September 2019 arXiv papers — page 25

Charbel Cherfan, Isam Manai, Samir Zemmouri, Jean-Claude Garreau

We demonstrate a laser frequency stabilization technique for laser cooling of Potassium atoms, based on saturated absorption spectroscopy in the C-Band optical telecommunication window, using ro-vibrationel transitions of the acetylene molecule ($12$C$_2$H$_2$). We identified and characterized several molecular lines, which allow to address each of the potas

Thanh Le, Vasant Honavar

The Dynamical Gaussian Process Latent Variable Models provide an elegant non-parametric framework for learning the low dimensional representations of the high-dimensional time-series. Real world observational studies, however, are often ill-conditioned: the observations can be noisy, not assuming the luxury of relatively complete and equally spaced like thos

Kristian Debrabant, Anne Kværnø, Nicky Cordua Mattsson

In this paper, we present a framework to construct general stochastic Runge-Kutta Lawson schemes. We prove that the schemes inherit the consistency and convergence properties of the underlying Runge-Kutta scheme, and confirm this in some numerical experiments. We also investigate the stability properties of the methods and show for some examples, that the ne

Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana, Haitham Bou Ammar

Recently, $\alpha$-Rank, a graph-based algorithm, has been proposed as a solution to ranking joint policy profiles in large scale multi-agent systems. $\alpha$-Rank claimed tractability through a polynomial time implementation with respect to the total number of pure strategy profiles. Here, we note that inputs to the algorithm were not clearly specified in

Daniele Bertacca, Angelo Ricciardone, Nicola Bellomo, Alexander C. Jenkins

The detection and characterization of the Stochastic Gravitational Wave Background (SGWB) is one of the main goals of Gravitational Wave (GW) experiments. The observed SGWB will be the combination of GWs from cosmological (as predicted by many models describing the physics of the early Universe) and astrophysical origins, which will arise from the superposit

Tristan Bepler, Ellen D. Zhong, Kotaro Kelley, Edward Brignole

Given an image dataset, we are often interested in finding data generative factors that encode semantic content independently from pose variables such as rotation and translation. However, current disentanglement approaches do not impose any specific structure on the learned latent representations. We propose a method for explicitly disentangling image rotat

Celia García-Pareja, Henrik Hult, Timo Koski

In this paper an exact rejection algorithm for simulating paths of the coupled Wright-Fisher diffusion is introduced. The coupled Wright-Fisher diffusion is a family of multidimensional Wright-Fisher diffusions that have drifts depending on each other through a coupling term and that find applications in the study of interacting genes' networks as those enco

Ayush Singh, Seyed Sadegh Mohseni Salehi, Ali Gholipour

Fetal magnetic resonance imaging (MRI) is challenged by uncontrollable, large, and irregular fetal movements. It is, therefore, performed through visual monitoring of fetal motion and repeated acquisitions to ensure diagnostic-quality images are acquired. Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level o

Shujie Cui, Xiangfu Song, Muhammad Rizwan Asghar, Steven D Galbraith

Searchable Encryption (SE) is a technique that allows Cloud Service Providers (CSPs) to search over encrypted datasets without learning the content of queries and records. In recent years, many SE schemes have been proposed to protect outsourced data from CSPs. Unfortunately, most of them leak sensitive information, from which the CSPs could still infer the

Vera Fischer, Diana Carolina Montoya

We study higher analogues of the classical independence number on $\omega$. For $\kappa$ regular uncountable, we denote by $i(\kappa)$ the minimal size of a maximal $\kappa$-independent family. We establish ZFC relations between $i(\kappa)$ and the standard higher analogues of some of the classical cardinal characteristics, e.g. $\mathfrak{r}(\kappa)\leq\mat

Huan Wang

We study the cohomology with high tensor powers of Nakano $q$-semipositive line bundles on complex manifolds. We obtain the asymptotic estimates for the dimension of cohomology with high tensor powers of semipositive line bundles over q-convex manifolds and various possibly non-compact complex manifolds, in which the order of estimates are optimal. Besides,

G. Hall, M. Mansi, I. Makrant

Block-chain world is very dynamic and there is need for strong governance and underlying technology architecture to be robust to face challenges. This paper considers Ethereum, a leading block chain. We deep dive into the nature of this block chain, wherein for software upgrades forks are performed. They types of forks and impact is discussed. A specific Eth

