June 2019 arXiv papers — page 7

Titiksha Srivastava, Willy Lim, Isabelle Joumard, Stéphane Auffret

Skyrmions are chiral magnetic textures that have immense potential for applications in spintronic devices. However, their formation is quite challenging and necessitates a subtle balance of the magnetic interactions at play. Here, we study Ta/FeCoB/TaOx trilayer using crossed double wedges i.e. thickness gradients of FeCoB and of top Ta, which is subsequentl

N. Singh, P. Elliott, J. K. Dewhurst, S. Sharma

We demonstrate optical control of magnons using femtosecond laser pulses by performing ab-initio real-time time-dependent density functional theory (TDDFT) simulations. We predict that the spin-wave dynamics in Fe$_{50}$Ni$_{50}$ can be manipulated by tailoring the applied laser pulse via three distinct mechanisms: (1) element selective destruction of magnon

Daniel Zügner, Stephan Günnemann

Recent works show that Graph Neural Networks (GNNs) are highly non-robust with respect to adversarial attacks on both the graph structure and the node attributes, making their outcomes unreliable. We propose the first method for certifiable (non-)robustness of graph convolutional networks with respect to perturbations of the node attributes. We consider the

David Hernandez

We give a proof of the periodicity of quantum $T$-systems of type $A_n\times A_\ell$ with certain spiral boundary conditions. Our proof is based on categorification of the $T$-system in terms of the representation theory of quantum affine algebras, more precisely on relations between classes of Kirillov-Reshetikhin modules and of evaluation modules.

Benjamin Antieau, Daniel Bragg

We consider derived invariants of varieties in positive characteristic arising from topological Hochschild homology. Using theory developed by Ekedahl and Illusie-Raynaud in their study of the slope spectral sequence, we examine the behavior under derived equivalences of various $p$-adic quantities related to Hodge-Witt and crystalline cohomology groups, inc

Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson

In complex tasks, such as those with large combinatorial action spaces, random exploration may be too inefficient to achieve meaningful learning progress. In this work, we use a curriculum of progressively growing action spaces to accelerate learning. We assume the environment is out of our control, but that the agent may set an internal curriculum by initia

M. C. Diamantini, S. V. Postolova, A. Yu. Mironov, L. Gammaitoni

The nature of hadrons is one of the most fundamental mysteries of physics. It is generally agreed that they are made of "colored" quarks, which move nearly free at short scales but are confined inside hadrons by strong interactions at large distances. Because of confinement, quarks are never directly observable and, experimentally, their properties can be te

Ferdinand Jost, Pascal Peter, Joachim Weickert

In spite of the fact that efficient compression methods for dense two-dimensional flow fields would be very useful for modern video codecs, hardly any research has been performed in this area so far. Our paper addresses this problem by proposing the first lossy diffusion-based codec for this purpose. It keeps only a few flow vectors on a coarse grid. Additio

Kristopher Tapp

In the context of modern sampling methods for redistricting, we define a natural measurement of the clustering of a political party, and we study how clustering affects the expected election outcome. We first prove general results and then apply this framework to understand how the political geography in Pennsylvania affects the expected outcome of congressi

Guillaume Chèze

In this article we suggest a model of computation for the cake cutting problem. In this model the mediator can ask the same queries as in the Robertson-Webb model but he or she can only perform algebraic operations as in the Blum-Shub-Smale model. All existing algorithms described in the Robertson-Webb model can be described in this new model.We show that in

Zhijie Qu, Joel N. Bregman

The warm ($\log~T\approx5$) gas is an important gaseous component in the galaxy baryonic cycle. We built a 2-dimension disk-CGM model to study the warm gas distribution of the Milky Way (MW) using the absorption line surveys of Si IV and O VI. In this model, the disk component of both ions has the same density profile ($n(r, z)=n_0\exp(-|z|/z_0)\exp(-r/r_0)$

Ofelia Pisanti

In the era of multi-messenger astronomy, neutrinos are among the most important astronomical messengers, due to their interaction properties. In these lessons I briefly review the main issues concerning the theory on astrophysical neutrinos.

Ahmed Zahari

The purpose of this paper is to study the structure and the algebraic varieties of BiHom-associative algebras. We provide a classication of n-dimensional BiHom-associative and BiHom-bialgebras and BiHom Hopf algebras for n $\le$ 3.

