February 2019 arXiv papers — page 111

Stefan Steinerberger

Let $X = \left\{x_1, \dots, x_N\right\} \subset \mathbb{T}^d \cong [0,1]^d$ be a set of $N$ points in the $d-$dimensional torus that we want to arrange as regularly possible. The purpose of this paper is to introduce a curious energy functional $$ E(X) = \sum_{1 \leq m,n \leq N \atop m \neq n} \prod_{k=1}^{d}{ (1 - \log{\left(2 \sin{ \left( π|x_{m,k} - y_{m,

Shixiang Zhu, Yao Xie

Crimes emerge out of complex interactions of human behaviors and situations. Linkages between crime incidents are highly complex. Detecting crime linkage given a set of incidents is a highly challenging task since we only have limited information, including text descriptions, incident times, and locations. In practice, there are very few labels. We propose a

David Hartich, Aljaz Godec

Extreme value functionals of stochastic processes are inverse functionals of the first passage time -- a connection that renders their probability distribution functions equivalent. Here, we deepen this link and establish a framework for analyzing extreme value statistics of ergodic reversible Markov processes in confining potentials on the hand of the under

Blaž Škrlj, Matej Martinc, Jan Kralj, Nada Lavrač

The use of background knowledge is largely unexploited in text classification tasks. This paper explores word taxonomies as means for constructing new semantic features, which may improve the performance and robustness of the learned classifiers. We propose tax2vec, a parallel algorithm for constructing taxonomy-based features, and demonstrate its use on six

Mats Vermeeren, Alessandro Bravetti, Marcello Seri

We present geometric numerical integrators for contact flows that stem from a discretization of Herglotz' variational principle. First we show that the resulting discrete map is a contact transformation and that any contact map can be derived from a variational principle. Then we discuss the backward error analysis of our variational integrators, includi

Majid Noroozi, Ramchandra Rimal, Marianna Pensky

The paper considers the Popularity Adjusted Block model (PABM) introduced by Sengupta and Chen (2018). We argue that the main appeal of the PABM is the flexibility of the spectral properties of the graph which makes the PABM an attractive choice for modeling networks that appear in biological sciences. We expand the theory of PABM to the case of an arbitrary

Jialun Li, Tuomas Sahlsten

Let $F$ be a self-similar set on $\mathbb{R}$ associated to contractions $f_j(x) = r_j x + b_j$, $j \in \mathcal{A}$, for some finite $\mathcal{A}$, such that $F$ is not a singleton. We prove that if $\log r_i / \log r_j$ is irrational for some $i \neq j$, then $F$ is a set of multiplicity, that is, trigonometric series are not in general unique in the compl

Lukas Einkemmer, Alexander Ostermann, Chiara Piazzola

The Vlasov--Maxwell equations are used for the kinetic description of magnetized plasmas. As they are posed in an up to 3+3 dimensional phase space, solving this problem is extremely expensive from a computational point of view. In this paper, we exploit the low-rank structure in the solution of the Vlasov equation. More specifically, we consider the Vlasov-

Björn Barz, Joachim Denzler

The CIFAR-10 and CIFAR-100 datasets are two of the most heavily benchmarked datasets in computer vision and are often used to evaluate novel methods and model architectures in the field of deep learning. However, we find that 3.3% and 10% of the images from the test sets of these datasets have duplicates in the training set. These duplicates are easily recog

E. Kirkman, J. J. Zhang

We study finite dimensional semisimple Hopf algebra actions on noetherian connected graded Artin-Schelter regular algebras, and introduce definitions of the Jacobian, the reflection arrangement and the discriminant in a noncommutative setting.

Nakwoo Kim

We study supergravity BPS equations which correspond to mass-deformation of some representative AdS/CFT examples. The field theory of interest are N=4, D=4 super Yang-Mills, the ABJM model in D=3, and the Brandhuber-Oz fixed point in D=5. For these gauge theories the free energy with mass terms for matter multiplets is calculable in large-N limit using super

S. N. Paneru, C. R. Brune, R. Giri, R. J. Livesay

The astrophysical $S$-factor for the radiative proton capture reaction on $^7$Be ($S_{17}$) at low energies is affected by the $s$-wave scattering lengths. We report the measurement of elastic and inelastic scattering cross sections for the $^7$Be+p system in the center-of-mass energy range 0.474 - 2.740 MeV and center-of-mass angular range of 70$^\circ$- 15

