February 2019 arXiv papers — page 23

Leonardo Gutiérrez-Gómez, Jean-Charles Delvenne

A main challenge in mining network-based data is finding effective ways to represent or encode graph structures so that it can be efficiently exploited by machine learning algorithms. Several methods have focused in network representation at node/edge or substructure level. However, many real life challenges such as time-varying, multilayer, chemical compoun

Angel Ballesteros, Ivan Gutierrez-Sagredo, Francisco J. Herranz

The space of time-like geodesics on Minkowski spacetime is constructed as a coset space of the Poincar\'e group in (3+1) dimensions with respect to the stabilizer of a worldline. When this homogeneous space is endowed with a Poisson homogeneous structure compatible with a given Poisson-Lie Poincar\'e group, the quantization of this Poisson bracket gives rise

Oscar Castillo-Felisola

We show that the effective field equations for a recently formulated polynomial affine model of gravity, in the sector of a torsion-free connection, accept general Einstein manifolds---with or without cosmological constant---as solutions. Moreover, the effective field equations are partially those obtained from a gravitational Yang-Mills theory known as the

Chenyang Si, Wentao Chen, Wei Wang, Liang Wang

Skeleton-based action recognition is an important task that requires the adequate understanding of movement characteristics of a human action from the given skeleton sequence. Recent studies have shown that exploring spatial and temporal features of the skeleton sequence is vital for this task. Nevertheless, how to effectively extract discriminative spatial

Parongama Sen

We consider a discrete time quantum walker in one dimension, where at each step, the step length $\ell$ is chosen from a distribution $P(\ell) \propto \ell^{-\delta -1}$ with $\ell \leq \ell_{max}$. We evaluate the probability $f(x,t)$ that the walker is at position $x$ at time $t$ and its first two moments. As expected, the disorder effectively localizes th

Zhuolin Wang, Keyou You, Shiji Song, Yuli Zhang

This paper proposes a data-driven distributionally robust shortest path (DRSP) model where the distribution of the travel time in the transportation network can only be partially observed through a finite number of samples. Specifically, we aim to find an optimal path to minimize the worst-case $\alpha$-reliable mean-excess travel time (METT) over a Wasserst

Fengchao Li, Yurong Zhou, Ming Liu, Gangqiang Dong

In this article, a novel hot wire oxidation-sublimation deposition (HWOSD) technique was developed to prepare molybdenum oxide (MoOx) thin films with high quality. Silicon heterojunction (SHJ) solar cells with the HWOSD MoOx as a hole selective transport layer (HSL) were fabricated. Thickness of the MoOx layer and annealing process of the solar cells were st

C. H. Yang, R. C. C. Leon, J. C. C. Hwang, A. Saraiva

Quantum computers are expected to outperform conventional computers for a range of important problems, from molecular simulation to search algorithms, once they can be scaled up to large numbers of quantum bits (qubits), typically millions. For most solid-state qubit technologies, e.g. those using superconducting circuits or semiconductor spins, scaling pose

Aditya Vidhate, Rahul Nigam

We explore the real solutions to the Spherical Collapse Model in a non-flat Universe with a Cosmological Constant, and observe a possible situation for a fake or Ghost Collapse, in which an expanding overdense spherical region, turns around and begins to collapse, turns around again after a finite time and starts expanding. To make such a situation of spurio

Buddhadeb Bhattacharjee, Pranjal Sarma

Nonstatistical fluctuation in pseudorapidity ($\eta$), azimuthal ($\phi$), and pseudorapidity-azimuthal ($\eta-\phi$) distribution spectra of primary particles of PYTHIA Monash (default) generated $pp$ events at $\sqrt{s}=$ 2.76, 7, and 13 TeV have been studied using the scaled factorial moments technique. A weak intermittent type of emission could be realiz

Farhad Ardalan

Using the precursor map in AdS/CFT, the renormalization group cutoff function is mapped to the dual theory. The resulting flow equations on the two sides of the duality are compared.

