May 2020 arXiv papers — page 39

Carl R. Shapiro, Dennice F. Gayme, Charles Meneveau

A quantitative understanding of the dominant mechanisms that govern the generation and decay of the counter-rotating vortex pair (CVP) produced by yawed wind turbines is needed to fully realize the potential of yawing for wind farm power maximization and regulation. Observations from large eddy simulations (LES) of yawed wind turbines in the turbulent atmosp

Jingwei Huang, Chiyu Max Jiang, Baiqiang Leng, Bin Wang

We present MeshODE, a scalable and robust framework for pairwise CAD model deformation without prespecified correspondences. Given a pair of shapes, our framework provides a novel shape feature-preserving mapping function that continuously deforms one model to the other by minimizing fitting and rigidity losses based on the non-rigid iterative-closest-point

Khuram Naveed, Naveed ur Rehman

A multivariate signal denoising method is proposed which employs a novel multivariate goodness of fit (GoF) test that is applied at multiple data scales obtained from discrete wavelet transform (DWT). In the proposed multivariate GoF test, we first utilize squared Mahalanobis distance (MD) measure to transform input multivariate data residing in M-dimensiona

Vahe Galstyan, Kabir Husain, Fangzhou Xiao, Arvind Murugan

Key enzymatic processes in biology use the nonequilibrium error correction mechanism called kinetic proofreading to enhance their specificity. Kinetic proofreading typically requires several dedicated structural features in the enzyme, such as a nucleotide hydrolysis site and multiple enzyme-substrate conformations that delay product formation. Such requirem

Omid Daei, Keivan Navi, Mariam Zomorodi-Moghadam

The main objective of this paper is to improve the communication costs in distributed quantum circuits. To this end, we present a method for generating distributed quantum circuits from monolithic quantum circuits in such a way that communication between partitions of a distributed quantum circuit is minimized. Thus, the communication between distributed com

Yuichiro Koyama, Bhiksha Raj

Acoustic beamformers have been widely used to enhance audio signals. Currently, the best methods are the deep neural network (DNN)-powered variants of the generalized eigenvalue and minimum-variance distortionless response beamformers and the DNN-based filter-estimation methods that are used to directly compute beamforming filters. Both approaches are effect

Asem Ghaleb, Karthik Pattabiraman

Security attacks targeting smart contracts have been on the rise, which have led to financial loss and erosion of trust. Therefore, it is important to enable developers to discover security vulnerabilities in smart contracts before deployment. A number of static analysis tools have been developed for finding security bugs in smart contracts. However, despite

Yuichiro Koyama, Oluwafemi Azeez, Bhiksha Raj

Although deep-learning-based methods have markedly improved the performance of speech separation over the past few years, it remains an open question how to integrate multi-channel signals for speech separation. We propose two methods, namely, early-fusion and late-fusion methods, to integrate multi-channel information based on the time-domain audio separati

Yuichiro Koyama, Tyler Vuong, Stefan Uhlich, Bhiksha Raj

Recently, deep neural networks (DNNs) have been successfully used for speech enhancement, and DNN-based speech enhancement is becoming an attractive research area. While time-frequency masking based on the short-time Fourier transform (STFT) has been widely used for DNN-based speech enhancement over the last years, time domain methods such as the time-domain

Antonio D'Innocente, Francesco Cappio Borlino, Silvia Bucci, Barbara Caputo

Despite impressive progress in object detection over the last years, it is still an open challenge to reliably detect objects across visual domains. Although the topic has attracted attention recently, current approaches all rely on the ability to access a sizable amount of target data for use at training time. This is a heavy assumption, as often it is not

Everton M. C. Abreu, Jorge Ananias Neto, Edésio M. Barboza

The Barrow entropy appears from the fact that the black hole surface can be modified due to quantum gravitational outcome. The measure of this perturbation is given by a new exponent $\Delta$. In this letter we have shown that, from the standard mathematical form of the equipartition theorem, we can relate it with Barrow entropy. From this equivalence, we ha

Sheriffo Ceesay, Adam Barker, Yuhui Lin

Understanding and predicting the performance of big data applications running in the cloud or on-premises could help minimise the overall cost of operations and provide opportunities in efforts to identify performance bottlenecks. The complexity of the low-level internals of big data frameworks and the ubiquity of application and workload configuration param

Stephan Weis

We prove that every symmetric separable state admits a convex decomposition into symmetric pure product states. While the result is not new in itself, here we focus on convex geometry. We discuss the decomposition in the context of numerical ranges and ground state problems of infinite bosonic systems.

