February 2019 arXiv papers — page 44

Davide Riccobelli, Davide Ambrosi

The mathematical modeling of the contraction of a muscle is a crucial problem in biomechanics. Several different models of muscle activation exist in literature. A possible approach to contractility is the so-called active strain: it is based on a multiplicative decomposition of the deformation gradient into an active contribution, accounting for the muscle

Christian Kraglund Andersen, Ants Remm, Stefania Balasiu, Sebastian Krinner

Fault tolerant quantum computing relies on the ability to detect and correct errors, which in quantum error correction codes is typically achieved by projectively measuring multi-qubit parity operators and by conditioning operations on the observed error syndromes. Here, we experimentally demonstrate the use of an ancillary qubit to repeatedly measure the $Z

R. I. Woodward, M. R. Majewski, N. Macadam, G. Hu

We report high-energy mid-infrared pulse generation by Q-switching of dysprosium-doped fiber lasers for the first time. Two different modulation techniques are demonstrated. Firstly, using active acousto-optic modulation, pulses are produced with up to 12 μJ energy and durations as short as 270 ns, with variable repetition rates from 100 Hz to 20 kHz and cen

Daniel B. S. Soh, Ryotatsu Yanagimoto, Eric Chatterjee, Hideo Mabuchi

We present a theoretical study of the optical response of a nonlinear oscillator formed by coupling a metal nanoparticle local surface plasmon resonance to excitonic degrees of freedom in a monolayer transition-metal dichalcogenide. We show that the combined system should exhibit strong anharmonicity in its low-lying states, predicting for example a seven or

Zhenyu Wang, Wei Zheng, Chunfeng Song

Environmental air quality affects people's life, obtaining real-time and accurate environmental air quality has a profound guiding significance for the development of social activities. At present, environmental air quality measurement mainly adopts the method that setting air quality detector at specific monitoring points in cities and timing sampling a

Nicole Bäuerle, Tomer Shushi

We generalize Quasi-Linear Means by restricting to the tail of the risk distribution and show that this can be a useful quantity in risk management since it comprises in its general form the Value at Risk, the Tail Value at Risk and the Entropic Risk Measure in a unified way. We then investigate the fundamental properties of the proposed measure and show its

Takeshi Morita

Recently the bound on the Lyapunov exponent $λ_L \le 2πT/ \hbar$ in thermal quantum systems was conjectured by Maldacena, Shenker, and Stanford. If we naively apply this bound to a system with a fixed Lyapunov exponent $λ_L$, it might predict the existence of the lower bound on temperature $T \ge \hbar λ_L/ 2π$. Particularly, it might mean that chaotic syste

Ahmed Kord, Mykhailo Tymchenko, Dimitrios Sounas, Harish Krishnaswamy

In this paper, we introduce the first integrated circuit (IC) implementation of spatiotemporally modulated angular-momentum (STM-AM) biased magnetless circulators. The design is based on a modified current-mode topology which is less sensitive to parasitics and relies on switched capacitors rather than varactors to achieve the desired modulation, thus reduci

Daniele Bartolucci, Changfeng Gui, Yeyao Hu, Aleks Jevnikar

We are concerned with the blow-up analysis of mean field equations. It has been proven in [6] that solutions blowing-up at the same non-degenerate blow-up set are unique. On the other hand, the authors in [18] show that solutions with a degenerate blow-up set are in general non-unique. In this paper we first prove that evenly symmetric solutions on a flat to

Daniele Dona

Following partially a suggestion by Pyber, we prove that the diameter of a product of non-abelian finite simple groups is bounded linearly by the maximum diameter of its factors. For completeness, we include the case of abelian factors and give explicit constants in all bounds.

Julie Josse, Jacob M. Chen, Nicolas Prost, Erwan Scornet

In many application settings, the data have missing entries which make analysis challenging. An abundant literature addresses missing values in an inferential framework: estimating parameters and their variance from incomplete tables. Here, we consider supervised-learning settings: predicting a target when missing values appear in both training and testing d

Tan Van Vu, Yoshihiko Hasegawa

The thermodynamic uncertainty relation, which establishes a universal trade-off between nonequilibrium current fluctuations and dissipation, has been found for various Markovian systems. However, this relation has not been revealed for non-Markovian systems; therefore, we investigate the thermodynamic uncertainty relation for time-delayed Langevin systems. W

