November 2018 arXiv papers — page 2

Nikit Begwani, Shrutendra Harsola, Rahul Agrawal

Retrieval models such as CLSM is trained on click-through data which treats each clicked query-document pair as equivalent. While training on click-through data is reasonable, this paper argues that it is sub-optimal because of its noisy and long-tail nature (especially for sponsored search). In this paper, we discuss the impact of incorporating or disregard

Max Maass, Nicolas Walter, Dominik Herrmann, Matthias Hollick

Today, online privacy is the domain of regulatory measures and privacy-enhancing technologies. Transparency in the form of external and public assessments has been proposed for improving privacy and security because it exposes otherwise hidden deficiencies. Previous work has studied privacy attitudes and behavior of consumers. However, little is known on how

Raphaël Deswarte, Véronique Gervais, Gilles Stoltz, Sébastien da Veiga

Production forecasting is a key step to design the future development of a reservoir. A classical way to generate such forecasts consists in simulating future production for numerical models representative of the reservoir. However, identifying such models can be very challenging as they need to be constrained to all available data. In particular, they shoul

Thibaud Ehret, Axel Davy, Jean-Michel Morel, Gabriele Facciolo

Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available. This makes model based video processing a still more complex task. In this paper we propose a fully blind video denoising method, with two versions off-line and on-line. This is achieved by fine-tuning a pre-trained AWGN denoisi

Alexis Devulder, Nina Gantert, Françoise Pene

We consider $d$ independent walkers in the same random environment in $\mathbb{Z}$. Our assumption on the law of the environment is such that a single walker is transient to the right but subballistic. We show that - no matter what $d$ is - the $d$ walkers meet infinitely often, i.e. there are almost surely infinitely many times for which all the random walk

Roberto Franzosi

In a recent paper [Franzosi, Physica A {\bf 494}, 302 (2018)], we have suggested to use of the surface entropy, namely the logarithm of the area of a hypersurface of constant energy in the phase space, as an expression for the thermodynamic microcanonical entropy, in place of the standard definition usually known as Boltzmann entropy. In the present manuscri

James Farre

We show that the bounded Borel class of any dense representation $ρ: G\to \PSL_n\bC$ is non-zero in degree three bounded cohomology and has maximal semi-norm, for any discrete group $G$. When $n=2$, the Borel class is equal to the $3$-dimensional hyperbolic volume class. Using tools from the theory of Kleinian groups, we show that the volume class of a dense

Rafael C. Nunes, Marcio E. S. Alves, Jose C. N. de Araujo

We investigate the propagation of primordial gravitational waves within the context of the Horndeski theories, for this, we present a generalized transfer function quantifying the sub-horizon evolution of gravitational waves modes after they enter the horizon. We compare the theoretical prediction of the modified primordial gravitational waves spectral densi

Arman Sharifi Kolarijani, Sander Bregman, Peyman Mohajerin Esfahani, Tamas Keviczky

In this paper, we propose an event-based sampling policy to implement a constraint-tightening, robust MPC method. The proposed policy enjoys a computationally tractable design and is applicable to perturbed, linear time-invariant systems with polytopic constraints. In particular, the triggering mechanism is suitable for plants with no centralized sensory nod

Axel Davy, Thibaud Ehret, Jean-Michel Morel, Pablo Arias

Non-local patch based methods were until recently state-of-the-art for image denoising but are now outperformed by CNNs. Yet they are still the state-of-the-art for video denoising, as video redundancy is a key factor to attain high denoising performance. The problem is that CNN architectures are hardly compatible with the search for self-similarities. In th

Y. K. Gupta, B. K. Nayak, U. Garg, N. Sensharma

Quasi-elastic scattering measurements have been performed using $^{16}$O and $^{24}$Mg projectiles off $^{90}$Zr at energies around the Coulomb barrier. Experimental data have been analyzed in the framework of coupled channels (CC) calculations using the code CCFULL. The quasi-elastic scattering excitation function and derived barrier distribution for $^{16}

Jiaxin Gu, Ce Li, Baochang Zhang, Jungong Han

The advancement of deep convolutional neural networks (DCNNs) has driven significant improvement in the accuracy of recognition systems for many computer vision tasks. However, their practical applications are often restricted in resource-constrained environments. In this paper, we introduce projection convolutional neural networks (PCNNs) with a discrete ba