M Van de Sande, T J Millar

Recent high spatial resolution observations of gas and dust in the circumstellar envelopes (CSEs) of AGB stars indicate morphologies much more complex than the smooth density distributions generated by spherically symmetric, constant mass loss rates. In particular, the observation of spiral arcs and disks indicate the likely presence of a binary companion wh

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Understanding proper distance measures between distributions is at the core of several learning tasks such as generative models, domain adaptation, clustering, etc. In this work, we focus on mixture distributions that arise naturally in several application domains where the data contains different sub-populations. For mixture distributions, established dista

Giovanni Panti

It has long been known that the set of primitive pythagorean triples can be enumerated by descending certain ternary trees. We unify these treatments by considering hyperbolic billiard tables in the Poincare disk model. Our tables have m>=3 ideal vertices, and are subject to the restriction that reflections in the table walls are induced by matrices in the t

Song-Bo Zhang, Björn Trauzettel

Perfect crossed Andreev reflection (CAR) is striking for high-efficiency Cooper pair splitting which bears promising applications in quantum communication. Recent experimental advances have disclosed the way to explore CAR in Dirac fermion systems under ultra-strong magnetic fields. We develop a scattering approach to study quantum Hall-superconductor-quantu

Matti Vihola, Jordan Franks

Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider a

Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi

Current methods to interpret deep learning models by generating saliency maps generally rely on two key assumptions. First, they use first-order approximations of the loss function neglecting higher-order terms such as the loss curvatures. Second, they evaluate each feature's importance in isolation, ignoring their inter-dependencies. In this work, we st

Sahil Singla, Soheil Feizi

While neural networks have achieved high performance in different learning tasks, their accuracy drops significantly in the presence of small adversarial perturbations to inputs. Defenses based on regularization and adversarial training are often followed by new attacks to defeat them. In this paper, we propose attack-agnostic robustness certificates for a m

Stefan Ruschel, Serhiy Yanchuk

We prove that the spectrum of the linear delay differential equation $x'(t)=A_{0}x(t)+A_{1}x(t-τ_{1})+\ldots+A_{n}x(t-τ_{n})$ with multiple hierarchical large delays $1\llτ_{1}\llτ_{2}\ll\ldots\llτ_{n}$ splits into two distinct parts: the strong spectrum and the pseudo-continuous spectrum. As the delays tend to infinity, the strong spectrum converges to

Paolo Antonelli, Lars Eric Hientzsch, Pierangelo Marcati

We investigate the low Mach number limit for the 3-D quantum Navier-Stokes system. For general ill-prepared initial data, we prove strong convergence of finite energy weak solutions to weak solutions of the incompressible Navier-Stokes equations. Our approach relies on a quite accurate dispersive analysis for the acoustic part, governed by the well-known Bog

Marc Calvo-Schwarzwälder

We model the growth of a one-dimensional solid by considering a modified Fourier law with a size-dependent effective thermal conductivity and a Newton cooling condition at the interface between the solid and the cold environment. In the limit of a large Biot number, this condition becomes the commonly used fixed-temperature condition. It is shown that in pra

Brent Everitt, Paul Turner

We give a long exact sequence for the homology of a graded atomic lattice equipped with a sheaf of modules, in terms of the deleted and restricted lattices. This is then used to compute the homology of the arrangement lattice of a hyperplane arrangement equipped with the natural sheaf. This generalises an old result of Lusztig.

François Orain, M. Hoelzl, F. Mink, M. Willensdorfer

The interaction between Edge Localized Modes (ELMs) and Resonant Magnetic Perturbations (RMPs) is modeled with the magnetohydrodynamic code JOREK using experimental parameters from ASDEX Upgrade discharges. The ELM mitigation or suppression is optimal when the amplification of both tearing and peeling-kink responses result in a better RMP penetration. The EL

Ghanem Soltana, Mehrdad Sabetzadeh, Lionel C. Briand

The ability to generate test data is often a necessary prerequisite for automated software testing. For the generated data to be fit for its intended purpose, the data usually has to satisfy various logical constraints. When testing is performed at a system level, these constraints tend to be complex and are typically captured in expressive formalisms based

Tobias Breiten, Karl Kunisch, Laurent Pfeiffer

The value function associated with an optimal control problem subject to the Navier-Stokes equations in dimension two is analyzed. Its smoothness is established around a steady state, moreover, its derivatives are shown to satisfy a Riccati equation at the order two and generalized Lyapunov equations at the higher orders. An approximation of the optimal feed

