June 2020 arXiv papers — page 27

Víctor Zapatero, Marcos Curty

The malicious manipulation of quantum key distribution (QKD) hardware is a serious threat to its security, as, typically, neither end users nor QKD manufacturers can validate the integrity of every component of their QKD system in practice. One possible approach to re-establish the security of QKD is to use a redundant number of devices. Following this idea,

Levent Sagun, Caglar Gulcehre, Adriana Romero, Negar Rostamzadeh

Science meets Engineering in Deep Learning took place in Vancouver as part of the Workshop section of NeurIPS 2019. As organizers of the workshop, we created the following report in an attempt to isolate emerging topics and recurring themes that have been presented throughout the event. Deep learning can still be a complex mix of art and engineering despite

Nikolaj Glazunov

The purpose of this paper is to survey some of the important results on Langlands program, global fields, $D$-shtukas and finite shtukas which have influenced the development of algebra and number theory. It is intended to be selective rather than exhaustive, as befits the occasion of the 80-th birthday of Yakovlev, 75-th birthday of Vostokov and 75-th birth

Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento

The success of deep learning, a brain-inspired form of AI, has sparked interest in understanding how the brain could similarly learn across multiple layers of neurons. However, the majority of biologically-plausible learning algorithms have not yet reached the performance of backpropagation (BP), nor are they built on strong theoretical foundations. Here, we

David Butler, Chris Hicks, James Bell, Carsten Maple

In the fight against Covid-19, many governments and businesses are in the process of evaluating, trialling and even implementing so-called immunity passports. Also known as antibody or health certificates, there is a clear demand for any technology that could allow people to return to work and other crowded places without placing others at risk. One of the m

Yu. B. Ivanov

Global polarization of $Λ$ and $\barΛ$ is calculated based on the axial vortical effect (AVE). Simulations are performed within the model of the three-fluid dynamics. Equations of state with the deconfinement transition result in a good agreement with STAR data for both $Λ$ and $\barΛ$ polarization, in particular, with the $Λ$-$\barΛ$ splitting. Suppression

Ian Walsh, Dmytro Fishman, Dario Garcia-Gasulla, Tiina Titma

Modern biology frequently relies on machine learning to provide predictions and improve decision processes. There have been recent calls for more scrutiny on machine learning performance and possible limitations. Here we present a set of community-wide recommendations aiming to help establish standards of supervised machine learning validation in biology. Ad

Sylvia Ploeckinger, Joop Schaye

We use the spectral synthesis code Cloudy to tabulate the properties of gas for an extensive range in redshift (z=0 to 9), temperature (log T [K] = 1 to 9.5), metallicity (log Z/$\mathrm{Z}_{\odot}$ = -4 to +0.5, Z=0), and density (log $n_{\mathrm{H}}$ [$\mathrm{cm}^{-3}$] = -8 to +6). This therefore includes gas with properties characteristic of the interst

Ilya F. Ginzburg, Gleb L. Kotkin

We discuss a photon collider based on the $e^+e^-$ \ linear collider with energies of $2E = 1÷2$ TeV in cms (ILC, CLIC, ...). Previously, this energy range was considered hopeless for the experiment in the foreseeable future. We discuss the realization of the TeV PLC based on modern lasers. A small modification of the laser-optical system prepared for the ph

Yeonsoo Jeon, Dongsuk Jeon

Various post-quantum cryptography algorithms have been recently proposed. Supersingluar isogeny Diffie-Hellman key exchange (SIKE) is one of the most promising candidates due to its small key size. However, the SIKE scheme requires numerous finite field multiplications for its isogeny computation, and hence suffers from slow encryption and decryption process

Emma Duchini, Stefania Simion, Arthur Turrell, Jack Blundell

Since 2018 UK firms with at least 250 employees have been mandated to publicly disclose gender equality indicators. Exploiting variations in this mandate across firm size and time we show that pay transparency closes 18 percent of the gender pay gap by reducing men's wage growth. The public availability of the equality indicators seems to influence emplo

Richard Santiago

We consider the following class of submodular k-multiway partitioning problems: (Sub-$k$-MP) $\min \sum_{i=1}^k f(S_i): S_1 \uplus S_2 \uplus \cdots \uplus S_k = V \mbox{ and } S_i \neq \emptyset \mbox{ for all }i\in [k]$. Here $f$ is a non-negative submodular function, and $\uplus$ denotes the union of disjoint sets. Hence the goal is to partition $V$ into

