November 2018 arXiv papers — page 55

Hui-Yun Cao, Hai-Qing Zhou

In this work, the non-relativistic asymptotic behavior of the transition $q\overline{q}\rightarrow2g\rightarrow q\overline{q}$ in the $^1S_0$ channel is discussed. Different with the usual calculation which expands the physical amplitude around the quark anti-quark threshold, we take the quark anti-quark pairs as off shell and only expand the expression on t

Markus Ahlers

The field of high-energy neutrino astronomy is undergoing a rapid evolution. After the discovery of a diffuse flux of astrophysical TeV-PeV neutrinos in 2013, the IceCube observatory has recently found first compelling evidence for neutrino emission from blazars. In this brief review, I will summarize the status of these neutrino observations and highlight t

Louis Gallagher, John B. McDonald

In this paper, we present a new system for live collaborative dense surface reconstruction. Cooperative robotics, multi participant augmented reality and human-robot interaction are all examples of situations where collaborative mapping can be leveraged for greater agent autonomy. Our system builds on ElasticFusion to allow a number of cameras starting with

Lili Yao, Ruijian Xu, Chao Li, Dongyan Zhao

To build an open-domain multi-turn conversation system is one of the most interesting and challenging tasks in Artificial Intelligence. Many research efforts have been dedicated to building such dialogue systems, yet few shed light on modeling the conversation flow in an ongoing dialogue. Besides, it is common for people to talk about highly relevant aspects

Pavel Ostyakov, Roman Suvorov, Elizaveta Logacheva, Oleg Khomenko

We present a novel approach to image manipulation and understanding by simultaneously learning to segment object masks, paste objects to another background image, and remove them from original images. For this purpose, we develop a novel generative model for compositional image generation, SEIGAN (Segment-Enhance-Inpaint Generative Adversarial Network), whic

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek, Jan "Honza" Cernocky

In this work, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker verification (SV) system. We start our approach by carefully designing a data augmentation process to cover wide range of acoustic conditions and obtain rich training data for various components of

Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg

While recent years have witnessed astonishing improvements in visual tracking robustness, the advancements in tracking accuracy have been limited. As the focus has been directed towards the development of powerful classifiers, the problem of accurate target state estimation has been largely overlooked. In fact, most trackers resort to a simple multi-scale se

Samuel Murray, Hedvig Kjellström

We present the Mixed Likelihood Gaussian process latent variable model (GP-LVM), capable of modeling data with attributes of different types. The standard formulation of GP-LVM assumes that each observation is drawn from a Gaussian distribution, which makes the model unsuited for data with e.g. categorical or nominal attributes. Our model, for which we use a

Xiao-Bo Jin, Kai-Zhu Huang, Jianyu Miao

In this paper, an adversarial erasing embedding network with the guidance of high-order attributes (AEEN-HOA) is proposed for going further to solve the challenging ZSL/GZSL task. AEEN-HOA consists of two branches, i.e., the upper stream is capable of erasing some initially discovered regions, then the high-order attribute supervision is incorporated to char

Max-Olivier Hongler

The collective behaviour of stochastic multi-agents swarms driven by Gaussian and non-Gaussian environments is analytically discussed in a mean-field approach. We first exogenously implement long range mutual interactions rules with strengths that are modulated by the real-time distance separating each agent with the swarm barycentre. Depending on the form o

Spyridon J. Hatjispyros, Christos Merkatas

We propose a Bayesian nonparametric model based on Markov Chain Monte Carlo (MCMC) methods for the joint reconstruction and prediction of discrete time stochastic dynamical systems, based on $m$-multiple time-series data, perturbed by additive dynamical noise. We introduce the Pairwise Dependent Geometric Stick-Breaking Reconstruction (PD-GSBR) model, which

Niccolo Anceschi, Jorge Hidalgo, Tommaso Bellini, Amos Maritan

The evolutionary and ecological processes behind the origin of species are among the most fundamental problems in biology. In fact, many theoretical hypothesis on different type of speciation have been proposed. In particular, models of sympatric speciation leading to the formation of new species without geographical isolation, are based on the niche hypothe

V. P. Goncalves

Although the Odderon is an unambiguous prediction of Quantum Chromodynamics, its existence still was not confirmed experimentally. One of the processes where the Odderon contribution is expected to be dominant is the diffractive photoproduction of tensor mesons. In this paper we study the diffractive $f_2(1270)$ photoproduction in $pA$ collisions at LHC and

