November 2020 arXiv papers — page 12

Seyed Mohsen Hosseini

A novel method for feature fusion in convolutional neural networks is proposed in this paper. Different feature fusion techniques are suggested to facilitate the flow of information and improve the training of deep neural networks. Some of these techniques as well as the proposed network can be considered a type of Directed Acyclic Graph (DAG) Network, where

Abdelkader Mokkadem, Mariane Pelletier, Louis Raimbault

Mining frequent itemsets and association rules is an essential task within data mining and data analysis. In this paper, we introduce PrefRec, a recursive algorithm for finding frequent itemsets and association rules. Its main advantage is its recursiveness with respect to the items. It is particularly efficient for updating the mining process when new items

Truong Thu Huong, Ta Phuong Bac, Dao M. Long, Bui D. Thang

Internet of Things and its applications are becoming commonplace with more devices, but always at risk of network security. It is therefore crucial for an IoT network design to identify attackers accurately, quickly and promptly. Many solutions have been proposed, mainly concerning secure IoT architectures and classification algorithms, but none of them have

Wen-Hua Chen

This paper presents a stability analysis tool for model predictive control (MPC) where control action is generated by optimising a cost function over a finite horizon. Stability analysis of MPC with a limited horizon but without terminal weight is a well known challenging problem. We define a new value function based on an auxiliary one-step optimisation rel

Palash Dey, Arnab Maiti, Amatya Sharma

In liquid democracy, each voter either votes herself or delegates her vote to some other voter. This gives rise to what is called a delegation graph. To decide the voters who eventually votes along with the subset of voters whose votes they give, we need to resolve the cycles in the delegation graph. This gives rise to the Resolve Delegation problem where we

Tullio Ceccherini-Silberstein, Michel Coornaert, Xuan Kien Phung

Let $G$ be a group and let $A$ be a finite-dimensional vector space over an arbitrary field $K$. We study finiteness properties of linear subshifts $\Sigma \subset A^G$ and the dynamical behavior of linear cellular automata $\tau \colon \Sigma \to \Sigma$. We say that $G$ is of $K$-linear Markov type if, for every finite-dimensional vector space $A$ over $K$

Alberto Poncelas, Jan Buts, James Hadley, Andy Way

Building Machine Translation (MT) systems for low-resource languages remains challenging. For many language pairs, parallel data are not widely available, and in such cases MT models do not achieve results comparable to those seen with high-resource languages. When data are scarce, it is of paramount importance to make optimal use of the limited material ava

Alexey Samokhin

For the KdV-Burgers equations for cylindrical and spherical waves the development of a regular profile starting from an equilibrium under a periodic perturbation at the boundary is studied. The equation describes a medium which is both dissipative and dispersive. For an appropriate combination of dispersion and dissipation the asymptotic profile looks like a

Igor Frenkel, Matvei Libine

In this paper we study left and right n-regular functions that originally were introduced in [FL4]. When n=1, these functions are the usual quaternionic left and right regular functions. We show that n-regular functions satisfy most of the properties of the usual regular functions, including the conformal invariance under the fractional linear transformation

U. A. Acharya, C. Aidala, Y. Akiba, M. Alfred

In 2015, the PHENIX collaboration has measured very forward ($\eta>6.8$) single-spin asymmetries of inclusive neutrons in transversely polarized proton-proton and proton-nucleus collisions at a center of mass energy of 200 GeV. A previous publication from this data set concentrated on the nuclear dependence of such asymmetries. In this measurement the explic

Ritesh Goenka, Shu-Jie Cao, Chau-Wai Wong, Ajit Rajwade

Group testing can save testing resources in the context of the ongoing COVID-19 pandemic. In group testing, we are given $n$ samples, one per individual, and arrange them into $m < n$ pooled samples, where each pool is obtained by mixing a subset of the $n$ individual samples. Infected individuals are then identified using a group testing algorithm. In this

Siyi Deng, Yang Ning, Jiwei Zhao, Heping Zhang

We consider the estimation problem in high-dimensional semi-supervised learning. Our goal is to investigate when and how the unlabeled data can be exploited to improve the estimation of the regression parameters of linear model in light of the fact that such linear models may be misspecified in data analysis. We first establish the minimax lower bound for pa