Andrey R. Kolovsky, Dima L. Shepelyansky

We study depletion dynamics of an open system of weakly interacting fermions with two-body random interactions. In this model fermions are escaping from the high-energy one-particle orbitals, that mimics the evaporation process used in laboratory experiments with neutral atoms to cool them to ultra-low temperatures. It is shown that due to dynamical thermali

Ken Kikuchi

We study conformal field theories (CFTs) on curved spaces including both orientable and unorientable manifolds possibly with boundaries. We first review conformal transformations on curved manifolds. We then compute the identity components of conformal groups acting on various metric spaces using a simple fact; given local coordinate systems be single-valued

Chang Chi Kwong, Eng Aik Chan, Syed Abdullah Aljunid, Rustem Shakhmuratov

Band-resolved frequency modulation spectroscopy is a common method to measure weak signals of radiative ensembles. When the optical depth of the medium is large, the signal drops exponentially and the technique becomes ineffective. In this situation, we show that a signal can be recovered when a larger modulation index is applied. Noticeably, this signal can

Venkata Pavan Kumar Miriyala, Zhifeng Zhu, Gengchiau Liang, Xuanyao Fong

Recent progress in all-electrical nucleation, detection and manipulation of magnetic skyrmions has unlocked the tremendous potential of skyrmion-based spintronic devices. Here, we show via micromagnetic simulations that the stable magnetic oscillations of STNO radiate spin waves (SWs) that can be scattered in the presence of skyrmions in the near vicinity. I

Bumsuk Ko, Jee Woo Park, Y. Shin

Near a continuous phase transition, systems with different microscopic origins display universal dynamics if their underlying symmetries are compatible. In a thermally quenched system, the Kibble-Zurek mechanism for the creation of topological defects unveils this universality through a characteristic power-law exponent, which captures the dependence of the

Wei Chen, Hai-Zhou Lu, Oded Zilberberg

New materials such as nodal-line semimetals offer a unique setting for novel transport phenomena. Here, we calculate the quantum correction to conductivity in a disordered nodal-line semimetal. The torus-shaped Fermi surface and encircled $π$ Berry flux carried by the nodal loop result in a fascinating interplay between the effective dimensionality of electr

Seojin Bang, Pengtao Xie, Heewook Lee, Wei Wu

Interpretable machine learning has gained much attention recently. Briefness and comprehensiveness are necessary in order to provide a large amount of information concisely when explaining a black-box decision system. However, existing interpretable machine learning methods fail to consider briefness and comprehensiveness simultaneously, leading to redundant

Matthew Brennan, Guy Bresler, Wasim Huleihel

In the general submatrix detection problem, the task is to detect the presence of a small $k \times k$ submatrix with entries sampled from a distribution $\mathcal{P}$ in an $n \times n$ matrix of samples from $\mathcal{Q}$. This formulation includes a number of well-studied problems, such as biclustering when $\mathcal{P}$ and $\mathcal{Q}$ are Gaussians an

Chunming Zheng, Arkady Pikovsky

We show that \emph{stochastic bursting} is observed in a ring of unidirectional delay-coupled noisy excitable systems, thanks to the combinational action of time-delayed coupling and noise. Under the approximation of timescale separation, i.e., when the time delays in each connection are much larger than the characteristic duration of the spikes, the observe

Yuji Ito, Yukihiro Tadokoro

A nanoscale receiver utilizing the cantilever of a carbon nanotube has been developed to detect phase information included in transmitted signals. The existing receiver consists of a phase detector and demodulator which employ a reference wave and carrier signal, respectively. This paper presents a design method to simplify the receiver in structure with enh

Shaojie Xu, Sihan Zeng, Justin Romberg

Deep learning models have significantly improved the visual quality and accuracy on compressive sensing recovery. In this paper, we propose an algorithm for signal reconstruction from compressed measurements with image priors captured by a generative model. We search and constrain on latent variable space to make the method stable when the number of compress

Daniel S. Gianola, T. Ben Britton, Stefan Zaefferer

Defects in crystalline materials control the properties of materials, and their characterization focuses our strategies to optimize performance. Electron microscopy has served as the backbone of our understanding of defect structure and their interactions owing to beneficial spatial resolution and contrast mechanisms that enable direct imaging of defects. Th

Jason Hartline, Aleck Johnsen, Denis Nekipelov, Zihe Wang

Econometric inference allows an analyst to back out the values of agents in a mechanism from the rules of the mechanism and bids of the agents. This paper gives an algorithm to solve the problem of inferring the values of agents in a dominant-strategy mechanism from the social choice function implemented by the mechanism and the per-unit prices paid by the a