Annalisa Cesaroni, Serena Dipierro, Matteo Novaga, Enrico Valdinoci

We consider an energy functional combining the square of the local oscillation of a one--dimensional function with a double well potential. We establish the existence of minimal heteroclinic solutions connecting the two wells of the potential. This existence result cannot be accomplished by standard methods, due to the lack of compactness properties. In addi

Aram Karakhanyan

In this paper we classify the nonnegative global minimizers of the functional \[ J_F(u)=\int_\Omega F(|\nabla u|^2)+\lambda^2\chi_{\{u>0\}}, \] where $F$ satisfies some structural conditions and $\chi_D$ is the characteristic function of a set $D\subset \mathbb R^n$. We compute the second variation of the energy and study the properties of the stability oper

Jian Xu, Chunheng Wang, Cunzhao Shi, Baihua Xiao

In recent year, the compact representations based on activations of Convolutional Neural Network (CNN) achieve remarkable performance in image retrieval. However, retrieval of some interested object that only takes up a small part of the whole image is still a challenging problem. Therefore, it is significant to extract the discriminative representations tha

Xibiao Ren, Jichen Dong, Peng Yang, Jidong Li

Large-area two-dimensional (2D) materials for technical applications can now be produced by chemical vapor deposition (CVD). Unfortunately, grain boundaries (GBs) are ubiquitously introduced as a result of the coalescence of grains with different crystallographic orientations. It is well known that the properties of materials largely depend on GB structures.

Myeonggi Kwon, Kai Zehmisch

We introduce the concept of fittings to symplectic fillings of the unit cotangent bundle of odd-dimensional spheres. Assuming symplectic asphericity we show that all fittings are diffeomorphic to the respective unit co-disc bundle.

Stiphen Chowdhury, Renato Cordeiro de Amorim

Density-based clustering is the task of discovering high-density regions of entities (clusters) that are separated from each other by contiguous regions of low-density. DBSCAN is, arguably, the most popular density-based clustering algorithm. However, its cluster recovery capabilities depend on the combination of the two parameters. In this paper we present

Edinah K. Gnang

We prove via a composition lemma, the Kotzig-Ringel-Rosa conjecture, better known as the Graceful Labeling Conjecture. We also prove via a stronger version of the composition lemma a stronger form of the Graceful Labeling Conjecture.

Hagop Sazdjian

Tetraquark properties are examined in the limit of large $N_c$ of color in QCD. The qualitative differences between molecular and compact tetraquarks are outlined. Consequences of the possible existence of compact tetraquarks are analyzed and shown to lead to upper bounds in the $N_c$-behavior of their decay widths. Open questions on theoretical grounds, rel

Bharath Srinivas Prabakaran, Mihika Dave, Florian Kriebel, Semeen Rehman

Reliability has emerged as a key topic of interest for researchers around the world to detect and/or mitigate the side effects of decreasing transistor sizes, such as soft errors. Traditional solutions, like DMR and TMR, incur significant area and power overheads, which might not always be applicable due to power restrictions. Therefore, we investigate alter

Xilin Zhang, Kenneth M. Nollett, Daniel R. Phillips

We use the next-to-leading-order (NLO) amplitude in an effective field theory (EFT) for ${}^3$He + ${}^4$He $\rightarrow {}^7$Be + $\gamma$ to perform the extrapolation of higher-energy data to solar energies. At this order the EFT describes the capture process using an s-wave scattering length and effective range, the asymptotic behavior of $^7$Be and its e

Sambaran Bandyopadhyay, Lokesh N, M. N. Murty

Attributed network embedding has received much interest from the research community as most of the networks come with some content in each node, which is also known as node attributes. Existing attributed network approaches work well when the network is consistent in structure and attributes, and nodes behave as expected. But real world networks often have a

Mingzhe Guo, Tom Van Doorsselaere, Kostas Karampelas, Bo Li

Recent numerical studies revealed that transverse motions of coronal loops can induce the Kelvin-Helmholtz Instability (KHI). This process could be important in coronal heating because it leads to dissipation of energy at small spatial-scale plasma interactions. Meanwhile, small amplitude decayless oscillations in coronal loops have been discovered recently

Juhee Hong, Su Houng Lee

For weakly bound quarkonia, we rederive the next-to-leading order cross sections of quarkonium dissociation by partons that include the hard thermal loop (HTL) resummation. Our results calculated with an effective vertex from the Bethe-Salpeter amplitude reduce to those obtained by potential nonrelativistic QCD (pNRQCD) in the relevant kinematical limit, and