Yining Xu, Zijian Xiong, Han-Qing Wu, Dao-Xin Yao*

We study the spin excitation spectra of the two-dimensional spin-$1/2$ Heisenberg model with a checkerboard structures using stochastic analytic continuation of the imaginary-time correlation function obtained from a quantum Monte Carlo simulation. The checkerboard models have two different antiferromagnetic nearest-neighbor interactions $J_{1}$ and $J_{2}$,

A. A. Aligia, C. Helman

Using maximally localized Wannier functions obtained from DFT calculations, we derive an effective Hubbard Hamiltonian for a bilayer of Sr$_3$Cr$_2$O$_7$, the $n=2$ member of the Ruddlesden-Popper Sr$_{n+1}$Cr$_n$O$_{3n+1}$ system. The model consists of effective $t_{2g}$ orbitals of Cr in two square lattices, one above the other. The model is further reduce

N. Zh. Bunzarova, N. C. Pesheva, J. G. Brankov

We study here one-dimensional model of aggregation and fragmentation of clusters of particles obeying the stochastic discrete-time kinetics of the generalized Totally Asymmetric Simple Exclusion Process (gTASEP) on open chains. Isolated particles and the first particle of a cluster of particles hop one site forward with probability $p$; when the first partic

Abdelaali Boudjemaa

We investigate the superfluidity and the coherence in dipolar binary Bose mixtures using the hydrodynamic approach. Useful analytical formulas for the excitations spectrum, the correlation function, the static structure factor, and the superfluid fraction are derived. We find that in the case of highly imbalanced mixture, the superfluidity can occur in the d

Tavi Halperin, Ariel Ephrat, Yedid Hoshen

Separating mixed distributions is a long standing challenge for machine learning and signal processing. Most current methods either rely on making strong assumptions on the source distributions or rely on having training samples of each source in the mixture. In this work, we introduce a new method---Neural Egg Separation---to tackle the scenario of extracti

Zhou Rui, Ya-Qian Li, Jie Zhang

We present an analysis of two isovector scalar resonant contributions to the $B$ decays into charmonia plus $K\bar K$ or $πη$ pair in the perturbative QCD approach. The Flatté model for the $a_0(980)$ resonance and the Breit Wigner formula for the $a_0(1450)$ resonance are adopted to parametrize the timelike form factors in the dimeson distribution amplitude

Krzysztof P. Wójcik, Maciej Misiorny, Ireneusz Weymann

We investigate theoretically the interplay of proximity effects due to the presence of a superconductor and normal ferromagnetic leads on the formation of the spintronic quadrupolar exchange field in a large-spin molecule. We show that the spintronic anisotropy can be enhanced by a few orders of magnitude, and tuned by changing the strength of coupling to th

ALICE Collaboration

The second ($v_2$) and third ($v_3$) flow harmonic coefficients of J/$ψ$ mesons are measured at forward rapidity (2.5 $<$ $y$ $<$ 4.0) in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV with the ALICE detector at the LHC. Results are obtained with the scalar product method and reported as a function of transverse momentum, $p_{\rm{T}}$, for various collis

Enrique Arrondo, Alessandra Bernardi, Pedro Macias Marques, Bernard Mourrain

We introduce the ``skew apolarity lemma&#39;&#39; and we use it to give algorithms for the skew-symmetric rank and the decompositions of tensors in {$\bigwedge^dV_{\mathbb{C}}$ with $d\leq 3$ and $\dim V_{\mathbb{C}} \leq 8$}. New algorithms to compute the rank and a minimal decomposition of a tritensor are also presented.

Pascal Gadient, Mohammad Ghafari, Patrick Frischknecht, Oscar Nierstrasz

Android Inter-Component Communication (ICC) is complex, largely unconstrained, and hard for developers to understand. As a consequence, ICC is a common source of security vulnerability in Android apps. To promote secure programming practices, we have reviewed related research, and identified avoidable ICC vulnerabilities in Android-run devices and the securi

Armin Tavakoli, Massimiliano Smania, Tamás Vértesi, Nicolas Brunner

Self-testing represents the strongest form of certification of a quantum system. Here we investigate theoretically and experimentally the question of self-testing non-projective quantum measurements. That is, how can one certify, from observed data only, that an uncharacterised measurement device implements a desired non-projective positive-operator-valued-m

Jishnu Mukhoti, Yarin Gal

Deep learning has been revolutionary for computer vision and semantic segmentation in particular, with Bayesian Deep Learning (BDL) used to obtain uncertainty maps from deep models when predicting semantic classes. This information is critical when using semantic segmentation for autonomous driving for example. Standard semantic segmentation systems have wel

Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan

Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards. However, a sharp characterization of the performance of traditional codes is available only in the large block-length limit. Guided by such asymptotic analysis, code designs require large block lengths as well as latency to achieve the desired err

Claude Semay

A generalization of the Kepler&#39;s third law has been proposed by BoHua Sun for $N$-body periodic orbits in a Newtonian gravitation field. In this paper, it is shown that this formula can apply for a quantum system of $N$ self-gravitating identical particles, for a good choice of the period for the quantum motion.

