January 2022 arXiv papers — page 74

Zach Degnan, Xin He, Alejandro Gomez Frieiro, Yauhen P. Sachkou

Substrate material imperfections and surface losses are one of the major factors limiting superconducting quantum circuitry from reaching the scale and complexity required to build a practicable quantum computer. One potential path towards higher coherence of superconducting quantum devices is to explore new substrate materials with a reduced density of impe

Yiding Wang, Decang Sun, Kai Chen, Fan Lai

Training deep neural networks (DNNs) is time-consuming. While most existing solutions try to overlap/schedule computation and communication for efficient training, this paper goes one step further by skipping computing and communication through DNN layer freezing. Our key insight is that the training progress of internal DNN layers differs significantly, and

Arnaud Plessis

Let $\Gamma\subset \bar{\mathbb{Q}}^*$ be a finitely generated subgroup. Denote by $\Gamma_\mathrm{div}$ its division group. A recent conjecture due to R\'emond, related to the Zilber-Pink conjecture, predicts that the absolute logarithmic Weil height of an element of $\mathbb{Q}(\Gamma_\mathrm{div})^*\backslash \Gamma_{\mathrm{div}}$ is bounded from below b

Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao

Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without seed alignments. The current SOTA self-supervised EA method draws inspiration from contrastive learning, originally designed in computer vision based on instance discrimination and contrastive loss, and suffers from two shortcomings. Firstly

Quanzhen Wan

The elemental image array (EIA) for light field display, especially integral imaging light field display, was reliant on a virtual camera array, novel sampling algorithms, high-performance hardware or corresponding complex algorithms, which hinder its application. Without sacrificing accuracy and precision, we innovate a novel algorithm set to achieve video-

P. Mitra

The axion particle may or may not exist, but the axion field can be used, as shown here, in an explicitly local formulation of a chiral U(1) gauge theory with both classical and quantum gauge invariance. Nonabelian analogues of axion fields, which have recently been introduced, can be used, together with their special symmetries, in a similar construction of

Hossein Khaleghy, Iman Izadi

Industrial alarm systems have recently progressed considerably in terms of network complexity and the number of alarms. The increase in complexity and number of alarms presents challenges in these systems that decrease system efficiency and cause distrust of the operator, which might result in widespread damages. One contributing factor in alarm inefficiency

Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai

Conversational Recommendation Systems (CRSs) have recently started to leverage pretrained language models (LM) such as BERT for their ability to semantically interpret a wide range of preference statement variations. However, pretrained LMs are well-known to be prone to intrinsic biases in their training data, which may be exacerbated by biases embedded in d

Changwook Jun, Jooyoung Choi, Myoseop Sim, Hyun Kim

Existing question answering systems mainly focus on dealing with text data. However, much of the data produced daily is stored in the form of tables that can be found in documents and relational databases, or on the web. To solve the task of question answering over tables, there exist many datasets for table question answering written in English, but few Kor

Yuta Yahagi, Daisuke Miura, Akimasa Sakuma

Spin currents in ferromagnets afford diverse functionalities. We evaluate the extrinsic spin Hall effects of magnetic impurity scattering in ferromagnetic metals. We show that spin-dependent scattering can provide a high spin current polarized perpendicularly to the magnetization direction and is a dominant mechanism in the moderate-conductivity regime. We f

Zuolin Liu, Hongbin Fang, Jian Xu, Kon-Well Wang

Transitions of multistability in structures have been exploited for various functions and applications, such as spectral gap tuning, impact energy trapping, and wave steering. However, a fundamental and comprehensive understanding of the transitions, either quasi-static or dynamic transitions, has not yet been acquired, especially in terms of the sequence pr

Sameer Aqib Hashmi

Face detection in unrestricted conditions has been a trouble for years due to various expressions, brightness, and coloration fringing. Recent studies show that deep learning knowledge of strategies can acquire spectacular performance inside the identification of different gadgets and patterns. This face detection in unconstrained surroundings is difficult d

Yuqiao Wen, Guoqing Luo, Lili Mou

Open-domain dialogue systems aim to converse with humans through text, and dialogue research has heavily relied on benchmark datasets. In this work, we observe the overlapping problem in DailyDialog and OpenSubtitles, two popular open-domain dialogue benchmark datasets. Our systematic analysis then shows that such overlapping can be exploited to obtain fake

A. M. Kamchatnov

Equations for contour dynamics of dark solitons are obtained for the general form of the nonlinearity function. Their self-similar solution which describes the nonlinear stage of the bending instability of dark solitons is studied in detail.

