February 2019 arXiv papers — page 103

Satoshi Nakano, Kazuhiko Nishimura

We model sectoral production by serially nesting (cascading) binary compounding processes. The sequence of processes is discovered in a self-similar hierarchical structure stylized in macroscopic input-output transactions. The feedback system of unit cost functions, with recursively estimated nest-wise CES parameters, is calibrated for sectoral productivitie

Hua Zhong, Rong Wang, Milivoj R. Belic, Yanpeng Zhang

We investigate linear and nonlinear evolution dynamics of light beams propagating along a dislocated edge-centered square lattice. The band structure and Brillouin zones of this novel lattice are analyzed analytically and numerically. Asymmetric Dirac cones as well as the corresponding Bloch modes of the lattice are obtained. By adopting the tight-binding ap

Jun Ohkubo, Yuuki Arai

A new derivation method of duality relations in stochastic processes is proposed. The current focus is on the duality between stochastic differential equations and birth-death processes. Although previous derivation methods have been based on the viewpoint of time-evolution operators, the current derivation is based on basis expansions. In addition, only the

Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba

Federated Learning is a distributed machine learning approach which enables model training on a large corpus of decentralized data. We have built a scalable production system for Federated Learning in the domain of mobile devices, based on TensorFlow. In this paper, we describe the resulting high-level design, sketch some of the challenges and their solution

Nikolai Dokuchaev

This paper introduces a new type of second order stochastic backward Hamilton-Jacobi-Bellman (HJB) equations for optimal stochastic control problems with a currently observable but non-predicable parameter process, in addition to the driving Brownian motion. The main feature of this HJB equation is that it excludes specifications of the parameter process whi

Keisuke Mizuta, Yoshiki Ishii, Kang Kim, Nobuyuki Matubayasi

Through molecular dynamics simulations, we examined hydrodynamic behavior of the Brownian motion of fullerene particles based on molecular interactions. The solvation free energy and the velocity autocorrelation function (VACF) were calculated by using the Lennard-Jones (LJ) and Weeks-Chandler-Andersen (WCA) potentials for the solute-solvent and solvent-solv

Georgios Katsimpas

We study the properties of the analogue of R-diagonal operators in the setting of bi-free probability. Products of bi-R-diagonal pairs of operators that are $*$-bi-free are studied and powers of such pairs are found to also be bi-R-diagonal. It is moreover shown that the joint $*$-distribution of a bi-R-diagonal pair of operators remains invariant under the

Alexis G. Page, Mathias Bechert, François Gallaire, Fabien Sorin

Fiber-based devices with advanced functionalities are emerging as promising solutions for various applications in flexible electronics and bioengineering. Multimaterial thermal drawing, in particular, has attracted strong interest for its ability to generate fibers with complex architectures. Thus far, however, the understanding of its fluid dynamics has onl

Robin Belton, Robyn Brooks, Stefania Ebli, Lisbeth Fajstrup

In the directed setting, the spaces of directed paths between fixed initial and terminal points are the defining feature for distinguishing different directed spaces. The simplest case is when the space of directed paths is homotopy equivalent to that of a single path; we call this the trivial space of directed paths. Directed spaces that are topologically t

Sameer Kumar, Shradha Mishra

We study the dynamics of a particle moving in one-dimensional Lorentz lattice-gas where particle performs mainly three different kinds of motion {\it viz} ballistic motion, diffusion and confinement. There are two different types of scatterers, {\it viz} reflector and transmitters, randomly placed in the lattice. Reflectors are such that they reverse the par

Y. Nakajima, T. Metz, C. Eckberg, K. Kirshenbaum

Quantum-mechanical fluctuations between competing phases at $T=0$ induce exotic finite-temperature collective excitations that are not described by the standard Landau Fermi liquid framework. These excitations exhibit anomalous temperature dependences, or non-Fermi liquid behavior, in the transport and thermodynamic properties in the vicinity of a quantum cr

Joshua Gild, Jeffrey Braun, Kevin Kaufmann, Eduardo Marin

A high-entropy metal disilicide, (Mo0.2Nb0.2Ta0.2Ti0.2W0.2)Si2, has been successfully synthesized. X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), and electron backscatter diffraction (EBSD) collectively show the formation of a single high-entropy silicide phase. This high-entropy (Mo0.2Nb0.2Ta0.2Ti0.2W0.2)Si2 possesses a hexagonal C40 c