A. Deb Ray, Atanu Mondal

This paper introduces the ring of all real valued Baire one functions, denoted by $B_1(X)$ and also the ring of all real valued bounded Baire one functions, denoted by $B_1^*(X)$. Though the resemblance between $C(X)$ and $B_1(X)$ is the focal theme of this paper, it is observed that unlike $C(X)$ and $C^*(X)$ (real valued bounded continuous functions), $B_1

Maciej Zamorski, Maciej Zięba, Piotr Klukowski, Rafał Nowak

Deep generative architectures provide a way to model not only images but also complex, 3-dimensional objects, such as point clouds. In this work, we present a novel method to obtain meaningful representations of 3D shapes that can be used for challenging tasks including 3D points generation, reconstruction, compression, and clustering. Contrary to existing m

Philipp Kurpiers, Marek Pechal, Baptiste Royer, Paul Magnard

Heralding techniques are useful in quantum communication to circumvent losses without resorting to error correction schemes or quantum repeaters. Such techniques are realized, for example, by monitoring for photon loss at the receiving end of the quantum link while not disturbing the transmitted quantum state. We describe and experimentally benchmark a schem

Ishwarya M S, Aswani Kumar Ch

In this paper, we propose a cognitive system that acquires knowledge on elderly daily activities to ensure their wellness in a smart home using a Knowledge-Information-Data (KID) model. The novel cognitive framework called high dimensional conceptual space is proposed and used as KID model. This KID model is built using geometrical framework of conceptual sp

N. V. Antonov, P. I. Kakin, N. M. Lebedev

The effects of a randomly moving environment on a randomly growing interface are studied by the field theoretic renormalization group analysis. The kinetic growth of an interface (kinetic roughening) is described by the Kardar-Parisi-Zhang stochastic differential equation while the velocity field of the moving medium is modelled by the Navier-Stokes equation

Edwin J Beggs

We study geodesics in noncommutative geometry by means of bimodule connections and completely positive maps using the Kasparov, Stinespring, Gel'fand, Naimark & Segal (KSGNS) construction. This is motivated from classical geometry, and we also consider examples on the algebras M_2(C) and C(Z_n), though restricting to classical real time. On the way we have t

Parag Agrawal, Anshuman Suri, Tulasi Menon

Most often, chat-bots are built to solve the purpose of a search engine or a human assistant: Their primary goal is to provide information to the user or help them complete a task. However, these chat-bots are incapable of responding to unscripted queries like "Hi, what's up", "What's your favourite food". Human evaluation judgments show that 4 humans come t

Anatoly Konechny

Critical 2D Ising model with a boundary magnetic field is arguably the simplest QFT that interpolates between two non-trivial fixed points. We use the diagonalising Bogolyubov transformation for this model to investigate two quantities. Firstly we explicitly construct an RG interface operator that is a boundary condition changing operator linking the free bo

Xu Lan, Xiatian Zhu, Shaogang Gong

Knowledge distillation is an effective approach to transferring knowledge from a teacher neural network to a student target network for satisfying the low-memory and fast running requirements in practice use. Whilst being able to create stronger target networks compared to the vanilla non-teacher based learning strategy, this scheme needs to train additional

Rémi Carles, Clément Gallo

We justify the WKB analysis for generalized nonlinear Schr{\"o}dinger equations (NLS), including the hyperbolic NLS and the Davey-Stewartson II system. Since the leading order system in this analysis is not hyperbolic, we work with analytic regularity, with a radius of analyticity decaying with time, in order to obtain better energy estimates. This provides

S. Yamada, N. Abe, H. Sagayama, K. Ogawa

The gigantic decrease of resistance by an applied magnetic field, which is often referred to as colossal magnetoresistance (CMR), has been an attracting phenomenon in strongly correlated electron systems. The discovery of CMR in manganese oxide compounds has developed the science of strong coupling among charge, orbital, and spin degrees of freedom. CMR is a

John Coates, Yongxiong Li

The paper uses Iwasawa theory at the prime $p=2$ to prove non-vanishing theorems for the value at $s=1$ of the complex $L$-series of certain quadratic twists of the Gross family of elliptic curves with complex multiplication by the field $K = \BQ(\sqrt{-q})$, where $q$ is any prime $\equiv 7 \mod 8$. Our results establish some broad generalizations of the no

J. Olivares-Sánchez, J. Casanova, E. Solano, L. Lamata

We present an experimental realization of a measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti cloud quantum computer. The experiment in this few-qubit superconducting chip faithfully reproduces the theoretical proposal, setting the first steps towards a semiautonomous quantum agent. This experiment paves the way towards q

