June 2019 arXiv papers — page 34

Marco Caroccia, Antonin Chambolle, Dejan Slepčev

We consider adaptations of the Mumford-Shah functional to graphs. These are based on discretizations of nonlocal approximations to the Mumford-Shah functional. Motivated by applications in machine learning we study the random geometric graphs associated to random samples of a measure. We establish the conditions on the graph constructions under which the min

Kenji Tomita

Renormalized cosmological models based on the general-relativistic second-order perturbation theory were proposed in the previous papers to solve a tension on the observed Hubble constants. The cosmological random adiabatic fluctuations were found to play an important role as the first-order perturbations. The second-order metric perturbations in a previous

D. Kaledin, A. Konovalov, K. Magidson

We revisit the non-commutative Hodge-to-de Rham Degeneration Theorem of the first author, and present its proof in a somewhat streamlined and improved form that explicitly uses spectral algebraic geometry. We also try to explain why topology is essential to the proof.

Thomas Lockard, Marius Millot, Burkhard Militzer, Sebastien Hamel

Equations of state (EOS) calculated from a computationally efficient atom-in-jellium treatment of the electronic structure have recently been shown to be consistent with more rigorous path integral Monte Carlo (PIMC) and quantum molecular dynamics (QMD) simulations of metals in the warm dense matter regime. Here we apply the atom-in-jellium model to predict

L. Dell'Anna, L. Barbiero, A. Trombettoni

The Motzkin and Fredkin quantum spin chains are described by frustration-free Hamiltonians recently introduced and studied because of their anomalous behaviors in the correlation functions and in the entanglement properties. In this paper we analyze their quantum dynamical properties, focusing in particular on the time evolution of the excitations driven by

Jeffrey Mc Hugh, Kurt Andresen, Ulrich F. Keyser

We present our findings on the changes to electroosmotic flow outside glass nanopores with respect to the choice of Group 1 cation species. In contrast with standard electrokinetic theory, flow reversal was observed for all salts under a negative driving voltage. Moving down Group 1 resulted in weaker flow when the driving voltage was negative, in line with

Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu

This paper studies recommender systems with knowledge graphs, which can effectively address the problems of data sparsity and cold start. Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations. Though these

Michel Barbeau, Joaquin Garcia-Alfaro, Evangelos Kranakis, Fillipe Santos

We present an error tolerant path planning algorithm for Micro Aerial Vehicle (MAV) swarms. We assume navigation without GPS-like techniques. The MAVs find their path using sensors and cameras, identifying and following a series of visual landmarks. The visual landmarks lead the MAVs towards their destination. MAVs are assumed to be unaware of the terrain an

Bert Lindenhovius, Michael Mislove, Vladimir Zamdzhiev

We describe a type system with mixed linear and non-linear recursive types called LNL-FPC (the linear/non-linear fixpoint calculus). The type system supports linear typing, which enhances the safety properties of programs, but also supports non-linear typing as well, which makes the type system more convenient for programming. Just as in FPC, we show that LN

Jérôme Darbon, Tingwei Meng

This paper provides new theoretical connections between multi-time Hamilton-Jacobi partial differential equations and variational image decomposition models in imaging sciences. We show that the minimal values of these optimization problems are governed by multi-time Hamilton-Jacobi partial differential equations. The minimizers of these optimization problem

Gábor Lugosi, Jakub Truszkowski, Vasiliki Velona, Piotr Zwiernik

We study the problem of recovering the structure underlying large Gaussian graphical models or, more generally, partial correlation graphs. In high-dimensional problems it is often too costly to store the entire sample covariance matrix. We propose a new input model in which one can query single entries of the covariance matrix. We prove that it is possible

Prahlad Sharma

Let $\pi$ be a $SL(3,\mathbb{Z})$ Hecke-Maass cusp form, $f$ be a $SL(2,\mathbb{Z})$ holomorphic cusp form or Maass cusp form and $\chi$ be any non-trivial character $\bmod \, p$, where $p$ is prime. We show that the $L$-function associated with this triplet satisfy \begin{equation*} L\left(\frac{1}{2},\pi\times f\times\chi\right)\ll_{\pi,f,\epsilon} p^{\fra

Xinyang Wang, Joanna Slawinska, Dimitrios Giannakis

Forecasting the El Nino-Southern Oscillation (ENSO) has been a subject of vigorous research due to the important role of the phenomenon in climate dynamics and its worldwide socioeconomic impacts. Over the past decades, numerous models for ENSO prediction have been developed, among which statistical models approximating ENSO evolution by linear dynamics have

Daniel J. Hernández, Karl Schwede, Pedro Teixeira, Emily E. Witt

This article describes the \emph{Macaulay2} package \emph{FrobeniusThresholds}, designed to estimate and calculate $F$-pure thresholds, more general $F$-thresholds, and related numerical invariants arising in the study of singularities in prime characteristic commutative algebra.

