July 2022 arXiv papers — page 100

Shu Liu, Tingyi Wu, Chaoping Xing, Chen Yuan

A locally repairable code is called Singleton-optimal if it achieves the Singleton-type bound. Such codes are of great theoretic interest in the study of locally repairable codes. In the recent years there has been a great amount of work on this topic. One of the main problems in this topic is to determine the largest length of a q-ary Singleton-optimal loca

Jacopo Ulivelli

Steiner symmetrization is well known for its rounding and general convergence properties. We identify a whole family of symmetrizations sharing analogue behaviors: In fact we prove that all these symmetrizations share the same converging symmetrization processes, together with some pathological phenomena.

Alexander Keller, Carsten Wächter, Nikolaus Binder

Based on the seminal work on Array-RQMC methods and rank-1 lattice sequences by Pierre L'Ecuyer and collaborators, we introduce efficient deterministic algorithms for image synthesis. Enumerating a low discrepancy sequence along the Hilbert curve superimposed on the raster of pixels of an image, we achieve noise characteristics that are desirable with respec

Sergei V. Talalov

This paper investigates quantized thin vortex rings with an internal structure. The quantization scheme of this dynamical system is based on an earlier the approach proposed by the author. Both energy spectrum and circulation spectrum are calculated. Examples show that the set of permissible circulation values has a fractal structure. The suggested model all

Zain UlAbideen, Tiago Diadami Perez, Mayler Martins, Samuel Pagliarini

Numerous threats are associated with the globalized integrated circuit (IC) supply chain, such as piracy, reverse engineering, overproduction, and malicious logic insertion. Many obfuscation approaches have been proposed to mitigate these threats by preventing an adversary from fully understanding the IC (or parts of it). The use of reconfigurable elements i

Frederic Bruno Campana

We show, using [14], that a smooth projective fibration f : X $\rightarrow$ Y between connected complex quasi-projective manifolds satisfies the equality $\kappa$(X) = $\kappa$(X y) + $\kappa$(Y) of Logarithmic Kodaira dimensions if its fibres X y admit a good minimal model. Without the last assumption, this was conjectured in [11]. Several cases are establi

Yves Achdou, Guillaume Carlier, Quentin Petit, Daniela Tonon

We consider an economy made of competing firms which are heterogeneous in their capital and use several inputs for producing goods. Their consumption policy is fixed rationally by maximizing a utility and their capital cannot fall below a given threshold (state constraint). We aim at modeling the interactions between firms on the markets of the different inp

Nguyen Viet Dang, Matthieu Léautaud, Gabriel Rivière

In analogy with the study of Pollicott-Ruelle resonances on negatively curved manifolds, we define anisotropic Sobolev spaces that are well-adapted to the analysis of the geodesic vector field associated with any translation invariant Finsler metric on the torus $\mathbb{T}^d$. Among several applications of this functional point of view, we study properties

Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin

Knowledge Distillation (KD) transfers the knowledge from a high-capacity teacher network to strengthen a smaller student. Existing methods focus on excavating the knowledge hints and transferring the whole knowledge to the student. However, the knowledge redundancy arises since the knowledge shows different values to the student at different learning stages.

Adrien Meynard, Bruno Torrésani

This paper deals with the modeling of non-stationary signals, from the point of view of signal synthesis. A class of random, non-stationary signals, generated by synthesis from a random timescale representation, is introduced and studied. Non-stationarity is implemented in the timescale representation through a prior distribution which models the action of t

Harsh Beohar, Sebastian Gurke, Barbara König, Karla Messing

We introduce a general and compositional, yet simple, framework that allows us to derive soundness and expressiveness results for modal logics characterizing behavioural equivalences or metrics (also known as Hennessy-Milner theorems). It is based on Galois connections between sets of (real-valued) predicates on the one hand and equivalence relations/metrics

Matteo Rizzato, Julien Wallart, Christophe Geissler, Nicolas Morizet

The finance industry is producing an increasing amount of datasets that investment professionals can consider to be influential on the price of financial assets. These datasets were initially mainly limited to exchange data, namely price, capitalization and volume. Their coverage has now considerably expanded to include, for example, macroeconomic data, supp

Lei-Hua Liu, Mian Zhu, Wentao Luo, Yi-Fu Cai

We systematically investigate the microlensing effect of charged spherically symmetric wormhole, where the light source is remote from the throat. Remarkably, there will be at most three images by considering the charge part. We study all situations including three images, two images, and one image, respectively. The numerical result shows that the range of

