July 2019 arXiv papers — page 77

Wei-Bang Liao, Tian-Yue Chen, Yari Ferrante, Stuart S. P. Parkin

The spin Hall effect originating from 5d heavy transition metal thin films such as Pt, Ta, and W is able to generate efficient spin-orbit torques that can switch adjacent magnetic layers. This mechanism can serve as an alternative to conventional spin-transfer torque for controlling next-generation magnetic memories. Among all 5d transition metals, W in its

Daniel Cervantes, Miguel angel Moreles, Joaquin Peña, Alonso Ramirez-Manzanares

In this work we develop a methodology to approximate the covariance matrix associated to the simulation of water diffusion inside the brain tissue. The computation is based on an implementation of the Discontinuous Galerkin method of the diffusion equation, in accord with the physical phenomenon. The implementation in in parallel using GPUs in the CUDA langu

Ye Liu, Chen Shen, Yankan Song, Jun Yan

With the complex hybrid AC-DC power system in China coming into being, the HVDC faults, such as DC block faults, have an enormous effect on the frequency stability of the AC side. In multi-infeed HVDC (MIDC) system, to improve the frequency stability of the receiving-end system, this paper proposes an emergency DC power support (EDCPS) strategy, which is bas

M. Abdolmaleki, S. Gh. Ilchi, E. S. Mahmoodian, MA. Shabani

The problem of finding necessary and sufficient conditions to decompose a complete tripartite graph $K_{r,s,t}$ into 5-cycles was first considered by E.S. Mahmoodian and Maryam Mirzakhani (1995). They stated some necessary conditions and conjectured that those conditions are also sufficient. Since then, many cases of the problem have been solved by various a

Ping Kwan Johnny Wong, Wen Zhang, Jun Zhou, Fabio Bussolotti

We present a combined experimental and theoretical study of monolayer VTe2 grown on highly oriented pyrolytic graphite by molecular-beam epitaxy. Using various in-situ microscopic and spectroscopic techniques, including scanning tunneling microscopy/spectroscopy, synchrotron X-ray and angle-resolved photoemission, and X-ray absorption, together with theoreti

Igor Bychkov, Julia Dubenskaya, Elena Korosteleva, Alexandr Kryukov

Today, the operating TAIGA (Tunka Advanced Instrument for cosmic rays and Gamma Astronomy) experiment continuously produces and accumulates a large volume of raw astroparticle data. To be available for the scientific community these data should be well-described and formally characterized. The use of metadata makes it possible to search for and to aggregate

B. A. Kochetov, O. G. Chelpanova, V. R. Tuz, A. I. Yakimenko

In contrast to conservative systems, in nonlinear media with gain and loss the dynamics of localized topological structures can exhibit unique features that can be controlled externally. We propose a robust mechanism to perform topological transformations changing characteristics of dissipative vortices and their complexes in a controllable way. We show that

Masahiro Manago, Shunsaku Kitagawa, Kenji Ishida, Kazuhiko Deguchi

A $^{59}$Co nuclear magnetic resonance (NMR) measurement was performed on the single-crystalline ferromagnetic (FM) superconductor UCoGe under a pressure of 1.09 GPa, where the FM state is suppressed and superconductivity occurs in the paramagnetic (PM) state, to study the superconducting (SC) state in the PMstate. $^{59}$Co-NMR spectra became broader but ha

Marcella Contini

The detailed modelling of the spectra observed from the long GRB031203 host galaxy at different epochs during the 2003-2009 years is presented. The line profiles show FWHM of about 100 km/s. A broad line profile with FWHM < 400 km/s appears in the line sockets from the 2009 observations. We suggest that the narrow lines show the velocity of star-burst (SB) d

Adam Breuer, Eric Balkanski, Yaron Singer

In this paper we describe a new algorithm called Fast Adaptive Sequencing Technique (FAST) for maximizing a monotone submodular function under a cardinality constraint $k$ whose approximation ratio is arbitrarily close to $1-1/e$, is $O(\log(n) \log^2(\log k))$ adaptive, and uses a total of $O(n \log\log(k))$ queries. Recent algorithms have comparable guaran

Ivan Bliznets, Danil Sagunov

We study the Maximum Happy Vertices and Maximum Happy Edges problems. The former problem is a variant of clusterization, where some vertices have already been assigned to clusters. The second problem gives a natural generalization of Multiway Uncut, which is the complement of the classical Multiway Cut problem. Due to their fundamental role in theory and pra

