arXiv papers from October 2017

Miquel Martí, Atsuto Maki

We propose an approach to Multitask Learning (MTL) to make deep learning models faster and lighter for applications in which multiple tasks need to be solved simultaneously, which is particularly useful in embedded, real-time systems. We develop a multitask model for both Object Detection and Semantic Segmentation and analyze the challenges that appear durin

Joshua Hinman, Borys Kuca, Alexander Schlesinger, Arseniy Sheydvasser

We give a number of results about families of Ulam sets. Generalizing behavior of Ulam sets U(1,n), we prove using an novel model theoretic approach that there is a rigidity phenomenon for Ulam sets U(a,b) as b increases. Based on this, we suggest a natural conjecture, and investigate its potential applications, including a method of proving certain families

C. R. Granstrom, I. Fridman, H. -C. Lei, C. Petrovic

Using Andreev reflection (AR) as an experimental gauge of the superconducting proximity effect (PE), we assess the topological purity of the superconductivity that is induced by the c-axis PE between an s-wave superconductor and the topological insulators Bi$_{2}$X$_{3}$ (X=Se,Te). Point-contact AR spectroscopy is performed with Nb tips on Bi$_{2}$X$_{3}$ si

O. Naaman, D. G. Ferguson, R. J. Epstein

We present design and simulation of a Josephson parametric amplifier with bandwidth exceeding 1.6 GHz, and with high saturation power approaching -90 dBm at a gain of 22.8 dB. An improvement by a factor of roughly 50 in bandwidth over the state of the art is achieved by using well-established impedance matching techniques. An improvement by a factor of rough

Moulay Rchid Sidi Ammi, Ismail Jamiai, Delfim F. M. Torres

We begin by proving a local existence result for a fractional Caputo nonlocal thermistor problem. Then, additional existence and continuation theorems are obtained, ensuring global existence of solutions.

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo, Gonzalo Mateos

We study the problem of sampling a bandlimited graph signal in the presence of noise, where the objective is to select a node subset of prescribed cardinality that minimizes the signal reconstruction mean squared error (MSE). To that end, we formulate the task at hand as the minimization of MSE subject to binary constraints, and approximate the resulting NP-

Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng

We address the issue of limit cycling behavior in training Generative Adversarial Networks and propose the use of Optimistic Mirror Decent (OMD) for training Wasserstein GANs. Recent theoretical results have shown that optimistic mirror decent (OMD) can enjoy faster regret rates in the context of zero-sum games. WGANs is exactly a context of solving a zero-s

Michael Kopp, Kyriakos Vattis, Constantinos Skordis

We demonstrate that the Vlasov equation describing collisionless self-gravitating matter may be solved with the so-called Schr\"odinger method (ScM). With the ScM, one solves the Schr\"odinger-Poisson system of equations for a complex wave function in d dimensions, rather than the Vlasov equation for a 2d-dimensional phase space density. The ScM also allows

Min Tang, Zichen Zhang, Dana Cobzas, Martin Jagersand

We propose an attention mechanism for 3D medical image segmentation. The method, named segmentation-by-detection, is a cascade of a detection module followed by a segmentation module. The detection module enables a region of interest to come to attention and produces a set of object region candidates which are further used as an attention model. Rather than

Sam Greydanus, Anurag Koul, Jonathan Dodge, Alan Fern

While deep reinforcement learning (deep RL) agents are effective at maximizing rewards, it is often unclear what strategies they use to do so. In this paper, we take a step toward explaining deep RL agents through a case study using Atari 2600 environments. In particular, we focus on using saliency maps to understand how an agent learns and executes a policy

Jacob Schreiber

We present pomegranate, an open source machine learning package for probabilistic modeling in Python. Probabilistic modeling encompasses a wide range of methods that explicitly describe uncertainty using probability distributions. Three widely used probabilistic models implemented in pomegranate are general mixture models, hidden Markov models, and Bayesian

Stephane Shao, Pierre E. Jacob, Jie Ding, Vahid Tarokh

The Bayes factor is a widely used criterion in model comparison and its logarithm is a difference of out-of-sample predictive scores under the logarithmic scoring rule. However, when some of the candidate models involve vague priors on their parameters, the log-Bayes factor features an arbitrary additive constant that hinders its interpretation. As an altern