G. Oelsner, U. Hübner, E. Il&#39;ichev

We study the influence of a strong off-resonant driving signal to the energy levels of a superconducting flux qubit both experimentally and theoretically. In the experiment, we carry out a three-tone spectroscopy. This allows us to directly observe the modification of the qubit&#39;s energy levels by the dynamical Stark shift caused by the driving signal. A

Anna Chiara Lai, Monica Motta

We extend the classical concepts of sampling and Euler solutions for control systems associated to discontinuous feedbacks by considering also the corresponding costs. In particular, we introduce the notions of Sample and Euler stabilizability to a closed target set (p0,W)-regulated cost, for some continuous, state-dependent function W and some positive cons

Gane Samb Lo

Left and right-continuous functions play an important role in Real analysis, especially in Measure Theory and Integration on the real line and in Stochastic processes indexed by a continuous real time. Semi-continuous functions are also of major interest in the same way. This paper aims at presenting a useful handling of semi-continuous function in parallel

Peter Cox, Chengcheng Han, Tsutomu T. Yanagida, Norimi Yokozaki

We explore the possibility that the muon $g-2$ anomaly and the nature of dark matter can be simultaneously explained within the framework of gaugino mediation, focusing on bino-like dark matter where the observed abundance is obtained via co-annihilations. The minimal model with non-universal gaugino masses is excluded by stau vacuum instability, although th

Fumiaki Kohsaka

We study the existence and approximation of fixed points of metrically nonspreading mappings and firmly metrically nonspreading mappings in Hadamard spaces. The resolvents of monotone operators satisfying range conditions are typical examples of firmly metrically nonspreading mappings. Applications to monotone operators in such spaces are also included.

Dimitrios Kilymis, Simona Ispas, Bernard Hehlen, Sylvain Peuget

The vibrational properties of three sodosilicate glasses have been investigated in the framework of Density Functional Theory. The pure vibrational density of states has been calculated for all systems and the different vibrational modes have been assigned to specific atoms or structural units. It is shown that the Na content affects several vibrational feat

Qi Wang, Quan Zhou, Zhen-Hua Wan, De-Jun Sun

Penetrative turbulent Rayleigh-Bénard convection which depends on the density maximum of water near $4^\circ\rm{C}$ is studied using two-dimensional (2D) and three-dimensional (3D) direct numerical simulations (DNS). The working fluid is water near $4^\circ\rm{C}$ with Prandtl number $Pr=11.57$. The considered Rayleigh numbers $Ra$ range from $10^7$ to $10^{

Ivan Levcovitz

We prove that thick groups (and more generally thick graphs) have trivial Floyd boundary. This shows a wide class of finitely generated groups that are non-relatively hyperbolic have trivial Floyd boundary. In addition to giving new examples, our result provides a common proof and framework for many of the known results in the literature.

Konstantinos Gavriil, Georg Muntingh, Oliver J. D. Barrowclough

In recent years, advances in machine learning algorithms, cheap computational resources, and the availability of big data have spurred the deep learning revolution in various application domains. In particular, supervised learning techniques in image analysis have led to superhuman performance in various tasks, such as classification, localization, and segme

Enrico Facca, Franco Cardin, Mario Putti

Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based $L^1$-optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of the transported masses with a time-varying conductivity that volves proportionally to the transported flux. In this paper we present an extension of this model that considers a time

Thomas Hertog, Brecht Truijen, Thomas Van Riet

We show that Euclidean axion wormholes in theories of gravity coupled to a single axion have several independent inhomogeneous perturbations that lower the Euclidean action. Our analysis relies on a judiciously chosen gauge-invariant variable which makes the negative mode structure about axion wormholes transparent. Perturbations lowering the action are conc