Leonardo A. Lerer

We extend the notion of absolute subsets of Betti moduli spaces of smooth algebraic varieties to the case of normal varieties. As a consequence we prove that twisted cohomology jump loci in rank one over a normal variety are a finite union of translated subtori. We show that the same holds for jump loci twisted by a unitary local system in the case where the

Boris S. Bardin, Alexander S. Kuleshov

In 1890 German mathematician and physicist W. Hess found new special case of integrability of Euler - Poisson equations of motion of a heavy rigid body with a fixed point. In 1892 P. A. Nekrasov proved that the solution of the problem of motion of a heavy rigid body with a fixed point under Hess conditions reduces to integrating the second order linear diffe

Ghadeer O. Ghosheh, Bana Alamad, Kai-Wen Yang, Faisil Syed

Existing prognostic tools mainly focus on predicting the risk of mortality among patients with coronavirus disease 2019. However, clinical evidence suggests that COVID-19 can result in non-mortal complications that affect patient prognosis. To support patient risk stratification, we aimed to develop a prognostic system that predicts complications common to C

Zihuan Liu, Tapabrate Maiti, Andrew R. Bender

The transition from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of great interest to clinical researchers. This phenomenon also serves as a valuable data source for quantitative methodological researchers developing new approaches for classification. However, the growth of machine learning (ML) approaches for classification may falsely lea

Christopher Eur, Tara Fife, José Alejandro Samper, Tim Seynnaeve

We show that the reciprocal maximal likelihood degree (rmld) of a diagonal linear concentration model $\mathcal L \subseteq \mathbb{C}^n$ of dimension $r$ is equal to $(-2)^r\chi_M( \textstyle\frac{1}{2})$, where $\chi_M$ is the characteristic polynomial of the matroid $M$ associated to $\mathcal L$. In particular, this establishes the polynomiality of the r

Jon-Ivar Skullerud

This is a translation into English of my Masters thesis (hovedoppgave) from 1991. The main topic of the thesis is the relation between fundamental physics and philosophy, and a discussion of several possible ontologies of quantum field theory.

Yuan Xu

Highly localized kernels constructed by orthogonal polynomials have been fundamental in recent development of approximation and computational analysis on the unit sphere, unit ball and several other regular domains. In this work we first study homogeneous spaces that are assumed to contain highly localized kernels and establish a framework for approximation

Olga Szewczyk, Piotr Pala, Karol Tarnowski, Jacek Olszewski

We report the design of a microstructured silica-based fiber for widely tunable soliton self-frequency shift, suitable for pumping with two most common fiber laser wavelengths: 1.04 {\mu}m and 1.55 {\mu}m. Depending on the pump source, the output spectrum can be continuously tuned up to 1.67 {\mu}m (pump at 1.04 {\mu}m) or 1.95 {\mu}m (pump at 1.55 {\mu}m) i

Fabian Müller, Akaki Rusetsky, Tiansu Yu

Using the framework of non-relativistic effective field theory, the finite-volume ground-state energy shift is calculated up-to-and-including $O(L^{-6})$ for the system of three pions in the channel with the total isospin $I=1$. The relativistic corrections are included perturbatively, up to the same order in the inverse of the box size $L$. The obtained exp

Sirui Bi, Jiaxin Zhang, Guannan Zhang

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, m

Karin Baur, Dusko Bogdanic, Jian-Rong Li

The category ${\rm CM}(B_{k,n}) $ of Cohen-Macaulay modules over a quotient $B_{k,n}$ of a preprojective algebra provides a categorification of the cluster algebra structure on the coordinate ring of the Grassmannian variety of $k$-dimensional subspaces in $\mathbb C^n$, \cite{JKS16}. Among the indecomposable modules in this category are the rank $1$ modules

Valentin Lychagin, Mikhail Roop

In this paper, we analyze various types of critical phenomena in one-dimensional gas flows described by Euler equations. We give a geometrical interpretation of thermodynamics with a special emphasis on phase transitions. We use ideas from the geometrical theory of PDEs, in particular, symmetries and differential constraints to find solutions to the Euler sy

James Davies

We prove that there are intersection graphs of axis-aligned boxes in $\mathbb{R}^3$ and intersection graphs of straight lines in $\mathbb{R}^3$ that have arbitrarily large girth and chromatic number.