Lucas Gamertsfelder

In the first part of the paper, we consider a discrete-time stochastic control system. We show that, under certain conditions, the set of random occupational measures generated by the state-control trajectories of the system as well as the set of their mathematical expectations converge (as the time horizon tends to infinity) to a convex and compact (non-ran

Xijun Li, Qingyu Qu, Fangzhou Zhu, Jia Zeng

It has been verified that the linear programming (LP) is able to formulate many real-life optimization problems, which can obtain the optimum by resorting to corresponding solvers such as OptVerse, Gurobi and CPLEX. In the past decades, a serial of traditional operation research algorithms have been proposed to obtain the optimum of a given LP in a fewer sol

Alexander K. Y. Tam, Matthew J. Simpson

The Fisher-Stefan model involves solving the Fisher-KPP equation on a domain whose boundary evolves according to a Stefan-like condition. The Fisher-Stefan model alleviates two practical limitations of the standard Fisher-KPP model when applied to biological invasion. First, unlike the Fisher-KPP equation, solutions to the Fisher-Stefan model have compact su

Anuj Kumar

This paper is concerned with the optimal upper bound on mean quantities (torque, dissipation and the Nusselt number) obtained in the framework of the background method for the Taylor--Couette flow with a stationary outer cylinder. Along the way, we perform the energy stability analysis of the laminar flow, and demonstrate that below radius ratio 0.0556, the

Qingyu Qu, Xijun Li, Yunfan Zhou, Jia Zeng

Most combinatorial optimization problems can be formulated as mixed integer linear programming (MILP), in which branch-and-bound (B\&B) is a general and widely used method. Recently, learning to branch has become a hot research topic in the intersection of machine learning and combinatorial optimization. In this paper, we propose a novel reinforcement learni

Zihan Liu, Jingwen Leng, Zhihui Zhang, Quan Chen

Deep learning (DL) models have achieved great success in many application domains. As such, many industrial companies such as Google and Facebook have acknowledged the importance of multi-tenant DL services. Although the multi-tenant service has been studied in conventional workloads, it is not been deeply studied on deep learning service, especially on gene

Daniel J. George, Yuval R. Sanders, Mohsen Bagherimehrab, Barry C. Sanders

Quantum field theory (QFT) describes nature using continuous fields, but physical properties of QFT are usually revealed in terms of measurements of observables at a finite resolution. We describe a multiscale representation of a free scalar bosonic and Ising model fermionic QFTs using wavelets. Making use of the orthogonality and self similarity of the wave

Wrik Mallik, Neil Farvolden, Jasmin Jelovica, Rajeev K. Jaiman

This article presents a reduced-order modeling methodology via deep convolutional neural networks (CNNs) for shape optimization applications. The CNN provides a nonlinear mapping between the shapes and their associated attributes while conserving the equivariance of these attributes to the shape translations. To implicitly represent complex shapes via a CNN-

Urmila Shrawankar

Traditionally, adaptive filters have been deployed to achieve AEC by estimating the acoustic echo response using algorithms such as the Normalized Least-Mean-Square (NLMS) algorithm. Several approaches have been proposed over recent years to improve the performance of the standard NLMS algorithm in various ways for AEC. These include algorithms based on Time

Tatsuki Sonoyama, Warit Asavanant, Kosuke Fukui, Mamoru Endo

Quantum state preparation is important for quantum information processing. In particular, in optical quantum computing with continuous variables, non-Gaussian states are needed for universal operation and error correction. Optical non-Gaussian states are usually generated by heralding schemes using photon detectors. In previous experiments, the temporal reso

Arjun R Akula, Song-Chun Zhu

Video paragraph captioning is the task of automatically generating a coherent paragraph description of the actions in a video. Previous linguistic studies have demonstrated that coherence of a natural language text is reflected by its discourse structure and relations. However, existing video captioning methods evaluate the coherence of generated paragraphs

Yushi Bai, Xin Lv, Juanzi Li, Lei Hou

Multi-hop knowledge graph (KG) reasoning has been widely studied in recent years to provide interpretable predictions on missing links with evidential paths. Most previous works use reinforcement learning (RL) based methods that learn to navigate the path towards the target entity. However, these methods suffer from slow and poor convergence, and they may fa

Guilherme Cassales, Heitor Gomes, Albert Bifet, Bernhard Pfahringer

In recent years, the Edge Computing (EC) paradigm has emerged as an enabling factor for developing technologies like the Internet of Things (IoT) and 5G networks, bridging the gap between Cloud Computing services and end-users, supporting low latency, mobility, and location awareness to delay-sensitive applications. Most solutions in EC employ machine learni