Teresa Bautista, André Benevides, Atish Dabholkar

Virtual massless particles in quantum loops lead to nonlocal effects which can have interesting consequences, for example, for primordial magnetogenesis in cosmology or for computing finite $N$ corrections in holography. We describe how the quantum effective actions summarizing these effects can be computed efficiently for Weyl-flat metrics by integrating th

Guo Deng, Sitai Li, Gino Biondini, Stefano Trillo

We address the degree of universality of the Fermi-Pasta-Ulam recurrence induced by multisoliton fission from a harmonic excitation by analysing the case of the semiclassical defocusing nonlinear Schrodinger equation, which models nonlinear wave propagation in a variety of physical settings. Using a suitable Wentzel-Kramers-Brillouin approach to the solution

V. V. Prokofev, L. I. Arzamasskiy, V. S. Beskin

We investigate the internal structure of the current sheet in the pulsar wind within force-free and two-fluid MHD approximations. Within the force-free approximation we obtain general asymptotic solution of the Grad-Shafranov equation for quasi-spherical pulsar wind up to the second order in small parameter $\varepsilon = (\Omega r/c)^{-1}$. The solution all

Santiago Echeverri-Arteaga, Herbert Vinck-Posada, Edgar A. Gómez

We theoretically investigate the unexpected occurrence of an extra emission peak that has been experimentally observed in off-resonant studies of cavity QED systems. Our results within the Markovian master equation approach successfully explain why the central peak arises, and how it reveals that the system is suffering a dynamical phase transition induced b

Vahid Jamali, Nariman Farsad, Robert Schober, Andrea Goldsmith

This paper focuses on molecular communication (MC) systems where the signaling molecules may participate in a reversible bimolecular reaction in the channel. The motivation for studying these MC systems is that they can realize the concept of constructive and destructive signal superposition, which leads to favorable properties such as inter-symbol interfere

Haoze Wu

Suppose we know that an object is in a sorted table and we want to determine the index of that object. To achieve this goal we could perform a binary search. However, suppose it is time-consuming to determine the relative position of that object to any other objects in the table. In this scenario, we might want to resort to an incomplete solution: we could d

Zoltan Fodor, Kieran Holland, Julius Kuti, Daniel Nogradi

Results are reported for the beta-function of weakly coupled conformal gauge theories on the lattice, SU(3) with Nf=14 fundamental and Nf=3 sextet fermions. The models are chosen to be close to the upper end of the conformal window where perturbation theory is reliable hence a fixed point is expected. The study serves as a test of how well lattice methods pe

Xiao Li, Yao Ma, Calin Belta

Skills learned through (deep) reinforcement learning often generalizes poorly across domains and re-training is necessary when presented with a new task. We present a framework that combines techniques in \textit{formal methods} with \textit{reinforcement learning} (RL). The methods we provide allows for convenient specification of tasks with logical express

Srikrishna Sekhar, Ramana Athreya

We present two algorithms to identify and flag radio frequency interference (RFI) in radio interferometric imaging data. The first algorithm utilizes the redundancy of visibilities inside a UV cell in the visibility plane to identify corrupted data, while varying the detection threshold in accordance with the observed reduction in noise with radial UV distan

Yu-Ting Chen

We consider two independent stationary random walks on large random regular graphs of degree $k\geq 3$ with $N$ vertices. On these graphs, the exponential approximations of the meeting times are known to follow from existing methods and form a basis for the voter model's diffusion approximations. The main result of this note improves the exponential approxim

Abolfazl Hashemi, Haris Vikalo

State-of-the-art algorithms for sparse subspace clustering perform spectral clustering on a similarity matrix typically obtained by representing each data point as a sparse combination of other points using either basis pursuit (BP) or orthogonal matching pursuit (OMP). BP-based methods are often prohibitive in practice while the performance of OMP-based sch

Ariyan Javanpeykar, John Voight

We exhibit an algorithm that, given input a curve $X$ over a number field, computes as output the minimal degree of a Belyi map $X \to \mathbb{P}^1$.