Simone S. Bavera, Tassos Fragos, Ying Qin, Emmanouil Zapartas

We study the formation of coalescing binary black holes via the evolution of isolated field binaries that go through the common envelope phase in order to obtain the combined distributions of the main observables of Advanced LIGO. We used a hybrid technique that combines the parametric binary population synthesis code COMPAS with detailed binary evolution si

Hugo Vanneuville

In this paper, we introduce and study the annealed spectral sample of Voronoi percolation, which is a continuous and finite point process in $\mathbb{R}^2$ whose definition is mostly inspired by the spectral sample of Bernoulli percolation introduced in [GPS10] by Garban, Pete and Schramm. We show a clustering effect as well as estimates on the full lower ta

Kelong Cheng, Cheng Wang, Steven M. Wise

In this paper we propose and analyze an energy stable numerical scheme for the square phase field crystal (SPFC) equation, a gradient flow modeling crystal dynamics at the atomic scale in space but on diffusive scales in time. In particular, a modification of the free energy potential to the standard phase field crystal model leads to a composition of the 4-

Lukáš Flajšman, Kai Wagner, Marek Vaňatka, Jonáš Gloss

Metastable face-centered-cubic Fe78Ni22 thin films grown on Cu(001) substrates are excellent candidates for focused ion beam direct writing of magnonic structures due to their favorable magnetic properties after ion-beam-induced transformation. The focused ion beam transforms the originally nonmagnetic fcc phase into the ferromagnetic bcc phase with addition

Rustem Khasanov, Hubertus Luetkens, Alex Amato, Elvezio Morenzoni

The temperature dependent measurements of the thermodynamic critical field and the specific heat for the pressure stabilized Ga-II phase of elemental Gallium are presented. The discussion of these and other Ga phases data in the context of elemental and binary phonon-mediated type-I superconductors allowed to establish simple scaling relations between BCS qu

Elliot Bridges, Carlos R. Mafra

We write down closed formulas for all necessary steps to obtain multiparticle super Yang--Mills superfields in the so-called BCJ gauge. The superfields in this gauge have obvious applications in the quest for finding BCJ-satisfying representations of amplitudes. As a benefit of having these closed formulas, we identify the explicit finite gauge transformatio

Anton Andreev, Grégoire Cattan, M Congedo

In this article, we explore the availability of head-mounted display (HMD) devices which can be coupled in a seamless way with P300-based brain-computer interfaces (BCI) using electroencephalography (EEG). The P300 is an event-related potential appearing about 300ms after the onset of a stimulation. The recognition of this potential on the ongoing EEG requir

Adam Amos-Binks, Dustin Dannenhauer

Anticipatory thinking is a complex cognitive process for assessing and managing risk in many contexts. Humans use anticipatory thinking to identify potential future issues and proactively take actions to manage their risks. In this paper we define a cognitive systems approach to anticipatory thinking as a metacognitive goal reasoning mechanism. The contribut

Fan Jia, Jun Liu, Xue-cheng Tai

Convolutional neural networks (CNNs) show outstanding performance in many image processing problems, such as image recognition, object detection and image segmentation. Semantic segmentation is a very challenging task that requires recognizing, understanding what's in the image in pixel level. Though the state of the art has been greatly improved by CNNs, th

Jihun Choi, Chirag Rao, Fikadu T. Dagefu

This paper presents an experimental investigation of real-time digital video streaming in physically complex Non-Line-Of-Sight (NLoS) channels using a low-power, low-VHF system integrated on a compact robotic platform. Reliable video streaming in NLoS channels over infrastructure-poor ad-hoc radio networks is challenging due to multipath and shadow fading. I

Nikolaj G. Ebensperger, Benedikt Ferdinand, Dieter Koelle, Reinhold Kleiner

We present an experimental approach for cryogenic dielectric measurements on ultra-thin insulating films. Based on a coplanar microwave waveguide design we implement superconducting quarter-wave resonators with inductive coupling, which allows us to determine the real part $\varepsilon_1$ of the dielectric function at GHz frequencies and for sample thickness

Jonathan D. Axtell, Kyu-Hwan Lee

We establish an embedding of the quantum enveloping algebra of a symmetric generalized Kac--Moody algebra into a localized Hall algebra of $\mathbb Z_2$-graded complexes of representations of a quiver with (possible) loops. To overcome difficulties resulting from the existence of infinite dimensional projective objects, we consider the category of finitely-p

