May 2020 arXiv papers — page 21

Phillip W. K. Jensen, Lasse Bjørn Kristensen, Jakob S. Kottmann, Alán Aspuru-Guzik

There is widespread interest in calculating the energy spectrum of a Hamiltonian, for example to analyze optical spectra and energy deposition by ions in materials. In this study, we propose a quantum algorithm that samples the set of energies within a target energy-interval without requiring good approximations of the target energy-eigenstates. We discuss t

Elizabeth Himwich, Sruthi A. Narayanan, Monica Pate, Nisarga Paul

The gravitational $\mathcal{S}$-matrix defined with an infrared (IR) cutoff factorizes into hard and soft factors. The soft factor is universal and contains all the IR and collinear divergences. Here we show, in a momentum space basis, that the intricate expression for the soft factor is fully reproduced by two boundary currents, which live on the celestial

Akshat Mudgal

Given $d \in \mathbb{N}$, we establish sum-product estimates for finite, non-empty subsets of $\mathbb{R}^d$. This is equivalent to a sum-product result for sets of diagonal matrices. In particular, let $A$ be a finite, non-empty set of $d \times d$ diagonal matrices with real entries. Then for all $\delta_1 < 1/3 + 5/5277$, we have \[ |A+A| + |A\cdot A| \gg

A. A. Buturlakin, S. S. Presnyakov, D. O. Revin, S. A. Savin

Consider a triangle $ABC$ with given lengths $l_a,l_b,l_c$ of its internal angle bisectors. We prove that in general, it is impossible to construct a square of the same area as $ABC$ using a ruler and compass. Moreover, it is impossible to express the area of $ABC$ in radicals of $l_a,l_b,l_c$.

Pierre Pellat-Finet, Éric Fogret

The first part of the paper is devoted to diffraction phenomena that can be expressed by fractional Fourier transforms whose orders are real numbers. According to a scalar theory, diffraction acts on the amplitude of the electric field as well as on its spherical angular spectrum, and Wigner distributions can be defined on a space-frequency phase space. The

Tong Zhou

Requirements on subsystems have been made clear in this paper for a linear time invariant (LTI) networked dynamic system (NDS), under which subsystem interconnections can be estimated from external output measurements. In this NDS, subsystems may have distinctive dynamics, and subsystem interconnections are arbitrary. It is assumed that system matrices of ea

Ashley M. Hou, Line A. Roald

In this paper, we consider a chance-constrained formulation of the optimal power flow problem to handle uncertainties resulting from renewable generation and load variability. We propose a tuning method that iterates between solving an approximated reformulation of the optimization problem and using a posteriori sample-based evaluations to refine the reformu

Panayotis Smyrnelis

We construct double layered solutions to the extended Fisher-Kolmogorov P.D.E., under the assumption that the set of minimal heteroclinics of the corresponding O.D.E. satisfies a separation condition. The aim of our work is to provide for the extended Fisher-Kolmogorov equation, the first examples of two-dimensional minimal solutions, since these solutions p

Hans-Georg Raumer, Carsten Spehr, Thorsten Hohage, Daniel Ernst

This article discusses aeroacoustic imaging methods based on correlation measurements in the frequency domain. Standard methods in this field assume that the estimated correlation matrix is superimposed with additive white noise. In this paper we present a mathematical model for the measurement process covering arbitrarily correlated noise. The covariance ma

Martin Karp, Niclas Jansson, Artur Podobas, Philipp Schlatter

In the CFD solver Nek5000, the computation is dominated by the evaluation of small tensor operations. Nekbone is a proxy app for Nek5000 and has previously been ported to GPUs with a mixed OpenACC and CUDA approach. In this work, we continue this effort and optimize the main tensor-product operation in Nekbone further. Our optimization is done in CUDA and us

Lukas Gierster, Sesha Vempati, Julia Stähler

Band bending at semiconductor surfaces induced by chemical doping or electric fields can create metallic surfaces with properties not found in the bulk, such as high electron mobility, magnetism or superconductivity. Optical generation of such metallic surfaces via BB on ultrafast timescales would facilitate a drastic manipulation of the conduction, magnetic

Yunlei Tang, Sebastian Dorn, Chiragkumar Savani

Localizing objects in 3D space and understanding their associated 3D properties is challenging given only monocular RGB images. The situation is compounded by the loss of depth information during perspective projection. We present Center3D, a one-stage anchor-free approach, to efficiently estimate 3D location and depth using only monocular RGB images. By exp