Dóra Gréta Petróczy, László Csató

A model is proposed to allocate Formula One World Championship prize money among the constructors. The methodology is based on pairwise comparison matrices, allows for the use of any weighting method, and makes possible to tune the level of inequality. We introduce an axiom called scale invariance, which requires the ranking of the teams to be independent of

MAGIC Collaboration, V. A. Acciari, S. Ansoldi, L. A. Antonelli

Extreme high-energy peaked BL Lac objects (EHBLs) are an emerging class of blazars. Their typical two-hump structured spectral energy distribution (SED) peaks at higher energies with respect to conventional blazars. Multi-wavelength (MWL) observations constrain their synchrotron peak in the medium to hard X-ray band. Their gamma-ray SED peaks above the GeV b

Fabrizio Minganti, Adam Miranowicz, Ravindra W. Chhajlany, Franco Nori

Exceptional points (EPs) correspond to degeneracies of open systems. These are attracting much interest in optics, optoelectronics, plasmonics, and condensed matter physics. In the classical and semiclassical approaches, Hamiltonian EPs (HEPs) are usually defined as degeneracies of non-Hermitian Hamiltonians such that at least two eigenfrequencies are identi

Tra Huynh, Eleanor C Sayre

Mathematics is the language of science. Fluent and productive use of mathematics requires one to understand the meaning embodied in mathematical symbols, operators, syntax, etc., which can be a difficult task. For instance, in algebraic symbolization, the negative and positive signs carry multiple meanings depending on contexts. In the context of electromagn

Alexandr Buryak, Paolo Rossi

In this paper we compute the intersection number of two double ramification cycles (with different ramification profiles) and the top Chern class of the Hodge bundle on the moduli space of stable curves of any genus. These quadratic double ramification integrals are the main ingredient for the computation of the double ramification hierarchy associated to th

Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin

Rapid intensification (RI) of tropical cyclones often causes major destruction to human civilization due to short response time. It is an important yet challenging task to accurately predict this kind of extreme weather event in advance. Traditionally, meteorologists tackle the task with human-driven feature extraction and predictor correction procedures. Ne

Robin J. Dolleman, Yaroslav M. Blanter, Herre S. J. van der Zant, Peter G. Steeneken

Recent experiments have shown surprisingly large thermal time constants in suspended graphene ranging from 10 to 100 ns in drums with a diameter ranging from 2 to 7 microns. The large time constants and their scaling with diameter points towards a thermal resistance at the edge of the drum. However, an explanation of the microscopic origin of this resistance

Robin J. Dolleman, Gerard J. Verbiest, Yaroslav M. Blanter, Herre S. J. van der Zant

Recent theory has predicted large temperature differences between the in-plane (LA and TA) and out-of-plane (ZA) acoustic phonon baths in locally-heated suspended graphene. To verify these predictions, and their implications for understanding the nonequilibrium thermodynamics of 2D materials, experimental techniques are needed. Here, we present a method to d

Alexander Mazurenko, Vladimir A. Stukopin

We consider fundamental facts from the theory of Hopf superalgebras. We use them to construct the quantum double of the quantum superalgebra $sl(2|1)$ at roots of unity. Thus we obtain a multiplicative formula for universal $R$-matrix. Next we construct an $R$-matrix to investigate parametrized family of centralizer algebras. We give multiplication laws in p

Francesco Benini, Dongmin Gang, Leopoldo A. Pando Zayas

We compute the superconformal index of 3d $\mathcal{N}=2$ superconformal theories obtained from $N$ M5-branes wrapped on a hyperbolic 3-manifold. Exploiting the 3d-3d correspondence, we use perturbative invariants of $SL(N,\mathbb{C})$ Chern-Simons theory to determine the superconformal index in the large $N$ limit, including corrections logarithmic in $N$.

Chris Timberlake, Giulio Gasbarri, Andrea Vinante, Ashley Setter

We experimentally demonstrate stable trapping of a permanent magnet sphere above a lead superconductor, in vacuum pressures of $4 \times 10^{-8}$~mbar. The levitating magnet behaves as a harmonic oscillator, with frequencies in the 4-31~Hz range detected, and shows promise to be an ultrasensitive acceleration sensor. We directly apply an acceleration to the

Carl Allen, Ivana Balažević, Timothy Hospedales

Many models learn representations of knowledge graph data by exploiting its low-rank latent structure, encoding known relations between entities and enabling unknown facts to be inferred. To predict whether a relation holds between entities, embeddings are typically compared in the latent space following a relation-specific mapping. Whilst their predictive p