Ertugrul Basar, Marco Di Renzo, Julien de Rosny, Merouane Debbah

The future of mobile communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) and beyond wireless networks. Since the beginning of the modern era of wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which d

Camillo De Lellis, Guido De Philippis, Jonas Hirsch

We construct a Riemannian metric $g$ on $\mathbb{R}^4$ (arbitrarily close to the euclidean one) and a smooth simple closed curve $Γ\subset \mathbb R^4$ such that the unique area minimizing surface spanned by $Γ$ has infinite topology. Furthermore the metric is almost Kähler and the area minimizing surface is calibrated.

Dongchan Lee, Konstantin Turitsyn, Daniel K. Molzahn, Line A. Roald

Nonconvexity induced by the nonlinear AC power flow equations challenges solution algorithms for AC optimal power flow (OPF) problems. While significant research efforts have focused on reliably computing high-quality OPF solutions, it is not always clear that there exists a feasible path to reach the desired operating point. Transitioning between operating

Fahima Islam, Jiao Y. Y. Lin, Richard Archibald, Douglas L. Abernathy

Neutron direct-geometry time-of-flight chopper spectroscopy is instrumental in studying fundamental excitations of vibrational and/or magnetic origin. We report here that techniques in super-resolution optical imagery (which is in real-space) can be adapted to enhance resolution and reduce noise for a neutron spectroscopy (an instrument for mapping excitatio

B. Eslam Panah, Kh. Jafarzade

In this paper, we study thermodynamic features of the charged rotating accelerating black holes in anti-de Sitter spacetime. First, we consider these black holes as the thermodynamic systems and analyze thermal stability/instability through the use of heat capacity in the canonical ensemble. We also investigate the effects of angular momentum, electric charg

Dmitry Yarotsky, Anton Zhevnerchuk

We explore the phase diagram of approximation rates for deep neural networks and prove several new theoretical results. In particular, we generalize the existing result on the existence of deep discontinuous phase in ReLU networks to functional classes of arbitrary positive smoothness, and identify the boundary between the feasible and infeasible rates. More

Sandeep Joshi, Sudhir R. Jain

We study the phenomenon of neutrino spin-flavor oscillations due to solar magnetic fields. This allows us to examine how significantly the electron neutrinos produced in the solar interior undergo a resonant spin-flavor conversion. We construct analytical models for the solar magnetic field in all the three regions of the Sun. Neutrino spin-flavor oscillatio

Yang Liu, David Ruppert

This paper develops a novel approach to density estimation on a network. We formulate nonparametric density estimation on a network as a nonparametric regression problem by binning. Nonparametric regression using local polynomial kernel-weighted least squares have been studied rigorously, and its asymptotic properties make it superior to kernel estimators su

Radim Spetlik, Ivan Razumenic

We propose a novel convolutional neural network to verify a~match between two normalized images of the human iris. The network is trained end-to-end and validated on three publicly available datasets yielding state-of-the-art results against four baseline methods. The network performs better by a 10% margin to the state-of-the-art method on the CASIA.v4 data

Falk Bruckmann, Matthias Puhr

Perturbative expansions in many physical systems yield 'only' asymptotic series which are not even Borel resummable. Interestingly, the corresponding ambiguities point to nonperturbative physics. We numerically verify this renormalon mechanism for the first time in two-dimensional sigma models, that, like four-dimensional gauge theories, are asymptotically f

Sebastian Tapia, Jilberto Zamora-Saá

In this work, we study the lepton number violating tau decays via two intermediate on-shell Majorana neutrinos $N_j$ into two charged pions, and a charged lepton $\tau^{\pm} \to \pi^{\pm} N_j \to \pi^{\pm} \pi^{\pm} \ell^{\mp}$. We consider the scenario where the heavy neutrino masses are within $0.5$ GeV $\leq M_N \leq 1.5$ GeV. We evaluated the possibility

