November 2019 arXiv papers — page 52

Paolo Bartesaghi, Stefano Benati, Gian Paolo Clemente, Rosanna Grassi

Understanding the structure of communities in a network has a great importance in the economic analysis. Communities are indeed characterized by specific properties, that are different from those of both the individual node and the whole network, and they can affect various processes on the network. In the International Trade Network, community detection aim

Federico Norbiato, Flavio Seno, Antonio Trovato, Marco Baiesi

Many native structures of proteins accomodate complex topological motifs such as knots, lassos, and other geometrical entanglements. How proteins can fold quickly even in the presence of such topological obstacles is a debated question in structural biology. Recently, the hypothesis that energetic frustration might be a mechanism to avoid topological frustra

Jason A. Platt, Anna Miller, Lawson Fuller, Henry D. I. Abarbanel

We present a novel machine learning architecture for classification suggested by experiments on olfactory systems. The network separates input stimuli, represented as spatially distinct currents, via winnerless competition---a process based on the intrinsic sequential dynamics of the neural system---then uses a support vector machine (SVM) to provide precisi

Gady Kozma, Ron Peled

The vertex-reinforced jump process (VRJP) is a form of self-interacting random walk in which the walker is biased towards returning to previously visited vertices with the bias depending linearly on the local time at these vertices. We prove that, for any initial bias, the weights sampled from the magic formula on a two-dimensional graph decay at least at a

Niall Taggart

We construct the unitary analogue of orthogonal calculus developed by Weiss, utilising model categories to give a clear description of the intricacies in the equivariance and homotopy theory involved. The subtle differences between real and complex geometry lead to subtle differences between orthogonal and unitary calculus. To address these differences we co

Agustín Rost, Federico Stasyszyn, Luis Pereyra, Héctor J. Martínez

In this work we compare three catalogues of cosmological filaments identified in the Sloan Digital Sky Survey by means of different algorithms by Tempel et al., Pereyra et al., and Martínez et al. We analyse how different identification techniques determine differences in the filament statistical properties: length, elongation, redshift distribution, and abu

Mauricio Toledo-Acosta

In this work we study and provide a full description, up to a finite index subgroup, of the dynamics of solvable complex Kleinian subgroups of PSL(3,C). These groups havesimpledynamics, contrary to strongly irre-ducible groups. Because of this, we propose to define elementary subgroups of PSL(3,C) as solvable groups. We show that triangular groups can be de-

Shuang Zhang, Ada Zhen, Robert L. Stevenson

Removing spatially variant motion blur from a blurry image is a challenging problem as blur sources are complicated and difficult to model accurately. Recent progress in deep neural networks suggests that kernel free single image deblurring can be efficiently performed, but questions about deblurring performance persist. Thus, we propose to restore a sharp i

Michael Krivelevich, Gal Kronenberg, Adva Mond

We study the Tur\'an number of long cycles in random graphs and in pseudo-random graphs. Denote by $ex(G(n,p),H)$ the random variable counting the number of edges in a largest subgraph of $G(n,p)$ without a copy of $H$. We determine the asymptotic value of $ex(G(n,p), C_t)$ where $C_t$ is a cycle of length $t$, for $p\geq \frac Cn$ and $A \log n \leq t \leq

Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai

Graph representation learning is to learn universal node representations that preserve both node attributes and structural information. The derived node representations can be used to serve various downstream tasks, such as node classification and node clustering. When a graph is heterogeneous, the problem becomes more challenging than the homogeneous graph

Alex Albaugh, Todd R. Gingrich

Reaction rates are a complicated function of molecular interactions, which can be selected from vast chemical design spaces. Seeking the design that optimizes a rate is a particularly challenging problem since the rate calculation for any one design is itself a difficult computation. Toward this end, we demonstrate a strategy based on transition path samplin

Sreevatsa Anantharamu, Krishnan Mahesh

The sources of wall-pressure fluctuations in turbulent channel flow are studied using a novel framework. The wall-pressure power spectral density (PSD) $(\phi_{pp}(\omega))$ is expressed as an integrated contribution from all wall-parallel plane pairs, $\phi_{pp}(\omega)=\int_{-\delta}^{+\delta}\int_{-\delta}^{+\delta}\Gamma(r,s,\omega)\,\mathrm{dr}\,\mathrm

Marius Junge, Nicholas LaRacuente, Cambyse Rouzé

We generalize Holley-Stroock's perturbation argument from commutative to quantum Markov semigroups. As a consequence, results on (complete) modified logarithmic Sobolev inequalities and logarithmic Sobolev inequalities for self-adjoint quantum Markov process can be used to prove estimates on the exponential convergence in relative entropy of quantum Markov s

