April 2019 arXiv papers — page 55

Harinder P. Singh, Susmita Das, Anupam Bhardwaj, Shashi Kanbur

We present results from a comparative study of light curves of Cepheid and RR Lyrae stars in the Galaxy and the Magellanic Clouds with their theoretical models generated from the stellar pulsation codes. Fourier decomposition method is used to analyse the theoretical and the observed light curves at multiple wavelengths. In case of RR Lyrae stars, the amplit

Emil Horozov

The subject of this paper is a connection between d-orthogonal polynomials and the Toda lattice hierarchy. In more details we consider some polynomial systems similar to Hermite polynomials, but satisfying $d+2$-term recurrence relation, $d >1$. Any such polynomial system defines a solution of the Toda lattice hierarchy. However we impose also the condition

Moreno Bonaventura, Valerio Ciotti, Pietro Panzarasa, Silvia Liverani

By drawing on large-scale online data we construct and analyze the time-varying worldwide network of professional relationships among start-ups. The nodes of this network represent companies, while the links model the flow of employees and the associated transfer of know-how across companies. We use network centrality measures to assess, at an early stage, t

Barnabas Porfy

One of the main goals of NA61/SHINE is the investigation of the phase diagram of strongly interacting matter. NA61/SHINE observes collisions of various nuclei at different energies, allowing to study the same phenomena and observables in vastly different conditions. One of the observables related to the quark-hadron transition is the Bose-Einstein momentum c

Zacharias M. Nikolaou, Charalambos Chrysostomou, Yuki Minamoto, Luc Vervisch

Data-driven methods for modelling purposes in fluid mechanics are a promising alternative given the continuous increase of both computational power and data-storage capabilities. Highly non-linear flows including turbulence and reaction are challenging to model, and accurate closures for the unresolved terms in large eddy simulations of such flows are diffic

Julian Stier, Gabriele Gianini, Michael Granitzer, Konstantin Ziegler

Artificial Neural Networks have shown impressive success in very different application cases. Choosing a proper network architecture is a critical decision for a network's success, usually done in a manual manner. As a straightforward strategy, large, mostly fully connected architectures are selected, thereby relying on a good optimization strategy to fi

Yuko Aoyanagi, Ko Okumura

Recently, it has been found experimentally that hydrated nacre exhibits a nonlinear mechanical response. While mechanical nonlinearity has been shown to be important in other biological structures, such as spider webs, the implications of mechanical nonlinearity in nacre have not been explored. Here, we show that the nonlinear mechanical response of nacre ca

Sandun Dasanayake, Sanja Aaramaa, Jouni Markkula, Markku Oivo

Requirements volatility is a major issue in software development, causing problems such as higher defect density, project delays and cost overruns. Software architecture that guides the overall vision of software product, is one of the areas that is greatly affected by requirements volatility. Since critical architecture decisions are made based on the requi

Evgeny A. Kochurin

A direct numerical simulation of the interaction of plane capillary waves on the surface of a liquid dielectric in an external tangential electric field taking into account viscous forces has been performed. It has been shown that the interaction of counter-propagating nonlinear waves can generate a direct energy cascade. In the quasistationary energy dissip

V. V. Bannikov, I. R. Shein

The comparative study of structural, electronic properties, topology of the Fermi surface, and the features of chemical bonding in layered 1111-oxyarsenides LaRhAsO and LaIrAsO has been performed based on the results of ab initio modeling of their electronic structure. It was established that only weak sensitivity with respect both to electron and hole dopin

Justin Le Louedec, Thomas Guntz, James Crowley, Dominique Vaufreydaz

This article reports on an investigation of the use of convolutional neural networks to predict the visual attention of chess players. The visual attention model described in this article has been created to generate saliency maps that capture hierarchical and spatial features of chessboard, in order to predict the probability fixation for individual pixels

Alexey S. Zhevlakov, Thomas Gutsche, Valery E. Lyubovitskij

We complete our derivation of upper limits on the CP violating $ηππ$ and $η'ππ$ couplings from an analysis of their two-loop contributions to the neutron electric dipole moment (nEDM). We use a phenomenological Lagrangian approach which is formulated in terms of hadronic degrees of freedom - nucleons and pseudoscalar mesons. The essential part of the Lag

Marc Paul Noordman, Marius van der Put, Jaap Top

The problem of algebraic dependence of solutions to (non-linear) first order autonomous equations over an algebraically closed field of characteristic zero is given a `complete' answer, obtained independently of model theoretic results on differentially closed fields. Instead, the geometry of curves and generalized Jacobians provides the key ingredient.

