July 2019 arXiv papers — page 55

C. Guidorzi, M. Marongiu, R. Martone, L. Amati

No transient electromagnetic emission has yet been found in association to fast radio bursts (FRBs), the only possible exception (3sigma confidence) being the putative gamma-ray signal detected in Swift/BAT data in the energy band 15-150 keV at the time and position of FRB131104. Systematic searches for hard X/gamma-ray counterparts to other FRBs ended up wi

Ayse Borat, Tane Vergili

The concept of homotopic distance and its higher analog are introduced in [6]. In this paper we introduce some important properties of higher homotopic distance, investigate the conditions under which $\cat$, $\secat$ and higher dimensional topological complexity are equal to the higher homotopic distance, and give alternative proofs, using higher homotopic

Hong Wang, Cuixiang Wang, Yan Zhu, Zi-An Li

In two-dimensional van der Waals (vdW) magnets, the presence of magnetic orders, strong spin-orbit coupling and asymmetry at interfaces is the key ingredient for hosting chiral spin textures. However, experimental evidences for chiral magnetism in vdW magnets remain elusive. Here we demonstrate unambiguously the formation of chiral spin textures in thin Fe3G

Denny Kusuma Hendraningrat, Bhaskara Narottama, Soo Young Shin

In this paper, a joint transmission coordinated multi-point based non-orthogonal multiple access (JT-COMP NOMA) combined with spatial modulation (SM), termed as JT-COMP NOMA-SM, is proposed to enhance capacity. User capacity and ergodic sum capacity (ESC) of M number coordinated multi-point base stations (COMP BSs) within N number of cells are analyzed by co

G. Rajasekaran

Starting with the Wolfenstein form for the leptonic mixing matrix we show that renormaliztion group evolution brings that to the observed large mixing at low energies.

Surat Teerapittayanon, H. T. Kung

We introduce DaiMoN, a decentralized artificial intelligence model network, which incentivizes peer collaboration in improving the accuracy of machine learning models for a given classification problem. It is an autonomous network where peers may submit models with improved accuracy and other peers may verify the accuracy improvement. The system maintains an

Aritra Banerjee, Samudra Roy

We investigate the dynamics of an Airy pulse that experiences free carrier generated optical linear potential in the vicinity of zero group velocity dispersion (GVD) wavelength inside a Si based waveguide. The optically induced potential can be realized by an inhomogeneous medium which possesses a time dependent refractive index. We propose a pump-probe sche

Chen Gong, David S. Stoffer

The stochastic volatility model is a popular tool for modeling the volatility of assets. The model is a nonlinear and non-Gaussian state space model, and consequently is difficult to fit. Many approaches, both classical and Bayesian, have been developed that rely on numerically intensive techniques such as quasi-maximum likelihood estimation and Markov chain

Vaibhav H. Wasnik, Peter Lipp, Karsten Kruse

A living cell senses its environment and responds to external signals. In this work, we study theoretically, the precision at which cells can determine the position of a spatially localized transient extracellular signal. To this end, we focus on the case, where the stimulus is converted into the release of a small molecule that acts as a second messenger, f

Sen Mu, Da-Jian Zhang, Longwen Zhou, Jiangbin Gong

The adiabatic charge pumping of a non-equilibrium state of spinless fermions in a one-dimensional lattice is investigated, with an emphasis placed on its usefulness in revealing many-body interaction effects on interband coherence. For a non-interacting system, the pumped charge per adiabatic cycle depends not only on the topology of the occupied bands but a

Haris Javaid, Chengchen Hu, Gordon Brebner

Blockchain technologies are on the rise, and Hyperledger Fabric is one of the most popular permissioned blockchain platforms. In this paper, we re-architect the validation phase of Fabric based on our analysis from fine-grained breakdown of the validation phase's latency. Our optimized validation phase uses a chaincode cache during validation of transact

Kaelin Cook-Powell, David Jensen

We describe a conjectural stratification of the Brill-Noether variety for general curves of fixed genus and gonality. As evidence for this conjecture, we show that this Brill-Noether variety has at least as many irreducible components as predicted by the conjecture, and that each of these components has the expected dimension. Our proof uses combinatorial an

Anna Gilbert, Albert Gu, Christopher Re, Atri Rudra

In this paper we consider the following sparse recovery problem. We have query access to a vector $\vx \in \R^N$ such that $\vhx = \vF \vx$ is $k$-sparse (or nearly $k$-sparse) for some orthogonal transform $\vF$. The goal is to output an approximation (in an $\ell_2$ sense) to $\vhx$ in sublinear time. This problem has been well-studied in the special case

Tianyi Guo, Xiaoyu Zheng, Peter Palffy-Muhoray

In this paper, we propose a suitable surface energy expression for cholesteric liquid crystals. We show that there exists a symmetry allowed term for chiral nematics that doesn't appear in the traditional Rapini-Papoular surface energy form. We discuss some consequences of this new surface anchoring term.