Saloni Bhatiani, Xinyu Dai, Eduardo Guerras

Quasar microlensing serves as a unique probe of discrete objects within galaxies and galaxy clusters. Recent advancement of the technique shows that it can constrain planet-scale objects beyond our native galaxy by studying their induced microlensing signatures, the energy shift of emission lines originated in the vicinity of the black hole of high redshift

Fernando G. Gardim, Giuliano Giacalone, Jean-Yves Ollitrault

We predict that the mean transverse momentum of charged hadrons $\langle p_t\rangle$ rises as a function of the charged-particle multiplicity in ultracentral nucleus-nucleus collisions. We explain that this phenomenon has a simple physical origin and represents an unambiguous prediction of the hydrodynamic framework of heavy-ion collisions. We argue that the

Luka Grubišić, Harri Hakula, Mikael Laaksonen

We consider computing eigenspaces of an elliptic self-adjoint operator depending on a countable number of parameters in an affine fashion. The eigenspaces of interest are assumed to be isolated in the sense that the corresponding eigenvalues are separated from the rest of the spectrum for all values of the parameters. We show that such eigenspaces can in fac

Tao Guo, Ruida Zhou, Chao Tian

We consider information leakage to the user in private information retrieval (PIR) systems. Information leakage can be measured in terms of individual message leakage or total leakage. Individual message leakage, or simply individual leakage, is defined as the amount of information that the user can obtain on any individual message that is not being requeste

Xudong Liu, Christian Fritz, Matthew Klenk

Despite a tremendous amount of work in the literature and in the commercial sectors, current approaches to multi-modal trip planning still fail to consistently generate plans that users deem optimal in practice. We believe that this is due to the fact that current planners fail to capture the true preferences of users, e.g., their preferences depend on aspec

Michael Fiedler, Thomas Richthammer

While 2D Gibbsian particle systems might exhibit orientational order resulting in a lattice-like structure, these particle systems do not exhibit positional order if the interaction between particles satisfies some weak assumptions. Here we investigate to which extent particles within a box of size $2n \times 2n$ may fluctuate from their ideal lattice positi

Ameya D. Jagtap, Kenji Kawaguchi, George Em Karniadakis

We propose two approaches of locally adaptive activation functions namely, layer-wise and neuron-wise locally adaptive activation functions, which improve the performance of deep and physics-informed neural networks. The local adaptation of activation function is achieved by introducing a scalable parameter in each layer (layer-wise) and for every neuron (ne

Yoshimichi Nakatsuka, Andrew Paverd, Gene Tsudik

Security and privacy of the Internet Domain Name System (DNS) have been longstanding concerns. Recently, there is a trend to protect DNS traffic using Transport Layer Security (TLS). However, at least two major issues remain: (1) how do clients authenticate DNS-over-TLS endpoints in a scalable and extensible manner; and (2) how can clients trust endpoints to

Sayan Bhattacharya, Monika Henzinger, Danupon Nanongkai

We present a deterministic dynamic algorithm for maintaining a $(1+\epsilon)f$-approximate minimum cost set cover with $O(f\log(Cn)/\epsilon^2)$ amortized update time, when the input set system is undergoing element insertions and deletions. Here, $n$ denotes the number of elements, each element appears in at most $f$ sets, and the cost of each set lies in t

Rochdi Ben Charrada, Aziz El Kacimi Alaoui

Let ${\cal F}$ be a complex affine Reeb foliation of dimension $1$ on the Hopf manifold ${\Bbb S}^{n+1}\times {\Bbb S}^1$. We prove that its foliated Dolbeault cohomology in degree $1$ is isomorphic to ${\Bbb C}$ by giving an explicit generator.

Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang

The unmanned aerial vehicles base stations (UAV-BSs) have great potential in being widely used in many dynamic application scenarios. In those scenarios, the movements of served user equipments (UEs) are inevitable, so the UAV-BSs needs to be re-positioned dynamically for providing seamless services. In this paper, we propose a system framework consisting of

Youness Azimzade, Abbas Ali Saberi

Here, we investigate how competition in the Eden model is affected by short range dispersal and the requirement that site updates occur only after several updates of the same site have been attempted previously. The latter models the effect of tissue or media resistance to invasion. We found that the existence of tissue intensifies 'Natural Selection' and de

