August 2019 arXiv papers — page 3

Xenju Xu, Guanghui Wang, Alan Sullivan, Ziming Zhang

In this paper we propose integrating a priori knowledge into both design and training of convolutional neural networks (CNNs) to learn object representations that are invariant to affine transformations (i.e., translation, scale, rotation). Accordingly we propose a novel multi-scale maxout CNN and train it end-to-end with a novel rotation-invariant regulariz

Marten van Schijndel, Aaron Mueller, Tal Linzen

Recurrent neural networks can learn to predict upcoming words remarkably well on average; in syntactically complex contexts, however, they often assign unexpectedly high probabilities to ungrammatical words. We investigate to what extent these shortcomings can be mitigated by increasing the size of the network and the corpus on which it is trained. We find t

Kefeng Liu, Jianming Wan

We prove that if a compact Riemannian 4-manifold with positive sectional curvature satisfies a Kato type inequality, then it is definite. We also discuss some new insights for compact Riemannian 4-manifolds of positive sectional curvature.

Prashanth Gurunath Shivakumar, Shao-Yen Tseng, Panayiotis Georgiou, Shrikanth Narayanan

Most current language modeling techniques only exploit co-occurrence, semantic and syntactic information from the sequence of words. However, a range of information such as the state of the speaker and dynamics of the interaction might be useful. In this work we derive motivation from psycholinguistics and propose the addition of behavioral information into

Minho Kwon, Peiyu Yang, Preston Huft, Christopher Young

We present a continuous, narrow-linewidth, tunable laser system that outputs up to 14.0 W at 770 nm. The light is generated by frequency doubling 18.8 W of light from a 1540 nm fiber amplifier that is seeded by a single mode diode laser achieving >74% conversion efficiency. We utilize a Lithium Triborate Crystal in an enhancement ring cavity. The low intensi

Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley

Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes. We propose a new task of personalized recipe generation to help these users: expanding a name and incomplete ingredient details into complete natural-text instructions aligned with the user'

Shuaike Dong, Zhou Li, Di Tang, Jiongyi Chen

The IoT (Internet of Things) technology has been widely adopted in recent years and has profoundly changed the people's daily lives. However, in the meantime, such a fast-growing technology has also introduced new privacy issues, which need to be better understood and measured. In this work, we look into how private information can be leaked from network

Chao Min, Yang Chen

This paper studies the Hankel determinant generated by a perturbed Jacobi weight, which is closely related to the largest and smallest eigenvalue distribution of the degenerate Jacobi unitary ensemble. By using the ladder operator approach for the orthogonal polynomials, we find that the logarithmic derivative of the Hankel determinant satisfies a nonlinear

Alexander Hanbo Li, Abhinav Sethy

Neural network models have been very successful at achieving high accuracy on natural language inference (NLI) tasks. However, as demonstrated in recent literature, when tested on some simple adversarial examples, most of the models suffer a significant drop in performance. This raises the concern about the robustness of NLI models. In this paper, we propose

Henry Tsai, Jason Riesa, Melvin Johnson, Naveen Arivazhagan

We propose a practical scheme to train a single multilingual sequence labeling model that yields state of the art results and is small and fast enough to run on a single CPU. Starting from a public multilingual BERT checkpoint, our final model is 6x smaller and 27x faster, and has higher accuracy than a state-of-the-art multilingual baseline. We show that ou

Dongyeop Kang, Varun Gangal, Eduard Hovy

Stylistic variation in text needs to be studied with different aspects including the writer's personal traits, interpersonal relations, rhetoric, and more. Despite recent attempts on computational modeling of the variation, the lack of parallel corpora of style language makes it difficult to systematically control the stylistic change as well as evaluate

Sanja Singer

In this paper we develop algorithms for orthogonal similarity transformations of skew-symmetric matrices to simpler forms. The first algorithm is similar to the algorithm for the block antitriangular factorization of symmetric matrices, but in the case of skew-symmetric matrices, an antitriangular form is always obtained. Moreover, a simple two-sided permuta

Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield

Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. Conventional MRI reconstruction methods for fast MRI acquisition mostly relied on different regularizers which represent analytical models of sparsity. However, recent data-driven methods based on deep learni

Steven Y. Feng, Aaron W. Li, Jesse Hoey

In this paper, we present a novel method for measurably adjusting the semantics of text while preserving its sentiment and fluency, a task we call semantic text exchange. This is useful for text data augmentation and the semantic correction of text generated by chatbots and virtual assistants. We introduce a pipeline called SMERTI that combines entity replac