Ping Li, Jiangying Yu, Jinrong Xu, Li Zhang

Dozens of layered V$_2$IV$_2$VI$_6$ (V=P, As, Sb, Bi, IV=Si, Ge, Sn, Pb, VI=S, Se, Te) materials are investigated, several of which have been successfully synthesized in experiment. Among them, we predict nine strong topological insulators (TIs), two strong topological metals (TMs) and nearly twenty trivial insulators at their equilibrium structures. The TIs

Lisa Hui Sun

In this paper, by applying a range of classic summation and transformation formulas for basic hypergeometric series, we obtain a three-term identity for partial theta functions. It extends the Andrews-Warnaar partial theta function identity, and also unifies several results on partial theta functions due to Ramanujan, Lovejoy and Kim. We also establish a two

Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo, Jinxia Lin

Specifying a complete domain model is time-consuming, which has been a bottleneck of AI planning technique application in many real-world scenarios. Most classical domain-model learning approaches output a domain model in the form of the declarative planning language, such as STRIPS or PDDL, and solve new planning instances by invoking an existing planner. H

Wen-Long Li, Xiaojun Cui

We study heteroclinic solutions of a generalized Frenkel-Kontorova model. Using the methods of Rabinowitz and Stredulinsky, we prove that if the rotation vector of the configuration is rational and if there is an adjacent pair of periodic configurations, then there is a solution that is heteroclinic in one fixed direction and periodic in other directions. Fu

Stephane Dartois

Random tensors can be used to produce random matrices. This idea is, for instance, very natural when one studies random quantum states with the aim of exploring properties that are generically true, or true with some probability. We hereby study the moments generating function, in the sense of the Stieltjes transform - i.e. the resolvent -, of a random matri

Jeffrey G. Ulbrandt, Xiaozhi Zhang, Rui Liu, Kenneth Evans-Lutterodt

Pulsed Laser Deposition (PLD) is widely used to grow epitaxial thin films of quantum materials such as complex oxides. Here, we use in-situ X-ray scattering to study homoepitaxy of SrTiO$_3$ by energetic (e-) and thermalized (th-) PLD. We find that e-PLD suppresses the lateral growth of two-dimensional islands, which suggests that energetic particles break u

Kojiro Iizuka, Takeshi Yoneda, Yoshifumi Seki

Personalization plays an important role in many services. To evaluate personalized rankings, online evaluation, such as A/B testing, is widely used today. Recently, multileaving has been found to be an efficient method for evaluating rankings in information retrieval fields. This paper describes the first attempt to optimize the multileaving method for perso

Manuel Hohmann

In a recent work we derived the kinematic Hamiltonian and primary constraints of the new general relativity class of teleparallel gravity theories and showed that these theories can be grouped in 9 classes, based on the presence or absence of primary constraints in their Hamiltonian. Here we demonstrate an alternative approach towards this result, by using d

Guang-Xuan Lan, Hou-Dun Zeng, Jun-Jie Wei, Xue-Feng Wu

We study the luminosity function and formation rate of long gamma-ray bursts (GRBs) by using a maximum likelihood method. This is the first time this method is applied to a well-defined sample of GRBs that is complete in redshift. The sample is composed of 99 bursts detected by the $Swift$ satellite, 81 of them with measured redshift and luminosity for a com

Asako Terasawa, Munehisa Matsumoto, Taisuke Ozaki, Yoshihiro Gohda

For large-scale computation of the exchange coupling constants $J_{ij}$, we reconstruct the Liechtenstein formula for localized orbital representation and simplify the energy integrations by adopting the finite pole approximation of the Fermi function proposed by Ozaki [Phys. Rev. B 75, 035123 (2007)]. We calculate the exchange coupling constant $J_{\mathrm{

Hugo Caerols, Felipe A. Asenjo

On January 20th, 2019, a total lunar eclipse was possible to be observed in Santiago, Chile. Using a smartphone attached to a telescope, photographs of the phenomenon were taken. With Earth's shadow on those images, and using textbook geometry, a simple open-source software and analytical procedures, we were allowed to calculate the ratio between the rad