Haoyu Wang, Ming Tan, Mo Yu, Shiyu Chang

Most approaches to extraction multiple relations from a paragraph require multiple passes over the paragraph. In practice, multiple passes are computationally expensive and this makes difficult to scale to longer paragraphs and larger text corpora. In this work, we focus on the task of multiple relation extraction by encoding the paragraph only once (one-pas

Zeyuan Allen-Zhu, Yuanzhi Li

Recurrent Neural Networks (RNNs) are among the most popular models in sequential data analysis. Yet, in the foundational PAC learning language, what concept class can it learn? Moreover, how can the same recurrent unit simultaneously learn functions from different input tokens to different output tokens, without affecting each other? Existing generalization

Kenji Hashimoto, Taro Sano

We construct non-Kähler simply connected Calabi-Yau 3-folds with arbitrarily large 2nd Betti numbers by smoothing normal crossing varieties with trivial dualizing sheaves.

Jing-Rebecca Li, Van-Dang Nguyen, Try Nguyen Tran, Jan Valdman

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation (BTPDE). A mathematical model for the time-dependent apparent diffusion coefficient (ADC), called the H-ADC model, was obtained recently

Tomohiro Nishiyama

For a measurable function on a set which has a finite measure, an inequality holds between two Lp-norms. In this paper, we show similar inequalities for the Euclidean space and the Lebesgue measure by using a q-moment which is a moment of an escort distribution. As applications of these inequalities, we first derive upper bounds for the Renyi and the Tsallis

Katsuhiko Ishiguro, Shin-ichi Maeda, Masanori Koyama

Graph Neural Network (GNN) is a popular architecture for the analysis of chemical molecules, and it has numerous applications in material and medicinal science. Current lines of GNNs developed for molecular analysis, however, do not fit well on the training set, and their performance does not scale well with the complexity of the network. In this paper, we p

Changqing Ye, Junzhi Cui

This paper is devoted to studying a type of contact problems modeled by hemivariational inequalities with small periodic coefficients appearing in PDEs, and the PDEs we considered are linear, second order and uniformly elliptic. Under the assumptions, it is proved that the original problem can be homogenized, and the solution weakly converges. We derive an $

Masahiro Ikeda, Koichi Taniguchi

The purpose in this paper is to determine the global behavior of solutions to the initial-boundary value problems for energy-subcritical and critical semilinear heat equations by initial data with lower energy than the mountain pass level in energy spaces associated with self-adjoint operators satisfying Gaussian upper bounds. Our self-adjoint operators incl

Guanhao Feng, Jingyu He

This paper investigates asset allocation problems when returns are predictable. We introduce a market-timing Bayesian hierarchical (BH) approach that adopts heterogeneous time-varying coefficients driven by lagged fundamental characteristics. Our approach includes a joint estimation of conditional expected returns and covariance matrix and considers estimati

Zdzislaw Musielak, Niyousha Davachi, Marialis Rosario-Franco

A set of linear second-order differential equations is converted into a semigroup, whose algebraic structure is used to generate many novel equations. Two independent methods that can be used to derive the equations of the semigroup are considered, namely, the Lagrangian formalism and the Lie group approach. The advantages and disadvantages of each method ar

Zdzislaw Musielak, Niyousha Davachi, Marialis Rosario-Franco

Lagrangian formalism is established for differential equations with special functions of mathematical physics as solutions. Formalism is based on either standard or non-standard Lagrangians. This work shows that the procedure of deriving the standard Lagrangians leads to Lagrangians for which the Euler--Lagrange equation vanishes identically, and that only s

Subhrajit Roy, Umar Asif, Jianbin Tang, Stefan Harrer

Accurate classification of seizure types plays a crucial role in the treatment and disease management of epileptic patients. Epileptic seizure types not only impact the choice of drugs but also the range of activities a patient can safely engage in. With recent advances being made towards artificial intelligence enabled automatic seizure detection, the next

Pascal J. Elahi, Rodrigo Cañas, Rhys J. J. Poulton, Rodrigo J. Tobar

We present VELOCIraptor, a massively parallel galaxy/(sub)halo finder that is also capable of robustly identifying tidally disrupted objects and separate stellar halos from galaxies. The code is written in c++11, use the MPI and OpenMP API's for parallelisation, and includes python tools to read/manipulate the data products produced. We demonstrate the p

