September 2019 arXiv papers — page 41

Igor A. Batalin, Klaus Bering, Peter M. Lavrov, Igor V. Tyutin

Studying the gauge-invariant renormalizability of four-dimensional Yang-Mills theory using the background field method and the BV-formalism, we derive a classical master-equation homogeneous with respect to the antibracket by introducing antifield partners to the background fields and parameters. The constructed model can be renormalized by the standard meth

Mario Maurelli, Klas Modin, Alexander Schmeding

We consider stochastic versions of Euler--Arnold equations using the infinite-dimensional geometric approach as pioneered by Ebin and Marsden. For the Euler equation on a compact manifold (possibly with smooth boundary) we establish local existence and uniqueness of a strong solution (in the stochastic sense) in spaces of Sobolev mappings (of high enough reg

Yen Chin Ong

Hiscock and Weems showed that there is an attractor behavior in the evolution of asymptotically flat Reissner-Nordstr\"om black hole under Hawking evaporation. If the initial charge-to-mass ratio $Q/M$ of the black hole is relatively small, then the ratio first increases until the black hole hits the attractor, and then starts to discharge towards the Schwar

Pengcheng Yang, Min Yu, Ralf Betzholz, Christian Arenz

Single-qubit measurements are typically insufficient for inferring arbitrary quantum states of a multi-qubit system. We show that if the system can be fully controlled by driving a single qubit, then utilizing a local random pulse is almost always sufficient for complete quantum-state tomography. Experimental demonstrations of this principle are presented us

Joonas Hämäläinen, Alisson S. C. Alencar, Tommi Kärkkäinen, César L. C. Mattos

The Minimal Learning Machine (MLM) is a nonlinear supervised approach based on learning a linear mapping between distance matrices computed in the input and output data spaces, where distances are calculated using a subset of points called reference points. Its simple formulation has attracted several recent works on extensions and applications. In this pape

Jiyou Li, Xiang Yu

The Li--Wan sieve is extended to multisets when the underlying set is symmetric. The main ingredient of the proof is the Mobius inversion formula on the poset of partitions of $\{1,2,\dots,k\}$ ordered by refinement. As illustrative applications, we investigate the problems of partitions over finite fields and zero-sum multisets over the additive group $\mat

Xicheng Zhang

In this paper we prove a discretized version of Krylov's estimate for discretized Itô's processes. As applications, we study the weak and strong convergences for Euler's approximation of mean-field SDEs with measurable discontinuous and linear growth coefficients. Moreover, we also show the propagation of chaos for Euler's approximation of me

Debabrata Biswas, Rashbihari Rudra

Field emisison of electrons crucially depends on the enhancement of the local electric field around nanotips. The enhancement is maximum when individual emitter-tips are well separated. As the distance between two or more nanotips decreases, the field enhancement at individual tips reduces due to the shielding effect. The anode-proximity effect acts in quite

Joontae Kim

We prove that the count of Maslov index 2 $J$-holomorphic discs passing through a generic point of a real Lagrangian submanifold in a closed spherically monotone symplectic manifold must be even. As a corollary, we exhibit a genuine real symplectic phenomenon in terms of involutions, namely that the Chekanov torus $\mathbb{T}_{\text{Chek}}$ in $S^2\times S^2

J. M. Sanz-Serna, Konstantinos C. Zygalakis

We consider the application of Runge-Kutta (RK) methods to gradient systems $(d/dt)x = -\nabla V(x)$, where, as in many optimization problems, $V$ is convex and $\nabla V$ (globally) Lipschitz-continuous with Lipschitz constant $L$. Solutions of this system behave contractively, i.e. the Euclidean distance between two solutions $x(t)$ and $\widetilde{x}(t)$

Yun-Zhi Du, Ren Zhao, Li-Chun Zhang

Some ones have showed the first-order phase transition of the Horava-Lifshitz (HL) AdS black holes has unique characters from other AdS black holes. While the coexistence zone of the first-order phase transition was not exhibited. As well known the coexistence curve of a black hole carries a lot of information about black hole, which provides a powerful diag

Frank Göhmann

This script is based on the notes the author prepared to give a set of six lectures at the Les Houches School "Integrability in Atomic and Condensed Matter Physics" in the summer of 2018. The school had its focus on the application of integrability based methods to problems in non-equilibrium statistical mechanics. The lectures were meant to complement this