Rabah Labbas, Stéphane Maingot, Alexandre Thorel

After different variables and functions changes, the generalized dispersal problem, recalled in (1) below and considered in part I, see [14], leads us to invert a sum of linear operators in a suitable Banach space, see (2) below. The essential result of this second part lies in the complete study of this sum using the two well-known strategies: the one of Da

Rabah Labbas, Stéphane Maingot, Alexandre Thorel

The purpose of this article (composed of two parts) is the study of the generalized dispersal operator of a reaction-diffusion equation in $L^p$-spaces set in the finite conical domain $S_{\omega,\rho}$ of angle $\omega>0$ and radius $\rho>0$ in $\mathbb{R}^2$. This first part is devoted to the behaviour of the solution near the top of the cone which is comp

Anees Peringal, Mohamad Chehadeh, Rana Azzam, Mahmoud Hamandi

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a paylo

Wan Wu, Guojun Huang, Jiaxing Zhao, Pengfei Zhuang

The interaction potential between a pair of heavy quarks is calculated with resummed perturbation method in Gribov-Zwanziger approach at finite temperature. The resummed loop correction makes the potential complex. While the real part is, as expected, screened and becomes short-ranged in hot medium, the strength of the imaginary part increases with temperatu

Marc Satkowski, Franziska Kessler, Susanne Narciss, Raimund Dachselt

The ability to read, understand, and comprehend visual information representations is subsumed under the term visualization literacy (VL). One possibility to improve the use of information visualizations is to introduce adaptations. However, it is yet unclear whether people with different VL benefit from adaptations to the same degree. We conducted an online

Shun Tamura, Yukio Tanaka, Takehito Yokoyama

We investigate the proximity effect in an s-wave superconductor/ferromagnetic metal with a Rashba spin-orbit coupling/diffusive normal metal junction and an s-wave superconductor/noncollinear magnetic metal/diffusive normal metal junction. We show the generation of equal spin-triplet pairings in the diffusive normal metal due to spin-flip scattering in the i

Samodha Pallewatta, Vassilis Kostakos, Rajkumar Buyya

The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of fast-evolving IoT

Takashi Furuya, Roland Potthast

We study the inverse medium scattering problem to reconstruct the unknown inhomogeneous medium from the far-field patterns of scattered waves. The inverse scattering problem is generally ill-posed and nonlinear, and the iterative optimization method is often adapted. A natural iterative approach to this problem is to place all available measurements and mapp

Julong Young, Junhui Chen, Feihu Huang, Jian Peng

Transformers have demonstrated impressive strength in long-term series forecasting. Existing prediction research mostly focused on mapping past short sub-series (lookback window) to future series (forecast window). The longer training dataset time series will be discarded, once training is completed. Models can merely rely on lookback window information for

Aurelia Dymek, Stanisław Kasjan, Joanna Kułaga-Przymus

Let $K$ be a finite extension of $\mathbb{Q}$ and $\mathcal{O}_K$ be its ring of integers. Let $\mathfrak{B}$ be a primitive collection of ideals in $\mathcal{O}_K$. We show that any $\mathfrak{B}$-free system is essentially minimal. Moreoever, the $\mathfrak{B}$-free system is minimal if and only if the characteristic function of $\mathfrak{B}$-free numbers

Rémi Mattéoli, Joël Gilbert, Soizic Terrien, Jean-Pierre Dalmont

The ghost note is a natural note which can be played exclusively on bass brass instruments with a predominantly-expanding bore profile such as tubas, euphoniums or saxhorns. It stands between the pedal note-the lowest natural note playable, or first regime-and the instrument's second regime. However, if the interval between the pedal note and the second regi

Luca Barbaglia, Christophe Croux, Ines Wilms

Despite the increasing integration of the global economic system, anti-dumping measures are a common tool used by governments to protect their national economy. In this paper, we propose a methodology to detect cases of anti-dumping circumvention through re-routing trade via a third country. Based on the observed full network of trade flows, we propose a mea

Juan Gómez-Gómez, Ester Vidaña-Vila, Xavier Sevillano

The deployment of an expert system running over a wireless acoustic sensors network made up of bioacoustic monitoring devices that recognise bird species from their sounds would enable the automation of many tasks of ecological value, including the analysis of bird population composition or the detection of endangered species in areas of environmental intere