LHCb collaboration, R. Aaij, C. Abellán Beteta, T. Ackernley

The decays $B^+\rightarrow J/\psi \pi^+ \pi^- K^+$ are studied using a data set corresponding to an integrated luminosity of 9fb$^{-1}$ collected with the LHCb detector in proton-proton collisions between 2011 and 2018. Precise measurements of the ratios of branching fractions with the intermediate $\psi_2(3823)$, $\chi_{c1}(3872)$ and $\psi(2S)$ states are

Johan Bos, Lasha Abzianidze

Meaning banking--creating a semantically annotated corpus for the purpose of semantic parsing or generation--is a challenging task. It is quite simple to come up with a complex meaning representation, but it is hard to design a simple meaning representation that captures many nuances of meaning. This paper lists some lessons learned in nearly ten years of me

Derek Onken, Lars Ruthotto

We compare the discretize-optimize (Disc-Opt) and optimize-discretize (Opt-Disc) approaches for time-series regression and continuous normalizing flows (CNFs) using neural ODEs. Neural ODEs are ordinary differential equations (ODEs) with neural network components. Training a neural ODE is an optimal control problem where the weights are the controls and the

Kevin P. O'Keeffe, Virgil Griffith, Yang Xu, Paolo Santi

We analyse the darkweb and find its structure is unusual. For example, $ \sim 87 \%$ of darkweb sites \emph{never} link to another site. To call the darkweb a "web" is thus a misnomer -- it's better described as a set of largely isolated dark silos. As we show through a detailed comparison to the World Wide Web (www), this siloed structure is highly dissimil

LHCb collaboration, R. Aaij, C. Abellán Beteta, T. Ackernley

A study of the lineshape of the $\chi_{c1}(3872)$ state is made using a data sample corresponding to an integrated luminosity of $3\,$fb$^{-1}$ collected in $pp$ collisions at centre-of-mass energies of 7 and 8\,TeV with the LHCb detector. Candidate $\chi_{c1}(3872)$ and $\psi(2S)$ mesons from b-hadron decays are selected in the $ J/\psi \pi^+ \pi^-$ decay m

Mateus Araújo, Flavien Hirsch, Marco Túlio Quintino

In order to reject the local hidden variables hypothesis, the usefulness of a Bell inequality can be quantified by how small a p-value it will give for a physical experiment. Here we show that to obtain a small expected p-value it is sufficient to have a large gap between the local and Tsirelson bounds of the Bell inequality, when it is formulated as a nonlo

Tim Janke, Florian Steinke

The reliable estimation of forecast uncertainties is crucial for risk-sensitive optimal decision making. In this paper, we propose implicit generative ensemble post-processing, a novel framework for multivariate probabilistic electricity price forecasting. We use a likelihood-free implicit generative model based on an ensemble of point forecasting models to

László Csató, Dóra Gréta Petróczy

We argue for the application of bibliometric indices to quantify the long-term uncertainty of outcome in sports. The Euclidean index is proposed to reward quality over quantity, while the rectangle index can be an appropriate measure of core performance. Their differences are highlighted through an axiomatic analysis and several examples. Our approach also r

Saeed Nejati, Vijay Ganesh

Over the last two decades, we have seen a dramatic improvement in the efficiency of conflict-driven clause-learning Boolean satisfiability (CDCL SAT) solvers on industrial problems from a variety of domains. The availability of such powerful general-purpose search tools as SAT solvers has led many researchers to propose SAT-based methods for cryptanalysis, i

Letizia Stella Di Mauro, Christian Mulder, Erminia Conti, Alessandro Pluchino

In this study three soil ecosystems, that differ in the type of management, have been compared in the attempt to understand if and how anthropogenic action affects them. The structure of the corresponding food webs was analyzed and their robustness was calculated through the use of a dynamic model. With regard to the topology, it has been found that the stru

Jarosław H. Bauer, Zbigniew Walczak

We perform ab initio calculations for the hydrogen atom initially in one of the six circular bound states with the principal quantum numbers n = 2, 3 and 4, irradiated by a short circularly polarized laser pulse of 400 nm. The field propagates in the direction parallel to the z-component of the angular momentum of the atom. We investigate probabilities for t

James Juno

In collisionless and weakly collisional plasmas, the particle distribution function is a rich tapestry of the underlying physics. However, actually leveraging the particle distribution function to understand the dynamics of a weakly collisional plasma is challenging. The equation system of relevance, the Vlasov-Maxwell-Fokker-Planck (VM-FP) system of equatio

