we develop a novel neighborhood-assisted and posterior-adjusted (NAPA) approach to incorporate both the spatial smoothness and sparsity type side information to improve the power of the test while controlling the false

Likun Sui, Zihuai Lin, Pei Xiao, H. Vincent Poor

This paper analyzes the maximal achievable rate for a given blocklength and error probability over a multiple-antenna ambient backscatter channel with perfect channel state information at the receiver. The result consists of a finite blocklength channel coding achievability bound and a converse bound based on the Neyman-Pearson test and the normal approximat

Ao Xu, Hua-Lin Wu, Heng-Dong Xi

We present a numerical study of training a self-propelling agent to migrate in the unsteady flow environment. We control the agent to utilize the background flow structure by adopting the reinforcement learning algorithm to minimize energy consumption. We considered the agent migrating in two types of flows: one is simple periodical double-gyre flow as a pro

Jose R. Alonso, Daniel Winklehner, Joshua Spitz, Janet M. Conrad

IsoDAR@Yemilab is a novel isotope-decay-at-rest experiment that has preliminary approval to run at the Yemi underground laboratory (Yemilab) in Jeongseon-gun, South Korea. In this technical report, we describe in detail the considerations for installing this compact particle accelerator and neutrino target system at the Yemilab underground facility. Specific

Ying Chen, Yuhang Yin, Ze-Huan Zheng, Yang Liu

Disclinations are ubiquitous lattice defects existing in almost all crystalline materials. In two-dimensional nanomaterials, disclinations lead to the warping and deformation of the hosting material, yielding non-Euclidean geometries. However, such geometries have never been investigated experimentally in the context of topological phenomena. Here, by creati

Dongkyu Lim

Araci et al. introduced a $p$-adic $(\rho,q)$-analogue of the Haar distribution. By means of the distribution, they constructed the $p$-adic $(\rho,q)$-Volkenborn integral. In this paper, by virtue of the Mahler expansion of continuous functions, the author gives the Radon-Nikodym theorem with respect to the $p$-adic $(\rho,q)$-distribution on $\Bbb Z_p$.

L. E. Chow, S. Kunniniyil Sudheesh, Z. Y. Luo, P. Nandi

The superconducting infinite-layer nickelate family has risen as a promising platform for revealing the mechanism of high-temperature superconductivity. However, its challenging material synthesis has obscured effort in understanding the nature of its ground state and low-lying excitations, which is a prerequisite for identifying the origin of the Cooper pai

Steve Huntsman

Promoting and maintaining diversity of candidate solutions is a key requirement of evolutionary algorithms in general and multi-objective evolutionary algorithms in particular. In this paper, we use the recently developed theory of magnitude to construct a gradient flow and similar notions that systematically manipulate finite subsets of Euclidean space to e

Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng

Technology companies have been leading the way to a renewable energy transformation, by investing in renewable energy sources to reduce the carbon footprint of their datacenters. In addition to helping build new solar and wind farms, companies make power purchase agreements or purchase carbon offsets, rather than relying on renewable energy every hour of the

Alexander Thebelt, Johannes Wiebe, Jan Kronqvist, Calvin Tsay

It is well-documented how artificial intelligence can have (and already is having) a big impact on chemical engineering. But classical machine learning approaches may be weak for many chemical engineering applications. This review discusses how challenging data characteristics arise in chemical engineering applications. We identify four characteristics of da

Dongrui Liu, Chuanchuan Chen, Changqing Xu, Robert Qiu

As a fundamental yet challenging problem in intelligent transportation systems, point cloud registration attracts vast attention and has been attained with various deep learning-based algorithms. The unsupervised registration algorithms take advantage of deep neural network-enabled novel representation learning while requiring no human annotations, making th

Kyoung-Seog Lee, Han-Bom Moon

We show that the derived category of a curve is embedded into the derived category of the moduli space of vector bundles on the curve of coprime rank and degree. We also generalize the semiorthogonal decomposition constructed by Narasimhan and Belmans-Mukhopadhyay. Finally, we produce a one-dimensional family of ACM bundles over the moduli space.