I. O. Kuznetsov, P. F. Kartsev

We present the efficient and universal numerical method for simulation of interacting quantum gas kinetics on a finite momentum lattice, based on the Boltzmann equation for occupation numbers. Usually, the study of models with two-particle interaction generates the excessive amount of terms in the equations essentially limiting the possible system size. Here

Jiaxin Zhang, Congjie Wei, Chenglin Wu

For multilayer materials in thin substrate systems, interfacial failure is one of the most challenges. The traction-separation relations (TSR) quantitatively describe the mechanical behavior of a material interface undergoing openings, which is critical to understand and predict interfacial failures under complex loadings. However, existing theoretical model

Dan Han, Stanislav Molchanov, Yanjmaa Jutmaan

In this paper, we study the Galton-Watson process in the random environment for the particular case when the number of the offsprings in each generation has the fractional linear generation function with random parameters. In this case, the distribution of $N_t$, the number of particles at the moment time $t=0,1,2,\cdots$ can be calculated explicitly. We pre

U. A. Acharya, C. Aidala, Y. Akiba, M. Alfred

We present a measurement of the transverse single-spin asymmetry for $\pi^0$ and $\eta$ mesons in $p^\uparrow$$+$$p$ collisions in the pseudorapidity range $|\eta|<0.35$ and at a center-of-mass energy of 200 GeV with the PHENIX detector at the Relativistic Heavy Ion Collider. In comparison with previous measurements in this kinematic region, these results ha

Zhongwei Shen

This paper is concerned with Darcy's law for an incompressible viscous fluid flowing in a porous medium. We establish the sharp $O(\sqrt{\e})$ convergence rate in a periodically perforated and bounded domain in $R^d$ for $d\ge 2$, where $\e$ represents the size of solid obstacles. This is achieved by constructing two boundary correctors to control the bounda

B. P. Osilenker

In the paper we study the multipliers of Fourier series in polynomials orthogonal in continuous-discrete Sobolev's spaces. Multiplier Theorem for Fourier-Sobolev series is obtained. This result is based on the representation of the Fej\'er kernel, on the construction of the "humpbacked majorant" and weighted estimates of maximal functions.

Randall M. Feenstra, Grayson R. Frazier, Yi Pan, Stefan Fölsch

Acquisition and analysis is described for scanning tunneling spectroscopy data acquired from a monolayer of WSe$_2$ grown on epitaxial graphene on SiC. Curve fitting of the data is performed, in order to deduce band-edge energies. In addition to describing the details of the theoretical curves used for the fitting, the acquisition and analysis methods are al

Pouya Aminaie, Poorya Aminaie

We present a step by step definition of Profinet and Profibus. We introduced different types of each of the two communication protocols. Then, the topology and performance of each one has been described individually. Finally, the properties of them have been compared to show that which one has a better performance in the industry.

Robert Underwood

Let $p$ be prime, let $K$ be a non-archimedean local field of characteristic $p$ and let $C_p^3$ denote the elementary abelian group of order $p^3$. We give a complete classification of Hopf orders in the $K$-Hopf algebra $(K[C_p^3])^*$ and under a mild condition compute their dual Hopf orders in the group ring $K[C_p^3]$.

I. G. Rebollo, F. C. Rodrigues-Machado, W. Wright, G. J. Melin

We report a deterministic 2D material (2DM) transfer method to assemble any-stacking-order heterostructures incorporating suspended ultra-thin 2D materials, such as single-layer graphene (SLG) and bilayer graphene (BLG). The transfer procedure relies on a single-step preparation nitrocellulose micro-stamp, which combines both outstanding adhesion and softnes

Massimo Bartoletti, Stefano Lande, Maurizio Murgia, Roberto Zunino

Smart contracts - computer protocols that regulate the exchange of crypto-assets in trustless environments - have become popular with the spread of blockchain technologies. A landmark security property of smart contracts is liquidity: in a non-liquid contract, it may happen that some assets remain frozen, i.e. not redeemable by anyone. The relevance of this

Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu

The data-driven nature of deep learning (DL) models for semantic segmentation requires a large number of pixel-level annotations. However, large-scale and fully labeled medical datasets are often unavailable for practical tasks. Recently, partially supervised methods have been proposed to utilize images with incomplete labels in the medical domain. To bridge

Steve Isaac, Delaram Kahrobaei

We examine two public key exchange protocols proposed recently by Grigoriev and Shpilrain (arXiv:1811.06386), which use tropical algebra. We introduce a fast attack on the first protocol, and we show that the second protocol cannot be implemented as described.