Yaniv David, Uri Alon, Eran Yahav

We address the problem of reverse engineering of stripped executables, which contain no debug information. This is a challenging problem because of the low amount of syntactic information available in stripped executables, and the diverse assembly code patterns arising from compiler optimizations. We present a novel approach for predicting procedure names in

Sunghyun Kang, Stefano Scopel, Gaurav Tomar

We discuss the compatibility of the combined annual modulation effect measured by DAMA/LIBRA-phase1 and DAMA/LIBRA-phase2 with an explanation in terms of inelastic scattering events induced by the most general Galilean-invariant effective contact interaction of a Weakly Interacting Massive Particle (WIMP) dark matter particle of spin 0, 1/2 or 1. We take int

Yuka Matsui, Sachiko Kuroyanagi

We calculate the power spectrum of the stochastic gravitational wave (GW) background expected from kink-kink collisions on infinite cosmic strings. Intersections in the cosmic string network continuously generate kinks, which emit GW bursts by their propagation on curved strings as well as by their collisions. First, we show that the GW background from kink-

Shoji Hashimoto

Heavy flavor physics entered a new era when the Belle II experiment observed its first collision. There are several hints found so far by BaBar, Belle, and LHCb in particular, that suggest the physics beyond the Standard Model appearing in the loop processes at short distances. They will be further tested by higher precision experiments in the coming years,

Yavar Kian, Masahiro Yamamoto

We consider the inverse source problem of determining a source term depending on both time and space variable for fractional and classical diffusion equations in a cylindrical domain from boundary measurements. With suitable boundary conditions we prove that some class of source terms which are independent of one space direction, can be reconstructed from bo

Rik Chattopadhyay, Shyamal K. Bhadra

We report trapping and propagation of photonic Dirac mode in a helically twisted hollow core photonic crystal fiber (HC-PCF) where the trapped light in the hollow (air) defect can preserve the orbital angular momentum (OAM). We show that a photonic Dirac point can emerge even in a twisted system for a suitable choice of curvilinear coordinate and the related

Sandi Klavžar, Mostafa Tavakoli

Let $G$ be a graph and $S\subseteq V(G)$. If every two adjacent vertices of $G$ have different metric $S$-representations, then $S$ is a local metric generator for $G$. A local metric generator of smallest order is a local metric basis for $G$, its order is the local metric dimension of $G$. Lower and upper bounds on the local metric dimension of the general

Avanna, Psycho Zhang, Simon Yan, Jonne Mao

Using multi group asymmetric public and private keys, this paper proposes a encryption email communication system, which makes email communication more secure, lowers the service provider\'s network and storage consumption, and completely eliminates any spam. Prior to this, PGP (Pretty Good Privacy) partially solved the encryption problem, but it only encryp

Zonglei Bai, Yongzhi Cao, Hanpin Wang

In this paper, we give a sampling algorithm for the Potts model using Markov chains. Based on the sampling algorithm, we give \emph{FPRAS}es for the Potts model and the number of $k$-colorings of the graph.

Qipeng Guo, Xipeng Qiu, Pengfei Liu, Yunfan Shao

Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data. In this paper, we present Star-Transformer, a lightweight alternative by careful sparsification. To reduce model complexity, we replace the fully-connected structure with a star-shap

Hong Qian, Yu-Chen Cheng, Lowell F. Thompson

A change in a stochastic system has three representations: Probabilistic, statistical, and informational: (i) is based on random variable $u(\omega)\to\tilde{u}(\omega)$; this induces (ii) the probability distributions $F_u(x)\to F_{\tilde{u}}(x)$, $x\in\mathbb{R}^n$; and (iii) a change in the probability measure $\mathbb{P}\to\tilde{\mathbb{P}}$ under the s

V. Venkatraman Krishnan, M. Bailes, W. van Straten, E. F. Keane

PSR J1141$-$6545 is a precessing binary pulsar that has the rare potential to reveal the two-dimensional structure of a non-recycled pulsar emission cone. It has undergone $\sim 25 \deg$ of relativistic spin precession in the $\sim18$ years since its discovery. In this paper, we present a detailed Bayesian analysis of the precessional evolution of the width

Yong CHEN, Yong LIU

In this article, some properties of complex Wiener-It\^o multiple integrals and complex Ornstein-Uhlenbeck operators and semigroups are obtained. Those include Stroock's formula, Hu-Meyer formula, Clark-Ocone formula and the hypercontractivity of complex Ornstein-Uhlenbeck semigroups. As an application, several expansions of the fourth moments of complex Wie

Yukiyoshi Nakkajima, Fuetaro Yobuko

In this article we prove that the log Hodge de Rham spectral sequences of certain proper log smooth schemes of Cartier type in characteristic $p>0$ degenerate at $E_1$. We also prove that the log Kodaira vanishings for them hold when they are projective. We formulate the log weak Lefschetz conjecture for log crystalline cohomologies and prove that it is true