Lorenzo Luzzi, Paolo Roselli

In this work we develop the mathematical framework of !FTL, a new gesture recognition algorithm and we prove its convergence. Such convergence suggests to adopt a notion of shape for smooth gestures as a complex valued function. However, the idea inspiring that notion came to us from Clifford numbers and not from complex numbers. Moreover, the Clifford vecto

Giulio Bondanelli, Srdjan Ostojic

Following a stimulus, the neural response typically strongly varies in time and across neurons before settling to a steady-state. While classical population coding theory disregards the temporal dimension, recent works have argued that trajectories of transient activity can be particularly informative about stimulus identity and may form the basis of computa

Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

Learning a deep neural network requires solving a challenging optimization problem: it is a high-dimensional, non-convex and non-smooth minimization problem with a large number of terms. The current practice in neural network optimization is to rely on the stochastic gradient descent (SGD) algorithm or its adaptive variants. However, SGD requires a hand-desi

Jorge Segovia, Sebastian Steinbeißer, Antonio Vairo

We compute the electric dipole transitions $\chi_{bJ}(1P)\to \gamma\Upsilon(1S)$, with $J=0,1,2$, and $h_{b}(1P)\to \gamma\eta_{b}(1S)$ in a model-independent way. We use potential non-relativistic QCD (pNRQCD) at weak coupling with either the Coulomb potential or the complete static potential incorporated in the leading order Hamiltonian. In the last case,

Katarzyna Siudzińska, Dariusz Chruściński

We analyze the fidelity of the generalized Pauli channels governed by memory kernel master equations. It is shown that, by appropriate engineering of parameters of the corresponding memory kernel, the quantum evolution with non-local noise can have higher fidelity than the corresponding purely Markovian evolution governed by the Markovian semigroup. Similar

Andrés Viña

Considering the $D$-branes on a variety $Z$ as the objects of the derived category $D^b(Z)$, we propose a definition for the charge of $D$-branes on not necessarily smooth varieties. We define the charge $Q({\mathcal G})$ of ${\mathcal G}\in D^b(Z)$ as an element of the homology of $Z$, so that the mapping $Q$ is compatible with the pushforward by proper map

Daniel Azagra, Tadeusz Dobrowolski, Miguel García-Bravo

Let $E$, $F$ be separable Hilbert spaces, and assume that $E$ is infinite-dimensional. We show that for every continuous mapping $f:E\to F$ and every continuous function $\varepsilon: E\to (0, \infty)$ there exists a $C^{\infty}$ mapping $g:E\to F$ such that $\|f(x)-g(x)\|\leq\varepsilon(x)$ and $Dg(x):E\to F$ is a surjective linear operator for every $x\in

Eric Aristidi, Jean Vernin, Eric Fossat, F. -X. Schmider

The optical turbulence above Dome C in winter is mainly concentrated in the first tens of meters above the ground. Properties of this so-called surface layer (SL) were investigated during the period 2007-2012 by a set of sonics anemometers placed on a 45 m high tower. We present the results of this long-term monitoring of the refractive index structure const

Thierry Gallay, Didier Smets

We investigate the linear stability of inviscid columnar vortices with respect to finite energy perturbations. For a large class of vortex profiles, we show that the linearized evolution group has a sub-exponential growth in time, which means that the associated growth bound is equal to zero. This implies in particular that the spectrum of the linearized ope

Jaime Spencer, Oscar Mendez, Richard Bowden, Simon Hadfield

How many times does a human have to drive through the same area to become familiar with it? To begin with, we might first build a mental model of our surroundings. Upon revisiting this area, we can use this model to extrapolate to new unseen locations and imagine their appearance. Based on this, we propose an approach where an agent is capable of modelling n

Darius A. Faroughy

We discuss the physics case for direct searches at the LHC motivated by the $B$-physics anomalies. After correlating semi-tauonic $B$ decays to di-tau production at the LHC, and discussing the possible models solving the $B$-anomalies, we show how current LHC data in $\tau\bar\tau$ tails exclude most beyond the SM scenarios except for a handful of leptoquark

Iva Halacheva, Allen Knutson, Paul Zinn-Justin

Given a Schubert class on $Gr(k,V)$ where $V$ is a symplectic vector space of dimension $2n$, we consider its restriction to the symplectic Grassmannian $SpGr(k,V)$ of isotropic subspaces. Pragacz gave tableau formulae for positively computing the expansion of these $H^*(Gr(k,V))$ classes into Schubert classes of the target when $k=n$, which corresponds to e