William G. Tobias, Kyle Matsuda, Giacomo Valtolina, Luigi De Marco

We observe thermalization in the production of a degenerate Fermi gas of polar ${}^{40}\text{K}{}^{87}\text{Rb}$ molecules. By measuring the atom--dimer elastic scattering cross section near the Feshbach resonance, we show that Feshbach molecules rapidly reach thermal equilibrium with both parent atomic species. Equilibrium is essentially maintained through

Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou

Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios including voice recognition and conversational understanding for customer support, autotuning for videoconferencing, intelligent feedback loops in large-scale sysops, manufacturing an

Run Chen, Andrew L. Liu

We propose a Jacobi-style distributed algorithm to solve convex, quadratically constrained quadratic programs (QCQPs), which arise from a broad range of applications. While small to medium-sized convex QCQPs can be solved efficiently by interior-point algorithms, large-scale problems pose significant challenges to traditional algorithms that are mainly desig

Alexander Heaton, Isabelle Shankar

It is known that differences of symmetric functions corresponding to various bases are nonnegative on the nonnegative orthant exactly when the partitions defining them are comparable in dominance order. The only exception is the case of homogeneous symmetric functions where it is only known that dominance of the partitions implies nonnegativity of the corres

Avinash Madasu, Vijjini Anvesh Rao

Text classification has been one of the major problems in natural language processing. With the advent of deep learning, convolutional neural network (CNN) has been a popular solution to this task. However, CNNs which were first proposed for images, face many crucial challenges in the context of text processing, namely in their elementary blocks: convolution

Thomas Lew, Tomoki Emmei, David D. Fan, Tara Bartlett

Autonomous exploration of unknown environments with aerial vehicles remains a challenge, especially in perceptually degraded conditions. Dust, fog, or a lack of visual or LiDAR-based features results in severe difficulties for state estimation algorithms, which failure can be catastrophic. In this work, we show that it is indeed possible to navigate in such

Dinesh Baral, Zhuangen Fu, Andrei S. Zadorozhnyi, Rabindra Dulal

CrBr$_{3}$ is a layered van der Waals material with magnetic ordering down to the 2D limit. For decades, based on optical measurements, it is believed that the energy gap of CrBr$_{3}$ is in the range of 1.68-2.1 eV. However, controversial results have indicated that the band gap of CrBr$_{3}$ is possibly smaller than that. An unambiguous determination of th

Ricardo Augusto Borsoi

Video super-resolution reconstruction (SRR) algorithms attempt to reconstruct high-resolution (HR) video sequences from low-resolution observations. Although recent progress in video SRR has significantly improved the quality of the reconstructed HR sequences, it remains challenging to design SRR algorithms that achieve good quality and robustness at a small

Laura Colmenarejo, Charles F. Dunkl

Singular nonsymmetric Macdonald polynomials are constructed by use of the representation theory of the Hecke algebras of the symmetric groups. These polynomials are labeled by quasistaircase partitions and are associated to special parameter values $(q,t)$. For $N$ variables, there are singular polynomials for any pair of positive integers $m$ and $n$, with

Jose J. Blanco-Pillado, Heling Deng, Alexander Vilenkin

The much-discussed swampland conjectures suggest significant constraints on the properties of string theory landscape and on the nature of the multiverse that this landscape can support. The conjectures are especially constraining for models of inflation; in particular, they exclude the existence of de Sitter (dS) vacua. If the conjectures are false and dS v

Amanda Coston, Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova

Algorithmic risk assessments are increasingly used to help humans make decisions in high-stakes settings, such as medicine, criminal justice and education. In each of these cases, the purpose of the risk assessment tool is to inform actions, such as medical treatments or release conditions, often with the aim of reducing the likelihood of an adverse event su

MohammadReza Ebrahimi, Farshad Lahouti, Victoria Kostina

We propose a two-layer coding architecture for communication of multiple users over a shared slotted medium enabling joint collision resolution and decoding. Each user first encodes its information bits with an outer code for reliability, and then transmits these coded bits with possible repetitions over transmission time slots of the access channel. The tra