Takashi Komatsu, Norio Konno, Iwao Sato

Chinta, Jorgenson and Karlsson introduced a generalized version of the determinant formula for the Ihara zeta function associated to finite or infinite regular graphs. On the other hand, Konno and Sato obtained a formula of the characteristic polynomial of the Grover matrix by using the determinant expression for the second weighted zeta function of a finite

Kristina Oganesyan

We show that for a nonnegative monotone sequence $\{c_k\}$ the condition $c_kk\to 0$ is sufficient for uniform convergence of the series $\sum_{k=1}^{\infty}c_k\sin k^{\alpha} x$ on any bounded set for $\alpha\in (0,2)$, and for an odd natural $\alpha$ it is sufficient for uniform convergence on the whole $\mathbb{R}$. Moreover, the latter assertion still ho

Barbara Csima, Dino Rossegger, Zhi Ying "Daniel" Yu

We study reductions well suited to compare structures and classes of structures with respect to properties based on enumeration reducibility. We introduce the notion of a positive enumerable functor and study the relationship with established reductions based on functors and alternative definitions.

Rui Morais, Paul Crocker, Simao Melo de Sousa

This paper presents Adamastor, a new low latency and scalable decentralized anonymous payment system, which is an extension of Ring Confidential Transactions (RingCT) that is compatible with consensus algorithms that use Delegated Proof of Stake (DPoS) as a defense mechanism against Sybil attacks. Adamastor also includes a new Decoy Selection Algorithm (DSA)

Reza Vatan Meidanshahi, Stephen M. Goodnick, Dragica Vasileska

In this paper, we explore the effect of H and its bonding configurations on the defect state density and orbital localization of hydrogenated amorphous Si (a-Si:H)/crystalline Si (c-Si) heterostructures using density functional theory (DFT) studies of model interfaces between amorphous silicon (a- Si)/a-Si:H and c-Si. To model the atomic configuration of a-S

W. D. Jennings, C. A. Watkinson, F. B. Abdalla

Three-point and high-order clustering statistics of the high-redshift 21cm signal contain valuable information about the Epoch of Reionization. We present 3PCF-Fast, an optimised code for estimating the three-point correlation function of 3D pixelised data such as the outputs from numerical and semi-numerical simulations. After testing 3PCF-Fast on data with

A. Mazel, I. Stuhl, Y. Suhov

We study dense packings of disks and related Gibbs distributions representing high-density phases in the hard-core model on unit triangular, honeycomb and square lattices. The model is characterized by a Euclidean exclusion distance $D>0$ and a value of fugacity $u>0$. We use the Pirogov-Sinai theory to study the Gibbs distributions for a general $D$ when $u

Jianpeng Zhang, Yutong Xie, Yan Wang, Yong Xia

Automated and accurate 3D medical image segmentation plays an essential role in assisting medical professionals to evaluate disease progresses and make fast therapeutic schedules. Although deep convolutional neural networks (DCNNs) have widely applied to this task, the accuracy of these models still need to be further improved mainly due to their limited abi

Lela Bones, Garrett Fowler, Lisa Schneider, Ryan M. Shifler

Property $\mathcal{O}$ for an arbitrary complex, Fano manifold $X$, is a statement about the eigenvalues of the linear operator obtained from the quantum multiplication of the anticanonical class of $X$. Conjecture $\mathcal{O}$ is a conjecture that Property $\mathcal{O}$ holds for any Fano variety. Pasquier listed the smooth non-homogeneous horospherical va

Renan Gross

We study the scenery reconstruction problem on the $d$-dimensional torus, proving that a criterion on Fourier coefficients obtained by Matzinger and Lember (2006) for discrete cycles applies also in continuous spaces. In particular, with the right drift, Brownian motion can be used to reconstruct any scenery. To this end, we prove an injectivity property of

Gaoping Long, Chun-Yen Lin

To clarify the geometric information encoded in the $SO(D+1)$ spin-network states for the higher dimensional loop quantum gravity, we generalize the twisted-geometry parametrization of the $SU(2)$ phase space for $(1+3)$ dimensional loop quantum gravity to that of the $SO(D+1)$ phase space for the all-dimensional case. The Poisson structure in terms of the t