Biswanath Rath

We propose a model CCS (complex-conjugate-space) to understand the inner and outer product nature of wave functions in non-hermitian PT-symmetry model in quantum mechanics considering (NxN) matrix model. Further we reflect the correct nature of C-symmetry ,P-parity and original Hamiltonian matrix for any arbitrary values of N. Interestingly the present resul

Jun Ueki

We discuss the relationship between two analogues in a 3-manifold of the set of prime ideals in a number field. We prove that if $(K_i)_{i\in \mathbb{N}_{>0}}$ is a sequence of knots obeying the Chebotarev law in the sense of Mazur and McMullen, then $\mathcal{K}=\cup_i K_i$ is a stably generic link in the sense of Mihara. An example we investigate is the pl

Qiang Wen

The Entanglement contour function quantifies the contribution from each degree of freedom in a region $\mathcal{A}$ to the entanglement entropy $S_{\mathcal{A}}$. Recently in \cite{Wen:2018whg} the author gave two proposals for the entanglement contour in two-dimensional theories. The first proposal is a fine structure analysis of the entanglement wedge whic

Shubham Gupta, Ambedkar Dukkipati

Humans use language to collectively execute abstract strategies besides using it as a referential tool for identifying physical entities. Recently, multiple attempts at replicating the process of emergence of language in artificial agents have been made. While existing approaches study emergent languages as referential tools, in this paper, we study their ro

Abdullah Al-Dujaili, Una-May O'Reilly

We present a black-box adversarial attack algorithm which sets new state-of-the-art model evasion rates for query efficiency in the $\ell_\infty$ and $\ell_2$ metrics, where only loss-oracle access to the model is available. On two public black-box attack challenges, the algorithm achieves the highest evasion rate, surpassing all of the submitted attacks. Si

Samuel Thomas, Ana Hayne, Jonad Pulaj, Hammurabi Mendes

We present a data partitioning technique performed over skip graphs that promotes significant quantitative and qualitative improvements on NUMA locality in concurrent data structures, as well as reduced contention. We build on previous techniques of thread-local indexing and laziness, and, at a high level, our design consists of a partitioned skip graph, wel

G. Cacciapaglia, G. Ferretti, T. Flacke, H. Serôdio

A composite Higgs boson is likely to be accompanied by additional light states generated by the same dynamics. This expectation is substantiated when realising the composite Higgs mechanism by an underlying gauge theory. We review the dynamics of such objects, which may well be the first sign of compositeness at colliders. We also update our previous analysi

James Stokes, John Terilla

Inspired by the possibility that generative models based on quantum circuits can provide a useful inductive bias for sequence modeling tasks, we propose an efficient training algorithm for a subset of classically simulable quantum circuit models. The gradient-free algorithm, presented as a sequence of exactly solvable effective models, is a modification of t

Maryna L. Meretska, Gilles Vissenberg, Ad Lagendijk, Wilbert L. IJzerman

Lighting is a crucial technology that is used every day. The introduction of the white light emitting diode (LED) that consists of a blue LED combined with a phosphor layer, greatly reduces the energy consumption for lighting. Despite the fast-growing market white LED's are still designed using slow, numerical, trial-and-error algorithms. Here we introduce a

Jean-Pierre Fouque, Ruimeng Hu

Empirical studies indicate the presence of multi-scales in the volatility of underlying assets: a fast-scale on the order of days and a slow-scale on the order of months. In our previous works, we have studied the portfolio optimization problem in a Markovian setting under each single scale, the slow one in [Fouque and Hu, SIAM J. Control Optim., 55 (2017),

Zac Cranko, Robert C. Williamson, Richard Nock

The study of a machine learning problem is in many ways is difficult to separate from the study of the loss function being used. One avenue of inquiry has been to look at these loss functions in terms of their properties as scoring rules via the proper-composite representation, in which predictions are mapped to probability distributions which are then score

Chieh-Yu Chang, Nathan Green, Yoshinori Mishiba

For each positive characteristic multiple zeta value (defined by Thakur), the first and third authors constructed a $t$-module together with an algebraic point such that a specified coordinate of the logarithmic vector of the algebraic point is a rational multiple of that multiple zeta value. The objective of this paper is to use the Taylor coefficients of A