Arian Ahmadi, Omid Semiari, Mehdi Bennis, Merouane Debbah

Multi-access edge computing (MEC) is viewed as an integral part of future wireless networks to support new applications with stringent service reliability and latency requirements. However, guaranteeing ultra-reliable and low-latency MEC (URLL MEC) is very challenging due to uncertainties of wireless links, limited communications and computing resources, as

Geunsu Choi, Han Ju Lee

We study the denseness of Crawford number attaining operators on Banach spaces. Mainly, we prove that if a Banach space has the RNP, then the set of Crawford number attaining operators is dense in the space of bounded linear operators. We also see among others that the set of Crawford number attaining operators may be dense in the space of all bounded linear

Letong Hong

Motivated by the pop-stack-sorting map on the symmetric groups, Defant defined an operator $\mathsf{Pop}_M : M \to M$ for each complete meet-semilattice $M$ by $$\mathsf{Pop}_M(x)=\bigwedge(\{y\in M: y\lessdot x\}\cup \{x\}).$$ This paper concerns the dynamics of $\mathsf{Pop}_{\mathrm{Tam}_n}$, where $\mathrm{Tam}_n$ is the $n$-th Tamari lattice. We say an

Santhosh Kumar Ramakrishnan, Devendra Singh Chaplot, Ziad Al-Halah, Jitendra Malik

State-of-the-art approaches to ObjectGoal navigation rely on reinforcement learning and typically require significant computational resources and time for learning. We propose Potential functions for ObjectGoal Navigation with Interaction-free learning (PONI), a modular approach that disentangles the skills of `where to look?' for an object and `how to navig

Arkka Bhattacharyya, Shivam Sharma, Fikadu Alema, Praneeth Ranga

Field-plated (FP) depletion-mode MOVPE-grown $\beta$-Ga$_2$O$_3$ lateral MESFETs are realized with superior reverse breakdown voltages and ON currents. A sandwiched SiN$_x$ dielectric field plate design was utilized that prevents etching-related damage in the active region and a deep mesa-etching was used to reduce reverse leakage. The device with L$_{GD}$ =

Saikumar R. Yeddula, Juan Guzmán-Iñigo, Aimee S. Morgans

The unsteady response of nozzles with steady heat transfer forced by acoustic and/or entropy waves is modelled. The approach is based on the quasi-one-dimensional linearised Euler equations. The equations are cast in terms of three variables, namely the dimensionless mass, stagnation temperature and entropy fluctuations, which are invariants of the system at

Miroslav D. Filipović, J. L. Payne, R. Z. E. Alsaberi, R. P. Norris

We report the discovery of J0624-6948, a low-surface brightness radio ring, lying between the Galactic Plane and the Large Magellanic Cloud (LMC). It was first detected at 888 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP), and with a diameter of ~196 arcsec. This source has phenomenological similarities to Odd Radio Circles (ORCs). Signif

Jun Hu, Shixuan Wang

This paper studies the seminormal bases $\{f_{\mathfrak{s}\mathfrak{t}}\}$ and the dual seminormal bases $\{g_{\mathfrak{s}\mathfrak{t}}\}$ of the non-degenerate and the degenerate cyclotomic Hecke algebras ${H}_{\ell,n}$ of type $G(\ell,1,n)$. We present some explicit formulae for the constants $\alpha_{\mathfrak{s}\mathfrak{t}}:=g_{\mathfrak{s}\mathfrak{t}

Mu Gao, Mark Coletti, Russell B. Davidson, Ryan Prout

Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic resolution in some cases, and with accelerators like GPUs and TPUs making inference using large models rapid, fast genome-level structure pr

A. M. A. Alsnayyan, L. Kempel, B. Shanker

The analysis of electromagnetic scattering in the isogeometric analysis (IGA) framework based on Loop subdivision has long been restricted to simply-connected geometries. The inability to analyze multiply-connected objects is a glaring omission. In this paper, we address this challenge. IGA provides seamless integration between the geometry and analysis by u

K. L. Ngai

An advance was made by Guiselin et al. [arXiv:2103.01569 (2021)] in molecular dynamics simulations of the equilibrium dynamics of supercooled liquids near the experimental glass transition by utilizing the giant equilibration speedup provided by the swap Monte Carlo algorithm. The found emergence of a power law in relaxation spectra at lower temperatures on

Lei Lan, Danny M. Kaufman, Minchen Li, Chenfanfu Jiang

Simulating stiff materials in applications where deformations are either not significant or can safely be ignored is a pivotal task across fields. Rigid body modeling has thus long remained a fundamental tool and is, by far, the most popular simulation strategy currently employed for modeling stiff solids. At the same time, numerical models of a rigid body c