Rama Mishra, Visakh Narayanan

This paper discusses some geometric ideas associated with knots in real projective 3-space $\mathbb{R}P^3$. These ideas are borrowed from classical knot theory. Since knots in $\mathbb{R}P^3$ are classified into three disjoint classes, - affine, class-$0$ non-affine and class-$1$ knots, it is natural to wonder in which class a given knot belongs to. In this

Yoshio Kitadono, Tomohiro Inagaki

The elliptically oscillating solutions in the Abelian Higgs-model are presented and the classical massive-dispersion-relation through the non-linear dynamics is discussed. The generated massive-dispersion-relation including a field value of the scalar field is derived as the consequence of the equation of motions. We discuss the property of the new solutions

Xian-Kai Jiang, Jian Wu, Deng-Yi Chen, Yi-Ming Hu

Quantitative and analytical analysis of modulation process of the collimator is a great challenge, and is also of great value to the design and development of Fourier transform imaging telescopes. The Hard X-ray Imager (HXI), as one of the three payloads onboard the Advanced Space-based Solar Observatory(ASO-S) mission, adopts modulating Fourier-Transformati

G. E. Volovik

Several approaches to quantum gravity (including the model of superplastic vacuum; Diakonov tetrads emerging as the bilinear combinations of the fermionis fields; $BF$-theories of gravity; and effective acoustic metric) suggest that in general relativity the metric must have dimension 2, i.e. $[g_{\mu\nu}]=1/[L]^2$, irrespective of the dimension of spacetime

Josua Schott

It is shown that any symplectic $2n\times 2n$-matrix, whose entries are complex holomorphic functions on a reduced Stein space, can be decomposed into a finite product of elementary symplectic matrices if and only if it is null-homotopic. Moreover, if this is the case, the number of factors can be bounded by a constant depending only on $n$ and the dimension

Honghui Liu, Changjian Wang, Kele Xu, Fangzhao Li

Wound image segmentation is a critical component for the clinical diagnosis and in-time treatment of wounds. Recently, deep learning has become the mainstream methodology for wound image segmentation. However, the pre-processing of the wound image, such as the illumination correction, is required before the training phase as the performance can be greatly im

Oded Zafrani

Socially Assistive Robots (SARs) are expected to support autonomy, aging in place, and wellbeing in later life. For successful assimilation, it is necessary to understand factors affecting older adults Quality Evaluations (QEs) of SARs, including the pragmatic and hedonic evaluations and overall attractiveness. Previous studies showed that trust in robots si

Jie Hu, Hao Li, Yue Wang, Donglei Yang

An \emph{incompatibility system} $(G,\mathcal{F})$ consists of a graph $G$ and a family $\mathcal{F}=\{F_v\}_{v\in V(G)}$ over $G$ with $F_v\subseteq \{\{e,e'\}\in {E(G)\choose 2}: e\cap e'=\{v\}\}$. We say that two edges $e,e'\in E(G)$ are \emph{incompatible} if $\{e,e'\}\in F_v$ for some $v\in V(G)$, and otherwise \emph{compatible}. A subgraph $H$ of $G$ i

Yichen Sheng, Yifan Liu, Jianming Zhang, Wei Yin

Shadows are essential for realistic image compositing. Physics-based shadow rendering methods require 3D geometries, which are not always available. Deep learning-based shadow synthesis methods learn a mapping from the light information to an object's shadow without explicitly modeling the shadow geometry. Still, they lack control and are prone to visual art

Karsten Kruse

This paper is dedicated to weighted composition semigroups on spaces of continuous functions and their subspaces. We consider semigroups induced by semiflows and semicocycles on Banach spaces $\mathcal{F}(\Omega)$ of continuous functions on a Hausdorff space $\Omega$ such that the norm-topology is stronger than the compact-open topology like the Hardy spaces

Yuanyu Zhang, Zhumeng Zheng, Ji He, Shuangrui Zhao

While the millimeter-wave (mmWave) communication is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a

Yuyang Long, Qilong Zhang, Boheng Zeng, Lianli Gao

For black-box attacks, the gap between the substitute model and the victim model is usually large, which manifests as a weak attack performance. Motivated by the observation that the transferability of adversarial examples can be improved by attacking diverse models simultaneously, model augmentation methods which simulate different models by using transform

Jinn Ho, Wen-Liang Hwang

Compressive sensing involves the inversion of a mapping $SD \in \mathbb{R}^{m \times n}$, where $m < n$, $S$ is a sensing matrix, and $D$ is a sparisfying dictionary. The restricted isometry property is a powerful sufficient condition for the inversion that guarantees the recovery of high-dimensional sparse vectors from their low-dimensional embedding into a