Nguyen Van Huynh, Nguyen Quang Hieu, Nam H. Chu, Diep N. Nguyen

Unlike conventional anti-eavesdropping methods that always require additional energy or computing resources (e.g., in friendly jamming and cryptography-based solutions), this work proposes a novel anti-eavesdropping solution that comes with mostly no extra power nor computing resource requirement. This is achieved by leveraging the ambient backscatter commun

Lili Zhao, Wenlu Lin, Y. J. Chung, K. W. Baldwin

In this report, we study ultra-high-mobility two-dimensional (2D) electron/hole systems with high precision capacitance measurement. We find that the capacitance charge appears only at the fringe of the gate at high magnetic field when the 2D conductivity decreases significantly. At integer quantum Hall effects, the capacitance vanishes and forms a plateau a

Liang Chen, Qibiao Peng, Jintang Li, Yang Liu

Backdoor attacks have been widely studied to hide the misclassification rules in the normal models, which are only activated when the model is aware of the specific inputs (i.e., the trigger). However, despite their success in the conventional Euclidean space, there are few studies of backdoor attacks on graph structured data. In this paper, we propose a new

R. Bruce Doak

A bent-crystal mirror has been used to focus an atomic helium beam. The mirror is made from gold deposited onto a mica substrate to form a thin film (~5000 {\AA} thick) of large single crystal domains (domain size ~4000 {\AA} ). The mica sheet is then bent in situ to form a cylindrical mirror of variable radius of curvature. Measurement of scattered beam int

Yongshun Hu, Hongwei Yu

We explore the nonadditive three-body quantum gravitational quadrupole interaction among three nonpointlike objects in their ground states in the framework of linearized quantum gravity and find that the interaction exhibits a distance behavior of $r_A^{-5}r_B^{-5}r_C^{-5}$ in the near regime where the interobject distances are small compared with the charac

Yujin Takahashi, Masahiro Kaneko, Masato Mita, Mamoru Komachi

This study investigates how supervised quality estimation (QE) models of grammatical error correction (GEC) are affected by the learners' proficiency with the data. QE models for GEC evaluations in prior work have obtained a high correlation with manual evaluations. However, when functioning in a real-world context, the data used for the reported results hav

B. F. Liu, Erlin Qiao

Observations of black hole X-ray binaries and active galactic nuclei indicate that the accretion flows around black holes are composed of hot and cold gas, which have been theoretically described in terms of either a hot geometrically thick corona lying above and below a cold geometrically thin disk or an inner advection dominated accretion flow connected to

Hayato Kato, Toshihiro Okubo

When do multinationals show resilience during natural disasters? To answer this, we develop a simple model in which foreign multinationals and local firms in the host country are interacted through input-output linkages. When natural disasters seriously hit local firms and thus increase the cost of sourcing local intermediate inputs, most multinationals may

Shu-Xu Yi, Fiorenzo Stoppa, Gijs Nelemans, Eric Cator

We employ the method used by the GW-Universe Toolbox to generate a synthetic catalogue of detection of stellar mass binary black hole (BBH) mergers. We study advanced LIGO (aLIGO) and Einstein Telescope (ET) as two representatives for the 2nd and 3rd generation GW observatories, and study how GW observations of BBHs can be used to constrain the merger rate a

Thomas Meier, Florian Trybel, Dominique Laniel, Saiana Khandarkhaeva

The experimental study of hydrogen bonds and their symmetrisation under extreme conditions is predominantly driven by diffraction methods, despite challenges of localising or probing the hydrogen subsystems directly. Until recently, H-bond symmetrisation has been addressed in terms of either nuclear quantum effects, spin crossovers or direct structural trans

Felix Lev

We argue that fundamental objects in particle theory are not elementary particles and antiparticles but objects described by irreducible representations (IRs) of the de Sitter (dS) algebra. One might ask why, then, experimental data give the impression that particles and antiparticles are fundamental and there are conserved additive quantum numbers (electric

Ryosuke Kurihara, Yusuke Hirose, Sumika Sano, Keisuke Mitsumoto

We performed ultrasonic measurements on (Ta$_{0.952}$V$_{0.048}$)$_2$NiSe$_5$ to investigate the contribution of acoustic phonons at the zone center to structural and possible excitonic transitions. The transverse elastic constant $C_{55}$ with irreducible representation $B_\mathrm{2g}$ exhibits softening over 90\% above a transition temperature of $T_\mathr