Julian Fischer, Michael Kniely

In the computation of the material properties of random alloys, the method of "special quasirandom structures" attempts to approximate the properties of the alloy on a finite volume with higher accuracy by replicating certain statistics of the random atomic lattice in the finite volume as accurately as possible. In the present work, we provide a rigorous jus

Matteo Biagetti

The understanding of the primordial mechanism that seeded the cosmic structures we observe today in the sky is one of the major goals in cosmology. The leading paradigm for such a mechanism is provided by the inflationary scenario, a period of violent accelerated expansion in the very early stages of evolution of the Universe. While our current knowledge of

A. Belfakir, A. Belhaj, Y. El Maadi, S-E. Ennadifi

Using the toroidal compactification of string theory on n-dimensional tori, Tn, we investigate dyonic objects in arbitrary dimensions. First, we present a class of dyonic black solutions formed by two different D-branes using a correspondence between toroidal cycles and objects possessing both magnetic and electric charges, belonging to %%%% dyonic gauge sym

Giorgia Franchini, Mathilde Galinier, Micaela Verucchi

In the context of deep learning, the costliest phase from a computational point of view is the full training of the learning algorithm. However, this process is to be used a significant number of times during the design of a new artificial neural network, leading therefore to extremely expensive operations. Here, we propose a low-cost strategy to predict the

Laurent Mombaerts, Atte Aalto, Johan Markdahl, Jorge Goncalves

In the past years, many computational methods have been developed to infer the structure of gene regulatory networks from time-series data. However, the applicability and accuracy presumptions of such algorithms remain unclear due to experimental heterogeneity. This paper assesses the performance of recent and successful network inference strategies under a

Koen Pauwels, Georgios Karachalias, Michiel Derhaeg, Tom Schrijvers

GADTs were introduced in Haskell's eco-system more than a decade ago, but their interaction with several mainstream features such as type classes and functional dependencies has a lot of room for improvement. More specifically, for some GADTs it can be surprisingly difficult to provide an instance for even the simplest of type classes. In this paper we ident

Chiara Marletto, Vlatko Vedral

We argue that the fermionic exchange phase could be detected by local means. We propose a simple experiment to test our idea. This leads us to speculate that there might be a deeper mechanism behind the notion of particle statistics in quantum physics that goes beyond the conventional argument based on the spin-statistics connections.

AR. Murugan, J. Dianavinnarasi, C. Ganesa Moorthy

The concept of statistical convergence based on asymptotic density is introduced in this article through nets. Some possible extensions of classical results for statistical convergence of sequences are obtained in this article, with extensions to nets.

Anthony Bell, James Matthews, Katherine Blundell

We show that the energy required to turbulently amplify magnetic field during cosmic ray (CR) acceleration by shocks extracts energy from the CR and steepens the CR energy spectrum.

Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder

Automata learning techniques automatically generate system models from test observations. These techniques usually fall into two categories: passive and active. Passive learning uses a predetermined data set, e.g., system logs. In contrast, active learning actively queries the system under learning, which is considered more efficient. An influential active l

Igor N. Cherepanov, Giacomo Bighin, Lars Christiansen, Anders Vestergaard Jørgensen

We use laser-induced rotation of single molecules embedded in superfluid helium nanodroplets to reveal angular momentum dynamics and transfer in a controlled setting, under far-from-equilibrium conditions. As an unexpected result, we observe pronounced oscillations of time-dependent molecular alignment that have no counterpart in gas-phase molecules. Angulon

Alberto Sonnino, George Danezis

The Sybil attack plagues all peer-to-peer systems, and modern open distributed ledgers employ a number of tactics to prevent it from proof of work, or other resources such as space, stake or memory, to traditional admission control in permissioned settings. With SybilQuorum we propose an alternative approach to securing an open distributed ledger against Syb

P. G. Jonker, N. C. Stone, A. Generozov, S. van Velzen

We present Chandra X-ray observations of four optically-selected tidal disruption events (TDEs) obtained 4-9 years after discovery. Three sources were detected with luminosities between 9X10^40 and 3X10^42 erg/s. The spectrum of PTF09axc is consistent with a power law of index 2.5+-0.1, whereas the spectrum of PTF09ge is very soft. The power law spectrum of