Philip Kennerberg, Magnus Wiktorsson

We show that non continuous Dirichlet processes, defined as in \cite{NonCont} are closed under a wide family of locally Lipschitz continuous maps (similar to the time-homogeneous variants of the maps considered in \cite{Low}) thus extending Theorem 2.1. from that paper. We provide an It\^o formula for these transforms and apply it to study of how $[f(X^n)-f(

Yuhui Xu, Lingxi Xie, Cihang Xie, Jieru Mei

Batch normalization (BN) is a fundamental unit in modern deep networks, in which a linear transformation module was designed for improving BN's flexibility of fitting complex data distributions. In this paper, we demonstrate properly enhancing this linear transformation module can effectively improve the ability of BN. Specifically, rather than using a singl

Alexandru Chirvasitu, Mateusz Wasilewski

We prove a number of results to the effect that generic quantum graphs (defined via operator systems as in the work of Duan-Severini-Winter / Weaver) have few symmetries: for a Zariski-dense open set of tuples $(X_1,\cdots,X_d)$ of traceless self-adjoint operators in the $n\times n$ matrix algebra the corresponding operator system has trivial automorphism gr

Karena X. Cai, Tung Phan-Minh, Soon-Jo Chung, Richard M. Murray

The ability to guarantee safety and progress for all vehicles is vital to the success of the autonomous vehicle industry. We present a framework for designing autonomous vehicle behavior in a way that is safe and guarantees progress for all agents. In this paper, we first introduce a new game paradigm which we term the quasi-simultaneous game. We then define

Claudio Grimaldi

Probabilistic arguments about the existence of technological life beyond Earth traditionally refer to the Drake equation to draw possible estimates of the number of technologically advanced civilizations releasing, either intentionally or not, electromagnetic emissions in the Milky Way. Here, we introduce other indicators than Drake's number $N_D$ to develop

Isa Inuwa-Dutse

Conventional preventive measures during pandemic include social distancing and lockdown. Such measures in the time of social media brought about a new set of challenges - vulnerability to the toxic impact of online misinformation is high. A case in point is the prevailing COVID-19; as the virus propagates, so does the associated misinformation and fake news

Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang

We develop a probabilistic machine learning method, which formulates a class of stochastic neural networks by a stochastic optimal control problem. An efficient stochastic gradient descent algorithm is introduced under the stochastic maximum principle framework. Numerical experiments for applications of stochastic neural networks are carried out to validate

Spyros Angelopoulos, Malachi Voss

We study the setting in which a mobile agent must locate a hidden target in a bounded or unbounded environment, with no information about the hider's position. In particular, we consider online search, in which the performance of the search strategy is evaluated by its worst case competitive ratio. We introduce a multi-criteria search problem in which the se

Tarun Yenamandra, Ayush Tewari, Florian Bernard, Hans-Peter Seidel

We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expressions of the frontal face, but also models the entire head, including hair. We collect a new dataset consisting of 64 people with different expressions and hairstyles to train i3

Jie Ma, Tianyun Tang

Akin to the Erd\H{o}s-Rademacher problem, Linial and Morgenstern made the following conjecture in tournaments: for any $d\in (0,1]$, among all $n$-vertex tournaments with $d\binom{n}{3}$ many 3-cycles, the number of 4-cycles is asymptotically minimized by a special random blow-up of a transitive tournament. Recently, Chan, Grzesik, Kr\'al' and Noel introduce

Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka

We address the problem of estimating a high quality dense depth map from a single RGB input image. We start out with a baseline encoder-decoder convolutional neural network architecture and pose the question of how the global processing of information can help improve overall depth estimation. To this end, we propose a transformer-based architecture block th

V. V. Borzov, E. V. Damaskinsky

In this paper, we calculate the Mandel parameter $Q_M$ for an oscillator-like system generated by generalized Chebyshev polynomials \cite{01}, \cite{02}, \cite{03}. The sign of the Mandel parameter $Q_M$ characterizes the deviation of the excitation statistics from the Poisson one. This work is a continuation of our works \cite{04}, \cite{05}.