Olivier Ozenda, Epifanio G. Virga

The Kirchhoff-Love hypothesis expresses a kinematic constraint that is assumed to be valid for the deformations of a three-dimensional body when one of its dimensions is much smaller than the other two, as is the case for plates. This hypothesis has a long history checkered with the vicissitudes of life: even its attribution has been questioned, and recent r

Christoph Bandt

We present a simple technique to compare the development of the Covid-19 epidemic in different regions, based only on the time series of confirmed cases. Weekly new infections, taken for every day, are interpreted as infection potential of Covid-19. We derive a robust time-varying reproduction rate for the infection potential, including asymptomatic cases, w

Freid Tong

In this note, we introduce a new type of positivity condition for the curvature of a Hermitian manifold, which generalizes the notion of nonnegative quadratic orthogonal bisectional curvature to the non-K\"ahler case. We derive a Bochner formula for closed $(1, 1)$-forms from which this condition appears naturally and prove that if a Hermitian manifold satis

Stephan Sponar, Armin Danner, Vito Pecile, Nico Einsidler

Information-theoretic uncertainty relations formulate the joint immeasurability of two non-commuting observables in terms of information entropies. The trade-off of the accuracy in the outcome of two successive measurements manifests in entropic noise-disturbance uncertainty relations. Recent theoretical analysis predicts that projective measurements are not

Stephan Baier, Dwaipayan Mazumder

The distribution of $\alpha p$ modulo one, where $p$ runs over the rational primes and $\alpha$ is a fixed irrational real, has received a lot of attention. It is natural to ask for which exponents $\nu>0$ one can establish the infinitude of primes $p$ satisfying $||\alpha p||\le p^{-\nu}$. The latest record in this regard is Kaisa Matom\"aki's landmark resu

Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart

Understanding predictions made by deep neural networks is notoriously difficult, but also crucial to their dissemination. As all machine learning based methods, they are as good as their training data, and can also capture unwanted biases. While there are tools that can help understand whether such biases exist, they do not distinguish between correlation an

Sebastian Jaszczur, Michał Łuszczyk, Henryk Michalewski

We use neural graph networks with a message-passing architecture and an attention mechanism to enhance the branching heuristic in two SAT-solving algorithms. We report improvements of learned neural heuristics compared with two standard human-designed heuristics.

Qing Liu, Nageswari Shanmugalingam, Xiaodan Zhou

In this paper we prove the equivalence between some known notions of solutions to the eikonal equation and more general analogs of the Hamilton-Jacobi equations in complete and rectifiably connected metric spaces. The notions considered are that of curve-based viscosity solutions, slope-based viscosity solutions, and Monge solutions. By using the induced int

Xun Zou, Mehdi Ganji, Hamid Jafarkhani

In this letter, we study a two-user downlink asynchronous non-orthogonal multiple access (ANOMA) with limited feedback. We employ the max-min criterion for the power allocation and derive the closed-form expressions for the upper and lower bounds of the max-min rate. It is demonstrated that ANOMA can achieve the same or even higher average maxmin rate with a

Pratik Mazumder, Pravendra Singh, Kranti Kumar Parida, Vinay P. Namboodiri

In this paper, we propose a novel approach for generalized zero-shot learning in a multi-modal setting, where we have novel classes of audio/video during testing that are not seen during training. We use the semantic relatedness of text embeddings as a means for zero-shot learning by aligning audio and video embeddings with the corresponding class label text

Hajime Fukushima, Hidenobu Yajima, Kazuyuki Sugimura, Takashi Hosokawa

We study star cluster formation in various environments with different metallicities and column densities by performing a suite of three-dimensional radiation hydrodynamics simulations. We find that the photoionization feedback from massive stars controls the star formation efficiency (SFE) in a star-forming cloud, and its impact sensitively depends on the g

Lasha Abzianidze, Rik van Noord, Hessel Haagsma, Johan Bos

The paper presents the IWCS 2019 shared task on semantic parsing where the goal is to produce Discourse Representation Structures (DRSs) for English sentences. DRSs originate from Discourse Representation Theory and represent scoped meaning representations that capture the semantics of negation, modals, quantification, and presupposition triggers. Additional

Anar Rustamov

One of the ultimate goals of nuclear collision experiments at high energy is to map the phase diagram of strongly interacting matter. A very challenging task is the determination of the QCD phase structure including the search for critical behavior and verification of the possible existence of a critical end point of a first order phase transition line. A pr

Angelo Tartaglia

The paper concerns the use of satellites of the Galileo constellation for relativistic positioning and for measurements of the gravito-magnetic effects induced by the angular momentum both of the Earth and of the dark halo of the Milky Way. The experimental approach is based on the generalized Sagnac effect, induced both by the rotation of the device and the

Davide Ravagli, Georgi N. Boshnakov

Obtaining reliable estimates of conditional covariance matrices is an important task of heteroskedastic multivariate time series. In portfolio optimization and financial risk management, it is crucial to provide measures of uncertainty and risk as accurately as possible. We propose using mixture vector autoregressive (MVAR) models for portfolio optimization.