Peter A. Perry

These notes are a considerably revised and expanded version of expository lectures given at the Fields Institute Workshop on "Nonlinear Dispersive Partial Differential Equations and Inverse Scattering" in August 2017. We give a complete and self-contained treatment of inverse scattering for the defocussing cubic NLS in one-dimension, following the 20

Jose Risomar Sousa

In a previous paper, we saw how to create formulae for the sum of the terms of a harmonic progression of order $k$, $HP_k(n)$, with integer parameters, $a$ and $b$. In this new paper we make those formulae more general by lifting the restriction that the parameters be integers. These new formulae always hold, except when $i b/a\in \mathbb{Z}$. This paper emp

R. Thomas McCoy, Ellie Pavlick, Tal Linzen

A machine learning system can score well on a given test set by relying on heuristics that are effective for frequent example types but break down in more challenging cases. We study this issue within natural language inference (NLI), the task of determining whether one sentence entails another. We hypothesize that statistical NLI models may adopt three fall

Chuan-Ren Chen, Cheng-Wei Chiang, Kuo-Yen Lin

We consider a two-Higgs doublet model extended with a broken Abelian gauge symmetry under which all Standard Model (SM) quarks, fourth generation fermions and a new SM-singlet scalar boson are charged. Such a setup is shown to be able to accommodate the muon anomalous magnetic dipole moment while being consistent with existing constraints of flavor-violating

Poorvi L. Vora

We propose a simple common framework for Risk-Limiting and Bayesian (polling) audits for two-candidate plurality elections. Using it, we derive an expression for the general Bayesian audit; in particular, we do not restrict the prior to a beta distribution. We observe that the decision rule for the Bayesian audit is a simple comparison test, which enables th

J. I. Katz, S. Wang

Flyby images of (486958) Arrokoth (Ultima Thule, 2014 MU$_{69}$) show a comparatively bright "necklace" in the neck, or cleft between its two lobes, in contrast to its generally low albedo. We suggest that the necklace may be the result of thermally controlled ice deposition. The necklace is found in the most (orbitally averaged) shaded part of its s

Yi-An Ma, Niladri Chatterji, Xiang Cheng, Nicolas Flammarion

We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as optimization on the space of probability measures, with Kullback-Leibler (KL) divergence as the objective functional. We show that an underdamped form of the Langevin algorithm performs accelerated gradient descent in this metric. To characterize the convergence of the algorithm, we cons

Manfried Faber, Martin Suda

We discuss that the singularities appearing in Dirac's formulation of magnetic monopoles are due to the set of fields which he used and not due to the physical properties of magnetic monopoles. We explain in detail that we can find the same algebraic expressions and singularities for the affine connections on the sphere $S^2$, which Dirac found for the U

L. V. Androshchuk, Aidan Rooney

Airline route planning takes into account the factors of commercial and customer preferences, safety, and should allow a flexibility given the tremendous uncertainty about market conditions. The mathematical model on the Bayes formula allows optimizing the interaction of the base factors.

Amit Kumar, Tanya Ahuja, Rajesh Kumar Madabhattula, Murali Kante

With exponential increase in the availability oftelemetry / streaming / real-time data, understanding contextualbehavior changes is a vital functionality in order to deliverunrivalled customer experience and build high performance andhigh availability systems. Real-time behavior change detectionfinds a use case in number of domains such as social networks,ne

Wanming Huang, Yida Xu, Ian Oppermann

The Generative Adversarial Network (GAN) has recently been applied to generate synthetic images from text. Despite significant advances, most current state-of-the-art algorithms are regular-grid region based; when attention is used, it is mainly applied between individual regular-grid regions and a word. These approaches are sufficient to generate images tha

Guoqiang Zhang, Haopeng Li, Fabian Wenger

This paper considers object detection and 3D estimation using an FMCW radar. The state-of-the-art deep learning framework is employed instead of using traditional signal processing. In preparing the radar training data, the ground truth of an object orientation in 3D space is provided by conducting image analysis, of which the images are obtained through a c

Xu Zhao, Zongli Jiang

This paper considers the problem of nonlinear dimensionality reduction. Unlike existing methods, such as LLE, ISOMAP, which attempt to unfold the true manifold in the low dimensional space, our algorithm tries to preserve the nonlinear structure of the manifold, and shows how the manifold is folded in the high dimensional space. We call this method Tangent D