Fatih Altay, Guillermo Ramon Sanchez, Yanli James, Stephen V. Faraone

Alzheimer's disease is one of the diseases that mostly affects older people without being a part of aging. The most common symptoms include problems with communicating and abstract thinking, as well as disorientation. It is important to detect Alzheimer's disease in early stages so that cognitive functioning would be improved by medication and training. In t

İsmail Sağlam

An ideal triangulation of a singular flat surface is a geodesic triangulation such that its vertex set is equal to the set of singular points of the surface. Using the fact that each pair of points in a surface has a finite number of geodesics having length $\leq L$ connecting them, where $L$ is any positive number, we prove that each singular flat surface h

Abdul Wahab, Muhammad Anas Tahir, Naveed Iqbal, Faisal Shafait

Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency. Electricity demand profiles can vary drastically from one region to another on diurnal, seasonal and yearly scale. Hence to devise a load forecasting technique that can yield the best estimates

Huu Phuoc Le, Mohab Safey El Din

We design a new algorithm for solving parametric systems having finitely many complex solutions for generic values of the parameters. More precisely, let $f = (f_1, \ldots, f_m)\subset \mathbb{Q}[y][x]$ with $y = (y_1, \ldots, y_t)$ and $x = (x_1, \ldots, x_n)$, $V\subset \mathbb{C}^{t+n}$ be the algebraic set defined by $f$ and $\pi$ be the projection $(y,

Abhishek Malik, Benjamin P. Moster, Christian Obermeier

We introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. We aim to exploit some of these methods to improve the conventional algorithm based approaches presently used in astrophysics to detect exop

Soumick Chatterjee, Alessandro Sciarra, Max Dünnwald, Steffen Oeltze-Jafra

In MRI, motion artefacts are among the most common types of artefacts. They can degrade images and render them unusable for accurate diagnosis. Traditional methods, such as prospective or retrospective motion correction, have been proposed to avoid or alleviate motion artefacts. Recently, several other methods based on deep learning approaches have been prop

Mohit Lamba, Atul Balaji, Kaushik Mitra

The ability to capture good quality images in the dark and near-zero lux conditions has been a long-standing pursuit of the computer vision community. The seminal work by Chen et al. [5] has especially caused renewed interest in this area, resulting in methods that build on top of their work in a bid to improve the reconstruction. However, for practical util

Quan Huu Cap, Hitoshi Iyatomi, Atsushi Fukuda

Medical images have been indispensable and useful tools for supporting medical experts in making diagnostic decisions. However, taken medical images especially throat and endoscopy images are normally hazy, lack of focus, or uneven illumination. Thus, these could difficult the diagnosis process for doctors. In this paper, we propose MIINet, a novel image-to-

Christian Wahl, Marvin Hoffmann, Thilo vom Hoevel, Frank Vewinger

Bose-Einstein condensation, an effect long known for material particles as cold atomic gases, has in recent years also been observed for photons in microscopic optical cavitites. Here, we report absorption and emission spectroscopic measurements on the lowest electronic transition ($5\text{p}^6 \rightarrow 5\text{p}^5 6\text{s}$) of xenon, motivated by the s

Yong-Liang Xiao

Unitary learning is a backpropagation that serves to unitary weights update in deep complex-valued neural network with full connections, meeting a physical unitary prior in diffractive deep neural network ([DN]2). However, the square matrix property of unitary weights induces that the function signal has a limited dimension that could not generalize well. To

M. R. Setare, S. N. Sajadi

Flat Space Cosmology (FSC) spacetimes are exact solutions of 3D gravity theories. In this work, we study phase transition between FSC spacetimes and Hot Flat Spacetimes (HFS) in general minimal massive gravity and exotic general massive gravity. We show that similar to topological massive gravity the tunneling occurs between two spacetimes by comparing their

Gaëtan Gras, Anthony Martin, Jeong Woon Choi, Félix Bussières

We present the physical model for the entropy source of a quantum random number generator chip based on the quantum fluctuations of the photon number emitted by light-emitting diodes. This model, combined with a characterization of the chip, estimates a quantum min-entropy of over 0.98 per bit without post-processing. Finally, we show with our model that the

Fred Diamond

We carry out a thorough study of weight-shifting operators on Hilbert modular forms in characteristic $p$, generalizing the author's prior work with Sasaki to the case where $p$ is ramified in the totally real field $F$. In particular we use the partial Hasse invariants and Kodaira-Spencer filtrations defined by Reduzzi and Xiao to improve on Andreatta and G