Jack E. N. Swallow, Christian Vorwerk, Piero Mazzolini, Patrick Vogt

The search for new wide band gap materials is intensifying to satisfy the need for more advanced and energy efficient power electronic devices. Ga$_2$O$_3$ has emerged as an alternative to SiC and GaN, sparking a renewed interest in its fundamental properties beyond the main $\beta$-phase. Here, three polymorphs of Ga$_2$O$_3$, $\alpha$, $\beta$ and $\vareps

Piotr Kucharski

We introduce and explore the relation between quivers and 3-manifolds with the topology of the knot complement. This idea can be viewed as an adaptation of the knots-quivers correspondence to Gukov-Manolescu invariants of knot complements (also known as $F_K$ or $\hat{Z}$). Apart from assigning quivers to complements of $T^{(2,2p+1)}$ torus knots, we study t

Md. Asif Afzal, S. H. Naqib

A topological insulator possesses a bulk energy gap splitting the lowest empty band from the highest occupied electronic band. The electronic states at the surface (or edge in two dimensions), on the other hand, of a topological insulator are gapless and are protected by the time reversal symmetry. Such systems are promising for variety of optoelectronic, su

Santiago I. Betelu

This is an investigation of the limits of quantum circuit simulation with Schrodinger's formulation and low precision arithmetic. The goal is to estimate how much memory can be saved in simulations that involve random, maximally entangled quantum states. An arithmetic polar representation of $B$ bits is defined for each quantum amplitude and a normalization

Christian L. Bachman, Gabriel B. Goodwin

Simulations of a supersonic, premixed, reacting flow over a wedge were performed to investigate the effect of a boundary layer on the wedge surface on ignition and stability of oblique detonation waves (ODWs). Two computational domains were used: one containing a wedge of a single angle with a straight after-body, and the other containing a double-angle wedg

Ivan G. Graham, Owen R. Pembery, Euan A. Spence

This paper analyses the following question: let $\mathbf{A}_j$, $j=1,2,$ be the Galerkin matrices corresponding to finite-element discretisations of the exterior Dirichlet problem for the heterogeneous Helmholtz equations $\nabla\cdot (A_j \nabla u_j) + k^2 n_j u_j= -f$. How small must $\|A_1 -A_2\|_{L^q}$ and $\|{n_1} - {n_2}\|_{L^q}$ be (in terms of $k$-de

Anasua Mukhopadhyay, Iliya D. Stoev, David A. King, Kamendra P. Sharma

Prevention of protein aggregation and thus stabilization of proteins has large biological and biotechnological implications. Here, we show that inhibition of amyloid-like aggregates is possible in stoichiometric conjugates of polymer surfactant and bovine serum albumin (BSA) chosen as a model protein. We investigate using a combination of Thioflavin-T fluore

Amanda F. Mejia, David Bolin, Yu Ryan Yue, Jiongran Wang

Independent component analysis is commonly applied to functional magnetic resonance imaging (fMRI) data to extract independent components (ICs) representing functional brain networks. While ICA produces reliable group-level estimates, single-subject ICA often produces noisy results. Template ICA (tICA) is a hierarchical ICA model using empirical population p

Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski

In this paper, we introduce a new class of decision rules, referred to as Constant Depth Decision Rules (CDDRs), for multistage optimization under linear constraints with uncertainty-affected right-hand sides. We consider two uncertainty classes: discrete uncertainties which can take at each stage at most a fixed number d of different values, and polytopic u

R. D. Haywood, T. W. Milbourne, S. H. Saar, A. Mortier

We estimate disc-averaged RV variations of the Sun over the last magnetic cycle, from the single Fe I line observed by SDO/HMI, using a physical model for rotationally modulated magnetic activity that was previously validated against HARPS-N solar observations. We estimate the disc-averaged, unsigned magnetic flux and show that a simple linear fit to it redu