D Vijay Anand, Kelin Xia, Yuguang Mu

It has long been observed that trimethylamin N-oxide (TMAO) and urea demonstrate dramatically different properties in a protein folding process. Even with the enormous theoretical and experimental research work of the two osmolytes, various aspects of their underlying mechanisms still remain largely elusive. In this paper, we propose to use the weighted pers

Marcin Junczys-Dowmunt

This paper describes the Microsoft Translator submissions to the WMT19 news translation shared task for English-German. Our main focus is document-level neural machine translation with deep transformer models. We start with strong sentence-level baselines, trained on large-scale data created via data-filtering and noisy back-translation and find that back-tr

Gilberto Aguilar-Pérez, Miguel Cruz, Samuel Lepe, Israel Moran-Rivera

Supported by the use of a regular scalar field we find a black hole solution in the Einstein-Gauss-Bonnet model. From the obtained solution we can recover the Schwarzschild black hole as in other works. Later, by implementing the odd parity perturbations method we study the stability of the linearized equations of motion of the model, we find the explicit fo

Parneet Kaur, Karan Sikka, Weijun Wang, Serge Belongie

Food classification is a challenging problem due to the large number of categories, high visual similarity between different foods, as well as the lack of datasets for training state-of-the-art deep models. Solving this problem will require advances in both computer vision models as well as datasets for evaluating these models. In this paper we focus on the

Menassie Ephrem

Given a directed graph $E$ and a labeling $\mathcal{L}$, one forms the labelled graph $C^*$-algebra by taking a weakly left--resolving labelled space $(E, \mathcal{L}, \mathcal{B})$ and considering a universal generating family of partial isometries and projections. In this paper we provide characterization for primitive ideals of labelled graph $C^*$-algebr

Riyi Qiu, Yugang Jia, Mirsad Hadzikadic, Michael Dulin

Deep learning models have exhibited superior performance in predictive tasks with the explosively increasing Electronic Health Records (EHR). However, due to the lack of transparency, behaviors of deep learning models are difficult to interpret. Without trustworthiness, deep learning models will not be able to assist in the real-world decision-making process

Devon Jensen, Mohammad Ghashami, Keunhan Park

Over the past years, thermionic energy conversion (TEC) with a reduced inter-electrode vacuum gap has been studied as an effective way to mitigate a large potential barrier due to space charge accumulation. However, existing theoretical models do not fully consider the fundamental aspects of thermionic emission when the inter-electrode gap shrinks to the nan

Heng Guo, Jingcheng Liu, Pinyan Lu

We study zeros of the partition functions of ferromagnetic 2-state spin systems in terms of the external field, and obtain new zero-free regions of these systems via a refinement of Asano&#39;s and Ruelle&#39;s contraction method. The strength of our results is that they do not depend on the maximum degree of the underlying graph. Via Barvinok&#39;s method,

J. Ralph Alexander, John E. Wetzel, Wacharin Wichiramala

In 2006 P. Coulton and Y. Movshovich established an unfamilar but note-worthy general property of simple, polygonal, open arcs in the plane. We give a new and quite different proof of this property, and we consider a few generalizations.

B. M. Motamedi, T. N. Shannon, Z. Papp

We propose a solution method for studying relativistic spin-$0$ particles. We adopt the Feshbach-Villars formalism of the Klein-Gordon equation and express the formalism in an integral equation form. The integral equation is represented in the Coulomb-Sturmian basis. The corresponding Green&#39;s operator with Coulomb and linear confinement potential can be

Huai-Liang Chang, Jun Li, Wei-Ping Li, Chiu-Chu Melissa Liu

We outline various developments of affine and general Landau Ginzburg models in physics. We then describe the A-twisting and coupling to gravity in terms of Algebraic Geometry. We describe constructions of various path integral measures (virtual fundamental class) using the algebro-geometric technique of cosection localization, culminating in the theory of `

Matthew A. Wright, Simon F. G. Ehlers, Roberto Horowitz

Deep neural networks can be powerful tools, but require careful application-specific design to ensure that the most informative relationships in the data are learnable. In this paper, we apply deep neural networks to the nonlinear spatiotemporal physics problem of vehicle traffic dynamics. We consider problems of estimating macroscopic quantities (e.g., the

Everton M. C. Abreu, Newton J. Moura, Abner D. Soares, Marcelo B. Ribeiro

Oscillations in the complementary cumulative distribution function (CCDF) of individual income data have been found in the data of various countries studied by different authors at different time periods, but the dynamical origins of this behavior are currently unknown. Although these datasets can be fitted by different functions at different income ranges,