Jeffrey D. Adler, Manish Mishra

For a connected reductive group $G$ defined over a non-archimedean local field $F$, we consider the Bernstein blocks in the category of smooth representations of $G(F)$. Bernstein blocks whose cuspidal support involves a regular supercuspidal representation are called $\textit{regular}$ Bernstein blocks. Most Bernstein blocks are regular when the residual ch

Leszek Gasinski, Patrick Winkert

We study parametric double phase problems involving superlinear nonlinearities with a growth that need not necessarily be polynomial. Based on truncation and comparison methods the existence of two constant sign solutions is shown provided the parameter is larger than the first eigenvalue of the $p$-Laplacian. As a result of independent interest we prove a p

Bakhtiyar Syed, Gaurav Verma, Balaji Vasan Srinivasan, Anandhavelu Natarajan

Given the recent progress in language modeling using Transformer-based neural models and an active interest in generating stylized text, we present an approach to leverage the generalization capabilities of a language model to rewrite an input text in a target author's style. Our proposed approach adapts a pre-trained language model to generate author-styliz

Xin Cai, Yi-Fei Pu

In this paper, we focus on devising a versatile framework for dense pixelwise prediction whose goal is to assign a discrete or continuous label to each pixel for an image. It is well-known that the reduced feature resolution due to repeated subsampling operations poses a serious challenge to Fully Convolutional Network (FCN) based models. In contrast to the

Xiang Ji, Yanqing Wang, Wei Wei

In this paper, we derive regular criteria via pressure or gradient of the velocity in Lorentz spaces to the 3D Navier-Stokes equations. It is shown that a Leray-Hopf weak solution is regular on $(0,T]$ provided that either the norm $\|\Pi\|_{L^{p,\infty}(0,T; L ^{q,\infty}(\mathbb{R}^{3}))} $ with $ {2}/{p}+{3}/{q}=2$ $({3}/{2}<q<\infty)$ or $\|\nabla\Pi\|_{

Yanqing Wang, Wei Wei, Huan Yu

In this paper, we are concerned with regularity of suitable weak solutions of the 3D Navier-Stokes equations in Lorentz spaces. We obtain $\varepsilon$-regularity criteria in terms of either the velocity, the gradient of the velocity, the vorticity, or deformation tensor in Lorentz spaces. As an application, this allows us to extend the result involving Lera

Ke-Jian He, Guo-Ping Li, Xin-Yun Hu

We adopt the energy momentum relation of charged particles to study the thermodynamics laws and weak cosmic censorship conjecture of $D$-dimensional $f(R)$ AdS black holes in different phase spaces by considering charged particle absorption. In the normal phase space, it turns out that the laws of thermodynamic and the weak cosmic censorship conjecture are v

I. M. Mejía, V. S. Manko, E. Ruiz

In the present paper we argue that a special case of the Bach-Weyl metric describing a static configuration of two Schwarzschild black holes gives rise, after extending its parameter space to complex values, to a very simple 2-parameter model for the gravitational field of a static deformed mass. We compare this model, which has no restrictions on the quadru

Anningzhe Gao

We will calculate the essential dimension of the moduli stack of polarized K3 surfaces, including the positive char case.

Tahir Bachar Issa, Wenxian Shen

The current paper is concerned with pointwise persistence in full chemotaxis models with local as well as nonlocal time and space dependent logistic source in bounded domains. We first prove the global existence and boundedness of nonnegative classical solutions under some conditions on the coefficients in the models. Next, under the same conditions on the c

Naeimeh Mohseni, Marek Narozniak, Alexey N. Pyrkov, Valentin Ivannikov

Incorporating protection against quantum errors into adiabatic quantum computing (AQC) is an important task due to the inevitable presence of decoherence. Here we investigate an error-protected encoding of the AQC Hamiltonian, where qubit ensembles are used in place of qubits. Our Hamiltonian only involves total spin operators of the ensembles, offering a si

Tanzila Rahman, Bicheng Xu, Leonid Sigal

Multi-modal learning, particularly among imaging and linguistic modalities, has made amazing strides in many high-level fundamental visual understanding problems, ranging from language grounding to dense event captioning. However, much of the research has been limited to approaches that either do not take audio corresponding to video into account at all, or