Nathan Grieve, Julie Tzu-Yueh Wang

We establish consequences of the moving form of Schmidt's Subspace Theorem. Indeed, we obtain inequalities that bound the logarithmic greatest common divisor of moving multivariable polynomials evaluated at moving $S$-unit arguments. In doing so, we complement recent work of Levin. As an additional application, we obtain results that pertain to the greatest

Qi Shi, Yangyu Liu, Shunqing Zhang, Shugong Xu

Channel estimation is crucial for modern WiFi system and becomes more and more challenging with the growth of user throughput in multiple input multiple output configuration. Plenty of literature spends great efforts in improving the estimation accuracy, while the interpolation schemes are overlooked. To deal with this challenge, we exploit the super-resolut

Masahiro Ikeda, Takahisa Inui, Mamoru Okamoto

We consider the asymptotic behavior of solutions to the Cauchy problem for the defocusing nonlinear Klein-Gordon equation (NLKG) with exponential nonlinearity in the one spatial dimension with data in the energy space $H^1(\mathbb{R}) \times L^2(\mathbb{R})$. We prove that any energy solution has a global bound of the $L^6_{t,x}$ space-time norm, and hence s

Abinaya Manimaran, Thiyagarajan Ramanathan, Suya You, C-C Jay Kuo

In this work, we study the power of Saak features as an effort towards interpretable deep learning. Being inspired by the operations of convolutional layers of convolutional neural networks, multi-stage Saak transform was proposed. Based on this foundation, we provide an in-depth examination on Saak features, which are coefficients of the Saak transform, by

Seung-il Nam, Atsushi Hosaka

We study the photo- and electro-productions of the vector kaon off the proton, i.e., $\gamma^{(*)}p\to K^{*+}\pi^0\Sigma^0$, and investigate the line shape of the $\pi^0\Sigma^0$ invariant mass in an effective Lagrangian approach with the inclusion of a $K^*N\Lambda^*$ interaction. Relevant electromagnetic form factors for the neutral hyperons and charged st

Jinyu Guo, Chao Xia

In this paper, we study stability and instability problem for type-II partitioning problem. First, we make a complete classification of stable type-II stationary hypersurfaces in a ball in a space form as totally geodesic $n$-balls. Second, for general ambient spaces and convex domains, we give some topological restriction for type-II stable stationary immer

Yuan Hu, Yunpeng Chen, Xiang Li, Jiashi Feng

Features from multiple scales can greatly benefit the semantic edge detection task if they are well fused. However, the prevalent semantic edge detection methods apply a fixed weight fusion strategy where images with different semantics are forced to share the same weights, resulting in universal fusion weights for all images and locations regardless of thei

David Wu

Understanding the distribution of digits in the expansions of perfect powers in different bases is difficult. Rather than consider the asymptotic digit distributions, we consider the base-10 digits of a restricted sequence of powers of two. We apply elementary methods to show that this sequence of powers of two can be constructed to preserve trailing digits

Tianwei Shen, Zixin Luo, Lei Zhou, Hanyu Deng

Accurate relative pose is one of the key components in visual odometry (VO) and simultaneous localization and mapping (SLAM). Recently, the self-supervised learning framework that jointly optimizes the relative pose and target image depth has attracted the attention of the community. Previous works rely on the photometric error generated from depths and pose

Andrew M. Childs, Eddie Schoute, Cem M. Unsal

Quantum computer architectures impose restrictions on qubit interactions. We propose efficient circuit transformations that modify a given quantum circuit to fit an architecture, allowing for any initial and final mapping of circuit qubits to architecture qubits. To achieve this, we first consider the qubit movement subproblem and use the routing via matchin

Jing Jiang, Xiaojing Wang, Guftaar Ahmad Sardar Sidhu, Li Zhen

Codebook design is one of the core technologies in limited feedback multi-input multi-output (MIMO) communication systems. However, the conventional codebook designs usually assume MIMO vectors are uniformly distributed or isotropic. Motivated by the excellent classfication and analysis ability of clustering algorithms, we propose a K-means clustering based

Jia Kan, Kyeong Soo Kim

The blockchain technology has been changing our daily lives since Bitcoin - i.e., the first decentralized cryptocurrency - was invented and released as open-source software by an unidentified person or a group called Satoshi Nakamoto in 2009. Of many applications which can be implemented based on the blockchain, storage is an important one, a notable example