Jawad Abuhlail, Rangga Ganzar Noegraha

Flat modules play an important role in the study of the category of modules over rings and in the characterization of some classes of rings. We study the e-flatness for semimodules introduced by the first author using his new notion of exact sequences of semimodules and its relationships with other notions of flatness for semimodules over semirings. We also

Cong Fu, Changxu Wang, Deng Cai

Approximate Nearest Neighbor Search (ANNS) in high dimensional space is essential in database and information retrieval. Recently, there has been a surge of interest in exploring efficient graph-based indices for the ANNS problem. Among them, Navigating Spreading-out Graph (NSG) provides fine theoretical analysis and achieves state-of-the-art performance. Ho

Olanrewaju Akande, Gabriel Madson, D. Sunshine Hillygus, Jerome P. Reiter

Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources, for example, administrative databases or other high quality surveys. We present and illustrate a model-based framework for leveraging such auxiliary marginal information when handl

Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Ji Liu

In this paper, we present a probability one convergence proof, under suitable conditions, of a certain class of actor-critic algorithms for finding approximate solutions to entropy-regularized MDPs using the machinery of stochastic approximation. To obtain this overall result, we prove the convergence of policy evaluation with general regularizers when using

Naoki Sasakura, Shingo Takeuchi

We study a matrix model that has $ϕ_a^i\ (a=1,2,\ldots,N,\ i=1,2,\ldots,R)$ as its dynamical variable, whose lower indices are pairwise contracted, but upper ones are not always done so. This matrix model has a motivation from a tensor model for quantum gravity, and is also related to the physics of glasses, because it has the same form as what appears in th

Tianbo Liu, Jian-Wei Qiu

The COMPASS collaboration published precise data on production cross section of charged hadrons in lepton-hadron semi-inclusive deep inelastic scattering, showing almost an order of magnitude larger than next-to-leading order QCD calculations when $P_{h_T}$ and $z_h$ are sufficiently large. We explore the role of power corrections to the theoretical calculat

Eugenia Ellis, Emanuel Rodríguez Cirone, Gisela Tartaglia, Santiago Vega

Controlled topology is one of the main tools for proving the isomorphism conjecture concerning the algebraic $K$-theory of group rings. In this article we dive into this machinery in two examples: when the group is infinite cyclic and when it is the infinite dihedral group - in both cases with the family of finite subgroups. We prove a vanishing theorem and

Lihua Lei, Peter J. Bickel

We propose the Cyclic Permutation Test (CPT) to test general linear hypotheses for linear models. This test is non-randomized and valid in finite samples with exact Type I error $α$ for an arbitrary fixed design matrix and arbitrary exchangeable errors, whenever $1 / α$ is an integer and $n / p \ge 1 / α- 1$. The test involves applying the marginal rank test

ATLAS Collaboration

This Letter presents direct searches for lepton flavour violation in Higgs boson decays, $H\rightarrow eτ$ and $H\rightarrowμτ$, performed with the ATLAS detector at the LHC. The searches are based on a data sample of proton-proton collisions at a centre-of-mass energy $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of $36.1\,\mathrm{fb}^{-1}$

Bao Tran Truong, Xiaodan Lou, Alessandro Flammini, Filippo Menczer

Social media, seen by some as the modern public square, is vulnerable to manipulation. By controlling inauthentic accounts impersonating humans, malicious actors can amplify disinformation within target communities. The consequences of such operations are difficult to evaluate due to the challenges posed by collecting data and carrying out ethical experiment

Miguel Martín-Landrove, Francisco Torres-Hoyos, Antonio Rueda-Toicen

Tumor growth is a complex process characterized by uncontrolled cell proliferation and invasion of neighboring tissues. The understanding of these phenomena is of vital importance to establish appropriate diagnosis and therapeutic strategy and starts with the evaluation of their complexity with suitable descriptors, such as those produced by scaling analysis

Viktor Bengs, Eyke Hüllermeier

In this paper, we introduce the Preselection Bandit problem, in which the learner preselects a subset of arms (choice alternatives) for a user, which then chooses the final arm from this subset. The learner is not aware of the user&#39;s preferences, but can learn them from observed choices. In our concrete setting, we allow these choices to be stochastic an