Yuma Koizumi, Shoichiro Saito, Masataka Yamaguchi, Shin Murata

Use of an autoencoder (AE) as a normal model is a state-of-the-art technique for unsupervised-anomaly detection in sounds (ADS). The AE is trained to minimize the sample mean of the anomaly score of normal sounds in a mini-batch. One problem with this approach is that the anomaly score of rare-normal sounds becomes higher than that of frequent-normal sounds,

Jake Roemer, Michael D. Bond

Predictive data race detectors find data races that exist in executions other than the observed execution. Smaragdakis et al. introduced the causally-precedes (CP) relation and a polynomial-time analysis for sound (no false races) predictive data race detection. However, their analysis cannot scale beyond analyzing bounded windows of execution traces. This w

Lawrence S. Moss

This is the proceedings of the Seventeenth conference on Theoretical Aspects of Rationality and Knowledge, 17-19 July 2019, Institut de Recherche en Informatique de Toulouse (IRIT), Toulouse University Toulouse, France. The mission of the TARK conferences is to bring together researchers from a wide variety of fields, including Artificial Intelligence, Crypt

Eddie Anderson, Harrison Nguyen

We explore the performance of sample average approximation in comparison with several other methods for stochastic optimization when there is information available on the underlying true probability distribution. The methods we evaluate are (a) bagging; (b) kernel smoothing; (c) maximum likelihood estimation (MLE); and (d) a Bayesian approach. We use two tes

Abdul Karim, Jaspreet Singh, Avinash Mishra, Abdollah Dehzangi

Prediction of toxicity levels of chemical compounds is an important issue in Quantitative Structure-Activity Relationship (QSAR) modeling. Although toxicity prediction has achieved significant progress in recent times through deep learning, prediction accuracy levels obtained by even very recent methods are not yet very high. We propose a multimodal deep lea

Tao Chen, Han Wu, Chi Wang, Xiaoxin Zhang

Although earthquake prediction is a big challenge in the world, some simple observational tools can capture many physical signals and demonstrate that an earthquake (EQ) may be forthcoming in short period. Many researchers have studied the significant variation of atmospheric electrostatic field related to the forthcoming earthquake. However, until now, ther

Joshua M. Siktar

We generalize aspects of Fourier Analysis from intervals on $\mathbb{R}$ to bounded and measurable subsets of $\mathbb{R}^n$. In doing so, we obtain a few interesting results. The first is a new proof of the famous Integral Cauchy-Schwarz Inequality. The second is a restatement of Parseval's Identity that doubles as a representation of integrating bounde

Egor Khaidarov, Zhengtong Liu, Ramon Paniagua-Dominguez, Son Tung Ha

The improvement of light-emitting diodes (LEDs) is one of the major goals of optoelectronics and photonics research. While emission rate enhancement is certainly one of the targets, in this regard, for LED integration to complex photonic devices, one would require to have, additionally, precise control of the wavefront of the emitted light. Metasurfaces are

Sergei V. Fotin, David F. Yankelevitz, Claudia I. Henschke, Anthony P. Reeves

Candidate generation, the first stage for most computer aided detection (CAD) systems, rapidly scans the entire image data for any possible abnormality locations, while the subsequent stages of the CAD system refine the candidates list to determine the most probable or significant of these candidates. The candidate generator creates a list of the locations a

Matteo Bordignon

This paper improves the upper bound for the exceptional zeroes of Dirichlet L-functions with even characters. The result is obtained by improving on explicit estimate for $L'(σ;χ)$ for $σ$ close to unity, using a result on the average of Dirichlet characters, and on the lower bound for $L(1;χ)$, with computational aid.

Sashank Santhanam, Vidhushini Srinivasan, Shaina Glass, Samira Shaikh

We study how emojis are used to express solidarity in social media in the context of two major crisis events - a natural disaster, Hurricane Irma in 2017 and terrorist attacks that occurred on November 2015 in Paris. Using annotated corpora, we first train a recurrent neural network model to classify expressions of solidarity in text. Next, we use these expr

Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh

With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural networks) calls for advanced techniques in exploring and interpreting model behaviors. Second, the rapid growth in computin

Aleksander Cieślak, Marcin Michalski

In this paper we consider a notion of universal sets for ideals. We show that there exist universal sets of minimal Borel complexity for classic ideals like null subsets of $2^ω$ and meager subsets of any Polish space, and demonstrate that the existence of such sets is helpful in establishing some facts about the real line in generic extensions. We also cons

Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari

This paper proposes novel algorithms for speaker embedding using subjective inter-speaker similarity based on deep neural networks (DNNs). Although conventional DNN-based speaker embedding such as a $d$-vector can be applied to multi-speaker modeling in speech synthesis, it does not correlate with the subjective inter-speaker similarity and is not necessaril

Isaac Kamlish, Isaac Bentata Chocron, Nicholas McCarthy

We present SentiMATE, a novel end-to-end Deep Learning model for Chess, employing Natural Language Processing that aims to learn an effective evaluation function assessing move quality. This function is pre-trained on the sentiment of commentary associated with the training moves and is used to guide and optimize the agent's game-playing decision making.

James V. Burke, Tim Hoheisel, Quang V. Nguyen

In this note we provide a full conjugacy and subdifferential calculus for convex convex-composite functions in finite-dimensional space. Our approach, based on infimal convolution and cone-convexity, is straightforward and yields the desired results under a verifiable Slater-type condition, with relaxed monotonicity and without lower semicontinuity assumptio

Lukas Einkemmer

In this paper, our goal is to efficiently solve the Vlasov equation on GPUs. A semi-Lagrangian discontinuous Galerkin scheme is used for the discretization. Such kinetic computations are extremely expensive due to the high-dimensional phase space. The SLDG code, which is publicly available under the MIT license abstracts the number of dimensions and uses a s

Preston Jones, Douglas Singleton, Pragati Pradhan

This paper presents the scenario that gravitational waves, generated in core-collapse of a pre-supernova star, can produce both electromagnetic radiation and sound radiation as gravitational waves propagate outward from the collapsing core. While the energy of this co-produced electromagnetic and sound radiation is orders of magnitude smaller than the initia

C. A. Argüelles, A. J. Aurisano, B. Batell, J. Berger

With the advent of a new generation of neutrino experiments which leverage high-intensity neutrino beams for precision measurements, it is timely to explore physics topics beyond the standard neutrino-related physics. Given that the realm of beyond the standard model (BSM) physics has been mostly sought at high-energy regimes at colliders, such as the LHC at

Yash Patel, Srikar Appalaraju, R. Manmatha

Several deep learned lossy compression techniques have been proposed in the recent literature. Most of these are optimized by using either MS-SSIM (multi-scale structural similarity) or MSE (mean squared error) as a loss function. Unfortunately, neither of these correlate well with human perception and this is clearly visible from the resulting compressed im

Syamantak Das, Lavina Jain, Nikhil Kumar

Given a graph $G=(V,E)$ with non-negative real edge lengths and an integer parameter $k$, the Min-Max k-Tree Cover problem seeks to find a set of at most $k$ subtrees of $G$, such that the union of the trees is the vertex set $V$. The objective is to minimize the maximum length among all the trees. We give the first constant factor approximation for the hard

Davide Barbieri, Carlos Cabrelli, Eugenio Hernández, Ursula Molter

In this article we study the structure of $Γ$-invariant spaces of $L^2(\bf R)$. Here $\bf R$ is a second countable LCA group. The invariance is with respect to the action of $Γ$, a non commutative group in the form of a semidirect product of a discrete cocompact subgroup of $\bf R$ and a group of automorphisms. This class includes in particular most of the c

A. Y. Potekhin, A. I. Chugunov, G. Chabrier

We study long-term thermal evolution of neutron stars in soft X-ray transients (SXTs), taking the deep crustal heating into account consistently with the changes of the composition of the crust. We collect observational estimates of average accretion rates and thermal luminosities of such neutron stars and compare the theory with observations. We perform sim

Maxime Paillassa, Emmanuel Bertin, Hervé Bouy

In this work, we propose two convolutional neural network classifiers for detecting contaminants in astronomical images. Once trained, our classifiers are able to identify various contaminants, such as cosmic rays, hot and bad pixels, persistence effects, satellite or plane trails, residual fringe patterns, nebulous features, saturated pixels, diffraction sp

Adrian S. Hamers, Todd A. Thompson

The isolated binary evolution model for merging neutron stars (NSs) involves processes such as mass transfer, common-envelope evolution, and natal kicks, all of which are poorly understood. Also, the predicted NS-NS merger rates are typically lower than the rates inferred from the LIGO GW170817 event. Here, we investigate merger rates of NS and black hole (B