M. W. Healy, M. J. Darnley, C. M. Copperwheat, A. V. Filippenko

A transient in the Local Group dwarf irregular galaxy NGC 6822 (Barnard's Galaxy) was discovered on 2017 August 2 and is only the second classical nova discovered in that galaxy. We conducted optical, near-ultraviolet, and X-ray follow-up observations of the eruption, the results of which we present here. This 'very fast' nova had a peak $V$-band

Daniel Lokshtanov, Pranabendu Misra, Saket Saurabh, Meirav Zehavi

Let $G$ be a directed graph with $n$ vertices and $m$ edges, and let $s \in V(G)$ be a designated source vertex. We consider the problem of single source reachability (SSR) from $s$ in presence of failures of edges (or vertices). Formally, a spanning subgraph $H$ of $G$ is a {\em $k$-Fault Tolerant Reachability Subgraph ($k$-FTRS)} if it has the following pr

Akihiro Ozawa, Kentaro Nomura

We construct a two-orbital effective model for a ferromagnetic Kagome-lattice shandite, $\rm{{Co}_3{Sn}_2{S}_2}$, a candidate material of magnetic Weyl semimetals, by considering one $d$ orbital from Co, and one $p$ orbital from interlayer Sn. The energy spectrum near the Fermi level, and the configurations of the Weyl points, computed by using our model, ar

Huaibing Jian, Yuean Zhu, Yongchao Long, Bin Li

In recent year, the write-heavy applications is more and more prevalent. How to efficiently handle this sort of workload is one of intensive research direction in the field of database system. The overhead caused by write operation is mainly issued by two reasons: 1) the hardware level, i.e., the IO cost caused by logging. We can't remove this cost in sh

Tekin Dereli, Keremcan Doğan, Cem Yetişmişoğlu

In this work, the Kaluza-Klein reduction of the Dirac equation on a 6 dimensional spacetime $\mathbb{M}^{1+5} := \mathbb{M}^{1+2} \times \mathbb{S}^3$ is studied. Because of the group structure on $\mathbb{S}^3$, $\mathbb{M}^{1+5}$ can be seen as a principal $SU(2)$ bundle over the model Lorentzian spacetime $\mathbb{M}^{1+2}$. The dimensional reduction indu

Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe

Accurate prediction of drug-target interaction (DTI) is essential for in silico drug design. For the purpose, we propose a novel approach for predicting DTI using a GNN that directly incorporates the 3D structure of a protein-ligand complex. We also apply a distance-aware graph attention algorithm with gate augmentation to increase the performance of our mod

C. Gadea, Q. Hanniet, A. Lesch, D. Marani

Inkjet printing of 8% Y2O3-stabilized ZrO2 (YSZ) thin films is achieved by designing a novel water-based reactive ink for Drop-on-Demand (DoD) inkjet printing. The ink formulation is based on a novel chemical strategy that consists of a combination of metal oxide precursors (zirconium alkoxide and yttrium salt), water and a nucleophilic agent, i.e. n-methyld

V. A. Slipko, Y. V. Pershin

Some memristors are quite interesting from the point of view of dynamical systems. When driven by narrow pulses of alternating polarities, their dynamics has a stable fixed point, which may be useful for future applications. We study the transient dynamics of two types of memristors characterized by a stable fixed point using a time-averaged evolution equati

Shuangjie Xu, Daizong Liu, Linchao Bao, Wei Liu

We address the problem of semi-supervised video object segmentation (VOS), where the masks of objects of interests are given in the first frame of an input video. To deal with challenging cases where objects are occluded or missing, previous work relies on greedy data association strategies that make decisions for each frame individually. In this paper, we p

S. Molinari, A. Baldeschi, T. P. Robitaille, E. F. E. Morales

A grid of 20 millions 3-1100$μ$m SED models is presented for synthetic young clusters embedded in dense clumps. The models depend on four primary parameters: the clump mass M$_{clump}$ and dust temperature T$_{dust}$, the fraction of mass f$_{core}$ locked in dense cores, and the age of the clump t$_{SF}$. We populate the YSO clusters using the IMF from Krou