Xiaoyu Wang, Qijin Chen, K. Levin

This paper addresses the transition from the normal to the superfluid state in strongly correlated two dimensional fermionic superconductors and Fermi gases. We arrive at the Berezinskii-Kosterlitz-Thouless (BKT) temperature $T_{\text{BKT}}$ as a function of \emph{attractive} pairing strength by associating it with the onset of &#34;quasi-condensation&#34; i

Geoff Boeing

As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings&#39; representativeness could impact different communities&#39; access to housing searc

Mingchang Ding, Xiaofeng Cai, Wei Guo, Jing-Mei Qiu

In this paper, we propose an efficient high order semi-Lagrangian (SL) discontinuous Galerkin (DG) method for solving linear convection-diffusion equations. The method generalizes our previous work on developing the SLDG method for transport equations (J. Sci. Comput. 73: 514-542, 2017), making it capable of handling additional diffusion and source terms. Wi

Sai Li, Tony T. Cai, Hongzhe Li

Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear mixed-effects models with high-dimensional fixed effects. The proposed method is applicable to general settings where the dimension of the random effects and the

Isabella Novik, Hailun Zheng

In 1995, Jockusch constructed an infinite family of centrally symmetric $3$-dimensional simplicial spheres that are cs-$2$-neighborly. Here we generalize his construction and show that for all $d\geq 3$ and $n\geq d+1$, there exists a centrally symmetric $d$-dimensional simplicial sphere with $2n$ vertices that is cs-$\lceil d/2\rceil$-neighborly. This resul

Yiannis Loizides

In this short note we revisit the `shift-desingularization&#39; version of the $[Q,R]=0$ theorem for possibly singular symplectic quotients. We take as starting point an elegant proof due to Szenes-Vergne of the quasi-polynomial behavior of the multiplicity as a function of the tensor power of the prequantum line bundle. We use the Berline-Vergne index formu

Peter Gladbach, Heiner Olbermann

We prove upper and lower bounds for a variational functional for convex functions satisfying certain boundary conditions on a sector of the unit ball in two dimensions. The functional contains two terms: The full Hessian and its determinant, where the former is treated as a small perturbation in the space $L^2$ and the latter as the leading-order term, in th

Laurent Bétermin, Lucia De Luca, Mircea Petrache

We consider two-dimensional zero-temperature systems of $N$ particles to which we associate an energy of the form $$ \mathcal{E}[V](X):=\sum_{1\le i<j\le N}V(|X(i)-X(j)|), $$ where $X(j)\in\mathbb R^2$ represents the position of the particle $j$ and $V(r)\in\mathbb R$ is the {pairwise interaction} energy potential of two particles placed at distance $r$. We

H. T. Özer, Aytül Filiz

In this paper, we present a candidate for $\mathcal{N}=(1,1)$ extended higher - spin $AdS_3$ supergravity with the most general boundary conditions discussed by Grumiller and Riegler recently. We show that the asymptotic symmetry algebra consists of two copies of the $\mathfrak{osp}(3|2)_k$ affine algebra in the presence of the most general boundary conditio

Helmut Prodinger

Recent results about sums of cubes of Fibonacci numbers [Frontczak, 2018] are extended to arbitrary powers.

Shadi Fatayer, Florian Albrecht, Yunlong Zhang, Darius Urbonas

The charge state of a molecule governs its physicochemical properties, such as conformation, reactivity and aromaticity, with implications for on-surface synthesis, catalysis, photo conversion and applications in molecular electronics. On insulating, multilayer NaCl films we control the charge state of organic molecules and resolve their structures in neutra

Ms. Navya Singh, Anshul Dhull, Barath Mohan. S, Bhavish Pahwa

Our game Pommerman is based on the console game Bommerman. The game starts on an 11 by 11 platform. Pommerman is a multi-agent environment and is made up of a set of different situations and contains four agents.

Ming-Zhu Liu, Tian-Wei Wu, Mario Sánchez Sánchez, Manuel Pavon Valderrama

The LHCb collaboration has recently observed three pentaquark peaks, the $P_c(4312)$, $P_c(4440)$ and $P_c(4457)$. They are very close to a pair of heavy baryon-meson thresholds, with the $P_c(4312)$ located $8.9\,{\rm MeV}$ below the $\bar{D} Σ_c$ threshold, and the $P_c(4440)$ and $P_c(4457)$ located $21.8$ and $4.8\,{\rm MeV}$ below the $\bar{D}^* Σ_c$ on