Jingbo Wang, Chungha Sung, Chao Wang

The code generation modules inside modern compilers such as GCC and LLVM, which use a limited number of CPU registers to store a large number of program variables, may introduce side-channel leaks even in software equipped with state-of-the-art countermeasures. We propose a program analysis and transformation based method to eliminate this side channel. Our

Cui Li, Karin Schoenning

The BESIII collaboration here reports the first observation of polarized $\Lambda$ and $\bar{\Lambda}$ hyperons produced in two different processes: i) the resonant $e^+e^- \to J/\psi\to\Lambda\bar{\Lambda}$, using a data sample of 1.31 $\times$ 10$^9$ $J/\psi$ events and ii) the non-resonant $e^+e^-\to \gamma^* \to \Lambda\bar{\Lambda}$, using a 66.9 pb$^{-

Joe Booth, Jackson Booth

Recent advances in deep reinforcement learning in the paradigm of locomotion using continuous control have raised the interest of game makers for the potential of digital actors using active ragdoll. Currently, the available options to develop these ideas are either researchers' limited codebase or proprietary closed systems. We present Marathon Environments

Rakib Hyder, M. Salman Asif

Finding compact representation of videos is an essential component in almost every problem related to video processing or understanding. In this paper, we propose a generative model to learn compact latent codes that can efficiently represent and reconstruct a video sequence from its missing or under-sampled measurements. We use a generative network that is

Qiang Li, Feng-Kui Gong, Pei-Yang Song, Sheng-Hua Zhai

A symbol-based multi-layer iterative successive interference cancellation (MLISIC) algorithm is proposed to eliminate the inter-symbol interference (ISI) for faster-than-Nyquist (FTN) signaling. The computational complexity of the proposed MLISIC algorithm is much lower than most existing block-based estimation algorithms. By comparison with existing symbol-

Li Zhang, Weichen Shen, Shijian Li, Gang Pan

Recommendation systems and computing advertisements have gradually entered the field of academic research from the field of commercial applications. Click-through rate prediction is one of the core research issues because the prediction accuracy affects the user experience and the revenue of merchants and platforms. Feature engineering is very important to i

Mario Ivan Estrada Delgado, David José Fernández Cabrera

Position dependent mass systems can be described by a class of operators which include the Ben Daniel-Duke Hamiltonians. The usual methods to solve this kind of problems are, in general, either numerical or those looking for a connection with constant mass problems. In this paper we impose the existence of first-order ladder operators to fix our initial syst

Nima Karimian, Fatemeh Tehranipoor, Nikolaos Anagnostopoulos, Wei Yan

Nowadays, there is an increasing interest in the development of Autonomous Vehicles (AV). However, there are two types of attack challenges that can affect AVs and are yet to be resolved, i.e., sensor attacks and vehicle access attacks. This paper, to the best of our knowledge, is the first work that proposes a novel authentication scheme involving DRAM powe

Igor Labutov, Bishan Yang, Anusha Prakash, Amos Azaria

Question Answering (QA), as a research field, has primarily focused on either knowledge bases (KBs) or free text as a source of knowledge. These two sources have historically shaped the kinds of questions that are asked over these sources, and the methods developed to answer them. In this work, we look towards a practical use-case of QA over user-instructed

Wanyun Cui, Guangyu Zheng, Zhiqiang Shen, Sihang Jiang

Transfer learning aims to solve the data sparsity for a target domain by applying information of the source domain. Given a sequence (e.g. a natural language sentence), the transfer learning, usually enabled by recurrent neural network (RNN), represents the sequential information transfer. RNN uses a chain of repeating cells to model the sequence data. Howev

Bishan Yang, Tom Mitchell

This paper focuses on how to take advantage of external knowledge bases (KBs) to improve recurrent neural networks for machine reading. Traditional methods that exploit knowledge from KBs encode knowledge as discrete indicator features. Not only do these features generalize poorly, but they require task-specific feature engineering to achieve good performanc

Ahmad Mohsin, Naeem Khalid Janjua, Syed MS Islam, Valdemar Vicente Graciano Neto

Systems-of-Systems (SoS) result from the collaboration of independent Constituent Systems (CSs) to achieve particular missions. CSs are not totally known at design time, and may also leave or join SoS at runtime, which turns the SoS architecture to be inherently dynamic, forming new architectural configurations and impacting the overall system quality attrib

Yulong Zeng, Song Zuo

We study the computation contests where players compete for searching a solution to a given problem with a winner-take-all reward. The search processes are independent across the players and the search speeds of players are proportional to their computational powers. One concrete application of this abstract model is the mining process of proof-of-work type

Stine Franziska Beitz

We introduce the new notion of Bianchi-convex sets, a generalization of convex sets of algebraic curvature tensors inspired by the second Bianchi identity. It turns out that Hamilton's maximum principle for the Ricci flow can be generalized for Bianchi-convex sets.