Yuta Ito, Hideo Matsufuru, Jun Nishimura, Shinji Shimasaki

Monte Carlo studies of QCD at finite density suffer from the sign problem, which becomes easily uncontrollable as the chemical potential $μ$ is increased even for a moderate lattice size. In this work we make an attempt to approach the high density low temperature region by the complex Langevin method (CLM) using four-flavor staggered fermions with reasonabl

Jens Hornbostel, Heng Xie, Marcus Zibrowius

We compute the Chow-Witt rings of split quadrics over a field of characteristic not two. We even determine the full bigraded I-cohomology and Milnor-Witt cohomology rings, including twists by line bundles. The results on I-cohomology corroborate the general philosophy that I-cohomology is an algebro-geometric version of singular cohomology of real varieties:

Steven Roberts, Arash Sarshar, Adrian Sandu

Traditional time discretization methods use a single timestep for the entire system of interest and can perform poorly when the dynamics of the system exhibits a wide range of time scales. Multirate infinitesimal step (MIS) methods (Knoth and Wolke, 1998) offer an elegant and flexible approach to efficiently integrate such systems. The slow components are di

Kevin Morand

The aim of this series of papers is to generalise the ambient approach of Duval et al. regarding the embedding of Galilean and Carrollian geometries inside gravitational waves with parallel rays. In this first part, we propose a generalisation of the embedding of torsionfree Galilean and Carrollian manifolds inside larger classes of gravitational waves. On t

Baptiste Cecconi, Pierre Le Sidaner, Lukasz Tomasik, Chiara Marmo

With its Planetary Space Weather Service (PSWS), the Europlanet-H2020 Research Insfrastructure (EPN2020RI) project is proposing a compelling set of databases and tools to that provides Space Weather forecasting throughout the Solar System. We present here the selected event transfer system (VOEvent). We describe the user requirements, develop the way to impl

Patrick Helber, Bradley Gram-Hansen, Indhu Varatharajan, Faiza Azam

Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understanding where these settlements are is of paramount importance to both government and non-government organizations

Xinsheng Wang, Weisheng Wu, Yujun Zhu

Let $\mathcal{F}$ be a $C^2$ random partially hyperbolic dynamical system. For the unstable foliation, the corresponding unstable metric entropy, unstable topological entropy and unstable pressure via the dynamics of $\mathcal{F}$ on the unstable foliation are introduced and investigated. A version of Shannon-McMillan-Breiman Theorem for unstable metric entr

Xiaojun Jia, Xingxing Wei, Xiaochun Cao, Hassan Foroosh

Deep neural networks (DNNs) have been demonstrated to be vulnerable to adversarial examples. Specifically, adding imperceptible perturbations to clean images can fool the well trained deep neural networks. In this paper, we propose an end-to-end image compression model to defend adversarial examples: \textbf{ComDefend}. The proposed model consists of a compr

John N. Bray, Qi Cai, Peter J. Cameron, Pablo Spiga

The Hall--Paige conjecture asserts that a finite group has a complete mapping if and only if its Sylow subgroups are not cyclic. The conjecture is now proved, and one aim of this paper is to document the final step in the proof (for the sporadic simple group $\mathrm{J}_4$). We apply this result to prove that primitive permutation groups of simple diagonal t

Jianing Zhang

Monte Carlo radiative transfer, which has been demonstrated as a successful algorithm for modeling radiation transport through the astrophysical medium, relies on sampling of scattering phase functions. We review several classic sampling algorithms such as the tabulated method and the accept-reject method for sampling the scattering phase function. The tabul

Qiuchi Li, Yijun Yu, Dawei Song, Bashar Nuseibeh

During software maintenance and evolution, developers need to deal with a large number of change requests by modifying existing code or adding code into the system. An efficient tackling of change request calls for an accurate localising of software changes, i.e. identifying which code are problematic and where new files should be added for any type of chang

Arda Antikacioglu, Tanvi Bajpai, R. Ravi

Recommender systems often operate on item catalogs clustered by genres, and user bases that have natural clusterings into user types by demographic or psychographic attributes. Prior work on system-wide diversity has mainly focused on defining intent-aware metrics among such categories and maximizing relevance of the resulting recommendations, but has not co

Simon J. Murphy

Binary systems anchor many of the fundamental relations relied upon in asteroseismology. Masses and radii are rarely constrained better than when measured via orbital dynamics and eclipse depths. Pulsating binaries have much to offer. They are clocks, moving in space, that encode orbital motion in the Doppler-shifted pulsation frequencies. They offer twice t

J. Kluson

In this note we perform canonical analysis of T-duality for non-relativistic string in stringy Newton-Cartan background. We confirm recent result that T-duality along longitudinal spatial direction of stringy Newton-Cartan geometry maps non-relativistic string to the relativistic string that propagates on the background with light-like isometry.