F. Sukochev, K. Tulenov, D. Zanin

In this paper, we study the boundedness of the Hilbert transformation in Lorentz function spaces, thereby complementing classical results of Boyd. We also characterize the optimal range of a triangular truncation operator in Schatten-Lorentz ideals. These results further entail sharp commutator estimates and applications to operator Lipschitz functions in Sc

Walid Koussa, Mustapha Maamache

The Lewis and Riesenfeld method has been investigated, by Ramos et al in Ref.[1], for quantum systems governed by time-dependent PT symmetric Hamiltonians and particularly where the quantum system is a particle submitted to action of a complex time-dependent linear potential. We discuss the method they used and propose an alternative one which leads to physi

Jiaqi Zhang, Keyou You, Kai Cai

This paper proposes a distributed dual gradient tracking algorithm (DDGT) to solve resource allocation problems over an unbalanced network, where each node in the network holds a private cost function and computes the optimal resource by interacting only with its neighboring nodes. Our key idea is the novel use of the distributed push-pull gradient algorithm

Mayra Samaniego, Ralph Deters

With the advent of blockchain technology, some management tasks of IoT networks can be moved from central systems to distributed validation authorities. Cloud-centric blockchain implementations for IoT have shown satisfactory performance. However, some features of blockchain are not necessary for IoT. For instance, a competitive consensus. This research pres

Yuanxin Wu, Yury A. Litmanovich

This paper compares two basic approaches to solving ordinary differential equations, which form the basis for attitude computation in strapdown inertial navigation systems, namely, the Taylor series expansion approach that was used in its low-order form for deriving all mainstream algorithms and the functional iterative integration approach developed recentl

Bohan Zhuang, Chunhua Shen, Mingkui Tan, Peng Chen

We propose methods to train convolutional neural networks (CNNs) with both binarized weights and activations, leading to quantized models that are specifically friendly to mobile devices with limited power capacity and computation resources. Previous works on quantizing CNNs often seek to approximate the floating-point information using a set of discrete val

Hernando Garcia, Juan Serna, Edgar Rueda

Using an Electrically Focus Tunable Lens (EFTL), an integrating sphere and a tunable femtosecond-pulse laser (Mai Tai HP), we were able to measure the degenerate two-photon absorption coefficient (in transmission) of CdS and ZnSe in a long range of wavelengths (690-1040 nm), with a 5 nm resolution, in less than 30 minutes. We compared our results with theore

Haifeng Li, Jun Liu, Li Cui, Haiyang Huang

Image segmentation with a volume constraint is an important prior for many real applications. In this work, we present a novel volume preserving image segmentation algorithm, which is based on the framework of entropic regularized optimal transport theory. The classical Total Variation (TV) regularizer and volume preserving are integrated into a regularized

Jiangtao Duan, Wei Gao, Hao Qu, Hon Keung Tony

In this paper, a statistical model for panel data with unobservable grouped factor structures which are correlated with the regressors and the group membership can be unknown. The factor loadings are assumed to be in different subspaces and the subspace clustering for factor loadings are considered. A method called least squares subspace clustering estimate

Weizhi Xu, Yintai Sun, fhengyu Fan, Hui Yu

Convolutional neural network (CNN) is an important deep learning method. The convolution operation takes a large proportion of the total execution time for CNN. Feature maps for convolution operation are usually sparse. Multiplications and additions for zero values in the feature map are useless for convolution results. In addition, the convolution layer and

Cheuk Yu Mak, Ivan Smith

Let $\omega$ denote an area form on $S^2$. Consider the closed symplectic 4-manifold $M=(S^2\times S^2, A\omega \oplus a \omega)$ with $0<a<A$. We show that there are families of displaceable Lagrangian tori $L_{0,x},\, L_{1,x} \subset M$, for $x \in [0,1]$, such that the two-component link $L_{0,x} \cup L_{1,x}$ is non-displaceable for each $x$.

