January 2019 arXiv papers — page 3

Minne Li, Zhiwei, Qin, Yan Jiao

A fundamental question in any peer-to-peer ridesharing system is how to, both effectively and efficiently, dispatch user's ride requests to the right driver in real time. Traditional rule-based solutions usually work on a simplified problem setting, which requires a sophisticated hand-crafted weight design for either centralized authority control or decentra

Jörg P. Bachmann

A common approach to implementing similarity search applications is the usage of distance functions, where small distances indicate high similarity. In the case of metric distance functions, metric index structures can be used to accelerate nearest neighbor queries. On the other hand, many applications ask for approximate subsequences or subsets, e.g. search

Amir Leshem, Uri Erez

It is shown that a receiver equipped with two antennas may null an arbitrary large number of spatial directions to any desired accuracy, while maintaining the interference-free signal-to-noise ratio, by judiciously adjusting the distance between the antenna elements. The main theoretical result builds on ergodic theory. The practicality of the scheme in mode

Chaochao Li, Pei Lv, Dinesh Manocha, Hua Wang

Antagonistic crowd behaviors are often observed in cases of serious conflict. Antagonistic emotions, which is the typical psychological state of agents in different roles (i.e. cops, activists, and civilians) in crowd violent scenes, and the way they spread through contagion in a crowd are important causes of crowd antagonistic behaviors. Moreover, games, wh

Antonio Martínez, A. L. Martínez Triviño

Calabi observed that there is a natural correspondence between the solutions of the minimal surface equation in $\mathbb{R}^3$ with those of the maximal spacelike surface equation in $\mathbb{L}^3$. We are going to show how this correspondence can be extended to the family of $\varphi $-minimal graphs in $\mathbb{R}^3 $ when the function $\varphi$ is invaria

Iordan Ganev, David Jordan, Pavel Safronov

We prove that quantized multiplicative quiver varieties and quantum character varieties define sheaves of Azumaya algebras over the corresponding classical moduli spaces, and we prove that the Azumaya locus of the Kauffman bracket skein algebras contains the smooth locus, proving a strong form of the Unicity Conjecture of Bonahon and Wong. The proofs exploit

Massimiliano Polito

The work presents two algorithms of manipulation and comparison between strings whose purpose is the orthographic recognition of the apostrophe and of the compound expressions. The theory supporting general reasoning refers to the basic concept of EditDistance, the improvements that ensure the achievement of the objective are achieved with the aid of tools b

Wei-Feng Zhuang, Yue-Xin Huang, Guang-Can Guo, Ming Gong

We demonstrate that the two degenerate energy levels in spin-orbit coupled trapped Bose gases, coupled by a quenched Zeeman field, can be used for angular momentum Josephson effect. In a static quenched field, we can realize a Josephson oscillation with period ranging from millisecond to hundreds of milliseconds. Moreover, by a driven Zeeman field, we realiz

Yiying Li, Yongxin Yang, Wei Zhou, Timothy M. Hospedales

The well known domain shift issue causes model performance to degrade when deployed to a new target domain with different statistics to training. Domain adaptation techniques alleviate this, but need some instances from the target domain to drive adaptation. Domain generalisation is the recently topical problem of learning a model that generalises to unseen

Jason W. Wei, Jerry W. Wei, Christopher R. Jackson, Bing Ren

Celiac disease prevalence and diagnosis have increased substantially in recent years. The current gold standard for celiac disease confirmation is visual examination of duodenal mucosal biopsies. An accurate computer-aided biopsy analysis system using deep learning can help pathologists diagnose celiac disease more efficiently. In this study, we trained a de

Ming Lu, Weiqiang Wang

A quantum symmetric pair consists of a quantum group $\mathbf U$ and its coideal subalgebra ${\mathbf U}^{\imath}_{\boldsymbol{\varsigma}}$ with parameters $\boldsymbol{\varsigma}$ (called an $\imath$quantum group). We initiate a Hall algebra approach for the categorification of $\imath$quantum groups. A universal $\imath$quantum group $\widetilde{\mathbf U}

John D. Carter, Morgan Rozman

Recently, the Whitham and capillary-Whitham equations were shown to accurately model the evolution of surface waves on shallow water. In order to gain a deeper understanding of these equations, we compute periodic, traveling-wave solutions to both and study their stability. We present plots of a representative sampling of solutions for a range of wavelengths