Feng Peng, Yanming Ma, Maosheng Miao

We demonstrate in this paper that high pressure can promote the reactions between the ionic compounds and H2 molecules and form thermodynamically stable hybrid compounds. Using crystal structure search method based on first principles calculations and particle swarm optimization algorithm, we show that many alkali halides XY (X=Na, K, Rb, Cs; Y=Cl, Br, I) ca

Ying Xu, Zhihua Qu, Roland Harvey, Toru Namerikawa

A novel wide-area control design is presented to mitigate inter-area power frequency oscillations. A large-scale power system is decomposed into a network of passivity-short subsystems whose nonlinear interconnections have a state-dependent affine form, and by utilizing the passivity shortage framework a two-level design procedure is developed. At the lower

Sheehan Olver, Yuan Xu

The wave equation $\left(\partial_{tt} - c^2 Δ_x\right) u(x,t) = e^{-t} f(x,t)$ is shown to have a unique solution if $u$ and its partial derivatives in $x$ are in $L^2(e^{-t})$ on the cone, and the solution can be explicit given in the Fourier series of orthogonal polynomials on the cone. This provides a particular solution for the boundary value problems o

Samrat Acharya, Yury Dvorkin, Ramesh Karri

High-wattage demand-side appliances such as Plug-in Electric Vehicles (PEVs) are proliferating. As a result, information on the charging patterns of PEVs is becoming accessible via smartphone applications, which aggregate real-time availability and historical usage of public PEV charging stations. Moreover, information on the power grid infrastructure and op

Bennet Meyers, Michael Deceglie, Chris Deline, Dirk Jordan

A novel unsupervised machine learning approach for analyzing time-series data is applied to the topic of photovoltaic (PV) system degradation rate estimation, sometimes referred to as energy-yield degradation analysis. This approach only requires a measured power signal as an input--no irradiance data, temperature data, or system configuration information. W

J. D. P. Machado, Ya. M. Blanter

Phenomena such as state-swap, quadrature squeezing, entanglement and violation of entanglement inequalities are frequently reported to occur in quantum systems only. It is shown here that these effects can also occur in cholesteric liquid crystals in the presence of an applied magnetic field. The nature of these effects as well as the conditions for their ob

Li Ling, Zhiqiang Gao, Michael A Silas, Ian Lee

Banking Trojans, botnets are primary drivers of financially-motivated cybercrime. In this paper, we first analyzed how an APT-based banking botnet works step by step through the whole lifecycle. Specifically, we present a multi-stage system that detects malicious banking botnet activities which potentially target the organizations. The system leverages Cyber

Yaohua Zang, Gang Bao, Xiaojing Ye, Haomin Zhou

Solving general high-dimensional partial differential equations (PDE) is a long-standing challenge in numerical mathematics. In this paper, we propose a novel approach to solve high-dimensional linear and nonlinear PDEs defined on arbitrary domains by leveraging their weak formulations. We convert the problem of finding the weak solution of PDEs into an oper

John Southworth, M. Dominik, U. G. Jorgensen, M. I. Andersen

Transits in the planetary system WASP-4 were recently found to occur 80s earlier than expected in observations from the TESS satellite. We present 22 new times of mid-transit that confirm the existence of transit timing variations, and are well fitted by a quadratic ephemeris with period decay dP/dt = -9.2 +/- 1.1 ms/yr. We rule out instrumental issues, stel

Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle

The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs. However, construction histories for these discrete objects are typically not unique and so generative models must reason about intractably large spaces in order to learn. Additionally, structured disc

S. Rojas-Rojas, E. Barriga, C. Muñoz, P. Solano

We present a scheme for generating and manipulating three-mode squeezed states with genuine tripartite entanglement by injecting single-mode squeezed light into an array of coupled optical waveguides. We explore the possibility to selectively generate single-mode squeezing or multimode squeezing at the output of an elliptical waveguides array, determined sol

Tarak Nath Maity, Tirtha Sankar Ray

Assisted annihilation is a novel mechanism to generate viable sub-GeV thermal dark matter, where a pair of stable dark matter annihilates with an assister to Standard Model states. Typically such $3 \to 2$ annihilation topologies are flux suppressed compared to $2 \to 2$ processes. In this paper, we explore the possibility of a resonant $3 \to 2$ assisted an

Caroline Moosmüller, Felix Dietrich, Ioannis G. Kevrekidis

Different observations of a relation between inputs ("sources") and outputs ("targets") are often reported in terms of histograms (discretizations of the source and the target densities). Transporting these densities to each other provides insight regarding the underlying relation. In (forward) uncertainty quantification, one typically studie