Marc Winstel, Jonas Stoll, Marc Wagner

We investigate the phase structure of the 2+1-dimensional Gross-Neveu model in the large-Nf limit, where Nf denotes the number of fermion flavors. We discuss two different fermion representations and their implication on the interpretation of a discrete symmetry of the action. We present numerical results, which indicate the existence of an inhomogeneous pha

Moulay Tahar Benameur, James L. Heitsch

In a recent paper, the authors proved that no spin foliation on a compact enlargeable manifold with Hausdorff homotopy graph admits a metric of positive scalar curvature on its leaves. This result extends groundbreaking results of Lichnerowicz, Gromov and Lawson, and Connes on the non-existence of metrics of positive scalar curvature. In this paper we review

John Sun, Christopher S. Wang, Ellie S. Krossa

Sprawl, according to Glaeser and Kahn, is the 21st century phenomenon that some people are not dependent on city-living due to automobiles and therefore can live outside public transportation spheres and cities. This is usually seen as pleasant and accompanied by improved qualities of life, but as they addressed, the problem remains that sprawl causes loss o

Hirofumi Sakakibara, Hidetomo Usui, Katsuhiro Suzuki, Takao Kotani

Effective models are constructed for a newly discovered superconductor (Nd,Sr)NiO2, which has been considered as a possible nickelate analogue of the cuprates owing to the d9 electron configuration. Estimation of the effective interaction, which turns out to require a multiorbital model that takes account of all the orbitals involved on the Fermi surface, sh

Mohammadhasan Hedayati, Matt J. Kipper, Diego Krapf

In this work, protein-surface interactions were probed in terms of adsorption and desorption of a model protein, bovine serum albumin, on a low-fouling surface with single-molecule localization microscopy. Single-molecule experiments enable precise determination of both adsorption and desorption rates. Strikingly the experimental data show anomalous desorpti

Amey Agrawal, Rohit Karlupia

Recently, in the paper "Weight Agnostic Neural Networks" Gaier & Ha utilized architecture search to find networks where the topology completely encodes the knowledge. However, architecture search in topology space is expensive. We use the existing framework of binarized networks to find performant topologies by constraining the weights to be either,

M. V. Burdastyh, S. V. Postolova, T. Proslier, S. S. Ustavshikov

The suppression of superconductivity in disordered systems is a fundamental problem of condensed matter physics. Here we investigate the superconducting niobium-titanium-nitride (Nb_{1-x}Ti_{x}N) thin films grown by atomic layer deposition (ALD) where disorder is controlled by the slight tuning of the ALD process parameters. We observe the smooth crossover f

Justin Miller

Recent work in computability theory has focused on various notions of asymptotic computability, which capture the idea of a set being "almost computable." One potentially upsetting result is that all four notions of asymptotic computability admit "almost computable" sets in every Turing degree via coding tricks, contradicting the notion that

Chao He, Jintao Chang, Qi Hu, Jingyu Wang

Graded index (GRIN) lenses are commonly used for compact imaging systems. It is not widely appreciated that the ion-exchange process that creates the rotationally symmetric GRIN lens index profile also causes a symmetric birefringence variation. This property is usually considered a nuisance, such that manufacturing processes are optimized to keep it to a mi

Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis

When the data is distributed across multiple servers, lowering the communication cost between the servers (or workers) while solving the distributed learning problem is an important problem and is the focus of this paper. In particular, we propose a fast, and communication-efficient decentralized framework to solve the distributed machine learning (DML) prob

Chunmin Mi, Runjie Xu, Ching-Torng Lin, Run Yu Meng

Smartphones have become an important tool for people's daily lives, which brings higher security requirements in high-risk application areas, for example, mobile payment. Although the combination of physical password, fingerprint and facial recognition have improved the security to a certain extent, there still exists a high risk of being decrepted. This

Corey Ostrove, Brian La Cour, Andrew Lanham, Granville Ott

The use of analog classical systems for computation is generally thought to be a difficult proposition due to the susceptibility of these devices to noise and the lack of a clear framework for achieving fault-tolerance. We present experimental results for the application of quantum error correction (QEC) techniques to a prototype analog computational device

Chen Jia, Le Yi Wang, George G. Yin, Michael Q. Zhang

Here we investigate single-cell stochastic gene expression kinetics in a minimal coupled gene circuit with positive-plus-negative feedback. A triphasic stochastic bifurcation upon the increasing ratio of the positive and negative feedback strengths is observed, which reveals a strong synergistic interaction between positive and negative feedback loops. We di

Di Kang, Dongfang Yun, Bartosz Protas

This investigation concerns a systematic search for potentially singular behavior in 3D Navier-Stokes flows. Enstrophy serves as a convenient indicator of the regularity of solutions to the Navier Stokes system --- as long as this quantity remains finite, the solutions are guaranteed to be smooth and satisfy the equations in the classical (pointwise) sense.

