April 2019 arXiv papers — page 73

Eunok Bae, Soojoon Lee

There have been several research works on the hidden shift problem, quantum algorithms for the problem, and their applications. However, all the results have focused on discrete groups with discrete oracle functions. In this paper, we define the continuous hidden shift problem on $\mathbb{R}^n$ with a continuous oracle function as an extension of the hidden

Shohei Tamaoki, Koji Sugitani, Quang Nguyen-Luong, Fumitaka Nakamura

The RCW 106 molecular cloud complex is an active massive star-forming region where a ministarburst is taking place. We examined its magnetic structure by near-IR polarimetric observations with the imaging polarimeter SIRPOL on the IRSF 1.4 m telescope. The global magnetic field is nearly parallel to the direction of the Galactic plane and the cloud elongatio

L. Markhof, M. Pletyukhov, V. Meden

The nonlinear Luttinger liquid phenomenology of one-dimensional correlated Fermi systems is an attempt to describe the effect of the band curvature beyond the Tomonaga-Luttinger liquid paradigm. It relies on the observation that the dynamical structure factor of the interacting electron gas shows a logarithmic threshold singularity when evaluated to first or

James E. Davies, Simon J. Mutch, Yuxiang Qin, Andrei Mesinger

Intergalactic medium temperature is a powerful probe of the epoch of reionisation, as information is retained long after reionisation itself. However, mean temperatures are highly degenerate with the timing of reionisation, with the amount heat injected during the epoch, and with the subsequent cooling rates. We post-process a suite of semi-analytic galaxy f

Federico Nanni, Goran Glavas, Ines Rehbein, Simone Paolo Ponzetto

During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science. Prominent text scaling algorithms, however, rely on the assumption that latent positions can be captured just by leveraging the information about word frequencies in documents under study. We challenge this traditional vie

Ziming Zhu, Zhi-Ming Yu, Weikang Wu, Lifa Zhang

Weak topological insulators and Dirac semimetals are gapped and nodal phases with distinct topological properties, respectively. Here, we propose a novel topological phase that exhibits features of both and is dubbed composite Dirac semimetal (CDSM). In its bulk, the CDSM has a pair of Dirac points and a pair of bands inverted along a high-symmetry path. At

Adrien Bitton, Philippe Esling, Antoine Caillon, Martin Fouilleul

Generative models have thrived in computer vision, enabling unprecedented image processes. Yet the results in audio remain less advanced. Our project targets real-time sound synthesis from a reduced set of high-level parameters, including semantic controls that can be adapted to different sound libraries and specific tags. These generative variables should a

Laurent Schmalen, Vahid Aref

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing the amount of coupling between spatial positions, we show that we can construct codes with improved decoding speed compare

S. M. Shaaban, M. Lazar, P. H. Yoon, S. Poedts

Context. Solar outflows are a considerable source of free energy which accumulates in multiple forms like beaming (or drifting) components and/or temperature anisotropies. However, kinetic anisotropies of plasma particles do not grow indefinitely and particle-particle collisions are not efficient enough to explain the observed limits of these anisotropies. I

James Pearson, Nan Li, Simon Dye

We explore the effectiveness of deep learning convolutional neural networks (CNNs) for estimating strong gravitational lens mass model parameters. We have investigated a number of practicalities faced when modelling real image data, such as how network performance depends on the inclusion of lens galaxy light, the addition of colour information and varying s

Roel Henckaerts, Marie-Pier Côté, Katrien Antonio, Roel Verbelen

Pricing actuaries typically operate within the framework of generalized linear models (GLMs). With the upswing of data analytics, our study puts focus on machine learning methods to develop full tariff plans built from both the frequency and severity of claims. We adapt the loss functions used in the algorithms such that the specific characteristics of insur

Yinggu Chen, Boualem Djehiche, Said Hamadene

We study a general class of fully coupled backward-forward stochastic differential equations of mean-field type (MF-BFSDE). We derive existence and uniqueness results for such a system under weak monotonicity assumptions and without the non-degeneracy condition on the forward equation. This is achieved by suggesting an implicit approximation scheme that is s

Muhammad Hassani, Alexandra E. Lagogianni, Fathollah Varnik

Recent experiments provide evidence for density variations along shear bands (SB) in metallic glasses with a length scale of a few hundreds nanometers. Via molecular dynamics simulations of a generic binary glass model, here we show that this is strongly correlated with variations of composition, coordination number, viscosity and heat generation. Individual