Yuxuan Lai, Yansong Feng, Xiaohan Yu, Zheng Wang

Short text matching often faces the challenges that there are great word mismatch and expression diversity between the two texts, which would be further aggravated in languages like Chinese where there is no natural space to segment words explicitly. In this paper, we propose a novel lattice based CNN model (LCNs) to utilize multi-granularity information inh

Andre Laestadius, Erik I. Tellgren, Markus Penz, Michael Ruggenthaler

Recent work has established Moreau-Yosida regularization as a mathematical tool to achieve rigorous functional differentiability in density-functional theory. In this article, we extend this tool to paramagnetic current-density-functional theory, the most common density-functional framework for magnetic field effects. The extension includes a well-defined Ko

Maciej Besta, Dimitri Stanojevic, Johannes De Fine Licht, Tal Ben-Nun

Graph processing has become an important part of various areas, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Various graphs, for example web or social networks, may contain up to trillions of edges. The sheer size of such datasets, combined with the irregular nature of graph processing, pos

Zihao W. Wang, Vibhav Vineet, Francesco Pittaluga, Sudipta Sinha

The risk of unauthorized remote access of streaming video from networked cameras underlines the need for stronger privacy safeguards. We propose a lens-free coded aperture camera system for human action recognition that is privacy-preserving. While coded aperture systems exist, we believe ours is the first system designed for action recognition without the n

Jason L. Evans, Natsumi Nagata, Keith A. Olive

The lack of evidence for low-scale supersymmetry suggests that the scale of supersymmetry breaking may be higher than originally anticipated. However, there remain many motivations for supersymmetry including gauge coupling unification and a stable dark matter candidate. Models like pure gravity mediation (PGM) evade LHC searches while still providing a good

Andrei V. Zavarnitsine

To follow up on the results of [1], we propose a computationally efficient explicit cyclic decomposition of the maximal tori in the groups $SL_n(q)$ and $SU_n(q)$ and their projective images. We also derive some corollaries to simplify practical calculation of the maximal tori. The result is based on a generic cyclic decomposition of a finite abelian group w

K L Sebastian

The usual Kramers theory of reaction rates in a condensed medium predict the rate to have an $\eta^{-1}$ dependence, $\eta$ being the viscosity of the medium. However, experiments on ligand binding to proteins performed long ago, showed the rate to have $\eta^{-\nu}$ dependence, with $\nu $ in the range $0.4-0.8$. Zwanzig {\it (Journal of Chemical Physics 97

Nan Yang, Zhong-Qi Ren, Zhao Guan, Bo-Bo Tian

Memristors have been intensively studied in recent years as promising building blocks for next-generation non-volatile memory, artificial neural networks and brain-inspired computing systems. Even though the environment adaptability of memristor has been required in many application fields, it has been rarely reported due to the underlying mechanism could be

Chengju Zhou, Meiqing Wu, Siew-Kei Lam

Pedestrian detection plays an important role in many applications such as autonomous driving. We propose a method that explores semantic segmentation results as self-attention cues to significantly improve the pedestrian detection performance. Specifically, a multi-task network is designed to jointly learn semantic segmentation and pedestrian detection from

Jie Zhao, Jian Xiang, Zhi-Pan Li, Tamara Nikšić

Low-energy positive and negative parity collective states in the equilibrium minimum, and the dynamics of induced fission of actinide nuclei are investigated in a unified theoretical framework based on the generator coordinate method (GCM) with the Gaussian overlap approximation (GOA). The collective potential and inertia tensor, both at zero and finite temp

M. N. Islam, A. Siddika, M. B. Hossain, A. Rahman

During plastic deformation of granular materials due to loading, the stress-strain and strength characteristics of sand grains are influenced with grain size, their distribution and packing. Also the macroscopic behaviour of granular materials changes with the variation of microscopic behaviour. Particle size is one of the important properties which plays a

Michael C. H. Choi

Motivated by the notion of resistance distance on graph, we define a new resistance distance between two states on a given finite ergodic Markov chain based on its fundamental matrix. We prove a few equivalent formulations and discuss its relation with other parameters of the Markov chain such as its group inverse, stationary distribution, eigenvalues or hit