James R. Ashford, Liam D. Turner, Roger M. Whitaker, Alun Preece

Wikipedia serves as a good example of how editors collaborate to form and maintain an article. The relationship between editors, derived from their sequence of editing activity, results in a directed network structure called the revision network, that potentially holds valuable insights into editing activity. In this paper we create revision networks to asse

Friederike U. J. Klauck, Lucas Teuber, Marco Ornigotti, Matthias Heinrich

Parity-Time (PT) symmetric quantum mechanics is a complex extension of conventional Hermitian quantum mechanics in which physical observables possess a real eigenvalue spectrum. However, an experimental demonstration of the true quantum nature of PT symmetry has been elusive thus far, as only single-particle physics has been exploited to date. In our work, w

Aurélien Drezet

We review several no-go theorems attributed to Gisin and Hardy, Conway and Kochen purporting the impossibility of Lorentz-invariant deterministic hidden-variable model for explaining quantum nonlocality. Those theorems claim that the only known solution to escape the conclusions is either to accept a preferred reference frame or to abandon the hidden-variabl

Hanieh Afkhamiardakani, Jean-Claude Diels

A bidirectional mode-locked fiber laser producing two correlated frequency combs of the same repetition rate is demonstrated. The intensity dependence of pulse and phase velocities are measured simultaneously. As expected, the phase delay is determined by the linear and nonlinear indices of refraction. The nonlinear Kerr effect contribution to the pulse velo

Yang Liu, Yixian Gao, Jian Zu

Consider the time-domain multiple cavity scattering problem, which arises in diverse scientific areas and has significant industrial and military applications. The multiple cavity embedded in an infinite ground plane, is filled with inhomogeneous media characterized by variable dielectric permittivities and magnetic permeabilities. Corresponding to the trans

Martina Iapichino, Yen Wen Wang, Savannah Gentry, Anne Pringle

Basidiomycete fungi eject spores using a surface tension catapult; a fluid drop forms at the base of each spore and after reaching a critical size, coalesces with the spore and launches it from the gill surface. Although basidiomycetes function within ecosystems as both devastating pathogens and mutualists critical to plant growth, an incomplete understandin

Tekin Dereli, Cem Yetişmişoğlu

We discuss locally Weyl (scale) covariant generalisations of gravitational theories using Riemann-Cartan-Weyl space-times in arbitrary dimensions. We demonstrate the procedure of Weyl gauging on two examples in particular: General relativity, and topologically massive gravity in three dimensions.

Avi Rosenfeld, Ariella Richardson

This paper presents a taxonomy of explainability in Human-Agent Systems. We consider fundamental questions about the Why, Who, What, When and How of explainability. First, we define explainability, and its relationship to the related terms of interpretability, transparency, explicitness, and faithfulness. These definitions allow us to answer why explainabili

Peeter Saari, Ott Rebane, Ioannis Besieris

A universal relation has been established between the local energy transport velocity along the direction of propagation and the group velocity of scalar and vector-valued propagation-invariant spatiotemporally localized superluminal and subluminal electromagnetic waves in free space. Under specific restrictions, this relationship is very closely valid for p

Zezhong Zhang, Zehua Zhou, Rui Wang, Yang Li

The performance of downlink massive multiple-input-multiple-output networks with co-channel device-to-device communications is investigated in this paper. Specifically, we consider a cellular network with sufficient number of antennas at the base station and typical hexagonal cell coverage, where the cell users and device-to-device transmitters are randomly

Samson Ojako, Rituparno Goswami, Sunil D. Maharaj, Rivendra Narain

In this paper we excavate, for the first time, the most general class of conformal Killing vectors, that lies in the two dimensional subspace described by the null and radial co-ordinates, that are admitted by the generalised Vaidya geometry. Subsequently we find the most general class of generalised Vaidya mass functions that give rise to such conformal sym

Yueyang Zheng, Jingtao Shi

This paper is concerned with a Stackelberg game of backward stochastic differential equations (BSDEs), where the coefficients of the backward system and the cost functionals are deterministic, and the control domain is convex. Necessary and sufficient conditions of the optimality for the follower and the leader are first given for the general problem, by the

Clara Stegehuis, Remco van der Hofstad, Johan S. H. van Leeuwaarden

For scale-free networks with degrees following a power law with an exponent $τ\in(2,3)$, the structures of motifs (small subgraphs) are not yet well understood. We introduce a method designed to identify the dominant structure of any given motif as the solution of an optimization problem. The unique optimizer describes the degrees of the vertices that togeth