Reza Ghaffari, Farzad Shirazian, Ming Hu, Roger A. Sauer

A new hyperelastic membrane material model is proposed for single layer blue phosphorus ($β\text{-P}$), also known as blue phosphorene. The model is fully nonlinear and captures the anisotropy of $β\text{-P}$ at large strains. The material model is calibrated from density functional theory (DFT) calculations considering a set of elementary deformation states

D. Valim, AG Souza Filho, J M Filho, OL Alves

We have performed the LiTaWO$_6$ vibrational studies for both Raman and infrared actives modes. Although we do not have crystalline samples, the study was conducted qualitatively, firstly comparing the sample with similar compounds in the literature, and secondly comparing both Raman and infrared spectra of the LiTaWO$_6$ compound. Although the procedure is

Hakime Öztürk, Elif Ozkirimli, Arzucan Özgür

Motivation: Prediction of the interaction affinity between proteins and compounds is a major challenge in the drug discovery process. WideDTA is a deep-learning based prediction model that employs chemical and biological textual sequence information to predict binding affinity. Results: WideDTA uses four text-based information sources, namely the protein seq

Barbara Pacchiarotti, Alessandro Pigliacelli

The problem of (pathwise) large deviations for conditionally continuous Gaussian processes is investigated. The theory of large deviations for Gaussian processes is extended to the wider class of random processes -- the conditionally Gaussian processes. The estimates of level crossing probability for such processes are given as an application.

Abdulhameed Qahtan Abbood Altai

In this paper, we propose the theory of fuzzy limit of fuzzy function depending on the Altai principle and using the representation theorem (resolution principle) to run the fuzzy arithmetic

Svitlana Alkhimova

In perfusion analysis automated approaches for image processing is preferable due to reduce time-consuming tasks for radiologists. Assessment of perfusion results quality is important step in development of algorithms for automated processing. One of them is an assessment of perfusion maps quality based on detection of perfusion ROI.

Giuseppe C. Ng

Purpose - The research aims to show the relevance of company client sponsored student projects in the University of Asia and the Pacific Information Technology (UA&P IT) Capstone Program through the use ofan Agile Methodology with Scrum Approach. Method - The modified program is employed on two batches with content analysis and survey results as benchmarks.

Ken-Ichi Aoki, Tamao Kobayashi, Shin-Ichiro Kumamoto, Shinnosuke Onai

We propose a new iterative method to directly calculate the spontaneous mass generation. It is regarded as a new regularization method resembling the finite volume calculation which assures non-negative fluctuation property at every stage. We work with the Nambu--Jona-Lasinio model and the strong coupling gauge theory where the dynamical chiral symmetry brea

Hassan Jameel Asghar, Ming Ding, Thierry Rakotoarivelo, Sirine Mrabet

We propose a generic mechanism to efficiently release differentially private synthetic versions of high-dimensional datasets with high utility. The core technique in our mechanism is the use of copulas. Specifically, we use the Gaussian copula to define dependencies of attributes in the input dataset, whose rows are modelled as samples from an unknown multiv

Mikil D. Foss, Petronela Radu, Cory Wright

In this paper we consider minimizers for nonlocal energy functionals generalizing elastic energies that are connected with the theory of peridynamics \cite{Silling2000} or nonlocal diffusion models \cite{Rossi}. We derive nonlocal versions of the Euler-Lagrange equations under two sets of growth assumptions for the integrand. Existence of minimizers is shown

Eshan Singh, Keerthikumara Devarajegowda, Sebastian Simon, Ralf Schnieder

We present an industrial case study that demonstrates the practicality and effectiveness of Symbolic Quick Error Detection (Symbolic QED) in detecting logic design flaws (logic bugs) during pre-silicon verification. Our study focuses on several microcontroller core designs (~1,800 flip-flops, ~70,000 logic gates) that have been extensively verified using an

Marco A. Galvani Cunha, Mark O. Robbins

The Newtonian viscosity of 2,2,4-trimethylhexane at 293K is determined at pressures from 0.1MPa to 1000MPa. Non-equilibrium molecular dynamics simulations are performed using AIREBO-M, an all-atom potential for hydrocarbons especially parameterized for high pressures. The steady-state shear stress and viscosity are determined from simple shear simulations at

Arthur Stoutchinin, Francesco Conti, Luca Benini

Embedded inference engines for convolutional networks must be parsimonious in memory bandwidth and buffer sizing to meet power and cost constraints. We present an analytical memory bandwidth model for loop-nest optimization targeting architectures with application managed buffers. We applied this model to optimize the CNN convolution loop-nest. We show that