Yatie Xiao, Chi-Man Pun

Deep neural networks are easily fooled high confidence predictions for adversarial samples

Miguel A. Delgado, Andrés García-Suaza, Pedro H. C. Sant'Anna

This article proposes inference procedures for distribution regression models in duration analysis using randomly right-censored data. This generalizes classical duration models by allowing situations where explanatory variables' marginal effects freely vary with duration time. The article discusses applications to testing uniform restrictions on the varying

Aniket Biswas, Subrata Chakraborty

The unit-Lindley distribution was recently introduced in the literature as a viable alternative to the Beta and the Kumaraswamy distributions with support in (0; 1). This distribution enjoys many virtuous properties over the named distributions. In this article, we address the issue of parameter estimation from a Bayesian perspective and study relative perfo

Rogelio A. Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen

Credit scoring models based on accepted applications may be biased and their consequences can have a statistical and economic impact. Reject inference is the process of attempting to infer the creditworthiness status of the rejected applications. In this research, we use deep generative models to develop two new semi-supervised Bayesian models for reject inf

Yoshiaki Tsujimoto, Chenglong You, Kentaro Wakui, Mikio Fujiwara

To realize the practical implementation of device-independent quantum key distribution~(DIQKD), the main difficulty is that its security relies on the detection-loophole-free violation of the Clauser-Horne-Shimony-Holt~(CHSH) inequality, i.e. the CHSH value $S>2$, which is easily destroyed by the loss in transmission channels. One of the simplest methods to

F. M. Addesa, L. Burmistrov, D. Breton, G. Cavoto

The UA9 Experiment at CERN-SPS investigates channeling processes in bent silicon crystals with the aim to manipulate hadron beams. Monitoring and characterization of channeled beams in the high energy accelerators environment ideally requires in-vacuum and radiation hard detectors. For this purpose the Cherenkov detector for proton Flux Measurement (CpFM) wa

Klaus Renziehausen, Ingo Barth

The Ehrenfest theorem and the Robertson uncertainty relation are well-known basic equations in quantum mechanics. However, there exist problematic cases, where the Ehrenfest theorem and the Robertson uncertainty relation are not correct. These cases occur when the azimuthal angle in polar or spherical coordinates is used within these equations. The purpose o

Amirreza Khodadadian, Benjamin Stadlbauer, Clemens Heitzinger

Nanowire field-effect sensors have recently been developed for label-free detection of biomolecules. In this work, we introduce a computational technique based on Bayesian estimation to determine the physical parameters of the sensor and, more importantly, the properties of the analyte molecules. To that end, we first propose a PDE based model to simulate th

Søren Fournais, Jan Philip Solovej

For a dilute system of non-relativistic bosons interacting through a positive $L^1$ potential $v$ with scattering length $a$ we prove that the ground state energy density satisfies the bound $e(ρ) \geq 4πa ρ^2 (1+ \frac{128}{15\sqrtπ} \sqrt{ρa^3} +o(\sqrt{ρa^3}\,))$, thereby proving the Lee-Huang-Yang formula for the energy density.

Marijn van Vliet

Unorganized heaps of analysis code are a growing liability as data analysis pipelines are getting longer and more complicated. This is worrying, as neuroscience papers are getting retracted due to programmer error. In this paper, some guidelines are presented that help keep analysis code well organized, easy to understand and convenient to work with: 1. Each

Krzysztof Bisewski, Jevgenijs Ivanovs

For a L\'evy process $X$ on a finite time interval consider the probability that it exceeds some fixed threshold $x>0$ while staying below $x$ at the points of a regular grid. We establish exact asymptotic behavior of this probability as the number of grid points tends to infinity. We assume that $X$ has a zooming-in limit, which necessarily is $1/\alpha$-se

Andrew Francis, Henry Wynn

This paper introduces a new way to define a genome rearrangement distance, using the concept of mean first passage time from probability theory. Crucially, this distance estimate provides a genuine metric on genome space. We develop the theory and introduce a link to a graph-based zeta function. The approach is very general and can be applied to a wide varie

Stylianos Ioannis Mimilakis, Konstantinos Drossos, Estefanía Cano, Gerald Schuller

The goal of this work is to investigate what singing voice separation approaches based on neural networks learn from the data. We examine the mapping functions of neural networks based on the denoising autoencoder (DAE) model that are conditioned on the mixture magnitude spectra. To approximate the mapping functions, we propose an algorithm inspired by the k