Hiroyuki Tajima, Yuriy Yerin, Andrea Perali, Pierbiagio Pieri

We study the superfluid critical temperature in a two-band attractive Fermi system with strong pairing fluctuations associated with both interband and intraband couplings. We focus specifically on a configuration where the intraband coupling is varied from weak to strong in a shallow band coupled to a weakly-interacting deeper band. The whole crossover from

Alexei Bazavov, Simon Catterall, Raghav G. Jha, Judah Unmuth-Yockey

We study the $SU(2)$ gauge-Higgs model in two Euclidean dimensions using the tensor renormalization group (TRG) approach. We derive a tensor formulation for this model in the unitary gauge and compare the expectation values of different observables between TRG and Monte Carlo simulations finding excellent agreement between the two methods. In practice we fin

Y. Osorio, K. Lind, P. S. Barklem, C. Allende Prieto

Context. Departures from local thermodynamic equilibrium (LTE) distort the calcium abundance derived from stellar spectra in various ways, depending on the lines used and the stellar atmospheric parameters. The collection of atomic data adopted in non-LTE (NLTE) calculations must be sufficiently complete and accurate. Aims. We derive NLTE abundances from hig

Jorge Castillejos, Samuel Evington

We prove that Z-stable, simple, separable, nuclear, non-unital C*-algebras have nuclear dimension at most 1. This completes the equivalence between finite nuclear dimension and Z-stability for simple, separable, nuclear, non-elementary C*-algebras.

William Romine, Tanvi Banerjee, Garrett Goodman

We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep on six participants to test the efficacy of EDA data for sleep monitoring. We used factor analysis to find latent factors in the EDA data, and causal model search to find the most probable graphical model accounting for self-reported sleep efficiency (SE), sleep

Jérôme Pétri

Since the era of the Fermi/LAT and atmospheric Cerenkov telescopes, pulsars are known to emit high and very high-energy photons, in the MeV-GeV range and sometimes up to TeV. To date, it is still unclear where and how these photons are produced. Nevertheless gamma-ray photons require particle acceleration to ultra-relativistic speeds. In this paper, we compu

Shing-Chi Leung, Ken'ichi Nomoto, Tomoharu Suzuki

Stars of $\sim$ 8 - 10 $M_{\odot}$ on the main-sequence form strongly electron-degenerate O+Ne+Mg core and become super-AGB stars. If such an O+Ne+Mg core grows to 1.38 $M_\odot$, electron captures on $^{20}$Ne$(e,\nu_e)^{20}$F$(e,\nu_e)^{20}$O take place and ignite O-Ne deflagration around the center. In this paper, we perform two-dimensional hydrodynamics

Vasilii Semkin, Aleksei Ponomarenko-Timofeev, Aki Karttunen, Olga Galinina

In this work, we present the results of a wideband measurement campaign at 60 GHz conducted inside a Linkker electric city bus. Targeting prospective millimeter-wave (mmWave) public transportation wearable scenarios, we mimic a typical deployment of mobile high-end consumer devices in a dense environment. Specifically, our intra-vehicle deployment includes o

Lucas Lehnert, Michael L. Littman

A key question in reinforcement learning is how an intelligent agent can generalize knowledge across different inputs. By generalizing across different inputs, information learned for one input can be immediately reused for improving predictions for another input. Reusing information allows an agent to compute an optimal decision-making strategy using less d

William J. Wilkinson, Michael Riis Andersen, Joshua D. Reiss, Dan Stowell

A typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis. We show how time-frequency analysis and nonnegative matrix factorisation can be jointly formulated as a spectral mixture Gaussian process model with nonstationary prior

Dávid Csercsik, Franz Hubert, Balázs R. Sziklai, László Á. Kóczy

Existing cooperative game theoretic studies of bargaining power in gas pipeline systems are based on the so called characteristic function form (CFF). This approach is potentially misleading if some pipelines fall under regulated third party access (TPA). TPA, which is by now the norm in the EU, obliges the owner of a pipeline to transport gas for others, pr

Mohammad Hasan, Bhabani Prasad Mandal

We calculate the time taken by a wave packet to travel through a classically forbidden locally periodic rectangular potential in space fractional quantum mechanics (SFQM). We obtain the close form expression of tunneling time from such a potential by stationary phase method. We show that tunneling time depends upon the width $b$ of the single barrier and sep

Javier Gil Vidal, Dirk Oliver Theis

The topic area of this paper parameterized quantum circuits (quantum neural networks) which are trained to estimate a given function, specifically the type of circuits proposed by Mitarai et al. (Phys. Rev. A, 2018). The input is encoded into amplitudes of states of qubits. The no-cloning principle of quantum mechanics suggests that there is an advantage in