Prateesh Goyal, Preey Shah, Kevin Zhao, Georgios Nikolaidis

Effective congestion control for data center networks is becoming increasingly challenging with a growing amount of latency sensitive traffic, much fatter links, and extremely bursty traffic. Widely deployed algorithms, such as DCTCP and DCQCN, are still far from optimal in many plausible scenarios, particularly for tail latency. Many operators compensate by

Arijit Sehanobish, Chan Hee Song

Most Named Entity Recognition (NER) systems use additional features like part-of-speech (POS) tags, shallow parsing, gazetteers, etc. Such kind of information requires external knowledge like unlabeled texts and trained taggers. Adding these features to NER systems have been shown to have a positive impact. However, sometimes creating gazetteers or taggers c

Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan

Autonomous robots often encounter challenging situations where their control policies fail and an expert human operator must briefly intervene, e.g., through teleoperation. In settings where multiple robots act in separate environments, a single human operator can manage a fleet of robots by identifying and teleoperating one robot at any given time. The key

Jun-Jin Peng

In this paper, we aim to explore the properties and applications on the operators consisting of the Hodge star operator together with the exterior derivative, whose action on an arbitrary $p$-form field in $n$-dimensional spacetimes makes its form degree remain invariant. Such operations are able to generate a variety of $p$-forms with the even-order derivat

Forest Kobayashi, Sam Nelson

We introduce \textit{Kaestner brackets}, a generalization of biquandle brackets to the case of parity biquandles. This infinite set of quantum enhancements of the biquandle counting invariant for oriented virtual knots and links includes the classical quantum invariants, the quandle and biquandle $2$-cocycle invariants and the classical biquandle brackets as

Peter J. Forrester

We consider properties of the ground state density for the $d$-dimensional Fermi gas in an harmonic trap. Previous work has shown that the $d$-dimensional Fourier transform has a very simple functional form. It is shown that this fact can be used to deduce that the density itself satisfies a third order linear differential equation, previously known in the l

Haoyang Guo

In this article, we generalize the Hodge-Tate decomposition of p-adic \'etale cohomology to non-smooth rigid spaces. Our strategy is to study pro-\'etale cohomology of rigid spaces introduced by Scholze, using the resolution of singularities and the simplicial method.

Peter Bradshaw, Seyyed Aliasghar Hosseini

We consider a surrounding variant of cops and robbers on graphs of bounded genus. We obtain bounds on the number of cops required to surround a robber on planar graphs, toroidal graphs, and outerplanar graphs. We also obtain improved bounds for bipartite planar and toroidal graphs. We briefly consider general graphs of bounded genus and graphs with a forbidd

Samaneh Ghandali, Thorben Moos, Amir Moradi, Christof Paar

Hardware Trojans have drawn the attention of academia, industry and government agencies. Effective detection mechanisms and countermeasures against such malicious designs can only be developed when there is a deep understanding of how hardware Trojans can be built in practice, in particular Trojans specifically designed to avoid detection. In this work, we p

Samaneh Ghandali, Daniel Holcomb, Christof Paar

True random number generators (TRNGs) are essential components of cryptographic designs, which are used to generate private keys for encryption and authentication, and are used in masking countermeasures. In this work, we present a mechanism to design a stealthy parametric hardware Trojan for a ring oscillator based TRNG architecture proposed by Yang et al.

John A. Nairn

Computer calculations for most exact expected values in blackjack have been available since the 1960&#39;s, but exact results for pair splitting and resplitting have previously been too computer intensive. This paper describes a new algorithm for exact pair-splitting. By using dealer probability caching methods and revising the method for recursively generat

Shivam Barwey, Malik Hassanaly, Venkat Raman, Adam Steinberg

This work utilizes data-driven methods to morph a series of time-resolved experimental OH-PLIF images into corresponding three-component planar PIV fields in the closed domain of a premixed swirl combustor. The task is carried out with a fully convolutional network, which is a type of convolutional neural network (CNN) used in many applications in machine le

Adam Griffin, Sergey Nazarenko, Vishwanath Shukla, Marc-Etienne Brachet

Experimentalists use particles as tracers in liquid helium. The intrusive effects of particles on the dynamics of vortices remain poorly understood. We implement a study of how basic well understood vortex states, such as a propagating pair of oppositely signed vortices, change in the presence of particles by using a simple model based on the Magnus force. W

Georges Neaime

Garside theory emerged from the study of Artin groups and their generalizations. Finite-type Artin groups admit two types of interval Garside structures corresponding to their standard and dual presentations. Concerning affine Artin groups, Digne established interval Garside structures for two families of these groups by using their dual presentations. Recen