John D. Barrow

We demonstrate the existence of sudden, finite-time, singularities, with constant scale factor, expansion rate and density, in expanding Bianchi type IX universes with free anisotropic pressures. A new type of non-simultaneous anisotropic sudden singularity arises because of the divergences of the pressures, which may be of barrel or pancake type. The effect

Francesca Biagini, Katharina Oberpriller

In this paper we extend the reduced-form setting under model uncertainty introduced in [5] to include intensities following an affine process under parameter uncertainty, as defined in [15]. This framework allows to introduce a longevity bond under model uncertainty in a consistent way with the classical case under one prior, and to compute its valuation num

Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro

Measuring temperature fluctuations in the 21 cm signal from the Epoch of Reionization and the Cosmic Dawn is one of the most promising ways to study the Universe at high redshifts. Unfortunately, the 21 cm signal is affected by both cosmology and astrophysics processes in a non-trivial manner. We run a suite of 1,000 numerical simulations with different valu

Meriem Gharbi, Bahman Gharesifard, Christian Ebenbauer

In this paper, we address the efficient implementation of moving horizon state estimation of constrained discrete-time linear systems. We propose a novel iteration scheme which employs a proximity-based formulation of the underlying optimization algorithm and reduces computational effort by performing only a limited number of optimization iterations each tim

Jonas Heinze, Daniel Biehl, Anatoli Fedynitch, Denise Boncioli

We scrutinize the paradigm that conventional long-duration Gamma-Ray Bursts (GRBs) are the dominant source of the ultra-high energy cosmic rays (UHECRs) within the internal shock scenario by describing UHECR spectrum and composition and by studying the predicted (source and cosmogenic) neutrino fluxes. Since it has been demonstrated that the stacking searche

Claudio Guarcello, Giovanni Filatrella, Bernardo Spagnolo, Vincenzo Pierro

We propose to characterize Lévy-distributed stochastic fluctuations through the measurement of the average voltage drop across a current-biased Josephson junction. We show that the noise induced switching process in the Josephson washboard potential can be exploited to reveal and characterize Lévy fluctuations, also if embedded in a thermal noisy background.

O. V. Kibis, S. A. Kolodny, I. V. Iorsh

Optical spectra of semiconductor quantum wells driven by an off-resonant oscillating field are studied theoretically. Due to the dynamical stabilization effect, the field induces the quasi-stationary electron states confined at repulsive scatterers and immersed into the continuum of states of conduction electrons. As a result, the Fano resonances in the spec

Kaspar Märtens, Christopher Yau

Variational Autoencoders (VAEs) have become a popular approach for dimensionality reduction. However, despite their ability to identify latent low-dimensional structures embedded within high-dimensional data, these latent representations are typically hard to interpret on their own. Due to the black-box nature of VAEs, their utility for healthcare and genomi

Ariel Neufeld, Antonis Papapantoleon, Qikun Xiang

We consider derivatives written on multiple underlyings in a one-period financial market, and we are interested in the computation of model-free upper and lower bounds for their arbitrage-free prices. We work in a completely realistic setting, in that we only assume the knowledge of traded prices for other single- and multi-asset derivatives, and even allow

Bastian Prasse, Piet Van Mieghem

Currently, many countries are considering the introduction of tracing software on mobile smartphones with the main purpose to inform and alarm the mobile app user. Here, we demonstrate that, in addition to alarming and informing, mobile tracing can detect nearly all users that are infected by SARS-CoV-2. Our algorithm BETIS (Bayesian Estimation for Tracing I

Amit N. Kumar

In this paper, we obtain error bound for binomial and negative binomial approximations to weighted sums of locally dependent random variables, using Stein's method. We also discuss approximation results for weighted sums of independent random variables. We demonstrate our results through some applications in finance and runs in statistics.