Faseeh Ahmad, Robert L. Benedetto, Jennifer Cain, Gregory Carroll

The arboreal Galois group of a polynomial $f$ over a field $K$ encodes the action of Galois on the iterated preimages of a root point $x_0\in K$, analogous to the action of Galois on the $\ell$-power torsion of an abelian variety. We compute the arboreal Galois group of the postcritically finite polynomial $f(z) = z^2 - 1$ when the field $K$ and root point $

E. A. F. Bragança, R. L. L. Vitória, H. Belich, E. R. Bezerra de Mello

We investigated the effects of the global monopole spacetime on the Dirac and Klein-Gordon relativistic quantum oscillators. In order to do this, we solve the Dirac and Klein-Gordon equations analytically and discuss the influence of this background which is characterized by the curvature of the spacetime on the energy profiles of these oscillators. In addit

Grzegorz M. Koczan

Newton second law of dynamics is a law of motion but also a useful definition of force (F=MA) or inertial mass (M=F/A), assuming a definition of acceleration and parallelism of force and acceleration. In the special theory of relativity, out of these three only the description of force (F=dp/dt) does not raise doubts. The greatest problems are posed by mass,

Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah

Natural language programming is a promising approach to enable end users to instruct new tasks for intelligent agents. However, our formative study found that end users would often use unclear, ambiguous or vague concepts when naturally instructing tasks in natural language, especially when specifying conditionals. Existing systems have limited support for l

Kamran Javid

I compare the mass values obtained with data taken from the Arcminute Microkelvin Imager (AMI) radio interferometer system and from the Planck satellite. The former of these uses a Bayesian analysis pipeline that parameterises a cluster in terms of its physical quantities, and models the dark matter \& baryonic components of a cluster using Navarro-Frenk-Whi

Christina Karafyllia

Let $D \subset \mathbb{C}$ be a domain with $0 \in D$. For $R>0$, let ${{\hat ω}_D}\left( {R} \right)$ denote the harmonic measure of $ D \cap \left\{ {\left| z \right| = R} \right\}$ at $0$ with respect to the domain $ D \cap \left\{ {\left| z \right| < R} \right\} $ and ${ω_D}\left( {R} \right)$ denote the harmonic measure of $\partial D \cap \left\{ {\lef

Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Francesco Visin

Learning an efficient update rule from data that promotes rapid learning of new tasks from the same distribution remains an open problem in meta-learning. Typically, previous works have approached this issue either by attempting to train a neural network that directly produces updates or by attempting to learn better initialisations or scaling factors for a

M. Keith Chen, Kareem Haggag, Devin G. Pope, Ryne Rohla

Equal access to voting is a core feature of democratic government. Using data from millions of smartphone users, we quantify a racial disparity in voting wait times across a nationwide sample of polling places during the 2016 U.S. presidential election. Relative to entirely-white neighborhoods, residents of entirely-black neighborhoods waited 29% longer to v

Shwetadwip Chowdhury, Michael Chen, Regina Eckert, David Ren

Optical diffraction tomography (ODT) reconstructs a samples volumetric refractive index (RI) to create high-contrast, quantitative 3D visualizations of biological samples. However, standard implementations of ODT use interferometric systems, and so are sensitive to phase instabilities, complex mechanical design, and coherent noise. Furthermore, their reconst

Miles H. Anderson, Romain Bouchand, Junqiu Liu, Wenle Weng

Supercontinuum generation in optical fibers is one of the most dramatic nonlinear effects discovered, allowing short pulses to be converted into multi-octave spanning coherent spectra. However, generating supercontinua that are both coherent and broadband requires pulses that are simultaneously ultrashort with high peak power. This results in a reducing effi

Javier S. Turek, Shailee Jain, Vy Vo, Mihai Capota

Recent work has shown that topological enhancements to recurrent neural networks (RNNs) can increase their expressiveness and representational capacity. Two popular enhancements are stacked RNNs, which increases the capacity for learning non-linear functions, and bidirectional processing, which exploits acausal information in a sequence. In this work, we exp