K. T. Mpofu, C. Lee, G. E. M. Maguire, H. G. Kruger

The work done in this paper is an extension of the work done by Mpofu et al in [1]. The motivation for this paper is to show the potential of quantum bio-sensing techniques in applications to complex viruses like the human immunodeficiency virus (HIV) and to show it's potential in binding reactions where the signal is small and can potentially be buried in n

Vladimir A. Dorodnitsyn, Evgeniy I. Kaptsov, Roman V. Kozlov, Sergey V. Meleshko

A recent paper considered symmetries and conservation laws of the plane one-dimensional flows for magnetohydrodynamics in the mass Lagrangian coordinates. This paper analyses the one-dimensional magnetohydrodynamics flows with cylindrical symmetry in the mass Lagrangian coordinates. The medium is assumed inviscid and thermally non-conducting. It is modeled b

Zuzeng Lin, Ailin Huang, Zhewei Huang

Drawing images of characters with desired poses is an essential but laborious task in anime production. Assisting artists to create is a research hotspot in recent years. In this paper, we present the Collaborative Neural Rendering (CoNR) method, which creates new images for specified poses from a few reference images (AKA Character Sheets). In general, the

Xuetong Wu, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu

Transfer learning, or domain adaptation, is concerned with machine learning problems in which training and testing data come from possibly different probability distributions. In this work, we give an information-theoretic analysis of the generalization error and excess risk of transfer learning algorithms. Our results suggest, perhaps as expected, that the

Jinghui Xia, Zengfeng Huang

Motivated by many applications, we study clustering with a faulty oracle. In this problem, there are $n$ items belonging to $k$ unknown clusters, and the algorithm is allowed to ask the oracle whether two items belong to the same cluster or not. However, the answer from the oracle is correct only with probability $\frac{1}{2}+\frac{\delta}{2}$. The goal is t

Ignacio Heredia Cacha, Judith Sainz-Pardo Díaz, María Castrillo Melguizo, Álvaro López García

In this work we evaluate the applicability of an ensemble of population models and machine learning models to predict the near future evolution of the COVID-19 pandemic, with a particular use case in Spain. We rely solely in open and public datasets, fusing incidence, vaccination, human mobility and weather data to feed our machine learning models (Random Fo

Buzhen Huang, Yuan Shu, Jingyi Ju, Yangang Wang

Although significant progress has been achieved on monocular maker-less human motion capture in recent years, it is still hard for state-of-the-art methods to obtain satisfactory results in occlusion scenarios. There are two main reasons: the one is that the occluded motion capture is inherently ambiguous as various 3D poses can map to the same 2D observatio

Masud An Nur Islam Fahim, Nazmus Saqib, Shafkat Khan Siam, Ho Yub Jung

Class activation map (CAM) helps to formulate saliency maps that aid in interpreting the deep neural network's prediction. Gradient-based methods are generally faster than other branches of vision interpretability and independent of human guidance. The performance of CAM-like studies depends on the governing model's layer response, and the influences of the

Christian Fiedler, Sebastian Trimpe

In many applications of optimal control, the stage cost is not fixed, but rather a design choice with considerable impact on the control performance. In infinite horizon optimal control, the choice of stage cost is often restricted by the requirement of uniform cost controllability, which is nontrivial to satisfy. Here we revisit a previously proposed constr

Carmine Recchiuto, Antonio Sgorbissa

The article introduces the concept of "diversity-aware" robotics and discusses the need to develop computational models to embed robots with diversity-awareness: that is, robots capable of adapting and re-configuring their behavior to recognize, respect, and value the uniqueness of the person they interact with to promote inclusion regardless of their age, r

Ding-Hui Xu, Shu-Jun Rong

Leptonic mixing patterns are usually extracted on the basis of groups or algebraic structures. In this paper, we introduce an alternative geometric method to study the correlations between the leptonic mixing parameters. At the 3$\sigma$ level of the recent global fit data of neutrino oscillations, the distribution of the scattered points of the angles betwe

Mostafa Mohammadkarimi, Geert Leus, Raj Thilak Rajan

A new method for joint ranging and Phase Offset (PO) estimation of multiple drones/aircrafts is proposed in this paper. The proposed method employs the superimposed uncoordinated Automatic Dependent Surveillance Broadcast (ADS-B) packets broadcasted by drones/aircrafts for joint range and PO estimation. It jointly estimates range and PO prior to ADS-B packet