Ayush Jain, Alon Orlitsky

Many applications, including natural language processing, sensor networks, collaborative filtering, and federated learning, call for estimating discrete distributions from data collected in batches, some of which may be untrustworthy, erroneous, faulty, or even adversarial. Previous estimators for this setting ran in exponential time, and for some regimes re

Taesun Moon, Parul Awasthy, Jian Ni, Radu Florian

Information extraction is an important task in NLP, enabling the automatic extraction of data for relational database filling. Historically, research and data was produced for English text, followed in subsequent years by datasets in Arabic, Chinese (ACE/OntoNotes), Dutch, Spanish, German (CoNLL evaluations), and many others. The natural tendency has been to

Alexander Rogozin, Alexander Gasnikov

Decentralized distributed optimization over time-varying graphs (networks) is nowadays a very popular branch of research in optimization theory and consensus theory. One of the motivations to consider such networks is an application to drone networks. However, the first theoretical results in this branch appeared only five years ago (Nedic, 2014). The first

Zoltan Bajnok, Istvan Vona

The vacuum expectation values of conserved currents play an essential role in the generalized hydrodynamics of integrable quantum field theories. We use analytic continuation to extend these results for the excited state expectation values in a finite volume. Our formulas are valid for diagonally scattering theories and incorporate all finite size correction

Omar U. Florez, Erik Mueller

Memory Networks have emerged as effective models to incorporate Knowledge Bases (KB) into neural networks. By storing KB embeddings into a memory component, these models can learn meaningful representations that are grounded to external knowledge. However, as the memory unit becomes full, the oldest memories are replaced by newer representations. In this pap

Bruno Ferman, Cristine Pinto

We analyze the properties of the Synthetic Control (SC) and related estimators when the pre-treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre-treatment periods goes to infinity. Still, we show that a demeaned version

Shamma Nasrin, Srikanth Ramakrishna, Theja Tulabandhula, Amit Ranjan Trivedi

In this work, we introduce bitcell array-based support parameters to improve the prediction accuracy of SRAM-based binarized neural network (SRAM-BNN). Our approach enhances the training weight space of SRAM-BNN while requiring minimal overheads to a typical design. More flexibility of the weight space leads to higher prediction accuracy in our design. We ad

Danilo Francati, Giuseppe Ateniese, Abdoulaye Faye, Andrea Maria Milazzo

The cloud changed the way we manage and store data. Today, cloud storage services offer clients an infrastructure that allows them a convenient source to store, replicate, and secure data online. However, with these new capabilities also come limitations, such as lack of transparency, limited decentralization, and challenges with privacy and security. And, a

Arindam Mazumdar, Subhendra Mohanty, Priyank Parashari

Short baseline neutrino experiments, like LSND and MiniBooNE experiments, pointed towards the existence of eV mass scale sterile neutrinos. To reconcile sterile neutrinos with cosmology self interaction between sterile neutrinos has been studied. We analysed Planck cosmic microwave background (CMB) data with self-interacting sterile neutrino (SI$ν$) and stud

Radu-Alexandru Dragomir, Adrien Taylor, Alexandre d'Aspremont, Jérôme Bolte

We provide a lower bound showing that the $O(1/k)$ convergence rate of the NoLips method (a.k.a. Bregman Gradient) is optimal for the class of functions satisfying the $h$-smoothness assumption. This assumption, also known as relative smoothness, appeared in the recent developments around the Bregman Gradient method, where acceleration remained an open issue

Hector J. Hortua, Riccardo Volpi, Dimitri Marinelli, Luigi Malagò

In this paper, we present the first study that compares different models of Bayesian Neural Networks (BNNs) to predict the posterior distribution of the cosmological parameters directly from the Cosmic Microwave Background temperature and polarization maps. We focus our analysis on four different methods to sample the weights of the network during training:

Sevgi Karadağ, Mehmet Cem Güçlü

Ultra-relativistic peripheral collisions of heavy ions at LHC can produce copies of numbers of lepton pairs via the two-photon process. Since the energy of the heavy ions is so high, multi-pair production cross-sections of the light leptons especially electrons are quite large so that it is possible to measure them experimentally. To calculate the multi-pair

R. J. Bueno Rogerio

In the present communication we employ a split programme applied to spinors belonging to the regular and singular sectors of the Lounesto's classification, looking towards to unveil how it can be built or defined upon two spinors arrangement. We separate the spinors into two distinct parts and investigate to which class within the Lounesto's classifi