Xiao-Yun Xu, Xiao-Wei Wang, Dan-Yang Chen, C. Morais Smith

Fractals are fascinating structures, not only for their aesthetic appeal, but also because they allow for the investigation of physical properties in non-integer dimensions. In these unconventional systems, a myriad of intrinsic features might come into play, such as the fractal dimension, the spectral dimension, or the fractal geometry. Despite abundant the

Nicholas Hurtado, Hana Mir, Ian M. Shoemaker, Eli Welch

We study a Dark Matter (DM) model in which the dominant coupling to the standard model occurs through a neutrino-DM-scalar coupling. The new singlet scalar will generically have couplings to nuclei/electrons arising from renormalizable Higgs portal interactions. As a result the DM particle $X$ can convert into a neutrino via scattering on a target nucleus $\

Yizao Wang

A variation of Choquet random sup-measures is introduced. These random sup-measures are shown to arise as the scaling limits of empirical random sup-measures of a general aggregated model. Because of the aggregations, the finite-dimensional distributions of introduced random sup-measures do not necessarily have classical extreme-value distributions. Examples

Fang Yu, Daowen Qiu, Xiaoming Wang, Qin Li

New quantum private database (with N elements) query protocols are presented and analyzed. Protocols preserve O(logN) communication complexity of known protocols for the same task, but achieve several significant improvements in security, especially concerning user privacy. For example, the randomized form of our protocol has a cheat-sensitive property - it

Lukas Gebhard, Felix Hamborg

News articles covering policy issues are an essential source of information in the social sciences and are also frequently used for other use cases, e.g., to train NLP language models. To derive meaningful insights from the analysis of news, large datasets are required that represent real-world distributions, e.g., with respect to the contained outlets' popu

Haruhisa Enomoto

We give a classification of substructures (= closed subbifunctors) of a given skeletally small extriangulated category by using the category of defects, in a similar way to the author's classification of exact structures of a given additive category. More precisely, for an extriangulated category, possible substructures are in bijection with Serre subcategor

Nilasis Chaudhuri

The goal of the present paper is to prove that if a weak limit of a consistent approximation scheme of compressible complete Euler system in the full space $ \mathbb{R}^d,\; d=2,3 $ is a weak solution of the system then eventually the approximate solutions converge strongly in suitable norms locally under a minimal assumption on the initial data of the appro

Rajasekhar Medapalli, Guanqiao Li, Sheena K. K. Patel, Rostislav. V. Mikhaylovskiy

Femtosecond laser excitation of FeRh/Pt bilayers launches an ultrafast pulse of electric photocurrent in the Pt-layer and thus results in emission of electromagnetic radiation in the THz spectral range. Analysis of the THz emission as a function of polarization of the femtosecond laser pulse, external magnetic field, sample temperature and sample orientation

Hiroshi Ito

This paper demonstrates input-to-state stability (ISS) of the SIR model of infectious diseases with respect to the disease-free equilibrium and the endemic equilibrium. Lyapunov functions are constructed to verify that both equilibria are individually robust with respect to perturbation of newborn/immigration rate which determines the eventual state of popul

Thomas Berger

In this paper the feasibility of funnel control techniques for the Fokker-Planck equation corresponding to a multi-dimensional Ornstein-Uhlenbeck process on an unbounded spatial domain is explored. First, using weighted Lebesgue and Sobolev spaces, an auxiliary operator is defined via a suitable sesquilinear form. This operator is then transformed to the des

Hariharan Narayanan

Motivated by connections to random matrices, Littlewood-Richardson coefficients and tilings, we study random discrete concave functions on an equilateral lattice. We show that such functions having a periodic Hessian of a fixed average value $- s$ concentrate around a quadratic function. We consider the set of all concave functions $g$ on an equilateral latt

Adam M. Edwards, Robert B. Gramacy

Large scale Gaussian process (GP) regression is infeasible for larger data sets due to cubic scaling of flops and quadratic storage involved in working with covariance matrices. Remedies in recent literature focus on divide-and-conquer, e.g., partitioning into sub-problems and inducing functional (and thus computational) independence. Such approximations can

Mahyar Tourchi Moghaddam

Fires, earthquakes, floods, hurricanes, overcrowding, or and even pandemic viruses endanger human lives. Hence, designing infrastructures to handle possible emergencies has become an ever-increasing need. The safe evacuation of occupants from the building takes precedence when dealing with the necessary mitigation and disaster risk management. This thesis de

Michael Mesarcik, Albert-Jan Boonstra, Christiaan Meijer, Walter Jansen

Modern radio telescopes combine thousands of receivers, long-distance networks, large-scale compute hardware, and intricate software. Due to this complexity, failures occur relatively frequently. In this work we propose novel use of unsupervised deep learning to diagnose system health for modern radio telescopes. The model is a convolutional Variational Auto