Qingqing Long, Yilun Jin, Guojie Song, Yi Li

Graph Convolutional Networks (GCNs) achieved tremendous success by effectively gathering local features for nodes. However, commonly do GCNs focus more on node features but less on graph structures within the neighborhood, especially higher-order structural patterns. However, such local structural patterns are shown to be indicative of node properties in num

K. L. Yeo, S. K. Solanki, N. A. Krivova

How global faculae and network coverage relates to that of sunspots is relevant to the brightness variations of the Sun and Sun-like stars. We extend earlier studies that found the facular-to-sunspot-area ratio diminishes with total sunspot coverage. Chromospheric indices and the total magnetic flux enclosed in network and faculae, referred to here as 'f

Haeran Cho, Claudia Kirch

We discuss the theoretical guarantee provided by the WBS2.SDLL proposed in Fryzlewicz (2020) and explore an alternative, MOSUM-based candidate generation method for the SDLL.

Max Nendel, Frank Riedel, Maren Diane Schmeck

We provide an axiomatic approach to general premium principles in a probability-free setting that allows for Knightian uncertainty. Every premium principle is the sum of a risk measure, as a generalization of the expected value, and a deviation measure, as a generalization of the variance. One can uniquely identify a maximal risk measure and a minimal deviat

Lachlan Ewen MacDonald

We define a notion of connection in a fibre bundle that is compatible with a singular foliation of the base. Fibre bundles equipped with such connections are in plentiful supply, arising naturally for any Lie groupoid-equivariant bundle, and simultaneously generalising regularly foliated bundles in the sense of Kamber-Tondeur and singular foliations. We defi

Arianna Rubino, Can Livanelioglu, Ning Qiao, Melika Payvand

Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal neuromorphic architectures provide promising ultra-low-power solutions for edge-computing sensory-processing applications, thanks to their ability to emulate spiking neural networks

Ke Ye, Mu Niu, Pokman Cheung, Zhenwen Dai

Amidst the growing interest in nonparametric regression, we address a significant challenge in Gaussian processes(GP) applied to manifold-based predictors. Existing methods primarily focus on low dimensional constrained domains for heat kernel estimation, limiting their effectiveness in higher-dimensional manifolds. Our research proposes an intrinsic approac

Yassine Ouali, Victor Bouvier, Myriam Tami, Céline Hudelot

Learning Invariant Representations has been successfully applied for reconciling a source and a target domain for Unsupervised Domain Adaptation. By investigating the robustness of such methods under the prism of the cluster assumption, we bring new evidence that invariance with a low source risk does not guarantee a well-performing target classifier. More p

Johannes Siegele, Hans-Peter Schröcker, Martin Pfurner

We study an isomorphism between the group of rigid body displacements and the group of dual quaternions modulo the dual number multiplicative group from the viewpoint of differential geometry in a projective space over the dual numbers. Some seemingly weird phenomena in this space have lucid kinematic interpretations. An example is the existence of non-strai

Joshua Baines, Thomas Berry, Alex Simpson, Matt Visser

The standard Lense-Thirring metric is a century-old slow-rotation large-distance approximation to the gravitational field outside a rotating massive body, depending only on the total mass and angular momentum of the source. Although it is not an exact solution to the vacuum Einstein equations, asymptotically the Lense-Thirring metric approaches the Kerr metr

Arnaud Gloppe, Masaru Onga, Ryusuke Hisatomi, Atac Imamoglu

Spin and photonic systems are at the heart of modern information devices and emerging quantum technologies. An interplay between electron-hole pairs (excitons) in semiconductors and collective spin excitations (magnons) in magnetic crystals would bridge these heterogeneous systems, leveraging their individual assets in novel interconnected devices. Here, we

Haofan Wang, Rakshit Naidu, Joy Michael, Soumya Snigdha Kundu

Interpretation of the underlying mechanisms of Deep Convolutional Neural Networks has become an important aspect of research in the field of deep learning due to their applications in high-risk environments. To explain these black-box architectures there have been many methods applied so the internal decisions can be analyzed and understood. In this paper, b

Samapan Bhadury, Wojciech Florkowski, Amaresh Jaiswal, Radoslaw Ryblewski

We extend the Boltzmann equation in the relaxation time approximation to explicitly include transitions between particles forming an interacting mixture. Using the detailed balance condition as well as conditions of energy-momentum and current conservation, we show that only two independent relaxation time scales are allowed in such an interacting system. Di