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo, Francisco Flórez-Revuelta

The detection of the environment where user is located, is of extreme use for the identification of Activities of Daily Living (ADL). ADL can be identified by use of the sensors available in many off-the-shelf mobile devices, including magnetic and motion, and the environment can be also identified using acoustic sensors. The study presented in this paper is

Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder

Gradient-based optimization is the foundation of deep learning and reinforcement learning. Even when the mechanism being optimized is unknown or not differentiable, optimization using high-variance or biased gradient estimates is still often the best strategy. We introduce a general framework for learning low-variance, unbiased gradient estimators for black-

Jingyin Huang, Damian Osajda

We describe the structure of quasiflats in two-dimensio\-nal Artin groups. We rely on the notion of metric systolicity developed in our previous work. Using this weak form of non-positive curvature and analyzing in details the combinatorics of tilings of the plane we describe precisely the building blocks for quasiflats in all two-dimensional Artin groups --

Weiren Yu, Xuemin Lin, Wenjie Zhang, Julie A. McCann

In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs. Li {\em et al}.'s approach requires $O(r^4 n^2)$ time and $O(r^2 n^2)$ memory in a graph with $n$ nodes, where $r$ is the target rank of the low-rank SVD. (1) We first consider edge update that does not accompany new node insertions. We show that the S

Marzieh Najafi, Hedieh Ajam, Vahid Jamali, Panagiotis D. Diamantoulakis

We consider a drone-based communication network, where several drones hover above an area and serve as mobile remote radio heads for a large number of mobile users. We assume that the drones employ free space optical (FSO) links for fronthauling of the users' data to a central unit. The main focus of this paper is to quantify the geometric loss of the FSO ch

Kirill Batmanov, Junbai Wang

DNA shape readout is an important mechanism of target site recognition by transcription factors, in addition to the sequence readout. Several models of transcription factor-DNA binding which consider DNA shape have been developed in recent years. We present a new biophysical model of protein-DNA interaction by considering the DNA shape features, which is bas

Maciej Misiorny, Gwendal Fève, Janine Splettstoesser

We study a coherent conductor supporting a single edge channel in which alternating current pulses are created by local time-dependent gating and sent on a beam-splitter realized by a quantum point contact. The current response to the gate voltage in this setup is intrinsically linear. Based on a fully self-consistent treatment employing a Floquet scattering

Ankita Mangal, Elizabeth A. Holm

We investigate the formation of stress hotspots in polycrystalline materials under uniaxial tensile deformation by integrating full field crystal plasticity based deformation models and machine learning techniques to gain data driven insights about microstructural properties. Synthetic 3D microstructures are created representing single phase equiaxed microst

R. D. Lehn, S. S. Chabysheva, J. R. Hiller

We solve the relativistic Klein--Gordon equation for a light particle gravitationally bound to a heavy central mass, with the gravitational interaction prescribed by the metric of a spherically symmetric space-time. Metrics are considered for an impenetrable sphere, a soft sphere of uniform density, and a soft sphere with a linear transition from constant to

Chuan Guo, Mayank Rana, Moustapha Cisse, Laurens van der Maaten

This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system. Specifically, we study applying image transformations such as bit-depth reduction, JPEG compression, total variance minimization, and image quilting before feeding the image to a conv

Andrei G. Lebed

We review recent theoretical results, demonstrating breakdown of the equivalence between active and passive gravitational masses and energy due to quantum effects in General Relativity. In particular, we discuss the simplest composite quantum body - a hydrogen atom - and define its gravitational masses operators. Using Gedanken experiment, we show that the f

Byung-Jay Kahng, Alfons Van Daele

In this series of papers, we develop the theory of a class of locally compact quantum groupoids, which is motivated by the purely algebraic notion of weak multiplier Hopf algebras. In this Part I, we provide motivation and formulate the definition in the C*-algebra framework. Existence of a certain canonical idempotent element is required and it plays a fund

Leonard Gross

The existence and uniqueness of solutions to the Yang-Mills heat equation over domains in Euclidean three space was proven in a previous paper for initial data lying in the Sobolev space of order one-half, which is the critical Sobolev index for this equation. In the present paper the stability of these solutions will be established. The variational equation

Dariusz Biernacki, Serguei Lenglet, Piotr Polesiuk

Normal-form bisimilarity is a simple, easy-to-use behavioral equivalence that relates terms in $\lambda$-calculi by decomposing their normal forms into bisimilar subterms. Moreover, it typically allows for powerful up-to techniques, such as bisimulation up to context, which simplify bisimulation proofs even further. However, proving soundness of these relati