Yiling Chen, Shuran Zheng

We study a data analyst&#39;s problem of acquiring data from self-interested individuals to obtain an accurate estimation of some statistic of a population, subject to an expected budget constraint. Each data holder incurs a cost, which is unknown to the data analyst, to acquire and report his data. The cost can be arbitrarily correlated with the data. The d

Alex Turzillo

The two dimensional state sum models of Barrett and Tavares are extended to unoriented spacetimes. The input to the construction is an algebraic structure dubbed half twist algebras, a class of examples of which is real separable superalgebras with a continuous parameter. The construction generates pin-minus TQFTs, including the root invertible theory with p

Fei Sun, Jieming Zhou

Systemic risk measures are crucial for the stability of financial markets, yet classical formulations fail to capture the complexity of market volatility. We propose a new framework for systemic risk measurement on the variable-exponent Bochner-Lebesgue space $L^{p(\cdot)}$, where the exponent $p(\cdot)$ is a random variable rather than a deterministic const

Andrew Zhai, Hao-Yu Wu

Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images. Two major applications of metric learning are content-based image retrieval and face verification. For the retrieval tasks, the majority of current state-of-the-art (SOTA) approaches are triplet-based non-parametric traini

Jinseok Choi, Yunseong Cho, Brian L. Evans, Alan Gatherer

In this paper, we investigate learning-based maximum likelihood (ML) detection for uplink massive multiple-input and multiple-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). To overcome the significant dependency of learning-based detection on the training length, we propose two one-bit ML detection methods: a biased-learning method a

Ning Dai. Qing-Feng Sun

One of the typical features of Majorana zero mode (MZM) at the end of topological superconductor is a zero-bias peak in the tunneling spectroscopy of the normal lead-superconductor junction. In this paper we study on a model with one phonon mode coupling to the superconductor lead of the normal lead-superconductor junction, which can be viewed as an electron

Xingxing Wei, Siyuan Liang, Ning Chen, Xiaochun Cao

Adversarial examples have been demonstrated to threaten many computer vision tasks including object detection. However, the existing attacking methods for object detection have two limitations: poor transferability, which denotes that the generated adversarial examples have low success rate to attack other kinds of detection methods, and high computation cos

Sudeshna Roy, Meghana Madhyastha, Sheril Lawrence, Vaibhav Rajan

The Internet has rich and rapidly increasing sources of high quality educational content. Inferring prerequisite relations between educational concepts is required for modern large-scale online educational technology applications such as personalized recommendations and automatic curriculum creation. We present PREREQ, a new supervised learning method for in

Raquel Galazo, Irene Bartolomé, Laura Ares, Alfredo Luis

Two complementary observables can be measured simultaneously so that the exact individual distributions can be recovered by a proper data inversion. We apply this program to the paradigmatic example of the Young interferometer from the classical and quantum points of view. We show complete parallelism between complementarity in the quantum and classical theo

Yahui Wang, Shaojun Cai, Shi-Jie Li, Yun Liu

We present a real-time feature-based SLAM (Simultaneous Localization and Mapping) system for fisheye cameras featured by a large field-of-view (FoV). Large FoV cameras are beneficial for large-scale outdoor SLAM applications, because they increase visual overlap between consecutive frames and capture more pixels belonging to the static parts of the environme

Xiang Fan

A well-known result of von zur Gathen asserts that a non-exceptional permutation polynomial of degree $n$ over $\mathbb{F}_{q}$ exists only if $q<n^{4}$. With the help of the Weil bound for the number of $\mathbb{F}_{q}$-points on an absolutely irreducible (possibly singular) affine plane curve, Chahal and Ghorpade improved von zur Gathen&#39;s proof to repl

Yurui Ming, Chin-Teng Lin, Stephen D. Bartlett, Wei-Wei Zhang

Topologically ordered materials may serve as a platform for new quantum technologies such as fault-tolerant quantum computers. To fulfil this promise, efficient and general methods are needed to discover and classify new topological phases of matter. We demonstrate that deep neural networks augmented with external memory can use the density profiles formed i