Daniel Obmann, Johannes Schwab, Markus Haltmeier

We propose a sparse reconstruction framework for solving inverse problems. Opposed to existing sparse regularization techniques that are based on frame representations, we train an encoder-decoder network by including an $\ell^1$-penalty. We demonstrate that the trained decoder network allows sparse signal reconstruction using thresholded encoded coefficient

Thomas Sanchez, Baran Gözcü, Ruud B. van Heeswijk, Armin Eftekhari

Compressed sensing applied to magnetic resonance imaging (MRI) allows to reduce the scanning time by enabling images to be reconstructed from highly undersampled data. In this paper, we tackle the problem of designing a sampling mask for an arbitrary reconstruction method and a limited acquisition budget. Namely, we look for an optimal probability distributi

Shengcao Cao, Xiaofang Wang, Kris M. Kitani

We propose a method to incrementally learn an embedding space over the domain of network architectures, to enable the careful selection of architectures for evaluation during compressed architecture search. Given a teacher network, we search for a compressed network architecture by using Bayesian Optimization (BO) with a kernel function defined over our prop

ATLAS Collaboration

Searches for scalar leptoquarks pair-produced in proton-proton collisions at $\sqrt{s}=13$ TeV at the Large Hadron Collider are performed by the ATLAS experiment. A data set corresponding to an integrated luminosity of 36.1 fb$^{-1}$ is used. Final states containing two electrons or two muons and two or more jets are studied, as are states with one electron

Benjamin Paaßen, Astrid Bunge, Carolin Hainke, Leon Sindelar

In recent years, machine learning techniques have been increasingly applied in sensitive decision making processes, raising fairness concerns. Past research has shown that machine learning may reproduce and even exacerbate human bias due to biased training data or flawed model assumptions, and thus may lead to discriminatory actions. To counteract such biase

Malte Schlosser, Jens Kruse, Gerhard Birkl

Advanced quantum technologies, such as quantum simulation, computation, and metrology are thriving for the implementation of large-scale configurations of identical quantum systems. Sets of atoms and molecules have the advantage of having identical intrinsic properties but need to be placed in identical environments as well. In this work, we present a strong

Liuquan Wang, Yifan Yang

Atkin and Garvan introduced the functions $N_k(n)$ and $M_k(n)$, which denote the $k$-th moments of ranks and cranks in the theory of partitions. Let $e_{2r}(n)$ be the $n$-th Fourier coefficient of $E_{2r}(τ)/η(τ)$, where $E_{2r}(τ)$ is the classical Eisenstein series of weight $2r$ and $η(τ)$ is the Dedekind eta function. Via the theory of quasi-modular fo

Piotr Sierant, Krzysztof Biedroń, Giovanna Morigi, Jakub Zakrzewski

We show that a one-dimensional Hubbard model with all-to-all coupling may exhibit many-body localization in the presence of local disorder. We numerically identify the parameter space where many-body localization occurs using exact diagonalization and finite-size scaling. The time evolution from a random initial state exhibits features consistent with the lo

Friedrich Wehrung

Anti-elementarity is a strong way of ensuring that a class of structures , in a given first-order language, is not closed under elementary equivalence with respect to any infinitary language of the form L $\infty$$λ$. We prove that many naturally defined classes are anti-elementary, including the following: $\bullet$ the class of all lattices of finitely gen

S. Liu, D. Liu

Light bridge (LB) is bright structure crossing the umbra of sunspots and associated to the breakup or assembly of sunspots. In this paper, a LB is presented and studied using the observatory data obtained by {\it Hinode} satellites. Force-free factor ($α$) and the z-component of current ($J_{z}$) and tension force ($T_{z}$) are calculated basing on the vecto

Christoph Angermann, Markus Haltmeier, Ruth Steiger, Sergiy Pereverzyev

Convolutional neural networks are state-of-the-art for various segmentation tasks. While for 2D images these networks are also computationally efficient, 3D convolutions have huge storage requirements and require long training time. To overcome this issue, we introduce a network structure for volumetric data without 3D convolutional layers. The main idea is

Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi

Optimal transport (\OT) theory defines a powerful set of tools to compare probability distributions. \OT~suffers however from a few drawbacks, computational and statistical, which have encouraged the proposal of several regularized variants of OT in the recent literature, one of the most notable being the \textit{sliced} formulation, which exploits the close