Helmut Abels, Josef Weber

We show well-posedness of a diffuse interface model for a two-phase flow of two viscous incompressible fluids with different densities locally in time. The model leads to an inhomogeneous Navier-Stokes/Cahn-Hilliard system with a solenoidal velocity field for the mixture, but a variable density of the fluid mixture in the Navier-Stokes type equation. We prov

Farzali Izadi

In this paper, we demonstrate the intimate relationships among some geometric figures and the families of elliptic curves with positive ranks. These geometric figures include \textit{\textbf{Heron triangles}}, \textit{\textbf{Brahmagupta quadrilaterals}} and \textit{\textbf{Bicentric quadrilaterals}}. Firstly, we investigate the important properties of these

Takayuki Miyadera, Leon Loveridge

The imposition of symmetry upon the nature and structure of quantum observables has recently been extensively studied, with quantum reference frames playing a crucial role. In this paper, we extend this work to quantum transformations, giving quantitative results showing, in direct analogy to the case of observables, that a "large" reference frame is

Navid Mahmoudian Bidgoli, Thomas Maugey, Aline Roumy

In this paper, we propose a new interactive compression scheme for omnidirectional images. This requires two characteristics: efficient compression of data, to lower the storage cost, and random access ability to extract part of the compressed stream requested by the user (for reducing the transmission rate). For efficient compression, data needs to be predi

Ricardo Gallego Torromé, Nadya Ben Bekhti-Winkel, Peter Knott

After a brief introduction to the notion of quantum entanglement and quantum correlations, several schemes for a quantum radar based upon the quantum illumination and others protocols are discussed. We review different concepts that have been introduced to overcome several of the inherent difficulties in the implementation of quantum generation and/or detect

Quentin Changeat, Ahmed F. Al-Refaie

In the recent years, retrieval analysis of exoplanet atmospheres have been very successful, providing deep insights on the composition and the temperature structure of these worlds via the transit and eclipse methods. Analysis of spectral phase curve observations, which in theory provides even more information, are still limited to a few planets. In the next

Vincent Duchêne, Luis Miguel Rodrigues

We complete a full classification of non-degenerate traveling waves of scalar balance laws from the point of view of spectral and nonlinear stability/instability under (piecewise) smooth perturbations. A striking feature of our analysis is the elucidation of the prominent role of characteristic points in the determination of both the spectra of the linearize

Thomas Fernique

We consider hard-disc mixtures with disc sizes within ratio $\sqrt{2}-1$, that is, the small disc exactly fits in the hole between four large discs. For each prescribed stoichiometry of large and small discs, the densest packings are rigorously determined via a computer-assisted proof. The density is maximal for the 1:1 stoichiometry: the large discs then fo

Benjamin Merkel, Alexander Ulanowski, Andreas Reiserer

The stability and outstanding coherence of dopants and other atom-like defects in tailored host crystals make them a leading platform for the implementation of distributed quantum information processing and sensing in quantum networks. Albeit the required efficient light-matter coupling can be achieved via the integration into nanoscale resonators, in this a

Marcella Palese, Ekkehart Winterroth

We prove that with a $(2+1)$-dimensional Toda type system are associated algebraic skeletons which are (compatible assemblings) of particle-like Lie algebras of dyons and triadons type. We obtain trix-coaxial and dyx-coaxial Lie algebra structures for the system from algebraic skeletons of some particular choice for compatible associated absolute parallelism

Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy

This paper considers the deconvolution problem in the case where the target signal is multidimensional and no information is known about the noise distribution. More precisely, no assumption is made on the noise distribution and no samples are available to estimate it: the deconvolution problem is solved based only on the corrupted signal observations. We es

Beniamin Bogosel, Thomas Giletti, Andrea Tellini

In this paper, we investigate propagation phenomena for KPP bulk-surface systems in a cylindrical domain with general section and heterogeneous coefficients. As for the scalar KPP equation, we show that the asymptotic spreading speed of solutions can be computed in terms of the principal eigenvalues of a family of self-adjoint elliptic operators. Using this

Bruno Andreis, Seanie Lee, A. Tuan Nguyen, Juho Lee

Deep models are designed to operate on huge volumes of high dimensional data such as images. In order to reduce the volume of data these models must process, we propose a set-based two-stage end-to-end neural subsampling model that is jointly optimized with an \textit{arbitrary} downstream task network (e.g. classifier). In the first stage, we efficiently su