I. V. Chelovekov, S. A. Grebenev, A. S. Pozanenko, P. Yu. Minaev

A systematic search for cosmic gamma-ray bursts (GRBs) and other short hard X-ray events in the archival data from the IBIS/ISGRI telescope of the INTEGRAL observatory over 2003-2018 has been carried out. Seven previously unknown GRBs have been recorded in the telescope field of view; all of them have been localized with an accuracy < 2 arcmin. These events

Oussama Melkemi, Mohamed Zerguine

Inspired by the recently published paper \cite{Hassainia-Hmidi}, the current paper investigates the local well-posedness for the generalized $2d-$Boussinesq system in the setting of regular/singular vortex patch. Under the condition that the initial vorticity $\omega_{0}={\bf 1}_{D_0}$, with $\partial D_0$ is a Jordan curve with a H\"older regularity $C^{1+\

Anastasiya Ivanova, Sergey Omelchenko, Ekaterina Kotliarova, Vladislav Matyukhin

In this paper, we consider the problem of restoring the correspondence matrix based on the observations of real correspondences in Moscow. Following the conventional approach, the transport network is considered as a directed graph whose edges correspond to road sections and the graph vertices correspond to areas that the traffic participants leave or enter.

Guruprasad Raghavan, Jiayi Li, Matt Thomson

Biological neural networks have evolved to maintain performance despite significant circuit damage. To survive damage, biological network architectures have both intrinsic resilience to component loss and also activate recovery programs that adjust network weights through plasticity to stabilize performance. Despite the importance of resilience in technology

Ehsan Azmoodeh, Yuliya Mishura, Farzad Sabzikar

The present paper investigates the effects of tempering the power law kernel of moving average representation of a fractional Brownian motion (fBm) on some local and global properties of this Gaussian stochastic process. Tempered fractional Brownian motion (TFBM) and tempered fractional Brownian motion of the second kind (TFBMII) are the processes that are c

Carmen Galaz-García

A pseudomodular group is a discrete subgroup $\Gamma \leq PGL(2,\mathbb{Q})$ which is not commensurable with $PSL(2,\mathbb{Z})$ and has cusp set precisely $\mathbb{Q}\cup\{\infty\}$. The existence of such groups was proved by Long and Reid. Later, Lou, Tan and Vo constructed two infinite families of non-commensurable pseudomodular groups which they called j

Ke Li, Haifeng Nie, Huifu Gao, Xin Yao

Knee points, characterised as their smallest trade-off loss at all objectives, are attractive to decision makers in multi-criterion decision-making. In contrast, other Pareto-optimal solutions are less attractive since a small improvement on one objective can lead to a significant degradation on at least one of the other objectives. In this paper, we propose

Wennan Chang, Xinyu Zhou, Yong Zang, Chi Zhang

Parameter estimation of mixture regression model using the expectation maximization (EM) algorithm is highly sensitive to outliers. Here we propose a fast and efficient robust mixture regression algorithm, called Component-wise Adaptive Trimming (CAT) method. We consider simultaneous outlier detection and robust parameter estimation to minimize the effect of

Francisco-Shu Kitaura, Andrés Balaguera-Antolínez, Francesco Sinigaglia, Marcos Pellejero-Ibáñez

This work investigates the connection between the cosmic web and the halo distribution through the gravitational potential at the field level. We combine three fields of research, cosmic web classification, perturbation theory expansions of the halo bias, and halo (galaxy) mock catalogue making methods. In particular, we use the invariants of the tidal field

Fadi Salo, MohammadNoor Injadat, Ali Bou Nassif, Aleksander Essex

Cloud computing has become a powerful and indispensable technology for complex, high performance and scalable computation. The exponential expansion in the deployment of cloud technology has produced a massive amount of data from a variety of applications, resources and platforms. In turn, the rapid rate and volume of data creation has begun to pose signific

Redi Haderi

In this work we propose a realization of Lurie's prediction that inner fibrations $p: X \rightarrow A$ are classified by $A$-indexed diagrams in a ``higher category" whose objects are $\infty$-categories, morphisms are correspondences between them and higher morphisms are higher correspondences. We will obtain this as a corollary of a more general result whi

Sergei Manzhos, Pavlo Golub

We study the dependence of kinetic energy densities (KED) on density-dependent variables that have been suggested in previous works on kinetic energy functionals (KEF) for orbital-free DFT (OF-DFT). We focus on the role of data distribution and on data and regressor selection. We compare unweighted and weighted linear and Gaussian process regressions of KED