Jeffrey Manning

We use the Taylor-Wiles-Kisin patching method to investigate the multiplicities with which Galois representations occur in the mod $\ell$ cohomology of Shimura curves over totally real number fields. Our method relies on explicit computations of local deformation rings done by Shotton, which we use to compute the Weil class group of various deformation rings

Nil Mamano, Alon Efrat, David Eppstein, Daniel Frishberg

We show new applications of the nearest-neighbor chain algorithm, a technique that originated in agglomerative hierarchical clustering. We apply it to a diverse class of geometric problems: we construct the greedy multi-fragment tour for Euclidean TSP in $O(n\log n)$ time in any fixed dimension and for Steiner TSP in planar graphs in $O(n\sqrt{n}\log n)$ tim

James P. Edwards, Mariana Kirchbach

We construct the Rarita-Schwinger basis vectors, $U^μ$, spanning the direct product space, $U^μ:=A^μ\otimes u_M$, of a massless four-vector, $ A^μ$, with massless Majorana spinors, $u_M$, together with the associated field-strength tensor, ${\mathcal T}^{μν}:=p^μU^ν-p^νU^μ$. The ${\mathcal T}^{μν}$ space is reducible and contains one massless subspace of a p

Pablo E. Baldivieso, J. J. P. Veerman

In this paper, we give necessary conditions for stability of coupled autonomous vehicles in R. We focus on linear arrays with decentralized vehicles, where each vehicle interacts with only a few of its neighbors. We obtain explicit expressions for necessary conditions for stability in the cases that a system consists of a periodic arrangement of two or three

Yao Zhou, Hongxuan Zhu, I. Y. Dodin

The dynamics of the radial envelope of a weak coherent drift wave is approximately governed by a nonlinear Schrödinger equation, which emerges as a limit of the modified Hasegawa-Mima equation. The nonlinear Schrödinger equation has well-known soliton solutions, and its modulational instability can naturally generate solitary structures. In this paper, we de

Ricardo A. Pastrán, Oscar G. Riaño C

This paper is devoted to study the Cauchy problem for the fractional dissipative BO equations $u_t+\mathcal{H}u_{xx}-(D_x^α-D_x^β)u+uu_x=0$, $0< α< β$. When $1<β<2$, we prove GWP in $H^s(\mathbb{R})$, $s>-β/4$. For $β\geq 2$, we show GWP in $H^s(\mathbb{R})$, $s>\max\{3/2-β, \, -β/2\}$. We establish that our results are sharp in the sense that the flow map $

William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare

Reinforcement learning (RL) typically defines a discount factor as part of the Markov Decision Process. The discount factor values future rewards by an exponential scheme that leads to theoretical convergence guarantees of the Bellman equation. However, evidence from psychology, economics and neuroscience suggests that humans and animals instead have hyperbo

Lech Duraj

The Longest Common Increasing Subsequence problem (LCIS) is a natural variant of the celebrated Longest Common Subsequence (LCS) problem. For LCIS, as well as for LCS, there is an $O(n^2)$-time algorithm and a SETH-based conditional lower bound of $O(n^{2-\varepsilon})$. For LCS, there is also the Masek-Paterson $O(n^2 / \log{n})$-time algorithm, which does

Taishi Kurahashi

This paper is a continuation of Arai&#39;s paper on derivability conditions for Rosser provability predicates. We investigate the limitations of the second incompleteness theorem by constructing three different Rosser provability predicates satisfying several derivability conditions.

Clark Zhang, Arbaaz Khan, Santiago Paternain, Alejandro Ribeiro

Modeling how a robot interacts with the environment around it is an important prerequisite for designing control and planning algorithms. In fact, the performance of controllers and planners is highly dependent on the quality of the model. One popular approach is to learn data driven models in order to compensate for inaccurate physical measurements and to a

Paul Kabaila, Nishika Ranathunga

We consider the problem of numerically evaluating the expected value of a smooth bounded function of a chi-distributed random variable, divided by the square root of the number of degrees of freedom. This problem arises in the contexts of simultaneous inference, the selection and ranking of populations and in the evaluation of multivariate t probabilities. I

N. Harrison, J. B. Betts, M. R. Wartenbe, F. F. Balakirev

(Pu) has an unusually rich phase diagram that includes seven distinct solid state phases and an unusually large 25% collapse in volume from its delta phase to its low temperature alpha phase via a series of structural transitions. Despite considerable advances in our understanding of strong electronic correlations within various structural phases of Pu and o