Marisa Gaetz, Caleb Ji

Given a finite word $w$ over a finite alphabet $V$, consider the graph with vertex set $V$ and with an edge between two elements of $V$ if and only if the two elements alternate in the word $w$. Such a graph is said to be word-representable or 11-representable by the word $w$; this latter terminology arises from the phenomenon that the condition of two eleme

I. V. Anikin, L. Szymanowski

We revisit the standard representation of the (inverse) Radon transform which is well-known in the mathematical literature. We extend this representation to the case involving the parton distributions. We have found the new additional contribution which is essentially related to the generalized transverse-momentum dependent parton distribution and double-dis

Gonçalo M. Correia, Vlad Niculae, André F. T. Martins

Attention mechanisms have become ubiquitous in NLP. Recent architectures, notably the Transformer, learn powerful context-aware word representations through layered, multi-headed attention. The multiple heads learn diverse types of word relationships. However, with standard softmax attention, all attention heads are dense, assigning a non-zero weight to all

G. Ramalho

The data associated with the electromagnetic excitations of the nucleon ($γ^\ast N \to N^\ast$) are usually parametrized by helicity amplitudes at the resonance $N^\ast$ rest frame. The properties of the $γ^\ast N \to N^\ast$ transition current at low $Q^2$ can be, however, better understood when expressed in terms of structure form factors, particularly nea

Timothy Cohen, Gilly Elor, Andrew J. Larkoski, Jesse Thaler

In this paper, we extend the collinear superspace formalism to include the full range of $\mathcal{N} = 1$ supersymmetric interactions. Building on the effective field theory rules developed in a companion paper - &#34;Navigating Collinear Superspace&#34; - we construct collinear superspace Lagrangians for theories with non-trivial $F$- and $D$-term auxiliar

Jens Stücker, Oliver Hahn, Raul E. Angulo, Simon D. M. White

At early times dark matter has a thermal velocity dispersion of unknown amplitude which, for warm dark matter models, can influence the formation of nonlinear structure on observable scales. We propose a new scheme to simulate cosmologies with a small-scale suppression of perturbations that combines two previous methods in a way that avoids the numerical art

Darius A. Faroughy, Jernej F. Kamenik, Nejc Košnik, Aleks Smolkovič

We analyze the prospects of probing the $CP$-odd $i \tilde κ\bar t γ^5 t h$ interaction at the LHC and its projected upgrades, the high-luminosity and high-energy LHC, directly using associated on-shell Higgs boson and top quark or top quark pair production. To this end we first construct a $CP$-odd observable based on top quark polarization in $W b \to t h$

Ivanna Escala, Karoline M. Gilbert, Evan N. Kirby, Jennifer Wojno

We measured [Fe/H] and [$α$/Fe] using spectral synthesis of low-resolution stellar spectroscopy for 70 individual red giant branch stars across four fields spanning the outer disk, Giant Stellar Stream (GSS), and inner halo of M31. Fields at M31-centric projected distances of 23 kpc in the halo, 12 kpc in the halo, 22 kpc in the GSS, and 26 kpc in the outer

Wolfgang Altmannshofer, Stefania Gori, Dean J. Robinson

Ultraviolet completions for axion-like particles (ALPs) lighter than the neutral pion generically induce ALP-neutral pion mixing, and are therefore sensitive to direct constraints on the mixing angle. For ALPs below the pion mass, we demonstrate that strong and novel bounds on the ALP-pion mixing angle can be extracted from existing rare pion decay data, mea

Suoqing Ji, T. K. Chan, Cameron B. Hummels, Philip F. Hopkins

We investigate the impact of cosmic rays (CRs) on the circumgalactic medium (CGM) in FIRE-2 simulations, for ultra-faint dwarf through Milky Way (MW)-mass halos hosting star-forming (SF) galaxies. Our CR treatment includes injection by supernovae, anisotropic streaming and diffusion along magnetic field lines, collisional and streaming losses, with constant

Pamela B Pyzza, Katherine A Newhall, Douglas Zhou, Gregor Kovacic

Early olfactory pathway responses to the presentation of an odor exhibit remarkably similar dynamical behavior across phyla from insects to mammals, and frequently involve transitions among quiescence, collective network oscillations, and asynchronous firing. We hypothesize that the time scales of fast excitation and fast and slow inhibition present in these