Dogeun Jang, Ki-Yong Kim

We report multicycle, narrowband, terahertz radiation at 14.8 THz produced by phase-matched optical rectification of femtosecond laser pulses in bulk lithium niobate (LiNbO$_3$) crystals. Our experiment and simulation show that the output terahertz energy greatly enhances when the input laser pulse is highly chirped, contrary to a common optical rectificatio

Michael Larsen, Aner Shalev

Let $A$ be a residually finite dimensional algebra (not necessarily associative) over a field $k$. Suppose first that $k$ is algebraically closed. We show that if $A$ satisfies a homogeneous almost identity $Q$, then $A$ has an ideal of finite codimension satisfying the identity $Q$. Using well known results of Zelmanov, we conclude that, if a residually fin

Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

We study finite-armed stochastic bandits where the rewards of each arm might be correlated to those of other arms. We introduce a novel phased algorithm that exploits the given structure to build confidence sets over the parameters of the true bandit problem and rapidly discard all sub-optimal arms. In particular, unlike standard bandit algorithms with no st

Sijie Zhu, Taojiannan Yang, Chen Chen

Street-to-aerial image geo-localization, which matches a query street-view image to the GPS-tagged aerial images in a reference set, has attracted increasing attention recently. In this paper, we revisit this problem and point out the ignored issue about image alignment information. We show that the performance of a simple Siamese network is highly dependent

A. Chouikh, T. Said, M. Bennai

In this paper, we develop a new classical simulation of quantum bit (qubit) by use of analog components in order to be able to simulate the quantum properties such as the superposition of states. As part of this new approach, we have also implemented many logical gates (Pauli-X, Hadamard, and Conditional phase-shift gates). Simulation of Hadamard and Conditi

Selvi Kara

Weighted simplicial complexes (WSCs) are powerful tools for describing weighted cloud data or networks with weighted nodes. In this paper, we propose a novel approach to study WSCs via the concept of polarization. Polarization of a WSC allows one to construct a new (unweighted) simplicial complex which coincides with an object called the mixed wreath product

Yuval Filmus, Meena Mahajan, Gaurav Sood, Marc Vinyals

We study the MaxRes rule in the context of certifying unsatisfiability. We show that it can be exponentially more powerful than tree-like resolution, and when augmented with weakening (the system MaxResW), p-simulates tree-like resolution. In devising a lower bound technique specific to MaxRes (and not merely inheriting lower bounds from Res), we define a ne

Wenyu Chen, Rahul Mazumder

We present new large-scale algorithms for fitting a subgradient regularized multivariate convex regression function to $n$ samples in $d$ dimensions -- a key problem in shape constrained nonparametric regression with applications in statistics, engineering and the applied sciences. The infinite-dimensional learning task can be expressed via a convex quadrati

Hongyu Miao, Qianmiao Gao, Han Feng, Chengxue Zhong

The sudden onset of the coronavirus (SARS-CoV-2) pandemic has resulted in tremendous loss of human life and economy in more than 210 countries and territories around the world. While self-protections such as wearing mask, sheltering in place and quarantine polices and strategies are necessary for containing virus transmission, tens of millions people in the

O. Cohen, C. Garraffo, S. Moschou, J. Drake

We investigate the space environment conditions near the Earth-size planet TOI~700~d using a set of numerical models for the stellar corona and wind, the planetary magnetosphere, and the planetary ionosphere. We drive our simulations using a scaled-down stellar input and a scaled-up solar input in order to obtain two independent solutions. We find that for t

Thierry Chekouo, Sandra E. Safo

Cardiovascular diseases (CVD), including atherosclerosis CVD (ASCVD), are multifactorial diseases that present a major economic and social burden worldwide. Tremendous efforts have been made to understand traditional risk factors for ASCVD, but these risk factors account for only about half of all cases of ASCVD. It remains a critical need to identify nontra

Joy Morris, Josip Smolcic

A number of authors have studied the question of when a graph can be represented as a Cayley graph on more than one nonisomorphic group. The work to date has focussed on a few special situations: when the groups are $p$-groups; when the groups have order $pq$; when the Cayley graphs are normal; or when the groups are both abelian. In this paper, we construct

Seema, Akhil Tayal, S. M. Amir, Sabine Pütter

We studied the growth behavior, structural, electronic, and magnetic properties of cobalt nitride (Co-N) thin films deposited using direct current (dc) and high power impulse magnetron sputtering (HiPIMS) processes. The N$_2$ partial gas flow (\pn) was varied in close intervals to achieve the optimum conditions for the growth of tetra cobalt nitride (\tcn) p