Tanja Gologranc, Marko Jakovac, Tim Kos, Tilen Marc

A sequence $(v_1,\ldots ,v_k)$ of vertices in a graph $G$ without isolated vertices is called a total dominating sequence if every vertex $v_i$ in the sequence totally dominates at least one vertex that was not totally dominated by $\{v_1,\ldots , v_{i-1}\}$ and $\{v_1,\ldots ,v_k\}$ is a total dominating set of $G$. The length of a shortest such sequence is

Ariel Barton

We solve the Neumann problem in the half space $\mathbb{R}^{n+1}_+$, for higher order elliptic differential equations with variable self-adjoint $t$-independent coefficients, and with boundary data in the negative smoothness space $\dot W^{-1,p}$, where $\max(0,\frac{1}{2}-\frac{1}{n}-\varepsilon) <\frac{1}{p} <\frac{1}{2}$. Our arguments are inspired by an

Gerald Eigen

We present herein new results from Belle on the $\tau^- \rightarrow \pi^- \nu_{\rm \tau} \ell^+ \ell^- $ branching fraction and from BABAR on the $\tau^- \rightarrow K^- (0,1,2,3) \pi^0 \nu_{\rm \tau}$, $\tau^- \rightarrow \pi^- (3,4) \pi^0 \nu_{\rm \tau}$ and $\tau^- \rightarrow K^- K^0_{\rm S} \nu_{\rm \tau}$ branching fractions. From the $K^- K^0_{\rm S}$

Davide Grassano, Olivia Pulci, Elena Cannuccia, Friedhelm Bechstedt

By means of $ab \ initio$ band structure methods and model Hamiltonians we investigate the electronic, spin and topological properties of four monopnictides crystallizing in body centered tetragonal structure. We show that the Weyl bands around a Weyl point W1 or W2 possess a strong anisotropy and tilt of the accompanying Dirac cones. These effects are large

Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson

We present FIESTA, a model selection approach that significantly reduces the computational resources required to reliably identify state-of-the-art performance from large collections of candidate models. Despite being known to produce unreliable comparisons, it is still common practice to compare model evaluations based on single choices of random seeds. We

Iuliana Bubuianu, Sergiu I. Vacaru, Elşen Veli Veliev

We investigate classical and quantum geometric information flow theories (respectively, GIFs and QGIFs) when the geometric flow evolution and field equations for nonholonomic Einstein systems, NES, are derived from Perelman-Lyapunov type entropic type functionals. In this work, the term NES encodes models of gravitational and matter fields interactions and t

Ovidiu Cristinel Stoica

One of the major concerns of Schr\"odinger, Lorentz, Einstein, and many others about the wave function is that it is defined on the $3\mathbf{N}$-dimensional configuration space, rather than on the $3$-dimensional physical space. This gives the impression that quantum mechanics cannot have a three-dimensional space or spacetime ontology, even in the absence

Wolfram Schmidt, Philipp Grete

We revisit the problem of how energy transfer through the turbulent cascade operates in compressible hydrodynamic turbulence. In general, there is no conservative compressible cascade since the kinetic and internal energy reservoirs can exchange energy through pressure dilatation. Moreover, statistically stationary turbulence at high Mach number can only be

Pierre Quinton, Pablo Martínez-Nuevo, Martin B. Møller

We propose a theoretical framework for the image source method that generalizes to arbitrary reflecting boundaries, e.g. boundaries that are curved or even with certain openings. Furthermore, it can seamlessly incorporate boundary absorption, source directivity, and nonspecular reflections. This framework is based on the notion of reflection paths that allow

ATLAS Collaboration

The momentum measurement capability of the ATLAS muon spectrometer relies fundamentally on the intrinsic single-hit spatial resolution of the monitored drift tube precision tracking chambers. Optimal resolution is achieved with a dedicated calibration program that addresses the specific operating conditions of the 354000 high-pressure drift tubes in the spec

Kin Quan, Ryutaro Tanno, Michael Duong, Arjun Nair

Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exhibit dilation of the airways. Accurate measurement of dilatation enables assessment of the progression of disease. Unfortunately the combination of image noise and airway bifurcations causes high variability in the profiles of cross-sectional areas, rendering the identification of affect