Betül Demirkaya, Tekin Dereli, Kaan Güven

The axisymmetric acoustic perturbations in the velocity potential of a Bose-Einstein condensate in the presence of a single vortex behave like minimally coupled massless scalar fields propagating in a curved (1+1) dimensional Lorentzian space-time, governed by the Klein-Gordon wave equation. Thus far, the amplified scattering of these perturbations from the

Liu Yang, Lijing Song

In this paper, we address the question answering challenge with the SQuAD 2.0 dataset. We design a model architecture which leverages BERT's capability of context-aware word embeddings and BiDAF's context interactive exploration mechanism. By integrating these two state-of-the-art architectures, our system tries to extract the contextual word represe

Rasmus E. Christiansen, Fengwen Wang, Ole Sigmund, Søren Stobbe

Designing photonic topological insulators is highly non-trivial because it requires inversion of band symmetries around the band gap, which was so far done using intuition combined with meticulous trial and error. Here we take a completely different approach: we consider the design of photonic topological insulators as an inverse design problem and use topol

Robin Kreuzig, Matthias Ochs, Rudolf Mester

Classical monocular vSLAM/VO methods suffer from the scale ambiguity problem. Hybrid approaches solve this problem by adding deep learning methods, for example by using depth maps which are predicted by a CNN. We suggest that it is better to base scale estimation on estimating the traveled distance for a set of subsequent images. In this paper, we propose a

Qingshan Xu, Wenbing Tao

In this paper, we propose an efficient multi-scale geometric consistency guided multi-view stereo method for accurate and complete depth map estimation. We first present our basic multi-view stereo method with Adaptive Checkerboard sampling and Multi-Hypothesis joint view selection (ACMH). It leverages structured region information to sample better candidate

Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue

In many high-throughput experimental design settings, such as those common in biochemical engineering, batched queries are more cost effective than one-by-one sequential queries. Furthermore, it is often not possible to directly choose items to query. Instead, the experimenter specifies a set of constraints that generates a library of possible items, which a

Lei Lei, Jiaju Qi, Kan Zheng

The number of approved patents worldwide increases rapidly each year, which requires new patent analytics to efficiently mine the valuable information attached to these patents. Vector space model (VSM) represents documents as high-dimensional vectors, where each dimension corresponds to a unique term. While originally proposed for information retrieval syst

Gerard Higgins, Fabian Pokorny, Chi Zhang, Markus Hennrich

Usually the influence of the quadratic Stark effect on an ion's trapping potential is minuscule and only needs to be considered in atomic clock experiments. In this work we excite a trapped ion to a Rydberg state with polarizability $\sim$~eight orders of magnitude higher than a low-lying electronic state; we find that the highly-polarizable ion experien

Qiang Li, Bo Xie, Jane You, Wei Bian

In this paper, we present correlated logistic (CorrLog) model for multilabel image classification. CorrLog extends conventional logistic regression model into multilabel cases, via explicitly modeling the pairwise correlation between labels. In addition, we propose to learn the model parameters of CorrLog with elastic net regularization, which helps exploit

Abhimanyu Pallavi Sudhir

Significant research has been carried out in the past half-century on defining generalised determinants for transformations between (typically real) vector spaces of different dimensions. We review three different generalisations of the determinant to non-square matrices, that we term for convenience the determinant-like function, the vector determinant and

Steffen Smolka, Praveen Kumar, David M Kahn, Nate Foster

This paper presents McNetKAT, a scalable tool for verifying probabilistic network programs. McNetKAT is based on a new semantics for the guarded and history-free fragment of Probabilistic NetKAT in terms of finite-state, absorbing Markov chains. This view allows the semantics of all programs to be computed exactly, enabling construction of an automatic verif

Atsushi Kamimura, Kunihiko Kaneko

A great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address an essential role of the huge diversity of cellular components, we study a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. As the resources are limited, it is shown

Joonho Lee, Luke W. Bertels, Martin Head-Gordon

We show that using complex, spin-restricted orbitals (cR) in Kohn-Sham density functional theory (KS-DFT) allows one to access a new class of densities that is not accessible by either spin-restricted (RKS) or spin-unrestricted (UKS) orbitals. We further show that the real part of a cRKS density matrix can be non-idempotent when the imaginary part of the den