Pooja Rani, Sebastiano Panichella, Manuel Leuenberger, Mohammad Ghafari

Previous studies have characterized code comments in various programming languages to support better program comprehension activities and maintenance tasks. However, very few studies have focused on understanding developer practices to write comments. None of them has compared such developer practices to the standard comment guidelines to study the extent to

YuChen Xiang, Carin Basirun, Joshua Chou, Majid E. Warkiani

Brillouin spectroscopy is a century-old technique that has recently received renewed interest, as modern instrumentation has transformed it into a powerful contactless and label-free probe of micromechanical properties for biomedical applications. In particular, to fully harness the non-contact and non-destructive nature of Brillouin imaging, there is strong

Kenneth R. Davidson, Benjamin Passer

We use Arveson's notion of strongly peaking representation to generalize uniqueness theorems for free spectrahedra and matrix convex sets which admit minimal presentations. A fully compressed separable operator system necessarily generates the C*-envelope and is such that the identity is the direct sum of strongly peaking representations. In particular, a fu

Xingyuan Pan, Maitrey Mehta, Vivek Srikumar

Various natural language processing tasks are structured prediction problems where outputs are constructed with multiple interdependent decisions. Past work has shown that domain knowledge, framed as constraints over the output space, can help improve predictive accuracy. However, designing good constraints often relies on domain expertise. In this paper, we

Michael W. Toomey, Foteini Oikonomou, Kohta Murase

We present a search for high-energy $\gamma$-ray emission from 566 Active Galactic Nuclei at redshift $z > 0.2$, from the 2WHSP catalog of high-synchrotron peaked BL Lac objects with eight years of Fermi-LAT data. We focus on a redshift range where electromagnetic cascade emission induced by ultra-high-energy cosmic rays can be distinguished from leptonic em

Honglin Bao, Wolfgang Banzhaf

The complexity of cooperative behavior is a crucial issue in multiagent-based social simulation. In this paper, an agent-based model is proposed to study the evolution of cooperative hunting behaviors in an artificial society. In this model, the standard hunting game of stag is modified into a new situation with social hierarchy and penalty. The agent societ

Lauren Mancia, Mauro Rodriguez, Jonathan Sukovich, Scott Haskell

Understanding the acoustic cavitation threshold is essential for minimizing cavitation bioeffects in diagnostic ultrasound and for controlling cavitation--mediated tissue ablation in focused ultrasound procedures. The homogeneous cavitation threshold is an intrinsic material property of recognized importance to a variety of applications requiring cavitation

Silas L. Carvalho, Alexander Condori

In this work, we show that if $f$ is a uniformly continuous map defined over a Polish metric space, then the set of $f$-invariant measures with zero metric entropy is a $G_\delta$ set (in the weak topology). In particular, this set is generic if the set of $f$-periodic measures is dense in the set of $f$-invariant measures. This settles a conjecture posed by

Nikesh Bajaj, Jesús Requena Carrión, Francesco Bellotti

Auditory attention to natural speech is a complex brain process. Its quantification from physiological signals can be valuable to improving and widening the range of applications of current brain-computer-interface systems, however it remains a challenging task. In this article, we present a dataset of physiological signals collected from an experiment on au

Jie Yang, Jiarou Fan, Yiru Wang, Yige Wang

Attribute recognition is a crucial but challenging task due to viewpoint changes, illumination variations and appearance diversities, etc. Most of previous work only consider the attribute-level feature embedding, which might perform poorly in complicated heterogeneous conditions. To address this problem, we propose a hierarchical feature embedding (HFE) fra

Viktor Domazetoski, Axel Masó-Puigdellosas, Trifce Sandev, Vicenç Méndez

We study a diffusion process on a three-dimensional comb under stochastic resetting. We consider three different types of resetting: global resetting from any point in the comb to the initial position, resetting from a finger to the corresponding backbone and resetting from secondary fingers to the main fingers. The transient dynamics along the backbone in a

Abdul Moeed

Developments in Brain Computer Interfaces (BCIs) are empowering those with severe physical afflictions through their use in assistive systems. Common methods of achieving this is via Motor Imagery (MI), which maps brain signals to code for certain commands. Electroencephalogram (EEG) is preferred for recording brain signal data on account of it being non-inv