Jaka Stavanja, Matej Klemen, Lovro Šubelj

TV series such as HBO's Game of Thrones have seen a high number of dedicated followers, mostly due to the dramatic murders of the most important characters. In our work, we try to predict killer and victim pairs using data about previous kills and additional metadata. We construct a network where two character nodes are linked if one killed the other and use

David Murrugarra, Elena Dimitrova

Developing efficient computational methods to assess the impact of external interventions on the dynamics of a network model is an important problem in systems biology. This paper focuses on quantifying the global changes that result from the application of an intervention to produce a desired effect, which we define as the total effect of the intervention.

Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér, László Gerencsér

In this paper we revisit a fundamental technical issue within the theory of stochastic approximation (SA) in a Markovian framework, first proposed in the book by Djereveckii and Fradkov (1981), and further developed in much detail in the book by Benveniste, M{\'e}tivier, and Priouret (1990). This theory is instrumental in many application areas such as the s

Zhuang Zhao, Yibing Chen, Jianxian Qiu

In this paper, we propose a hybrid finite volume Hermite weighted essentially non-oscillatory (HWENO) scheme for solving one and two dimensional hyperbolic conservation laws. The zeroth-order and the first-order moments are used in the spatial reconstruction, with total variation diminishing Runge-Kutta time discretization. The main idea of the hybrid HWENO

S. Massalkhi, M. Agúndez, J. Cernicharo

Aim: We aim to determine the abundances of CS, SiO, and SiS in a large sample of carbon star envelopes covering a wide range of mass loss rates to investigate the potential role that these molecules could play in the formation of dust in the surroundings of the central AGB star. Methods: We surveyed a sample of 25 carbon-rich AGB stars in the $λ$ 2 mm band,

Fabio Vitale, Anand Rajagopalan, Claudio Gentile

We investigate active learning by pairwise similarity over the leaves of trees originating from hierarchical clustering procedures. In the realizable setting, we provide a full characterization of the number of queries needed to achieve perfect reconstruction of the tree cut. In the non-realizable setting, we rely on known important-sampling procedures to ob

Paul Rosen, Ashley Suh, Christopher Salgado, Mustafa Hajij

Line charts are commonly used to visualize a series of data values. When the data are noisy, smoothing is applied to make the signal more apparent. Conventional methods used to smooth line charts, e.g., using subsampling or filters, such as median, Gaussian, or low-pass, each optimize for different properties of the data. The properties generally do not incl

Silvia Celli, Giovanni Morlino, Stefano Gabici, Felix Aharonian

The escape process of particles accelerated at supernova remnant (SNR) shocks is one of the poorly understood aspects of the shock acceleration theory. Here we adopt a phenomenological approach to study the particle escape and its impact on the gamma-ray spectrum resulting from hadronic collisions both inside and outside of a middle-aged SNR. Under the assum

Bo Chen, Yukun Guo, Fuming Ma, Yao Sun

This paper is concerned with the numerical simulation of three dimensional time-dependent inverse source problems of acoustic waves. The reconstructions of both multiple stationary point sources and a moving point source are considered. The modified method of fundamental solutions (MMFS), which expands the solution utilizing the time convolution of the Green

Jianwei Gao, Xun Xie

We prove Lusztig's conjectures P1-P15 for hyperbolic Coxeter groups of rank 3. Our proof enables us to give a description of the a-function and Kazhdan-Lusztig cells for these Coxeter groups.

Bartosz Zieliński, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk

Diagnosis of fungal infections can rely on microscopic examination, however, in many cases, it does not allow unambiguous identification of the species due to their visual similarity. Therefore, it is usually necessary to use additional biochemical tests. That involves additional costs and extends the identification process up to 10 days. Such a delay in the

Alon E. Faraggi

I argue that the ten dimensional non--supersymmetric tachyonic superstrings may serve as good starting points for the construction of viable phenomenological vacua. Thus, enlarging the space of possible solutions that may address some of the outstanding problems in string phenomenology. A tachyon free six generation Standard--like Model is presented, which c

Tomoki Kurikawa, Omri Barak, Kunihiko Kaneko

Memories in neural system are shaped through the interplay of neural and learning dynamics under external inputs. By introducing a simple local learning rule to a neural network, we found that the memory capacity is drastically increased by sequentially repeating the learning steps of input-output mappings. The origin of this enhancement is attributed to the