M. J. I. Brown, K. J. Duncan, H. Landt, M. Kirk

We present ongoing work on the spectral energy distributions (SEDs) of active galactic nuclei (AGNs), derived from X-ray, ultraviolet, optical, infrared and radio photometry and spectroscopy. Our work is motivated by new wide-field imaging surveys that will identify vast numbers of AGNs, and by the need to benchmark AGN SED fitting codes. We have constructed

Ganapati Bhat, Ranadeep Deb, Umit Y. Ogras

Movement disorders are becoming one of the leading causes of functional disability due to aging populations and extended life expectancy. Wearable health monitoring is emerging as an effective way to augment clinical care for movement disorders. However, wearable devices face a number of adaptation and technical challenges that hinder their widespread adopti

Jian Yao, Jeff A. Sherman, Tara Fortier, Holly Leopardi

A time scale is a procedure for accurately and continuously marking the passage of time. It is exemplified by Coordinated Universal Time (UTC), and provides the backbone for critical navigation tools such as the Global Positioning System (GPS). Present time scales employ microwave atomic clocks, whose attributes can be combined and averaged in a manner such

Dogancan Temel, Tariq Alshawi, Min-Hung Chen, Ghassan AlRegib

State-of-the-art algorithms successfully localize and recognize traffic signs over existing datasets, which are limited in terms of challenging condition type and severity. Therefore, it is not possible to estimate the performance of traffic sign detection algorithms under overlooked challenging conditions. Another shortcoming of existing datasets is the lim

Peng Sun, Wansen Feng, Ruobing Han, Shengen Yan

It is important to scale out deep neural network (DNN) training for reducing model training time. The high communication overhead is one of the major performance bottlenecks for distributed DNN training across multiple GPUs. Our investigations have shown that popular open-source DNN systems could only achieve 2.5 speedup ratio on 64 GPUs connected by 56 Gbps

Soufiane Hayou, Arnaud Doucet, Judith Rousseau

The weight initialization and the activation function of deep neural networks have a crucial impact on the performance of the training procedure. An inappropriate selection can lead to the loss of information of the input during forward propagation and the exponential vanishing/exploding of gradients during back-propagation. Understanding the theoretical pro

Mark F. Demers, Francoise Pene, Hong-Kun Zhang

We study limit theorems in the context of random perturbations of dispersing billiards in finite and infinite measure. In the context of a planar periodic Lorentz gas with finite horizon, we consider random perturbations in the form of movements and deformations of scatterers. We prove a Central Limit Theorem for the cell index of planar motion, as well as a

B. Harding, Y. M. Stokes, A. L. Bertozzi

We develop a model of the forces on a spherical particle suspended in flow through a curved duct under the assumption that the particle Reynolds number is small. This extends an asymptotic model of inertial lift force previously developed to study inertial migration in straight ducts. Of particular interest is the existence and location of stable equilibria

R. H. M. Tsang, A. Piepke, D. J. Auty, B. Cleveland

Radiation transport models of two high purity germanium detectors, GeII and GeIII, located at the University of Alabama have been created in GEANT4 \cite{geant4}. These detectors have been used extensively for radioassay measurements of materials used in various low background experiments. The two models have been validated against actual data under several

Jianqing Fan, Yingying Fan, Xiao Han, Jinchi Lv

Characterizing the asymptotic distributions of eigenvectors for large random matrices poses important challenges yet can provide useful insights into a range of statistical applications. To this end, in this paper we introduce a general framework of asymptotic theory of eigenvectors (ATE) for large spiked random matrices with diverging spikes and heterogeneo

Alex May

We consider an operational restatement of the holographic principle, which we call the principle of asymptotic quantum tasks. Asymptotic quantum tasks are quantum information processing tasks with inputs given and outputs required on points at the boundary of a spacetime. The principle of asymptotic quantum tasks states that tasks which are possible using th

Kazuya Yoshihara

Let $N_{g}$ denote the closed non-orientable surface of genus $g$ and let ${\mathcal M} _g$ denote the mapping class group of $N_{g}$. Let ${\mathcal T} _g$ denote the twist subgroup of ${\mathcal M} _g$ which is the subgroup of ${\mathcal M} _g$ is generated by all Dehn twists. In this thesis, we proved that ${\mathcal T} _g$ is generated by six involutions

Adarsh Sehgal, Hung Manh La, Sushil J. Louis, Hai Nguyen

Reinforcement learning (RL) enables agents to take decision based on a reward function. However, in the process of learning, the choice of values for learning algorithm parameters can significantly impact the overall learning process. In this paper, we use a genetic algorithm (GA) to find the values of parameters used in Deep Deterministic Policy Gradient (D