Neng-Hui Liao, Li-Ming Dou, Ning Jiang, Yi-Bo Wang

We report on OVRO, WISE, Swift and Fermi-LAT observations of the high redshift blazar CGRaBS J0733+0456, from which significant flux variations in radio, infrared (IR) as well as $\gamma$-ray domains are detected. Particularly, the amplitude of long-term IR variation is over one order of magnitude and the IR variability timescale can be constrained as short

Susanna Dann, Grigoris Paouris, Peter Pivovarov

Building on work of Furstenberg and Tzkoni, we introduce ${\bf r}$-flag affine quermassintegrals and their dual versions. These quantities generalize affine and dual affine quermassintegrals as averages on flag manifolds (where the Grassmannian can be considered as a special case). We establish affine and linear invariance properties and extend fundamental r

Yaomin Zhao, Harshal D. Akolekar, Jack Weatheritt, Vittorio Michelassi

This paper presents a novel CFD-driven machine learning framework to develop Reynolds-averaged Navier-Stokes (RANS) models. The CFD-driven training is an extension of the gene expression programming method (Weatheritt and Sandberg, 2016), but crucially the fitness of candidate models is now evaluated by running RANS calculations in an integrated way, rather

Christos H Skiadas, Charilaos Skiadas

The Healthy Life Years Lost Methodology (HLYL) is introduced to model and estimate the Health Expenditure in Japan in 2011. The HLYL theory and estimation methods are presented in our books in the Springer Series on Demographic Methods and Population Analysis vol. 45 and 46 titled: Exploring the Health State of a Population by Dynamic Modeling Methods and De

Xin Fang, Liang Zou, Jin Li, Lei Sun

The conventional speaker recognition frameworks (e.g., the i-vector and CNN-based approach) have been successfully applied to various tasks when the channel of the enrolment dataset is similar to that of the test dataset. However, in real-world applications, mismatch always exists between these two datasets, which may severely deteriorate the recognition per

Jaewoong Cho, Changho Suh

Generative Adversarial Networks (GANs) have become a powerful framework to learn generative models that arise across a wide variety of domains. While there has been a recent surge in the development of numerous GAN architectures with distinct optimization metrics, we are still lacking in our understanding on how far away such GANs are from optimality. In thi

R. Saldanha, H. O. Back, R. H. M. Tsang, T. Alexander

We have experimentally determined the production rate of $^{39}$Ar and $^{37}$Ar from cosmic ray neutron interactions in argon at sea level. Understanding these production rates is important for argon-based dark matter experiments that plan to utilize argon extracted from deep underground because it is imperative to know what the ingrowth of $^{39}$Ar will b

Xian Li, Xiangyun Zhou, Derrick Wing Kwan Ng, Changyin Sun

This work considers the design of online transmission policy in a wireless-powered communication system with a given energy budget. The system design objective is to maximize the long-term throughput of the system exploiting the energy storage capability at the wireless-powered node. We formulate the design problem as a constrained Markov decision process (C

Tianhao Ren, Mian Zhang, Cheng Wang, Linbo Shao

Electro-optic phase modulators are critical components in modern communication, microwave photonic, and quantum photonic systems. Important for these applications is to achieve modulators with low half-wave voltage at high frequencies. Here we demonstrate an integrated phase modulator, based on a thin-film lithium niobate platform, that simultaneously featur

Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein

In this work, we consider applying machine learning to the analysis and compression of audio signals in the context of monitoring elephants in sub-Saharan Africa. Earth's biodiversity is increasingly under threat by sources of anthropogenic change (e.g. resource extraction, land use change, and climate change) and surveying animal populations is critical for

Shiwen Liu, Kan Zheng, Long Zhao, Pingzhi Fan

In a mixed-traffic scenario where both autonomous vehicles and human-driving vehicles exist, a timely prediction of driving intentions of nearby human-driving vehicles is essential for the safe and efficient driving of an autonomous vehicle. In this paper, a driving intention prediction method based on Hidden Markov Model (HMM) is proposed for autonomous veh

Olya A. Ilinskaya, Danko Radic, Hee Chul Park, Ilya V. Krive

Exchange forces on the movable dot ("shuttle") in a magnetic shuttle device depend on the parity of the number of shuttling electrons. The performance of such a device can therefore be tuned by changing the strength $U$ of Coulomb correlations to block or unblock parity fluctuations. We show that by increasing $U$ the spintro-mechanics of the device crosses