Samuel R. Totorica, Amitava Bhattacharjee

Magnetospheric substorms are preceded by a slow growth phase of magnetic flux loading and current sheet thinning in the tail. Extensive datasets have provided evidence of the triggering of instabilities at substorm onset, including magnetic reconnection and ballooning instabilities. Using an exact kinetic magnetotail equilibrium we present particle-in-cell s

Wei Jia, Zhaojun Lu, Haichun Zhang, Zhenglin Liu

Adversarial Examples (AEs) can deceive Deep Neural Networks (DNNs) and have received a lot of attention recently. However, majority of the research on AEs is in the digital domain and the adversarial patches are static, which is very different from many real-world DNN applications such as Traffic Sign Recognition (TSR) systems in autonomous vehicles. In TSR

Orli Herscovici, Galyna V. Livshyts

In this note, we provide an adaptation of the Kohler-Jobin rearrangement technique to the setting of the Gauss space. As a result, we prove the Gaussian analogue of the Kohler-Jobin's resolution of a conjecture of P\'{o}lya-Szeg\"o: when the Gaussian torsional rigidity of a (convex) domain is fixed, the Gaussian principal frequency is minimized for the half-

Shiying Lu, Qiusheng Gu, Xue Ge, Luis C. Ho

Comparing to the inactive and gas-poor normal lenticular galaxies (S0s) in the local universe, we study a barred star-forming S0 galaxy, PGC 34107, which has been observed by the Centro Astron\'{o}mico Hispano Alem\'{a}n (CAHA) 3.5-m telescope and the Northern Extended Millimeter Array (NOEMA). The spatially resolved ionized gas and molecular gas traced by $

Tao Yu, Bowen Zeng

Non-Hermitian skin effect was observed in one-dimensional systems with short-range chiral interaction. Long-range chiral interaction mediated by traveling waves also favors the accumulation of energy, but has not yet showed non-Hermitian topology. Here we find that the strong interference brought by the wave propagation is detrimental for accumulation. By su

Simanraj Sadana, Som Kanjilal, Dipankar Home, Urbasi Sinha

We focus on characterizing entanglement of high dimensional bipartite states using various statistical correlators for two-qudit mixed states. The salient results obtained are as follows: (a) A scheme for determining the entanglement measure given by Negativity is explored by analytically relating it to the widely used statistical correlators viz. mutual pre

Jieli Liu, Weilin Zheng, Dingyuan Lu, Jiajing Wu

Recently, many Delegated Proof-of-Stake (DPoS)-based blockchains have been widely used in decentralized applications, such as EOSIO, Tron, and Binance Smart Chain. Compared with traditional PoW-based blockchain systems, these systems achieve a higher transaction throughput and are well adapted to large-scale scenes in daily applications. Decentralization is

Kent Yagi

In this chapter, we review the eikonal technique to analytically derive approximate quasi-normal mode frequencies of black holes. We first review the procedure in General Relativity and extend it to theories beyond General Relativity. As an example of the latter, we focus on scalar Gauss-Bonnet gravity in which a scalar field can couple to the Gauss-Bonnet i

Kan Takase, Akito Kawasaki, Byung Kyu Jeong, Mamoru Endo

Continuous-wave (CW) squeezed light is used in generation of various optical quantum states thus is a fundamental resource of fault-tolerant universal quantum computation using optical continuous variables. To realize a practical quantum computer, a waveguide optical parametric amplifier (OPA) is an attractive CW squeezed light source in terms of its THz-ord

Daniel R. Johnston

We prove that the Riemann hypothesis is equivalent to the condition $\int_{2}^x\left(\pi(t)-\text{li}(t)\right)\mathrm{d}t<0$ for all $x>2$. Here, $\pi(t)$ is the prime-counting function and $\text{li}(t)$ is the logarithmic integral. This makes explicit a claim of Pintz (1991). Moreover, we prove an analogous result for the Chebyshev function $\theta(t)$ an

Kelli Francis-Staite

This paper describes multi-portfolio `internal' rebalancing processes used in the finance industry. Instead of trading with the market to `externally' rebalance, these internal processes detail how portfolio managers buy and sell between their portfolios to rebalance. We give an overview of currently used internal rebalancing processes, including one known a

Dongxing Yu, Hongxin Yang, Mairbek Chshiev, Albert Fert

Logic gates based on magnetic elements are promising candidates for the logic-in-memory applications with nonvolatile data retention, near-zero leakage and scalability. In such spin-based logic device, however, the multi-strip structure and fewer functions are obstacles to improving integration and reducing energy consumption. Here we propose a skyrmions-bas