Gil Badel, Gabriel Cuomo, Alexander Monin, Riccardo Rattazzi

In arXiv:1909.01269 it was shown that the scaling dimension of the lightest charge $n$ operator in the $U(1)$ model at the Wilson-Fisher fixed point in $d=4-\varepsilon$ can be computed semiclassically for arbitrary values of $λn$, where $λ$ is the perturbatively small fixed point coupling. Here we generalize this result to the fixed point of the $U(1)$ mode

Yichen Xu, Hao Geng, Xiao-Chuan Wu, Chao-Ming Jian

Non-fermi liquid and unconventional quantum critical points (QCP) with strong fractionalization are two exceptional phenomena beyond the classic condensed matter doctrines, both of which could occur in strongly interacting quantum many-body systems. This work demonstrates that using a controlled method one can construct a non-Fermi liquid within a considerab

F. Bezrukov, A. Chudaykin, D. Gorbunov

It has been recently suggested \cite{Bezrukov:2017ike,Bezrukov:2018wvd} that a cosmic scalar field can completely change the keV-scale sterile neutrino production in the early Universe. Its effect may, for various parameter choices, either suppress sterile neutrino production and make moderate active-sterile mixing cosmologically acceptable, or increase the

Yohanes S. Gani, Eric J. Walter, Enrico Rossi

We study the electronic structure of heterostructures formed by a graphene nanoribbon (GNR) and a transition metal dichalcogenides (TMD) monolayer using first-principles. We consider both semiconducting TMDs and metallic TMDs, and different stacking configurations. We find that when the TMD is semiconducting the effects on the band structure of the GNRs are

N. Jordana-Mitjans, C. G. Mundell, S. Kobayashi, R. J. Smith

We report multi-color optical imaging and polarimetry observations of the afterglow of the first TeV- detected gamma-ray burst, GRB 190114C, using RINGO3 and MASTER II polarimeters. Observations begin 31 s after the onset of the GRB and continue until $\sim 7000\,$s post-burst. The light curves reveal a chromatic break at $\sim 400- 500\,$s, with initial tem

Elina Fuchs, Marta Losada, Yosef Nir, Yehonatan Viernik

The upper bounds from the ATLAS and CMS experiments on the decay rate of the Higgs boson to two muons provide the strongest constraint on an imaginary part of the muon Yukawa coupling. This bound is more than an order of magnitude stronger than bounds from $\mathcal{CP}$-violating observables, specifically the electric dipole moment of the electron. It exclu

Aurel Schneider, Alexandre Refregier, Sebastian Grandis, Dominique Eckert

An accurate modelling of baryonic feedback effects is required to exploit the full potential of future weak-lensing surveys such as Euclid or LSST. In this second paper in a series of two, we combine Euclid-like mock data of the cosmic shear power spectrum with an eROSITA X-ray mock of the cluster gas fraction to run a combined likelihood analysis including

J. D. Simon, T. S. Li, D. Erkal, A. B. Pace

We present Magellan/IMACS spectroscopy of three recently discovered ultra-faint Milky Way satellites, Grus II, Tucana IV, and Tucana V. We measure systemic velocities of V_hel = -110.0 +/- 0.5 km/s, V_hel = 15.9 +/- 1.8 km/s, and V_hel = -36.2 +/-2.5 km/s for the three objects, respectively. Their large relative velocity differences demonstrate that the sate

Ian Low, Zhewei Yin

Nonlinear sigma model (NLSM) based on the coset $\text{SU}(N)\times \text{SU}(N)/\text{SU}(N)$ exhibits several intriguing features at the leading ${\cal O}(p^2)$ in the derivative expansion, such as the flavor-kinematics duality and an extended theory controlling the single and triple soft limits. In both cases the cubic biadjoint scalar theory plays a prom

Alexios P. Polychronakos

We demonstrate that fluid mechanical systems arising from large fluctuations of one-dimensional statistical processes generically exhibit solitons and nonlinear waves. We derive the explicit form of these solutions and examine their properties for the specific cases of the Kipnis-Marchioro-Presutti model (KMP) and the Symmetric Exclusion Process (SEP). We sh

K. Aggarwal, Z. Arzoumanian, P. T. Baker, A. Brazier

The mergers of supermassive black hole binaries (SMBHBs) promise to be incredible sources of gravitational waves (GWs). While the oscillatory part of the merger gravitational waveform will be outside the frequency sensitivity range of pulsar timing arrays (PTAs), the non-oscillatory GW memory effect is detectable. Further, any burst of gravitational waves wi