Luca Piccolboni, Giuseppe Di Guglielmo, Luca Carloni

Systems-on-chip (SoCs) are becoming heterogeneous: they combine general-purpose processor cores with application-specific hardware components, also known as accelerators, to improve performance and energy efficiency. The advantages of heterogeneity, however, come at a price of threatening security. The architectural dissimilarities of processors and accelera

Junzhe Zhang, Sai Ho Yeung, Yao Shu, Bingsheng He

GPU (graphics processing unit) has been used for many data-intensive applications. Among them, deep learning systems are one of the most important consumer systems for GPU nowadays. As deep learning applications impose deeper and larger models in order to achieve higher accuracy, memory management becomes an important research topic for deep learning systems

Yunpu Ma, Volker Tresp, Liming Zhao, Yuyi Wang

In this work, we propose the first quantum Ansätze for the statistical relational learning on knowledge graphs using parametric quantum circuits. We introduce two types of variational quantum circuits for knowledge graph embedding. Inspired by the classical representation learning, we first consider latent features for entities as coefficients of quantum sta

Shaojie Xu, Anvesha Amaravati, Justin Romberg, Arijit Raychowdhury

We propose a novel appearance-based gesture recognition algorithm using compressed domain signal processing techniques. Gesture features are extracted directly from the compressed measurements, which are the block averages and the coded linear combinations of the image sensor&#39;s pixel values. We also improve both the computational efficiency and the memor

Ritesh Kapse, S. Adarsh

In this paper we have implemented the autonomous emergency braking using two radar sensors with different angle of coverage. The synthetic radar data is generated by radar detection generator block available in AEBTestBench simulation module. AEBTestBench is autonomous emergency simulation module available in Matlab 2018b version under ADAS toolbox. From dif

Sahithya Ravi, Pouria Zand, Mohieddine El Soussi, Majid Nabi

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the

Manfredo Harri Tabacniks

LAMFI is a laboratory dedicated to the development and application of ion beam techniques for the analysis of bulk materials and thin films. Its main facilities comprise an 1.7MV Pelletron tandem accelerator and two analytical setups, one mainly for Rutherford Backscattering Spectrometry (RBS), and channeling, and another, for Particle Induced X-ray Emission

Renchang Dai, Xiang Zhang, Junjie Shi, Guangyi Liu

Power flow calculation methods have been developed in decades using power injections and Newton-Raphson method. The nonlinear characteristics of the power flow to the bus voltage require Jacobian matrix reformation and refactorization in each iteration. Power network is composed by resistors, reactors, and capacitors which is a linear circuit when investigat

Anderson Santos Nunes, Allan Schwanz, Eduardo Postali, Marcelo Kruger

The cooling system is a key factor in power transformer designs. The frequent need for optimized projects further increases the importance of development through of increasingly developed tools. This work aims to evaluate a transformer design, in which the refrigeration is performed through of exhaust fans and heat exchangers installed on the lower side of t

A. M. Perelomov

We consider the relation between Euler&#39;s trinomial problem and the problem of decomposition of tensor powers of adjoint representation of $A_1$ Lie algebra. By using this approach, some new results for both problems are obtained.

Subhayan Maity, Pritikana Bhandari, Subenoy Chakraborty

The present work deals with homogeneous and isotropic FLRW model of the Universe having a system of non-interacting diffusive cosmic fluids with barotropic equation of state (constant or variable equation of state parameter). Due to diffusive nature of the cosmic fluids, the divergence of the energy momentum tensor is chosen to be proportional to the diffusi

David Faux, Mayank Shah, Christopher Knapp

Conway&#39;s classic game of life is a two-dimensional cellular automaton in which each cell, either alive or dead, evolves according to rules based on its local environment. The semi-quantum game of life (SQGOL) is an adaptation in which each cell is in a superposed state of both dead and alive and evolves according to modified rules. Computer simulation of

David Faux, Mayank Shah, Christopher Knapp

The classical &#34;game of life&#34; (GOL) due to Conway is a famous mathematical game constructed as a two-dimensional cellular automaton in which each cell is either alive or dead. A set of evolutionary rules determines whether a cell dies, survives or is born at each generation based on its local environment. The game of life is interesting because comple