Gayatri Parthasarathy, G. Abhilash

This paper proposes a learning method to construct an efficient sensing (measurement) matrix, having orthogonal rows, for compressed sensing of a class of signals. The learning scheme identifies the sensing matrix by maximizing the entropy of measurement vectors. The bounds on the entropy of the measurement vector necessary for the unique recovery of a signa

Keith M. Smith

Networks of disparate phenomena-- be it the global ecology, human social institutions, within the human brain, or in micro-scale protein interactions-- exhibit broadly consistent architectural features. To explain this, we propose a new theory where link probability is modelled by a log-normal node fitness (surface) factor and a latent Euclidean space-embedd

Aythami Morales, Julian Fierrez, Ruben Vera-Rodriguez, Ruben Tolosana

This work proposes a novel privacy-preserving neural network feature representation to suppress the sensitive information of a learned space while maintaining the utility of the data. The new international regulation for personal data protection forces data controllers to guarantee privacy and avoid discriminative hazards while managing sensitive data of use

Pedro Monroy, Gabor Drotos, Emilio Hernandez-Garcia, Cristobal Lopez

Sedimentation of particles in the ocean leads to inhomogeneous horizontal distributions at depth, even if the release process is homogeneous. We study this phenomenon considering a horizontal sheet of sinking particles immersed in an oceanic flow, and determine how the particles are distributed when they sediment on the seabed (or are collected at a given de

S. Liu, D. Liu

The magnetic field plays a key role in producing solar flares, so that the investigation on the relationship between the magnetic field properties and flares is significant. In this paper, based on the magnetic field extrapolated from the photospheric vector magnetograms of the active region NOAA 9077 obtained at Huairou Solar Observing Station, the magnetic

Gregor Ulm, Simon Smith, Adrian Nilsson, Emil Gustavsson

A fleet of connected vehicles easily produces many gigabytes of data per hour, making centralized (off-board) data processing impractical. In addition, there is the issue of distributing tasks to on-board units in vehicles and processing them efficiently. Our solution to this problem is OODIDA (On-board/Off-board Distributed Data Analytics), which is a platf

Pouya Badri, Mahdi Sojoodi, Elyar Zavvari

This paper considers the problem of robust stability and stabilization for linear fractional-order system with nonlinear uncertain parameters, with fractional order 0<a<2. A dynamic output feedback controller, with predetermined order, for asymptotically stabilizing such uncertain fractional-order systems is designed. The derived stabilization conditions are

Diego Bravo, Charles Paquette

In this note, we prove that if $Λ$ is an Artin algebra with a simple module $S$ of finite projective dimension, then the finiteness of the finitistic dimension of $Λ$ implies that of $(1-e)Λ(1-e)$ where $e$ is the primitive idempotent supporting $S$. We derive some consequences of this. In particular, we recover a result of Green-Solberg-Psaroudakis: if $Λ$

Mathias R. Jørgensen, Felix A. Pollock

In the path integral formulation of the evolution of an open quantum system coupled to a Gaussian, non-interacting environment, the dynamical contribution of the latter is encoded in an object called the influence functional. Here, we relate the influence functional to the process tensor -- a more general representation of a quantum stochastic process -- des

Yuanzhi Liang, Yalong Bai, Wei Zhang, Xueming Qian

Relationships encode the interactions among individual instances, and play a critical role in deep visual scene understanding. Suffering from the high predictability with non-visual information, existing methods tend to fit the statistical bias rather than ``learning&#39;&#39; to ``infer&#39;&#39; the relationships from images. To encourage further developme

Igor Proudnikov

The purpose of this paper is to develop a numerical method for finding an equilibrium point in a model, in which the loss function of each object (subject) is described by a convex function with respect to one of its variables. Such models are found in medicine, economics, game theory, and biology. For the more complex case, with nonsmooth functions describi

Oleksii Sidorov, Congcong Wang, Faouzi Alaya Cheikh

In minimally invasive surgery, the use of tissue dissection tools causes smoke, which inevitably degrades the image quality. This could reduce the visibility of the operation field for surgeons and introduces errors for the computer vision algorithms used in surgical navigation systems. In this paper, we propose a novel approach for computational smoke remov

Ilmari Kangasniemi

Suppose that $M$ is a closed, connected, and oriented Riemannian $n$-manifold, $f \colon \mathbb{R}^n \to M$ is a quasiregular map automorphic under a discrete group $\Gamma$ of Euclidean isometries, and $f$ has finite multiplicity in a fundamental cell of $\Gamma$. We show that if $\Gamma$ has a sufficiently large translation subgroup $\Gamma_T$, then $\dim

Mathieu Lewin, Peter S. Madsen, Arnaud Triay

We study a system of $N$ interacting fermions at positive temperature in a confining potential. In the regime where the intensity of the interaction scales as $1/N$ and with an effective semi-classical parameter $\hbar=N^{-1/d}$ where $d$ is the space dimension, we prove the convergence to the corresponding Thomas-Fermi model at positive temperature.