Qiang Zou, Juyong Zhang, Bailin Deng, Jibin Zhao

The aim of tool path planning is to maximize the efficiency against some given precision criteria. In practice, scallop height should be kept constant to avoid unnecessary cutting, while the tool path should be smooth enough to maintain a high feed rate. However, iso-scallop and smoothness often conflict with each other. Existing methods smooth iso-scallop p

Yonatan Geifman, Ran El-Yaniv

We consider active learning of deep neural networks. Most active learning works in this context have focused on studying effective querying mechanisms and assumed that an appropriate network architecture is a priori known for the problem at hand. We challenge this assumption and propose a novel active strategy whereby the learning algorithm searches for effe

Qing Guo, Hua Wang, Xiaohua Yao

In this paper, we consider a 3d cubic focusing nonlinear Schr\"odinger equation (NLS) with slowing decaying potentials. Adopting the variational method of Ibrahim-Masmoudi-Nakanishi \cite{IMN}, we obtain a condition for scattering. It is actually sharp in some sense since the solution will blow up if it's false. The proof of blow-up part relies on the method

Magdalena Brunner, Marko Mecina, Matthias Maercker, Ernst A. Dorfi

Aims. The carbon-rich asymptotic giant branch (AGB) star TX Piscium (TX Psc) has been observed multiple times during multiple epochs and at different wavelengths and resolutions, showing a complex molecular CO line profile and a ring-like structure in thermal dust emission. We investigate the molecular counterpart in high resolution, aiming to resolve the ri

Gaetano Calogero, Nick R. Papior, Bernhard Kretz, Aran Garcia-Lekue

Designing platforms to control phase-coherence and interference of electron waves is a cornerstone for future quantum electronics, computing or sensing. Nanoporous graphene (NPG) consisting of linked graphene nanoribbons has recently been fabricated using molecular precursors and bottom-up assembly [Moreno et al., Science 360, 199 (2018)] opening an avenue f

Alberto Eljarrat, Christoph T. Koch

Low-loss electron energy loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) probes the valence electron density and relevant optoelectronic properties such as band gap energies and other band structure transitions. The measured spectra can be formulated in a dielectric theory framework, comparable to optical spectroscopies and a

Michal Kozlowski, Ryan McConville, Raul Santos-Rodriguez, Robert Piechocki

As sensor networks for health monitoring become more prevalent, so will the need to control their usage and consumption of energy. This paper presents a method which leverages the algorithm's performance and energy consumption. By utilising Reinforcement Learning (RL) techniques, we provide an adaptive framework, which continuously performs weak training in

Yongbo Li, Honggang Chen, Mingzhong Wang, Longxuan Xu

On the basis of the idea that the injecting energy will improve the conditions for the formation of Cooper pairs, a smart meta-superconductor (SMSC) was prepared by doping inhomogeneous phase of luminescent nanocomposite Y2O3:Eu3+/Ag, which has the strong luminescence characteristic, in MgB2 to improve the superconducting transition temperature (TC) of the M

Pranav Madhikar, Jan Åström, Björn Baumeier, Mikko Karttunen

We investigate morphologies of proliferating cellular tissue using a newly developed numerical simulation model for mechanical cell division. The model reproduces structures of simple multi-cellular organisms via simple rules for selective division and division plane orientation. The model is applied to a bimodal mixture of stiff cells with a low growth pote

Loïc Foissy

Typed decorated trees are used by Bruned, Hairer and Zambotti to give a description of a renormalisation processon stochastic PDEs. We here study the algebraic structures on these objects: multiple prelie algebrasand related operads (generalizing a result by Chapoton and Livernet), noncommutative and cocommutative Hopf algebras (generalizing Grossman and Lar

Kento Asai, Koichi Hamaguchi, Natsumi Nagata, Shih-Yen Tseng

It is well known that the differences between the lepton numbers can be gauged with the Standard Model matter content. Such extended gauge theories, dubbed as the gauged U(1)$_{L_\alpha - L_\beta}$ models, have been widely discussed so far as potential candidates for physics beyond the Standard Model. In this work, we study the minimal versions of these gaug

Daniele Bartoli, Maria Montanucci, Giovanni Zini

In this article we explicitly determine the structure of the Weierstrass semigroups $H(P)$ for any point $P$ of the Suzuki curve $\mathcal{S}_q$. As the point $P$ varies, exactly two possibilities arise for $H(P)$: one for the $\mathbb{F}_q$-rational points (already known in the literature), and one for all remaining points. For this last case a minimal set