Soujanya Ponnapalli, Aashaka Shah, Amy Tai, Souvik Banerjee

Public blockchains like Ethereum use Merkle trees to verify transactions received from untrusted servers before applying them to the blockchain. We empirically show that the low throughput of such blockchains is due to the I/O bottleneck associated with using Merkle trees for processing transactions. We present RAINBLOCK, a new architecture for public blockc

Hong-Hua Fang, Jie Yang, Sampson Adjokatse, Machteld E. Kamminga

Two-dimensional (2D) perovskite materials have recently re-attracted intense research interest for applications in photovoltaics and optoelectronics. As a consequence of the dielectric and quantum confinement effect, they show strongly bound and stable excitons at room temperature. In this report, the band-edge exciton fine structure and in particular its ex

Ziliang Chen, Zhanfu Yang

It is feasible and practically-valuable to bridge the characteristics between graph neural networks (GNNs) and logical reasoning. Despite considerable efforts and successes witnessed to solve Boolean satisfiability (SAT), it remains a mystery of GNN-based solvers for more complex predicate logic formulae. In this work, we conjectures with some evidences, tha

András Csóré, Adam Gali

Paramagnetic point defects in solids may exhibit a rich set of interesting and not yet fully resolved physics. In particular, character of wavefunctions and electron-phonon coupling in these defects may highly influence their interaction with external magnetic fields. Complex interplay between the electronic orbitals, phonons and electron spin determines the

N. J. Klingler, J. A. Kennea, P. A. Evans, A. Tohuvavohu

The Neil Gehrels Swift Observatory carried out prompt searches for gravitational wave (GW) events detected by the LIGO/Virgo Collaboration (LVC) during the second observing run ("O2"). Swift performed extensive tiling of eight LVC triggers, two of which had very low false-alarm rates (GW 170814 and the epochal GW 170817), indicating a high confidence of bein

Li-Chun Wang, Chuan-Chi Lai, Hong-Han Shuai, Hsin-Piao Lin

Future mobile communication networks require an Aerial Base Station (ABS) with fast mobility and long-term hovering capabilities. At present, unmanned aerial vehicles (UAV) or drones do not have long flight times and are mainly used for monitoring, surveillance, and image post-processing. On the other hand, the traditional airship is too large and not easy t

E. Roueff, H. Abgrall, P. Czachorowski, K. Pachucki

The high spectral resolution R about 45,000 provided by IGRINS (Immersion Grating INfrared Spectrometer) at MacDonald Observatory and R 100,000 achieved by CRIRES (CRyogenic high-resolution InfraRed Echelle Spectrograph) at VLT (Very Large Telescope) challenges the present knowledge of infrared spectra. aims We aim to predict the full infrared spectrum of mo

Hongwei Mei, George Yin

This paper focuses on a class of continuous-time controlled Markov chains with time-inconsistent and distribution-dependent cost functional (in some appropriate sense). A new definition of time-inconsistent distribution-dependent equilibrium in closed-loop sense is given and its existence and uniqueness have been established. Because of the time-inconsistenc

Simon Schmitt, Matteo Hessel, Karen Simonyan

We investigate the combination of actor-critic reinforcement learning algorithms with uniform large-scale experience replay and propose solutions for two challenges: (a) efficient actor-critic learning with experience replay (b) stability of off-policy learning where agents learn from other agents behaviour. We employ those insights to accelerate hyper-param

Jung-Wan Ryu, Jinhang Cho, Soo-Young Lee, Yushin Kim

In the case of two-dimensional gradient index cavities designed by the conformal transformation optics, we propose a boundary integral equation method for the calculation of resonant mode functions by employing a fictitious space which is reciprocally equivalent to the physical space. Using the Green's function of the interior region of the uniform index cav

Alessandro Valentini, Andrea Micheli, Alessandro Cimatti

Automated temporal planning is the technology of choice when controlling systems that can execute more actions in parallel and when temporal constraints, such as deadlines, are needed in the model. One limitation of several action-based planning systems is that actions are modeled as intervals having conditions and effects only at the extremes and as invaria

Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar

Deep Graph Neural Networks (GNNs) are useful models for graph classification and graph-based regression tasks. In these tasks, graph pooling is a critical ingredient by which GNNs adapt to input graphs of varying size and structure. We propose a new graph pooling operation based on compressive Haar transforms -- HaarPooling. HaarPooling implements a cascade