John Mangeri, S. Pamir Alpay, Serge Nakhmanson, Olle G. Heinonen

Using a free-energy based computational model, we have investigated the response of a system comprising two interacting ferroelectric nanospheres, embedded in a dielectric medium, to a static external electric field. The system response is hysteretic and tunable by changing the inter-particle distance and the orientation of the applied field, which strongly

Carlos E. Kenig, Gustavo Ponce, Luis Vega

We prove that if $u_1,\,u_2$ are solutions of the Benjamin-Ono equation defined in $ (x,t)\in\R \times [0,T]$ which agree in an open set $\Omega\subset \R \times [0,T]$, then $u_1\equiv u_2$. We extend this uniqueness result to a general class of equations of Benjamin-Ono type in both the initial value problem and the initial periodic boundary value problem.

Thomas Breuer, Gerhard Hiss, Frank Lübeck, Klaus Lux

Using computational methods, we complete the determination of the $3$-modular character table of the Chevalley group $F_4(2)$ and its covering group.

Jiangshan Lan, Chandan Mondal, Shaoyang Jia, Xingbo Zhao

We obtain the pion and the kaon parton distribution functions from the eigenstates of a light front effective Hamiltonian in the constituent quark-antiquark representation suitable for low-momentum scale applications. By taking these scales as the only free parameters, the valence quark distribution functions of the pion, after QCD evolution, are consistent

Venkata Subrahmanyan Govindarajan, Benjamin Van Durme, Aaron Steven White

We present a novel semantic framework for modeling linguistic expressions of generalization---generic, habitual, and episodic statements---as combinations of simple, real-valued referential properties of predicates and their arguments. We use this framework to construct a dataset covering the entirety of the Universal Dependencies English Web Treebank. We us

Xavier Bonnetain

Hidden shift problems are relevant to assess the quantum security of various cryptographic constructs. Multiple quantum subexponential time algorithms have been proposed. In this paper, we propose some improvements on a polynomial quantum memory algorithm proposed by Childs, Jao and Soukharev in 2010. We use subset-sum algorithms to significantly reduce its

Nicolas Mauron, Kamo S. Gigoyan, Karen K. Gigoyan, Luc P. A. Maurin

As part of our ongoing study of the evolved giants in the galactic halo, we consider the sample of 1286 long-period variables (LPVs) in the southern hemisphere provided by the Catalina Sky Survey experiment. These LPVs have periods P larger than 80 days and amplitudes over 0.2 mag. First, by using the Hamburg-ESO spectral survey, we aim to determine the spec

Stephen I. Thomson, Geoffrey K. Vallis

The climate and circulation of a terrestrial planet are governed by, among other things, the distance to its host star, its size, rotation rate, obliquity, atmospheric composition and gravity. Here we explore the effects of the last of these, the Newtonian gravitational acceleration, on its atmosphere and climate. We first demonstrate that if the atmosphere

Keisuke Isogai, Taichi Kato, Berto Monard, Franz-Josef Hambsch

In 2015 and 2017, the AM CVn candidate NSV 1440 showed superoutbursts having the characteristic features of WZ Sge-type dwarf novae (DNe). By analogy with hydrogen-rich cataclysmic variables (CVs), we can interpret these outbursts as `double superoutbursts' which are composed of the first superoutburst with early superhumps and the second superoutburst with

Yuan Da Liao, Zi Yang Meng, Xiao Yan Xu

An extended Hubbard model on a honeycomb lattice with two orbitals per site at charge neutrality is investigated with unbiased large-scale quantum Monte Carlo simulations. The Fermi velocity of the Dirac fermions is renormalized as the cluster charge interaction increases, until a mass term emerges and a quantum phase transition from Dirac semi-metal to vale

Xiangyu Meng, Christos G. Cassandras

This paper develops an optimal acceleration/speed profile for a single autonomous vehicle crossing multiple signalized intersections without stopping in free flow mode. The design objective is to produce both time and energy efficient acceleration profiles of autonomous vehicles based on vehicle to infrastructure communication. Our design approach differs fr

Zhuangkun Wei, Weisi Guo, Bin Li, Jerome Charmet

In emerging Internet-of-Nano-Thing (IoNT), information will be embedded and conveyed in the form of molecules through complex and diffusive medias. One main challenge lies in the long-tail nature of the channel response causing inter-symbol-interference (ISI), which deteriorates the detection performance. If the channel is unknown, we cannot easily achieve t