Hanbit Oh, Eun-Gook Moon

Exotic quantum phases including topological states and non-Fermi liquids may be realized by quantum states with total angular momentum $j=3/2$, as manifested in HgTe and pyrochlore iridates. Recently, an exotic superconducting state with non-zero density of states of zero energy Bogoliubov (BG) quasiparticles, Bogoliubov Fermi-surface (BG-FS), was also propo

Markus A. Ebert, Frank J. Tackmann

Kinematic selection cuts and isolation requirements are a necessity in experimental measurements for identifying prompt leptons and photons that originate from the hard-interaction process of interest. We analyze how such cuts affect the application of the $q_T$ and $N$-jettiness subtraction methods for fixed-order calculations. We consider both fixed-cone a

Andrea Dei, Lorenz Eberhardt

We exploit null vectors of the fractional Virasoro algebra of the symmetric product orbifold to compute correlation functions of twist fields in the large $N$ limit. This yields a new method to derive correlation functions in these orbifold CFTs that is purely based on the symmetry algebra. We explore various generalisations, such as subleading (torus) contr

Srinivasan Raghunathan, Seshadri Nadathur, Blake D. Sherwin, Nathan Whitehorn

We report a $5.3σ$ detection of the gravitational lensing effect of cosmic voids from the Baryon Oscillation Spectroscopic (BOSS) Data Release 12 seen in the $Planck$ 2018 cosmic microwave background (CMB) lensing convergence map. To make this detection, we introduce new optimal techniques for void stacking and filtering of the CMB maps, such as binning void

Adolfo Arroyo-Rabasa, Anna Skorobogatova

We establish certain fine properties for functions of bounded $\mathscr A$-variation known in the classical $BV$ setting. Here, $\mathscr A$ is a $k$th order constant-coefficient homogeneous linear differential operator with a finite-dimensional kernel (also known as a complex-elliptic operator). We prove that if $\mathscr Au$ can be represented by a finite

Nayara Fonseca, Enrico Morgante, Ryosuke Sato, Géraldine Servant

In implementations of the electroweak scale cosmological relaxation mechanism proposed so far, the effect of the quantum fluctuations of the homogeneous relaxion field has been ignored. We show that they can grow during the classical cosmological evolution of the relaxion field passing through its many potential barriers. The resulting production of relaxion

Nayara Fonseca, Enrico Morgante, Ryosuke Sato, Géraldine Servant

We investigate the production of axion quanta during the early universe evolution of an axion-like field rolling down a wiggly potential. We compute the growth of quantum fluctuations and their back-reaction on the homogeneous zero-mode. We evaluate the transfer of kinetic energy from the zero mode to the quantum fluctuations and the conditions to decelerate

Giovanni Aricò, Raul E. Angulo, Carlos Hernández-Monteagudo, Sergio Contreras

We present and test a framework that models the three-dimensional distribution of mass in the Universe as a function of cosmological and astrophysical parameters. Our approach combines two different techniques: a rescaling algorithm that modifies the cosmology of gravity-only N-body simulations, and a baryonification algorithm which mimics the effects of ast

Charles Daly, Jonah Gaster, Max Lahn, Aisha Mechery

A collection $ Δ$ of simple closed curves on an orientable surface is an algebraic $ k $-system if the algebraic intersection number $\langle α,β\rangle$ is equal to $k $ in absolute value for every $ α, β\in Δ$ distinct. Generalizing a theorem of [MRT14] we compute that the maximum size of an algebraic $k$-system of curves on a surface of genus $g$ is $2g+1

Nishant Mohan, Steven B. Lowen, Malvin Carl Teich

A broad variety of light sources exhibit photon-count fluctuations that display inverse-square spectral behavior at extremely low frequencies. These sources include light-emitting diodes, superluminescent diodes, laser diodes, incandescent sources, and betaluminescent sources. In a series of experiments carried out over an 18-month period, the photon-count f

Chandrakala Meena, Pranay Deep Rungta, Sudeshna Sinha

We investigate the collective dynamics of chaotic multi-stable Duffing oscillators connected in different network topologies, ranging from star and ring networks, to scale-free networks. We estimate the resilience of such networks by introducing a variant of the concept of multi-node Basin Stability, which allows us to gauge the global stability of the colle

Zachary A. H. Goodwin, Valerio Vitale, Fabiano Corsetti, Dmitri K. Efetov

The effective interaction between electrons in two-dimensional materials can be modified by their environment, enabling control of electronic correlations and phases. Here, we study the dependence of electronic correlations in twisted bilayer graphene (tBLG) on the separation to the metallic gate(s) in two device configurations. Using an atomistic tight-bind