Benoit Nennig, Emmanuel Perrey-Debain

A numerical algorithm is proposed to explore in a systematic way the trajectories of the eigenvalues of non-Hermitian matrices in the parametric space and exploit this in order to find the locations of defective eigenvalues in the complex plane. These non-Hermitian degeneracies also called exceptional points (EP) have raised considerable attention in the sci

Sean Eberhard, Jeff Kahn, Bhargav Narayanan, Sophie Spirkl

A family of vectors $A \subset [k]^n$ is said to be intersecting if any two elements of $A$ agree on at least one coordinate. We prove, for fixed $k \ge 3$, that the size of a symmetric intersecting subfamily of $[k]^n$ is $o(k^n)$, which is in stark contrast to the case of the Boolean hypercube (where $k =2$). Our main contribution addresses limitations of

Panagiotis Charalampopoulos, Tomasz Kociumaka, Manal Mohamed, Jakub Radoszewski

We introduce data structures answering queries concerning the occurrences of patterns from a given dictionary $\mathcal{D}$ in fragments of a given string $T$ of length $n$. The dictionary is internal in the sense that each pattern in $\mathcal{D}$ is given as a fragment of $T$. This way, $\mathcal{D}$ takes space proportional to the number of patterns $d=|\

Karin Stacke, Gabriel Eilertsen, Jonas Unger, Claes Lundström

Domain shift is a significant problem in histopathology. There can be large differences in data characteristics of whole-slide images between medical centers and scanners, making generalization of deep learning to unseen data difficult. To gain a better understanding of the problem, we present a study on convolutional neural networks trained for tumor classi

Karsten Roth, Biagio Brattoli, Björn Ommer

Metric learning seeks to embed images of objects suchthat class-defined relations are captured by the embeddingspace. However, variability in images is not just due to different depicted object classes, but also depends on other latent characteristics such as viewpoint or illumination. In addition to these structured properties, random noise further obstruct

Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen, Duc Thanh Nguyen

Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. One of those deep learning-powered applications recently emerged

Dar Gilboa, Guy Gur-Ari

Transferability of learned features between tasks can massively reduce the cost of training a neural network on a novel task. We investigate the effect of network width on learned features using activation atlases --- a visualization technique that captures features the entire hidden state responds to, as opposed to individual neurons alone. We find that, wh

Wayne Zheng, Zheng-Yu Weng

In contrast to the conventional von Neumann bipartite entanglement entropy (bEE), we show that a more appropriate description of the one-dimensional doped Mott insulator is a new kind of mutual entanglement entropy (mEE) between the charge and spin degrees of freedom. Such a charge-spin mEE can clearly distinguish the important and distinct features between

Andrea Aspri, Yury Korolev, Otmar Scherzer

We study linear inverse problems under the premise that the forward operator is not at hand but given indirectly through some input-output training pairs. We demonstrate that regularization by projection and variational regularization can be formulated by using the training data only and without making use of the forward operator. We study convergence and st

Samantha Walker, Carlos E. Sierra, Jason E. Austermann, James A. Beall

We describe the design and measurement of feedhorn-coupled, transition-edge sensor (TES) polarimeters with two passbands centered at 220 GHz and 280 GHz, intended for observations of the cosmic microwave background. Each pixel couples polarized light in two linear polarizations by use of a planar orthomode transducer and senses power via four TES bolometers,

Tobias Barker

In this paper we consider classes of initial data that ensure local-in-time Hadamard well-posedness of the associated weak Leray-Hopf solutions of the three-dimensional Navier-Stokes equations. In particular, for any solenodial $L_{2}$ initial data $u_{0}$ belonging to certain subsets of $VMO^{-1}(\mathbb{R}^3)$, we show that weak Leray-Hopf solutions depend

David Cushing, Supanat Kamtue, Riikka Kangaslampi, Shiping Liu

In this paper, we compare Ollivier Ricci curvature and Bakry-\'Emery curvature notions on combinatorial graphs and discuss connections to various types of Ricci flatness. We show that non-negativity of Ollivier Ricci curvature implies non-negativity of Bakry-\'Emery curvature under triangle-freeness and an additional in-degree condition. We also provide exam

Giacomo Aletti

This paper develops a new mathematical-statistical approach to analyze a class of Flajolet-Martin algorithms (FMa), and provides analytical confidence intervals for the number F0 of distinct elements in a stream, based on Chernoff bounds. The class of FMa has reached a significant popularity in bigdata stream learning, and the attention of the literature has