Andrés Flórez, Alfredo Gurrola, Will Johns, Jessica Maruri

Dark matter that is electrically neutral but couples to the electromagnetic current through higher-dimensional operators constitutes an interesting class of models. We investigate this class of models at the Large Hadron Collider, focusing on the anapole moment operator in an effective field theory (EFT) framework, and utilizing the vector boson fusion (VBF)

Ivo Düntsch, Günther Gediga

A widespread approach in machine learning to evaluate the quality of a classifier is to cross -- classify predicted and actual decision classes in a confusion matrix, also called error matrix. A classification tool which does not assume distributional parameters but only information contained in the data is based on the rough set data model which assumes tha

Diego Cifuentes, Shmuel Onn

We investigate the computational complexity of problems on toric ideals such as normal forms, Gröbner bases, and Graver bases. We show that all these problems are strongly NP-hard in the general case. Nonetheless, we can derive efficient algorithms by taking advantage of the sparsity pattern of the matrix. We describe this sparsity pattern with a graph, and

Nikolaj Tatti, Aristides Gionis

Finding communities in graphs is one of the most well-studied problems in data mining and social-network analysis. In many real applications, the underlying graph does not have a clear community structure. In those cases, selecting a single community turns out to be a fairly ill-posed problem, as the optimization criterion has to make a difficult choice betw

Efthymios Tzinis

In this work, a unified framework for gradient-free Multidimensional Scaling (MDS) based on Coordinate Search (CS) is proposed. This family of algorithms is an instance of General Pattern Search (GPS) methods which avoid the explicit computation of derivatives but instead evaluate the objective function while searching on coordinate steps of the embedding sp

Katiana Kontolati, Constantinos Siettos

We perform one and two-parameter numerical bifurcation analysis of a mechanotransduction model approximating the dynamics of mesenchymal stem cell differentiation into neurons, adipocytes, myocytes and osteoblasts. For our analysis, we use as bifurcation parameters the stiffness of the extracellular matrix and parameters linked with the positive feedback mec

Nikolaj Tatti, Taneli Mielikainen, Aristides Gionis, Heikki Mannila

Many 0/1 datasets have a very large number of variables; on the other hand, they are sparse and the dependency structure of the variables is simpler than the number of variables would suggest. Defining the effective dimensionality of such a dataset is a nontrivial problem. We consider the problem of defining a robust measure of dimension for 0/1 datasets, an

Yu. D. Panov, A. S. Moskvin

The continuous quasi-classical two-sublattice approximation is constructed for the 2D system of charged hard-core bosons to explore metastable inhomogeneous states analogous to inhomogeneous localized excitations in magnetic systems. The types of localized excitations are determined by asymptotic analysis and compared with numerical results. Depending on the

Nikolaj Tatti

Many real-world phenomena exhibit strong hierarchical structure. Consequently, in many real-world directed social networks vertices do not play equal role. Instead, vertices form a hierarchy such that the edges appear mainly from upper levels to lower levels. Discovering hierarchies from such graphs is a challenging problem that has gained attention. Formall

D. Dikranjan, I. Protasov, N. Zava

In this paper we define some ballean structure on the power set of a group and, in particular, we study the subballean with support the lattice of all its subgroups. If $G$ is a group, we denote by $L(G)$ the family of all subgroups of $G$. For two groups $G$ and $H$, we relate their algebraic structure via the ballean structure of $L(G)$ and $L(H)$.

D. Dikranjan, I. Protasov, K. Protasova, N. Zava

A ballean $\mathcal{B}$ (or a coarse structure) on a set $X$ is a family of subsets of $X$ called balls (or entourages of the diagonal in $X\times X$) defined in such a way that $\mathcal{B}$ can be considered as the asymptotic counterpart of a uniform topological space. The aim of this paper is to study two concrete balleans defined by the ideals in the Boo

Marcos salvai

Self dual symmetric R-spaces have special curves, called circles, introduced by Burstall, Donaldson, Pedit and Pinkall in 2011, whose definition does not involve the choice of any Riemannian metric. We characterize the elements of the big transformation group G of a self dual symmetric R-space M as those diffeomorphisms of M sending circles in circles. Besid