Louis Crane, David N. Yetter

We solve a very classical problem motivated by considerations in quantum gravity: providing a description of the geometry of a Euclidean tetrahedron from the initial data of the areas of the faces and the areas of the medial parallelograms of Yetter or equivalently of the pseudofaces of McConnell. In particular, we derive expressions for the dihedral angles,

Roy Cerqueti, Emilio De Santis

This paper presents a novel theoretical Monte Carlo Markov chain procedure in the framework of graphs. It specifically deals with the construction of a Markov chain whose empirical distribution converges to a given reference one. The Markov chain is constrained over an underlying graph, so that states are viewed as vertices and the transition between two sta

Mohamed S. Elmahdy, Jelmer M. Wolterink, Hessam Sokooti, Ivana Išgum

Joint image registration and segmentation has long been an active area of research in medical imaging. Here, we reformulate this problem in a deep learning setting using adversarial learning. We consider the case in which fixed and moving images as well as their segmentations are available for training, while segmentations are not available during testing; a

Michael Fröwis, Thilo Gottschalk, Bernhard Haslhofer, Christian Rückert

Analyzing cryptocurrency payment flows has become a key forensic method in law enforcement and is nowadays used to investigate a wide spectrum of criminal activities. However, despite its widespread adoption, the evidential value of obtained findings in court is still largely unclear. In this paper, we focus on the key ingredients of modern cryptocurrency an

Arno Pauly, Dongseong Seon, Martin Ziegler

According to Haar's Theorem, every compact group $G$ admits a unique (regular, right and) left-invariant Borel probability measure $\mu_G$. Let the Haar integral (of $G$) denote the functional $\int_G:\mathcal{C}(G)\ni f\mapsto \int f\,d\mu_G$ integrating any continuous function $f:G\to\mathbb{R}$ with respect to $\mu_G$. This generalizes, and recovers for t

Jorge Vitório Pereira, Olivier Thom

We prove that the formal completion of a complex projective surface along a rigid smooth curve with trivial normal bundle determines the birational equivalence class of the surface.

Hung Nguyen, Xuejian Wang, Leman Akoglu

Given a labeled dataset that contains a rare (or minority) class of of-interest instances, as well as a large class of instances that are not of interest, how can we learn to recognize future of-interest instances over a continuous stream? We introduce RaRecognize, which (i) estimates a general decision boundary between the rare and the majority class, (ii)

J. Dukelsky, J. E. García-Ramos, J. M. Arias, P. Pérez-Fernández

We present a number conserving particle-hole RPA theory for collective excitations in the transition from normal to superfluid nuclei. The method derives from an RPA theory developed long ago in quantum chemistry using antisymmetric geminal powers, or equivalently number projected HFB states, as reference states. We show within a minimal model of pairing plu

Mirko Pasquini, David Angeli

In this work we addressed the problem of stability analysis for an uncertain piecewise affine model of a genetic regulatory network. In particular we considered polytopic parameter uncertainties on the proteins production rate functions, giving conditions for the existence of a piecewise quadratic Lyapunov function for any possible realization of the system.

Nawapon Nakharutai, Matthias C. M. Troffaes, Camila C. S. Caiado

Maximality, interval dominance, and E-admissibility are three well-known criteria for decision making under severe uncertainty using lower previsions. We present a new fast algorithm for finding maximal gambles. We compare its performance to existing algorithms, one proposed by Troffaes and Hable (2014), and one by Jansen, Augustin, and Schollmeyer (2017). T

Balazs Boros, Stefan Müller, Georg Regensburger

It is well known that, for mass-action systems, complex-balanced equilibria are asymptotically stable. For generalized mass-action systems, even if there exists a unique complex-balanced equilibrium (in every stoichiometric class and for all rate constants), it need not be stable. We first discuss several notions of matrix stability (on a linear subspace) su

Junmo Song, Jiwon Kang

This study considers the problem of testing for a parameter change in the presence of outliers. For this, we propose a robust test using the objective function of minimum density power divergence estimator (MDPDE) by Basu et al. (Biometrika, 1998), and then derive its limiting null distribution. Our test procedure can be naturally extended to any parametric

Nicola Pia, Giovanni Placini

We classify complex surfaces $(M,\,J)$ admitting Engel structures $\mathcal{D}$ which are complex line bundles. Namely we prove that this happens if and only if $(M,\,J)$ has trivial Chern classes. We construct examples of such Engel structures by adapting a construction due to Geiges. We also study associated Engel defining forms and define a unique splitti

Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao

Local differential privacy (LDP) is a recently proposed privacy standard for collecting and analyzing data, which has been used, e.g., in the Chrome browser, iOS and macOS. In LDP, each user perturbs her information locally, and only sends the randomized version to an aggregator who performs analyses, which protects both the users and the aggregator against

Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli

We present PUFFINN, a parameterless LSH-based index for solving the $k$-nearest neighbor problem with probabilistic guarantees. By parameterless we mean that the user is only required to specify the amount of memory the index is supposed to use and the result quality that should be achieved. The index combines several heuristic ideas known in the literature.

S. K. Maurya, Ayan Banerjee, Francisco Tello-Ortiz

This paper is devoted in the study of the hydrostatic equilibrium of stellar structure in the framework of modified $f(R, T)$ gravity theory that allows the non-conservation of energy-momentum, with possible implications for several cosmological and astrophysical issues such as the late-time cosmic acceleration of the universe without appealing to exotic mat

Tyler Brown, Alexander G. Melnikov, Timothy H. McNicholl

Computability theory is used to evaluate the complexity of classifying various kinds of Lebesgue spaces and associated isometric isomorphism problems.

Junmo Song

This paper deals with the problem of testing for dispersion parameter change in discretely observed diffusion processes when the observations are contaminated by outliers. To lessen the impact of outliers, we first calculate residuals using a robust estimate and then propose a trimmed-residual based CUSUM test. The proposed test is shown to converge weakly t

Marco Covelli, Massimiliano Morrelli

This document was created in order to study the algorithms for the categorization of phrases and rank them using the facilities provided by the framework Apache Spark. Starting from the study illustrated in the publication "Classifying textual data: shallow, deep and ensemble methods" by Laura Anderlucci, Lucia Guastadisegni, Cinzia Viroli, we wanted to carr

Thierry Jolicoeur, Olivier Golinelli

The antiferromagnetic Heisenberg spin chain with integer spin has short-range magnetic order and an excitation energy gap above the ground state. This so-called Haldane gap is proportional to the exchange coupling $J$ of the Heisenberg chain. We discuss recent results about the spin dependence of the Haldane gap and conjecture an analytical formula valid asy

Patrick Morton

A formula is proved for the number of linear factors over $\mathbb{F}_l$ of the Hasse invariant of the Tate normal form $E_5(b)$ for a point of order $5$, as a polynomial in the parameter $b$, in terms of the class number of the imaginary quadratic field $K=\mathbb{Q}(\sqrt{-l})$, proving a conjecture of the author from 2005. A similar theorem is proved for

Jiao He, Rafael Granero-Belinchón

In this article, we consider a non-local variant of the Kuramoto-Sivashinsky equation in three dimensions (2D interface). Besides showing the global wellposedness of this equation we also obtain some qualitative properties of the solutions. In particular, we prove that the solutions become analytic in the spatial variable for positive time, the existence of

Fazal Hayat

The first multiplicative Zagreb index $\Pi_1$ of a graph $G$ is the product of the square of every vertex degree, while the second multiplicative Zagreb index $\Pi_2$ is the product of the products of degrees of pairs of adjacent vertices. In this paper, we give sharp lower bound for $\Pi_1$ and upper bound for $\Pi_2$ of trees with given distance $k$-domina

Pierre Barbillon, Julien Chiquet, Timothée Tabouy

The Stochastic Block Model (SBM) is a popular probabilistic model for random graphs. It is commonly used for clustering network data by aggregating nodes that share similar connectivity patterns into blocks. When fitting an SBM to a network which is partially observed, it is important to take into account the underlying process that generates the missing val

Shuai Han, Sai Xu, Weixiao Meng, Lei He

An artificial-noise (AN)-aided beamformer specific to correlated main and wiretap channels is designed in this paper. We consider slow-fading multiple-input-single-output (MISO) wiretap channels with a passive single-antenna eavesdropper, in which independent transmitter-side and correlated receiver-side are assumed. Additionally, the source has accurate mai

Yury A. Neretin

Consider an infinite homogeneous tree $T_n$ of valence $n+1$, its group $Aut(T_n)$ of automorphisms, and the group $Hie(T_n)$ of its spheromorphisms (hierarchomorphisms), i.~e., the group of homeomorphisms of the boundary of $T_n$ that locally coincide with transformations defined by automorphisms. We show that the subgroup $Aut(T_n)$ is spherical in $Hie(T_