Shintaro Eijima, Ryuichiro Kitano, Wen Yin

The simplest possibility to explain the baryon asymmetry of the Universe is to assume that radiation is created asymmetrically between baryons and anti-baryons after the inflation. We propose a new mechanism of this kind where CP-violating flavor oscillations of left-handed leptons in the reheating era distribute the lepton asymmetries partially into the rig

Alexander Rietzler, Sebastian Stabinger, Paul Opitz, Stefan Engl

Aspect-Target Sentiment Classification (ATSC) is a subtask of Aspect-Based Sentiment Analysis (ABSA), which has many applications e.g. in e-commerce, where data and insights from reviews can be leveraged to create value for businesses and customers. Recently, deep transfer-learning methods have been applied successfully to a myriad of Natural Language Proces

Deanna M. Abrams, Nicolas Didier, Shane A. Caldwell, Blake R. Johnson

In the gate model of quantum computing, a program is typically decomposed into a sequence of 1- and 2-qubit gates that are realized as control pulses acting on the system. A key requirement for a scalable control system is that the qubits are addressable - that control pulses act only on the targeted qubits. The presence of control crosstalk makes this addre

Pascal Friederich, Artem Fediai, Jing Li, Anirban Mondal

Amorphous organic semiconductors based on small molecules and polymers are used in many applications, most prominently organic light emitting diodes (OLEDs) and organic solar cells. Impurities and charge traps are omnipresent in most currently available organic semiconductors and limit charge transport and thus device efficiency. The microscopic cause as wel

Anna Kuzina, Evgenii Egorov, Evgeny Burnaev

Variational autoencoder (VAE) is a deep generative model for unsupervised learning, allowing to encode observations into the meaningful latent space. VAE is prone to catastrophic forgetting when tasks arrive sequentially, and only the data for the current one is available. We address this problem of continual learning for VAEs. It is known that the choice of

Binbin Xu, Cédric Gil-Jardiné, Frantz Thiessard, Eric Tellier

To build a French national electronic injury surveillance system based on emergency room visits, we aim to develop a coding system to classify their causes from clinical notes in free-text. Supervised learning techniques have shown good results in this area but require a large amount of expert annotated dataset which is time consuming and costly to obtain. W

Davide Palitta

We show that the discrete operator stemming from the time and space discretization of evolutionary partial differential equations can be represented in terms of a single Sylvester matrix equation. A novel solution strategy that combines projection techniques with the full exploitation of the entry-wise structure of the involved coefficient matrices is propos

Peter Athron, Csaba Balazs, Andrew Fowlie, Giancarlo Pozzo

Motivated by the fact that the Next-to-Minimal Supersymmetric Standard Model is one of the most plausible models that can accommodate electroweak baryogenesis, we analyze its phase structure by tracing the temperature dependence of the minima of the effective potential. Our results reveal rich patterns of phase structure that end in the observed electroweak

S. A. R. Horsley, M. Woolley

Here we re-examine one of the most basic quantities in optics: the refractive index. Considering propagation in a plane, we first develop a general formalism for calculating the direction dependent refractive index in a general bi-anisotropic material. From this we derive the general condition for achieving zero refractive index in a given direction. We show

Benedict Leimkuhler, Charles Matthews, Tiffany Vlaar

Traditionally, neural networks are parameterized using optimization procedures such as stochastic gradient descent, RMSProp and ADAM. These procedures tend to drive the parameters of the network toward a local minimum. In this article, we employ alternative &#34;sampling&#34; algorithms (referred to here as &#34;thermodynamic parameterization methods&#34;) w

Yuri Bakhtin, Hong-Bin Chen

For a smooth vector field in a neighborhood of a critical point with all positive eigenvalues of the linearization, we consider the associated dynamics perturbed by white noise. Using Malliavin calculus tools, we obtain polynomial asymptotics for probabilities of atypically long exit times in the vanishing noise limit.