V. S. Rychkov

Volterra integral operators ${\cal A}=\sum_{k=0}^m {\cal A}_k$, $({\cal A}_k f)(x)= a_k (x)\int_0^x t^k f(t) \,dt$, are studied acting between weighted $L_2$ spaces on $(0,+\infty)$. Under certain conditions on the weights and functions $a_k$, it is shown that $\cal A$ is bounded if and only if each ${\cal A}_k$ is bounded. This result is then applied to des

O. V. Kompaniiets, A. A. Vasylenko

We present the results of X-ray spectral analysis of the Seyfert type 2 galaxy Mrk 417 observed by the NuSTAR (3-60 keV) and the Swift/BAT (14-150) observatories. The NuSTAR data shows a good fit with a baseline model which composed of an absorbed cutoff power-law component and reflected emission from the cold neutral medium. We found that the spectrum is st

Garrett Wendel, Luis Martinez, Martin Bojowald

If time is described by a fundamental process rather than a coordinate, it interacts with any physical system that evolves in time. The resulting dynamics is shown here to be consistent provided the fundamental period of the time system is sufficiently small. A strong upper bound T_C < 10^{-33}s of the fundamental period of time, several orders of magnitude

Andrés Cañas, Víctor Marín, Héctor Pinedo

In this article we construct the inverse semigroup of equivalence classes of partial Galois abelian extensions of a commutative ring R with same group G, called the Harrison partial inverse semigroup.

Hai-Jun Tian

We report the discovery of a young (only 30-40\,Myr) snake-like structure (dubbed a stellar "snake") in the solar neighborhood from {\it Gaia} DR2. The average distance of this structure is about 310\,pc from us. Both the length and width are over 200\,pc, but the thickness is only about 80\,pc. The "snake" has one tail and two dissolving cores, which can be

Stephen Theriault

We analyze a general family of fibrations which, after looping, have sections. Methods are developed to determine the homotopy type of the fibre and the homotopy classes of the map from the fibre to the base. The methods are driven by applications to two-cones, Poincare Duality complexes, the connected sum operation, and polyhedral products.

S. Ahmad, M. Zubair, O. Jalil, M. Q. Mehmood

Binding energy calculation in two-dimensional (2D) materials is crucial in determining their electronic and optical properties pertaining to enhanced Coulomb interactions between charge carriers due to quantum confinement and reduced dielectric screening. Based on full solutions of the Schr\"odinger equation in screened hydrogen model with a modified Coulomb

David Bevan

We introduce a new natural notion of convergence for permutations at any specified scale, in terms of the density of patterns of restricted width. In this setting we prove that limits may be chosen independently at a countably infinite number of scales.

Srisha M. V. Rao, S. K. Karthick, Abhinav Anand

Elliptic nozzle geometry is attractive for mixing enhancement of supersonic jets. However, jet dynamics, such as flapping, gives rise to high-intensity tonal sound. We experimentally manipulate the supersonic elliptic jet morphology by using two sharp-tipped lobes. The lobes are placed on either end of the minor axis in an elliptic nozzle. The design Mach nu

G. Bono, V. F. Braga, J. Crestani, M. Fabrizio

We collected over 6000 high-resolution spectra of four dozen field RR Lyrae (RRL) variables pulsating either in the fundamental (39 RRab) or in the first overtone (9 RRc) mode. We measured radial velocities (RVs) of four strong metallic and four Balmer lines along the entire pulsational cycle and derived RV amplitudes with accuracies better than 1$-$2~\kmsec

Oleg S. Ugolnikov, Boris V. Kozelov, Sergey V. Pilgaev, Alexey V. Roldugin

The intensive polar stratospheric vortex in the Arctic that shifted to northern Europe in the winter of 2019-2020 caused low temperatures and the frequent occurrence of polar stratospheric clouds followed by a significant decrease in the total ozone content. Polarimetry and multi-color photometry using all-sky cameras in Lovozero (Murmansk Region, Russia, 68

Saša Ceci, Marin Vukšić, Branimir Zauner

The broad non-strange meson $f_0$(500) is considered to be a non-Breit-Wigner resonance. It is generally assumed that if a resonance is broad it can hardly be described by a Breit-Wigner form. We show here that is not true neither for the broad Z boson, nor for the much narrower $\Delta(1232)$, and explain why the $f_0$(500) fits with them perfectly. Key dif

Grigoris Panotopoulos, Ilídio Lopes

We report constraints on the nucleon-dark matter particle cross section using the internal luminosity of observed white dwarf stars in the globular cluster Messier 4. Our results cover the parameter space corresponding to relatively light dark matter particles, in the mass range $0.1~GeV-5~GeV$, which is known to be very difficult to be probed by direct dark