Robert Auffarth, Sebastián Rahausen

Given an embedding of a smooth projective curve $X$ of genus $g\geq1$ into $\mathbb{P}^N$, we study the locus of linear subspaces of $\mathbb{P}^N$ of codimension 2 such that projection from said subspace, composed with the embedding, gives a Galois morphism $X\to\mathbb{P}^1$. For genus $g\geq2$ we prove that this locus is a smooth projective variety with c

Serena Di Giorgio, Paulo Mateus

Herein we study the problem of recovering a density operator from a set of compatible marginals, motivated from limitations of physical observations. Given that the set of compatible density operators is not singular, we adopt Jaynes' principle and wish to characterize a compatible density operator with maximum entropy. We first show that comparing the entro

Bruno J. De Bórtoli, Lilia P. Bassino, Juan P. Caso, Ana I. Ennis

We present the first photometric study of the globular cluster system (GCS) of the E galaxy NGC 3613 (Mv = -21.5, d = 30.1 Mpc), as well as the surface photometry of the host galaxy, based on Gemini/GMOS images. Being considered the central galaxy of a group, NGC 3613 inhabits a low-density environment although its intrinsic brightness is similar to the expe

Francesco Zola, Jan Lukas Bruse, Xabier Etxeberria Barrio, Mikel Galar

In Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these ground-truth datasets are frequently affected by significant class imbalance as generally they contain much more information regarding legal services (Exchange, Gambling), than regardi

Yohsuke Matsuzawa, Sheng Meng, Takahiro Shibata, De-Qi Zhang

Let $f:X\to X $ be a dominant self-morphism of an algebraic variety over an algebraically closed field of characteristic zero. We consider the set $\Sigma_{f^{\infty}}$ of $f$-periodic (irreducible closed) subvarieties of small dynamical degree, the subset $S_{f^{\infty}}$ of maximal elements in $\Sigma_{f^{\infty}}$, and the subset $S_f$ of $f$-invariant el

Quentin Henry, Guillaume Faye, Luc Blanchet

We compute the gravitational-wave (GW) energy flux up to the next-to-next-to-leading (NNL) order of tidal effects in a spinless compact binary system on quasi-circular orbits. Starting from an effective matter action, we obtain the stress-energy tensor of the system, which we use in a GW generation formalism based on multipolar-post-Minkowskian (MPM) and pos

Jingyang Zhang, Guotai Wang, Hongzhi Xie, Shuyang Zhang

The segmentation of coronary arteries in X-ray angiograms by convolutional neural networks (CNNs) is promising yet limited by the requirement of precisely annotating all pixels in a large number of training images, which is extremely labor-intensive especially for complex coronary trees. To alleviate the burden on the annotator, we propose a novel weakly sup

Marco Cicalese, Matthias Ruf, Gianluca Orlando

We investigate the relationship between the $N$-clock model (also known as planar Potts model or $\mathbb{Z}_N$-model) and the $XY$ model (at zero temperature) through a $\Gamma$-convergence analysis of a suitable rescaling of the energy as both the number of particles and $N$ diverge. We prove the existence of rates of divergence of $N$ for which the contin

Jan Albert, Ferran Macià, Joan Manel Hernàndez

Spin-torque nano-oscillators (STNO) are microwave auto-oscillators based on magnetic resonances having a nonlinear response with the oscillating amplitude, which provides them with a large frequency tunability including the possibility of mutual synchronization. The magnetization dynamics in STNO are induced by spin transfer torque (STT) from spin currents a

Zhuoying Wang, Yongtao Wang, Zhi Tang, Yangyan Li

Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-transfer operations, i.e., up-sampling and down-sampling to learn multi-scale features. In this work, we find th

Edison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs, Stephen Gould

Despite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews. In light of this issue, we propose a multi-modal approach for mining fine-grained opinions from video reviews that is able to determine the aspects of the item under review that are being discussed and the sentiment orientation t

Roberto Merlin

A brief, tutorial account is given of the differences between the near and far regions of the elec-tromagnetic field emphasizing the source-dependent behavior of the former and the universal properties of the latter. Field patterns of near-field plates, that is, metasurfaces used for sub-wavelength applications, are discussed in some detail. Examples are giv

L. Jetsu

Constant orbital period ephemerides of eclipsing binaries give the computed eclipse epochs (C). These ephemerides based on the old data can not accurately predict the observed future eclipse epochs (O). Predictability can be improved by removing linear or quadratic trends from the O-C data. Additional companions in an eclipsing binary system cause light-time