L. Caldwell, H. J. Williams, N. J. Fitch, J. Aldegunde

Polar molecules in superpositions of rotational states exhibit long-range dipolar interactions, but maintaining their coherence in a trapped sample is a challenge. We present calculations that show many laser-coolable molecules have convenient rotational transitions that are exceptionally insensitive to magnetic fields. We verify this experimentally for CaF

Anne-Sophie Himmel, Matthias Bentert, André Nichterlein, Rolf Niedermeier

Node connectivity plays a central role in temporal network analysis. We provide a comprehensive study of various concepts of walks in temporal graphs, that is, graphs with fixed vertex sets but edge sets changing over time. Taking into account the temporal aspect leads to a rich set of optimization criteria for &#34;shortest&#34; walks. Extending and signifi

Wanpeng Tan

Dark energy is interpreted as the leftover of mostly canceled vacuum energy due to the spontaneous mirror symmetry breaking (SMSB) at the electroweak phase transition. Based on the newly proposed mirror-matter model (M$^3$), the extended standard model with mirror matter (SM$^3$) is elaborated to provide a consistent foundation for understanding dark energy,

Erfan Yazdandoost Hamedani, Necdet Serhat Aybat

We propose decentralized primal-dual methods for cooperative multi-agent consensus optimization problems over both static and time-varying communication networks, where only local communications are allowed. The objective is to minimize the sum of agent-specific convex functions over conic constraint sets defined by agent-specific nonlinear functions; hence,

Shangbang Long, Yushuo Guan, Bingxuan Wang, Kaigui Bian

Reading text from natural images is challenging due to the great variety in text font, color, size, complex background and etc.. The perspective distortion and non-linear spatial arrangement of characters make it further difficult. While rectification based method is intuitively grounded and has pushed the envelope by far, its potential is far from being wel

Arash Badie-Modiri, Márton Karsai, Mikko Kivelä

Time-limited states characterise many dynamical processes on networks: disease infected individuals recover after some time, people forget news spreading on social networks, or passengers may not wait forever for a connection. These dynamics can be described as limited waiting-time processes, and they are particularly important for systems modelled as tempor

Nalin Bhardwaj, Antonio Molina Lovett, Bryce Sandlund

We consider the minimum cut problem in undirected, weighted graphs. We give a simple algorithm to find a minimum cut that $2$-respects (cuts two edges of) a spanning tree $T$ of a graph $G$. This procedure can be used in place of the complicated subroutine given in Karger&#39;s near-linear time minimum cut algorithm (J. ACM, 2000). We give a self-contained v

Rei Sato, Tetsuro Nikuni, Shohei Watabe

We investigate a quantum spatial search problem on fractal lattices, such as Sierpinski carpets and Menger sponges. In earlier numerical studies of the Sierpinski gasket, the Sierpinski tetrahedron, and the Sierpinski carpet, conjectures have been proposed for the scaling of a quantum spatial search problem finding a specific target, which is given in terms

Jaksa Vucicevic, Michel Ferrero

Diagrammatic expansions are a central tool for treating correlated electron systems. At thermal equilibrium, they are most naturally defined within the Matsubara formalism. However, extracting any dynamic response function from a Matsubara calculation ultimately requires the ill-defined analytical continuation from the imaginary- to the real-frequency domain

Dawei Huang, Seth Pettie, Yixiang Zhang, Zhijun Zhang

In this paper we explore fundamental problems in randomized communication complexity such as computing Set Intersection on sets of size $k$ and Equality Testing between vectors of length $k$. Sağlam and Tardos and Brody et al. showed that for these types of problems, one can achieve optimal communication volume of $O(k)$ bits, with a randomized protocol that

Alexander Mey, Marco Loog

In this work we investigate to which extent one can recover class probabilities within the empirical risk minimization (ERM) paradigm. The main aim of our paper is to extend existing results and emphasize the tight relations between empirical risk minimization and class probability estimation. Based on existing literature on excess risk bounds and proper sco

Ananya Gupta, Yao Peng, Simon Watson, Hujun Yin

A semantic feature extraction method for multitemporal high resolution aerial image registration is proposed in this paper. These features encode properties or information about temporally invariant objects such as roads and help deal with issues such as changing foliage in image registration, which classical handcrafted features are unable to address. These

Lech Duraj, Krzysztof Kleiner, Adam Polak, Virginia Vassilevska Williams

We define a natural class of range query problems, and prove that all problems within this class have the same time complexity (up to polylogarithmic factors). The equivalence is very general, and even applies to online algorithms. This allows us to obtain new improved algorithms for all of the problems in the class. We then focus on the special case of the

Vaiva Vasiliauskaite, Tim S. Evans

In this work we give a community detection algorithm in which the communities both respects the intrinsic order of a directed acyclic graph and also finds similar nodes. We take inspiration from classic similarity measures of bibliometrics, used to assess how similar two publications are, based on their relative citation patterns. We study the algorithm&#39;