Kai Hou Yip, Nikolaos Nikolaou, Piero Coronica, Angelos Tsiaras

Further advances in exoplanet detection and characterisation require sampling a diverse population of extrasolar planets. One technique to detect these distant worlds is through the direct detection of their thermal emission. The so-called direct imaging technique, is suitable for observing young planets far from their star. These are very low signal-to-nois

Milo Viviani

Isospectral flows are abundant in mathematical physics; the rigid body, the the Toda lattice, the Brockett flow, the Heisenberg spin chain, and point vortex dynamics, to mention but a few. Their connection on the one hand with integrable systems and, on the other, with Lie--Poisson systems motivates the research for optimal numerical schemes to solve them. S

Miquel Junyent, Anders Jonsson, Vicenç Gómez

Width-based planning has demonstrated great success in recent years due to its ability to scale independently of the size of the state space. For example, Bandres et al. (2018) introduced a rollout version of the Iterated Width algorithm whose performance compares well with humans and learning methods in the pixel setting of the Atari games suite. In this se

Akihito Tamada, Yasutomo Ota, Kazuhiro Kuruma, Katsuyuki Watanabe

We report single plasmon generation with a self-assembled InAs/GaAs quantum dot embedded in a plasmonic microring resonator. The plasmonic cavity based on a GaAs microring is defined on an atomically-smooth silver surface. We fabricated this structure with the help of transfer printing, which enables the pick-and-place assembly of the complicated, heterogene

Felipe R. Monteiro, Mikhail R. Gadelha, Lucas C. Cordeiro

Software model checking has experienced significant progress in the last two decades, however, one of its major bottlenecks for practical applications remains its scalability and adaptability. Here, we describe an approach to integrate software model checking techniques into the DevOps culture by exploiting practices such as continuous integration and regres

Jibril Ben Achour, Etera R. Livine

The polymer quantization of cosmological backgrounds provides an alternative path to the original Wheeler-de Witt (WdW) quantum cosmology, based on a different representation the commutation relations of the canonical variables. This polymer representation allows to capture the lattice like structure of the quantum geometry and leads to a radically different

Ari Heljakka, Arno Solin, Juho Kannala

We present a generative autoencoder that provides fast encoding, faithful reconstructions (eg. retaining the identity of a face), sharp generated/reconstructed samples in high resolutions, and a well-structured latent space that supports semantic manipulation of the inputs. There are no current autoencoder or GAN models that satisfactorily achieve all of the

Andreas E. Kyprianou, Juan Carlos Pardo, Matija Vidmar

Motivated by a recent paper of Budd, where a new family of positive self-similar Markov processes associated to stable processes appears, we introduce a new family of Lévy processes, called the double hypergeometric class, whose Wiener-Hopf factorisation is explicit, and as a result many functionals can be determined in closed form.

Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy

In a standard classification framework a set of trustworthy learning data are employed to build a decision rule, with the final aim of classifying unlabelled units belonging to the test set. Therefore, unreliable labelled observations, namely outliers and data with incorrect labels, can strongly undermine the classifier performance, especially if the trainin

Pierros Ntelis, Adam James Hawken, Stephanie Escoffier, Anne Ealet

In this paper, we study the normalised characteristic scale of transition to cosmic homogeneity, $\mathcal{R}_H/d_V$, as a cosmological probe. We use a compilation of SDSS galaxy samples, comprising more than $10^6$ galaxies in the redshift range $0.17 \leq z \leq 2.2$ within the largest comoving volume to date, $\sim 8 h^{-3}\mathrm{Gpc}^3$. We show that th

Zhanna Sarsenbayeva, Vassilis Kostakos, Jorge Goncalves

Research has shown that various environmental factors impact smartphone interaction and lead to Situationally-Induced Impairments and Disabilities. In this work we discuss the importance of thoroughly understanding the effects of these situational impairments on smartphone interaction. We argue that systematic investigation of the effects of different situat

Wolfgang Mück

The generalized Fradkin-Tseytlin counterterm for the (type I) Green-Schwarz superstring is determined for background fields satisfying the generalized supergravity equations (GSE). For this purpose, we revisit the derivation of the GSE based upon the requirement of kappa-symmetry of the superstring action. Lifting the constraint of vanishing bosonic torsion