Cameron Trotter, Georgia Atkinson, Matt Sharpe, Kirsten Richardson

We introduce the Northumberland Dolphin Dataset 2020 (NDD20), a challenging image dataset annotated for both coarse and fine-grained instance segmentation and categorisation. This dataset, the first release of the NDD, was created in response to the rapid expansion of computer vision into conservation research and the production of field-deployable systems s

Jong-Hoon Ahn

In recent years, machine learning methods have been widely used to study physical systems that are challenging to solve with governing equations. Physicists and engineers are framing the data-driven paradigm as an alternative approach to physical sciences. In this paradigm change, the deep learning approach is playing a pivotal role. However, most learning a

E. F. Talantsev, R. C. Mataira

Dissipative-free electric current flow is one of the most fascinating and practically important property of superconductors. Theoretical consideration of the charge carriers flow in infinitely long rectangular slab of superconductor in the absence of external magnetic field (so called, self-field) is based on an assumption that the charge carriers have recti

Rita Ferreira, Irene Fonseca, Raghavendra Venkatraman

We consider a homogenization problem associated with quasi-crystalline multiple integrals of the form \begin{equation*} \begin{aligned} u_\varepsilon\in L^p(\Omega;\mathbb{R}^d) \mapsto \int_\Omega f_R\Big(x,\frac{x}{\varepsilon}, u_\varepsilon(x)\Big)\, dx, \end{aligned} \end{equation*} where $u_\varepsilon$ is subject to constant-coefficient linear partial

Sumit Som, Lakshmi Kanta Dey, Sudeshna Basu

In this paper, we prove that if $E$ is a uniquely remotal subset of a real normed linear space $X$ such that $E$ has a Chebyshev center $c \in X$ and the farthest point map $F:X\rightarrow E$ restricted to $[c,F(c)]$ is partially statistically continuous at $c$, then $E$ is a singleton. We obtain a necessary condition on uniquely remotal subsets of uniformly

Riccardo Montalto

We prove the existence of small amplitude, time-quasi-periodic solutions (invariant tori) for the incompressible Navier-Stokes equation on the $d$-dimensional torus $\T^d$, with a small, quasi-periodic in time external force. We also show that they are orbitally and asymptotically stable in $H^s$ (for $s$ large enough). More precisely, for any initial datum

Youri Raaijmakers, Sem Borst, Onno Boxma

We consider a system with several job types and two parallel server pools. Within the pools the servers are homogeneous, but across pools possibly not in the sense that the service speed of a job may depend on its type as well as the server pool. Immediately upon arrival, jobs are assigned to a server pool. This could be based on (partial) knowledge of their

Hexin Bai, Peng Chu, Jeng-Yuan Tsai, Nathan Wilson

Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties. Traditional electronic structure methods require expensive computation time and memory consumption, thus a fast and accurate prediction model is desired with increasing importance. Repr

A. Diaz-Fernandez

We consider the three-dimensional Hamiltonian for Bi$_2$Se$_3$, a second-generation topological insulator, under the effect of a periodic drive for both in-plane and out-of-plane fields. As it will be shown by means of high-frequency expansions up to second order in the Floquet Hamiltonian, the driving induces anisotropies in the Dirac cone and opens up a qu

Marcus J. Grote, Simon Michel, Stefan Sauter

Local time-stepping methods permit to overcome the severe stability constraint on explicit methods caused by local mesh refinement without sacrificing explicitness. In \cite{DiazGrote09}, a leapfrog based explicit local time-stepping (LF-LTS) method was proposed for the time integration of second-order wave equations. Recently, optimal convergence rates were

Tobias Ekholm, Angus Gruen, Sergei Gukov, Piotr Kucharski

Reducing a 6d fivebrane theory on a 3-manifold $Y$ gives a $q$-series 3-manifold invariant $\widehat{Z}(Y)$. We analyse the large-$N$ behaviour of $F_K=\widehat{Z}(M_K)$, where $M_K$ is the complement of a knot $K$ in the 3-sphere, and explore the relationship between an $a$-deformed ($a=q^N$) version of $F_{K}$ and HOMFLY-PT polynomials. On the one hand, in

Gerhard Jung, Thomas Voigtmann, Thomas Franosch

Multiple relaxation channels often arise in the dynamics of liquids where the momentum current associated to the particle-conservation law splits into distinct contributions. Examples are strongly confined liquids for which the currents in lateral and longitudinal direction to the walls are very different, or fluids of nonspherical particles with distinct re