Hailong Fu, Ke Huang, Kenji Watanabe, Takashi Taniguchi

The charge and exchange statistics of an elementary excitation manifest in quantum coherent oscillations that can be explored in interferometry measurements. Quantum Hall interferometers are primary tools to uncover unconventional quantum statistics associated with fractional and non-Abelian anyons of a two-dimensional system, the latter being the foundation

G. Contursi, P. de Laverny, A. Recio-Blanco, E. Spitoni

The recent Gaia Third Data Release contains a homogeneous analysis of millions of high-quality Radial Velocity Spectrometer (RVS) stellar spectra by the GSP-Spec module. This led to the estimation of millions of individual chemical abundances and allows us to chemically map the Milky Way. Among the published GSP-Spec abundances, three heavy-elements produced

Satoshi Takada, Kazuhiro Hara, Hisao Hayakawa

We demonstrate that a discontinuous shear thickening (DST) can take place even in a moderately dense inertial suspension consisting of frictionless soft particles. This DST can be regarded as an ignited-quenched transition in the inertial suspension. An approximate kinetic theory well recovers the results of the Langevin simulation in the wide range of the v

Xin Fu, Wenjia Jing

We consider the Lame system of linear elasticity with periodically distributed inclusions whose elastic parameters have high contrast compared to the background media. We develop a unified method based on layer potential techniques to quantify three convergence results when some parameters of the elastic inclusions are sent to extreme values. More precisely,

Hitoshi Kiya, Ryota Iijima, MaungMaung Aprilpyone, Yuma Kinoshita

In this paper, we propose a combined use of transformed images and vision transformer (ViT) models transformed with a secret key. We show for the first time that models trained with plain images can be directly transformed to models trained with encrypted images on the basis of the ViT architecture, and the performance of the transformed models is the same a

Sheng Feng, Songqing You, Peng Yang, Fenglei Zhang

We study optical cavity locking for laser stabilization through spatial modulation of the phase front of a light beam. A theoretical description of the underlying principle is developed for this method and special attention is paid to residual amplitude modulation (RAM) caused by experimental imperfections, especially the manufacture errors of the spatial ph

Junbeom Kim, Hoon Lee, Seung-Eun Hong, Seok-Hwan Park

Deep learning (DL) techniques have been intensively studied for the optimization of multi-user multiple-input single-output (MU-MISO) downlink systems owing to the capability of handling nonconvex formulations. However, the fixed computation structure of existing deep neural networks (DNNs) lacks flexibility with respect to the system size, i.e., the number

Aikaterini A. Forouli, Georgios K. Papazoglou, Emmanouil A. Bakirtzis, Pandelis N. Biskas

This paper proposes a novel continuous Local Flexibility Market where active power flexibility located in the distribution system can be traded. The market design engages the Market Operator, the Distribution System Operator and Market Participants with dispatchable assets. The proposed market operates in a single distribution system and considers network co

Hanlun Lei, Xiumin Huang

Nonrestricted hierarchical three-body configurations are common in various scales of astrophysical systems. Dynamical structures of the quadrupole-order resonance (the von Zeipel-Lidov-Kozai resonance) and the octupole-order resonance (the apsidal resonance) under the nonrestricted hierarchical planetary systems are investigated in this work by taking advant

Sujay K. Ashok, Jan Troost

We compute the path integral for a particle on the covering group of SL(2,R) using a decomposition of the Lie algebra into adjoint orbits. We thus intuitively derive the Hilbert space of the particle on the group including discrete and continuous representations. Next, we perform a Lorentzian hyperbolic orbifold of the partition function and relate it to the

Kevissen Sellapillay, Alberto Verga, Giuseppe Di Molfetta

Ergodicity breaking is observed in the blockade regime of Rydberg atoms arrays, in the form of low entanglement eigenstates known as scars, which fail to thermalize. The signature of these states persists in periodically driven systems, where they coexist with an extensive number of chaotic states. Here we investigate a quantum cellular automaton based on th

Mingye Xu, Yali Wang, Yihao Liu, Tong He

Point cloud completion aims to predict complete shape from its partial observation. Current approaches mainly consist of generation and refinement stages in a coarse-to-fine style. However, the generation stage often lacks robustness to tackle different incomplete variations, while the refinement stage blindly recovers point clouds without the semantic aware