Mattia Udina, Tommaso Cea, Lara Benfatto

Time-resolved spectroscopies using intense THz pulses appear as a promising tool to address collective electronic excitations in condensed matter. In particular recent experiments showed the possibility to selectively excite collective modes emerging across a phase transition, as it is the case for superconducting and charge-density-wave (CDW) systems. One p

E. Cannuccia, A. Gali

Direct observation of temperature dependence of individual bands of semiconductors for a wide temperature region is not straightforward, in particular. However, this fundamental property is a prerequisite in understanding the electron-phonon coupling of semiconductors. Here we apply \emph{ab initio} many body perturbation theory to the electron-phonon coupli

Tomonari Mizoguchi, Mina Maruyama, Susumu Okada, Yasuhiro Hatsugai

In a class of carbon-based materials called polymerized triptycene, which consist of triptycene molecules and phenyls, exotic electronic structures such as Dirac cones and flat bands arise from the kagome-type network. In this paper, we theoretically investigate the tight-binding models for polymerized triptycene, focusing on the origin of flat bands and the

Felix Frey, Johannes K. Fischer, Robert F. H. Fischer

A discrete-time end-to-end fiber-optical channel model is derived based on the first-order perturbation approach. The model relates the discrete-time input symbol sequences of co-propagating wavelength channels to the received symbol sequence after matched filtering and T-spaced sampling. To this end, the interference from both self- and cross-channel nonlin

Shikha Patel, Om Prakash

In this paper, we first consider the iterated skew polynomial ring $\mathscr{R}[z_1;\tau_1,\delta_{\tau_1}]$\\$[z_2;\tau_2,\delta_{\tau_2}]$, where $\mathscr{R}$ is a finite ring with unity. Then we use this structure for the construction of skew generalized polycyclic codes over the ring $\mathscr{R}$ and finite field $\mathbb{F}_q$, where $q=p^m$ for some

Alessandro Di Marco, Giancarlo De Gasperis, Gianfranco Pradisi, Paolo Cabella

We discuss the perturbative decay of the energy density of a non standard inflaton field $ρ_ϕ$ and the corresponding creation of the energy density of the relativistic fields $ρ_r$ at the end of inflation, in the perfect fluid description, refining some concepts and providing some new computations. In particular, the process is characterized by two fundament

Siddique Latif, Junaid Qadir, Muhammad Bilal

Cross-lingual speech emotion recognition (SER) is a crucial task for many real-world applications. The performance of SER systems is often degraded by the differences in the distributions of training and test data. These differences become more apparent when training and test data belong to different languages, which cause a significant performance gap betwe

Yi An, Tianyue Hou, Jun Li, Liangjin Huang

The Hermite-Gaussian (HG) modes make up a complete and orthonormal basis, which have been extensively used to describe optical fields. Here, we demonstrate, for the first time to our knowledge, deep learning-based modal decomposition (MD) of HG beams. This method offers a fast, economical and robust way to acquire both the power content and phase information

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

Knowledge graph embedding methods often suffer from a limitation of memorizing valid triples to predict new ones for triple classification and search personalization problems. To this end, we introduce a novel embedding model, named R-MeN, that explores a relational memory network to encode potential dependencies in relationship triples. R-MeN considers each

Geovani Nunes Grapiglia, Yurii Nesterov

In this paper we consider the problem of finding $ε$-approximate stationary points of convex functions that are $p$-times differentiable with $ν$-Hölder continuous $p$th derivatives. We present tensor methods with and without acceleration. Specifically, we show that the non-accelerated schemes take at most $\mathcal{O}\left(ε^{-1/(p+ν-1)}\right)$ iterations

Siddique Latif, Rajib Rana, Sara Khalifa, Raja Jurdak

Inspite the emerging importance of Speech Emotion Recognition (SER), the state-of-the-art accuracy is quite low and needs improvement to make commercial applications of SER viable. A key underlying reason for the low accuracy is the scarcity of emotion datasets, which is a challenge for developing any robust machine learning model in general. In this paper,

Eric Loubeau, Henrique N. Sá Earp

We give a twistorial interpretation of geometric structures on a Riemannian manifold, as sections of homogeneous fibre bundles, following an original insight by Wood (2003). The natural Dirichlet energy induces an abstract harmonicity condition, which gives rise to a geometric gradient flow. We establish a number of analytic properties for this flow, such as

Lei Zhang, Weihai Chen, Chao Hu, Xingming Wu

Dense depth completion is essential for autonomous systems and 3D reconstruction. In this paper, a lightweight yet efficient network (S\&CNet) is proposed to obtain a good trade-off between efficiency and accuracy for the dense depth completion. A dual-stream attention module (S\&C enhancer) is introduced to measure both spatial-wise and the channel-wise glo