Siddharth Srivastava, Sumit Soman, Astha Rai

This paper introduces a novel approach for dengue fever classification based on online learning paradigms. The proposed approach is suitable for practical implementation as it enables learning using only a few training samples. With time, the proposed approach is capable of learning incrementally from the data collected without need for retraining the model

Chunrong Feng, Huaizhong Zhao, Johnny Zhong

Periodic measures are the time-periodic counterpart to invariant measures for dynamical systems and can be used to characterise the long-term periodic behaviour of stochastic systems. This paper gives sufficient conditions for the existence, uniqueness and geometric convergence of a periodic measure for time-periodic Markovian processes on a locally compact

Andrew Balchunas, Leroy L. Jia, Mark Zakhary, Zvonimir Dogic

We study the emergence of helical structures subjected to a stretching force, demonstrating that the force transforms disk-shaped colloidal membranes into twisted chiral ribbons of predetermined handedness. Using an experimental technique that enforces torque-free boundary conditions we simultaneously measure the force-extension curve and quantify the shape

Timur V. Medvedev, Olga V. Pochinka, Svetlana Kh. Zinina

We prove the existence of a continuous Morse energy function for an arbitrary topological flow with finite hyperbolic (in topological sense) chain recurrent set on a topological manifold of any dimension. This result is a partial solution of the Morse problem of existence of continuous Morse functions on any topological manifolds. Namely, we prove that a top

Soichiro Fujii

In the study of computational effects, it is important to consider the notion of computational effects with parameters. The need of such a notion arises when, for example, statically estimating the range of effects caused by a program, or studying the ways in which effects with local scopes are derived from effects with only the global scope. Extending the c

Eric Larson

In this paper we compute the Chow ring of the moduli stack $\bar{M}_2$ of stable curves of genus 2 with integral coefficients.

Raymond Walter, Charles Paillard, Sergey Prosandeev, Laurent Bellaiche

Negative capacitance in BaTiO$_3$/SrTiO$_3$ superlattices is investigated by Monte Carlo simulations in an atomistic effective Hamiltonian model, using fluctuation formulas for responses to the local macroscopic field that incorporates depolarizing fields. We show epitaxial strain can tune the negative capacitance of the BaTiO$_3$ ferroelectric layer and the

Yuchen Liu, Hao Xiong, Zhongjun He, Jiajun Zhang

End-to-end speech translation (ST), which directly translates from source language speech into target language text, has attracted intensive attentions in recent years. Compared to conventional pipeline systems, end-to-end ST models have advantages of lower latency, smaller model size and less error propagation. However, the combination of speech recognition

Jingyi Mah, Ramon Brasser

The source of impactors capable of producing the cratering asymmetry on Triton is open to debate. While hyperbolic comets are the likely source of impactors, the theoretically predicted crater distribution due to impacts from comets is incompatible with the observed crater distribution on Triton. In this study, we adopted a dynamical approach to investigate

Km Arti Mishra, Almas, Upendra Kumar

Graphene and phosphorene are monolayer of graphite and phosphorous, respectively. Graphene is completely relativistic (Dirac) fermionic system, but phosphorene is pseudorelativistic fermionic system. In phosphorene, electronic spectrum of phosphorene has a Dirac like (linear) band in one direction and Schrodinger like (parabolic) band in other direction. Con

Zhang Guo, Kevin Yu, Rebecca Pearlman, Nassir Navab

The analysis of the collaborative learning process is one of the growing fields of education research, which has many different analytic solutions. In this paper, we provided a new solution to improve automated collaborative learning analyses using deep neural networks. Instead of using self-reported questionnaires, which are subject to bias and noise, we au

Gilles Ferrand, Donald C. Warren, Masaomi Ono, Shigehiro Nagataki

Recent progress in the three-dimensional modeling of supernovae (SN) has shown the importance of asymmetries for the explosion. This calls for a reconsideration of the modeling of the subsequent phase, the supernova remnant (SNR), which has commonly relied on simplified ejecta models. In this paper we bridge SN and SNR studies by using the output of a SN sim

Jia Li, Xiao Sun, Xing Wei, Changliang Li

In recent years, the generation of conversation content based on deep neural networks has attracted many researchers. However, traditional neural language models tend to generate general replies, lacking logical and emotional factors. This paper proposes a conversation content generation model that combines reinforcement learning with emotional editing const