Gabriel Synnaeve, Qiantong Xu, Jacob Kahn, Tatiana Likhomanenko

We study pseudo-labeling for the semi-supervised training of ResNet, Time-Depth Separable ConvNets, and Transformers for speech recognition, with either CTC or Seq2Seq loss functions. We perform experiments on the standard LibriSpeech dataset, and leverage additional unlabeled data from LibriVox through pseudo-labeling. We show that while Transformer-based a

Li Lai, Pin Yu

It is proved that, for all odd integer $s \geqslant s_0(\varepsilon)$, there are at least $\big( c_0 - \varepsilon \big) \frac{s^{1/2}}{(\log s)^{1/2}} $ many irrational numbers among the following odd zeta values: $\zeta(3),\zeta(5),\zeta(7),\cdots,\zeta(s)$. The constant $c_0 = 1.192507\ldots$ can be expressed in closed form. The work is based on the previ

L. S. I. Veiga, J. R. L. Mardegan, M. v. Zimmermann, D. T. Maimone

We explore the evolution of the structural phase transition of $\rm{(Sr, Ca)_3Ir_4Sn_{13}}$, a model system to study the interplay between structural quantum criticality and superconductivity, by means of high-energy x-ray diffraction measurements at high pressures and low temperatures. Our results confirm a rapid suppression of the superlattice transition t

Sungbong Chun, Sergei Gukov, Sunghyuk Park, Nikita Sopenko

One of the main challenges in 3d-3d correspondence is that no existent approach offers a complete description of 3d $N=2$ SCFT $T[M_3]$ --- or, rather, a "collection of SCFTs" as we refer to it in the paper --- for all types of 3-manifolds that include, for example, a 3-torus, Brieskorn spheres, and hyperbolic surgeries on knots. The goal of this paper is to

Ji Wang, Miroslav Krstic

A deep-sea construction vessel is used to install underwater parts of an off-shore oil drilling platform at the designated locations on the seafloor. By using extended Hamilton's principle, a nonlinear PDE system governing the lateral-longitudinal coupled vibration dynamics of the deep-sea construction vessel consisting of a time-varying-length cable with an

Punit Gandhi, Sara Bonetti, Sarah Iams, Amilcare Porporato

From infiltration of water into the soil during rainstorms to seasonal plant growth and death, the ecohydrological processes that are thought to be relevant to the formation of banded vegetation patterns in drylands occur across multiple timescales. We propose a new fast-slow switching model in order to capture these processes on appropriate timescales withi

Stijn Cambie, Rémi de Joannis de Verclos, Ross J. Kang

Motivated by a Gan-Loh-Sudakov-type problem, we introduce the regular Tur\'an numbers, a natural variation on the classical Tur\'an numbers for which the host graph is required to be regular. Among other results, we prove a striking supersaturation version of Mantel's theorem in the case of a regular host graph of odd order. We also characterise the graphs f

E. Lacchin, F. Matteucci, F. Vincenzo, M. Palla

We test the integrated galactic initial mass function (IGIMF) on the chemical evolution of 16 ultra-faint dwarf (UFD) galaxies discussing in detail the results obtained for three of them: Boötes I, Boötes II and Canes Venatici I, taken as prototypes of the smallest and the largest UFDs. These objects have very small stellar masses ($\sim 10^3-10^4 \mathrm{M_

Ivan Cherednik

We propose a mathematical model of momentum risk-taking, which is essentially real-time risk management focused on short-term volatility of stock markets. Its implementation, our fully automated momentum equity trading system presented systematically, proved to be successful in extensive historical and real-time experiments. Momentum risk-taking is one of th

Amarlingam Madapu, Santiago Segarra, Sundeep Prabhakar Chepuri, Antonio G. Marques

We study the problem of missing data imputation for graph signals from signed one-bit quantized observations. More precisely, we consider that the true graph data is drawn from a distribution of signals that are smooth or bandlimited on a known graph. However, instead of observing these signals, we observe a signed version of them and only at a subset of the

Thomas Walker, Samir Vartabi Kashanian, Travers Ward, Matthias Keller

We investigate schemes for generating indistinguishable single photons, a key feature of quantum networks, from a trapped ion coupled to an optical cavity. Through selection of the initial state in a cavity-assisted Raman transition, we suppress the detrimental effect of spontaneous emission present in previously demonstrated schemes in similar systems. We m