Janna Burman, Ho-Lin Chen, Hsueh-Ping Chen, David Doty

We consider the standard population protocol model, where (a priori) indistinguishable and anonymous agents interact in pairs according to uniformly random scheduling. The self-stabilizing leader election problem requires the protocol to converge on a single leader agent from any possible initial configuration. We initiate the study of time complexity of pop

Yehui Tang, Shan You, Chang Xu, Boxin Shi

Compressing giant neural networks has gained much attention for their extensive applications on edge devices such as cellphones. During the compressing process, one of the most important procedures is to retrain the pre-trained models using the original training dataset. However, due to the consideration of security, privacy or commercial profits, in practic

Markus Redeker

A number-conserving cellular automaton is a simplified model for a system of interacting particles. This paper contains two related constructions by which one can find all one-dimensional number-conserving cellular automata with one kind of particle. The output of both methods is a "flow function", which describes the movement of the particles. In the first

A. Neronov, D. V. Semikoz

Measuring the diffuse Galactic gamma-ray flux in the TeV range is difficult for ground-based gamma-ray telescopes because of the residual cosmic-ray background, which is higher than the gamma-ray flux by several orders of magnitude. Its detection is also challenging for space-based telescopes because of low signal statistics. We characterize the diffuse TeV

Tadahiro Oh, Tristan Robert, Philippe Sosoe, Yuzhao Wang

We study the two-dimensional stochastic sine-Gordon equation (SSG) in the hyperbolic setting. In particular, by introducing a suitable time-dependent renormalization for the relevant imaginary multiplicative Gaussian chaos, we prove local well-posedness of SSG for any value of a parameter $β^2 > 0$ in the nonlinearity. This exhibits sharp contrast with the p

Giannis Nikolentzos, George Dasoulas, Michalis Vazirgiannis

Graph neural networks (GNNs) have emerged recently as a powerful architecture for learning node and graph representations. Standard GNNs have the same expressive power as the Weisfeiler-Leman test of graph isomorphism in terms of distinguishing non-isomorphic graphs. However, it was recently shown that this test cannot identify fundamental graph properties s

Marc Technau, Agamemnon Zafeiropoulos

Let $f\colon\mathbb{N}\rightarrow\mathbb{C}$ be an arithmetic function and consider the Beatty set $\mathcal{B}(\alpha) = \lbrace\, \lfloor n\alpha \rfloor : n\in\mathbb{N} \,\rbrace$ associated to a real number $\alpha$, where $\lfloor\xi\rfloor$ denotes the integer part of a real number $\xi$. We show that the asymptotic formula \[ \Bigl\lvert \sum_{\subst

Mattia Zorzi

We study the problem of distributed Kalman filtering for sensor networks in the presence of model uncertainty. More precisely, we assume that the actual state-space model belongs to a ball, in the Kullback-Leibler topology, about the nominal state-space model and whose radius reflects the mismatch modeling budget allowed for each time step. We propose a dist

Jeff Manning, Jack Shotton

We prove Ihara's lemma for the mod $l$ cohomology of Shimura curves, localised at a maximal ideal of the Hecke algebra, under a large image hypothesis on the associated Galois representation. This was proved by Diamond and Taylor, for Shimura curves over $\mathbb{Q}$, under various assumptions on $l$. Our method is totally different and can avoid these assum

Alexander Komech, Elena Kopylova

We survey the theory of attractors of nonlinear Hamiltonian partial differential equations since its appearance in 1990. These are results on global attraction to stationary states, to solitons and to stationary orbits, on adiabatic effective dynamics of solitons and their asymptotic stability. Results of numerical simulation are given. The obtained results

Song He, Fei Teng, Yong Zhang

We further elaborate on the general construction proposed in arXiv:1812.03369, which connects, via tree-level double copy, massless string amplitudes with color-ordered QFT amplitudes that are given by Cachazo-He-Yuan formulas. The current paper serves as a detailed study of the integration-by-parts procedure for any tree-level massless string correlator out

Garrick Brazil, Xiaoming Liu

Understanding the world in 3D is a critical component of urban autonomous driving. Generally, the combination of expensive LiDAR sensors and stereo RGB imaging has been paramount for successful 3D object detection algorithms, whereas monocular image-only methods experience drastically reduced performance. We propose to reduce the gap by reformulating the mon