Aninda Chakraborty

A partial semigroup is a set with restricted binary operation. In this work we will extend a result due to V. Bergelson and N. Hindman concerning the rich structure presented in the product space of semigroups to partial semigroup. An $IP^{\star}$ set in a semigroup is a set that intersect every set of the form $\left\{ FS(x_{n})_{n=1}^{\infty}:x_{n}\in S\ri

Shanshan Chen, Junping Shi

The effect of diffusion rates on the basic reproduction number of a general compartmental reaction-diffusion epidemic model in a heterogeneous environment is considered. It is shown when the diffusion rates tend to zero, the limit of the basic reproduction number is the maximum value of the local reproduction number on the spatial domain. On the other hand w

Esha Bangar, Nima Taherkhani, Kamran Kiasaleh

In this paper, the impact of channel estimation error (CEE) on the sum-rate capacity of multiple-input-multiple-output (MIMO) heterogeneous networks (HetNets) is investigated. It is assumed that the receiver is a linear minimum mean-square (LMMS) receiver. The architecture is based on the deployment of macro base stations with large antenna arrays and a seco

Nima Taherkhani, Merve Apalak, Kamran Kiasaleh

The linear error-correcting codes are known to be well suited for battling and correcting the burst errors caused by noise in the wireless data transmission system. However, different types of codes offer different decoding and burst-error-correcting capabilities. This paper compares the Low-Density-Parity Check (LDPC) and Reed Solomon (RS) encoding schemes

G. Amico, M. Amico, C. Benna, D. Gardiol

An analysis of available photometric data of NSVS 1925037 and a search of a variable counterpart has been performed using astrometric and photometric data from Gaia DR2 and ASAS-SN databases.

Ramen Ghosh, Jakub Marecek, Robert Shorten

Within the study of uncertain dynamical systems, iterated random functions are a key tool. There, one samples a family of functions according to a stationary distribution. Here, we introduce an extension, where one sample functions according to a time-varying distribution over the family of functions. For such iterated piecewise-stationary random functions o

Yazan Mualla, Amro Najjar, Timotheus Kampik, Igor Tchappi

This paper presents an initial design concept and specification of a civilian Unmanned Aerial Vehicle (UAV) management simulation system that focuses on explainability for the human-in-the-loop control of semi-autonomous UAVs. The goal of the system is to facilitate the operator intervention in critical scenarios (e.g. avoid safety issues or financial risks)

Ryan Vitale

We give presentations of the planar algebra of unipotent representations of the groups $\mathbb{C}$ and $\mathbb{F}_p$ under addition using jellyfish and light leaf style arguments. These are some of the most natural examples of non-semisimple planar algebras. For the characteristic $p$ family of examples, a new generator appears in arbitrarily large box spa

Shou-fei Gao, Ying-ying Wang, Wei Ding, Yi-Feng Hong

The ultimate limit on fiber loss is set by the intrinsic Rayleigh scattering of silica glass material. Here, we challenge this limit in the visible region by using a hollow-core fiber approach. Two visible-guiding hollow-core conjoined-tube negative-curvature fibers are successfully fabricated and exhibit the overall losses of 3.8 dB/km at 680 nm and 4.9 dB/

T. Joubaud, I. A. Grenier, J. Ballet, J. D. Soler

The Orion-Eridanus superbubble has been blown by supernovae and supersonic winds of the massive stars in the Orion OB associations. The formation history and current structure of the superbubble are still poorly understood. It possibly consists of a combination of nested shells along the line of sight. We have investigated the composite structure of the Erid

Kourosh Darvish, Yeshasvi Tirupachuri, Giulio Romualdi, Lorenzo Rapetti

Humanoid robot teleoperation allows humans to integrate their cognitive capabilities with the apparatus to perform tasks that need high strength, manoeuvrability and dexterity. This paper presents a framework for teleoperation of humanoid robots using a novel approach for motion retargeting through inverse kinematics over the robot model. The proposed method

Shih-Kang Chao, Guang Cheng

Excessive computational cost for learning large data and streaming data can be alleviated by using stochastic algorithms, such as stochastic gradient descent and its variants. Recent advances improve stochastic algorithms on convergence speed, adaptivity and structural awareness. However, distributional aspects of these new algorithms are poorly understood,

Indranil Roy, Rini Ganguly, Harkirat Singh, Pratap Raychaudhuri

We investigate the magnetic field evolution of the superconducting state in a strongly disordered NbN thin film which exhibits a magnetic field tuned superconductor to insulator-like transition, employing low temperature scanning tunneling spectroscopy (STS). Transport measurements of the sample reveals a characteristic magnetic field, which separates the lo

Kelsey Scott

We extend George Andrew&#39;s general principle for counting generalized Frobenius partitions to include arrays with nonzero row difference and establish some congruences for these arrays.