R. Zhou, M. Hirata, T. Wu, I. Vinograd

The value of the upper critical field Hc2, a fundamental characteristic of the superconducting state, has been subject to strong controversy in high-Tc copper-oxides. Since the issue has been tackled almost exclusively by macroscopic techniques so far, there is a clear need for local-probe measurements. Here, we use 17O NMR to measure the spin susceptibility

Elliot Meyerson, Risto Miikkulainen

Existing deep multitask learning (MTL) approaches align layers shared between tasks in a parallel ordering. Such an organization significantly constricts the types of shared structure that can be learned. The necessity of parallel ordering for deep MTL is first tested by comparing it with permuted ordering of shared layers. The results indicate that a flexib

Caiming Xiong, Victor Zhong, Richard Socher

Traditional models for question answering optimize using cross entropy loss, which encourages exact answers at the cost of penalizing nearby or overlapping answers that are sometimes equally accurate. We propose a mixed objective that combines cross entropy loss with self-critical policy learning. The objective uses rewards derived from word overlap to solve

Kevin Wilk, D. John Hillier, Luc Dessart

We present one-dimensional non-local thermodynamic equilibrium time-dependent radiative transfer simulations (using CMFGEN) of two sub-Chandrasekhar (sub-$M_{\rm Ch}$), one $M_{\rm Ch}$ and one super-$M_{\rm Ch}$ Type Ia SN ejecta models. Three originate from $M_{\rm Ch}$ delayed detonation models, and the fourth is a sub-$M_{\rm Ch}$ detonation model. Eject

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo, Francisco Flórez-Revuelta

Most mobile devices include motion, magnetic, acoustic, and location sensors. They allow the implementation of a framework for the recognition of Activities of Daily Living (ADL) and its environments, composed by the acquisition, processing, fusion, and classification of data. This study compares different implementations of artificial neural networks, concl

Klaus Jansen, Felix Land

A moldable job is a job that can be executed on an arbitrary number of processors, and whose processing time depends on the number of processors allotted to it. A moldable job is monotone if its work doesn't decrease for an increasing number of allotted processors. We consider the problem of scheduling monotone moldable jobs to minimize the makespan. We argu

Diogo Buarque Franzosi, Federica Fabbri, Steffen Schumann

Constraints on models which predict resonant top-quark pair production at the LHC are provided via a reinterpretation of the Standard Model (SM) particle level measurement of the top-anti-top invariant mass distribution, $m(t\bar{t})$. We make use of state-of-the-art Monte Carlo event simulation to perform a direct comparison with measurements of $m(t\bar{t}

Anru R. Zhang, Kehui Chen

In mixed longitudinal studies, a group of subjects enter the study at different ages (cross-sectional) and are followed for successive years (longitudinal). In the context of such studies, we consider nonparametric covariance estimation with samples of noisy and partially observed functional trajectories. The proposed algorithm is based on a noniterative seq

Saulo Diles

This article is dedicated to the analysis of Weyl symmetry in the context of relativistic hydrodynamics. Here is discussed how this symmetry is properly implemented using the prescription of minimal coupling: $\partial\to \partial +\omega \mathcal{A}$. It is shown that this prescription has no problem to deal with curvature since it gives the correct express

Shakhobiddin Karimov

In the work an explicit formula of a solution of analogue of a Cauchy problem for an inhomogeneous manydimensional polycaloric equation with Bessel operator was found. Manydimensional Erdelyi-Kober operator of the fractional order was applied to construction of a solution

Monica Billio, Roberto Casarin, Matteo Iacopini

We propose a new Bayesian Markov switching regression model for multidimensional arrays (tensors) of binary time series. We assume a zero-inflated logit regression with time-varying parameters and apply it to multilayer temporal networks. The original contribution is threefold. First, to avoid over-fitting we propose a parsimonious parametrization based on a

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo, Francisco Flórez-Revuelta

This paper focuses on the recognition of Activities of Daily Living (ADL) applying pattern recognition techniques to the data acquired by the accelerometer available in the mobile devices. The recognition of ADL is composed by several stages, including data acquisition, data processing, and artificial intelligence methods. The artificial intelligence methods