B. M. Henson, K. F. Thomas, Z. Mehdi, T. G. Burnett

We describe a novel method of single-shot trap frequency measurement for a confined Bose-Einstein Condensate, which uses an atom laser to repeatedly sample the mean velocity of trap oscillations as a function of time. The method is able to determine the trap frequency to an accuracy of 39~ppm (16~mHz) in a single experimental realization, improving on the li

Erik A. Petigura, James G. Rogers, Howard Isaacson, James E. Owen

In 2017, the California-Kepler Survey (CKS) published its first data release (DR1) of high-resolution optical spectra of 1305 planet hosts. Refined CKS planet radii revealed that small planets are bifurcated into two distinct populations: super-Earths (smaller than 1.5 $R_E$) and sub-Neptunes (between 2.0 and 4.0 $R_E$), with few planets in between (the "Rad

Giuseppe Negro, Claudio Basilio Caporusso, Pasquale Digregorio, Giuseppe Gonnella

We study numerically the role of hydrodynamics in the liquid-hexatic transition of active colloids at intermediate activity, where motility induced phase separation (MIPS) does not occur. We show that in the case of active Brownian particles (ABP), the critical density of the transition decreases upon increasing the particle's mass, enhancing ordering, while

Thomas Schmidt, Maria-Rosa L. Cioni, Florian Niederhofer, Kenji Bekki

The Large Magellanic Cloud (LMC) is the most luminous satellite galaxy of the Milky Way and owing to its companion, the Small Magellanic Cloud (SMC), represents an excellent laboratory to study the interaction of dwarf galaxies. The aim of this study is to investigate the kinematics of the outer regions of the LMC by using stellar proper motions to understan

Yankai Lin, Iman Shames, Dragan Nešić

This paper considers the problem of online optimization where the objective function is time-varying. In particular, we extend coordinate descent type algorithms to the online case, where the objective function varies after a finite number of iterations of the algorithm. Instead of solving the problem exactly at each time step, we only apply a finite number

H. Jayatissa, M. L. Avila, K. E. Rehm, R. Talwar

Understanding the explosion mechanism of a core-collapse supernova (CCSN) is important to accurately model CCSN scenarios for different progenitor stars using model-observation comparisons. The uncertainties of various nuclear reaction rates relevant for CCSN scenarios strongly affect the accuracy of these stellar models. Out of these reactions, the $^{13}$N

Reza Maalek, Shahrokh Maalek

Advancements in optical metrology has enabled documentation of dense 3D point clouds of cultural heritage sites. For large scale and continuous digital documentation, processing of dense 3D point clouds becomes computationally cumbersome, and often requires additional hardware for data management, increasing the time cost, and complexity of projects. To this

Hanchen Wang, Ying Zhang, Lu Qin, Wei Wang

Subgraph matching is a fundamental problem in various fields that use graph structured data. Subgraph matching algorithms enumerate all isomorphic embeddings of a query graph q in a data graph G. An important branch of matching algorithms exploit the backtracking search approach which recursively extends intermediate results following a matching order of que

Oscar López, Daniel M. Dunlavy, Richard B. Lehoucq

We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts a

Omkar B. Shende, Ali Mani

Algebraic closure models with spatially nonlocal operators that are associated with both unresolved advective transport and nonlinear reaction terms in a Reynolds-averaged Navier-Stokes context are presented in this work. In particular, a system of two species subject to binary reaction and transport by advection and diffusion are examined by expanding upon

Noah Abou El Wafa, André Platzer

This paper investigates first-order game logic and first-order modal mu-calculus, which extend their propositional modal logic counterparts with first-order modalities of interpreted effects such as variable assignments. Unlike in the propositional case, both logics are shown to have the same expressive power and their proof calculi to have the same deductiv

Argyrios Deligkas, John Fearnley, Alexandros Hollender, Themistoklis Melissourgos

In the $\varepsilon$-Consensus-Halving problem, we are given $n$ probability measures $v_1, \dots, v_n$ on the interval $R = [0,1]$, and the goal is to partition $R$ into two parts $R^+$ and $R^-$ using at most $n$ cuts, so that $|v_i(R^+) - v_i(R^-)| \leq \varepsilon$ for all $i$. This fundamental fair division problem was the first natural problem shown to