Eric P. Nichols, Stefano Kalonaris, Gianluca Micchi, Anna Aljanaki

We propose a system for contrapuntal music generation based on a Neural Machine Translation (NMT) paradigm. We consider Baroque counterpoint and are interested in modeling the interaction between any two given parts as a mapping between a given source material and an appropriate target material. Like in translation, the former imposes some constraints on the

Jonathan Chappelon, Jorge Luis Ramírez Alfonsín

Let $S=\left\langle s_1,\ldots,s_n\right\rangle$ be a numerical semigroup generated by the relatively prime positive integers $s_1,\ldots,s_n$. Let $k\geqslant 2$ be an integer. In this paper, we consider the following $k$-power variant of the Frobenius number of $S$ defined as $${}^{k\!}r\!\left(S\right):= \text{ the largest } k \text{-power integer not bel

Xiaochen Wang, Arash Pakbin, Bobak J. Mortazavi, Hongyu Zhao

The proliferation of medical monitoring devices makes it possible to track health vitals at high frequency, enabling the development of dynamic health risk scores that change with the underlying readings. Survival analysis, in particular hazard estimation, is well-suited to analyzing this stream of data to predict disease onset as a function of the time-vary

Emanuele Aliverti, Massimiliano Russo

There has been considerable recent interest in Bayesian modeling of high-dimensional networks via latent space approaches. When the number of nodes increases, estimation based on Markov Chain Monte Carlo can be extremely slow and show poor mixing, thereby motivating research on alternative algorithms that scale well in high-dimensional settings. In this arti

Charitha Madapatha, Behrooz Makki, Chao Fang, Oumer Teyeb

In this paper, we introduce and study the potentials and challenges of integrated access and backhaul (IAB) as one of the promising techniques for evolving 5G networks. We study IAB networks from different perspectives. We summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on IAB, and highlight the main IAB-specific agreements on dif

Alexandr G. Rassadin

In this work we present a method for lung nodules segmentation, their texture classification and subsequent follow-up recommendation from the CT image of lung. Our method consists of neural network model based on popular U-Net architecture family but modified for the joint nodule segmentation and its texture classification tasks and an ensemble-based model f

I. Tsymbalov, D. Gorlova, A. Savel'ev

The hybrid Stimulated Raman Scattering - Two Plasmon Decay instability had shown to play the dominant role for plasma waves excitation and energy absorption at interaction of very intense femtosecond obliquely incident $p$-polarized laser pulse (intensity $10^{17}-5\cdot10^{19}$ W/cm$^2$) with a steep gradient ($L\sim λ$) plasma near the quarter critical sur

Sourav Bhattacharya, Himanshu Gaur, Nitin Joshi

We investigate two measures of quantum correlations and entanglement, namely the violation of the Bell-Mermin-Klyshko inequalities and the quantum discord, for Dirac fermions in the cosmological de Sitter background of dimension four. The BMK violation is focussed on the vacuum for two and four mode squeezed states and it is shown to increase with the number

Mahtab Uddin, M. Monir Uddin, Md. Abdul Hakim Khan

In this article, the focus is mainly on gaining the optimal control for the unstable power system models and stabilizing them through the Riccati-based feedback stabilization process with sparsity-preserving techniques. We are to find the solution of the Continuous-time Algebraic Riccati Equations (CAREs) governed from the unstable power system models derive

Peng Zhou, Lingxi Xie, Xiaopeng Zhang, Bingbing Ni

Conditional Generative Adversarial Networks (cGAN) were designed to generate images based on the provided conditions, \eg, class-level distributions. However, existing methods have used the same generating architecture for all classes. This paper presents a novel idea that adopts NAS to find a distinct architecture for each class. The search space contains r

Emiru Tsunoo, Yosuke Kashiwagi, Shinji Watanabe

The Transformer self-attention network has shown promising performance as an alternative to recurrent neural networks in end-to-end (E2E) automatic speech recognition (ASR) systems. However, Transformer has a drawback in that the entire input sequence is required to compute both self-attention and source--target attention. In this paper, we propose a novel b

Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert, Roland Tóth

Efficiently computable stability and performance analysis of nonlinear systems becomes increasingly more important in practical applications. Dissipativity can express stability and performance jointly, but existing results are limited to the regions around the equilibrium points of these nonlinear systems. The incremental framework, based on the convergence

Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte

Super-resolution is an ill-posed problem, since it allows for multiple predictions for a given low-resolution image. This fundamental fact is largely ignored by state-of-the-art deep learning based approaches. These methods instead train a deterministic mapping using combinations of reconstruction and adversarial losses. In this work, we therefore propose SR

William Pluriel, Niall Whiteford, Billy Edwards, Quentin Changeat

We present the analysis of the hot-Jupiter KELT-7b using transmission and emission spectroscopy from the Hubble Space Telescope (HST), both taken with the Wide Field Camera 3 (WFC3). Our study uncovers a rich transmission spectrum which is consistent with a cloud-free atmosphere and suggests the presence of H2O and H-. In contrast, the extracted emission spe

Lucas J. Liu, Hongwei Zhang, Jianzhong Di, Jin Chen

Many real-world Electronic Health Record (EHR) data contains a large proportion of missing values. Leaving substantial portion of missing information unaddressed usually causes significant bias, which leads to invalid conclusion to be drawn. On the other hand, training a machine learning model with a much smaller nearly-complete subset can drastically impact

Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer

We present a surprisingly simple yet accurate approach to reasoning in knowledge graphs (KGs) that requires \emph{no training}, and is reminiscent of case-based reasoning in classical artificial intelligence (AI). Consider the task of finding a target entity given a source entity and a binary relation. Our non-parametric approach derives crisp logical rules

Kenta Oishi

We consider the generalized Stokes resolvent problem in an infinite layer with Neumann boundary conditions. This problem arises from a free boundary problem describing the motion of incompressible viscous one-phase fluid flow without surface tension in an infinite layer bounded both from above and from below by free surfaces. We derive a new exact solution f

Kuanqi Cai, Chaoqun Wang, Jiyu Cheng, Clarence W De Silva

There are many challenges for robot navigation in densely populated dynamic environments. This paper presents a survey of the path planning methods for robot navigation in dense environments. Particularly, the path planning in the navigation framework of mobile robots is composed of global path planning and local path planning, with regard to the planning sc

Alex Sokolov, Tracy Rohlin, Ariya Rastrow

Grapheme-to-phoneme (G2P) models are a key component in Automatic Speech Recognition (ASR) systems, such as the ASR system in Alexa, as they are used to generate pronunciations for out-of-vocabulary words that do not exist in the pronunciation lexicons (mappings like "e c h o" to "E k oU"). Most G2P systems are monolingual and based on tradit

Ming Dong

Power systems have widely adopted the concept of health index to describe asset health statuses and choose proper asset management actions. The existing application and research works have been focused on determining the current or near-future asset health index based on the current condition data. For preventative asset management, it is highly desirable to

Javier Cebeiro, Cecilia Tarpau, Marcela Morvidone, Diana Rubio

Compton scatter tomography is an emerging technique with attractive applications in several fields in imaging such as non-destructive testing and medical scanning. In this paper, we introduce a novel modality in three dimensions with a fixed source and a single detector that moves on a spherical surface. We also study the Radon transform modeling the data th

Rifqi Aziz, Emre Mengi, Matthias Voigt

We first consider the problem of approximating a few eigenvalues of a rational matrix-valued function closest to a prescribed target. It is assumed that the proper rational part of the rational matrix-valued function is expressed in the transfer function form $H(s) = C (sI - A)^{-1} B$, where the middle factor is large, whereas the number of rows of $C$ and

Anna Bykhovskaya, Vadim Gorin

The paper analyses cointegration in vector autoregressive processes (VARs) for the cases when both the number of coordinates, $N$, and the number of time periods, $T$, are large and of the same order. We propose a way to examine a VAR of order $1$ for the presence of cointegration based on a modification of the Johansen likelihood ratio test. The advantage o

Walter Pulido, Hernando Quevedo

We study the collapse of a thin dust shell from the point of view of the horizon dynamics. We identify the critical surfaces at which time and space coordinates interchange their roles and investigate their properties by using the formalism of trapped surfaces. We show the existence of marginally outer trapped surfaces that are associated with the presence o

Sabine Hossenfelder

We here put forward a simple argument for Born's rule based on the requirement that the probability distribution should not be a function of the number of degrees of freedom.