Li Huang, Yifeng Yin, Zeng Fu, Shifa Zhang

Intensive care data are valuable for improvement of health care, policy making and many other purposes. Vast amount of such data are stored in different locations, on many different devices and in different data silos. Sharing data among different sources is a big challenge due to regulatory, operational and security reasons. One potential solution is federa

Haifeng Yu, Ivica Nikolic, Ruomu Hou, Prateek Saxena

Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their security guarantees. We propose a novel permissionless blockchain protocol OHIE which explicitly aims for sim

Hyungu Kahng, Yonghyun Jeong, Yoon Sang Cho, Gonie Ahn

StarCraft, one of the most popular real-time strategy games, is a compelling environment for artificial intelligence research for both micro-level unit control and macro-level strategic decision making. In this study, we address an eminent problem concerning macro-level decision making, known as the &#39;fog-of-war&#39;, which rises naturally from the fact t

Tsung-Wei Chen, Zhi-Yang Huang, Dah-Wei Chiou

We investigate the spin dynamics in the two-dimensional spin-orbit coupled system subject to an in-plane ($x$-$y$ plane) constant electric field, which is assumed to be turned on at the moment $t=0$. The equation of spin precession in linear response to the switch-on of the electric field is derived in terms of Heisenberg&#39;s equation by the perturbation m

Elham J. Barezi, Peyman Momeni, Pascale Fung

We propose a novel method, Modality-based Redundancy Reduction Fusion (MRRF), for understanding and modulating the relative contribution of each modality in multimodal inference tasks. This is achieved by obtaining an $(M+1)$-way tensor to consider the high-order relationships between $M$ modalities and the output layer of a neural network model. Applying a

Daniele Pinna, George Bourianoff, Karin Everschor-Sitte

The Reservoir Computing (RC) paradigm posits that sufficiently complex physical systems can be used to massively simplify pattern recognition tasks and nonlinear signal prediction. This work demonstrates how random topological magnetic textures present sufficiently complex resistance responses for the implementation of RC as applied to A/C current pulses. In

Hyunseok Kim, Hyunwoo Kwon

We consider the Dirichlet and Neumann problems for second-order linear elliptic equations: \[ -\triangle u +\mathrm{div}(u\mathbf{b}) =f \quad\text{ and }\quad -\triangle v -\mathbf{b} \cdot \nabla v =g \] in a bounded Lipschitz domain $Ω$ in $\mathbb{R}^n$ $(n\geq 3)$, where $\mathbf{b}:Ω\rightarrow \mathbb{R}^n$ is a given vector field. Under the assumptio

Yu-Ki Lee, Zhonghua Xi, Young-Joo Lee, Yun-Hyeong Kim

This study starts from the counter-intuitive question of how we can render a conventional stiff, non-stretchable and even brittle material conformable so that it can fully wrap around a curved surface, such as a sphere, without failure. Here, we answer this conundrum by extending geometrical design in computational kirigami (paper cutting and folding) to pap

Mingyuan Ma, Sen Na, Hongyu Wang, Congzhou Chen

Interactive news recommendation has been launched and attracted much attention recently. In this scenario, user&#39;s behavior evolves from single click behavior to multiple behaviors including like, comment, share etc. However, most of the existing methods still use single click behavior as the unique criterion of judging user&#39;s preferences. Further, al

Koji Hashimoto, Shunichiro Kinoshita, Keiju Murata

Thermal states in some quantum field theories (QFTs) correspond to black holes in asymptotically AdS spacetime in the AdS/CFT correspondence. We propose a direct procedure to construct holographic images of the black hole in the bulk from a given response function of the QFT on the boundary. The response function with respect to an external source correspond

Dinesh Kumar, Abhishek Kumar, Rajiv Prakash, Akhilesh Kumar Singh

The nanoparticles (NPs) of Zn1-xCuxFe2O4 (ZCFO) spinels with x = 0, 0.2, 0.4, 0.6 and 0.8 were synthesized by a sol-gel combustion method using acetate precursor. The NPs of ZCFO were prepared by following calcination process at 600C for 8hrs. The synthesized NPs of ZCFO were characterized by X-ray diffraction (XRD) analysis using Rietveld refinement. The Ri

Tao Zhu, Qiang Wu, Anzhong Wang

Field amplification and particle production due to parametric resonance are highly nontrivial predictions of quantum fields that couple to an oscillating source during inflation and reheating. Understanding this two effects is crucial for the connection between the resonance phenomenon and precise observational data. In this paper, we give a general and anal