Lu Yu, Wei Xiang, Juan Fang, Yi-Ping Phoebe Chen

Recently vision transformer models have become prominent models for a range of vision tasks. These models, however, are usually opaque with weak feature interpretability. Moreover, there is no method currently built for an intrinsically interpretable transformer, which is able to explain its reasoning process and provide a faithful explanation. To close thes

Jing-Jing Wang, Xiang Gao

Sonogenetics can be used as a new alternative for treating arrhythmia due to its advantages of noninvasive, high safety and strong penetration. In the treatment of arrhythmias by sonogenetics, cardiac myocytes are deformed by ultrasonic radiation force. We quantitatively calculated the shape variation of cardiomyocytes under ultrasonic radiation force, and t

Yaojie Cai, Xiaozhe Wang, Geza Joos, Innocent Kamwa

Forced oscillations may jeopardize the secure operation of power systems. To mitigate forced oscillations, locating the sources is critical. In this paper, leveraging on Sparse Identification of Nonlinear Dynamics (SINDy), an online purely data-driven method to locate the forced oscillation is developed. Validations in all simulated cases (in the WECC 179-bu

Timothy Budd, Alicia Castro

The search for scale-invariant random geometries is central to the Asymptotic Safety hypothesis for the Euclidean path integral in quantum gravity. In an attempt to uncover new universality classes of scale-invariant random geometries that go beyond surface topology, we explore a generalization of the mating of trees approach introduced by Duplantier, Miller

Bin He

We construct a new class of entanglement measures named "rotating R\'enyi entropy" by the holographic calculation of a rotating topological black hole belonging to the Petrov type-D class, we compute this kind of entropy for a spherical entangling surface of a vacuum state in the dual CFT. We find that the latter one could be conformally transformed to a the

Joel Davidsson, Fabian Bertoldo, Kristian S. Thygesen, Rickard Armiento

Doping of a two-dimensional (2D) material by impurity atoms occurs \textit{via} two distinct mechanisms: absorption of the dopants by the 2D crystal or adsorption on its surface. To distinguish the relevant mechanism, we systematically dope 53 experimentally synthesized 2D monolayers by 65 different chemical elements in both absorption and adsorption sites.

Miruna T. Cretu, Marjan Mirahmadi, Jesús Pérez-Ríos

We present a detailed study about ion-atom-atom three-body recombination in hydrogen and deuterium plasmas based on classical trajectory calculations in hyperspherical coordinates. Our results, due to the predominant role of the long-range charged-induced dipole interaction, indicate that H$_2^+$ and D$_2^+$ are the main reaction products in the case of hydr

Ahmad K. Omar, Yuyuan Lu, Lijia An, Zhen-Gang Wang

We construct a micromechanical version of an early model for topologically constrained polymers -- a 2D chain amongst point-like uncrossable obstacles -- which allows us to explicitly elucidate the role of topological forces beyond confining the chain to a curvilinear tube-like path. Our simulations reveal that linear relaxation of the contour length \textit

Huan Gao, Yongqiang Wang, Angelia Nedić

With decentralized optimization having increased applications in various domains ranging from machine learning, control, sensor networks, to robotics, its privacy is also receiving increased attention. Existing privacy-preserving approaches for decentralized optimization achieve privacy preservation by patching decentralized optimization with information-tec

Jean-Baptiste Fouvry

Long-range interacting systems irreversibly relax as a result of their finite number of particles, $N$. At order $1/N$, this process is described by the inhomogeneous Balescu--Lenard equation. Yet, this equation exactly vanishes in one-dimensional inhomogeneous systems with a monotonic frequency profile and sustaining only 1:1 resonances. In the limit where

Satoshi Takada, Kazuhiro Hara, Hisao Hayakawa

We demonstrate that discontinuous shear thickening (DST) can occur even in moderately dense, inertial suspensions of hydrodynamically interacting, frictionless soft particles. Using the Lubrication-Friction Discrete Element Method, our simulations reveal that DST can emerge at lower particle densities, provided that both the inertia of the suspended particle

Aranya Bhattacharya, Pratik Nandy, Pingal Pratyush Nath, Himanshu Sahu

Inspired by the universal operator growth hypothesis, we extend the formalism of Krylov construction in dissipative open quantum systems connected to a Markovian bath. Our construction is based upon the modification of the Liouvillian superoperator by the appropriate Lindbladian, thereby following the vectorized Lanczos algorithm and the Arnoldi iteration. T