M. Pizzardo, S. Di Gioia, A. Diaferio, C. De Boni

We use a new spherical accretion recipe tested on N-body simulations to measure the observed mass accretion rate (MAR) of 129 clusters in the Cluster Infall Regions in the Sloan Digital Sky Survey (CIRS) and in the Hectospec Cluster Survey (HeCS). The observed clusters cover the redshift range of $0.01<z<0.30$ and the mass range of $\sim 10^{14}-10^{15} {h^{

Kai-Kit Wong, Arman Shojaeifard, Kin-Fai Tong, Yangyang Zhang

Over the past decades, multiple antenna technologies have appeared in many different forms, most notably as multiple-input multiple-output (MIMO), to transform wireless communications for extraordinary diversity and multiplexing gains. The variety of technologies has been based on placing a number of antennas at fixed locations which dictates the fundamental

Haoteng Tang, Guixiang Ma, Yurong Chen, Lei Guo

Recent years have witnessed the emergence and development of graph neural networks (GNNs), which have been shown as a powerful approach for graph representation learning in many tasks, such as node classification and graph classification. The research on the robustness of these models has also started to attract attentions in the machine learning field. Howe

Ilya D. Shkredov, Jozsef Solymosi

In this paper we show examples for applications of the Bombieri-Lang conjecture in additive combinatorics, giving bounds on the cardinality of sumsets of squares and higher powers of integers. Using similar methods we give bounds on the sum-product problem for matchings.

Vasileios Petridis

In this paper PREMONN (PREdictive MOdular Neural Networks) model/architecture is generalized to functions of two variables and to non-Euclidean spaces. It is presented in the context of 3D invariant shape recognition and texture recognition. PREMONN uses local relation, it is modular and exhibits incremental learning. The recognition process can start at any

Abhiram Soori

An integral part of scattering theory calculations in continuum quantum systems involves identifying appropriate boundary conditions in addition to writing down the correct Hamiltonian. In the simplest problem of scattering in one dimensional lattice, scattering due to an on-site potential and scattering due to an unequal bond (in otherwise translationally i

Thomas K. Dasaklis, Fran Casino, Constantinos Patsakis

Human beings produce electronic waste (e-waste) at an unprecedented pace. Mobile phones and other inter-connected smart devices make a significant contribution to the generation of e-waste. Reverse logistics (RL) activities play an essential role in managing mobile phones during their end-of-life. However, remanufacturing and/or refurbishing of mobile phones

Frank Hessel, Lars Almon, Flor Álvarez

Low-power wide-area networks (LPWANs) are becoming an integral part of the Internet of Things. As a consequence, businesses, administration, and, subsequently, society itself depend on the reliability and availability of these communication networks. Released in 2015, LoRaWAN gained popularity and attracted the focus of security research, revealing a number

Timothy C. Burness, Adam R. Thomas

Let $G$ be a finite primitive permutation group on a set $\Omega$ with nontrivial point stabilizer $G_{\alpha}$. We say that $G$ is extremely primitive if $G_{\alpha}$ acts primitively on each of its orbits in $\Omega \setminus \{\alpha\}$. In earlier work, Mann, Praeger and Seress have proved that every extremely primitive group is either almost simple or o

Leonid Bedratyuk

The aim of this paper is to clear up the problem of the connection between the 3D geometric moments invariants and the invariant theory, considering a problem of describing of the 3D geometric moments invariants as a problem of the classical invariant theory. Using the remarkable fact that the groups $SO(3)$ and $SL(2)$ are locally isomorphic, we reduced the

Timothy C. Burness, Adam R. Thomas

Let $G$ be a finite primitive permutation group on a set $\Omega$ with nontrivial point stabilizer $G_{\alpha}$. We say that $G$ is extremely primitive if $G_{\alpha}$ acts primitively on each of its orbits in $\Omega \setminus \{\alpha\}$. These groups arise naturally in several different contexts and their study can be traced back to work of Manning in the

Long Chen, Zhihua Liu, Lei Tong, Zheheng Jiang

In recent years, deep learning based methods have achieved promising performance in standard object detection. However, these methods lack sufficient capabilities to handle underwater object detection due to these challenges: (1) Objects in real applications are usually small and their images are blurry, and (2) images in the underwater datasets and real app

Nick Bezhanishvili, Marcello Bonsangue, Helle Hvid Hansen, Dexter Kozen

Stone-type dualities provide a powerful mathematical framework for studying properties of logical systems. They have recently been fruitfully explored in understanding minimisation of various types of automata. In Bezhanishvili et al. (2012), a dual equivalence between a category of coalgebras and a category of algebras was used to explain minimisation. The