Chenge Li, Gregory Dobler, Xin Feng, Yao Wang

Object detection and object tracking are usually treated as two separate processes. Significant progress has been made for object detection in 2D images using deep learning networks. The usual tracking-by-detection pipeline for object tracking requires that the object is successfully detected in the first frame and all subsequent frames, and tracking is done

Behdad Davoudi, Ehsan Taheri, Karthik Duraisamy, Balaji Jayaraman

In trajectory planning and control design for unmanned air vehicles, highly simplified models are typically used to represent the vehicle dynamics and the operating environment. The goal of this work is to perform real-time, but realistic flight simulations and trajectory planning for quad-copters in low altitude (<500m) atmospheric conditions. The aerodynam

R Deno Stelter, Stephen S Eikenberry

We present the innovative macro-slicer optical and opto-mechanical designs for the third-generation Mid-resolution InfraReD Astronomical Spectrograph (MIRADAS) instrument for the 10.4m Gran Telescopio Canarias (GTC) in the 1-2.5 $μ$m bandpass. MIRADAS uses up to 12 cryogenic, fully steerable probes to select simultaneous targets in a 5 arcminute field of vie

Hongxia Hao, Brenda M. Rubenstein, Hao Shi

In the study of strongly-correlated, many-electron systems, the Hubbard Kanamori (HK) model has emerged as one of the prototypes for transition metal oxide physics. The model is multi-band in nature and contains Hund&#39;s coupling terms, which have pronounced effects on metal-insulator transitions, high-temperature superconductivity, and other physical prop

Mohammad Javad Amiri, Divyakant Agrawal, Amr El Abbadi

Many existing blockchains do not adequately address all the characteristics of distributed system applications and suffer from serious architectural limitations resulting in performance and confidentiality issues. While recent permissioned blockchain systems, have tried to overcome these limitations, their focus has mainly been on workloads with no-contentio

Ariel Barel, Rotem Manor, Alfred M. Bruckstein

This report surveys results on distributed systems comprising mobile agents that are identical and anonymous, oblivious and interact solely by adjusting their motion according to the relative location of their neighbours. The agents are assumed capable of sensing the presence of other agents within a given sensing range and able to implement rules of motion

Stavros Akras, Lizette Guzman-Ramirez, Marcelo L. Leal-Ferreira, Gerardo Ramos-Larios

We present a new census of Galactic and extragalactic symbiotic stars (SySts). This compilation contains 323 known and 87 candidate SySts. Of the confirmed SySts, 257 are Galactic and 66 extragalactic. The spectral energy distributions (SEDs) of 348 sources have been constructed using 2MASS and AllWISE data. Regarding the Galactic SySts, 74% are S-types, 13%

Baruch Epstein, Ron Meir

Autoencoders are widely used for unsupervised learning and as a regularization scheme in semi-supervised learning. However, theoretical understanding of their generalization properties and of the manner in which they can assist supervised learning has been lacking. We utilize recent advances in the theory of deep learning generalization, together with a nove

BESIII Collaboration, M. Ablikim, M. N. Achasov, S. Ahmed

Using a data sample of $448.1\times10^6$ $ψ(3686)$ events collected at $\sqrt{s}=$ 3.686 GeV with the BESIII detector at the BEPCII, we search for the rare decay $J/ψ\to ϕe^+ e^-$ via $ψ(3686) \to π^+π^- J/ψ$. No signal events are observed and the upper limit on the branching fraction is set to be $\mathcal{B}(J/ψ\to ϕe^+ e^-) < 1.2 \times 10^{-7}$ at the 90

Christian Klingenberg, Simon Markfelder

In this note we consider the ideal compressible magneto-hydrodynamics (MHD) equations in a special two dimensional setting. We show that there exist particular initial data for which one obtains infinitely many entropy-conserving weak solutions by using the convex integration technique. Our result is also true for the isentropic case.

Trupti Mayee Behera, Sushanta Kumar Mohapatra, Umesh Chandra Samal, Mohammad. S. Khan

Wireless sensor networks (WSN) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important

Eric Angelini, Lars Blomberg, Charlie Neder, Remy Sigrist

The &#34;Choix de Bruxelles&#34; operation replaces a positive integer n by any of the numbers that can be obtained by halving or doubling a substring of the decimal representation of n. For example, 16 can become any of 16, 26, 13, 112, 8, or 32. We investigate the properties of this interesting operation and its iterates.