Tomoya Mori, Takashi Akamatsu, Yuki Takayama, Minoru Osawa

City-size distributions follow an approximate power law in various countries despite high volatility in relative city sizes over time. Our empirical evidence for the United States and Japan indicates that the scaling law stems from a spatial fractal structure owing to the coordination of industrial locations. While the locations of individual industries chan

Luting Wang, Xiaojie Li, Yue Liao, Zeren Jiang

Conventional knowledge distillation (KD) methods for object detection mainly concentrate on homogeneous teacher-student detectors. However, the design of a lightweight detector for deployment is often significantly different from a high-capacity detector. Thus, we investigate KD among heterogeneous teacher-student pairs for a wide application. We observe tha

Jianing Ye, Chenghao Li, Yongqiang Dou, Jianhao Wang

Decentralized execution is one core demand in multi-agent reinforcement learning (MARL). Recently, most popular MARL algorithms have adopted decentralized policies to enable decentralized execution, and use gradient descent as the optimizer. However, there is hardly any theoretical analysis of these algorithms taking the optimization method into consideratio

Jiguang He, Aymen Fakhreddine, George C. Alexandropoulos

Simultaneously transmitting (refracting) and reflecting reconfigurable intelligent surfaces (STAR-RISs) have been recently identified to improve the spectrum/energy efficiency and extend the communication range. However, their potential for enhanced concurrent indoor and outdoor localization has not yet been explored. In this paper, we study the fundamental

B. C. Johnson, M. Stuiber, D. L. Creedon, A. Berhane

The development of a materials platform that exhibits both superconducting and semiconducting properties is an important endeavour for a range of emerging quantum technologies. We investigate the formation of superconductivity in nanowires fabricated with silicon-on-insulator (SOI). Aluminium from deposited contact electrodes is found to interdiffuses with t

Parthak Mehta, Sarthak Mishra, Nikhil Chouhan, Neel Pethani

In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers and engineers that work with deep learning. It has been a ground-breaking technique which can generate new pieces of content of data in a consistent way. The topic of GANs has exploded in popularity due to its applicability in fields like image generation and sy

Junbin Xiao, Pan Zhou, Tat-Seng Chua, Shuicheng Yan

This paper proposes a Video Graph Transformer (VGT) model for Video Quetion Answering (VideoQA). VGT's uniqueness are two-fold: 1) it designs a dynamic graph transformer module which encodes video by explicitly capturing the visual objects, their relations, and dynamics for complex spatio-temporal reasoning; and 2) it exploits disentangled video and text Tra

Yong Wang, Lijun Liu, Shuming Cheng, Li Li

Reconstructing the state of quantum many-body systems is of fundamental importance in quantum information tasks, but extremely challenging due to the curse of dimensionality. In this work, we present an efficient quantum tomography protocol that combines the state-factored with eigenvalue mapping to address the rank-deficient issue and incorporates a momentu

Shuangrui Ding, Rui Qian, Hongkai Xiong

Contrastive learning has shown promising potential in self-supervised spatio-temporal representation learning. Most works naively sample different clips to construct positive and negative pairs. However, we observe that this formulation inclines the model towards the background scene bias. The underlying reasons are twofold. First, the scene difference is us

Zbigniew Palmowski, Lewis Ramsden, Apostolos D. Papaioannou

In this paper we develop the Gerber-Shiu theory for the classic and dual discrete risk processes in a Markovian (regime switching) environment. In particular, by expressing the Gerber-Shiu function in terms of potential measures of an upward (downward) skip-free discrete-time and discrete-space Markov Additive Process (MAP), we derive closed form expressions

Zeqiang Li, Yujuan Wang, Xiucai Huang

In this paper, a new yet indirect performance guaranteed framework is established to address the distributed tracking control problem for networked uncertain nonlinear strict-feedback systems with unknown time-varying gains under a directed interaction topology. The proposed framework involves two steps: In the first one, a fully distributed robust filter is

Saeid K. Dehkordi, Lorenzo Gaudio, Mari Kobayashi, Giuseppe Caire

Motivated by automotive applications, we consider joint radar sensing and data communication for a system operating at millimeter wave (mmWave) frequency bands, where a Base Station (BS) is equipped with a co-located radar receiver and sends data using the Orthogonal Time Frequency Space (OTFS) modulation format. We consider two distinct modes of operation.