Adam Freese, Ian C. Cloët

We calculate the leading-twist, helicity-independent generalized parton distributions (GPDs) of the proton, at finite skewness, in the Nambu--Jona-Lasinio (NJL) model of quantum chomodynamics (QCD). The NJL model reproduces low-energy characteristics of QCD, including dynamical chiral symmetry breaking (DCSB). The proton bound-state amplitude is solved for u

Apurba Das

Dendriform coalgebras are the dual notion of dendriform algebras and are splitting of associative coalgebras. In this paper, we define a cohomology theory for dendriform coalgebras based on some combinatorial maps. We show that the cohomology with self coefficients governs the formal deformation of the structure. We also relate this cohomology with the cohom

Angelos Alexopoulos, Leonardo Bottolo

We develop a novel Bayesian method to select important predictors in regression models with multiple responses of diverse types. A sparse Gaussian copula regression model is used to account for the multivariate dependencies between any combination of discrete and/or continuous responses and their association with a set of predictors. We utilize the parameter

Zad Rafi

A recently published randomized controlled trial in JAMA investigated the impact of the selective serotonin reuptake inhibitor, escitalopram, on the risk of major adverse events (MACE). The authors estimated a hazard ratio (HR) of 0.69 (95% CI: 0.49, 0.96; $p$ = 0.03) and then attempted to calculate how much statistical power their study (test) had attained,

Yoshimasa Hidaka, Yuki Minami

We discuss spontaneous symmetry breaking of open classical and quantum systems. When a continuous symmetry is spontaneously broken in an open system, a gapless excitation mode appears corresponding to the Nambu-Goldstone mode. Unlike isolated systems, the gapless mode is not always a propagation mode, but it is a diffusion one. Using the Ward-Takahashi ident

Santiago Hernández-Gómez, Stefano Gherardini, Francesco Poggiali, Francesco S. Cataliotti

Elucidating the energy transfer between a quantum system and a reservoir is a central issue in quantum non-equilibrium thermodynamics, which could provide novel tools to engineer quantum-enhanced heat engines. The lack of information on the reservoir inherently limits the practical insight that can be gained on the exchange process of open quantum systems. H

Anthony C. K. Leung, Tom Kirchner

The processes of electron excitation, capture, and ionization were investigated in proton collisions with atomic hydrogen in the initial $n=1$ and $n=2$ states at impact energies from 1 to 300 keV. The theoretical analysis is based on the close-coupling two-center basis generator method in the semiclassical approximation. Calculated cross sections are compar

M. A. Arroyo-Ureña, R. Gaitan, R. Martinez, J. H. Montes de Oca Yemha

We study Dark Matter (DM) abundance in the framework of the extension of the Standard Model (SM) with an additional $U(1)_X$ gauge symmetry. One complex singlet is included to break the $U(1)_X$ gauge symmetry, meanwhile one of the doublets is considered inert to introduce a DM candidate. The stability of the DM candidate is analyzed with a continuous $U(1)_

Siddarth Koduru Joshi, Djeylan Aktas, Sören Wengerowsky, Martin Lončarić

Quantum communication is rapidly gaining popularity due to its high security and technological maturity. However, most implementations are limited to just two communicating parties (users). Quantum communication networks aim to connect a multitude of users. Here we present a fully connected quantum communication network on a city wide scale without active sw

Indira Sen, Fabian Floeck, Katrin Weller, Bernd Weiss

Peoples' activities and opinions recorded as digital traces online, especially on social media and other web-based platforms, offer increasingly informative pictures of the public. They promise to allow inferences about populations beyond the users of the platforms on which the traces are recorded, representing real potential for the Social Sciences and a co

Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala

Gradient-based algorithms are effective for many machine learning tasks, but despite ample recent effort and some progress, it often remains unclear why they work in practice in optimising high-dimensional non-convex functions and why they find good minima instead of being trapped in spurious ones. Here we present a quantitative theory explaining this behavi

Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine

Reinforcement learning requires manual specification of a reward function to learn a task. While in principle this reward function only needs to specify the task goal, in practice reinforcement learning can be very time-consuming or even infeasible unless the reward function is shaped so as to provide a smooth gradient towards a successful outcome. This shap