Marta Luszczak, Antoni Szczurek

We discuss single-diffractive production of dijets. The cross section is calculated for the first time in the $k_t$-factorization approach, neglecting transverse momentum of the pomeron. We use Kimber-Martin-Ryskin unintegrated parton (gluon, quark, antiquark) distributions (UPDF) both in the proton as well as in the pomeron or subleading reggeon. The UPDFs

Yanzhu Chen, Abhishodh Prakash, Tzu-Chieh Wei

Measurement-based quantum computation describes a scheme where entanglement of resource states is utilized to simulate arbitrary quantum gates via local measurements. Recent works suggest that symmetry-protected topologically non-trivial, short-ranged entanged states are promising candidates for such a resource. Miller and Miyake [NPJ Quantum Information 2,

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo, Francisco Flórez-Revuelta

Several types of sensors have been available in off-the-shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL) using pattern

Akhmadjon Urinov, Shakhobiddin Karimov

An analogue of the Cauchy problem for the iterated multidimensional Klein- Gordon-Fock equation with a time-dependent Bessel operator is investigated. Applying the generalized Erdelyi-Kober operator of fractional order, the problem posed is reduced to the Cauchy problem for the polywave equation. An explicit formula for solving this problem is constructed by

Amita Misra, Shereen Oraby, Shubhangi Tandon, Sharath TS

Online argumentative dialog is a rich source of information on popular beliefs and opinions that could be useful to companies as well as governmental or public policy agencies. Compact, easy to read, summaries of these dialogues would thus be highly valuable. A priori, it is not even clear what form such a summary should take. Previous work on summarization

Mitra Shamsabadi, Ali Akbar Arefijamaal, Peter Balazs

For applications like the numerical solution of physical equations a discretization scheme for operators is necessary. Recently frames have been used for such an operator representation. In this paper, we apply fusion frames for this task. We interpret the operator representation using fusion frames as a generalization of fusion Gram matrices. We present the

Sheng Liu, Polina P. Vabishchevich, Aleksandr Vaskin, John L. Reno

A frequency mixer is a nonlinear device that combines electromagnetic waves to create waves at new frequencies. Mixers are ubiquitous components in modern radio-frequency technology and are widely used in microwave signal processing. The development of versatile frequency mixers for optical frequencies remains challenging: such devices generally rely on weak

Enrico Carlini, Emanuele Ventura

In this paper we study the complex simultaneous Waring rank for collections of monomials. For general collections we provide a lower bound, whereas for special collections we provide a formula for the simultaneous Waring rank. Our approach is algebraic and combinatorial. We give an application to ranks of binomials and maximal simultaneous ranks. Moreover, w

Max H. Quinn, Erik Conser, Jordan M. Witte, Melanie Mitchell

We describe a novel architecture for semantic image retrieval---in particular, retrieval of instances of visual situations. Visual situations are concepts such as "a boxing match," "walking the dog," "a crowd waiting for a bus," or "a game of ping-pong," whose instantiations in images are linked more by their common spatial and semantic structure than by low

Abdulla Aydın

Let $(x_\alpha)$ be a net in a vector lattice normed by locally solid lattice $(X,p,E_\tau)$. We say that $(x_\alpha)$ is unbounded $p_\tau$-convergent to $x\in X$ if $p(\lvert x_\alpha-x\rvert\wedge u)\xrightarrow{\tau} 0$ for every $u\in X_+$. This convergence has been studied recently for lattice-normed vector lattices as the $up$-convergence in \cite{AGG

K. A. Bronnikov

We consider spherically symmetric configurations in general relativity, supported by nonlinear electromagnetic fields with gauge-invariant Lagrangians depending on the single invariant $f = F_{\mu\nu} F^{\mu\nu}$. Static black hole and solitonic solutions are briefly described, both with only an electric or magnetic charge and with both nonzero charges (the

Anh D. Phan, Kenneth S. Schweizer

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization (ECNLE theory) of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there

D. Kozieł-Wierzbowska, G. Stasińska, N. Vale Asari, M. Sikora

Active galactic nuclei (AGNs) are known to cover an extremely broad range of radio luminosities and the spread of their radio-loudness is very large at any value of the Eddington ratio. This implies very diverse jet production efficiencies which can result from the spread of the black hole spins and magnetic fluxes. Magnetic fluxes can be developed stochasti