Guangchi Liu, Qing Yang, Honggang Wang, Alex X. Liu

Assessing trust in online social networks (OSNs) is critical for many applications such as online marketing and network security. It is a challenging problem, however, due to the difficulties of handling complex social network topologies and conducting accurate assessment in these topologies. To address these challenges, we model trust by proposing the three

Vladislav Terekhovich

In this paper, I consider the issue of how two mathematical models of modern physics, the variational principles and the quantum path integral formalism, relate to reality. I assume that the observed phenomena are consistent with the calculations because both of these models have some common ontological foundations. According to the hypothesis of the summati

Muthiah Annamalai, T. Shrinivasan

Tamil language has an agglutinative, diglossic, alpha-syllabary structure which provides a significant combinatorial explosion of morphological forms all of which are effectively used in Tamil prose, poetry from antiquity to the modern age in an unbroken chain of continuity. However, for the language understanding, spelling correction purposes some of these

Latif Eliaz

This work studies geometrical characterizations of the essential spectrum $σ_{\text ess}$ of Schrödinger operators on graphs. Especially we focus on generalizing characterizations which are given in terms of the concept of right limits. Intuitively the set of right limits of a Schrödinger operator $H$ on $\ell^2(\mathbb{N})$ includes the limit operators whic

Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman

Latent tree learning(LTL) methods learn to parse sentences using only indirect supervision from a downstream task. Recent advances in latent tree learning have made it possible to recover moderately high quality tree structures by training with language modeling or auto-encoding objectives. In this work, we explore the hypothesis that decoding in machine tra

Luke Liu, Qing Yang

Trust assessment plays a key role in many online applications, such as online money lending, product reviewing and active friending. Trust models usually employ a group of parameters to represent the trust relation between a trustor-trustee pair. These parameters are originated from the trustor&#39;s bias and opinion on the trustee. Naturally, these paramete

Lior M. Burko

Analysis of collisions is standardly included in the introductory physics course. In one dimension (1D), there do not seem to be any unusual issues: Typically, the initial velocities of the two colliding objects are specified, and the problem is to find the final velocities. In 1D there are therefore two unknown variables. One can write the equation for cons

James T. Griffin

We define a class of probability distributions that we call simplicial mixture models, inspired by simplicial complexes from algebraic topology. The parameters of these distributions represent their topology and we show that it is possible and feasible to fit topological structure to data using a maximum-likelihood approach. We prove under reasonable assumpt

Vladislav Terekhovich

Some interpretations of quantum mechanics use notions of possible states and possible trajectories. I investigate how this modal approach correlates with several metaphysical conceptions of a transition from potential to actual existence. The comparison is based on a discussion in contemporary analytical metaphysics of modality. I also consider an analogy be

Daniel Juliano Pamplona da Silva, Edmundo Capelas de Oliveira

This paper starts from the Fisher-Kolmogorov-Petrovskii-Piskunov equation to model diffusive populations. The main result, according to this model, is that two connected patches in a system do not always contribute to each other. Specifically, inserting a large fragment next to a small one is always positive for life inside the small patch, while inserting a

Maria Rosario Astudillo Rojas, Marcelo M. Cavalcanti, Wellington J. Correa, Valeria N. Domingos Cavalcanti

In the present paper, we are concerned with the semilinear viscoelastic wave equation subject to a locally distributed dissipative effect of Kelvin-Voigt type, posed on a bounded domain with smooth boundary. We begin with an auxiliary problem and we show that its solution decays exponentially in the weak phase space. The method of proof combines an observabi

Yan-Ling Wang

Special unextendible entangled basis of &#34;type $k$&#34; (SUEBk), a set of incomplete orthonormal special entangled states of &#34;type $k$&#34; whose complementary space has no special entangled state of &#34;type $k$&#34;. This concept can be seem as a generalization of the unextendible product basis (UPB) introduced by Bennett et al. in [ Phys. Rev. Let