Tatiana Konstantinova, Lutz Wiegart, Maksim Rakitin, Anthony M DeGennaro

Analysis of X-ray Photon Correlation Spectroscopy (XPCS) data for non-equilibrium dynamics often requires manual binning of age regions of an intensity-intensity correlation function. This leads to a loss of temporal resolution and accumulation of systematic error for the parameters quantifying the dynamics, especially in cases with considerable noise. Moreo

Ognjen Malkoc, Peter Stano, Daniel Loss

We investigate theoretically charge-noise induced spin dephasing of a hole confined in a quasi-two-dimensional silicon quantum dot. Central to our treatment is accounting for higher-order corrections to the Luttinger Hamiltonian. Using experimentally reported parameters, we find that the new terms give rise to sweet-spots for the hole-spin dephasing, which a

Hafiz Zeeshan Iqbal Khan, Surrayya Mobeen, Jahanzeb Rajput, Jamshed Riaz

Modern aircraft are designed with redundant control effectors to cater for fault tolerance and maneuverability requirements. This leads to aircraft being over-actuated and requires control allocation schemes to distribute the control commands among control effectors. Traditionally, optimization-based control allocation schemes are used; however, for nonlinea

Radovan Dermisek

I review possible explanations of the muon g-2 anomaly in models with extended Higgs and matter sectors, focusing on extensions of the standard model and the two Higgs doublet model with vectorlike leptons. Predictions of these models, namely the modifications of muon Yukawa and gauge couplings, that can be searched for at the LHC and future colliders, are s

Fioralba Cakoni, Heejin Lee, Peter Monk, Yangwen Zhang

In this paper we consider the inverse problem of determining structural properties of a thin anisotropic and dissipative inhomogeneity in ${\mathbb R}^m$, $m=2,3$ from scattering data. In the asymptotic limit as the thickness goes to zero, the thin inhomogeneity is modeled by an open $m-1$ dimensional manifold (here referred to as screen), and the field insi

Sebastián Nájera, Aram Aguilar, Geovanny A. Rave-Franco, Celia Escamilla-Rivera

In this paper we explore the possibility to find exact solutions for Teleparallel Gravity (TG) of the type of spherically symmetric Lema\^\i tre-Tolman-Bondi (LTB) dust models. We apply to the LTB metric the formalism of Teleparallel Gravity in its extension to $f(T,B)$ models, which can be seen it as the analagous from the Schwarzschild solution in General

Tariq M. Khan, Donald G. bailey, Yinan Kong

This paper presents a hybrid approach to achieve iris localization based on a Laplacian of Gaussian (LoG) filter, region growing, and zero-crossings of the LoG filter. In the proposed method, an LoG filter with region growing is used to detect the pupil region. Subsequently, zero-crossings of the LoG filter are used to accurately mark the inner and outer cir

Julian Kaspczyk

Let $q$ be a nontrivial odd prime power, and let $n \ge 2$ be a natural number with $(n,q) \ne (2,3)$. We characterize the groups $PSL_n(q)$ and $PSU_n(q)$ by their $2$-fusion systems. This contributes to a programme of Aschbacher aiming at a simplified proof of the classification of finite simple groups.

Muhammad Amir Shafiq, Zhiling Long, Haibin Di, Ghassan AlRegib

A new approach to seismic interpretation is proposed to leverage visual perception and human visual system modeling. Specifically, a saliency detection algorithm based on a novel attention model is proposed for identifying subsurface structures within seismic data volumes. The algorithm employs 3D-FFT and a multi-dimensional spectral projection, which decomp

Dhileeban Kumaresan, Richard Wang, Ernesto Martinez, Richard Cziva

When cloud layers cover photovoltaic (PV) panels, the amount of power the panels produce fluctuates rapidly. Therefore, to maintain enough energy on a power grid to match demand, utilities companies rely on reserve power sources that typically come from fossil fuels and therefore pollute the environment. Accurate short-term PV power prediction enables operat

K. Zhang, H. D. Yan

Recently, a new concept called multiplicative differential was introduced by Ellingsen et al. Inspired by this pioneering work, power functions with low c-differential uniformity were constructed. Wang et al. defined the c-differential spectrum of a power function [27]. In this paper, we present some properties of the c-differential spectrum of a power funct

Jun-Jie Zhang, Xin-Li Sheng, Shi Pu, Jian-Nan Chen

We have calculated the directed flow $v_{1}$ and charge-dependent directed flow $\Delta v_{1}$ for pions and protons in Au+Au collisions at $\sqrt{s_{NN}}=200$GeV by solving the coupled Boltzmann-Maxwell equations self-consistently. Our numerical results show that $v_{1}$ for pions and protons are all negative in the positive mid rapidity region and have sim