Arpan Bhattacharyya, Pratik Nandy, Aninda Sinha

We propose a modification to Nielsen's circuit complexity for Hamiltonian simulation using the Suzuki-Trotter (ST) method, which provides a network like structure for the quantum circuit. This leads to an optimized gate counting linear in the geodesic distance and spatial volume, unlike in the original proposal. The optimized ST iteration order is correl

Lasko Basnarkov, Miroslav Mirchev, Ljupco Kocarev

We study random walk on complex networks with transition probabilities which depend on the current and previously visited nodes. By using an absorbing Markov chain we derive an exact expression for the mean first passage time between pairs of nodes, for a random walk with a memory of one step. We have analyzed one particular model of random walk, where the t

Nakarin Lohitsiri, David Tong

We explore the phase structure of the Standard Model as the relative strengths of the SU(2) weak force and SU(3) strong force are varied. With a single generation of fermions, the structure of chiral symmetry breaking suggests that there is no phase transition as we interpolate between the SU(3)-confining phase and the SU(2)-confining phase. Remarkably, the

Giacomo Fragione, Abraham Loeb

Observations of black hole-neutron star (BH-NS) mergers via gravitational waves (GWs) are of great interest for their electromagnetic counterparts, such as short gamma-ray bursts, and could provide crucial information on the nature of BHs and the NS crust and magnetosphere. While no event has been confirmed, a recent possible detection of a BH-NS merger even

M. Lemoine, A. Vanthieghem, G. Pelletier, L. Gremillet

In this second paper of a series, we discuss the dynamics of a plasma entering the precursor of an unmagnetized, relativistic collisionless pair shock. We discuss how this background plasma is decelerated and heated through its interaction with a microturbulence that results from the growth of a current filamentation instability (CFI) in the shock precursor.

Arlene C. Aguilar, Zafir Ahmed, Christine Aidala, Salina Ali

Understanding the origin and dynamics of hadron structure and in turn that of atomic nuclei is a central goal of nuclear physics. This challenge entails the questions of how does the roughly 1 GeV mass-scale that characterizes atomic nuclei appear; why does it have the observed value; and, enigmatically, why are the composite Nambu-Goldstone (NG) bosons in q

Manuel Valiente

I consider a particle in the topologically non-trivial Su-Schrieffer-Heeger (SSH) model interacting strongly with a mobile impurity, whose quantum dynamics is described by a topologically trivial Hamiltonian. A particle in the SSH model admits a topological zero-energy edge mode when a hard boundary is placed at a given site of the chain, which may be modell

Annabelle Bohrdt, Fabian Grusdt, Michael Knap

We numerically study the real-time dynamics of a single hole created in the $t-J$ model on a square lattice. Initially, the hole spreads ballistically with a velocity proportional to the hopping matrix element. At intermediate to long times, the dimensionality as well as the spin background determine the hole dynamics. A hole created in the ground state of a

Bhaskar Mukherjee, Sourav Nandy, Arnab Sen, Diptiman Sen

The presence of quantum scars, athermal eigenstates of a many-body Hamiltonian with finite energy density, leads to absence of ergodicity and long-time coherent dynamics in closed quantum systems starting from simple initial states. Such non-ergodic coherent dynamics, where the system does not explore its entire phase space, has been experimentally observed

Adrian Liu, J. Richard Shaw

The redshifted 21 cm line is an emerging tool in cosmology, in principle permitting three-dimensional surveys of our Universe that reach unprecedentedly large volumes, previously inaccessible length scales, and hitherto unexplored epochs of our cosmic timeline. Large radio telescopes have been constructed for this purpose, and in recent years there has been

Giacomo Pantaleoni, Ben Q. Baragiola, Nicolas C. Menicucci

We introduce a framework to decompose a bosonic mode into two virtual subsystems-a logical qubit and a gauge mode. This framework allows the entire toolkit of qubit-based quantum information to be applied in the continuous-variable setting. We give a detailed example based on a modular decomposition of the position basis and apply it in two situations. First

Anders Andreassen, Benjamin Nachman

Precise scientific analysis in collider-based particle physics is possible because of complex simulations that connect fundamental theories to observable quantities. The significant computational cost of these programs limits the scope, precision, and accuracy of Standard Model measurements and searches for new phenomena. We therefore introduce Deep neural n

Santanu Dey, Eric C. Andrade, Matthias Vojta

We consider frustrated Heisenberg antiferromagnets, whose clean-limit ground state is characterized by non-collinear long-range order with non-zero vector chirality, and study the effects of quenched bond disorder, i.e., random exchange couplings. A single bond defect is known to induce a dipolar texture in the spin background independent of microscopic deta