Charles Bordenave, Bastien Dubail

In operator algebra, the linearization trick is a technique that reduces the study of a non-commutative polynomial evaluated at elements of an algebra A to the study of a polynomial of degree one, evaluated on the enlarged algebra A x M r (C), for some integer r. We introduce a new instance of the linearization trick which is tailored to study a finitely sup

Samet Uzun, Nazim Kemal Ure

This paper introduces a probabilistic guidance approach for the swarm-to-swarm engagement problem. The idea is based on driving the controlled swarm towards an adversary swarm, where the adversary swarm aims to converge to a stationary distribution that corresponds to a defended base location. The probabilistic approach is based on designing a Markov chain f

Zakaria Mhammedi

Acquisition of data is a difficult task in many applications of machine learning, and it is only natural that one hopes and expects the population risk to decrease (better performance) monotonically with increasing data points. It turns out, somewhat surprisingly, that this is not the case even for the most standard algorithms that minimize the empirical ris

Jinlu Li, Yanghai Yu, Weipeng Zhu

The failure of uniform dependence on the data is an interesting property of classical solution for a hyperbolic system. In this paper, we consider the solution map of the Cauchy problem to the 2D viscous shallow water equations which is a hyperbolic-parabolic system. We prove that the solution map of this problem is not uniformly continuous in Sobolev spaces

Edward Lockhart, Neil Burch, Nolan Bard, Sebastian Borgeaud

We introduce a human-compatible reinforcement-learning approach to a cooperative game, making use of a third-party hand-coded human-compatible bot to generate initial training data and to perform initial evaluation. Our learning approach consists of imitation learning, search, and policy iteration. Our trained agents achieve a new state-of-the-art for bridge

Zhe Chu, Mengkai Hu, Xiangyu Chen

Recently, deep learning has been successfully applied to robotic grasp detection. Based on convolutional neural networks (CNNs), there have been lots of end-to-end detection approaches. But end-to-end approaches have strict requirements for the dataset used for training the neural network models and it's hard to achieve in practical use. Therefore, we propos

T. Petrushevska

Strong lensing by galaxy clusters can be used to significantly expand the survey reach, thus allowing observation of magnified high-redshift supernovae that otherwise would remain undetected. Strong lensing can also provide multiple images of the galaxies that lie behind the clusters. Detection of strongly lensed Type Ia supernovae (SNe Ia) is especially use

E. Ievlev

This thesis is devoted to studying strong coupling phenomena (and confinement in particular) in supersymmetric gauge theories. The central object of investigation is the non-Abelian string that is responsible for the "instead-of-confinement" phase for monopoles in 4D ${\mathcal N} = 2$ supersymmetric QCD with the U($N$) gauge group and $N_f$ flavors of quark

Souheil Fenghour, Daqing Chen, Kun Guo, Perry Xiao

The performance of automated lip reading using visemes as a classification schema has achieved less success compared with the use of ASCII characters and words largely due to the problem of different words sharing identical visemes. The Generative Pre-Training transformer is an effective autoregressive language model used for many tasks in Natural Language P

D. J. Carter, D. J. Dunstan, W. Just, O. F. Bandtlow

Euler solved the problem of the collapse of tall thin columns under unexpectedly small loads in 1744. The analogous problem of the collapse of circular elastic rings or tubes under external pressure was mathematically intractable and only fully solved recently. In the context of carbon nanotubes, an additional phenomenon was found experimentally and in atomi

Lorenzo Fornari, Enrico Laeng, Vittorino Pata

We propose a rather elementary method to compute a certain family of integrals on the half line, depending on the integer parameters $n\geq q\geq 1$.

Letian Yu, Haoran Xue, Baile Zhang

Chiral edge modes in photonic topological insulators host great potential to realize slow-light waveguides with topological protection. Increasing the winding of the chiral edge mode around the Brillouin zone can lead to broadband topological slow light with ultra-low group velocity. However, this effect usually requires careful modifications on a relatively

Freja Nordsiek, Eberhard Bodenschatz, Gholamhossein Bagheri

In the case of airborne diseases, pathogen copies are transmitted by droplets of respiratory tract fluid that are exhaled by the infectious and, after partial or full drying, inhaled as aerosols by the susceptible. The risk of infection in indoor environments is typically modelled using the Wells-Riley model or a Wells-Riley-like formulation, usually assumin