Dangka Shylla, Elijah Ogaro Nyakango, Kirthanaa Indumathi, Kanhaiya Pandey

In this work we present a theoretical frame work to identify the role and the nature of interference between Autler-Townes (AT) peaks (or dressed states) in generic multi-level system. The destructive interference between the AT peaks, gives rise to sharp transparency window known as electromagnetically induced transparency (EIT). In the three-level system,

Zhun Fan, Jiajie Mo, Benzhang Qiu, Wenji Li

Retinal vessel segmentation is a crucial step in diagnosing and screening various diseases, including diabetes, ophthalmologic diseases, and cardiovascular diseases. In this paper, we propose an effective and efficient method for vessel segmentation in color fundus images using encoder-decoder based octave convolution networks. Compared with other convolutio

Marc Brockschmidt

This paper presents a new Graph Neural Network (GNN) type using feature-wise linear modulation (FiLM). Many standard GNN variants propagate information along the edges of a graph by computing "messages" based only on the representation of the source of each edge. In GNN-FiLM, the representation of the target node of an edge is additionally used to compute a

K. Laiho, M. Schmidt, H. Suchomel, M. Kamp

Due to their strict photon-number correlation, the twin beams produced in parametric down-conversion (PDC) work well for heralded state generation. Often, however, this state manipulation is distorted by the optical losses in the herald and by the higher photon-number contributions inevitable in the PDC process. In order to find feasible figures of merit for

Anna Krzyżewska, Anna Dyrdał

The anomalous Hall and Nernst effects are considered theoretically within Matsubara-Green's function formalism. The effective Hamiltonian of a magnetized two-dimensional electron gas with cubic Rashba spin-orbit interaction may describe transport properties of electronic states at the interfaces or surfaces of perovskite oxides or another type of heterostruc

Tomohiro Yamada

We shall show that there is no odd perfect number of the form $2^n+1$ or $n^n+1$.

Benny Avelin, Kaj Nyström

In this paper we prove that, in the deep limit, the stochastic gradient descent on a ResNet type deep neural network, where each layer shares the same weight matrix, converges to the stochastic gradient descent for a Neural ODE and that the corresponding value/loss functions converge. Our result gives, in the context of minimization by stochastic gradient de

Roy Barbara

We provide a method, using essentially elementary arithmetic, to solve the exponential diophantine equation 7x^2 + 59y^2 = 3^m, which leads to a simple algorithm, with no use of radicals or complex numbers, that generates all the (infinitely many) primitive and positive solutions of this equation. The method can be generalized to solve a class of exponential

Dominik Janzing

I argue that regularizing terms in standard regression methods not only help against overfitting finite data, but sometimes also yield better causal models in the infinite sample regime. I first consider a multi-dimensional variable linearly influencing a target variable with some multi-dimensional unobserved common cause, where the confounding effect can be

Torsten Neubert, Nikolai Østgaard, Victor Reglero, Elisabeth Blanc

The Atmosphere-Space Interactions Monitor (ASIM) is an instrument suite on the International Space Station (ISS) for measurements of lightning, Transient Luminous Events (TLEs) and Terrestrial Gamma-ray Flashes (TGFs). Developed in the framework of the European Space Agency (ESA), it was launched April 2, 2018 on the SpaceX CRS-14 flight to the ISS. ASIM was

Tomoyuki Tanaka, Kaito Hagiwara, Enrico Gazzola, Takashi Sudo

Natural gadolinium is widely used for its excellent thermal neutron capture cross section, because of its two major isotopes: $^{\rm 155}$Gd and $^{\rm 157}$Gd. We measured the $\gamma$-ray spectra produced from the thermal neutron capture on targets comprising a natural gadolinium film and enriched $^{\rm 155}$Gd (in Gd$_{2}$O$_{3}$ powder) in the energy ra

R. E. Hibbins, P. J. Espy, Y. J. Orsolini, V. Limpasuvan

Using meteor wind data from the Super Dual Auroral Radar Network (SuperDARN) in the Northern Hemisphere, we (1) demonstrate that the migrating (Sun-synchronous) tides can be separated from the nonmigrating components in the mesosphere and lower thermosphere (MLT) region and (2) use this to determine the response of the different components of the semidiurnal