Yixing Zhu, Xueqing Wu, Jun Du

We propose a novel method for representing oriented objects in aerial images named Adaptive Period Embedding (APE). While traditional object detection methods represent object with horizontal bounding boxes, the objects in aerial images are oritented. Calculating the angle of object is an yet challenging task. While almost all previous object detectors for a

Jens Wittsten, Erik F. M. Koene, Fredrik Andersson, Johan O. A. Robertsson

We describe a method for removing the numerical errors in the modeling of linear evolution equations that are caused by approximating the time derivative by a finite difference operator. The method is based on integral transforms realized as certain Fourier integral operators, called time dispersion transforms, and we prove that, under an assumption about th

Prashant Singh, Anupam Kundu

The 'Arcsine' laws of Brownian particles in one dimension describe distributions of three quantities: the time $t_m$ to reach maximum position, the time $t_r$ spent on the positive side and the time $t_\ell$ of the last visit to the origin. Interestingly, the cumulative distribution of all the three quantities are same and given by Arcsine function. In this

Alex Townsend, Michael Stillman, Steven H. Strogatz

For any network of identical Kuramoto oscillators with identical positive coupling, there is a critical connectivity above which the system is guaranteed to converge to the in-phase synchronous state, for almost all initial conditions. But the precise value of this critical connectivity remains unknown. In 2018, Ling, Xu, and Bandeira proved that if each osc

Yury A. Neretin

We classify irreducible unitary representations of the group of all infinite matrices over a $p$-adic field ($p\ne 2$) with integer elements equipped with a natural topology. Any irreducible representation passes through a group $GL$ of infinite matrices over a residue ring modulo $p^k$. Irreducible representations of the latter group are induced from finite

Maolin Shi, Shuo Wang, Wei Sun, Liye Lv

Computational simulations with different fidelity have been widely used in engineering design. A high-fidelity (HF) model is generally more accurate but also more time-consuming than an low-fidelity (LF) model. To take advantages of both HF and LF models, multi-fidelity surrogate models that aim to integrate information from both HF and LF models have gained

Xun Zhang, William B. Haskell, Zhisheng Ye

It is common to encounter large-scale monotone inclusion problems where the objective has a finite sum structure. We develop a general framework for variance-reduced forward-backward splitting algorithms for this problem. This framework includes a number of existing deterministic and variance-reduced algorithms for function minimization as special cases, and

Benyamin Ghojogh, Fakhri Karray, Mark Crowley

This is a detailed tutorial paper which explains the Fisher discriminant Analysis (FDA) and kernel FDA. We start with projection and reconstruction. Then, one- and multi-dimensional FDA subspaces are covered. Scatters in two- and then multi-classes are explained in FDA. Then, we discuss on the rank of the scatters and the dimensionality of the subspace. A re

Min Fu, Yong Zhou, Yuanming Shi

Intelligent reflecting surface (IRS) has recently been recognized as a promising technology to enhance the energy and spectrum efficiency of wireless networks by controlling the wireless medium with the configurable electromagnetic materials. In this paper, we consider the downlink transmit power minimization problem for a IRS-empowered non-orthogonal multip

Bence Borda

Let $X_1, X_2, \dots$ be independent, identically distributed random variables taking values from a compact metrizable group $G$. We prove that the random walk $S_k=X_1 X_2 \cdots X_k$, $k=1,2,\dots$ equidistributes in any given Borel subset of $G$ with probability $1$ if and only if $X_1$ is not supported on any proper closed subgroup of $G$, and $S_k$ has

Ercan Kilicarslan, Bayram Tekin

We study the local causality issue via the Shapiro time-delay computations in the on-shell consistent exotic massive gravity in three dimensions. The theory shows time-delay as opposed to time-advance despite having a ghost at the linearized level both for asymptotically flat and anti-de Sitter spacetimes. We also prove a Birkhoff-like theorem: any solution

Nicolò Defenu, Giovanna Morigi, Luca Dell'Anna, Tilman Enss

We study the out-of-equilibrium dynamics of $p$-wave superconducting quantum wires with long-range interactions, when the chemical potential is linearly ramped across the topological phase transition. We show that the heat produced after the quench scales with the quench rate $\delta$ according to the scaling law $\delta^\theta$, where the exponent $\theta$