Thomas Sutter

With the releases of Android Oreo and Pie, Android introduced some background execution limitations for apps. Google restricted the execution of background services to save energy and to prevent apps from running endlessly in the background. Moreover, access to the device's sensors was changed and a new concept named foreground service has been introduced. A

Ilija Buric, Volker Schomerus, Evgeny Sobko

In this work we construct the crossing symmetry equations for mixed correlators of two long and two BPS operators in 4D $\mathcal{N}=1$ SCFTs. The analysis presented here illustrates how our general group theoretic approach to long superblocks and tensor structures of superconformal algebras can be applied to give explicit ready-to-use expressions. In the ca

Johannes Gasteiger, Shankari Giri, Johannes T. Margraf, Stephan Günnemann

Many important tasks in chemistry revolve around molecules during reactions. This requires predictions far from the equilibrium, while most recent work in machine learning for molecules has been focused on equilibrium or near-equilibrium states. In this paper we aim to extend this scope in three ways. First, we propose the DimeNet++ model, which is 8x faster

Silvia Ferrario Ravasio, Giovanni Limatola, Paolo Nason

Infrared renormalons in Quantum Chromodynamics are associated with non-perturbative corrections to short distance observables. Linear renormalons, i.e. such that the associated non-perturbative corrections scale like one inverse power of the hard scale, can affect at a non-negligible level even the very high-energy phenomena studied at the Large Hadron Colli

Javier Argüello-Luengo, Tao Shi, Alejandro González-Tudela

Using quantum systems to efficiently solve quantum chemistry problems is one of the long-sought applications of near-future quantum technologies. In a recent work, ultra-cold fermionic atoms have been proposed for these purposes by showing us how to simulate in an analog way the quantum chemistry Hamiltonian projected in a lattice basis set. Here, we continu

Elnaz Gholipour, Béla Vizvári, Zoltán Lakner

Sovereign debt ratings provided by rating agencies measure the solvency of a country, as gauged by a lender or an investor. It is an indication of the risk involved in investment, and should be determined correctly and in a well timed manner. The present study reconstructs sovereign debt ratings through logical analysis of data, which is based on the theory

Nikita Kavokine, Roland R. Netz, Lydéric Bocquet

Nanofluidics has firmly established itself as a new field in fluid mechanics, as novel properties have been shown to emerge in fluids at the nanometric scale. Thanks to recent developments in fabrication technology, artificial nanofluidic systems are now being designed at the scale of biological nanopores. This ultimate step in scale reduction has pushed the

Filip Turoboś

Following the train of thought from our previous paper we revisit the theorems of Pongsriiam and Termwuttipong by further developing their characterization of certain property-preserving functions using the so-called triangle triplets. We develop more general analogues of disjoint sum lemmas for broader classes of metric-type spaces and we apply these to ext

Umberto Martínez-Peñas

We construct six new explicit families of linear maximum sum-rank distance (MSRD) codes, each of which has the smallest field sizes among all known MSRD codes for some parameter regime. Using them and a previous result of the author, we provide two new explicit families of linear partial MDS (PMDS) codes with smaller field sizes than previous PMDS codes for

Doron Gepner

We conjecture the inversion relations for thermalized solvable interaction round the face (IRF) two dimensional lattice models. We base ourselves on an ansatz for the Baxterization described by the author in the 90's. We solve these inversion relations in the four main regimes of the models, to give the free energy of the models, in these regimes. We use the

Hui-Po Wang, Ning Yu, Mario Fritz

While Generative Adversarial Networks (GANs) show increasing performance and the level of realism is becoming indistinguishable from natural images, this also comes with high demands on data and computation. We show that state-of-the-art GAN models -- such as they are being publicly released by researchers and industry -- can be used for a range of applicati

Maciej Bocheński

In this paper we give the classification of standard compact Clifford-Klein forms corresponding to triples (g,h,l) such that g = h+l and g is a sum of two absolutely simple ideals. The classification is done using Onishchik's results concerning semisimple decompositions of semisimple Lie algebras. Using this classification we obtain new examples of reductive

Chongzhi Wang, Lulu Pan, Haibin Shao, Dewei Li

In contrast with the scalar-weighted networks, where bipartite consensus can be achieved if and only if the underlying signed network is structurally balanced, the structural balance property is no longer a graph-theoretic equivalence to the bipartite consensus in the case of signed matrix-weighted networks. To re-establish the relationship between the netwo