Y. Yamaguchi, K. Kohno, B. Hatsukade, T. Wang

We make use of the ASAGAO, deep 1.2 mm continuum observations of a 26 arcmin$^2$ region in the GOODS-South field obtained with ALMA, to probe dust-enshrouded star formation in $K$-band selected (i.e., stellar mass selected) galaxies, which are drawn from the ZFOURGE catalog. Based on the ASAGAO combined map, which was created by combining ASAGAO and ALMA arc

Sumit Som, Adrian Petrusel, Lakshmi Kanta Dey

In \cite[\, An, V.T., Tuyen, Q.L. and Dung, V.N., Stone-type theorem on $b$-metric spaces and applications, Topology Appl. 185-186 (2015), 50-64.]{an}, An et al. had provided a sufficient condition for $b$-metric spaces to be metrizable. However, their proof of metrizability relied on an assumption that the distance function is continuous in one variable. In

Daniel Fernández-González, Carlos Gómez-Rodríguez

Transition-based parsers implemented with Pointer Networks have become the new state of the art in dependency parsing, excelling in producing labelled syntactic trees and outperforming graph-based models in this task. In order to further test the capabilities of these powerful neural networks on a harder NLP problem, we propose a transition system that, than

George Chechin, Denis Ryabov

The research group from the Rostov State University has been developing the theory of bushes of nonlinear normal modes (NNMs) in Hamiltonian systems with discrete symmetry since the late 90s of the last century. Group-theoretical methods for studying large-amplitude atomic vibrations in molecular and crystal structures were developed. Each bush represents a

Malte Ostendorff, Till Blume, Saskia Ostendorff

Recent advances in the area of legal information systems have led to a variety of applications that promise support in processing and accessing legal documents. Unfortunately, these applications have various limitations, e.g., regarding scope or extensibility. Furthermore, we do not observe a trend towards open access in digital libraries in the legal domain

Frédéric A. Dreyer, Alexander Karlberg, Jean-Nicolas Lang, Mathieu Pellen

Theoretical predictions with next-to-next-to-leading order (NNLO) QCD accuracy combined with the next-to-leading order (NLO) electroweak (EW) corrections are presented for differential observables of the double-Higgs production process via vector-boson fusion. While the QCD corrections were previously known, the EW ones are computed here for the first time.

Tomas Sikorsky, Jeschua Geist, Daniel Hengstler, Sebastian Kempf

We present a measurement of the low-energy (0--60$\,$keV) $\gamma$ ray spectrum produced in the $\alpha$-decay of $^{233}$U using a dedicated cryogenic magnetic micro-calorimeter. The energy resolution of $\sim$$10\,$eV, together with exceptional gain linearity, allow us to measure the energy of the low-lying isomeric state in $^{229}$Th using four complemen

Ivan Homoliak, Mario Larangeira, Martin Peresini, Pawel Szalachowski

Distributed ledger systems (i.e., blockchains) have received a lot of attention. They promise to enable mutually untrusted participants to execute transactions while providing the immutability of the data and censorship resistance. Although decentralized ledgers are a disruptive innovation, as of today, they suffer from scalability, privacy, or governance is

Lasse Hansen, Mattias P. Heinrich

Though, deep learning based medical image registration is currently starting to show promising advances, often, it still fells behind conventional frameworks in terms of registration accuracy. This is especially true for applications where large deformations exist, such as registration of interpatient abdominal MRI or inhale-to-exhale CT lung registration. M

Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki

Retinal imaging serves as a valuable tool for diagnosis of various diseases. However, reading retinal images is a difficult and time-consuming task even for experienced specialists. The fundamental step towards automated retinal image analysis is vessel segmentation and artery/vein classification, which provide various information on potential disorders. To

M. Boleininger, M. Gallauer, S. L. Dudarev, T. D. Swinburne

The ability of a body-centered cubic metal to deform plastically is limited by the thermally activated glide motion of screw dislocations, which are line defects with a mobility exhibiting complex dependence on temperature, stress, and dislocation segment length. We derive an analytical expression for the velocity of dislocation glide, based on a statistical

Yangguang Yu, Xiangke Wang, Zhiyong Sun, Lincheng Shen

In this paper, a novel design scheme is introduced to solve the optimal control problem for nonlinear systems with unsymmetrical and state-dependent input constraints. By introducing an initial stabilizing control policy as the baseline of the constructed optimal control policy, we remove the assumption in the current study for the adaptive optimal control,