Phillip Benjamin Ströbel, Simon Clematide, Martin Volk, Raphael Schwitter

The evaluation of Handwritten Text Recognition (HTR) models during their development is straightforward: because HTR is a supervised problem, the usual data split into training, validation, and test data sets allows the evaluation of models in terms of accuracy or error rates. However, the evaluation process becomes tricky as soon as we switch from developme

Xiaohong Chen, Zhengling Qi

We study the off-policy evaluation (OPE) problem in an infinite-horizon Markov decision process with continuous states and actions. We recast the $Q$-function estimation into a special form of the nonparametric instrumental variables (NPIV) estimation problem. We first show that under one mild condition the NPIV formulation of $Q$-function estimation is well

Nathan Hughes

Given $d\geq 2$, we show that the number of approximates $\frac{1}{q}\mathbf{p}\in \mathbb{Q}^d$ of $\mathbf{x}\in\mathbb{R}^d$ satisfying $|q\mathbf{x}-\mathbf{p}|\leq cq^{-\frac{1}{d}}$ with denominator $1\leq q < T$ decays to the asymptotic term $c\text{vol}_d(B_d(0,1))\log T$ with error of order $\left(\log T\right)^{-\frac{1}{2}}\left(\log \log T\right)

Saeed Hajizadeh, Haihao Lu, Benjamin Grimmer

Recently, minimax optimization received renewed focus due to modern applications in machine learning, robust optimization, and reinforcement learning. The scale of these applications naturally leads to the use of first-order methods. However, the nonconvexities and nonconcavities present in these problems, prevents the application of typical Gradient Descent

Yuya Tanizaki, Mithat Ünsal

We construct an anomaly-preserving compactification of 4d gauge theories, including $SU(N)$ Yang-Mills theory, $\mathcal{N}=1$ supersymmetric Yang-Mills theory, and QCD, down to 2d by turning on 't Hooft flux through $T^2$. It provides a new framework to analytically calculate nonperturbative properties such as confinement, chiral symmetry breaking, and mult

Michal Ferov, Mark Pengitore

In this article, we study the asymptotic behaviour of conjugacy separability for wreath products of abelian groups. We fully characterise the asymptotic class in the case of lamplighter groups and give exponential upper and lower bounds for generalised lamplighter groups. In the case where the base group is infinite, we give superexponential lower and upper

Rafael Bouzaglo, Yosi Keller

Deep learning-based models have been shown to improve the accuracy of fingerprint recognition. While these algorithms show exceptional performance, they require large-scale fingerprint datasets for training and evaluation. In this work, we propose a novel fingerprint synthesis and reconstruction framework based on the StyleGan2 architecture, to address the p

Michèle Levi

Pushing the precision frontier for gravitational waves is one of the most urgent tasks in theoretical physics today, in light of the increasing influx of data from a rapidly growing worldwide network of gravitational-wave detectors.

Daiki Kawabe

Let $f: X \rightarrow C$ be a genus 1 fibration from a smooth projective surface, i.e. its generic fiber is a regular genus 1 curve. Let $j: J \rightarrow C$ be the Jacobian fibration of $f$. In this paper, we prove that the Chow motives of $X$ and $J$ are isomorphic. As an application, combined with our concomitant work on motives of quasi-elliptic fibratio

Guillermo H. Goldsztein, Lars Q. English, Emma Behta, Hillel Finder

Using a combination of theory, experiment, and simulation, we revisit the dynamics of two coupled metronomes on a moving platform. Our experiments show that the platform's motion is damped by a dry friction force of Coulomb type, not the viscous linear friction force that has often been assumed in the past. Prompted by this result, we develop a new mathemati

Andi Brojbeanu, Cornel Pintea

We denote by ${\rm Hess}^+$ the set of all points $p\in\mathbb{R}^n$ such that the Hessian matrix $H_p(f)$ of the $C^2$-smooth function $f:\mathbb{R}^n\longrightarrow\mathbb{R}$ is positive definite. In this paper we provide a class of norm-coercive polynomial functions with large ${\rm Hess}^+$ regions, as their ${\rm Hess}^+$ complements happen to be bound

Kunal Gupta, Brendan Colvert, Francisco Contijoch

Motion during acquisition of a set of projections can lead to significant motion artifacts in computed tomography reconstructions despite fast acquisition of individual views. In cases such as cardiac imaging, motion may be unavoidable and evaluating motion may be of clinical interest. Reconstructing images with reduced motion artifacts has typically been ac