Ievgen I. Arkhipov, Adam Miranowicz, Omar Di Stefano, Roberto Stassi

We use a non-Lindbladian master equation of the Scully-Lamb laser model for the analysis of light propagation in a parity-time symmetric photonic system composed of coupled active and passive whispering-gallery microresonators. Performing the semiclassical approximation, we obtain a set of two nonlinear coupled differential equations describing the time evol

Shay Perera, Ayellet Tal, Lihi Zelnik-Manor

This paper deals with the prediction of the memorability of a given image. We start by proposing an algorithm that reaches human-level performance on the LaMem dataset - the only large scale benchmark for memorability prediction. The suggested algorithm is based on three observations we make regarding convolutional neural networks (CNNs) that affect memorabi

Francisco Javier Garcia-Gomez, Vahid Aref

In the presence of additive Gaussian noise, the statistics of the nonlinear Fourier transform (NFT) of a pulse are not yet completely known in closed form. In this paper, we propose a novel approach to study this problem. Our contributions are twofold: first, we extend the existing Fourier Collocation (FC) method to compute the whole discrete spectrum (eigen

Zhuangkun Wei, Bin Li, Weisi Guo, Wenxiu Hu

Extracting and detecting spike activities from the fluorescence observations is an important step in understanding how neuron systems work. The main challenge lies in that the combination of the ambient noise with dynamic baseline fluctuation, often contaminates the observations, thereby deteriorating the reliability of spike detection. This may be even wors

Michalis Michaelides, Jane Hillston, Guido Sanguinetti

Fluid approximations have seen great success in approximating the macro-scale behaviour of Markov systems with a large number of discrete states. However, these methods rely on the continuous-time Markov chain (CTMC) having a particular population structure which suggests a natural continuous state-space endowed with a dynamics for the approximating process.

Johannes Zabl, Nicolas F. Bouché, Ilane Schroetter, Martin Wendt

We use the MusE GAs FLOw and Wind (MEGAFLOW) survey to study the kinematics of extended disk-like structures of cold gas around $z\approx1$ star-forming galaxies. The combination of VLT/MUSE and VLT/UVES observations allows us to connect the kinematics of the gas measured through MgII quasar absorption spectroscopy to the kinematics and orientation of the as

Yan Peng

We study scalar condensation in the background of asymptotically flat spherically symmetric regular Dirichlet stars. We assume that the scalar field decreases as the star surface is approached. Under these circumstances, we prove a no hair theorem for neutral regular compact stars. We also extend the discussion to charged regular compact stars and find an up

Alexios Liakos, Alceste Bonanos, Emmanouil Xilouris, Ioannis Bellas-Velidis

NELIOTA (NEO Lunar Impacts and Optical TrAnsients) is an ESA-funded lunar monitoring project, which aims to determine the size-frequency distribution of small Near-Earth Objects (NEOs) via detection of impact flashes on the surface of the Moon. A prime focus, high-speed, twin-camera system providing simultaneous observations in two photometric bands at a rat

Merid Tufa, Fesseha Kassahun

We have considered the interaction of the subharmonic light modes with a three-level atom. We have found that the effect of this interaction is to decrease the quadrature squeezing and the mean photon number of the two-mode cavity light.

Giulio Chiribella, Adán Cabello, Matthias Kleinmann, Markus P. Müller

We address the problem of reconstructing quantum theory from the perspective of an agent who makes bets about the outcomes of possible experiments. We build a general Bayesian framework that can be used to organize the agent's beliefs and update them when new information becomes available. Our framework includes as special cases classical and quantum probabi

Gabriel Radanne, Jérôme Vouillon, Vincent Balat

Tierless Web programming languages allow programmers to combine client-side and server-side programming in a single program. Programmers can then define components with both client and server parts and get flexible, efficient and typesafe client-server communications. However, the expressive client-server features found in most tierless languages are not nec

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

In the solar wind an equipartition of kinetic energy densities can be easily established between thermal and suprathermal electrons and the instability conditions are markedly altered by the interplay of these two populations. The new thresholds derived here for the periodic branch of firehose instability shape the limits of temperature anisotropy reported b

Fatemeh Hajiloo, Fabian Hassler, Janine Splettstoesser

We study the heat conductance of hybrid superconducting junctions. Our analysis involves single-channel junctions with arbitrary transmission as well as diffusive connectors and shows the influence of the superconducting gaps and phases of the contacts on the heat conductance. If the junction is diffusive, these effects are completely quenched on average, ho