Saskia Demulder, Sibylle Driezen, Alexander Sevrin, Daniel C. Thompson

We investigate the integrable Yang-Baxter deformation of the 2d Principal Chiral Model with a Wess-Zumino term. For arbitrary groups, the one-loop beta functions are calculated and display a surprising connection between classical and quantum physics: the classical integrability condition is necessary to prevent new couplings being generated by renormalisati

Alejandro Schuler, Ken Jung, Robert Tibshirani, Trevor Hastie

Many decisions in healthcare, business, and other policy domains are made without the support of rigorous evidence due to the cost and complexity of performing randomized experiments. Using observational data to answer causal questions is risky: subjects who receive different treatments also differ in other ways that affect outcomes. Many causal inference me

Matthew Dawson, Raul Quiroga-Barranco

Let $D$ be an irreducible bounded symmetric domain with biholomorphism group $G$ with maximal compact subgroup $K$. For the Toeplitz operators with $K$-invariant symbols we provide explicit simultaneous diagonalization formulas on every weighted Bergman space. The expressions are given in the general case, but are also worked out explicitly for every irreduc

Alexander Ageev

In the $2$-Machine Flow Shop problem with exact delays the operations of each job are separated by a given time lag (delay). Leung et al. (2007) established that the problem is strongly NP-hard when the delays may have at most two different values. We present further results for this case: we prove that the existence of $(1.25-\varepsilon)$-approximation imp

Agata M. Brańczyk

This article is a detailed introduction to Hong-Ou-Mandel (HOM) interference, in which two photons interfere on a beamsplitter in a way that depends on the photons' distinguishability. We begin by considering distinguishability in the polarization degree of freedom. We then consider spectral distinguishability, and show explicitly how to calculate the HOM di

Yafang Yang, Shiang Fang, Valla Fatemi, Jonathan Ruhman

As superconductors are thinned down to the 2D limit, their critical temperature $T_c$ typically decreases. Here we report the opposite behavior, a substantial enhancement of $T_c$ with decreasing thickness, in 2D crystalline superconductor 2H-TaS$_2$. Remarkably, in the monolayer limit, $T_c$ increases to 3.4 K compared to 0.8 K in the bulk. Accompanying thi

Shay Leizerovitch, Benni Reznik

We propose a method for using ultracold atomic Bose-Einstein condensates, to form an analog model of a scalar field in five dimensional space-time, where one of the spatial dimensions is compact. In the analog system the extra dimension is discrete, and realized using the internal degrees of freedom of the system. In the low energy regime, the Kaluza-Klein t

Emilio Martínez-Pañeda, Rafael Gallego

This work investigates the existing capabilities and limitations in numerical modeling of fracture problems in functionally graded materials (FGMs) by means of the well-known finite element code ABAQUS. Quasi-static crack initiation and growth in planar FGMs is evaluated. Computational results of fracture parameters are compared to experimental results and g

E. Minguzzi

In a recent work I showed that the family of smooth steep time functions can be used to recover the order, the topology and the (Lorentz-Finsler) distance of spacetime. In this work I present the main ideas entering the proof of the (smooth) distance formula, particularly the product trick which converts metric statements into causal ones. The paper ends wit

Luke Zoltan Kelley, Laura Blecha, Lars Hernquist, Alberto Sesana

We calculate the properties, occurrence rates and detection prospects of individually resolvable 'single sources' in the low frequency gravitational wave (GW) spectrum. Our simulations use the population of galaxies and massive black hole binaries from the Illustris cosmological hydrodynamic simulations, coupled to comprehensive semi-analytic models of the b

A. R. Ferdinand, M. T. DiMario, F. E. Becerra

Measurements approaching the ultimate quantum limits of sensitivity are central in quantum information processing, quantum metrology, and communication. Quantum measurements to discriminate multiple states at the single-photon level are essential for optimizing information transfer in low-power optical communications and quantum communications, and can enhan

Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue

We present Higher-Order Tensor RNN (HOT-RNN), a novel family of neural sequence architectures for multivariate forecasting in environments with nonlinear dynamics. Long-term forecasting in such systems is highly challenging, since there exist long-term temporal dependencies, higher-order correlations and sensitivity to error propagation. Our proposed recurre