Björn Eichmann

The extended jet structures of radio galaxies (RGs) represent an ideal acceleration site for High Energy Cosmic Rays (HECRs) and a recent model showed that the HECR data can be explained by these sources, if the arrival directions of HECRs at energies $\lesssim 8\,\text{EeV}$ from a certain RG, Cygnus A, are isotropized. First, this work introduces the inver

Yu-Sheng Liu, Wei Wang, Ji Xu, Qi-An Zhang

Within the framework of large momentum effective theory (LaMET), genenaralized parton distributions (GPDs) can be extracted from lattice calculations of quasi-GPDs through a perturbative matching relation, up to power corrections that are suppressed by the hadron momentum. In this paper, we focus on isovector quark GPDs, including the unpolarized, longitudin

Joseph Lam-Weil, Alexandra Carpentier, Bharath K. Sriperumbudur

We consider the closeness testing problem for discrete distributions. The goal is to distinguish whether two samples are drawn from the same unspecified distribution, or whether their respective distributions are separated in $L_1$-norm. In this paper, we focus on adapting the rate to the shape of the underlying distributions, i.e. we consider \textit{a loca

Yoshiharu Kohayakawa, Guilherme Oliveira Mota, Olaf Parczyk, Jakob Schnitzer

For graphs $G$ and $H$, let $G {\displaystyle\smash{\begin{subarray}{c} \hbox{$\tiny\rm rb$} \\ \longrightarrow \\ \hbox{$\tiny\rm p$} \end{subarray}}}H$ denote the property that for every proper edge-colouring of $G$ there is a rainbow $H$ in $G$. It is known that, for every graph $H$, an asymptotic upper bound for the threshold function $p^{\rm rb}_H=p^{\r

Gaston Burrull, Nicolas Libedinsky, Paolo Sentinelli

For a prime number $p$ and any natural number $n$ we introduce, by giving an explicit recursive formula, the $p$-Jones-Wenzl projector ${}^p\operatorname{JW}_n$, an element of the Temperley-Lieb algebra $TL_n(2)$ with coefficients in ${\mathbb F}_p$. We prove that these projectors give the indecomposable objects in the $\tilde{A}_1$-Hecke category over ${\ma

Benjamin Doerr, Carola Doerr, Frank Neumann

When a problem instance is perturbed by a small modification, one would hope to find a good solution for the new instance by building on a known good solution for the previous one. Via a rigorous mathematical analysis, we show that evolutionary algorithms, despite usually being robust problem solvers, can have unexpected difficulties to solve such re-optimiz

Oleksii Sidorov, Jon Yngve Hardeberg

Deep learning algorithms have demonstrated state-of-the-art performance in various tasks of image restoration. This was made possible through the ability of CNNs to learn from large exemplar sets. However, the latter becomes an issue for hyperspectral image processing where datasets commonly consist of just a few images. In this work, we propose a new approa

Baptiste Cecconi, Alan Loh, Pierre Le Sidaner, Renaud Savalle

MASER (Measurements, Analysis, and Simulation of Emission in the Radio range) is a comprehensive infrastructure dedicated to time-dependent low frequency radio astronomy (up to about 50 MHz). The main radio sources observed in this spectral range are the Sun, the magnetized planets (Earth, Jupiter, Saturn), and our Galaxy, which are observed either from grou

Florian Schneider, Tobias Leibner

We provide two new classes of moment models for linear kinetic equations in slab and three-dimensional geometry. They are based on classical finite elements and low-order discontinuous-Galerkin approximations on the unit sphere. We investigate their realizability conditions and other basic properties. Numerical tests show that these models are more efficient

Xiaoxue Ran, Nvsen Ma, Dao-Xin Yao

We use the stochastic series expansion quantum Monte Carlo method to study the Heisenberg models on the square lattice with strong and weak couplings in the form of three different plaquette arrangements known as checkerboard models C$2\times2$, C$2\times4$ and C$4\times4$. The $a\times b$ here stands for the shape of plaquette consisting with spins connecte