Behrooz Khadem, Reza Ahmadian

With the development of imaging methods in wireless communications, enhancing the security and efficiency of image transfer requires image compression and encryption schemes. In conventional methods, encryption and compression are two separate processes, therefore an adversary can organize his attack more simply but if these two processes are combined, the o

Sihan Zhao, Pilkyung Moon, Yuhei Miyauchi, Kazunari Matsuda

We report the first experimental observation of strong coupling effect in one-dimensional moir\'e crystals. We study one-dimensional double-wall carbon nanotubes (DWCNTs) in which van der Waals-coupled two single nanotubes form one-dimensional moir\'e superlattice. We experimentally combine Rayleigh scattering spectroscopy and electron beam diffraction on th

Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen

Keyword spotting (KWS) is experiencing an upswing due to the pervasiveness of small electronic devices that allow interaction with them via speech. Often, KWS systems are speaker-independent, which means that any person --user or not-- might trigger them. For applications like KWS for hearing assistive devices this is unacceptable, as only the user must be a

Alexander V. Sobolev, Dmitri Yafaev

Self-adjoint Toeplitz operators have purely absolutely continuous spectrum. For Toeplitz operators $T$ with piecewise continuous symbols, we suggest a further spectral classification determined by propagation properties of the operator $T$, that is, by the behavior of $\exp(-iTt) f$ for $t\to\pm\infty$. It turns out that the spectrum is naturally partitioned

Huan Han, Hong Ci Liao, Zai Ping Lu

A graph is edge-primitive if its automorphism group acts primitively on the edge set, and 2-arc-transitive if its automorphism group acts transitively on the set of 2-arcs. In this paper, we present a classification for those edge-primitive graphs which are 2-arc-transitive and have soluble edge-stabilizers.

Fariba Yousefi, Michael Thomas Smith, Mauricio A. Álvarez

Aggregated data is commonplace in areas such as epidemiology and demography. For example, census data for a population is usually given as averages defined over time periods or spatial resolutions (cities, regions or countries). In this paper, we present a novel multi-task learning model based on Gaussian processes for joint learning of variables that have b

Grégoire Ferré, Gabriel Stoltz

We consider large deviations of empirical measures of diffusion processes. In a first part, we present conditions to obtain a large deviations principle (LDP) for a precise class of unbounded functions. This provides an analogue to the standard Cram\'er condition in the context of diffusion processes, which turns out to be related to a spectral gap condition

Abhinav Singh, Carsten Wiuf, Abhishek Behera, Manoj Gopalkrishnan

With a view towards molecular communication systems and molecular multi-agent systems, we propose the Chemical Baum-Welch Algorithm, a novel reaction network scheme that learns parameters for Hidden Markov Models (HMMs). Each reaction in our scheme changes only one molecule of one species to one molecule of another. The reverse change is also accessible but

Andrzej Okolow

We consider gravitational time dilation between stationary observers and present examples, which contradict the statement that "time slows down as gravity increases". We show furthermore that this statement cannot be true in general, if strength of gravity is defined in an observer independent manner. We provide also a pedagogical introduction to gravitation

Chen Zheng, Yu Sun, Shengxian Wan, Dianhai Yu

Deep neural networks have achieved significant improvements in information retrieval (IR). However, most existing models are computational costly and can not efficiently scale to long documents. This paper proposes a novel End-to-End neural ranking framework called Reinforced Long Text Matching (RLTM) which matches a query with long documents efficiently and

Weiran Shen, Zihe Wang, Song Zuo

First price auctions are widely used in government contracts and industrial auctions. In this paper, we consider the Bayesian Nash Equilibrium (BNE) in first price auctions with discrete value distributions. We study the characterization of the BNE in the first price auction and provide an algorithm to compute the BNE at the same time. Moreover, we prove the

Ryo Shimano, Naoto Tsuji

When a continuous symmetry of a physical system is spontaneously broken, two types of collective modes typically emerge: the amplitude and phase modes of the order-parameter fluctuation. For superconductors, the amplitude mode is recently referred to as the ''Higgs mode'' as it is a condensed-matter analogue of a Higgs boson in particle physics. Higgs mode i

Roland Vollgraf

In this work we propose a new neural network architecture that efficiently implements and learns general purpose set-equivariant functions. Such a function f maps a set of entities x = {x1, . . . , xn} from one domain to a set of same cardinality y = f (x) = {y1, . . . , yn} in another domain regardless of the ordering of the entities. The architecture is ba