Christopher Funk, Savinay Nagendra, Jesse Scott, Bharadwaj Ravichandran

Pose stability analysis is the key to understanding locomotion and control of body equilibrium, with applications in numerous fields such as kinesiology, medicine, and robotics. In biomechanics, Center of Pressure (CoP) is used in studies of human postural control and gait. We propose and validate a novel approach to learn CoP from pose of a human body to ai

Qingyu Liu, Haibo Zeng, Minghua Chen

We consider the scenario where a sender periodically sends a batch of data to a receiver over a multi-hop network, possibly using multiple paths. Our objective is to minimize peak/average Age-of-Information (AoI) subject to throughput requirements. The consideration of batch generation and multi-path communication differentiates our AoI study from existing o

Hossein Keshavarz, XuanLong Nguyen, Clayton Scott

Maximizing the likelihood has been widely used for estimating the unknown covariance parameters of spatial Gaussian processes. However, evaluating and optimizing the likelihood function can be computationally intractable, particularly for large number of (possibly) irregularly spaced observations, due to the need to handle the inverse of ill-conditioned and

Kyle Vedder, Joydeep Biswas

Real-world multi-agent systems such as warehouse robots operate under significant time constraints -- in such settings, rather than spending significant amounts of time solving for optimal paths, it is instead preferable to find valid collision-free paths quickly, even if suboptimal, and given additional time, to iteratively refine such paths to improve thei

Timur E. Gureyev, Alexander Kozlov, Yakov I. Nesterets, David M. Paganin

It is proved that the width of a function and the width of the distribution of its values cannot be made arbitrarily small simultaneously. In the case of ergodic stochastic processes, an ensuing uncertainty relationship is demonstrated for the product of correlation length and variance. A closely related uncertainty principle is also established for the aver

Yuuki Yokoyama, Tomu Katsumata, Muneki Yasuda

Generalization is one of the most important issues in machine learning problems. In this study, we consider generalization in restricted Boltzmann machines (RBMs). We propose an RBM with multivalued hidden variables, which is a simple extension of conventional RBMs. We demonstrate that the proposed model is better than the conventional model via numerical ex

Devlin Mallory

We give an answer in the &#34;geometric&#34; setting to a question of de Fernex, Ein, and Ishii, asking when local isomorphisms of $k$-schemes can be detected on the associated maps of local arc or jet schemes. In particular, we show that their ideal-closure operation $\mathfrak a\mapsto \mathfrak a^{\mathrm{ac}}$ (the arc-closure) on a local $k$-algebra $(R

Étienne André, Benoît Delahaye, Paulin Fournier, Didier Lime

In this paper we consider state reachability in networks composed of many identical processes running a parametric timed broadcast protocol (PTBP). PTBP are a new model extending both broadcast protocols and parametric timed automata. This work is, up to our knowledge, the first to consider the combination of both a parametric network size and timing paramet

Richard Cleve, Benoit Collins, Li Liu, Vern Paulsen

We consider a bipartite transformation that we call self-embezzlement and use it to prove a constant gap between the capabilities of two models of quantum information: the conventional model, where bipartite systems are represented by tensor products of Hilbert spaces; and a natural model of quantum information processing for abstract states on C*-algebras,

Quan Z. Sheng, Jian Yu, Hanchuan Xu, Wei Emma Zhang

In the era of Web of Things and Services, Context-aware Web Services (CASs) are emerging as an important technology for building innovative context-aware applications. CASs enable the information integration from both the physical and virtual world, which affects human living. However, it is challenging to build CASs, due to the lack of context provisioning

Amruta Mishra, Ankit Kumar, Pallabi Parui, Sourodeep De

The mass modifications of the light vector mesons ($ω$, $ρ$ and $ϕ$) are investigated in asymmetric nuclear matter in the presence of strong magnetic fields, using a QCD sum rule approach. These are computed from the medium modifications of the non-strange and strange light quark condensates as well as scalar gluon condensate. The quark and gluon condensates

Tsung-Hsi Wu, Chien-Chih Chen

In this paper, we propose a stochastic dynamic model for earthquake rupture and suggest that the Langevin equation of frictions may be used for interpreting the slip distributions of rupture processes in earthquakes. The steady-state solution of the derived Langevin equation analytically attains the truncated exponential (TEX) distribution that is empiricall

Marianna Chatzakou, Julio Delgado, Michael Ruzhansky

In this work we study a class of anharmonic oscillators within the framework of the Weyl-Hörmander calculus. The anharmonic oscillators arise from several applications in mathematical physics as natural extensions of the harmonic oscillator. A prototype is an operator on $\mathbb{R}^n$ of the form $(-Δ)^{\ell}+|x|^{2k}$ for $k,\ell$ integers $\geq 1$. The si

Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare

Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Thus, deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more.