Luca Studer

The presented splitting lemma extends the techniques of Gromov and Forstneri\v{c} to glue local sections of a given analytic sheaf, a key step in the proof of all Oka principles. The novelty on which the proof depends is a lifting lemma for transition maps of coherent sheaves, which yields a reduction of the proof to the work of Forstneri\v{c}. As applicatio

Kai Liu, Zhong-Yi Lu, Tao Xiang

An intact CuO$_2$ plane is widely believed to be a prerequisite for the high-$T_c$ superconductivity in cuprate superconductors. However, an exception may exist in the superconducting Ba$_2$CuO$_{3+\delta}$ materials where CuO chains play a more important role. From first-principles density functional theory calculations, we have studied the electronic and m

J. -M. Delouis, L. Pagano, S. Mottet, J. -L. Puget

This paper describes an improved mapmaking approach with respect to the one used for the Planck High Frequency Instrument 2018 Legacy release. The algorithm SRoll2 better corrects the known instrumental effects that still affected mostly the polarized large-angular-scale data by distorting the signal, and/or leaving residuals observable in null tests. The ma

Michael W. Coughlin, Tomas Ahumada, S. Bradley Cenko, Virginia Cunningham

There is significant interest in the models for production of short gamma-ray bursts. Until now, the number of known short gamma-ray bursts with multi-wavelength afterglows has been small. While the {\it Fermi} Gamma-Ray Burst Monitor detects many gamma-ray bursts relative to the Neil Gehrels {\it Swift} Observatory, the large localization regions makes the

Dimche Kostadinov, Behrooz Razdehi, Slava Voloshynovskiy

In this paper, we introduce a novel concept for learning of the parameters in a neural network. Our idea is grounded on modeling a learning problem that addresses a trade-off between (i) satisfying local objectives at each node and (ii) achieving desired data propagation through the network under (iii) local propagation constraints. We consider two types of

Andrea Richaud, Alessandro Zenesini, Vittorio Penna

We derive the complete mixing-demixing phase-diagram relevant to a bosonic binary mixture confined in a ring trimer and modeled within the Bose-Hubbard picture. The mixing properties of the two quantum fluids, which are shown to be strongly affected by the fragmented character of the confining potential, are evaluated by means of a specific indicator importe

P. Kroll

Hard exclusive electroproduction of kaons as well as the kaon-induced exclusive Drell-Yan process are investigated within the handbag approach which is based on factorization in hard subprocesses and soft generalized parton distributions (GPDs). The kaon-hyperon transition GPDs occurring here, are related to the proton GPDs by flavor symmetry. The latter one

V. Straižys, R. P. Boyle, K. Milašius, K. Černis

The open cluster IC 4996 in Cygnus and its vicinity are investigated by applying a two-dimensional photometric classification of stars measured in the Vilnius seven-color photometric system. Cluster members are identified by applying distances based on the Gaia DR2 parallaxes and the point vector diagram of the Gaia DR2 proper motions. For some B-type stars,

Balázs Gerencsér, László Gerencsér

The problems discussed in this paper are motivated by general ratio consensus algorithms, introduced by Kempe, Dobra, and Gehrke (2003) in a simple form as the push-sum algorithm, later extended by B\'en\'ezit et al. (2010) under the name weighted gossip algorithm. We consider a communication protocol described by a strictly stationary, ergodic, sequentially

Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor, Tomas Kocisky

We define general linguistic intelligence as the ability to reuse previously acquired knowledge about a language's lexicon, syntax, semantics, and pragmatic conventions to adapt to new tasks quickly. Using this definition, we analyze state-of-the-art natural language understanding models and conduct an extensive empirical investigation to evaluate them again

Giacomo Rocco, Gianmaria Silvello

In this paper, we present an InfoVis tool based on Sankey diagrams for the exploration of large combinatorial combinations of IR components - the Grid of Points (GoP). The goal of this tool is to ease the comprehension of the behavior of single IR components within fully functioning off-the-shelf IR systems without recurring to complex statistical tools.