Christian Limberg, Andrew Melnik, Augustin Harter, Helge Ritter

With this work we are explaining the "You Only Look Once" (YOLO) single-stage object detection approach as a parallel classification of 10647 fixed region proposals. We support this view by showing that each of YOLOs output pixel is attentive to a specific sub-region of previous layers, comparable to a local region proposal. This understanding reduces the co

Piernicola Bettiol, Carlo Mariconda

We consider a Bolza type optimal control problem of the form \begin{equation}\min J_{t}(y,u):=\int_t^T\Lambda(s,y(s), u(s))\,ds+g(y(T))\tag{P$_{t,x}$}\end{equation} Subject to: \begin{equation}\label{tag:admissible}\tag{D}\begin{cases} y\in AC([t,T];\mathbb R^n)\\y'=b(y)u\text{ a.e. } s\in [t,T], \,y(t)=x\\u(s)\in \mathcal U\text{ a.e. } s\in [t,T],\, y(s)\i

Mushuang Liu, Ilya Kolmanovsky, H. Eric Tseng, Suzhou Huang

Decision-making for autonomous driving is challenging, considering the complex interactions among multiple traffic agents (e.g., autonomous vehicles (AVs), human drivers, and pedestrians) and the computational load needed to evaluate these interactions. This paper develops two general potential game based frameworks, namely, finite and continuous potential g

Dina Hussein, Ganapati Bhat, Janardhan Rao Doppa

Wearable devices that integrate multiple sensors, processors, and communication technologies have the potential to transform mobile health for remote monitoring of health parameters. However, the small form factor of the wearable devices limits the battery size and operating lifetime. As a result, the devices require frequent recharging, which has limited th

Carlo Mariconda

Let $F(y):=\displaystyle\int_t^TL(s, y(s), y'(s))\,ds$ be a positive functional (the "energy"), unnecessarily autonomous, defined on the space of Sobolev functions $W^{1,p}([t,T]; \mathbb R^n)$ ($p\ge 1$). We consider the problem of minimizing $F$ among the functions $y$ that possibly satisfy one, or both, end point conditions. In many applications, where th

Jimmy He, Huy Tuan Pham, Max Wenqiang Xu

We show that the counts of low degree irreducible factors of a random polynomial $f$ over $\mathbb{F}_q$ with independent but non-uniform coefficients behave like that of a uniform random polynomial, exhibiting a form of universality for random polynomials over finite fields. Our strongest results require various assumptions on the parameters, but we are abl

Carlo Mariconda

Let $F(y):=\displaystyle\int_t^TL(s, y(s), y'(s))\,ds$ be a positive functional, unnecessarily autonomous, defined on the space $ W^{1,p}([t,T]; \mathbb R^n)$ ($p\ge 1$) of Sobolev functions, possibly with prescribed one or two end point conditions. It is important, especially for the applications, to be able to approximate the infimum of $F$ with the values

Zhichao Wang, Xin Zhou

We exhibit the first set of examples of non-bumpy metrics on the $(n+1)$-sphere ($2\leq n\leq 6$) in which the varifold associated with the two-parameter min-max construction must be a multiplicity-two minimal $n$-sphere. This is proved by a new area-and-separation estimate for certain minimal hypersurfaces with Morse index two inspired by an early work of C

Tomislav Ivek, Domagoj Vlah

We present our submission to the Extreme Value Analysis 2021 Data Challenge in which teams were asked to accurately predict distributions of wildfire frequency and size within spatio-temporal regions of missing data. For the purpose of this competition we developed a variant of the powerful variational autoencoder models dubbed the Conditional Missing data I

Daiki Kawabe

We prove that the transcendental motive of any quasi elliptic surface is trivial. To prove this, we focus on the uniruledness of quasi elliptic surfaces.

Rabindra N. Mohapatra, Nobuchika Okada

Affleck-Dine (AD) mechanism for leptogenesis involves the cosmological evolution of a complex scalar field (AD field) that carries non-zero lepton number. We show how explicit lepton number breaking terms, which involve the AD field needed to implement this scenario combined with fermionic WIMP dark matter, can generate neutrino mass at the one loop level, t

R. J. Hernández-Pinto, M. Bedolla-Hernández, L. X. Gutiérrez-Guerrero, A. Bashir

The extraction of elastic form factors for mesons in the context of the contact interaction model is revisited in this manuscript. The dressed masses of quarks and mesons are determined through the gap and Bethe-Salpeter equations. The generic elastic scattering process $M\gamma \to M$ is studied for the meson $M$ formed of two differently flavored quarks. T