Zachariah Addison, E. J. Mele

We develop a theory for the nonlinear time domain response of a Weyl semimetal driven by an ultrafast optical pulse. At quadratic order in the driving field we find that the response near a band inversion transition contains a coherent oscillating component proportional field intensity and with a frequency that can be tuned over a wide range (from THz to the

Mahdieh Abbasi, Denis Laurendeau, Christian Gagne

In the object detection task, merging various datasets from similar contexts but with different sets of Objects of Interest (OoI) is an inexpensive way (in terms of labor cost) for crafting a large-scale dataset covering a wide range of objects. Moreover, merging datasets allows us to train one integrated object detector, instead of training several ones, wh

Hamza Abudayyeh, Boaz Lubotzky, Anastasia Blake, Jun Wang

Deterministic coupling between photonic nodes in a quantum network is an essential step towards implementing various quantum technologies. The omnidirectionality of free-standing emitters, however, makes this coupling highly inefficient, in particular if the distant nodes are coupled via low numerical aperture (NA) channels such as optical fibers. This limit

Tobias Christiani

Weighted minwise hashing is a standard dimensionality reduction technique with applications to similarity search and large-scale kernel machines. We introduce a simple algorithm that takes a weighted set $x \in \mathbb{R}_{\geq 0}^{d}$ and computes $k$ independent minhashes in expected time $O(k \log k + \Vert x \Vert_{0}\log( \Vert x \Vert_1 + 1/\Vert x \Ve

VSR Veeravasarapu, Abhishek Goel, Deepak Mittal, Maneesh Singh

Contour shape alignment is a fundamental but challenging problem in computer vision, especially when the observations are partial, noisy, and largely misaligned. Recent ConvNet-based architectures that were proposed to align image structures tend to fail with contour representation of shapes, mostly due to the use of proximity-insensitive pixel-wise similari

Yuxi Liu, Xin Lin, Shaowen Qin

The impact of the outbreak of COVID-19 on health has been widely concerned. Disease risk assessment, prediction, and early warning have become a significant research field. Previous research suggests that there is a relationship between air quality and the disease. This paper investigated the impact of the atmospheric environment on the basic reproduction nu

Behnam Najafi, Katherine G. Young, Jonathan Bath, Ard A. Louis

The success of DNA nanotechnology has been driven by the discovery of novel structural motifs with a wide range of shapes and uses. We present a comprehensive study of the T-motif, a 3-armed, planar, right-angled junction that has been used in the self-assembly of DNA polyhedra and periodic structures. The motif is formed through the interaction of a bulge l

Xidong Mu, Yuanwei Liu, Li Guo, Jiaru Lin

The fundamental intelligent reflecting surface (IRS) deployment problem is investigated for IRS-assisted networks, where one IRS is arranged to be deployed in a specific region for assisting the communication between an access point (AP) and multiple users. Specifically, three multiple access schemes are considered, namely non-orthogonal multiple access (NOM

Zhifang Gu, He Chen, Pingping Xu, Yonghui Li

Achieving ultra-reliable, low-latency and secure communications is essential for realizing the industrial Internet of Things (IIoT). Non-coherent massive multiple-input multiple-output (MIMO) is one of promising techniques to fulfill ultra-reliable and low-latency requirements. In addition, physical layer authentication (PLA) technology is particularly suita

Yi-Xin Xiao, Zong-Quan Zhou, Yu Ma, Tian-Shu Yang

Praseodymium (Pr$^{3+}$) ions doped in the site 1 of yttrium orthosilicate (Y$_2$SiO$_5$) has been widely employed as the photonic quantum memory due to their excellent optical coherence and spin coherence. While praseodymium ions occupying the site 2 in Y$_2$SiO$_5$ crystal have better optical coherence as compared with those at site 1, which may enable bet

Ran Ben Basat, Xiaoqi Chen, Gil Einziger, Shir Landau Feibish

Network-wide traffic analytics are often needed for various network monitoring tasks. These measurements are often performed by collecting samples at network switches, which are then sent to the controller for aggregation. However, performing such analytics without ``overcounting'' flows or packets that traverse multiple measurement switches is challenging.