Shiheng Wang, Fangzhen Lin

Repeated games are difficult to analyze, especially when agents play mixed strategies. We study one-memory strategies in iterated prisoner's dilemma, then generalize the result to k-memory strategies in repeated games. Our result shows that there always exists a pure strategy best response, which can be computed with SMT or MDP solvers. However, there may no

Yavuz Yapici, Ismail Guvenc

Visible light communications (VLC) is an emerging technology with a promise of viable solution to spectrum crunch problem in conventional radio frequency (RF) bands. In this work, we consider a downlink multiuser VLC network where users randomly change their location and vertical orientation. In order to increase the spectral efficiency, we consider the non-

Boudewijn F. Roukema, Jan J. Ostrowski

Cosmological observational analysis frequently assumes that the Universe is spatially flat. We aim to non-perturbatively check the conditions under which a flat or nearly flat expanding dust universe, including the LCDM model if interpreted as strictly flat, forbids the gravitational collapse of structure. We quantify spatial curvature at turnaround. We use

Amber L. Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello

Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is contingent on the availability of high-quality imaging data with corresponding labels provided by experts. We sought to create a large collection of annotated medical image datasets

Yi Han, David Hubczenko, Paul Montague, Olivier De Vel

Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to vulnerabilities previously demonstrated in the supervised learning setting. While most existing work studies the problem in the context of computer vision or console games, this paper focuses on reinforcement learning in autonomous

Sejeong Kim, Johannes E. Fröch, Augustine Gardner, Chi Li

We report second-harmonic generation (SHG) from thick hexagonal boron nitride (hBN) flakes with approximately 109-111 layers. The resulting effective second-order susceptibility is similar to previously reported few-layer experiments. This confirms that thick hBN flakes can serve as a platform for nonlinear optics, which is useful because thick flakes are ea

Jiawei Yin, Agung Julius, John T. Wen

The light-based minimum-time circadian entrainment problem for mammals, Neurospora, and Drosophila is studied based on the mathematical models of their circadian gene regulation. These models contain high order nonlinear differential equations. Two model simplification methods are applied to these high-order models: the phase response curves (PRC) and the Pr

Xiaoqiang Zhang, Yong Xu, Weisheng Zhao

With the feature of low-power magnetization manipulation at an ultrashort time scale, all optical switching (AOS) has been propelled to the forefront in investigations. To further speed up the magnetization reversal by manipulating ultrashort optical pulses, in this paper, one single square-wave laser pulse (SWLP) vie the combination of heating and Inverse F

Hong-Fei Zhang, Yu Feng, Wen-Long Sang, Yu-Peng Yan

We study the $\eta_c$ photoproduction in $ep$ collisions in this paper. The short-distance coefficients for $c\bar{c}(^1S_0^{[1]})$, $c\bar{c}(^1S_0^{[8]})$, $c\bar{c}(^3S_1^{[8]})$, and $c\bar{c}(^1P_1^{[8]})$ photoproductions are evaluated at leading order in $\alpha_s$ expansion, where the color-singlet contribution is achieved for the first time. We have

Xiaofeng Cao, Guoming Tang, Deke Guo, Yan Li

Edge computing is a promising computing paradigm for pushing the cloud service to the network edge. To this end, edge infrastructure providers (EIPs) need to bring computation and storage resources to the network edge and allow edge service providers (ESPs) to provision latency-critical services to users. Currently, EIPs prefer to establish a series of priva

Vinay Tripathi, Mostafa Khezri, Alexander N. Korotkov

We analyze analytically, semi-analytically, and numerically the operation of Cross-Resonance (CR) gate for superconducting qubits (transmons). We find that a relatively simple semi-analytical method gives accurate results for the CNOT-equivalent gate duration and compensating single-qubit rotations. It also allows us to minimize the CNOT gate duration over t

Shintaro Hoshino, Philipp Werner, Ryotaro Arita

Non-local order parameters in space-time are proposed to characterize the unconventional orbital-selective conducting state in fulleride superconductors, called the Jahn-Teller metal. In previous works, it has been argued that this state can be interpreted as a spontaneous orbital-selective Mott state, in which the electrons in two of the three $t_{1u}$ mole

Hu Zhang, Wei Huang, Jia-Wei Mei, Xing-Qiang Shi

Based on first-principles calculations and k .p effective models, we report physical properties of ferroelectric-like hexagonal polar metals with P63mc symmetry, which are distinct from those of conventional metals with spatial inversion symmetry. Spin textures exist on the Fermi surface of polar metals (e.g. ternary LiGaGe and elemental polar metal of Bi) a