Ahasan Ahamed, Cesar Bartolo-Perez, Ahmed Sulaiman Mayet, Soroush Ghandiparsi

Optical spectrometers are widely used scientific equipment with many applications involving material characterization, chemical analysis, disease diagnostics, surveillance, etc. Emerging applications in biomedical and communication fields have boosted the research in the miniaturization of spectrometers. Recently, reconstruction-based spectrometers have gain

A. P. Isaev, A. A. Provorov

We find the characteristic identities for the split Casimir operator in the defining and adjoint representations of the $osp(M|N)$ and $s\ell(M|N)$ Lie superalgebras. These identities are used to build the projectors onto invariant subspaces of the representation $T^{\otimes 2}$ of the $osp(M|N)$ and $s\ell(M|N)$ Lie superalgebras in the cases when $T$ is th

Liyi Gu, Chintan Shah, Ruitian Zhang

Relevant uncertainties on theoretical atomic data are vital to determine the accuracy of plasma diagnostics in a number of areas including in particular the astrophysical study. We present a new calculation of the uncertainties on the present theoretical ion-impact charge exchange atomic data and X-ray spectra based on a set of comparisons with the existing

Giovanni Bellettini, Roberta Marziani, Riccardo Scala

We consider a Plateau problem in codimension $1$ in the non-parametric setting. A Dirichlet boundary datum is given only on part of the boundary $\partial \Omega$ of a bounded convex domain $\Omega\subset\mathbb{R}^2$. Where the Dirichlet datum is not prescribed, we allow a free contact with the horizontal plane. We show existence of a solution, and prove re

Sebastian Junge

We construct of the main object of the Partite Lemma as the colimit over a certain diagram. This gives a purely category theoretic take on the Partite Lemma and establishes the canonicity of the object. Additionally, the categorical point of view allows us to unify the direct Partite Lemma in the Ne\v{s}et\v{r}il--R\"odl Theorem with the dual Paritite Lemma

Ali K. Z. Tehrani, Ivan M. Rosado-Mendez, Hassan Rivaz

Quantitative UltraSound (QUS) aims to reveal information about the tissue microstructure using backscattered echo signals from clinical scanners. Among different QUS parameters, scatterer number density is an important property that can affect estimation of other QUS parameters. Scatterer number density can be classified into high or low scatterer densities.

Yue Sun, Adhyyan Narang, Halil Ibrahim Gulluk, Samet Oymak

An overarching goal in machine learning is to build a generalizable model with few samples. To this end, overparameterization has been the subject of immense interest to explain the generalization ability of deep nets even when the size of the dataset is smaller than that of the model. While the prior literature focuses on the classical supervised setting, t

Çağın Ararat, Umur Cetin

As appropriate generalizations of convex combinations with uncountably many terms, we introduce the so-called Choquet combinations, Choquet decompositions and Choquet convex decompositions, as well as their corresponding hull operators acting on the power sets of Lebesgue-Bochner spaces. We show that Choquet hull coincides with convex hull in the finite-dime

Fabian Dunker, Stefan Hoderlein, Hiroaki Kaido

This paper studies nonparametric identification in market level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual specific coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also function

Gennadiy Burlak, Zhaopin Chen, Boris A. Malomed

We construct families of one-dimensional (1D) stable solitons in two-component $\mathcal{PT}$-symmetric systems with spin-orbit coupling (SOC) and quintic nonlinearity, which plays the critical role in 1D setups. The system models light propagation in a dual-core waveguide with skewed coupling between the cores. Stability regions for the solitons are identif

Ran Li, Jin Wang

Based on the free energy landscape description of Hawking-Page phase transition, the transition process from the Schwarzschild-anti-de Sitter black hole to the thermal anti-de Sitter space are considered to be stochastic under the thermal fluctuations. If the correlation time of the effective thermal bath is comparable or even longer than the oscillating tim

Chungjae Lee, Kevin Dalmeijer, Pascal Van Hentenryck

Autonomous trucks are expected to fundamentally transform the freight transportation industry. In particular, Autonomous Transfer Hub Networks (ATHN), which combine autonomous trucks on middle miles with human-driven on the first and last miles, are seen as the most likely deployment pathway of this technology. This paper presents three methods to optimize A

Varun Mannam, Xiaotong Yuan, Scott Howard

Fluorescence lifetime imaging microscopy (FLIM) is an important technique to understand the chemical micro-environment in cells and tissues since it provides additional contrast compared to conventional fluorescence imaging. When two fluorophores within a diffraction limit are excited, the resulting emission leads to non-linear spatial distortion and localiz