Suelen Gasparin, Denys Dutykh, Nathan Mendes

This work presents an efficient numerical method based on spectral expansions for simulation of heat and moisture diffusive transfers through multilayered porous materials. Traditionally, by using the finite-difference approach, the problem is discretized in time and space domains (Method of lines) to obtain a large system of coupled Ordinary Differential Eq

Hans Christian Öttinger

A Noether-enhanced Legendre transformation from Lagrange densities to energy-momentum tensors is developed into an alternative framework for formulating classical field equations. This approach offers direct access to the Hamiltonian while keeping manifest Lorentz covariance in the formulation of relativistic field theories. The field equations are obtained

Daiki Ishi, Kumi Ishikawa, Masaki Numazawa, Yoshizumi Miyoshi

Suzaku detected an enhancement of soft X-ray background associated with solar eruptions on 2013 April 14-15. The solar eruptions were accompanied by an M6.5 solar flare and a coronal mass ejection with magnetic flux ropes. The enhanced soft X-ray background showed a slight variation in half a day and then a clear one in a few hours. The former spectrum was c

Pier Luigi Silvestrelli, Alberto Ambrosetti

A new implementation is proposed for including van der Waals (vdW) interactions in Density Functional Theory (DFT) using the Maximally-Localized Wannier functions (MLWFs), which is free from empirical parameters. With respect to the previous DFT/vdW-WF2 method, in the present DFT/vdW-WF2-x approach, the empirical, short-range, damping function is replaced by

Ahmed Jellal, Abdeldjalil Merdaci

We study two entropies of a system composed of two coupled harmonic oscillators which is brought to a canonical thermal equilibrium with a heat-bath at temperature $T$. Using the purity function, we explicitly determine the Rényi and van Newmon entropies in terms of different physical parameters. We will numerically analyze these two entropies under suitable

Victor Barsan

This paper gives a coherent and comprehensive review of the results concerning the inverse Langevin L(x) and Brillouin functions B_J (x) and of the inverse of L(x)/x and B_J (x)/x. As these functions are used in several fields of physics, without evident interconnections - magnetism (ferromagnetism, superparamagnetism, nanomagnetism, hysteretic physics), rub

V. Hussin, M. Lafrance, I. Yurdusen

We explore the constant curvature holomorphic solutions of the supersymmetric grassmannian sigma model $G(M,N)$ using in particular the gauge invariance of the model. Supersymmetric invariant solutions are constructed via generalizing a known result for ${C}P^{N-1}$. We show that some other such solutions also exist. Indeed, considering the simplest case of

Ethan Madison, Zachary Zipper

Bloom filters are data structures used to determine set membership of elements, with applications from string matching to networking and security problems. These structures are favored because of their reduced memory consumption and fast wallclock and asymptotic time bounds. Generally, Bloom filters maintain constant membership query time, making them very f

Malgorzata Turalska, Keith Burghardt, Martin Rohden, Ananthram Swami

Large cascades are a common occurrence in many natural and engineered complex systems. In this paper we explore the propagation of cascades across networks using realistic network topologies, such as heterogeneous degree distributions, as well as intra- and interlayer degree correlations. We find that three properties, scale-free degree distribution, interna

Michael Atallah, Georges Kaddoum

This paper proposes a new security cooperative protocol, for dual phase amplify-and-forward large wireless sensor networks. In such a network, a portion of the K relays can be potential eavesdroppers. The source agrees to share with the destination a given channel state information (CSI) of a source-trusted relay-destination link to encode the message. Then,

Kasidit Toprasertpong, Amaury Delamarre, Yoshiaki Nakano, Jean-François Guillemoles

Two reciprocity theorems are important for fundamental understanding of the solar cell operation and applications to device evaluation: (1) the carrier-transport reciprocity connecting the dark-carrier injection with the short-circuit photocarrier collection and (2) the optoelectronic reciprocity connecting the electroluminescence with the photovoltaic quant

S. Cavazzani, S. Ortolani, N. Scafetta, V. Zitelli

In this paper we investigate the correlation between the atmospheric perturbations at Paranal Observatory and the Chilean coast tides, which are mostly modulated by the 14-day syzygy solar-lunar tidal cycle. To this aim, we downloaded 15 years (2003-2017) of cloud coverage data from the AQUA satellite, in a matrix that includes also Armazones, the site of th

George Kappos, Ania M. Piotrowska

Although Bitcoin in its original whitepaper stated that it offers anonymous transactions, de-anonymization techniques have found otherwise. Therefore, alternative cryptocurrencies, like Dash, Monero, and Zcash, were developed to provide better privacy. As Edward Snowden stated, &#34;Zcash&#39;s privacy tech makes it the most interesting Bitcoin alternative (