Eli Sherman, Ilya Shpitser

The assumption that data samples are independent and identically distributed (iid) is standard in many areas of statistics and machine learning. Nevertheless, in some settings, such as social networks, infectious disease modeling, and reasoning with spatial and temporal data, this assumption is false. An extensive literature exists on making causal inference

Chenge Li, Weixi Zhang, Yong Liu, Yao Wang

360-degree videos have gained increasing popularity in recent years with the developments and advances in Virtual Reality (VR) and Augmented Reality (AR) technologies. In such applications, a user only watches a video scene within a field of view (FoV) centered in a certain direction. Predicting the future FoV in a long time horizon (more than seconds ahead)

Monica Guica

The $J\bar T$ deformation, built from the components of the stress tensor and of a $U(1)$ current, is a universal irrelevant deformation of two-dimensional CFTs that preserves the left-moving conformal symmetry, while breaking locality on the right-moving side. Operators in the $J\bar T$-deformed CFT are naturally labeled by the left-moving position and righ

B. M. Rose, P. M. Garnavich, M. A. Berg

The reliability of Type Ia supernovae (SNIa) may be limited by the imprint of their galactic origins. To investigate the connection between supernovae and their host characteristics, we developed an improved method to estimate the stellar population age of the host as well as the local environment around the site of the supernova. We use a Bayesian method to

Xiumin Du, Jongchon Kim, Hong Wang, Ruixiang Zhang

We give new lower bounds for $L^p$ estimates of the Schrödinger maximal function by generalizing an example of Bourgain.

Jérémy Sok, Jan Philip Solovej

We study the spectral flow of Dirac operators with magnetic links on $\mathbb{S}^3$. These are generalisations of Aharonov-Bohm solenoids where the magnetic fields contain finitely many field lines coinciding with the components of a link, the flux of each exhibiting the same $2π$-periodicity as A-B solenoids. We study the spectral flow of the loop obtained

S. D Odintsov, V. K. Oikonomou

In this paper we study the effects of spatial curvature of the metric on the phase space of vacuum $f(R)$ gravity. Particularly, we appropriately choose the variables of the dynamical system, in order for this to be autonomous, and we study the phase space of the resulting theory, focusing on de Sitter, matter and radiation domination fixed points. Our analy

Volodymyr P. Kravchuk, Ulrich K. Rößler, Jeroen van den Brink, Markus Garst

Chiral magnets possess topological line excitations where the magnetization within each cross section forms a skyrmion texture. We study analytically and numerically the low-energy, non-linear dynamics of such a skyrmion string in a field-polarized cubic chiral magnet, and we demonstrate that it supports solitary waves. Theses waves are in general non-recipr

S. S. Larsen, H. Baumgardt, N. Bastian, S. Hernandez

We present new deep imaging of the central regions of the remote globular cluster NGC 2419, obtained with the F343N and F336W filters of HST/WFC3. The new data are combined with archival imaging to constrain nitrogen and helium abundance variations within the cluster. We find a clearly bimodal distribution of the nitrogen-sensitive F336W-F343N colours of red

Tankut Can, Vadim Oganesyan, Dror Orgad, Sarang Gopalakrishnan

We discuss the decay rates of chaotic quantum systems coupled to noise. We model both the Hamiltonian and the system-noise coupling by random $N \times N$ Hermitian matrices, and study the spectral properties of the resulting Lindblad superoperator. We consider various random-matrix ensembles, and find that for all of them the asymptotic decay rate remains n

Nimisha Kumari, Roberto Maiolino, Francesco Belfiore, Mirko Curti

Using integral field spectroscopic data of 24 nearby spiral galaxies obtained with the Multi-Unit Spectroscopic Explorer (MUSE), we derive empirical calibrations to determine the metallicity of the diffuse ionized gas (DIG) and/or of the low-ionisation emission region (LI(N)ER) in passive regions of galaxies. To do so, we identify a large number of HII--DIG/

Lucas Thiel, Zhe Wang, Märta A. Tschudin, Dominik Rohner

The recent discovery of ferromagnetism in 2D van der Waals (vdw) crystals has generated widespread interest, owing to their potential for fundamental and applied research. Advancing the understanding and applications of vdw magnets requires methods to quantitatively probe their magnetic properties on the nanoscale. Here, we report the study of atomically thi

I. Yudhistira, N. Chakraborty, G. Sharma, D. Y. H. Ho

Recent experiments on twisted bilayer graphene (tBG) close to magic angle show that a small relative rotation in a van der Waals heterostructure greatly alters its electronic properties. We consider various scattering mechanisms and show that the carrier transport in tBG is dominated by a combination of charged impurities and acoustic gauge phonons. Charged