Shiyu Zhu, Lingyuan Kong, Lu Cao, Hui Chen

Majorana zero-modes (MZMs) are spatially-localized zero-energy fractional quasiparticles with non-Abelian braiding statistics that hold a great promise for topological quantum computing. Due to its particle-antiparticle equivalence, an MZM exhibits robust resonant Andreev reflection and 2e2/h quantized conductance at low temperature. By utilizing variable-tu

Johannes Schleischitz

Consider a real matrix $\Theta$ consisting of rows $(\theta_{i,1},\ldots,\theta_{i,n})$, for $1\leq i\leq m$. The problem of making the system linear forms $x_{1}\theta_{i,1}+\cdots+x_{n}\theta_{i,n}-y_{i}$ for integers $x_{j},y_{i}$ small naturally induces an ordinary and a uniform exponent of approximation, denoted by $w(\Theta)$ and $\widehat{w}(\Theta)$

Walter Metzner, Hiroyuki Yamase

We analyze the suppression of the phase stiffness in a superconductor by antiferromagnetic order. The analysis is based on a general expression for the phase stiffness in a mean-field state with coexisting spin-singlet superconductivity and spiral magnetism. Neel order is included as a special case. Close to half-filling, where the pairing gap is much smalle

Paola Gervasio, Federico Marini

In this paper we apply the INTERNODES method to solve second order elliptic problems discretized by Isogeometric Analysis methods on non-conforming multiple patches in 2D and 3D geometries. INTERNODES is an interpolation-based method that, on each interface of the configuration, exploits two independent interpolation operators to enforce the continuity of th

Joachim Berg, Nils Gustav Andreas Berggren, Sivert Allergodt Borgeteien, Christian Ruben Alexander Jahren

In this work, an evolutionary art project is presented where images are approximated by transparent, overlapping and geometric shapes of different types, e.g., polygons, circles, lines. Genotypes representing features and order of the geometric shapes are evolved with a fitness function that has the corresponding pixels of an input image as a target goal. A

Xiaowei Yuan, In Kyu Park

In recent decades, 3D morphable model (3DMM) has been commonly used in image-based photorealistic 3D face reconstruction. However, face images are often corrupted by serious occlusion by non-face objects including eyeglasses, masks, and hands. Such objects block the correct capture of landmarks and shading information. Therefore, the reconstructed 3D face mo

Yasir Mahmood, Arne Meier

In this paper, we initiate a systematic study of the parametrised complexity in the field of Dependence Logics which finds its origin in the Dependence Logic of Väänänen from 2007. We study a propositional variant of this logic (PDL) and investigate a variety of parametrisations with respect to the central decision problems. The model checking problem (MC) o

Yoshikazu Giga, Koya Sakakibara, Kazutoshi Taguchi, Masaaki Uesaka

In this paper, we propose a new numerical scheme for a spatially discrete model of constrained total variation flows, which are total variation flows whose values are constrained in a Riemannian manifold. The difficulty of this problem is that the underlying function space is not convex and it is hard to calculate the minimizer of the functional with the man

Jan Kyzioł, Andrzej Okniński

Dynamics of the Duffing--Van der Pol driven oscillator is investigated. Periodic steady-state solutions of the corresponding equation are computed within the Krylov-Bogoliubov-Mitropolsky approach to yield dependence of amplitude $A$ on forcing frequency $Ω$ as an implicit function, $F\left( A,Ω\right) =0$, referred to as resonance curve or amplitude profile

Tomasz Witczak

Generalized topological spaces are not necessarily closed under finite intersections. Moreover, the whole universe does not need to be open. We use modified version of this framework to establish certain models for non-normal modal logics. We consider at least two approaches to this topic, wherein one of them is based on the interplay of two operators, both

Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh

Single-image super-resolution aims to generate a high-resolution version of a low-resolution image, which serves as an essential component in many computer vision applications. This paper investigates the robustness of deep learning-based super-resolution methods against adversarial attacks, which can significantly deteriorate the super-resolved images witho

Sergey Arsenyev, Alexej Grudiev, Daniel Schulte

In particle accelerators, pumping holes in a vacuum chamber can be a source of unwanted broadband coupling impedance, leading to beam instabilities. Analytical methods have been previously developed to estimate the impedance of holes in circular-like chambers e.g. the beamscreen of the Large Hadron Collider (LHC). More sophisticated chamber designs like that