Dirk Pauly, Jan Valdman

We give some theoretical as well as computational results on Laplace and Maxwell constants. Besides the classical de Rham complex we investigate the complex of elasticity and the complex related to the biharmonic equation and general relativity as well using the general functional analytical concept of Hilbert complexes. We consider mixed boundary conditions

Zhijin Qin, Xiangwei Zhou, Lin Zhang, Yue Gao

It has been 20 years since the concept of cognitive radio (CR) was proposed, which is an efficient approach to provide more access opportunities to connect massive wireless devices. To improve the spectrum efficiency, CR enables unlicensed usage of licensed spectrum resources. It has been regarded as the key enabler for intelligent communications. In this ar

Kung-Ching Lin

In deterministic compressive sensing, one constructs sampling matrices that recover sparse signals from highly incomplete measurements. However, the so-called square-root bottleneck limits the usefulness of such matrices, as they are only able to recover exceedingly sparse signals with respect to the matrix dimension. In view of the flat restricted isometry

Jessica Welding, Peter Neal

Infectious diseases have severe health and economic consequences for society. It is important in controlling the spread of an emerging infectious disease to be able to both estimate the parameters of the underlying model and identify those individuals most at risk of infection in a timely manner. This requires having a mechanism to update inference on the mo

Fatemeh Bagheri, Sedighe Sajadian, Sohrab Rahvar

We investigate the possibility of exoplanet detection orbiting source stars in microlensing events through WFIRST observations. We perform a Monto Carlo simulation on the detection rate of exoplanets via microlensing, assuming that each source star has at least one exoplanet. The exoplanet can reflect part of the light from the parent star or emit internal t

Avi Cohen, David Peleg

The classical Hotelling game is played on a line segment whose points represent uniformly distributed clients. The $n$ players of the game are servers who need to place themselves on the line segment, and once this is done, each client gets served by the player closest to it. The goal of each player is to choose its location so as to maximize the number of c

Guillaume Barraquand, Pierre Le Doussal, Alberto Rosso

We study the Kardar-Parisi-Zhang (KPZ) growth equation in one dimension with a noise variance $c(t)$ depending on time. We find that for $c(t)\propto t^{-\alpha}$ there is a transition at $\alpha=1/2$. When $\alpha>1/2$, the solution saturates at large times towards a non-universal limiting distribution. When $\alpha<1/2$ the fluctuation field is governed by

Angela Fan, Edouard Grave, Armand Joulin

Overparameterized transformer networks have obtained state of the art results in various natural language processing tasks, such as machine translation, language modeling, and question answering. These models contain hundreds of millions of parameters, necessitating a large amount of computation and making them prone to overfitting. In this work, we explore

Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler

Batch training of machine learning models based on neural networks is now well established, whereas to date streaming methods are largely based on linear models. To go beyond linear in the online setting, nonparametric methods are of interest due to their universality and ability to stably incorporate new information via convexity or Bayes' Rule. Unfortunate

Chuan-Chi Lai, Li-Chun Wang, Zhu Han

In this paper, we consider an Unmanned Aerial Vehicle (UAV)-assisted cellular system which consists of multiple UAV base stations (BSs) cooperating the terrestrial BSs. In such a heterogeneous network, for cellular operators, the problem is how to determine the appropriate number, locations, and altitudes of UAV-BSs to improve the system sumrate as well as s

Alix Lhéritier

Pairwise Choice Markov Chains (PCMC) have been recently introduced to overcome limitations of choice models based on traditional axioms unable to express empirical observations from modern behavior economics like context effects occurring when a choice between two options is altered by adding a third alternative. The inference approach that estimates the tra

Victor E. Ambrus, Felix Sharipov, Victor Sofonea

In this paper, we consider the capabilities of the Boltzmann equation with the Shakhov and ellipsoidal models for the collision term to capture the characteristics of rarefied gas flows. The benchmark is performed by comparing the results obtained using these kinetic model equations with direct simulation Monte Carlo (DSMC) results for particles interacting

Tobias Diez, Tudor S. Ratiu

Given a closed surface endowed with a volume form, we equip the space of compatible Riemannian structures with the structure of an infinite-dimensional symplectic manifold. We show that the natural action of the group of volume-preserving diffeomorphisms by push-forward has a group-valued momentum map that assigns to a Riemannian metric the canonical bundle.