Emanuel Gouveia, Ricardo Gonçalo, António Onofre, Duarte Azevedo

The ATLAS and CMS collaborations recently announced the observation of the associated production of the Higgs boson with a top quark pair ($t\bar tH$) at the LHC. This process depends directly on the the top quark Yukawa coupling and provides access to its properties. In particular, a CP-odd component is allowed in models beyond the Standard Model with exten

Ambrus Kaposi, András Kovács

Higher inductive-inductive types (HIITs) generalize inductive types of dependent type theories in two ways. On the one hand they allow the simultaneous definition of multiple sorts that can be indexed over each other. On the other hand they support equality constructors, thus generalizing higher inductive types of homotopy type theory. Examples that make use

P. A. Boyle, V. Guelpers, A. Juettner, C. Lehner

RBC/UKQCD is preparing a calculation of leptonic decay rates including isospin breaking corrections using a perturbative approach to include NLO contributions from QED effects. We present preliminary numerical results for a contribution to the leptonic pion decay rate and report on exploratory studies of computational techniques based on all-to-all propagato

Ariel Barel, Thomas Dagès, Rotem Manor, Alfred M. Bruckstein

Gathering is a fundamental task for multi-agent systems and the problem has been studied under various assumptions on the sensing capabilities of mobile agents. This paper addresses the problem for a group of agents that are identical and indistinguishable, oblivious, and lack the capacity of direct communication. At the beginning of unit-time intervals, the

Wouter Van Gansbeke, Bert De Brabandere, Davy Neven, Marc Proesmans

Lane detection is typically tackled with a two-step pipeline in which a segmentation mask of the lane markings is predicted first, and a lane line model (like a parabola or spline) is fitted to the post-processed mask next. The problem with such a two-step approach is that the parameters of the network are not optimized for the true task of interest (estimat

A. Ya. Maltsev

We consider angular diagrams describing the dependence of the magnetic conductivity of metals on the direction of the magnetic field in rather strong fields. As it can be shown, all angular conductivity diagrams can be divided into a finite number of classes with different complexity. The greatest interest among such diagrams is represented by diagrams with

Zhao-Yu Yin, Hao Wei

In the literature, it was proposed that the growth index $γ$ is useful to distinguish the scenarios of dark energy and modified gravity. In the present work, we consider the constraints on the growth index $γ$ by using the latest observational data. To be model-independent, we use cosmography to describe the cosmic expansion history, and also expand the gene

Suying Liu, Chao Zhang

In this paper, we derive the $L^p$-boundedness of the variation operators associated with the heat semigroup which is generated by the high order Schrödinger type operator $(-Δ)^2+V^2$. Further more, we prove the boundedness of the variation operators on Morrey spaces. In the proof of the main results, we always make use of the variation inequalities associa

Daniel Ohl de Mello, Dominik Schäffner, Jan Werkmann, Tilman Preuschoff

We demonstrate the defect-free assembly of versatile target patterns of up 111 neutral atoms, building on a 361-site subset of a micro-optical architecture that readily provides thousands of sites for single-atom quantum systems. By performing multiple assembly cycles in rapid succession, we drastically increase achievable structure sizes and success probabi

Francisco J. Fernández, Aurea Martínez, Lino J. Alzarez-Vázquez

In this work, the artificial recirculation of water is presented and analyzed, from the perspective of the optimal control of partial differential equations, as a tool to prevent eutrophication effects in large waterbodies. A novel formulation of the environmental problem, based on the coupling of nonlinear models for hydrodynamics, water temperature and con

Chang Liu, Jingwei Zhuo, Jun Zhu

It is known that the Langevin dynamics used in MCMC is the gradient flow of the KL divergence on the Wasserstein space, which helps convergence analysis and inspires recent particle-based variational inference methods (ParVIs). But no more MCMC dynamics is understood in this way. In this work, by developing novel concepts, we propose a theoretical framework

Francisco J. Fernández, Lino J. Alvarez-Vázquez, Aurea Martínez

This work is devoted to the analysis and resolution of a well-posed mathematical model for several processes involved in the artificial circulation of water in a large waterbody. This novel formulation couples the convective heat transfer equation with the modified Navier-Stokes system following a Smagorinsky turbulence model, completed with a suitable set o

Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan

Flow-based generative models are powerful exact likelihood models with efficient sampling and inference. Despite their computational efficiency, flow-based models generally have much worse density modeling performance compared to state-of-the-art autoregressive models. In this paper, we investigate and improve upon three limiting design choices employed by f