P D Sacramento

The image of a Majorana mode located on the focus of an elliptical corral of free electrons is studied. The Majorana mode may be taken at the edge of a topological wire superimposed on the two-dimensional electron gas. At low energies the states of the wire are ignored except for the Majorana mode. Usual tunneling to a fermionic mode is compared. In the favo

Ivar Ekeland, Eric Séré

In this paper we introduce a new algorithm for solving perturbed nonlinear functional equations which admit a right-invertible linearization, but with an inverse that loses derivatives and may blow up when the perturbation parameter $\epsilon$ goes to zero. These equations are of the form $F_\epsilon(u)=v$ with $F_\epsilon(0)=0$, $v$ small and given, $u$ sma

Li Niu, Ashok Veeraraghavan, Ashu Sabharwal

Fine-grained classification remains a very challenging problem, because of the absence of well-labeled training data caused by the high cost of annotating a large number of fine-grained categories. In the extreme case, given a set of test categories without any well-labeled training data, the majority of existing works can be grouped into the following two r

J. L. Wu, S. L. Su

Universal speeded-up adiabatic geometric quantum computation~(SAGQC) is studied in $\Lambda$-type three-level system with different coupling cases, i.e., time-dependent detuning, large detuning and one-photon resonance couplings, respectively. In these cases, the counterdiabatic driving method is used to speed up the universal quantum computation. These sche

Amandine Pierrot

In this paper, we introduce a family of hyper-elliptic curves. For this family we compute the matrix of the divided Frobenius and we obtain general formulas. We use a recent results of Huyghe-Wach : the divided Frobenius coincides with the morphism built by Deligne-Illusie in 1987.

Nazife Ozdes Koca, Abeer Al-Siyabi, Mehmet Koca, Ramazan Koc

We exploit the fact that two-dimensional facets of the Voronoi and Delone cells of the root lattice A_n in n-dimensional space are the identical rhombuses and equilateral triangles respectively.The prototiles obtained from orthogonal projections of the Voronoi and Delaunay (Delone) cells of the root lattice of the Coxeter-Weyl group W(a)_n are classified. Or

Vincent Calvez, Laurent Gosse, Monika Twarogowska

The existence of travelling waves for a coupled system of hyperbolic/ parabolic equations is established in the case of a finite number of velocities in the kinetic equation. This finds application in collective motion of chemotactic bacteria. The analysis builds on the previous work by the first author (arXiv:1607.00429) in the case of a continuum of veloci

Julien Brémont

We study Markov chains on a lattice in a codimension-one stratified independent random environment, exploiting results established in [2]. First of all the random walk is transient in dimension at least three. Focusing on dimension two, both recurrence and transience can happen, but transience remains by far the most general situation. We identify the critic

Eric Aristidi, Yan Fantei-Caujolle, Aziz Ziad, Cécile Dimur

We present first results of a new instrument, the Generalized Differential Image Motion Monitor (GDIMM), aiming at monitoring parameters of the optical turbulence (seeing, isoplanatic angle, coherence time and outer scale). GDIMM is based on a small telescope equipped with a 3-holes mask at its entrance pupil. The seeing is measured by the classical DIMM tec

Johannes Polster, Julian Petrasch, Randolf Menzel, Tim Landgraf

Over the last decades, honeybees have been a fascinating model to study insect navigation. While there is some controversy about the complexity of underlying neural correlates, the research of honeybee navigation makes progress through both the analysis of flight behavior and the synthesis of agent models. Since visual cues are believed to play a crucial rol

Haohua Wen, Jianyi Liu, Yifeng Wu, Kan Lai

Helium diffusion in metals is the basic requirement of nucleation and growth of bubble, which gives rise to adverse degradation effects on mechanical properties of structural materials in reactors under irradiation. Multi-scale modeling scheme has been developed to study effects of helium on the long-term microstructural evolution. However, the implementatio

Andreas Ott

We develop an algebro-analytic framework for the systematic study of the continuous bounded cohomology of Lie groups in large degree. As an application, we examine the continuous bounded cohomology of PSL(2,R) with trivial real coefficients in all degrees greater than two. We prove a vanishing result for strongly reducible classes, thus providing further evi

Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes. However, this decomposition can fall short in the finite bit-length regime, as it requires non-trivial tuning of hand-crafted codes and assumes infinite compu