Changli Ma, He Cheng, Taisen Zuo, Guisheng Jiao

Empirical potential structure refinement (EPSR) is a neutron scattering data analysis algorithm and a software package. It was developed by the British spallation neutron source (ISIS) Disordered Materials Group in 1980s, and aims to construct the most-probable atomic structures of disordered liquids. It has been extensively used during the past decades, and

Li-Min Gu, Hai-Bo Li, Xin-Xin Ma, Mao-Zhi Yang

We study the electromagnetic Dalitz (EM) decays, $ψ\to η_{c} l^{+} l^{-}$ and $Υ\to η_{b} l^{+} l^{-}$ ($l = e$ or $μ$), in which the lepton pair comes from the virtual photon emitted by the M1 transition from $c\bar{c}$ ($b\bar{b}$) spin triplet state to the spin singlet state. We estimate the partial width of $ψ(Υ) \to η_{c}(η_{b}) l^{+} l^{-}$, based on t

Ryoko Hatakeyama, Akira Shimizu

We study nanomachines whose relevant (effective) degrees of freedom f >> 1 but smaller than f of proteins. In these machines, both the entropic and the quantum effects over the whole system play the essential roles in producing nontrivial functions. We therefore call them entropic quantum machines (EQMs). We propose a systematic protocol for designing the EQ

Dmitri A. Ivanov, Leonid Gurvits

We study the computational complexity of quantum-mechanical expectation values of single-particle operators in bosonic and fermionic multi-particle product states. Such expectation values appear, in particular, in full-counting-statistics problems. Depending on the initial multi-particle product state, the expectation values may be either easy to compute (th

D. Dauitbek, J. Huang, F. Sukochev

Let $f$ be an arbitrary integrable function on a finite measure space $(X,Σ, ν)$. We characterise the extreme points of the set $Ω(f)$ of all measurable functions on $(X,Σ, ν)$ majorised by $f$, providing a complete answer to a problem raised by W.A.J. Luxemburg in 1967. Moreover, we obtain a noncommutative version of this result.

Liumeng Xue, Wei Song, Guanghui Xu, Lei Xie

When deploying a Chinese neural text-to-speech (TTS) synthesis system, one of the challenges is to synthesize Chinese utterances with English phrases or words embedded. This paper looks into the problem in the encoder-decoder framework when only monolingual data from a target speaker is available. Specifically, we view the problem from two aspects: speaker c

Sergei Gukov, Ciprian Manolescu

The physical 3d $\mathcal{N}=2$ theory T[Y] was previously used to predict the existence of some 3-manifold invariants $\hat{Z}_{a}(q)$ that take the form of power series with integer coefficients, converging in the unit disk. Their radial limits at the roots of unity should recover the Witten-Reshetikhin-Turaev invariants. In this paper we discuss how, for

Ivan Heibi, Silvio Peroni, David Shotton

In this paper, we present COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations (http://opencitations.net/index/coci). COCI is the first open citation index created by OpenCitations, in which we have applied the concept of citations as first-class data entities, and it contains more than 445 million DOI-to-DOI citation links derived from the da

Charlotte Dion, Sarah Lemler, Eva Löcherbach

In this paper, we introduce a new class of processes which are diffusions with jumps driven by a multivariate nonlinear Hawkes process. Our goal is to study their long-time behavior. In the case of exponential memory kernels for the underlying Hawkes process we establish conditions for the positive Harris recurrence of the couple (X, Y), where X denotes the

Jun-ichi Takeshita, Yuto Arai, Mayu Ogawa, Xiao-Nan Lu

The present study defines a new statistic for detecting laboratory effects in the analysis of ordinal variation (ORDANOVA). The ORDANOVA is an analysis method similar to one-way analysis of variance for analysing ordinal data obtained from interlaboratory comparison studies. In this paper, we present an approximate continuous distribution for the new statist

Maho Nakata, Tomomi Shimazaki, Masatomo Hashimoto, Toshiyuki Maeda

We report on the largest dataset of optimized molecular geometries and electronic properties calculated by the PM6 method for 92.9% of the 91.2 million molecules cataloged in PubChem Compounds retrieved on Aug. 29, 2016. In addition to neutral states, we also calculated those for cationic, anionic, and spin flipped electronic states of 56.2%, 49.7%, and 41.3

A. Shlapunov, N. Tarkhanov

We consider a Sturm--Liouville boundary value problem in a boun\-ded domain $\cD$ of $\mathbb{R}^n$. By this is meant that the differential equation is given by a second order elliptic operator of divergent form in $\cD$ and the boundary conditions are of Robin type on $\partial \cD$. The first order term of the boundary operator is the oblique derivative wh