Xin Hong, Pengfei Xiong, Renhe Ji, Haoqiang Fan

Deep image completion usually fails to harmonically blend the restored image into existing content, especially in the boundary area. This paper handles with this problem from a new perspective of creating a smooth transition and proposes a concise Deep Fusion Network (DFNet). Firstly, a fusion block is introduced to generate a flexible alpha composition map

Kel-Meng See, Fan-Cheng Lin, Jer-Shing Huang

We present two-dimensional plasmonic Doppler grating (PDG) for broadband azimuthal angle-resolved nanophotonic applications. The PDG consists of a set of non-concentric circular rings mimicking the wavefronts of a moving point source that exhibits Doppler Effect and thereby offers continuous azimuthal angle-dependent lattice momentum for photon-plasmon coupl

Lei Liu, Jie Jiang, Wenjing Jia, Saeed Amirgholipour

Counting people or objects with significantly varying scales and densities has attracted much interest from the research community and yet it remains an open problem. In this paper, we propose a simple but an efficient and effective network, named DENet, which is composed of two components, i.e., a detection network (DNet) and an encoder-decoder estimation n

Weiming Shen, Yue Wang, Zhifei Zhang

In the case of favorable pressure gradient, Oleinik proved the global existence of classical solution for the 2-D steady Prandtl equation for a class of positive data. In the case of adverse pressure gradient, an important physical phenomena is the boundary layer separation. In this paper, we prove the boundary layer separation for a large class of Oleinik&#

Nikolay Achasov

It is shown that the molecular model for the X{3872) state contradicts the new experimental data as well as the old ones. It is suggested to study the χ_{c1} and χ_{b1} states in the e+e-\toχ_{c1}/χ_{b1} reactions.

Ioana Craiciu, Mi Lei, Jake Rochman, Jonathan M. Kindem

Quantum memories for light are important components for future long distance quantum networks. We present on-chip quantum storage of telecommunications band light at the single photon level in an ensemble of erbium-167 ions in an yttrium orthosilicate photonic crystal nanobeam resonator. Storage times of up to 10 $μ$s are demonstrated using an all-optical at

Qi Zhang, Siliang Tang, Xiang Ren, Fei Wu

This paper provides a new way to improve the efficiency of the REINFORCE training process. We apply it to the task of instance selection in distant supervision. Modeling the instance selection in one bag as a sequential decision process, a reinforcement learning agent is trained to determine whether an instance is valuable or not and construct a new bag with

Najeeb Khan, Ian Stavness

Dropout is commonly used to help reduce overfitting in deep neural networks. Sparsity is a potentially important property of neural networks, but is not explicitly controlled by Dropout-based regularization. In this work, we propose Sparseout a simple and efficient variant of Dropout that can be used to control the sparsity of the activations in a neural net

Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi

Multi-label classification (MLC) is the task of assigning a set of target labels for a given sample. Modeling the combinatorial label interactions in MLC has been a long-haul challenge. We propose Label Message Passing (LaMP) Neural Networks to efficiently model the joint prediction of multiple labels. LaMP treats labels as nodes on a label-interaction graph

Gianluca Bianchin, Fabio Pasqualetti, Soumya Kundu

This paper investigates the use of Infrastructure-To-Vehicle (I2V) communication to generate routing suggestions for drivers in transportation systems, with the goal of optimizing a measure of overall network congestion. We define link-wise levels of trust to tolerate the non-cooperative behavior of part of the driver population, and we propose a real-time o

Yipeng An, Yusheng Hou, Hui Wang, Jie Li

In a very recent experimental work [Gao et al., 2018 Adv. Mater. 30, 1707055], a graphene-like CuSe monolayer was realized. Motivated by this success, we performed first-principles calculations to investigate its electronic transport and photoelectronic properties. We find that the CuSe ML shows a strong electrical anisotropy, and its current-voltage (I-V) c

Graeme Wilkin

This paper extends previous work from arxiv:1702.05223, which shows that the main theorem of Morse theory holds for a large class of functions on singular spaces, where the function and the underlying singular space are required to satisfy the five conditions explained in detail in the introduction to arxiv:1702.05223. The fourth of these conditions requires

Shaohua Zhang, Hongyan Zhou, Xiheng Shi, Tuo Ji

The binary emission-line system, particularly the binary broad-line emission system, is considered the most effective indicator of the black hole binary. A plausible example of such a system, SDSS J153636.22+044127.0, was reported as the first known object with two hydrogen Balmer broad-line systems, which are interpreted to be the result of broad-line regio