Dhrubajyoti Biswas, Soumyajit Seth, Mita Bor

In this article, we have studied a 1D map, which is formed by combining the two well-known maps i.e. the tent and the logistic maps in the unit interval i.e. [0, 1]. The proposed map can behave as the piecewise smooth or non-smooth maps (depending on the behaviour of the map just before and after the border) and then the dynamics of the map has been studied

Xinzhe Zuo, Mason A Porter

The study of temporal networks in discrete time has yielded numerous insights into time-dependent networked systems in a wide variety of applications. For many complex systems, however, it is useful to develop continuous-time models of networks and to compare them to associated discrete models. In this paper, we study several continuous-time network models a

Anna E. Frid

The prefix palindromic length $PPL_u(n)$ of an infinite word $u$ is the minimal number of concatenated palindromes needed to express the prefix of length $n$ of $u$. In a 2013 paper with Puzynina and Zamboni we stated the conjecture that $PPL_u(n)$ is unbounded for every infinite word $u$ which is not ultimately periodic. Up to now, the conjecture has been p

Keiichi Kisamori, Keisuke Yamazaki, Yuto Komori, Hiroshi Tokieda

The interpretability of machine learning, particularly for deep neural networks, is crucial for decision making in real-world applications. One approach is replacing the un-interpretable machine learning model with a surrogate model, which has a simple structure for interpretation. Another approach is understanding the target system by using a simulation mod

Vasileios Porpodas

The experimental evaluation of fault-tolerance studies relies on tools that inject errors while programs are running, and then monitor the execution and the output for faulty execution. In particular, the established methodology in software-based transient-fault reliability studies, involves running each workload hundreds or thousands of times, injecting a r

Rohit Kumar Mishra, François Monard

For a one-parameter family of simple metrics of constant curvature ($4\kappa$ for $\kappa\in (-1,1)$) on the unit disk $M$, we first make explicit the Pestov-Uhlmann range characterization of the geodesic X-ray transform, by constructing a basis of functions making up its range and co-kernel. Such a range characterization also translates into moment conditio

Bo-Yan Cui, Ying-Ying Fan, Fu-Hu Liu, Wen-Fei Wang

We study the quasi-two-body decays $B\to P D^{\ast}_0(2400) \to P Dπ$ with $P=(π, K, η, η^{\prime})$ in the perturbative QCD factorization approach. The predicted branching fractions for the considered decays are in the range of $10^{-9}$-$10^{-4}$. The strong Cabibbo-Kobayashi-Maskawa (CKM) suppression factor $R_{CKM}\approx λ^4 (\barρ^2 + \barη^2) \approx

Hong-Zhong Wu, Long-Gang Pang, Xu-Guang Huang, Qun Wang

We revisit the azimuthal angle dependence of the local spin polarization of hyperons in heavy-ion collisions at 200 GeV in the framework of the (3+1)D viscous hydrodynamic model CLVisc. Two different initial conditions are considered in our simulation: the optical Glauber initial condition without initial orbital angular momentum and the AMPT initial conditi

Bowen Shi, Kohtaro Kato, Isaac H. Kim

We derive some of the axioms of the algebraic theory of anyon [A. Kitaev, Ann. Phys., 321, 2 (2006)] from a conjectured form of entanglement area law for two-dimensional gapped systems. We derive the fusion rules of topological charges and show that the multiplicities of the fusion rules satisfy these axioms. Moreover, even though we make no assumption about

Li Lin, Meihua Yang, Jinqiao Duan

We study the effective approximation for a nonlocal stochastic Schrodinger equation with a rapidly oscillating, periodically time-dependent potential. We use the natural diffusive scaling of heterogeneous system and study the limit behaviour as the scaling parameter tends to 0. This is motivated by data assimilations with non-Gaussian uncertainties. The nonl

K. L. Zhang, Z. Song

Unlike the edge state of a topological insulator where its energy level lives in the bulk energy gap, the edge state of a topological semimetal hides in the bulk spectrum and is difficult to be identified by the energy. We investigate the sensitivity of bulk and edge states of the gapless phase for a topological semimetal to the disordered perturbation via a