Yang Liu, Haizhao Yang

This paper introduces a hierarchical interpolative decomposition butterfly-LU factorization (H-IDBF-LU) preconditioner for solving two-dimensional electric-field integral equations (EFIEs) in electromagnetic scattering problems of perfect electrically conducting objects with open surfaces. H-IDBF-LU leverages the interpolative decomposition butterfly factori

Jannis Teunissen, Rony Keppens

We present an efficient MPI-parallel geometric multigrid library for quadtree (2D) or octree (3D) grids with adaptive refinement. Cartesian 2D/3D and cylindrical 2D geometries are supported, with second-order discretizations for the elliptic operators. Periodic, Dirichlet, and Neumann boundary conditions can be handled, as well as free-space boundary conditi

J. C. Ye, Y. Li, Q. Chen, S. G. Chen

Marcella in 2002 published a "quantum-mechanical" treatment of the famous single- and double-slit interference experiment in classical wave optics by a simple assumption that quantum mechanical wave function is a constant anywhere within a slit. Rothman and Boughn in 2011 commented that Marcella introduced no quantum physics into the problem other than\ a sy

Jue Jiang, Yu-Chi Hu, Neelam Tyagi, Pengpeng Zhang

Lack of large expert annotated MR datasets makes training deep learning models difficult. Therefore, a cross-modality (MR-CT) deep learning segmentation approach that augments training data using pseudo MR images produced by transforming expert-segmented CT images was developed. Eighty-One T2-weighted MRI scans from 28 patients with non-small cell lung cance

Gihan Mendis, Jin Wei, Arjuna Madanayakey, Soumyajit Mandalz

This paper presents a spectral attention-driven reinforcement learning based intelligent method for effective and efficient detection of important signals in a wideband spectrum. In the work presented in this paper, it is assumed that the modulation technique used is available as a priori knowledge of the targeted important signal. The proposed spectral atte

S. Sedigheh Hashemi, Mahdi Kord Zangeneh, Mir Faizal

We study quasi-normal modes for a higher dimensional black hole with Lifshitz scaling, as these quasi-normal modes can be used to test Lifshitz models with large extra dimensions. Furthermore, as the effective Planck scale is brought down in many models with large extra dimensions, we study these quasi-normal modes for a UV completion action. Thus, we analyz

Tanuj Hasija, Christian Lameiro, Timothy Marrinan, Peter J. Schreier

Detecting the components common or correlated across multiple data sets is challenging due to a large number of possible correlation structures among the components. Even more challenging is to determine the precise structure of these correlations. Traditional work has focused on determining only the model order, i.e., the dimension of the correlated subspac

Ying Zhou, Lie-Wen Chen, Zhen Zhang

While the equation of state (EOS) of symmetric nuclear matter (SNM) at suprasaturation densities has been relatively well constrained from heavy-ion collisions, the EOS of high-density neutron-rich matter is still largely uncertain due to the poorly known high-density behavior of the symmetry energy. Using the constraints on the EOS of SNM at suprasaturation

Andreas Deuchert, Robert Seiringer

We consider a dilute, homogeneous Bose gas at positive temperature. The system is investigated in the Gross-Pitaevskii (GP) limit, where the scattering length $a$ is so small that the interaction energy is of the same order of magnitude as the spectral gap of the Laplacian, and for temperatures that are comparable to the critical temperature of the ideal gas

Li Xing, Xuekui Zhang, Igor Burstyn, Paul Gustafson

The shape of the relationship between a continuous exposure variable and a binary disease variable is often central to epidemiologic investigations. This paper investigates a number of issues surrounding inference and the shape of the relationship. Presuming that the relationship can be expressed in terms of regression coefficients and a shape parameter, we

Siddhartha Karmakar, Subhendu Rakshit

In the wake of new scalar searches at LHC in various channels, it is interesting to investigate the sacrosanctity of the constraints on the masses and couplings of the heavier scalars in a two-Higgs-doublet model (2HDM). We consider the effects of new physics beyond a 2HDM encoded in terms of bosonic dim-6 operators. Although these constraints are mostly imm

Q. Chen, Q. H. Liu

The phonon number fluctuations in the Debye model of solid are calculated and are demonstrated to be proportional to the temperature cubed at low temperature, similar to the celebrated Debye's law of the heat capacity. For a fixed number of atoms, the relative fluctuations approach to infinity as the temperatture decreases to zero, and the proper definition

Thomas Zenkel, Joern Wuebker, John DeNero

Multi-layer models with multiple attention heads per layer provide superior translation quality compared to simpler and shallower models, but determining what source context is most relevant to each target word is more challenging as a result. Therefore, deriving high-accuracy word alignments from the activations of a state-of-the-art neural machine translat