Wenjie Liu, Yongguan Ke, Li Zhang, Chaohong Lee

The studies of multi-magnon excitations will extend our understandings of quantum magnetism and strongly correlated matters. Here, by using the time-evolving block decimation algorithm, we investigate the Bloch oscillations of two-magnon excitations under a gradient magnetic field. Through analyzing the symmetry of the Hamiltonian, we derive a rigorous and u

Luc Gossart

We consider the skew-product of an expanding map $E$ on the circle $\mathbb T$ with an almost surely $\mathcal C^k$ random perturbation $τ=τ_0+δτ$ of a deterministic function $τ_0$: \[F :\left\{\begin{array}{rcl} \mathbb T \times \mathbb R & \longrightarrow & \mathbb T \times \mathbb R\\ (x,y)& \longmapsto & (E(x), y+τ(x))\\ \end{array} \right.\] The associa

Liisa-Ida Sorsa, Mika Takala, Patrick Bambach, Jakob Deller

In this paper, we investigate full-wave computed radar tomography (CRT) using a rubble-pile asteroid model in which a realistic shape (Itokawa) is coupled with a synthetic material composition and structure model. The aim is to show that sparse bistatic radar measurements can distinguish details inside a complex-structured rubble-pile asteroid. The results o

Yatie Xiao, Chi-Man Pun

Deep Neural Networks have achieved remarkable success in computer vision, natural language processing, and audio tasks.

C. Azevedo, V. P. Goncalves, B. D. Moreira

In this paper we perform a systematic study of the exclusive dilepton production by $γγ$ interactions in $PbPb$ collisions at the LHC Run 2 energies considering different levels of precision for the treatment of the absorptive corrections and for the nuclear form factor. The rapidity and invariant mass distributions are estimated taking into account the expe

Peter Török, Matthew R. Foreman

Using Fisher information and the Cramér-Rao lower bound, we analyse fundamental precision limits in the determination of spectral parameters in inelastic optical scattering. General analytic formulae are derived which account for the instrument response functions of the dispersive element and relay optics found in practical Raman and Brillouin spectrometers.

Sirachak Panpanich, Supakchai Ponglertsakul, Kei-ichi Maeda

We investigate cosmological dynamics and screening mechanism of the Dirac-Born-Infeld (DBI) Galileon model. The model has been divided into two regimes, one has positive signs in front of scalar field kinetic terms so-called the DBI galileon, another one has negative signs and it is dubbed as the DBIonic galileon. We find de Sitter solution and evolution of

Beatriz Elizaga Navascués, Guillermo A. Mena Marugán, Santiago Prado

We use the freedom available in hybrid loop quantum cosmology to split the degrees of freedom between the geometry and the matter fields so as to build a quantum field theory for the matter content with good quantum properties. We investigate this issue in an inflationary, flat cosmology with inhomogeneous perturbations, and focus the discussion on a Dirac f

Peter Hästö, Jihoon Ok

We establish local $C^{1,α}$-regularity for some $α\in(0,1)$ and $C^α$-regularity for any $α\in(0,1)$ of local minimizers of the functional \[ v\ \mapsto\ \int_Ωϕ(x,|Dv|)\,dx, \] where $ϕ$ satisfies a $(p,q)$-growth condition. Establishing such a regularity theory with sharp, general conditions has been an open problem since the 1980s. In contrast to previou

Jesse Geneson, Amber Holmes, Xujun Liu, Dana Neidinger

An ordered graph $\mathcal{G}$ is a simple graph together with a total ordering on its vertices. The (2-color) Ramsey number of $\mathcal{G}$ is the smallest integer $N$ such that every 2-coloring of the edges of the complete ordered graph on $N$ vertices has a monochromatic copy of $\mathcal{G}$ that respects the ordering. In this paper we investigate the e

Christos Kaplanis, Murray Shanahan, Claudia Clopath

We propose a method for tackling catastrophic forgetting in deep reinforcement learning that is \textit{agnostic} to the timescale of changes in the distribution of experiences, does not require knowledge of task boundaries, and can adapt in \textit{continuously} changing environments. In our \textit{policy consolidation} model, the policy network interacts

M. Ya. Amusia, A. S. Baltenkov

We generalize here the one-level consideration in our recent paper arXiv:1901.00411 [1] to the case when an electron collides with a potential that have any number of s bound states. We investigate peculiarities in the Wigner time delay behavior for slow electron elastic s-scattering by spherically symmetric square-potential well. We have considered potentia