Aksel Kobiałka, Nicholas Sedlmayr, Maciej M. Maśka, Tadeusz Domański

We analyze influence of a dimerization on the topological phases of the Rashba nanowire proximitized to a superconducting substrate. We find that periodic alternations of the hopping integral and spin-orbit coupling can lead to band inversion, inducing transition to topologically nontrivial superconducting phase that hosts the Majorana zero-energy modes. Thi

Christian Simon, Matteo Torcoli, Jouni Paulus

Broadcasting and streaming services still suffer from various levels of accessibility barriers for a significant portion of the population, limiting the access to information and culture, and in the most severe cases limiting the empowerment of people. This paper provides a brief overview of some of the most common accessibility barriers encountered. It then

Naqeeb ur Rehman

Hurwitz orbits are the orbits of the braid group action on the powers of a rack. Hurwitz orbits for the action of the braid group on three strands are used in \cite{21} and \cite{22} for the classification of Nichols algebras. This classification is based on a combinatorial invariant called plague on the Hurwitz orbits. The method to calculate plagues on the

Clark Butler, Kiho Park

We study singular value potentials of H\"older continuous $GL_2(\mathbb{R})$-cocycles over hyperbolic systems whose canonical holonomies converge and are H\"older continuous. Such cocycles include locally constant $GL_2(\mathbb{R})$-cocycles as well as fiber-bunched $GL_2(\mathbb{R})$-cocycles. We show that singular value potentials of irreducible such cocyc

J. F. Wang, G. Qin

The equation $\kappa_{zz}=d\sigma^2/(2dt)$ (hereafter DCDV) is a well-known formula of energetic particles describing the relation of parallel diffusion coefficient $\kappa_{zz}$ with the parallel displacement variance $\sigma^2$. In this study, we find that DCDV is only applicable to two kinds of transport equations of isotropic distribution function, one i

Thotsaporn "Aek" Thanatipanonda, Doron Zeilberger

In the spirit of "multi-culturalism", we use four kinds of computations: simulation, numeric, symbolic, and "conceptual" to explore some "games of pure chance" inspired by children board games like "Snakes and Ladders" (aka as "Chutes and Ladders") and "gambler's ruin with unlimited credit". Even more interesting than the many computer-generated actual resul

Azadeh Maleknejad

Remarkably, if $CP$ was spontaneously broken in the physics of inflation, fermions would notice and remember it. Based on that, we present a new (non-thermal) mechanism for generating self-interacting dark Dirac fermions prior to the Hot Big Bang. The non-Abelian gauge fields and axions are well-motivated matter contents for the particle physics of inflation

Alexander Koryagin, Roman Khudorozkov, Sergey Tsimfer

Recently, a lot of papers proposed to use neural networks to approximately solve partial differential equations (PDEs). Yet, there has been a lack of flexible framework for convenient experimentation. In an attempt to fill the gap, we introduce a PyDEns-module open-sourced on GitHub. Coupled with capabilities of BatchFlow, open-source framework for convenien

Jack W. D. Skipper, Emil Wiedemann

We show weak lower semi-continuity of functionals assuming the new notion of a "convexly constrained" $\mathcal A$-quasiconvex integrand. We assume $\mathcal A$-quasiconvexity only for functions defined on a set $K$ which is convex. Assuming this and sufficient integrability of the sequence we show that the functional is still (sequentially) weakly lower sem

Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gu

Program verification offers a framework for ensuring program correctness and therefore systematically eliminating different classes of bugs. Inferring loop invariants is one of the main challenges behind automated verification of real-world programs which often contain many loops. In this paper, we present Continuous Logic Network (CLN), a novel neural archi

Jan Sperrhake, Matthias Falkner, Stefan Fasold, Thomas Kaiser

We show the existence of virtual polarization states during the interaction of modes in metasurface stacks. In support of our findings we experimentally realize a metasurface stack, consisting of an isotropic layer of nano-patches and an anisotropic layer of nano-wires. Utilizing an analogy to the interaction of electrons at junctions in mesoscopic electron

Claude Godrèche

Renewal processes generated by a power-law distribution of intervals with tail index less than unity are genuinely non-stationary. This issue is illustrated by a critical review of the recent paper by Barma, Majumdar and Mukamel 2019 \textit{J.~Phys.~A} {\bf 52} 254001, devoted to the investigation of the properties of a specific one-dimensional equilibrium

Giovanna Carnovale

Let G be a connected reductive algebraic group over an algebraically closed field k. We consider the strata in G defined by Lusztig as fibers of a map given in terms truncated induction of Springer representations. We extend to arbitrary characteristic the following two results: Lusztig's strata are locally closed and the irreducible components of a stratum