Matthias Kübel, Georgios P. Katsoulis, Zack Dube, Andrei Yu Naumov

Double ionization in intense laser fields can comprise electron correlations, which manifest in the non-independent emission of two electrons from an atom or molecule. However, experimental methods that directly access the electron emission times have been scarce. Here, we explore the application of an all-optical streaking technique to strong-field double i

A. Korochkin, A. Neronov, D. Semikoz

Cumulative optical and infrared emission from galaxies accumulated over cosmological time scales, the extragalactic background light (EBL), could be probed by complementary techniques of direct observations and source counting in the visible and infrared as well as via its imprint on the signal of distant active galactic nuclei in gamma rays. We compare the

Larissa T. Triess, David Peter, Christoph B. Rist, Markus Enzweiler

This paper presents a novel CNN-based approach for synthesizing high-resolution LiDAR point cloud data. Our approach generates semantically and perceptually realistic results with guidance from specialized loss-functions. First, we utilize a modified per-point loss that addresses missing LiDAR point measurements. Second, we align the quality of our generated

Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song

Action localization in untrimmed videos is an important topic in the field of video understanding. However, existing action localization methods are restricted to a pre-defined set of actions and cannot localize unseen activities. Thus, we consider a new task to localize unseen activities in videos via image queries, named Image-Based Activity Localization.

Boris Solomyak

We prove that, after removing a zero Hausdorff dimension exceptional set of parameters, all self-similar measures on the line have a power decay of the Fourier transform at infinity. In the homogeneous case, when all contraction ratios are equal, this is essentially due to Erd\H{o}s and Kahane. In the non-homogeneous case the difficulty we have to overcome i

Konstantin Beyer, Kimmo Luoma, Walter T. Strunz

We address the question of verifying the quantumness of thermal machines. A Szil\'ard engine is truly quantum if its work output cannot be described by a local hidden state (LHS) model, i. e. an objective local statistical ensemble. Quantumness in this scenario is revealed by a steering-type inequality which bounds the classically extractable work. A quantum

Vladislav V. Kabanov, Leonid Shalaginov

We present a construction that gives an infinite series of divisible design graphs which are Cayley graphs.

Mattia Mina, David F. Mota, Hans A. Winther

We present a new code, SCALAR, based on the high-resolution hydrodynamics and N-body code RAMSES, to solve the Schr\"odinger equation on adaptive refined meshes. The code is intended to be used to simulate axion or fuzzy dark matter models where the evolution of the dark matter component is determined by a coupled Schr\"odinger-Poisson equation, but it can a

Julie Bu Daher, Armelle Brun, Anne Boyer

The goals of Learning Analytics (LA) are manifold, among which helping students to understand their academic progress and improving their learning process, which are at the core of our work. To reach this goal, LA relies on educational data: students' traces of activities on VLE, or academic, socio-demographic information, information about teachers, pedagog

Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song

Open-ended video question answering aims to automatically generate the natural-language answer from referenced video contents according to the given question. Currently, most existing approaches focus on short-form video question answering with multi-modal recurrent encoder-decoder networks. Although these works have achieved promising performance, they may

Ifan Johnston, Vassili Kolokoltsov

We look at estimates for the Green's function of time-fractional evolution equations of the form $D^{\nu}_{0+*} u = Lu$, where $D^{\nu}_{0+*}$ is a Caputo-type time-fractional derivative, depending on a L\'evy kernel $\nu$ with variable coefficients, which is comparable to $y^{-1-\beta}$ for $\beta \in (0, 1)$, and $L$ is an operator acting on the spatial va

Janne P. Tamminen

We present a simple, analytic point source model for both static and time-varying point-like heat sources and the resulting temperature profile that solves the heat equation in dimension three. Simple algorithms to detect the location and spectral content of these sources are developed and numerically tested using Finite Element Mesh simulations. The resulti

Dmytro Kutnyakhov, Rui Patrick Xian, Maciej Dendzik, Michael Heber

Time-resolved photoemission with ultrafast pump and probe pulses is an emerging technique with wide application potential. Real-time recording of non-equilibrium electronic processes, transient states in chemical reactions or the interplay of electronic and structural dynamics offers fascinating opportunities for future research. Combining valence-band and c