Christoph A. Keller, Ida G. Zadeh

We investigate second order conformal perturbation theory for $\mathbb{Z}_2$ orbifolds of conformal field theories in two dimensions. To evaluate the necessary twisted sector correlation functions and their integrals, we map them from the sphere to its torus double cover. We discuss how this relates crossing symmetry to the modular group, and introduce a reg

Taeho Ryu, Julian Krolik, Tsvi Piran, Scott Noble

A star is tidally disrupted by a supermassive black hole when their separation is shorter than the "tidal radius". This quantity is often estimated on an order-of-magnitude basis without reference to the star's internal structure. Using MESA models for main sequence stars and fully general relativistic dynamics, we find the physical tidal radius

Dominic V. Else, Ryan Thorngren

The Lieb-Schultz-Mattis (LSM) theorem states that a spin system with translation and spin rotation symmetry and half-integer spin per unit cell does not admit a gapped symmetric ground state lacking fractionalized excitations. That is, the ground state must be gapless, spontaneously break a symmetry, or be a gapped spin liquid. Thus, such systems are natural

Chinmayee Mishra, Luis Santos, Rejish Nath

We analyze the physics of self-bound droplets in a doubly dipolar Bose-Einstein condensate (DDBEC) composed by particles with both electric and magnetic dipole moments. Using the particularly relevant case of dysprosium, we show that the anisotropy of the doubly-dipolar interaction potential is highly versatile and nontrivial, depending critically on the rel

Thomas Vojta, Sarah Skinner, Ralf Metzler

We investigate anomalous diffusion processes governed by the fractional Langevin equation and confined to a finite or semi-infinite interval by reflecting potential barriers. As the random and damping forces in the fractional Langevin equation fulfill the appropriate fluctuation-dissipation relation, the probability density on a finite interval converges for

Tom Westerhout, Nikita Astrakhantsev, Konstantin S. Tikhonov, Mikhail Katsnelson

Neural quantum states (NQS) attract a lot of attention due to their potential to serve as a very expressive variational ansatz for quantum many-body systems. Here we study the main factors governing the applicability of NQS to frustrated magnets by training neural networks to approximate ground states of several moderately-sized Hamiltonians using the corres

Sara Canilang, Michael P. Cohen, Nicolas Graese, Ian Seong

Let $X$ be a space equipped with $n$ topologies $\tau_1,...,\tau_n$ which are pairwise comparable and saturated, and for each $1\leq i\leq n$ let $k_i$ and $f_i$ be the associated topological closure and frontier operators, respectively. Inspired by the closure-complement theorem of Kuratowski, we prove that the monoid of set operators $\mathcal{KF}_n$ gener

Son Pham-Ba, Tobias Brink, Jean-François Molinari

Current engineering wear models are often based on empirical parameters rather than built upon physical considerations. Here, we look for a physical description of adhesive wear at the microscale, at which the interaction between two surfaces comes down to the contact of asperities. Recent theoretical work has shown that there is a critical micro-contact siz

Antoine Gloria

Consider an infinite cloud of hard spheres sedimenting in a Stokes flow in the whole space $\mathbb R^d$. Despite many contributions in fluid mechanics and applied mathematics, there is so far no rigorous definition of the associated effective sedimentation velocity. Calculations by Caflisch and Luke in dimension $d=3$ suggest that the effective velocity is

Ulbossyn Ualikhanova, Manuel Hohmann

We derive the post-Newtonian limit of a general class of teleparallel gravity theories, whose action is given by a free function of three scalar quantities obtained from the torsion of the teleparallel connection. This class of theories is chosen to be sufficiently generic in order to include the $f(T)$ class of theories as well as new general relativity as

Can Li, Catherine E. Graves, Xia Sheng, Darrin Miller

A content-addressable-memory compares an input search word against all rows of stored words in an array in a highly parallel manner. While supplying a very powerful functionality for many applications in pattern matching and search, it suffers from large area, cost and power consumption, limiting its use. Past improvements have been realized by using memrist

Philipp Grimm, Gary Razinskas, Jer-Shing Huang, Bert Hecht

Coherent perfect absorption (CPA) describes the absence of all outgoing modes from a lossy resonator, driven by lossless incoming modes. Here, we show that for nanoresonators that also exhibit radiative losses, e.g. plasmonic nanoantennas, a generalized version of CPA (gCPA) can be applied. In gCPA outgoing modes are sup-pressed only for a subset of (guided