Nicolas Crampé, Alfred Michel Grundland

The objective of this paper is to establish a new relationship between the Veronese subsequent analytic solutions of the Euclidean $\mathbb{C}P^{2s}$ sigma model in two dimensions and the orthogonal Krawtchouk polynomials. We show that such solutions of the $\mathbb{C}P^{2s}$ model, defined on the Riemann sphere and having a finite action, can be explicitly

A. Alberto, W. Alvarez, L. Ancari, M. Andrade Uzieda

The LAGO (Latin American Giant Observatory) observatory is an experiment that spans over Latin America in a wide range of latitudes that gives different rigidity cut offs for the enter of cosmic rays in the atmosphere. The motivation of the Observatory is to study atmospheric radiation and space weather through the measurement of the secondary emission of lo

Stanislav Komarov, Alexander Gorbatsievich

We present a research of the time evolution of the redshift of light received from the binary star that moves in the external gravitational field of Kerr black hole. We formulate a method for the solution of inverse problem: calculating of the parameters of relative motion of stars in binary system using the redshift data. The considered formalism has no res

Peter Carr, Liuren Wu, Zhibai Zhang

In this paper we formulate a regression problem to predict realized volatility by using option price data and enhance VIX-styled volatility indices&#39; predictability and liquidity. We test algorithms including regularized regression and machine learning methods such as Feedforward Neural Networks (FNN) on S&P 500 Index and its option data. By conducting a

Jian Shi, Kevin M. Lynch

We investigate in-hand regrasping by pushing an object against an external constraint and allowing sliding at the fingertips. Each fingertip is modeled as attached to a multidimensional spring mounted to a position-controlled anchor. Spring compliance maps contact forces to spring compressions, ensuring the fingers remain in contact, and sliding &#34;complia

Hu Yueqiang, Li Ling, Meng Min, Jin Lei

Metasurfaces hold great potentials for advanced holographic display with extraordinary information capacity and pixel sizes in an ultrathin flat profile. Dual-polarization channel to encode two independent phase profiles or spatially multiplexed meta-holography by interleaved metasurfaces are captivated popular solutions to projecting multiplexed and vectori

K. Navamani

We present the exact analytical equation of diffusion-mobility for two-dimensional (2D) Schrödinger type transport systems, from molecules to materials. The density of electronic states in such Schrödinger systems pertains to the 2D non-relativistic carrier dynamics. We implement the Gaussian function into carrier density derivation; accordingly we develop t

Alfred Michel Grundland, Alexander Hariton

In this paper, it is shown how a combination of approximate symmetries of a nonlinear wave equation with small dissipations and singularity analysis provides exact analytic solutions. We perform the analysis using the Lie symmetry algebra of this equation and identify the conjugacy classes of the one-dimensional subalgebras of this Lie algebra. We show that

Marina Ghisi, Massimo Gobbino

We investigate an abstract wave equation with a time-dependent propagation speed, and we consider both the non-dissipative case, and the case with a strong damping that depends on a power of the elastic operator. Previous results show that, depending on the values of the parameters and on the time regularity of the propagation speed, this equation exhibits e

Anita M. Bunea, Pietro Manfredi, Pompeo Della Posta, Mariangela Guidolin

The paper uses diffusion models to understand the main determinants of diffusion of solar photovoltaic panels (SPP) worldwide, focusing on the role of public incentives. We applied the generalized Bass model (GBM) to adoption data of 26 countries between 1992-2016. The SPP market appears as a frail and complicate one, lacking public media support. Even the m

Xin Han, Yasushi Kawase, Kazuhisa Makino, Haruki Yokomaku

In this paper, we introduce online knapsack problems with a resource buffer. In the problems, we are given a knapsack with capacity $1$, a buffer with capacity $R\ge 1$, and items that arrive one by one. Each arriving item has to be taken into the buffer or discarded on its arrival irrevocably. When every item has arrived, we transfer a subset of items in th

Yuji Nomura, Kouichi Taira

In this note, we study some properties of threshold resonant states or threshold eigenfunctions for discrete Schrödinger operators. We mainly prove two theorems. First, we prove that resonant states at the elliptic threshold have the same asymptotic expansion as the continuous Schrödinger operator. Second, we prove absence of resonant states at hyperbolic th

Kumari Neha, Shashank Srikanth, Sonali Singhal, Shwetanshu Singh

Users on Twitter are identified with the help of their profile attributes that consists of username, display name, profile image, to name a few. The profile attributes that users adopt can reflect their interests, belief, or thematic inclinations. Literature has proposed the implications and significance of profile attribute change for a random population of