Bilal Ahmed Lodhi

Breast cancer is one of the most common and prevalent type of cancer that mainly affects the women population. chances of effective treatment increases with early diagnosis. Mammography is considered one of the effective and proven techniques for early diagnosis of breast cancer. Tissues around masses look identical in mammogram, which makes automatic detect

P. Giommi, C. H. Brandt, U. Barres de Almeida, A. M. T. Pollock

Open Universe for blazars is a set of high-transparency data products for blazar science, and the tools designed to generate them. Blazar astrophysics is becoming increasingly data driven, depending on the integration and combined analysis of large quantities of data from the entire span of observational astrophysics techniques. The project was therefore cho

Huang Victoria, Chen Gang, Fu Qiang

Recent research on Software-Defined Networking (SDN) strongly promotes the adoption of distributed controller architectures. To achieve high network performance, designing a scheduling function (SF) to properly dispatch requests from each switch to suitable controllers becomes critical. However, existing literature tends to design the SF targeted at specific

Ye Jia, Ron J. Weiss, Fadi Biadsy, Wolfgang Macherey

We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an intermediate text representation. The network is trained end-to-end, learning to map speech spectrograms into target spectrograms in another language, corresponding to the translated co

Subhasish Chakrabarty, Amitabha Lahiri

The dynamics of fermions on curved spacetime requires a spin connection, which contains a part called contorsion, an auxiliary field without dynamics but fully expressible in terms of the axial current density of fermions. Its effect is the appearance of a quartic interaction of all fermions in the action, leading to a nonlinear Dirac equation involving all

Yoshitsune Kato, Shohei Fujimoto, Masayuki Kozawa, Hiroyuki Fujiwara

The Shockley and Queisser limit, a well-known efficiency limit for a solar cell, is based on unrealistic physical assumptions and its maximum limit is seriously overestimated. To understand the power loss mechanisms of record-efficiency cells, a more rigorous approach is necessary. Here, we have established a new formalism that can accurately predict absolut

Kazuya Shinjo, Kakeru Sasaki, Satoru Hase, Shigetoshi Sota

We demonstrate that supervised machine learning (ML) with entanglement spectrum can give useful information for constructing phase diagram in the half-filled one-dimensional extended Hubbard model. Combining ML with infinite-size density-matrix renormalization group, we confirm that bond-order-wave phase remains stable in the thermodynamic limit.

Saurabh Singh, Abhinav Shrivastava

Batch normalization (BN) has been very effective for deep learning and is widely used. However, when training with small minibatches, models using BN exhibit a significant degradation in performance. In this paper we study this peculiar behavior of BN to gain a better understanding of the problem, and identify a cause. We propose 'EvalNorm' to addres

Snigdh Sabharwal, Jan Willem Dalhuisen

We derive a superpotential for null electromagnetic fields in which the field line structure is in the form of an arbitrary torus knot. These fields are shown to correspond to single copies of a class of anti-self-dual Kerr-Schild spacetimes containing the Sparling-Tod metric. This metric is the pure Weyl double copy of the electromagnetic Hopfion, and we sh

Qingchen Yuan, Liang Fang, Hanlin Fang, Juntao Li

Silicon-based nonlinear metasurfaces were implemented only with third-order nonlinearity due to the crystal centrosymmetry and the efficiencies are considerably low, which hinders their practical applications with low-power lasers. Here, we propose to integrate a two-dimensional GaSe flake onto a silicon metasurface to assist high-efficiency second-order non

Yeping Hu, Alireza Nakhaei, Masayoshi Tomizuka, Kikuo Fujimura

In order to drive safely and efficiently under merging scenarios, autonomous vehicles should be aware of their surroundings and make decisions by interacting with other road participants. Moreover, different strategies should be made when the autonomous vehicle is interacting with drivers having different level of cooperativeness. Whether the vehicle is on t

Loc Hoang Tran, Linh Hoang Tran

Face recognition is the important field in machine learning and pattern recognition research area. It has a lot of applications in military, finance, public security, to name a few. In this paper, the combination of the tensor sparse PCA with the nearest-neighbor method (and with the kernel ridge regression method) will be proposed and applied to the face da