Marvin Künnemann, Dániel Marx

To study the question under which circumstances small solutions can be found faster than by exhaustive search (and by how much), we study the fine-grained complexity of Boolean constraint satisfaction with size constraint exactly $k$. More precisely, we aim to determine, for any finite constraint family, the optimal running time $f(k)n^{g(k)}$ required to fi

Seraina Glaus, Margarete Mühlleitner, Jonas Müller, Shruti Patel

In this work we present an update to a previous calculation of the Next-to-Leading Order (NLO) corrections to the Vector Dark Matter (VDM) direct detection cross section. The model under investigation is a minimal extension of the Standard Model (SM) with one extra vector boson and one extra complex scalar field, where the vector is the DM candidate. We have

Rawad Mezher, Joe Ghalbouni, Joseph Dgheim, Damian Markham

A defining feature in the field of quantum computing is the potential of a quantum device to outperform its classical counterpart for a specific computational task. By now, several proposals exist showing that certain sampling problems can be done efficiently quantumly, but are not possible efficiently classically, assuming strongly held conjectures in compl

Elena Bandini, Tiziano De Angelis, Giorgio Ferrari, Fausto Gozzi

Adopting a probabilistic approach we determine the optimal dividend payout policy of a firm whose surplus process follows a controlled arithmetic Brownian motion and whose cash-flows are discounted at a stochastic dynamic rate. Dividends can be paid to shareholders at unrestricted rates so that the problem is cast as one of singular stochastic control. The s

Mahboobeh Parsapoor

Accurate forecasting of an electroencephalogram (EEG) time series is crucial for the correct diagnosis of neurological disorders such as seizures and epilepsy. Since the EEG time series is chaotic, most traditional machine learning algorithms have failed to forecast its next steps accurately. Thus, we suggest a model, which has formed by taking inspiration f

E. Szegedi-Elek, P. Ábrahám, L. Wyrzykowski, M. Kun

We present optical-infrared photometric and spectroscopic observations of Gaia18dvy, located in the Cygnus OB3 association at a distance of 1.88 kpc. The object was noted by the Gaia alerts system when its lightcurve exhibited a $\gtrsim$4 mag rise in 2018-2019. The brightening was also observable at mid-infared wavelengths. The infrared colors of Gaia18dvy

Zhanqiang Bai, Wei Xiao, Xun Xie

In this paper, we present a uniform formula of Lusztig's $ \mathbf{a}$-functions on classical Weyl groups. Then we obtain an efficient algorithm for the Gelfand-Kirillov dimensions of simple highest weight modules of classical Lie algebras, whose highest weight is not necessarily regular or integral. To deal with type $ D $, we prove an interesting property

Jin Zhang, Hai-Ming Zhang, Ying-Ying Gan, Ting-Feng Yi

Compact steep-spectrum sources (CSSs) likely represent a population of young radio-loud active galactic nuclei (AGNs) and have been identified as gamma-ray emitting sources. We present a comprehensive analysis of their gamma-ray emission observed with Fermi/LAT and establish their broadband spectral energy distributions (SEDs). We derive their jet properties

Artyom Kosmarski, Nikolay Gordiychuk

In this paper, we propose a novel framework for a scholarly journal, a token-curated registry (TCR). This model originates in the field of blockchain and cryptoeconomics and is essentially a decentralized system where tokens (digital currency) are used to incentivize quality curation of information. TCR is an automated way to create lists of any kind where d

Alex Bartel, Henri Johnston, Hendrik W. Lenstra

The main purpose of the paper is to formulate a probabilistic model for Arakelov class groups in families of number fields, offering a correction to the Cohen--Lenstra--Martinet heuristic on ideal class groups. To that end, we show that Chinburg's Omega(3) conjecture implies tight restrictions on the Galois module structure of oriented Arakelov class groups.

Alireza Aghamohammadi, Seyed-Hassan Mirian-Hosseinabadi

Predictive Mutation Testing (PMT) is a technique to predict whether a mutant will be killed by using machine learning approaches. Researchers have proposed various machine learning methods for PMT under the cross-project setting. However, they did not consider the impact of uncovered mutants. A mutant is uncovered if the statement on which the mutant is gene

Ben Lewis

Th\^eo1 is a frequency stability statistic which is similar to the Allan variance but can provide stability estimates at longer averaging factors and with higher confidence. However, the calculation of Th\^eo1 is significantly slower than the Allan variance, particularly for large data sets, due to a worse computational complexity. A faster algorithm for cal

Colin Guillarmou, Antti Kupiainen, Rémi Rhodes, Vincent Vargas

The conformal bootstrap hypothesis is a powerful idea in theoretical physics which has led to spectacular predictions in the context of critical phenomena. It postulates an explicit expression for the correlation functions of a conformal field theory in terms of its 3-point correlation functions. In this paper we give the first mathematical proof of the conf