Kalobaran Maiti, Tathamay Basu, Sangeeta Thakur, Nishaina Sahadev

In the series R2PdSi3, Nd2PdSi3 is an anomalous compound in the sense that it exhibits ferromagnetic order unlike other members in this family. The magnetic ordering temperature is also unusually high compared to the expected value for a Nd-based system, assuming 4f localization. Here, we have studied the electronic structure of single crystalline Nd2PdSi3 e

João Ribeiro, Francisco S. Melo, João Dias

In this paper we investigate two hypothesis regarding the use of deep reinforcement learning in multiple tasks. The first hypothesis is driven by the question of whether a deep reinforcement learning algorithm, trained on two similar tasks, is able to outperform two single-task, individually trained algorithms, by more efficiently learning a new, similar tas

Tilo Schwalger, Anton V. Chizhov

The dominant modeling framework for understanding cortical computations are heuristic firing rate models. Despite their success, these models fall short to capture spike synchronization effects, to link to biophysical parameters and to describe finite-size fluctuations. In this opinion article, we propose that the refractory density method (RDM), also known

Debasish Pattanayak, John Augustine, Partha Sarathi Mandal

This paper revisits the widely researched \textit{gathering} problem for two robots in a scenario which allows randomization in the asynchronous scheduling model. The scheduler is considered to be the adversary which determines the activation schedule of the robots. The adversary comes in two flavors, namely, oblivious and adaptive, based on the knowledge of

Dongwei Li, Shuliang Wang, Nan Gao, Qiang He

Clustering big data often requires tremendous computational resources where cloud computing is undoubtedly one of the promising solutions. However, the computation cost in the cloud can be unexpectedly high if it cannot be managed properly. The long tail phenomenon has been observed widely in the big data clustering area, which indicates that the majority of

Kevin Zhang, Feng Xiong, Peize Sun, Li Hu

Detecting human in a crowd is a challenging problem due to the uncertainties of occlusion patterns. In this paper, we propose to handle the crowd occlusion problem in human detection by leveraging the head part. Double Anchor RPN is developed to capture body and head parts in pairs. A proposal crossover strategy is introduced to generate high-quality proposa

Mètolidji Moquilas Raymond Affossogbe, Guy Martial Nkiet, Carlos Ogouyandjou

We consider the smoothed version of sliced average variance estimation (SAVE) dimension reduction method for dealing with spatially dependent data that are observations of a strongly mixing random field. We propose kernel estimators for the interest matrix and the effective dimension reduction (EDR) space, and show their consistency.

Laxman K. Malla, Rajneesh Bhardwaj, Adrian Neild

The pattern and profile of a dried colloidal deposit formed after evaporation of a sessile water droplet containing polystyrene particles on a non-uniformly heated glass are investigated experimentally. In particular, the effects of temperature gradient across the substrate and particles size are investigated. The temperature gradient was imposed using Pelti

Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara

Acoustic-to-word (A2W) end-to-end automatic speech recognition (ASR) systems have attracted attention because of an extremely simplified architecture and fast decoding. To alleviate data sparseness issues due to infrequent words, the combination with an acoustic-to-character (A2C) model is investigated. Moreover, the A2C model can be used to recover out-of-v

Amit Moryossef, Ido Dagan, Yoav Goldberg

We follow the step-by-step approach to neural data-to-text generation we proposed in Moryossef et al (2019), in which the generation process is divided into a text-planning stage followed by a plan-realization stage. We suggest four extensions to that framework: (1) we introduce a trainable neural planning component that can generate effective plans several

Roman Föll, Ingo Steinwart

Variational approximation techniques and inference for stochastic models in machine learning has gained much attention the last years. Especially in the case of Gaussian Processes (GP) and their deep versions, Deep Gaussian Processes (DGPs), these viewpoints improved state of the art work. In this paper we introduce Probably Approximately Correct (PAC)-Bayes

Mingqi Hu, Deyu Zhou, Yulan He

In this paper, we propose a novel variational generator framework for conditional GANs to catch semantic details for improving the generation quality and diversity. Traditional generators in conditional GANs simply concatenate the conditional vector with the noise as the input representation, which is directly employed for upsampling operations. However, the