Krzysztof Cichy, Luigi Del Debbio, Tommaso Giani

We revise the relation between Parton Distribution Functions (PDFs) and matrix elements computable from lattice QCD, focusing on the quasi-Parton Distribution Functions (qPDFs) approach. We exploit the relation between PDFs and qPDFs in the case of the unpolarized isovector parton distribution to obtain a factorization formula relating the real and imaginary

Luca Mezincescu, Paul K. Townsend

The IR limit of a planar static D3-brane in AdS5 x S5 is a tensionless D3-brane at the AdS horizon, with dynamics governed by a strong-field limit of the Dirac-Born-Infeld action analogous to that found from the Born-Infeld action by Bialynicki-Birula. As in that case, the field equations are those of an interacting 4D conformal invariant field theory with a

Weiming Feng, Heng Guo, Yitong Yin

We introduce a new perfect sampling technique that can be applied to general Gibbs distributions and runs in linear time if the correlation decays faster than the neighborhood growth. In particular, in graphs with sub-exponential neighborhood growth like $\mathbb{Z}^d$, our algorithm achieves linear running time as long as Gibbs sampling is rapidly mixing. A

Zhenyue Zhang, Yuqing Xia

Subspace segmentation or subspace learning is a challenging and complicated task in machine learning. This paper builds a primary frame and solid theoretical bases for the minimal subspace segmentation (MSS) of finite samples. Existence and conditional uniqueness of MSS are discussed with conditions generally satisfied in applications. Utilizing weak prior i

Xiaoqian Wang, Mingming Ma

An urgent demand for new sustainable and efficient energy conversion and storage devices required the development of novel electrode materials with increased specific capacitance. However, low mass loading, poor scalability, and low working voltage always limited further practical application of most reported high-performance supercapacitors electrode materi

Antonin Chambolle, Matteo Novaga, Valerio Pagliari

We study the rate of convergence of some nonlocal functionals recently considered by Bourgain, Brezis and Mironescu. In particular we establish the $Γ$-convergence of the corresponding rate functionals, suitably rescaled, to a limit functional of second order.

Jianfeng Chen, Sha Liu, Yong Wang, Chengwen Zhong

Discrete unified gas-kinetic scheme (DUGKS) is a multi-scale numerical method for flows from continuum limit to free molecular limit, and is especially suitable for the simulation of multi-scale flows, benefiting from its multi-scale property. To reduce integration error of the DUGKS and ensure the conservation property of the collision term in isothermal fl

B. A. Khrenov, G. K. Garipov, M. A. Kaznacheeva, P. A. Klimov

TUS (Tracking Ultraviolet Set-up) is the world&#39;s first orbital detector of ultra-high-energy cosmic rays (UHECRs). It was launched into orbit on 28th April 2016 as a part of the scientific payload of the Lomonosov satellite. The main aim of the mission was to test the technique of measuring the ultraviolet fluorescence and Cherenkov radiation of extensiv

W. Y. Kon, T. Krisnanda, P. Sengupta, T. Paterek

When two quantum systems are coupled via a mediator, their dynamics has traces of non-classical properties of the mediator. We show how this observation can be effectively utilised to study the quantum nature of materials without well-established structure. A concrete example considered is Sr$_{14}$Cu$_{24}$O$_{41}$. Measurements of low temperature magnetic

Joseph Breen, Austin Christian, Ko Honda, Yang Huang

We lay the foundations of convex hypersurface theory in contact topology, extending the work of Giroux in dimension three. Specifically, we prove that any closed hypersurface in a contact manifold can be $C^0$-approximated by a convex one. We also prove that a $C^0$-generic family of mutually disjoint closed hypersurfaces parametrized by $t\in[0,1]$ is conve

Thomas Hudson, Tomoo Matsumura, Nicolas Perrin

In this paper, we construct stable Bott--Samelson classes in the projective limit of the algebraic cobordism rings of full flag varieties, upon an initial choice of a reduced word in a given dimension. Each stable Bott--Samelson class is represented by a bounded formal power series modulo symmetric functions in positive degree. We make some explicit computat

Yantao Wei, Shujian Yu, Luis Sanchez Giraldo, Jose C. Principe

This paper proposes a novel architecture, termed multiscale principle of relevant information (MPRI), to learn discriminative spectral-spatial features for hyperspectral image (HSI) classification. MPRI inherits the merits of the principle of relevant information (PRI) to effectively extract multiscale information embedded in the given data, and also takes a