R. Brasser, G. Pichierri, V. Dobos, A. C. Barr

The ultracool M-dwarf star TRAPPIST-1 is surrounded by seven planets configured in a resonant chain. Transit-timing variations have shown that the planets are caught in multiple three-body resonances and that their orbits are slightly eccentric, probably caused by resonant forcing. The current values of the eccentricities could be a remnant from their format

Dimitri Loutchko

The ability of a chemical reaction network to generate itself by catalyzed reactions from constantly present environmental food sources is considered a fundamental property in origin-of-life research. Based on Kaufmann's autocatalytic sets, Hordijk and Steel have constructed the versatile formalism of catalytic reaction systems (CRS) to model and to analyze

Hao Liu, Bin Chen, Bo Wang, Chunpeng Wu

Recently, many semi-supervised object detection (SSOD) methods adopt teacher-student framework and have achieved state-of-the-art results. However, the teacher network is tightly coupled with the student network since the teacher is an exponential moving average (EMA) of the student, which causes a performance bottleneck. To address the coupling problem, we

Xinyu Huang, Youcai Zhang, Ying Cheng, Weiwei Tian

Vision-Language Pre-training (VLP) with large-scale image-text pairs has demonstrated superior performance in various fields. However, the image-text pairs co-occurrent on the Internet typically lack explicit alignment information, which is suboptimal for VLP. Existing methods proposed to adopt an off-the-shelf object detector to utilize additional image tag

Takuya Kamijima, Sosuke Ito, Andreas Dechant, Takahiro Sagawa

A system can be driven out of equilibrium by both time-dependent and nonconservative forces, which gives rise to a decomposition of the dissipation into two non-negative components, called the excess and housekeeping entropy productions. We derive thermodynamic uncertainty relations for the excess and housekeeping entropy. These can be used as tools to estim

Sadman Sakib Enan, Michael Fulton, Junaed Sattar

In this paper, we present a motion-based robotic communication framework that enables non-verbal communication among autonomous underwater vehicles (AUVs) and human divers. We design a gestural language for AUV-to-AUV communication which can be easily understood by divers observing the conversation unlike typical radio frequency, light, or audio based AUV co

Pritam Das, Young-Su Lee, Seung-Cheol Lee, Satadeep Bhattacharjee

Hydrogen-based fuels demand high-density storage that can operate under ambient temperatures. Pd and its alloys are the most investigated metal hydrides for hydrogen fuel cell applications. This study presented an alternative Pd alloy for hydrogen storage that can store and release hydrogen at room temperature. The surface of the most studied Pd (110) was mo

Zaijun Chen, Alexander Sludds, Ronald Davis, Ian Christen

Deep neural networks (DNNs) are reshaping the field of information processing. With their exponential growth challenging existing electronic hardware, optical neural networks (ONNs) are emerging to process DNN tasks in the optical domain with high clock rates, parallelism and low-loss data transmission. However, to explore the potential of ONNs, it is necess

Offer Kella

For two independent, almost surely finite random variables, independence of their minimum (time) and the event that one of them is either greater, equal or less than the other (cause) is completely characterized. It is shown that, other than for trivial cases where, almost surely, one random variable is greater than or equal to the other, this happens if and

Hanbin Hong, Yuan Hong

Randomized smoothing has achieved great success for certified robustness against adversarial perturbations. Given any arbitrary classifier, randomized smoothing can guarantee the classifier's prediction over the perturbed input with provable robustness bound by injecting noise into the classifier. However, all of the existing methods rely on fixed i.i.d. pro

Xin Li, Kuangyin Deng, Benedetta Flebus

Several works have recently addressed the emergence of exceptional points (EPs), i.e., spectral singularities of non-Hermitian Hamiltonians, in the long-wavelength dynamics of coupled magnetic systems. Here, by focusing on the driven magnetization dynamics of a van der Waals ferromagnetic bilayer, we show that exceptional points can appear over extended port

Bo-Hae Im, Wonwoong Lee

We study certain types of Fuchsian groups of the first kind denoted by $R(N)$, which coincide with the Fricke groups or the arithmetic Hecke triangle groups of low levels. We find all elliptic points and cusps of $R(p)$ for a prime $p$, and prove that there is a one-to-one correspondence between the set of equivalence classes of elliptic points of $R(p)$ and

Xiou Ge, Yun-Cheng Wang, Bin Wang, C. -C. Jay Kuo

Translation, rotation, and scaling are three commonly used geometric manipulation operations in image processing. Besides, some of them are successfully used in developing effective knowledge graph embedding (KGE) models such as TransE and RotatE. Inspired by the synergy, we propose a new KGE model by leveraging all three operations in this work. Since trans