Anastasia Kruchinina

In this work we present and evaluate an implementation of the purify-shift-and-project method [J. Chem. Phys. 128, 176101 (2008)] for linear scaling computation of multiple eigenvectors around the homo-lumo gap of the Fock/Kohn-Sham matrix. Recursive polynomial expansions allow for linear scaling density matrix construction if matrices are sufficiently spars

S. I. Kruglov

Dyonic black hole solutions with spherically symmetric configurations within general relativity are investigated where the source of the gravitational field is Born - Infeld-type electrodynamics. Corrections to Coulomb's law and Reissner - Nordstrom solutions are obtained. From principles of causality and unitarity we find the restriction on electric and mag

Hongyu Sun, Laurent Demanet

The lack of low frequency information and a good initial model can seriously affect the success of full waveform inversion (FWI), due to the inherent cycle skipping problem. Computational low frequency extrapolation is in principle the most direct way to address this issue. By considering bandwidth extension as a regression problem in machine learning, we pr

Xiao Huang, Li Dong, Elizabeth Boschee, Nanyun Peng

Named entity recognition (NER) identifies typed entity mentions in raw text. While the task is well-established, there is no universally used tagset: often, datasets are annotated for use in downstream applications and accordingly only cover a small set of entity types relevant to a particular task. For instance, in the biomedical domain, one corpus might an

L. C. Oostrum, J. van Leeuwen, Y. Maan, T. Coenen

Binary millisecond pulsars (MSPs) provide several opportunities for research of fundamental physics. However, finding them can be challenging. Several subdwarf B (sdB) binary systems with possible neutron star companions have been identified, allowing us to perform a targeted search for MSPs within these systems. Six sdBs with companions in the neutron star

Dario Pierotti, Nicola Soave, Gianmaria Verzini

We consider the mass-critical nonlinear Schr\"odinger equation on non-compact metric graphs. A quite complete description of the structure of the ground states, which correspond to global minimizers of the energy functional under a mass constraint, is provided by Adami, Serra and Tilli in arXiv:1605.07666, where it is proved that existence and properties of

Yangang Chen, Justin W. L. Wan

We propose a deep neural network framework for computing prices and deltas of American options in high dimensions. The architecture of the framework is a sequence of neural networks, where each network learns the difference of the price functions between adjacent timesteps. We introduce the least squares residual of the associated backward stochastic differe

Ioannis Gkolias, Jerome Daquin, Despoina K. Skoulidou, Kleomenis Tsiganis

Navigation satellites are known from numerical studies to reside in a dynamically sensitive environment, which may be of profound importance for their long-term sustainability. We derive the fundamental Hamiltonian of GNSS dynamics and show analytically that near-circular trajectories lie in the neighborhood of a Normally Hyperbolic Invariant Manifold (NHIM)

Panu Lahti, Xiaodan Zhou

In this paper, we study functions of bounded variation on a complete and connected metric space with finite one-dimensional Hausdorff measure. The definition of BV functions on a compact interval based on pointwise variation is extended to this general setting. We show this definition of BV functions is equivalent to the BV functions introduced by Miranda. F

Dharm Veer Singh, Sanjay Siwach

We discuss the first law of thermodynamics of Bardeen black hole. The presence of magnetic monopole charge modifies the energy and we define the temperature of the system accordingly. We introduce a lower cut-off to the space time by introducing a spherical surface, which can be identified with the event horizon. The corresponding temperature is identified w

Jordi Borras, Gregori Vazquez

A novel scenario-adapted distributed signaling technique in the context of opportunistic communications is presented in this work. Each opportunistic user acquires locally sampled observations from the wireless environment to determine the occupied and available degrees-of-freedom (DoF). Due to sensing errors and locality of observations, a performance loss

Wei Hao Khoong

In this paper, we describe the hyper-parameter search problem in the field of machine learning and present a heuristic approach in an attempt to tackle it. In most learning algorithms, a set of hyper-parameters must be determined before training commences. The choice of hyper-parameters can affect the final model's performance significantly, but yet determin

Leihong Zhang, Li Wang, Zhaojun Bai, Ren-cang Li

We propose an efficient algorithm for solving orthogonal canonical correlation analysis (OCCA) in the form of trace-fractional structure and orthogonal linear projections. Even though orthogonality has been widely used and proved to be a useful criterion for pattern recognition and feature extraction, existing methods for solving OCCA problem are either nume