Francesca Cioffi, Margherita Guida, Luciana Ramella

Over an infinite field $K$, we investigate the minimal free resolution of some configurations of lines. We explicitly describe the minimal free resolution of "complete grids of lines" and obtain an analogous result about the so-called "complete pseudo-grids". Moreover, we characterize the total Betti numbers of configurations that are obtained posing a multi

Ron Berman, Elea McDonnell Feit

Incrementality experiments compare customers exposed to a marketing action designed to increase sales to those randomly assigned to a control group. These experiments suffer from noisy responses which make precise estimation of the average treatment effect (ATE) and marketing ROI difficult. We develop a model that improves the precision by estimating separat

Constantia Alexandrou, Joshua Berlin, Jacob Finkenrath, Theodoros Leontiou

We investigate the $D_{s0}^\ast(2317)$ meson using lattice QCD and considering correlation functions of several $\bar{c} s$ two-quark and $\bar{c} s (\bar{u} u + \bar{d} d)$ four-quark interpolating fields. These interpolating fields generate different structures in color, spin and position space including quark-antiquark pairs, tetraquarks and two-meson sca

João Pedrosa, Guilherme Aresta, Carlos Ferreira, Márcio Rodrigues

Lung cancer is the deadliest type of cancer worldwide and late detection is the major factor for the low survival rate of patients. Low dose computed tomography has been suggested as a potential screening tool but manual screening is costly, time-consuming and prone to variability. This has fueled the development of automatic methods for the detection, segme

Nicolas Kovensky, Andreas Schmitt

We study the phase structure of the Witten-Sakai-Sugimoto model in the plane of temperature and baryon chemical potential, including the effect of a nonzero current quark mass. Our study is performed in the decompactified limit of the model, which, at least regarding the chiral phase transition, appears to be closer to real-world QCD than the original versio

Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen

Robustness of convolutional neural networks (CNNs) has gained in importance on account of adversarial examples, i.e., inputs added as well-designed perturbations that are imperceptible to humans but can cause the model to predict incorrectly. Recent research suggests that the noises in adversarial examples break the textural structure, which eventually leads

Billy Quarles, Gongjie Li, Jack J. Lissauer

Changes in planetary obliquity, or axial tilt, influence the climates on Earth-like planets. In the solar system, the Earth's obliquity is stabilized due to interactions with our moon and the resulting {small amplitude variations ($\sim$2.4\degree)} are beneficial for advanced life. Most Sun-like stars have at least one stellar companion and the habitability

Sara Hamis, Stanislav Stratiev, Gibin G Powathil

Multiscale, agent-based mathematical models of biological systems are often associated with model uncertainty and sensitivity to parameter perturbations. Here, three uncertainty and sensitivity analyses methods, that are suitable to use when working with agent-based models, are discussed. These methods are namely Consistency Analysis, Robustness Analysis and

Christian Schäfer, Michael Ruggenthaler, Vasil Rokaj, Angel Rubio

Experiments at the interface of quantum-optics and chemistry have revealed that strong coupling between light and matter can substantially modify chemical and physical properties of molecules and solids. While the theoretical description of such situations is usually based on non-relativistic quantum electrodynamics, which contains quadratic light-matter cou

Fedor Stonyakin

We propose several adaptive algorithmic methods for problems of non-smooth convex optimization. The first of them is based on a special artificial inexactness. Namely, the concept of inexact ($ \delta, \Delta, L$)-model of objective functional in optimization is introduced and some gradient-type methods with adaptation of inexactness parameters are proposed.

Osman Asif Malik, Stephen Becker

In the recent paper [Jin, Kolda & Ward, arXiv:1909.04801], it is proved that the Kronecker fast Johnson-Lindenstrauss transform (KFJLT) is, in fact, a Johnson-Lindenstrauss transform, which had previously only been conjectured. In this paper, we provide an alternative proof of this, for when the KFJLT is applied to Kronecker vectors, using a coherence and sa

Alberto Escalante, Aldair-Pantoja

By using the Hamilton-Jacobi [HJ] framework the topological theories associated with Euler and Pontryagin classes are analyzed. We report the construction of a fundamental $HJ$ differential where the characteristic equations and the symmetries of the theory are identified. Moreover, we work in both theories with the same phase space variables and we show tha

Jung-Ho Kim, Soo-Jeong Kim, K. -I. Goh

How the giant component of a network disappears under attacking nodes or links addresses a key aspect of network robustness, which can be framed into percolation problems. Various strategies to select the node to be deactivated have been studied in the literature; for instance, a simple random failure or high-degree adaptive (HDA) percolation. Recently a new