Alvin K. Y. Li, Rico K. L. Lo, Surabhi Sachdev, C. L. Chan

Strong gravitational lensing of gravitational waves can produce duplicate signals separated in time with different amplitudes. We consider the case in which strong lensing produces superthreshold gravitational-wave events and weaker subthreshold signals buried in the noise background. We present the GstLAL-based TargetEd Subthreshold Lensing seArch search me

Ryan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas

We extend conformal prediction methodology beyond the case of exchangeable data. In particular, we show that a weighted version of conformal prediction can be used to compute distribution-free prediction intervals for problems in which the test and training covariate distributions differ, but the likelihood ratio between these two distributions is known---or

Xu Cao, Jian-ping Dai

The newly measurement of production fractions of $P_c$ states by LHCb collaboration have put restriction on their branching ratios of $J/ψp$ decay, thus constraining their photoproduction in $γp\to J/ψp$ reaction. We show the tension between LHCb results and the current experiments in search of $P_c$ photoproduction. We also find that the present information

Jorge Garza-Vargas, Archit Kulkarni

We study the Lanczos algorithm where the initial vector is sampled uniformly from $\mathbb{S}^{n-1}$. Let $A$ be an $n \times n$ Hermitian matrix. We show that when run for few iterations, the output of Lanczos on $A$ is almost deterministic. More precisely, we show that for any $ \varepsilon \in (0, 1)$ there exists $c >0$ depending only on $\varepsilon$ an

Aloni Cohen, Kobbi Nissim

There is a significant conceptual gap between legal and mathematical thinking around data privacy. The effect is uncertainty as to which technical offerings adequately match expectations expressed in legal standards. The uncertainty is exacerbated by a litany of successful privacy attacks, demonstrating that traditional statistical disclosure limitation tech

Qiuyu Zhu, Pengju Zhang, Xin Ye

With the development of convolutional neural networks (CNNs) in recent years, the network structure has become more and more complex and varied, and has achieved very good results in pattern recognition, image classification, object detection and tracking. For CNNs used for image classification, in addition to the network structure, more and more research is

Jeff Hicks

We produce for each tropical hypersurface $V(ϕ)\subset Q=\mathbb{R}^n$ a Lagrangian $L(ϕ)\subset (\mathbb{C}^*)^n$ whose moment map projection is a tropical amoeba of $V(ϕ)$. When these Lagrangians are admissible in the Fukaya-Seidel category, we show that they are unobstructed objects of the Fukaya category, and mirror to sheaves supported on complex hypers

Jiaji Li, Alex Matlock, Yunzhe Li, Qian Chen

We demonstrate a label-free, scan-free {\it intensity} diffraction tomography technique utilizing annular illumination (aIDT) to rapidly characterize large-volume 3D refractive index distributions in vitro. By optimally matching the illumination geometry to the microscope pupil, our technique reduces the data requirement by 60$\times$ to achieve high-speed 1

Huaqing Huang, Feng Liu

We develop a unified view of topological phase transitions (TPTs) in solids by revising the classical band theory with the inclusion of topology. Re-evaluating the band evolution from an "atomic crystal" [a normal insulator (NI)] to a solid crystal, such as a semiconductor, we demonstrate that there exists ubiquitously an intermediate phase of topolo

D. A. Goldston, C. L. Turnage-Butterbaugh

Assuming the Riemann Hypothesis, we improve on previous results by proving there are infinitely many zeros of the Riemann zeta-function whose differences are smaller than 0.50412 times the average spacing. To obtain this result, we generalize a set of weights that were developed by Xiaosheng Wu, who used them to find a positive proportion of large and small

Fangcao Xu, Bruce Desmarais, Donna Peuquet

Information, ideas, and diseases, or more generally, contagions, spread over space and time through individual transmissions via social networks, as well as through external sources. A detailed picture of any diffusion process can be achieved only when both a good network structure and individual diffusion pathways are obtained. The advent of rich social, me

Bo Feng, Xiaodi Li, Kang Zhou

The factorization form of the integrands in the Cachazo-He-Yuan (CHY) formalism makes the generalized Kawai-Lewellen-Tye (KLT) relations manifest, thus amplitudes of one theory can be expanded in terms of the amplitudes of another theory. Although this claim seems a rather natural consequence of the above structure, finding the exact expansion coefficients t

Ashwin Iyengar

We study the rigid generic fiber $\mathcal{X}^\square_{\overline\rho}$ of the framed deformation space of the trivial representation $\overline\rho: G_K \to \text{GL}_n(k)$ where $k$ is a finite field of characteristic $p>0$ and $G_K$ is the absolute Galois group of a finite extension $K/\mathbf{Q}_p$. Under some mild conditions on $K$ we prove that $\mathca