Yiping Shu, Joel R. Brownstein, Adam S. Bolton, Léon V. E. Koopmans

We present the full sample of 118 galaxy-scale strong-lens candidates in the Sloan Lens ACS (SLACS) Survey for the Masses (S4TM) Survey, which are spectroscopically selected from the final data release of the Sloan Digital Sky Survey. Follow-up Hubble Space Telescope (HST) imaging observations confirm that 40 candidates are definite strong lenses with multip

Roberto Onofrio

We review the status of cooling techniques aimed at achieving the deepest quantum degeneracy for atomic Fermi gases. We first discuss some physical motivations, providing a quantitative assessment of the need for deep quantum degeneracy in relevant physics cases, such as the search for unconventional superfluid states. Attention is then focused on the most w

Stephan Clémençon, Anna Korba, Eric Sibony

This article is devoted to the problem of predicting the value taken by a random permutation $\Sigma$, describing the preferences of an individual over a set of numbered items $\{1,\; \ldots,\; n\}$ say, based on the observation of an input/explanatory r.v. $X$ e.g. characteristics of the individual), when error is measured by the Kendall $\tau$ distance. In

Shulei Wang, Ellen T. Arena, Jordan T. Becker, William M. Bement

Colocalization analysis aims to study complex spatial associations between bio-molecules via optical imaging techniques. However, existing colocalization analysis workflows only assess an average degree of colocalization within a certain region of interest and ignore the unique and valuable spatial information offered by microscopy. In the current work, we i

Michael Dennis, Ljubomir Perković, Duru Türkoğlu

The problem of computing the exact stretch factor (i.e., the tight bound on the worst case stretch factor) of a Delaunay triangulation is one of the longstanding open problems in computational geometry. Over the years, a series of upper and lower bounds on the exact stretch factor have been obtained but the gap between them is still large. An alternative app

Thomas Appelquist, James Ingoldby, Maurizio Piai

In a recent paper, we developed and applied a dilaton-based effective field theory (EFT) to the analysis of lattice-simulation data for a class of confining gauge theories with near-conformal infrared behavior. It was employed there at the classical level to the SU(3) gauge theory with eight Dirac fermions in the fundamental representation. Here, we explore

Konrad Zolna, Devansh Arpit, Dendi Suhubdy, Yoshua Bengio

Recurrent neural networks (RNNs) are important class of architectures among neural networks useful for language modeling and sequential prediction. However, optimizing RNNs is known to be harder compared to feed-forward neural networks. A number of techniques have been proposed in literature to address this problem. In this paper we propose a simple techniqu

René Sondenheimer

The possible violation of the conventional lower Higgs mass stability bound by the discovered Higgs boson has far reaching consequences within particle physics and cosmology. We discuss the possibility that nonpolynomial bare interactions seeded at some high-momentum scale can considerably diminish the lower Higgs mass bound without introducing a metastabili

Chandler Zuo

In classification problems, sampling bias between training data and testing data is critical to the ranking performance of classification scores. Such bias can be both unintentionally introduced by data collection and intentionally introduced by the algorithm, such as under-sampling or weighting techniques applied to imbalanced data. When such sampling bias

M. Belén Farias, Wilton J. M. Kort-Kamp, Diego A. R. Dalvit

We develop the theory of quantum friction in two-dimensional topological materials. The quantum drag force on a metallic nanoparticle moving above such systems is sensitive to the non-trivial topology of their electronic phases, shows a novel distance scaling law, and can be manipulated through doping or via the application of external fields. We use the dev

Michael L. Wagman

The theory of quantum chromodynamics (QCD) encodes the strong interactions that bind quarks and gluons into nucleons and that bind nucleons into nuclei. Predictive control of QCD would allow nuclear structure and reactions as well as properties of supernovae and neutron stars to be theoretically studied from first principles. Lattice QCD can represent generi

Qifan Li

We establish weak Harnack inequalities for positive, weak supersolutions to certain doubly degenerate parabolic equations. The prototype of this kind of equations is $$\partial_tu-\operatorname{div}|u|^{m-1}|Du|^{p-2}Du=0,\quad p>2,\quad m+p>3.$$ Our proof is based on Caccioppoli inequalities, De Giorgi's estimates and Moser's iterative method.