Jacob Abernethy, Kevin A. Lai, Andre Wibisono

Fictitious Play (FP) is a simple and natural dynamic for repeated play in zero-sum games. Proposed by Brown in 1949, FP was shown to converge to a Nash Equilibrium by Robinson in 1951, albeit at a slow rate that may depend on the dimension of the problem. In 1959, Karlin conjectured that FP converges at the more natural rate of $O(1/\sqrt{t})$. However, Dask

Juan Carlos Garcia-Escartin

Boson sampling is a problem for which quantum devices could prove to go beyond classical computing using only linear optics and photon preparation and counting. While theoretically important, there is a lack of practical applications for this task. This paper presents a way to turn any boson sampling device for which there are certain fabrication limits into

Ondrej Skopek, Octavian-Eugen Ganea, Gary Bécigneul

Euclidean geometry has historically been the typical "workhorse" for machine learning applications due to its power and simplicity. However, it has recently been shown that geometric spaces with constant non-zero curvature improve representations and performance on a variety of data types and downstream tasks. Consequently, generative models like Var

Weihua Xu, Feifei Gao, Shi Jin, Ahmed Alkhateeb

In this paper, we present a novel framework of 3D scene based beam selection for mmWave communications that relies only on the environmental data and deep learning techniques. Different from other out-of-band side-information aided communication strategies, the proposed one fully utilizes the environmental information, e.g., the shape, the position, and even

Zhiguo Wang, Zhongliang Yang, Yu-Jin Zhang

Surveillance video anomaly detection is to detect events that rarely or never happened in a certain scene. The generation error (GE)-based methods exhibit excellent performance on this task. They firstly train a generative neural network (GNN) to generate normal samples, then judge the samples with large GEs as anomalies. Almost all the GE-based methods util

Ashwin K. Boddeti, Abubakr Alabassi, Vaneet Aggarwal, Zubin Jacob

Inverse design techniques in the context of nanophotonics have helped in discovery of compact and counter-intuitive structures/shapes. We introduce the concept of spectral domain inverse design to search through the optical trade-space (dispersive permittivity) of nanocomposite metamaterials. We develop a hybrid optimization technique that combines genetic a

Maxime Bassenne, Lin Fu, Ali Mani

Unconditionally stable implicit time-marching methods are powerful in solving stiff differential equations efficiently. In this work, a novel framework to handle stiff physical terms implicitly is proposed. Both physical and numerical stiffness originating from convection, diffusion and source terms (typically related to reaction) can be handled by a set of

E. Javier Elizondo, Eladio Escobar

We prove that the Euler-Chow series for ruled surfaces and scrolls is rational by means of an explicit computation.

Alexandru Hening

We analyze the long term behavior of interacting populations which can be controlled through harvesting. The dynamics is assumed to be discrete in time and stochastic due to the effect of environmental fluctuations. We present extinction and coexistence criteria when there are one or two interacting species. We then use these tools in order to see when harve

Thilo Egenolf, Uwe Niedermayer

Dielectric laser acceleration (DLA) is one of the advanced concepts for more compact accelerators. DLA gratings have apertures and period lengths within the range of optical wavelengths. Phase stability and wakefield effects are thus crucial for upcoming experiments with relativistic electrons. For this, we present a method to analytically calculate energy s

Ashwin Geet D'Sa, Irina Illina, Dominique Fohr

The spectacular expansion of the Internet has led to the development of a new research problem in the field of natural language processing: automatic toxic comment detection, since many countries prohibit hate speech in public media. There is no clear and formal definition of hate, offensive, toxic and abusive speeches. In this article, we put all these term

A. A. Lima, U. Camara da Silva, G. M. Sotkov

We describe a correspondence between domain wall solutions of Einstein gravity with a single scalar field and self-interaction potential. The correspondence we call 'conformal scale factor inversion (CSFI)' is a map comprising the inversion of the scale factor in conformal coordinates, and a transformation of the field and its potential which preserves the f

R. Bufalo, T. Cardoso e Bufalo

In this paper we discuss the Bhabha and Compton scattering for the quantum electrodynamics defined in the framework of very special relativity (VSR). The main aspect of the VSR setting is that it admits different types of interactions appearing in a nonlocal form due to the modified gauge invariance. We explore the richness of these new couplings in the eval

Sam Ainsworth, Timothy M. Jones

The disclosure of the Spectre speculative-execution attacks in January 2018 has left a severe vulnerability that systems are still struggling with how to patch. The solutions that currently exist tend to have incomplete coverage, perform badly, or have highly undesirable edge cases that cause application domains to break. MuonTrap allows processors to contin