Michael C. Loper

Virtual resolutions are homological representations of finitely generated $\text{Pic}(X)$-graded modules over the Cox ring of a smooth projective toric variety. In this paper, we identify two algebraic conditions that characterize when a chain complex of graded free modules over the Cox ring is a virtual resolution. We then turn our attention to the saturati

Takashi Iida, Kei Kamada, Masao Yoshino, Kyoung Jin Kim

A high light yield calcium iodide (CaI2) scintillator is being developed for an astroparticle physics experiments. This paper reports scintillation performance of calcium iodide (CaI2) crystal. Large light emission of 2.7 times that of NaI(Tl) and an emission wavelength in good agreement with the sensitive wavelength of the photomultiplier were obtained. A s

Hamed Alqahtani, Manolya Kavakli-Thorne, Charles Z. Liu

Person re-identification is a basic subject in the field of computer vision. The traditional methods have several limitations in solving the problems of person illumination like occlusion, pose variation and feature variation under complex background. Fortunately, deep learning paradigm opens new ways of the person re-identification research and becomes a ho

Francois P. Hamon, Martin Schreiber, Michael L. Minion

The modeling of atmospheric processes in the context of weather and climate simulations is an important and computationally expensive challenge. The temporal integration of the underlying PDEs requires a very large number of time steps, even when the terms accounting for the propagation of fast atmospheric waves are treated implicitly. Therefore, the use of

Rosa L. Becerra, Simone Dichiara, Alan M. Watson, Eleonora Troja

We present observations of the possible short GRB 180418A in $γ$-rays, X-rays, and in the optical. Early optical photometry with the TAROT and RATIR instruments show a bright peak ($\approx$ 14.2 AB mag) between $T+28$ and $T+90$ seconds that we interpret as the signature of a reversal shock. Later observations can be modeled by a standard forward shock mode

Muhammad U. Javed, Zaid Bin Tariq, Usama Muneeb, Ijaz Haider Naqvi

Energy utilization is a key attribute for energy constrained wireless sensor networks (WSN) that directly impacts the life time of the network. LEACH (and its variants) are considered to be the most common energy efficient routing protocols for WSN. In this paper, we propose an optimized modification of LEACH that makes use of multi-hop communication, dynami

Ján Dolinský, Mária Starovská, Robert Tóth

The Tangent Works team participated in GEFCom 2017 to test its automatic model building strategy for time series known as Tangent Information Modeller (TIM). Model building using TIM combined with historical temperature shuffling resulted in winning the competition. This strategy involved one remaining degree of freedom, a decision on using a trend variable.

Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong

In this paper, we consider advancing web-scale knowledge extraction and alignment by integrating OpenIE extractions in the form of (subject, predicate, object) triples with Knowledge Bases (KB). Traditional techniques from universal schema and from schema mapping fall in two extremes: either they perform instance-level inference relying on embedding for (sub

Jinyin Chen, Yangyang Wu, Lu Fan, Xiang Lin

Recommender systems are becoming more and more important in our daily lives. However, traditional recommendation methods are challenged by data sparsity and efficiency, as the numbers of users, items, and interactions between the two in many real-world applications increase fast. In this work, we propose a novel clustering recommender system based on node2ve

Hannes Diener, Matthew Hendtlass

We prove some constructive results that on first and maybe even on second glance seem impossible.

Pingyu Jiang, Pulin Li

Manufacturing industry is heading towards socialization, interconnection, and platformization. Motivated by the infiltration of sharing economy usage in manufacturing, this paper addresses a new factory model -- shared factory -- and provides a theoretical architecture and some actual cases for manufacturing sharing. Concepts related to three kinds of shared

Gouranga C Nayak

Recently we have reported the correct formulation of the hadron formation from the quarks and gluons by using the lattice QCD method at the zero temperature. Similarly we have also reported the correct formulation of the hadron formation from the thermalized quark-gluon plasma by using the lattice QCD method at the finite temperature. In this paper we extend

Malte Schilling

An internal model of the own body can be assumed a fundamental and evolutionary-early representation as it is present throughout the animal kingdom. Such functional models are, on the one hand, required in motor control, for example solving the inverse kinematic or dynamic task in goal-directed movements or a forward task in ballistic movements. On the other