Marianne Leitner

``Quasi-elliptic&#39;&#39; functions can be given a ring structure in two different ways, using either ordinary multiplication, or convolution. The map between the corresponding standard bases is calculated. A related structure has appeared recently in the computation of Feynman integrals. The two approaches are related by a sequence of polynomials closely t

Samuel Livingstone, Giacomo Zanella

There is a tension between robustness and efficiency when designing Markov chain Monte Carlo (MCMC) sampling algorithms. Here we focus on robustness with respect to tuning parameters, showing that more sophisticated algorithms tend to be more sensitive to the choice of step-size parameter and less robust to heterogeneity of the distribution of interest. We c

Kay Joerg Wiese, Andrei A. Fedorenko

Driven periodic elastic systems such as charge-density waves (CDWs) pinned by impurities show a non-trivial, glassy dynamical critical behavior. Their proper theoretical description requires the functional renormalization group. We show that their critical behavior close to the depinning transition is related to a much simpler model, $O(n)$-symmetric $ϕ^4$ t

Basant Lal Sharma

As an extension of the discrete Sommerfeld problems on lattices, the scattering of a time harmonic wave is considered on an infinite square lattice when there exists a pair of semi-infinite cracks or rigid constraints. Due to the presence of stagger, also called offset, in the alignment of the defect edges the asymmetry in the problem leads to a matrix Wiene

S. N. Klimin, H. Kurkjian, J. Tempere

The Leggett collective excitations for a two-band Fermi gas with s-wave pairing and Josephson interband coupling in the BCS-BEC crossover at finite temperatures are investigated within the Gaussian pair fluctuation approach. Eigenfrequencies and damping factors for Leggett modes are determined in a nonperturbative way, using the analytic continuation of the

Baptiste Battelier, Joël Bergé, Andrea Bertoldi, Luc Blanchet

We present the scientific motivation for future space tests of the equivalence principle, and in particular the universality of free fall, at the $10^{-17}$ level or better. Two possible mission scenarios, one based on quantum technologies, the other on electrostatic accelerometers, that could reach that goal are briefly discussed.

Steffen Betsch, Bruno Ebner, Bernhard Klar

We propose and investigate a new estimation method for the parameters of models consisting of smooth density functions on the positive half axis. The procedure is based on a recently introduced characterization result for the respective probability distributions, and is to be classified as a minimum distance estimator, incorporating as a distance function th

Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency

Transformer is a powerful architecture that achieves superior performance on various sequence learning tasks, including neural machine translation, language understanding, and sequence prediction. At the core of the Transformer is the attention mechanism, which concurrently processes all inputs in the streams. In this paper, we present a new formulation of a

Charlie Nation, Diego Porras

In this work we study a scenario where dynamics is restricted to a single excitation manifold, for particular physical observables with support in the manifold, which we label a `correlated quench&#39;. We ask how such dynamics may in general differ from predictions of the eigenstate thermalization hypothesis (ETH). We show that if thermalization occurs, it

Misha Verbitsky

A mapping class group of an oriented manifold is a quotient of its diffeomorphism group by the isotopies. In the published version of &#34;Mapping class group and a global Torelli theorem for hyperkahler manifolds&#34; I made an error based on a wrong quotation of Dennis Sullivan&#39;s famous paper &#34;Infinitesimal computations in topology&#34;. I claimed

Gongbo Tang, Rico Sennrich, Joakim Nivre

Neural machine translation (NMT) has achieved new state-of-the-art performance in translating ambiguous words. However, it is still unclear which component dominates the process of disambiguation. In this paper, we explore the ability of NMT encoders and decoders to disambiguate word senses by evaluating hidden states and investigating the distributions of s

Óscar Martín, Alberto Verdejo, Narciso Martí-Oliet

Rewriting logic is naturally concurrent: several subterms of the state term can be rewritten simultaneously. But state terms are global, which makes compositionality difficult to achieve. Compositionality here means being able to decompose a complex system into its functional components and code each as an isolated and encapsulated system. Our goal is to hel

Tianhong Wang, Vladimir Khudik, Gennady Shvets

Generation of highly collimated monoenergetic relativistic ion beams is one of the most challenging and promising areas in ultra-intense laser-matter interactions because of the numerous scientific and technological applications that require such beams. We address this challenge by introducing the concept of laser-ion lensing and acceleration (LILA). Using a