Vladimir Vargas-Calderón, Jorge E. Camargo

This paper presents a model that uses the information that sellers publish in real estate market websites to predict whether a property has higher or lower price than the average price of its similar properties. The model learns the correlation between price and information (text descriptions and features) of real estate properties through automatic identifi

Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy

Three important issues are often encountered in Supervised and Semi-Supervised Classification: class-memberships are unreliable for some training units (label noise), a proportion of observations might depart from the main structure of the data (outliers) and new groups in the test set may have not been encountered earlier in the learning phase (unobserved c

Darina Dvinskikh, Aleksandr Ogaltsov, Alexander Gasnikov, Pavel Dvurechensky

In this paper we propose several adaptive gradient methods for stochastic optimization. Unlike AdaGrad-type of methods, our algorithms are based on Armijo-type line search and they simultaneously adapt to the unknown Lipschitz constant of the gradient and variance of the stochastic approximation for the gradient. We consider an accelerated and non-accelerate

Azin Ghazimatin, Oana Balalau, Rishiraj Saha Roy, Gerhard Weikum

Interpretable explanations for recommender systems and other machine learning models are crucial to gain user trust. Prior works that have focused on paths connecting users and items in a heterogeneous network have several limitations, such as discovering relationships rather than true explanations, or disregarding other users' privacy. In this work, we

Benjamin Seeger

We study the homogenization of a Hamilton-Jacobi equation forced by rapidly oscillating noise that is colored in space and white in time. It is shown that the homogenized equation is deterministic, and, in general, the noise has an enhancement effect, for which we provide a quantitative estimate. As an application, we perform a noise sensitivity analysis for

Guillermo P. Curbera, Susumu Okada, Werner J. Ricker

It is proved that the finite Hilbert transform $T\colon X\to X$, which acts continuously on every rearrangement invariant space $X$ on $(-1,1)$ having non-trivial Boyd indices, is already optimally defined. That is, $T\colon X\to X$ cannot be further extended, still taking its values in $X$, to any larger domain space.

A. B. Smolders, H. J. Visser, U. Johannsen

Modern antenna systems include passive antenna structures, passive microwave circuits and interconnections to electronics. Therefore, the antenna engineer should have a deep understanding of antenna theory and should be able to apply microwave engineering concepts. This textbook provides all relevant material for Master-level courses in the domain of antenna

Vladimir Vargas-Calderón, Nicolás Parra-A., Jorge E. Camargo, Herbert Vinck-Posada

Cultural and social dynamics are important concepts that must be understood in order to grasp what a community cares about. To that end, an excellent source of information on what occurs in a community is the news, especially in recent years, when mass media giants use social networks to communicate and interact with their audience. In this work, we use a me

Jennifer Gosner, Björn Kubala, Joachim Ankerhold

Period tripling in driven quantum oscillators reveals unique features absent for linear and parametric drive, but generic for all higher-order resonances. Here, we focus at zero temperature on the relaxation dynamics towards a stationary state starting initially from a domain around a classical fixed point in phase space. Beyond a certain threshold for the d

Markus Brill, Paul Gölz, Dominik Peters, Ulrike Schmidt-Kraepelin

In the apportionment problem, a fixed number of seats must be distributed among parties in proportion to the number of voters supporting each party. We study a generalization of this setting, in which voters can support multiple parties by casting approval ballots. This approval-based apportionment setting generalizes traditional apportionment and is a natur

Hang Yang, Zi-Feng Xu, Jian Tang, Yi Zhang

Scintillation light from liquid noble gas in a neutrino or dark matter experiment lies typically within the vacuum ultraviolet (VUV) region and might be strongly absorbed by surrounding materials such as light guides or photomultiplier. Tetraphenyl butadiene (TPB) is a fluorescent material and acts as a wavelength shifter (WLS) which can turn the UV light to

Sasha Salter, Dushyant Rao, Markus Wulfmeier, Raia Hadsell

Image-based Reinforcement Learning is known to suffer from poor sample efficiency and generalisation to unseen visuals such as distractors (task-independent aspects of the observation space). Visual domain randomisation encourages transfer by training over visual factors of variation that may be encountered in the target domain. This increases learning compl

Kenny Young

Hindsight Credit Assignment (HCA) refers to a recently proposed family of methods for producing more efficient credit assignment in reinforcement learning. These methods work by explicitly estimating the probability that certain actions were taken in the past given present information. Prior work has studied the properties of such methods and demonstrated th