Elena Botoeva, Carsten Lutz, Vladislav Ryzhikov, Frank Wolter

We investigate the problem whether two ALC ontologies are indistinguishable (or inseparable) by means of queries in a given signature, which is fundamental for ontology engineering tasks such as ontology versioning, modularisation, update, and forgetting. We consider both knowledge base (KB) and TBox inseparability. For KBs, we give model-theoretic criteria

Evgeniy Martyushev, Bo Li

We propose two minimal solutions to the problem of relative pose estimation of (i) a calibrated camera from four points in two views and (ii) a calibrated generalized camera from five points in two views. In both cases, the relative rotation angle between the views is assumed to be known. In practice, such angle can be derived from the readings of a 3d gyros

Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu

We introduce a framework for Continual Learning (CL) based on Bayesian inference over the function space rather than the parameters of a deep neural network. This method, referred to as functional regularisation for Continual Learning, avoids forgetting a previous task by constructing and memorising an approximate posterior belief over the underlying task-sp

Caterina Schiavoni, Franz Palm, Stephan Smeekes, Jan van den Brakel

In this paper we consider estimation of unobserved components in state space models using a dynamic factor approach to incorporate auxiliary information from high-dimensional data sources. We apply the methodology to unemployment estimation as done by Statistics Netherlands, who uses a multivariate state space model to produce monthly figures for the unemplo

Arthur Bik, Jan Draisma, Alessandro Oneto, Emanuele Ventura

We introduce the monic rank of a vector relative to an affine-hyperplane section of an irreducible Zariski-closed affine cone $X$. We show that the monic rank is finite and greater than or equal to the usual $X$-rank. We describe an algorithmic technique based on classical invariant theory to determine, in concrete situations, the maximal monic rank. Using t

Myungshin Im, Changsu Choi, Sungyong Hwang, Gu Lim

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the

Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues

Inverse problems arise in a number of domains such as medical imaging, remote sensing, and many more, relying on the use of advanced signal and image processing approaches -- such as sparsity-driven techniques -- to determine their solution. This paper instead studies the use of deep learning approaches to approximate the solution of inverse problems. In par

Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama

Ordinal regression is aimed at predicting an ordinal class label. In this paper, we consider its semi-supervised formulation, in which we have unlabeled data along with ordinal-labeled data to train an ordinal regressor. There are several metrics to evaluate the performance of ordinal regression, such as the mean absolute error, mean zero-one error, and mean

Gideon P. Müller, Markus Hoffmann, Constantin Disselkamp, Daniel Schürhoff

The \textit{Spirit} framework is designed for atomic scale spin simulations of magnetic systems of arbitrary geometry and magnetic structure, providing a graphical user interface with powerful visualizations and an easy to use scripting interface. An extended Heisenberg type spin-lattice Hamiltonian including competing exchange interactions between neighbors

J. Burtscheidt, M. Claus, S. Dempe

We consider bilevel linear problems, where some parameters are stochastic, and the leader has to decide in a here-and-now fashion, while the follower has complete information. In this setting, the leader's outcome can be modeled by a random variable, which we evaluate based on some law-invariant convex risk measure. A qualitative stability result under pertu

Birgit Jacob, Hafida Laasri

We study a class of non-autonomous boundary control and observation linear systems that are governed by non-autonomous multiplicative perturbations. This class is motivated by different fundamental partial differential equations, such as controlled wave equations and Timoshenko beams. Our main results give sufficient condition for well-posedness, existence a

J. A. Krieger, Y. Ou, M. Caputo, A. Chikina

We probe the local magnetic properties of interfaces between the insulating ferromagnet EuS and the topological insulator Bi$_2$Se$_3$ using low energy muon spin rotation (LE-$\mu$SR). We compare these to the interface between EuS and the topologically trivial metal, titanium. Below the magnetic transition of EuS, we detect strong local magnetic fields which

Alfonso Allen-Perkins, Alfredo Blanco Serrano, Thiago Albuquerque de Assis, Juan Manuel Pastor

A Markov chain (MC) formalism is used to investigate the mean-square displacement (MSD) of a random walker on Newman-Watts (NW) networks. It leads to a precise analysis of the conditions for the emergence of anomalous sub- or super-diffusive regimes in such random media. Whereas results provided by most numerical approaches used so far base their results on

M. Ahmad Mirshafeazadeh, B. Bidabad

We first present the natural definitions of the horizontal differential, the divergence (as an adjoint operator), and a $p$-harmonic form on a Finsler manifold. Next, we prove a Hodge-type theorem for a Finsler manifold in the sense that a horizontal $p$-form is harmonic if and only if the horizontal Laplacian vanishes. This viewpoint provides a new appropri