William Hanlon, Rasha Abbasi

Ultra high energy cosmic rays (UHECRs) provide a natural source of particles accelerated to energies beyond those that can be attained in the laboratory. UHECRs have been observed with energies exceeding $10^{20}$ eV, which is equivalent to 433 TeV in the center-of-momentum frame. Using this natural source of particles physicists can extend the measurement o

Wrick Sengupta, Harold Weitzner

Quasisymmetry and omnigeneity of an equilibrium magnetic field are two distinct properties proposed to ensure radial localization of collisionless trapped particles in any stellarator. These constraints are incompletely explored, but have stringent restrictions on a magnetic geometry. This work employs an analytic approach to understand the implications of t

Toshiya Namikawa

We present constraints on the patchy reionization by measuring the trispectrum of the Planck 2015 cosmic microwave background (CMB) temperature anisotropies. The patchy reionization leads to anisotropies in the CMB optical depth, and the statistics of the observed CMB anisotropies is altered. We estimate the trispectrum of the CMB temperature anisotropies to

E. Colella, R. Citro, M. Barsanti, D. Rossini

We explore the quantum phases emerging from the interplay between spin and motional degrees of freedom of a one-dimensional quantum fluid of spinful fermionic atoms, effectively interacting via a photon-mediating mechanism with tunable sign and strength g, as it can be realized in present-day experiments with optical cavities. We find the emergence, in the v

Suchita Kulkarni, Lukas Lechner

The search for heavy Higgs bosons is an important step to probe the parameter space of the Minimal Supersymmetric Standard Model. In this work, we classify all possible decay modes of the supersymmetric heavy Higgs boson using the SModelS framework. We work within the phenomenological MSSM and use the ATLAS pMSSM study as our viable parameter space. We find

Wolfgang E. Kerzendorf, Tuan Do, Selma E. de Mink, Ylva Götberg

Massive stars in binaries can give rise to extreme phenomena such as X-ray binaries and gravitational wave sources after one or both stars end their lives as core-collapse supernovae. Stars in close orbit around a stellar or compact companion are expected to explode as "stripped-envelope supernovae", showing no (Type Ib/c) or little (Type IIb) signs of hydro

Zhenhua Zhang, Lei Lin

Border crossing delays cause problems like huge economics loss and heavy environmental pollutions. To understand more about the nature of border crossing delay, this study applies a dictionary-based compression algorithm to process the historical Niagara Frontier border wait times data. It can identify the abnormal spatial-temporal patterns for both passenge

Sreya Guha

The emergence of "Fake News" and misinformation via online news and social media has spurred an interest in computational tools to combat this phenomenon. In this paper we present a new "Related Fact Checks" service, which can help a reader critically evaluate an article and make a judgment on its veracity by bringing up fact checks that are relevant to the

Benjamin Archibeque, Florian Genz, Maxwell Franklin, Scott V Franklin

This project investigates how to quantitatively measure equity in small student groups. We follow several student groups to operationalize how discourse may be equitable or inequitable. The groups came from a two week, pre-college program that prepares first generation and deaf/hard-of-hearing students to major in a STEM field. In the program, students focus

Mingao Yuan, Yue Zhang

In this paper, we apply empirical likelihood method to inference for the regression parameters in the partial functional linear regression models based on B spline. We prove that the empirical log likelihood ratio for the regression parameters converges in law to a weighted sum of independent chi square distributions and run simulations to assess the finite

F. Tacchino, A. Chiesa, M. D. LaHaye, S. Carretta

Digital quantum simulators are among the most appealing applications of a quantum computer. Here we propose a universal, scalable, and integrated quantum computing platform based on tunable nonlinear electromechanical nano-oscillators. It is shown that very high operational fidelities for single and two qubits gates can be achieved in a minimal architecture,

Gideon Amir, Gady Kozma

We prove that all groups of exponential growth support non-constant positive harmonic functions. In fact, out results hold in the more general case of strongly connected, finitely supported Markov chains invariant under some transitive group of automorphisms for which the directed balls grow exponentially.

Zhe Guo, Xiang Li, Heng Huang, Ning Guo

Image analysis using more than one modality (i.e. multi-modal) has been increasingly applied in the field of biomedical imaging. One of the challenges in performing the multimodal analysis is that there exist multiple schemes for fusing the information from different modalities, where such schemes are application-dependent and lack a unified framework to gui