Daniel Drzisga, Brendan Keith, Barbara Wohlmuth

We give the first mathematically rigorous analysis of an emerging approach to finite element analysis (see, e.g., Bauer et al. [Appl. Numer. Math., 2017]), which we hereby refer to as the surrogate matrix methodology. This methodology is based on the piece-wise smooth approximation of the matrices involved in a standard finite element discretization. In part

Elena Braverman, Basak Karpuz

We provide explicit conditions for uniform stability, global asymptotic stability and uniform exponential stability for dynamic equations with a single delay and a nonnegative coefficient. Some examples on nonstandard time scales are also given to show applicability and sharpness of the new results.

Marcelo Aguiar, Jose Bastidas, Swapneel Mahajan

Characteristic elements of the Tits algebra of a real hyperplane arrangement carry information about the characteristic polynomial. We present this notion and its basic properties, and apply it to derive various results about the characteristic polynomial of an arrangement, from Zaslavsky&#39;s formulas to more recent results of Kung and of Klivans and Swart

Stephen Morrell, Zbigniew Wojna, Can Son Khoo, Sebastien Ourselin

State-of-the-art deep learning methods for image processing are evolving into increasingly complex meta-architectures with a growing number of modules. Among them, region-based fully convolutional networks (R-FCN) and deformable convolutional nets (DCN) can improve CAD for mammography: R-FCN optimizes for speed and low consumption of memory, which is crucial

Ermanno F. Borra

Extremely peculiar emission lines have been found in the spectra of some active galactic nuclei and quasars. Their origin is totally unknown. We investigate the hypothesis that they are generated from ultra-rapid quasi-periodic oscillations that may occur in jets or black holes, as predicted in a published theoretical paper. We conclude that, although not to

Gamal M. Hamed

We study the evolution of the normalized flux of selected ultraviolet emission lines of three classical novae (PW Vul, V1668 Cyg and V1974 Cyg). Different phases ofthe outbursts are studied. We attribute the spectral behavior of the three systems to the variation of the optical thickness and temperature of the envelope during the different phases of the outb

Jacek Komorowski, Grzegorz Kurzejamski, Grzegorz Sarwas

The paper describes a deep network based object detector specialized for ball detection in long shot videos. Due to its fully convolutional design, the method operates on images of any size and produces \emph{ball confidence map} encoding the position of detected ball. The network uses hypercolumn concept, where feature maps from different hierarchy levels o

Elena Braverman, Daniel Franco

In contrast with unstructured models, structured discrete population models have been able to fit and predict chaotic experimental data. However, most of the chaos control techniques in the literature have been designed and analyzed in a one-dimensional setting. Here, by introducing target oriented control for discrete dynamical systems, we prove the possibi

R. B. Menezes, T. V. Ricci, J. E. Steiner, Patrícia da Silva

We present a set of treatment techniques for GMOS/IFU data cubes, including: correction of the differential atmospheric refraction; Butterworth spatial filtering, to remove high spatial-frequency noise; instrumental fingerprint removal; Richardson-Lucy deconvolution, to improve the spatial resolution of the observations. A comparison with HST images shows th

Piotr Lugiewicz, Andrzej Frydryszak, Lech Jakobczyk

We present the complete solution of the problem of determination of trace-norm geometric discord for arbitrary two-qubit state. Final answer is achieved due to effective reduction of the problem to the study of critical points of certain mapping depending on projectors. Our results are illustrated on various, also new, families of two-qubit states and compar

Mate Kisantal, Zbigniew Wojna, Jakub Murawski, Jacek Naruniec

In recent years, object detection has experienced impressive progress. Despite these improvements, there is still a significant gap in the performance between the detection of small and large objects. We analyze the current state-of-the-art model, Mask-RCNN, on a challenging dataset, MS COCO. We show that the overlap between small ground-truth objects and th

I. de Pater, R. J. Sault, M. H. Wong, L. N. Fletcher

We observed Jupiter four times over a full rotation (10 hrs) with the upgraded Karl G. Jansky Very Large Array (VLA) between December 2013 and December 2014. Preliminary results at 4-17 GHz were presented in de Pater et al. (2016); in the present paper we present the full data set at frequencies between 3 and 37 GHz. Major findings are: (i) the radio-hot bel