Kun Li, Wei Yu

Propagation of right-hand circularly polarized laser into highly magnetized over-dense collisional plasma is analytically studied from basic equations. Highly magnetized plasma with density of 10^23 cm^-3 is efficiently heated from 100 eV to 1 keV within depth of around 20 μ{m} in one nanosecond by Nd:YAG laser with moderate irradiance of around 10^14 Wcm^-2

Yong-Liang Ma, Mannque Rho

When hadron-quark continuity is formulated in terms of a topology change at a density higher than twice the nuclear matter densiy $n_0$ the core of massive compact stars can be described in terms of quasiparticles of fractional baryon charges, behaving neither like pure baryons nor deconfined quarks. Hidden symmetries, both local gauge and pseudo-conformal (

Robert I McLachlan, Christian Offen

In backward error analysis, an approximate solution to an equation is compared to the exact solution to a nearby modified equation. In numerical ordinary differential equations, the two agree up to any power of the step size. If the differential equation has a geometric property then the modified equation may share it. In this way, known properties of differ

Shengyi Huang, Santiago Ontañón

In recent years, Deep Reinforcement Learning (DRL) algorithms have achieved state-of-the-art performance in many challenging strategy games. Because these games have complicated rules, an action sampled from the full discrete action distribution predicted by the learned policy is likely to be invalid according to the game rules (e.g., walking into a wall). T

Victor Miguel Banda Guzman, Ruben Flores-Mendieta, Johann Hernandez, Felipe de Jesus Rosales-Aldape

The quadratic Casimir operator of the special unitary $SU(N)$ group is used to construct projection operators, which can decompose any of its reducible finite-dimensional representation spaces contained in the tensor product of two and three adjoint spaces into irreducible components. Although the method is general enough, it is specialized to the $SU(2N_f)

Mikhail Yurochkin, Yuekai Sun

In this paper, we cast fair machine learning as invariant machine learning. We first formulate a version of individual fairness that enforces invariance on certain sensitive sets. We then design a transport-based regularizer that enforces this version of individual fairness and develop an algorithm to minimize the regularizer efficiently. Our theoretical res

Ajay Subramanian, Sharad Chitlangia, Veeky Baths

Reinforcement learning methods have recently been very successful at performing complex sequential tasks like playing Atari games, Go and Poker. These algorithms have outperformed humans in several tasks by learning from scratch, using only scalar rewards obtained through interaction with their environment. While there certainly has been considerable indepen

Rafael Stekolshchik

Some phenomena related to statistical noise which have been investigated by various authors under the framework of deep reinforcement learning (RL) algorithms are discussed. The following algorithms are examined: the deep Q-network (DQN), double DQN, deep deterministic policy gradient (DDPG), twin-delayed DDPG (TD3), and hill climbing algorithm. First, we co

Tadahito Nakajima

In this paper, we derive the universal (cut-off-independent) part of the holographic entanglement entropy in the noncommutative Yang-Mills theory and examine its properties in detail. The behavior of the holographic entanglement entropy as a function of a scale of the system changes drastically between large noncommutativity and small noncommutativity. The s

Kuize Zhang

In this paper, we for the first time obtain characterization of four fundamental notions of detectability for general labeled weighted automata over monoids (denoted by $\mathcal{A}^{\mathfrak{M}}$ for short), where the four notions are strong (periodic) detectability (SD and SPD) and weak (periodic) detectability (WD and WPD). Firstly, we formulate the noti

Jan F. Haase, Luca Dellantonio, Alessio Celi, Danny Paulson

Gauge theories establish the standard model of particle physics, and lattice gauge theory (LGT) calculations employing Markov Chain Monte Carlo (MCMC) methods have been pivotal in our understanding of fundamental interactions. The present limitations of MCMC techniques may be overcome by Hamiltonian-based simulations on classical or quantum devices, which fu

Kenzo Ishikawa, Kenji Nishiwaki, Kin-ya Oda

We compute an $s$-channel $2\to2$ scalar scattering $ϕϕ\toΦ\toϕϕ$ in the Gaussian wave-packet formalism at the tree-level. We find that wave-packet effects, including shifts of the pole and width of the propagator of $Φ$, persist even when we do not take into account the time-boundary effect for $2\to2$, proposed earlier. The result can be interpreted that a