Xin Wen, Zhizhong Han, Xinyu Yin, Yu-Shen Liu

Cross-modal retrieval aims to retrieve relevant data across different modalities (e.g., texts vs. images). The common strategy is to apply element-wise constraints between manually labeled pair-wise items to guide the generators to learn the semantic relationships between the modalities, so that the similar items can be projected close to each other in the c

Naser T. Sardari

We introduce a smooth variance sum associated to a pair of positive definite symmetric integral matrices $A_{m\times m}$ and $B_{n\times n}$, where $m\geq n$. By using the oscillator representation, we give a formula for this variance sum in terms of a smooth sum over the square of a functional evaluated on the $B$-th Fourier coefficients of the vector value

Asghar Aryanfar, Agustin J. Colussi, Laleh M. Kasmaee, Michael R. Hoffmann

Electropolymerization plays a critical role in the electrochemical systems. In this chapter, we address such role within the context of interplay between kinetics and energetics. The trains of chin radical reactions leads to the formation of thin films in electrochemical devices. The structure of so-called solid electrolyte interphase (SEI) during the initia

Jiabin Xue, Jiqing Han, Tieran Zheng, Xiang Gao

Recently, data-driven based Automatic Speech Recognition (ASR) systems have achieved state-of-the-art results. And transfer learning is often used when those existing systems are adapted to the target domain, e.g., fine-tuning, retraining. However, in the processes, the system parameters may well deviate too much from the previously learned parameters. Thus,

Thiagarajan Ramachandran, Andrew Reiman, Sai Pushpak Nandanoori, Mark Rice

Low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication, and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that

Richard Gottesman

Let $H$ denote a finite index subgroup of the modular group $Γ$ and let $ρ$ denote a finite-dimensional complex representation of $H.$ Let $M(ρ)$ denote the collection of holomorphic vector-valued modular forms for $ρ$ and let $M(H)$ denote the collection of modular forms on $H$. Then $M(ρ)$ is a $\textbf{Z}$-graded $M(H)$-module. It has been proven that $M(

Jiabin Xue, Jiqing Han, Tieran Zheng, Jiaxing Guo

It is an effective way that improves the performance of the existing Automatic Speech Recognition (ASR) systems by retraining with more and more new training data in the target domain. Recently, Deep Neural Network (DNN) has become a successful model in the ASR field. In the training process of the DNN based methods, a back propagation of error between the t

Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu

Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items. The matching stage retrieves candidate items relevant to user interests, while the ranking stage sorts candidate items by user interests. Thus, the most critical ability is to model and represent user interests

Wenyuan Wang, Zhimin Zhang

Motivated by Kyprianou and Zhou (2009), Wang and Hu (2012), Avram et al. (2017), Li et al. (2017) and Wang and Zhou (2018), we consider in this paper the problem of maximizing the expected accumulated discounted tax payments of an insurance company, whose reserve process (before taxes are deducted) evolves as a spectrally negative Lévy process with the usual

Bing Cheng, P. Taylor, P. Folkes, Charles Rong

Pb$_{1-x}$Sn$_x$Te has been shown to be an interesting tunable topological crystalline insulator system. We present a magneto-terahertz spectroscopic study of thin films of Pb$_{0.5}$Sn$_{0.5}$Te. The complex Faraday rotation angle and optical conductivity in the circular basis are extracted without any additional assumptions. Our quantitative measures of th

Teruaki Kitano, Takayuki Morifuji, Anh T. Tran

In this paper we give an explicit formula for the twisted Alexander polynomial of any torus link and show that it is a locally constant function on the $SL(2, \mathbb C)$-character variety. We also discuss similar things for the higher dimensional twisted Alexander polynomial and the Reidemeister torsion.