Alireza Shahsafi, Patrick Roney, You Zhou, Zhen Zhang

Thermal emission is the process by which all objects at non-zero temperatures emit light, and is well-described by the classic Planck, Kirchhoff, and Stefan-Boltzmann laws. For most solids, the thermally emitted power increases monotonically with temperature in a one-to-one relationship that enables applications such as infrared imaging and non-contact therm

Cong Fang, Zhouchen Lin, Tong Zhang

In this paper, we give a sharp analysis for Stochastic Gradient Descent (SGD) and prove that SGD is able to efficiently escape from saddle points and find an $(ε, O(ε^{0.5}))$-approximate second-order stationary point in $\tilde{O}(ε^{-3.5})$ stochastic gradient computations for generic nonconvex optimization problems, when the objective function satisfies g

Anselm Haak, Juha Kontinen, Fabian Müller, Heribert Vollmer

We study descriptive complexity of counting complexity classes in the range from #P to #$\cdot$NP. A corollary of Fagin&#39;s characterization of NP by existential second-order logic is that #P can be logically described as the class of functions counting satisfying assignments to free relation variables in first-order formulae. In this paper we extend this

Fan Wang, Xiaomin Fang, Lihang Liu, Yaxue Chen

In the combinatorial recommender systems, multiple items are fed to the user at one time in the result page, where the correlations among the items have impact on the user behavior. In this work, we model the combinatorial recommendation as the problem of generating a sequence(ordered list) of items from a candidate set, with the target of maximizing the exp

Jingnan Guo, Robert F. Wimmer-Schweingruber, Manuel Grande, Zoe Hannah Lee-Payne

It is extremely important to understand and model the Martian radiation environment in preparation for future human missions to Mars, especially during extreme and elevated conditions such as an intense solar energetic particle (SEP) event. Such events may enhance the radiation level drastically and should be forecasted as soon as possible to prevent severe

Geir-Arne Fuglstad, Ingeborg Gullikstad Hem, Alexander Knight, Håvard Rue

Variance parameters in additive models are typically assigned independent priors that do not account for model structure. We present a new framework for prior selection based on a hierarchical decomposition of the total variance along a tree structure to the individual model components. For each split in the tree, an analyst may be ignorant or have a sound i

N. H. Bian, A. G. Emslie, E. P. Kontar

Electromagnetic wave scattering off density inhomogeneities in the solar corona is an important process which determines both the apparent source size and the time profile of radio bursts observed at 1 AU. Here we model the scattering process using a Fokker-Planck equation and apply this formalism to several regimes of interest. In the first regime the densi

Jorge Puebla, Florent Auvray, Naoya Yamaguchi, Mingran Xu

At interfaces with inversion symmetry breaking, Rashba effect couples the motion of electrons to their spin; as a result, spin-charge interconversion mechanism can occur. These interconversion mechanisms commonly exploit Rashba spin splitting at the Fermi level by spin pumping or spin torque ferromagnetic resonance. Here, we report evidence of significant ph

Hui Li, Zili Chen

In this paper, we characterize Banach lattices on which each Dunford-Pettis operator (or weak Dunford-Pettis) is unbounded absolute weak Dunford-Pettis operator and the converse.

Mladen Kovačević, Sanja Brdar, Vladimir Crnojević

Tandem-duplication-random-loss (TDRL) is an important genome rearrangement operation studied in evolutionary biology. This paper investigates some of the formal properties of TDRL operations on the symmetric group (the space of permutations over an $ n $-set). In particular, the cardinality of `balls&#39; of radius one in the TDRL metric, as well as the card

Peng Li

We proposed a new estimation algorithm of extended Kalman filter (EKF) based on improved Thevenin model; Experiments were carried out to verify the validity with seven 4Ah lithium cobalt acid batteries in series. The experimental results showed that when using the algorithm, the estimation error of SOC is in the scope of error allowed, and the requirement of

Frederick Green

Microscopically conserving reduced models of many-body systems have a long, highly successful history. Established theories of this type are the random-phase approximation for Coulomb fluids and the particle-particle ladder model for nuclear matter. There are also more physically comprehensive approximations such as the induced-interaction and parquet theori

Jun-Jie Wei

The observation of Type Ia supernovae (SNe Ia) plays an essential role in probing the expansion history of the universe. But the possible presence of cosmic opacity can degrade the quality of SNe Ia. The gravitational-wave (GW) standard sirens, produced by the coalescence of double neutron stars and black hole--neutron star binaries, provide an independent w