James Gray, Juntao Wang

We study two aspects of the physics of heterotic Line Bundle Standard Models on smooth Calabi-Yau threefolds. First, we investigate to what degree modern moduli stabilization scenarios can affect the standard model spectrum in such compactifications. Specifically, we look at the case where some of the complex structure moduli are fixed by a choice of hidden

Eduardo Bonelli, Delia Kesner, Andrés Viso

The purpose of this paper is to identify programs with control operators whose reduction semantics are in exact correspondence. This is achieved by introducing a relation $\simeq$, defined over a revised presentation of Parigot's $\lambda\mu$-calculus we dub $\Lambda M$. Our result builds on two fundamental ingredients: (1) factorization of $\lambda\mu$-redu

Sumith Yesudasan

The computationally efficient classical MARTINI model is extended to simulate heat transfer simulations of water. The current MARTINI model, variations of it and other coarse grain water models focus on reproducing the thermodynamic properties below room temperature, hence making them unsuitable for studying high temperature simulations especially evaporatio

Kristen Pueschel, Timothy Riley

The algebraic mapping torus $M_{\Phi}$ of a group $G$ with an automorphism $\Phi$ is the HNN-extension of $G$ in which conjugation by the stable letter performs $\Phi$. We classify the Dehn functions of $M_{\Phi}$ in terms of $\Phi$ for a number of right-angled Artin groups $G$, including all $3$-generator right-angled Artin groups and $F_k \times F_l$ for a

STAR Collaboration

High transverse momentum ($p_T$) particle production is suppressed due to parton (jet) energy loss in the hot dense medium created in relativistic heavy-ion collisions. Redistribution of energy at low-to-modest $p_T$ has been elusive to measure because of large anisotropic backgrounds. We report a data-driven method for background evaluation and subtraction,

Shahab Azarfar, Masoud Khalkhali

In this paper we investigate a model for quantum gravity on finite noncommutative spaces using the theory of blobbed topological recursion. The model is based on a particular class of random finite real spectral triples ${(\mathcal{A}, \mathcal{H}, D , \gamma , J) \,}$, called random matrix geometries of type ${(1,0) \,}$, with a fixed fermion space ${(\math

Chong-Sun Chu, Yoji Koyama

The geodesic deviation of a pair of test particles is an natural observable for the gravitational memory effect. Nevertheless in curved spacetime, this observable is plagued with various issues that need to be clarified before one can extract the essential part that is related to the gravitational radiation. In this paper we consider the Anti deSitter space

Creighton Heaukulani, Mark van der Wilk

We implement gradient-based variational inference routines for Wishart and inverse Wishart processes, which we apply as Bayesian models for the dynamic, heteroskedastic covariance matrix of a multivariate time series. The Wishart and inverse Wishart processes are constructed from i.i.d. Gaussian processes, existing variational inference algorithms for which

Anuththara Rupasinghe, Behtash Babadi

Extracting the spectral representations of the neural processes that underlie spiking activity is key to understanding how the brain rhythms mediate cognitive functions. While spectral estimation of continuous time-series is well studied, inferring the spectral representation of latent non-stationary processes based on spiking observations is a challenging p

Ahmed Alghamdi, Mohamed Hammad, Hassan Ugail, Asmaa Abdel-Raheem

. In this paper, an effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart cities. Two types of transfer learning techniques are employed to retrain the pre-trained VGG-Net (Fine-tuning and VGG-Net as fixed feature extractor) and obtained two new networks VGG-

Yu Zhang

Influence maximization (IM) has been extensively studied for better viral marketing. However, previous works put less emphasis on how balancedly the audience are affected across different communities and how diversely the seed nodes are selected. In this paper, we incorporate audience diversity and seed diversity into the IM task. From the model perspective,

Panagiotis A. Traganitis, Georgios B. Giannakis

Ensemble learning, the machine learning paradigm where multiple algorithms are combined, has exhibited promising perfomance in a variety of tasks. The present work focuses on unsupervised ensemble classification. The term unsupervised refers to the ensemble combiner who has no knowledge of the ground-truth labels that each classifier has been trained on. Whi

Samaneh Berenjian, Saeed Hajizadeh, Reza Ebrahimi Atani

Peer-to-Peer networks are designed to rely on resources of their own users. Therefore, resource management plays an important role in P2P protocols. Therefore, resource management plays an important role in P2P protocols. Early P2P networks did not use proper mechanisms to manage fairness. However, after seeing difficulties and rise of freeloaders in network