Dimitar Pashov, Swagata Acharya, Walter R. L. Lambrecht, Jerome Jackson

This paper summarises the theory and functionality behind Questaal, an open-source suite of codes for calculating the electronic structure and related properties of materials from first principles. The formalism of the linearised muffin-tin orbital (LMTO) method is revisited in detail and developed further by the introduction of short-ranged tight-binding ba

Alex Scott, Elizabeth Wilmer

We investigate the combinatorial structure of subspaces of the exterior algebra of a finite-dimensional real vector space, working in parallel with the extremal combinatorics of hypergraphs. Using initial monomials, projections of the underlying vector space onto subspaces, and the interior product, we find analogues of local and global LYM inequalities, the

Kam Hung Yau

We obtain an asymptotic formula for the number of ways to represent every reduced residue class as a product of a prime and square-free integer. This may be considered as a relaxed version of a conjecture of Erdös, Odlyzko, and Sárközy.

Behnam Pourhassan, Sudhaker Upadhyay

In this paper, we study the thermodynamics and statistics of the galaxies clustering affected by the dynamical dark energy. We consider two important dark energy models based on time dependent equation of state to evaluate the gravitational partition function. In the first model, we consider barotropic dark energy with time dependent equation of state. Howev

Ibrahim Al-Nahhal, Octavia A. Dobre, Ertugrul Basar, Salama Ikki

Spatial modulation (SM)-sparse code multiple access (SCMA) systems provide high spectral efficiency (SE) at the expense of using a high number of transmit antennas. To overcome this drawback, this letter proposes a novel SM-SCM A system operating in uplink transmission, referred to as rotational generalized SM-SCMA (RGSM-SCMA). For the proposed system, the f

Qipei Mei, Mustafa Gül

Automatic crack detection on pavement surfaces is an important research field in the scope of developing an intelligent transportation infrastructure system. In this paper, a cost effective solution for road crack inspection by mounting commercial grade sport camera, GoPro, on the rear of the moving vehicle is introduced. Also, a novel method called ConnCrac

Ahmed H. Qureshi, Yinglong Miao, Anthony Simeonov, Michael C. Yip

This paper describes Motion Planning Networks (MPNet), a computationally efficient, learning-based neural planner for solving motion planning problems. MPNet uses neural networks to learn general near-optimal heuristics for path planning in seen and unseen environments. It takes environment information such as raw point-cloud from depth sensors, as well as a

Peter Y. Lu, Samuel Kim, Marin Soljačić

Experimental data is often affected by uncontrolled variables that make analysis and interpretation difficult. For spatiotemporal systems, this problem is further exacerbated by their intricate dynamics. Modern machine learning methods are particularly well-suited for analyzing and modeling complex datasets, but to be effective in science, the result needs t

Sofía Ibarra, Luis Manuel Rivera

In this paper we obtain the automorphism groups of the token graphs of some graphs. In particular we obtain the automorphism group of the $k$-token graph of the path graph $P_n$, for $n\neq 2k$. Also, we obtain the automorphism group of the $2$-token graph of the following graphs: cycle, star, fan and wheel graphs.

Minghui Liao, Boyu Song, Shangbang Long, Minghang He

With the development of deep neural networks, the demand for a significant amount of annotated training data becomes the performance bottlenecks in many fields of research and applications. Image synthesis can generate annotated images automatically and freely, which gains increasing attention recently. In this paper, we propose to synthesize scene text imag

Yu Gu, Xiang Zhang, Zhi Liu, Fuji Ren

The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in genera

Samith Abeywickrama, Rui Zhang, Chau Yuen

Intelligent reflecting surface (IRS) that enables the control of the wireless propagation environment has been looked upon as a promising technology for boosting the spectrum and energy efficiency in future wireless communication systems. Prior works on IRS are mainly based on the ideal phase shift model assuming the full signal reflection by each of the ele

Haining Wang

In this note we study the special fiber of the Rapoport-Zink space attached to a quaternionic unitary group. The special fiber is described using the so called Bruhat-Tits stratification and is intimately related to the Bruhat-Tits building of a split symplectic group. As an application we describe the supersingular locus of the related Shimura variety.

José Simental

We study Harish-Chandra bimodules for the rational Cherednik algebra associated to the symmetric group $S_{n}$. In particular, we show that for any parameter $c \in \mathbb{C}$, the category of Harish-Chandra $H_{c}$-bimodules admits a fully faithful embedding into the category $\mathcal{O}_{c}$, and describe the irreducibles in the image. We also construct