Thomas Berlok, Christoph Pfrommer

The Kelvin-Helmholtz instability (KHI) is a standard test of hydrodynamic and magnetohydrodynamic (MHD) simulation codes and finds many applications in astrophysics. The classic linear theory considers a discontinuity in density and velocity at the interface of two fluids. However, for numerical simulations of the KHI such initial conditions do not yield con

C. Dickey, M. Geha, A. Wetzel, K. El-Badry

We investigate the lowest-mass quiescent galaxies known to exist in isolated environments ($\mathrm{M^* = 10^{9.0-9.5} \ M_\odot}$; 1.5 Mpc from a more massive galaxy). This population may represent the lowest stellar mass galaxies in which internal feedback quenches galaxy-wide star formation. We present Keck/ESI long-slit spectroscopy for 27 isolated galax

Wajih Ullah Baig, Adeel Ejaz, Umar Munir, Kashif Sardar

In Biometric identification, fingerprints based identification has been the widely accepted mechanism. Automated fingerprints identification/verification techniques are widely adopted in many civilian and forensic applications. In forensic applications fingerprints are usually incomplete, broken, unclear or degraded which are known as partial fingerprints. F

Jennifer Hinton, Donnie Maclurcan

In this book, we outline a model of a non-capitalist market economy based on not-for-profit forms of business. This work presents both a critique of the current economic system and a vision of a more socially, economically, and ecologically sustainable economy. The point of departure is the purpose and profit-orientation embedded in the legal forms used by b

A. M. Ishkhanyan, V. P. Krainov

We have obtained the uncertainty relations for arbitrary states of the hydrogen atom. It is shown that the minimal value of the uncertainty relation is attained for the circular Rydberg states.

A. Yamin, M. Dayan, L. Squarcina, P. Brambilla

fMRI is a unique non-invasive approach for understanding the functional organization of the human brain, and task-based fMRI promotes identification of functionally relevant brain regions associated with a given task. Here, we use fMRI (using the Poffenberger Paradigm) data collected in mono- and dizygotic twin pairs to propose a novel approach for assessing

Javid Naikoo, Supriyo Dutta, Subhashish Banerjee

We consider two non-Markovian models: Random Telegraph Noise (RTN) and non-Markovian dephasing (NMD). The memory in these models is studied from the perspective of quantum Fisher information flow. This is found to be consistent with the other well known witnesses of non-Markovianity. The two noise channels are characterized quantum information theoretically

Yuan Chen, Wei-Guan Shen, Zhan-Ming Li, Cheng-Qiu Hu

As an emerging channel resource for modern optics, big data, internet traffic and quantum technologies, twisted photons carrying orbital angular momentum (OAM) have been extended their applicable boundary in different media, such as optical fiber and atmosphere. Due to the extreme condition of loss and pressure, underwater transmission of twisted photons has

Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh

Recent efforts on training visual navigation agents conditioned on language using deep reinforcement learning have been successful in learning policies for different multimodal tasks, such as semantic goal navigation and embodied question answering. In this paper, we propose a multitask model capable of jointly learning these multimodal tasks, and transferri

Carlos De la Cruz Mengual, Tobias Hartnick

We show that continuous bounded group cohomology stabilizes along the sequences of real or complex symplectic Lie groups, and deduce that bounded group cohomology stabilizes along sequences of lattices in them, such as $(\mathrm{Sp}_{2r}(\mathbb{Z}))_{r \geq 1}$ or $(\mathrm{Sp}_{2r}(\mathbb{Z}[i]))_{r \geq 1}$. Our method is based on a general stability cri

Ivan P. Loboda, Sergej A. Bogachev

Macrospicules are typically described as solar jets that are larger and longer-lived than spicules, and visible mostly in transition-region spectral lines. They show a broad variation in properties, which pose substantial difficulties for their identification, modelling, and the understanding of their role in the mass and energy balance of the solar atmosphe

Forrest W. Crawford, Olga Morozova, Ashley L. Buchanan, Donna Spiegelman

Some interventions may include important spillover or dissemination effects between study participants. For example, vaccines, cash transfers, and education programs may exert a causal effect on participants beyond those to whom individual treatment is assigned. In a recent paper, Buchanan et al. provide a causal definition of the &#34;individual effect&#34;