Helena B. Stage, Joseph Shingleton, Sanmitra Ghosh, Francesca Scarabel

We investigate the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden, and German states as case studies. By comparing the growth rates in daily hospitalisations or confirmed cases under different interventions, we provide evidence that the effect of school closure is visible as a reducti

Qingchun Li, Liam Bessell, Xin Xiao, Chao Fan

We examined the effect of social distancing on changes in visits to urban hotspot points of interest. Urban hotspots, such as central business districts, are gravity activity centers orchestrating movement and mobility patterns in cities. In a pandemic situation, urban hotspots could be potential superspreader areas as visits to urban hotspots can increase t

Liang Yu, Yi Sun, Zhanbo Xu, Chao Shen

In commercial buildings, about 40%-50% of the total electricity consumption is attributed to Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic burden on building operators. In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration o

Gavin Ball

This article studies closed G2-structures satisfying the quadratic condition, a second-order PDE system introduced by Bryant involving a parameter $λ.$ For certain special values of $λ$ the quadratic condition is equivalent to the Einstein condition for the metric induced by the closed G2-structure (for $λ= 1/2$), the extremally Ricci-pinched (ERP) condition

Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

Consider learning a policy purely on the basis of demonstrated behavior -- that is, with no access to reinforcement signals, no knowledge of transition dynamics, and no further interaction with the environment. This *strictly batch imitation learning* problem arises wherever live experimentation is costly, such as in healthcare. One solution is simply to ret

David Tamayo

In this work we explore the thermodynamic aspects of dark energy for late future time universe in two different scenarios: as a perfect fluid with constant and variable equation of state parameter; and as dissipative fluid described by a barotropic equation of state with bulk viscosity in the framework of the Eckart theory and the full Israel-Stewart theory.

Huai-Yu Wang

A wave function can be written in the form of ψ = ReiS/h. We put this form of wave function into quantum mechanics equations and take hydrodynamic limit, i. e., let Planck constant be zero. Then equations of motion (EOM) describing the movement of macroscopic bodies are retrieved. From Schrodinger equation, we obtain Newtonian mechanics, including Newtons th

Anton Kapustin, Nikita Sopenko

We study charge transport for zero-temperature infinite-volume gapped lattice systems in two dimensions with short-range interactions. We show that the Hall conductance is locally computable and is the same for all systems which are in the same gapped phase. We provide a rigorous versions of Laughlin's flux-insertion argument which shows that for short-r

M. Caner Tol, Berk Gulmezoglu, Koray Yurtseven, Berk Sunar

Several techniques have been proposed to detect vulnerable Spectre gadgets in widely deployed commercial software. Unfortunately, detection techniques proposed so far rely on hand-written rules which fall short in covering subtle variations of known Spectre gadgets as well as demand a huge amount of time to analyze each conditional branch in software. Moreov

Zhengping Luo, Shangqing Zhao, Zhuo Lu, Yalin E. Sagduyu

As Internet of Things (IoT) has emerged as the next logical stage of the Internet, it has become imperative to understand the vulnerabilities of the IoT systems when supporting diverse applications. Because machine learning has been applied in many IoT systems, the security implications of machine learning need to be studied following an adversarial machine

Wenjun Cai, Aaron Potechin

Graph matrices are a type of matrix which has played a crucial role in analyzing the sum of squares hierarchy on average case problems. However, except for rough norm bounds, little is known about graph matrices. In this paper, we take a step towards better understanding graph matrices by determining the limiting distribution of the spectrum of the singular

A Kundu, S D Pathak, V K Ojha

We discuss the coupling between dark energy and matter by considering a homogeneous tachyonic scalar field as a candidate for dark energy. We obtained the functional form of scale factor by assuming that the coupling strength depends linearly on the Hubble parameter and energy density. We also estimated the cosmic age of the universe for different values of

A. P. Buccino, L. Sraibman, P. Olivar, F. Minotti

During the last decade, the relation between activity cycle periods with stellar parameters has received special attention. The construction of reliable registries of activity reveals that solar type stars exhibit activity cycles with periods from few years to decades and, in same cases, long and short activity cycles coexist suggesting that two dynamos coul

Nikolaos D. Bagis

We examine $q-$series related to higher forms. These forms are cubics, quartics, etc. In some points, in the article we add parts from previous works, in such a way, the article be more complete and readable.