Hang Zhou, Bo Zheng, Zhen-Hua Zhang

We study the $\mathit{CP}$ violation induced by the interference between two intermediate resonances $K^*(892)^+$ and $K^*(892)^-$ in the phase space of singly-Cabibbo-suppressed decay $D^0 \to K^+K^-\pi^0$. We adopt the factorization-assisted topological approach in dealing with the decay amplitudes of $D^0 \to K^\pm K^*(892)^\mp$. The $\mathit{CP}$ asymmet

Yuxin Zhang, Huan Wang, Yang Luo, Lu Yu

Despite enjoying extensive applications in video analysis, three-dimensional convolutional neural networks (3D CNNs)are restricted by their massive computation and storage consumption. To solve this problem, we propose a threedimensional regularization-based neural network pruning method to assign different regularization parameters to different weight group

Bhaswar B. Bhattacharya, Shirshendu Ganguly

The upper tail problem for the largest eigenvalue of the Erd\H{o}s--R\'enyi random graph $\mathcal{G}_{n,p}$ is to estimate the probability that the largest eigenvalue of the adjacency matrix of $\mathcal{G}_{n,p}$ exceeds its typical value by a factor of $1+\delta$. In this note we show that for $\delta >0$ fixed, and $p \rightarrow 0$ such that $n^{\frac{1

Dong Yang

This short note surveys the constructions of 3-Calabi--Yau triangulated categories with simple-minded collections due to Ginzburg and Kontsevich--Soibelman and the constructions of 2-Calabi--Yau triangulated categories with cluster-tilting objects due to Buan--Marsh--Reineke--Reiten--Todorov and Amiot, and includes a discussion on the normal form of 2-Calabi

Nosheen Akbar, M. Atif Sultan, Bilal Masud, Faisal Akram

Using our analytical expressions that well model the lattice simulations of the gluonic excitations, we use the extended quark potential model to study the effects of orbital and radial excitations on the masses and sizes of conventional and hybrid $B_c$ mesons. A non relativistic formalism is used to numerically calculate the wave functions using the shooti

S. Recchia, S. Gabici, F. A. Aharonian, J. Vink

The total cosmic ray electron spectrum (electrons plus positrons) exhibits a break at a particle energy of $\sim 1\rm~TeV$ and extends without any attenuation up to $\rm \sim 20~ TeV $. Synchrotron and inverse Compton energy losses strongly constrain both the age and the distance of the potential sources of TeV and multi-TeV electrons to $\rm\approx 10^5~yr$

Yuexin Wu, Xiujun Li, Jingjing Liu, Jianfeng Gao

Training task-completion dialogue agents with reinforcement learning usually requires a large number of real user experiences. The Dyna-Q algorithm extends Q-learning by integrating a world model, and thus can effectively boost training efficiency using simulated experiences generated by the world model. The effectiveness of Dyna-Q, however, depends on the q

Pyeongjae Park, Joosung Oh, Klára Uhlířová, Jerome Jackson

$\mathsf{Mn_{3}Sn}$ has recently attracted considerable attention as a magnetic Weyl semimetal exhibiting concomitant transport anomalies at room temperature. The topology of the electronic bands, their relation to the magnetic ground state and their nonzero Berry curvature lie at the heart of the problem. The examination of the full magnetic Hamiltonian rev

Yuanliu Liu, Bo Peng, Peipei Shi, He Yan

Person identification in the wild is very challenging due to great variation in poses, face quality, clothes, makeup and so on. Traditional research, such as face recognition, person re-identification, and speaker recognition, often focuses on a single modal of information, which is inadequate to handle all the situations in practice. Multi-modal person iden

Ting-Hao Hsu, Gail S. K. Wolkowicz

We derive characteristic functions to determine the number and stability of relaxation oscillations for a class of planar systems. Applying our criterion, we give conditions under which the chemostat predator-prey system has a globally orbitally asymptotically stable limit cycle. Also we demonstrate that a prescribed number of relaxation oscillations can be

Sumit Shekhar, Aditya Siddhant, Anindya Shankar Bhandari, Nishant Yadav

There have been significant innovations in media technologies in the recent years. While these developments have improved experiences for individual users, design of multi-user interfaces still remains a challenge. A relatively unexplored area in this context, is enabling multiple users to enjoy shared viewing (e.g. deciding on movies to watch together). In

Takashi Goda, Tomohiko Hironaka, Takeru Iwamoto

The expected information gain is an important quality criterion of Bayesian experimental designs, which measures how much the information entropy about uncertain quantity of interest $\theta$ is reduced on average by collecting relevant data $Y$. However, estimating the expected information gain has been considered computationally challenging since it is def