Fenglei Jin, Cuiyun Gao, Michael R. Lyu

In this paper, we propose a novel online topic tracking framework, named IEDL, for tracking the topic changes related to deep learning techniques on Stack Exchange and automatically interpreting each identified topic. The proposed framework combines the prior topic distributions in a time window during inferring the topics in current time slice, and introduc

Yang-Ho Choi

According to the postulates of the special theory of relativity (STR), physical quantities such as proper times and Doppler shifts can be obtained from any inertial frame by regarding it as isotropic. Nonetheless many inconsistencies arise from the postulates, as shown in this paper. However, there are numerous experimental results that agree with the predic

Kim M. J. Alards, Rudie P. J. Kunnen, Herman J. H. Clercx, Federico Toschi

The dynamics of inertial particles in Rayleigh-Bénard convection, where both particles and fluid exhibit thermal expansion, is studied using direct numerical simulations (DNS). We consider the effect of particles with a thermal expansion coefficient larger than that of the fluid, causing particles to become lighter than the fluid near the hot bottom plate an

N. L. Shatashvili, S. M. Mahajan, V. I. Berezhiani

It is shown that a small contamination of a relativistically hot electron component can induce a new scale (for structure formation) to a system consisting of an ion-degenerate electron plasma. Mathematically expression of this additional scale length is the increase in the index of quasi-equilibrium Beltrami-Bernoulli states that have been invoked to model

Anis Koubaa, Azza Allouch, Maram Alajlan, Yasir Javed

The Micro Air Vehicle Link (MAVLink in short) is a communication protocol for unmanned systems (e.g., drones, robots). It specifies a comprehensive set of messages exchanged between unmanned systems and ground stations. This protocol is used in major autopilot systems, mainly ArduPilot and PX4, and provides powerful features not only for monitoring and contr

Shixian Wen, Laurent Itti

Sequential learning of multiple tasks in artificial neural networks using gradient descent leads to catastrophic forgetting, whereby previously learned knowledge is erased during learning of new, disjoint knowledge. Here, we propose a fundamentally new type of method - Beneficial Perturbation Network (BPN). We add task-dependent memory (biasing) units to all

Dekel Tsur

In the $l$-path vertex cover problem the input is an undirected graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that $G-S$ does not contain a path with $l$ vertices. In this paper we give parameterized algorithms for $l$-path vertex cover for $l = 5,6,7$, whose time complexities are $O^*(3.9

Kenneth Levasseur

The Stochastic Abacus is employed to compute winning probabilities at each level of the game Pass the Buck on a complete binary tree with the starting vertex being the root of the tree. The derivation is also generalized to play on complete k-ary trees.

Abusayeed Saifullah

Self-stabilization for non-masking fault-tolerant distributed system has received considerable research interest over the last decade. In this paper, we propose a self-stabilizing algorithm for 2-edge-connectivity and 2-vertex-connectivity of an asynchronous distributed computer network. It is based on a self-stabilizing depth-first search, and is not a comp

Carlos Alexandre X. Silva, Les Foulds, Humberto J. Longo

In a commonly-used version of the Simple Assembly Line Balancing Problem (SALBP-1) tasks are assigned to stations along an assembly line with a fixed cycle time in order to minimize the required number of stations. It has traditionally been assumed that the total work needed for each product unit has been partitioned into economically indivisible tasks. Howe

Behzad Khamidehi, Elvino S. Sousa

Aerial vehicles have recently attracted significant attention in a variety of commercial and civilian applications due to their high mobility, flexible deployment and cost-effectiveness. To leverage these promising features, the aerial users have to satisfy two critical requirements: First, they have to maintain a reliable communication link to the ground ba

Tadzio Levato, Leonardo V. Goncalves, Vincenzo Giannini

The idea of using a gas-mixture comprising atoms with high mass number in order to increase proton energies in laser induced plasma acceleration at under critical density is investigated by means of 2D PIC (Particle-In-Cell) simulations. Comparing and discussing the case of a pure hydrogen plasma, and that of a plasma containing higher mass number species wi

Tal Cohen

Predicting the shape of a crater formed by high velocity impact is of interest in several fields. It can aid in design of more efficient protective structures, in forensic analysis of bullet holes, and in understanding the effects of meteorite impact in both space systems and in extreme geological events. In this paper we present, for the first time, a compl