Terence L. J. Harris

An improved a.e. lower bound is given for Hausdorff dimension under vertical projections in the first Heisenberg group.

Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Peter Krafft

In this empirical paper, we investigate how learning agents can be arranged in more efficient communication topologies for improved learning. This is an important problem because a common technique to improve speed and robustness of learning in deep reinforcement learning and many other machine learning algorithms is to run multiple learning agents in parall

Keuntaek Lee, Ziyi Wang, Bogdan I. Vlahov, Harleen K. Brar

This work presents a novel ensemble of Bayesian Neural Networks (BNNs) for control of safety-critical systems. Decision making for safety-critical systems is challenging due to performance requirements with significant consequences in the event of failure. In practice, failure of such systems can be avoided by introducing redundancies of control. Neural Netw

Fabian Paul, Hao Wu, Maximilian Vossel, Bert L. de Groot

A popular approach to analyze the dynamics of high-dimensional many-body systems, such as macromolecules, is to project the trajectories onto a space of slowly-varying collective variables, where subsequent analyses are made, such as clustering or estimation of free energy profiles or Markov state models (MSMs). However, existing &#34;dynamical&#34; dimensio

Han Huang, Boaz A. Slomka, Tomasz Tkocz, Beatrice-Helen Vritsiou

A central problem in discrete geometry, known as Hadwiger&#39;s covering problem, asks what the smallest natural number $N\left(n\right)$ is such that every convex body in ${\mathbb R}^{n}$ can be covered by a union of the interiors of at most $N\left(n\right)$ of its translates. Despite continuous efforts, the best general upper bound known for this number

Édouard Bonnet, Sergio Cabello, Bojan Mohar, Hebert Pérez-Rosés

We introduce the inverse Voronoi diagram problem in graphs: given a graph $G$ with positive edge-lengths and a collection $\mathbb{U}$ of subsets of vertices of $V(G)$, decide whether $\mathbb{U}$ is a Voronoi diagram in $G$ with respect to the shortest-path metric. We show that the problem is NP-hard, even for planar graphs where all the edges have unit len

Ruslan Skuratovskii

We consider algebraic affine and projective curves of Edwards \cite{E, SkOdProj} over a finite field $\text{F}_{p^n}$. Most cryptosystems of the modern cryptography \cite{SkBlock} can be naturally transform into elliptic curves \cite{Kob}. We research Edwards algebraic curves over a finite field, which at the present time is one of the most promising support

Aleksander Matavž, Vid Bobnar, Barbara Malič

The surface properties of a substrate are among the most important parameters in the printing technology of functional materials, determining not only the printing resolution but also the stability of the printed features. This paper addresses the wetting difficulties encountered during inkjet printing on homogeneous substrates as a result of improper surfac

Jie Liu, Haifeng Ou, Rong Zeng, Wei Wei

Structures and/or materials with engineered functionality, capable of achieving targeted mechanical responses reacting to changes in external excitation, have various potential engineering applications, e.g. aerospace, oceanographic engineering, soft robot, and several others. Yet tunable mechanical performance is normally realized through carefully designin

Anthony D. Draper, Ryan K. Cole, Amanda S. Makowiecki, Jeffrey Mohr

We demonstrate fiber mode-locked dual frequency comb spectroscopy for broadband, high resolution measurements in a rapid compression machine (RCM). We apply an apodization technique to improve the short-term signal-to-noise-ratio (SNR), which enables broadband spectroscopy at combustion-relevant timescales. We measure the absorption on 24345 individual wavel

Sankha Shuvra Das, Shantimoy Kar, Sayantan Dawn, Partha Saha

Dielectrophoresis is a very promising technique for particle manipulation on a chip. In this study, we demonstrate a controlled mannuvering of polystryrene particles on a simple paper-and-pencil based device by exploiting the underlying electrokinetics with primary contribution from dielectrophoretic (DEP) forces. On contrary to other reported DEP devices, t