Ya Li, Xinyu Liu, Dan Liu, Xueqiang Zhang

Recent years has witnessed dramatic progress of neural machine translation (NMT), however, the method of manually guiding the translation procedure remains to be better explored. Previous works proposed to handle such problem through lexcially-constrained beam search in the decoding phase. Unfortunately, these lexically-constrained beam search methods suffer

Christian Elsholtz, Clemens Heuberger, Daniel Krenn

It is known that the following five counting problems lead to the same integer sequence~$f_t(n)$: the number of nonequivalent compact Huffman codes of length~$n$ over an alphabet of $t$ letters, the number of `nonequivalent' canonical rooted $t$-ary trees (level-greedy trees) with $n$~leaves, the number of `proper' words, the number of bounded degree sequenc

A. S. Barabash

An overview of modern experiments on the search for neutrinoless double decay is presented. The obtained limits on the effective mass of the Majorana neutrino $\langle m_{\nu} \rangle$ are discussed taking into account the uncertainties in the value of the nuclear matrix elements (NMEs) and the value of the axial-vector constant $g_A$. Predictions for the va

Fabian Isensee, Marianne Schell, Irada Tursunova, Gianluca Brugnara

Brain extraction is a critical preprocessing step in the analysis of MRI neuroimaging studies and influences the accuracy of downstream analyses. The majority of brain extraction algorithms are, however, optimized for processing healthy brains and thus frequently fail in the presence of pathologically altered brain or when applied to heterogeneous MRI datase

Zafar Ahmed, Sachin Kumar, Dona Ghosh, Tarit Goswami

Historically, most of the quantum mechanical results have originated in one dimensional model potentials. However, Von-Neumann's Bound states in the Continuum (BIC) originated in specially constructed, three dimensional, oscillatory, central potentials. One dimensional version of BIC has long been attempted, where only quasi-exactly-solvable models have succ

János Barát

Thomassen formulated the following conjecture: Every $3$-connected cubic graph has a red-blue vertex coloring such that the blue subgraph has maximum degree $1$ (that is, it consists of a matching and some isolated vertices) and the red subgraph has minimum degree at least $1$ and contains no $3$-edge path. We prove the conjecture for Generalized Petersen gr

Takayuki Myo, Hiroki Takemoto, Mengjiao Lyu, Niu Wan

We propose a new variational method for describing nuclear matter from nucleon-nucleon interaction. We use the unitary correlation operator method (UCOM) for central correlation to treat the short-range repulsion and further include the two-particle two-hole (2p2h) excitations of nucleon pair involving a large relative momentum, which is called 'high-momentu

Thomas Bauer, Peter Banzer, Frédéric Bouchard, Sergej Orlov

Electromagnetic plane waves, solutions to Maxwell's equations, are said to be `transverse' in vacuum. Namely, the waves' oscillatory electric and magnetic fields are confined within a plane transverse to the waves' propagation direction. Under tight-focusing conditions however, the field can exhibit longitudinal electric or magnetic components, transverse sp

Stephen Muirhead

We consider the number of critical points of a stationary planar Gaussian field, restricted to a large domain, whose heights lie in a certain interval. Asymptotics for the mean of this quantity are simple to establish via the Kac-Rice formula, and recently Estrade and Fournier proved a second moment bound that is optimal in the case that the height interval

Y. C. Daza C., M. F. Laguna, J. A. Monjeau, G. Abramson

We study a mathematical model inspired by a common scenario in northern Patagonia consisting of humans and their livestock living together with native wildlife. The main production system in this area is sheep farming, which due to wrong historical management has led to desertification of the habitat, with impact on both native wildlife and livestock. Partic

Gaetan J. D. R. Hains, Arvid Jakobsson, Youry Khmelevsky

Deep Learning (DL) techniques are now widespread and being integrated into many important systems. Their classification and recognition abilities ensure their relevance for multiple application domains. As machine-learning that relies on training instead of algorithm programming, they offer a high degree of productivity. But they can be vulnerable to attacks

Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews

Text attribute transfer aims to automatically rewrite sentences such that they possess certain linguistic attributes, while simultaneously preserving their semantic content. This task remains challenging due to a lack of supervised parallel data. Existing approaches try to explicitly disentangle content and attribute information, but this is difficult and of