Yunxiao Qin, Chenxu Zhao, Zezheng Wang, Junliang Xing

Deep learning based computer vision fails to work when labeled images are scarce. Recently, Meta learning algorithm has been confirmed as a promising way to improve the ability of learning from few images for computer vision. However, previous Meta learning approaches expose problems: 1) they ignored the importance of attention mechanism for the Meta learner

Jiawei Liu, Zheng-Jun Zha, Hongtao Xie, Zhiwei Xiong

Person re-identification aims to identify the same pedestrian across non-overlapping camera views. Deep learning techniques have been applied for person re-identification recently, towards learning representation of pedestrian appearance. This paper presents a novel Contextual-Attentional Attribute-Appearance Network (CA3Net) for person re-identification. Th

Stefano Zucca, Christian M. Firrone

Real applications in structural mechanics, where the dynamic behavior is linear, are rare. Usually, structures are made of components assembled together by means of joints whose behavior maybe highly nonlinear. Depending on the amount of excitation, joints can dramatically change the dynamic behavior of the whole system, and the modelling of this type of con

Jean Stawiaski

This article presents a convolutional neural network for the automatic segmentation of brain tumors in multimodal 3D MR images based on a U-net architecture.We evaluate the use of a densely connected convolutional network encoder (DenseNet) which was pretrained on the ImageNet data set. We detail two network architectures that can take into account multiple

Shintaro Nakamura, Antonio De Felice, Ryotaro Kase, Shinji Tsujikawa

The gravitational-wave event GW170817, together with the electromagnetic counterpart, shows that the speed of tensor perturbations $c_T$ on the cosmological background is very close to that of light $c$ for the redshift $z<0.009$. In generalized Proca theories, the Lagrangians compatible with the condition $c_T=c$ are constrained to be derivative interaction

Pascale Royer

Asymptotic multiple scale homogenisation allows to determine the effective behaviour of a porous medium by starting from the pore-scale description, when there is a large separation between the pore-scale and the macroscopic scale. When the scale ratio is "small but not too small," the standard approach based on first-order homogenisation may break down sinc

T. Shinbrot, B. Ferdowsi, S. Sundaresan, N. A. M. Araujo

Contact charging between insulators is one of the most basic, yet least well understood, of physical processes. For example we have no clear theory for how insulators recruit enough charge carriers to deposit charge but not enough to discharge. In this letter we note that charging and discharging kinetics may be distinct, and from this observation we develop

Saswati Dhara, Romesh K. Kaul, P. Ramadevi, Vivek Kumar Singh

Construction of representations of braid group generators from $N$-state vertex models provide an elegant route to study knot and link invariants. Using such a braid group representation, an algebraic formula for the link invariants was put forth when the same spin $(N-1)/2$ are placed on all the component knots. In this paper, we generalise the procedure to

Kentaro Kuga, Yuina Kanai, Hidenori Fujiwara, Kohei Yamagami

We have probed the crystalline electric-field ground states of pure $|J = 7/2, J_z = \pm 5/2\rangle$ as well as the anisotropic $c$-$f$ hybridization in both valence fluctuating systems $\alpha$- and $\beta$-YbAlB$_4$ by linear polarization dependence of angle-resolved core level photoemission spectroscopy. Interestingly, the small but distinct difference be

Constance Thierry, Jean-Christophe Dubois, Yolande Le Gall, Arnaud Martin

The crowdsourcing consists in the externalisation of tasks to a crowd of people remunerated to execute this ones. The crowd, usually diversified, can include users without qualification and/or motivation for the tasks. In this paper we will introduce a new method of user expertise modelization in the crowdsourcing platforms based on the theory of belief func

Chao Lu, Wei Xu, Hong Shen, Jun Zhu

In a multiple-input multiple-output (MIMO) system, the availability of channel state information (CSI) at the transmitter is essential for performance improvement. Recent convolutional neural network (NN) based techniques show competitive ability in realizing CSI compression and feedback. By introducing a new NN architecture, we enhance the accuracy of quant

Yuhang Liu, Wenyong Dong, Lei Zhang, Dong Gong

Variational dropout (VD) is a generalization of Gaussian dropout, which aims at inferring the posterior of network weights based on a log-uniform prior on them to learn these weights as well as dropout rate simultaneously. The log-uniform prior not only interprets the regularization capacity of Gaussian dropout in network training, but also underpins the inf