Junsoo Kim, Hyungbo Shim, Kyoohyung Han

The cryptosystem based on the Learning-with-Errors (LWE) problem is considered as a post-quantum cryptosystem, because it is not based on the factoring problem with large primes which is easily solved by a quantum computer. Moreover, the LWE-based cryptosystem allows fully homomorphic arithmetics so that two encrypted variables can be added and multiplied wi

Badong Chen, Lujuan Dang, Yuantao Gu, Nanning Zheng

To date most linear and nonlinear Kalman filters (KFs) have been developed under the Gaussian assumption and the well-known minimum mean square error (MMSE) criterion. In order to improve the robustness with respect to impulsive (or heavy-tailed) non-Gaussian noises, the maximum correntropy criterion (MCC) has recently been used to replace the MMSE criterion

Nicolas R. Gauger, Alexander Linke, Philipp W. Schroeder

An improved understanding of the divergence-free constraint for the incompressible Navier--Stokes equations leads to the observation that a semi-norm and corresponding equivalence classes of forces are fundamental for their nonlinear dynamics. The recent concept of {\em pressure-robustness} allows to distinguish between space discretisations that discretise

Tomáš Masopust

Critical observability is a property of cyber-physical systems to detect whether the current state belongs to a set of critical states. In safety-critical applications, critical states model operations that may be unsafe or of a particular interest. De Santis et al. introduced critical observability for linear switching systems, and Pola et al. adapted it fo

I. G. Graham, S. A. Sauter

We discuss the stability theory and numerical analysis of the Helmholtz equation with variable and possibly non-smooth or oscillatory coefficients. Using the unique continuation principle and the Fredholm alternative, we first give an existence-uniqueness result for this problem, which holds under rather general conditions on the coefficients and on the doma

Jian Ding, Julien Dubédat, Alexander Dunlap, Hugo Falconet

We study Liouville first passage percolation metrics associated to a Gaussian free field $h$ mollified by the two-dimensional heat kernel $p_t$ in the bulk, and related star-scale invariant metrics. For $\gamma \in (0,2)$ and $\xi = \frac{\gamma}{d_{\gamma}}$, where $d_{\gamma}$ is the Liouville quantum gravity dimension defined in [Ding-Gwynne18], we show t

Tom G. Mackay, Akhlesh Lakhtakia

The so-called electromagnetic ghost waves are simply electromagnetic nonuniform plane waves, whose association with both propagating and evanescent fields has long been known, even for isotropic dielectric materials that are non-dissipative.

Edoardo Fertitta, George H. Booth

We present a multi-scale approach to efficiently embed an ab initio correlated chemical fragment described by its energy-weighted density matrices, and entangled with a wider mean-field many-electron system. This approach, first presented in Phys. Rev. B, 98, 235132 (2018), is here extended to account for realistic long-range interactions and broken symmetry

Seunghyun Min, Qing Zhou

Although a few methods have been developed recently for building confidence intervals after model selection, how to construct confidence sets for joint post-selection inference is still an open question. In this paper, we develop a new method to construct confidence sets after lasso variable selection, with strong numerical support for its accuracy and effec

Antonio Alarcon, Franc Forstneric

In this paper, we show that if $R$ is a compact Riemann surface and $M=R\setminus\,\bigcup_i D_i$ is a domain in $R$ whose complement is a union of countably many pairwise disjoint smoothly bounded closed discs $D_i$, then $M$ is the complex structure of a complete bounded minimal surface in $\mathbb R^3$. We prove that there is a complete conformal minimal

Claudia Agliozzo, Andrea Mehner, Neil Matthew Phillips, Paolo Leto

The luminous blue variable (LBV) RMC143 is located in the outskirts of the 30~Doradus complex, a region rich with interstellar material and hot luminous stars. We report the $3σ$ sub-millimetre detection of its circumstellar nebula with ALMA. The observed morphology in the sub-millimetre is different than previously observed with HST and ATCA in the optical

Antony J. Speranza

Embedding fields provide a way of coupling a background structure to a theory while preserving diffeomorphism-invariance. Examples of such background structures include embedded submanifolds, such as branes; boundaries of local subregions, such as the Ryu-Takayanagi surface in holography; and foliations, which appear in fluid dynamics and force-free electrod

Maximiliano Isi, Katerina Chatziioannou, Will M. Farr

We propose a hierarchical approach to testing general relativity with multiple gravitational wave detections. Unlike existing strategies, our method does not assume that parameters quantifying deviations from general relativity are either common or completely unrelated across all sources. We instead assume that these parameters follow some underlying distrib

Mathieu Roche

This position paper presents a comparative study of co-occurrences. Some similarities and differences in the definition exist depending on the research domain (e.g. linguistics, NLP, computer science). This paper discusses these points, and deals with the methodological aspects in order to identify co-occurrences in a multidisciplinary paradigm.