Miguel Arduengo, Carme Torras, Luis Sentis

The ability to deal with articulated objects is very important for robots assisting humans. In this work, a framework to robustly and adaptively operate common doors, using an autonomous mobile manipulator, is proposed. To push forward the state-of-the-art in robustness and speed performance, we devise a novel algorithm that fuses a convolutional neural netw

Alexander J. Izzo

It is shown that there exists a compact set $X$ in ${\mathbb C}^2$ with a nontrivial polynomial hull $\widehat X$ such that some point of $\widehat X \setminus X$ is a one-point Gleason part for $P(X)$. Furthermore, $X$ can chosen so that $P(X)$ has a dense set of invertible elements.

Mai Ye, H. -H. Kung, Priscila F. S. Rosa, Eric D. Bauer

We performed an optical spectroscopy study of electronic and magnetic excitations for a rare-earth system with a single electron quasi-localized in the f-shell on an ion at high-symmetry crystallographic site in application to CeB$_{6}$ heavy-fermion metal. We carried out group-theoretical classification of the electronic crystal field (CF) transitions and a

Nitya Mani, Simon Rubinstein-Salzedo

For an element $r$ of a ring $R$, a Diophantine $D(r)$ $m$-tuple is an $m$-tuple $(a_1,a_2,\ldots,a_m)$ of elements of $R$ such that for all $i,j$ with $i\neq j$, $a_ia_j+r$ is a perfect square in $R$. In this article, we compute and estimate the measures of the sets of $D(r)$ $m$-tuples in the ring $\mathbb{Z}_p$ of $p$-adic integers, as well as its residue

Qin Li, Dong Sun

Cases have shown that WENO schemes usually behave robustly on problems containing shocks with high pressure ratios when uniformed or smooth grids are present, while nonlinear schemes based on WENO interpolations might relatively be liable to numerical instability. In the meanwhile, the latter have manifested their advantages in computations on grids of bad q

Matania Ben-Artzi, Jiequan Li

This paper addresses the three concepts of \textit{ consistency, stability and convergence } in the context of compact finite volume schemes for systems of nonlinear hyperbolic conservation laws. The treatment utilizes the framework of "balance laws". Such laws express the relevant physical conservation laws in the presence of discontinuities. Finite volume

David J. Warne, Scott A. Sisson, Christopher Drovandi

Many applications in Bayesian statistics are extremely computationally intensive. However, they are often inherently parallel, making them prime targets for modern massively parallel processors. Multi-core and distributed computing is widely applied in the Bayesian community, however, very little attention has been given to fine-grain parallelisation using s

Terrence Adams, Joseph Rosenblatt

Let $(X,\mathcal{B},\mu)$ be a standard probability space. We give new fundamental results determining solutions to the coboundary equation: \begin{eqnarray*} f = g - g \circ T \end{eqnarray*} where $f \in L^p$ and $T$ is ergodic invertible measure preserving on $(X, \mathcal{B}, \mu )$. We extend previous results by showing for any measurable $f$ that is no

Sara Fridovich-Keil, Peter J. Ramadge

We consider the problem of smartphone video-based heart rate estimation, which typically relies on measuring the green color intensity of the user's skin. We describe a novel signal in fingertip videos used for smartphone-based heart rate estimation: fingertip contact surface area. We propose a model relating contact surface area to pressure, and validate it

Alexander Tichai, Julien Ripoche, Thomas Duguet

The solution of the nuclear A-body problem encounters severe limitations from the size of many-body operators. These limitations are typically related to both the (iterative) storing of the associated tensors and to the computational time related to their multiple contractions in the calculation of various quantities of interest. However, not all the degrees

Peter J Forrester, Shi-Hao Li

The eigenvalue probability density function for symplectic invariant random matrix ensembles can be generalised to discrete settings involving either a linear or exponential lattice. The corresponding correlation functions can be expressed in terms of certain discrete, and $q$, skew orthogonal polynomials respectively. We give a theory of both of these class

Edisher Kaghashvili

Inhomogeneity generated waves, discovered more than a decade ago, play an important role in processes like energy transfer, turbulence generation, heating, etc. To understand the nature of these waves we developed the formalism that looks for the short-term changes in the initial waveform due to the linear interaction of the initial disturbance and inhomogen