April 2019 arXiv papers — page 116

Marcin Pikus, Wen Xu

A distribution matcher (DM) encodes a binary input data sequence into a sequence of symbols (codeword) with desired target probability distribution. The set of the output codewords constitutes a codebook (or code) of a DM. Constant-composition DM (CCDM) uses arithmetic coding to efficiently encode data into codewords from a constant-composition (CC) codebook

T. Kalewicz, V. Bommier

Magnetic field vector measurements are always ambiguous, that is, two or more field vectors are solutions of the observed polarisation. The aim of the present paper is to solve the ambiguity by comparing the ambiguous field vectors obtained in the same prominence observed on two consecutive days. The effect of the solar rotation is to modify the scattering a

Junghyup Lee, Dohyung Kim, Jean Ponce, Bumsub Ham

We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category. We propose to use images annotated with binary foreground masks and subjected to synthetic geometric deformations to train a convolutional neural network (CNN) for this task. Using thes

Urs Frauenfelder

In this note we study critical points of a variation of the action functional of classical mechanics, where the Hamiltonian term is retarded. Following a more than hundert and fifty year old paper by Carl Neumann we as well introduce Taylor approximations to this functional in terms of the fine structure constant. We see how in first order in the fine struct

Xiangtai Li, Houlong Zhao, Lei Han, Yunhai Tong

Semantic segmentation generates comprehensive understanding of scenes through densely predicting the category for each pixel. High-level features from Deep Convolutional Neural Networks already demonstrate their effectiveness in semantic segmentation tasks, however the coarse resolution of high-level features often leads to inferior results for small/thin ob

Takahiro Nagaoka, Akiko Yazawa

Anari, Gharan, and Vinzant proved (complete) log-concavity of the basis generating functions for all matroids. From the viewpoint of combinatorial Hodge theory, it is natural to ask whether these functions are "strictly" log-concave for simple matroids. In this paper, we show this strictness for simple graphic matroids, that is, we show that Kirchhof

H. Feichtinger, K. Gröchenig, Kuijie Li, Baoxiang Wang

In this paper we develop a new way to study the global existence and uniqueness for the Navier-Stokes equation (NS) and consider the initial data in a class of modulation spaces $E^s_{p,q}$ with exponentially decaying weights $(s<0, \ 1<p,q<\infty)$ for which the norms are defined by $$ \|f\|_{E^s_{p,q}} = \left(\sum_{k\in \mathbb{Z}^d} 2^{s|k|q}\|\mathscr{F

Ty Nguyen, Shreyas S. Shivakumar, Ian D. Miller, James Keller

Real-time semantic image segmentation on platforms subject to size, weight and power (SWaP) constraints is a key area of interest for air surveillance and inspection. In this work, we propose MAVNet: a small, light-weight, deep neural network for real-time semantic segmentation on micro Aerial Vehicles (MAVs). MAVNet, inspired by ERFNet, features 400 times f

Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona

We study notions of fairness in decision-making systems when individuals have diverse preferences over the possible outcomes of the decisions. Our starting point is the seminal work of Dwork et al. which introduced a notion of individual fairness (IF): given a task-specific similarity metric, every pair of individuals who are similarly qualified according to

Daichi Nishio, Satoshi Yamane

End-to-end deep reinforcement learning has enabled agents to learn with little preprocessing by humans. However, it is still difficult to learn stably and efficiently because the learning method usually uses a nonlinear function approximation. Neural Episodic Control (NEC), which has been proposed in order to improve sample efficiency, is able to learn stabl

Daniel Bertrand, Bas Edixhoven

The Poincaré torsor of a Shimura family of abelian varieties can be viewed both as a family of semi-abelian varieties and as a mixed Shimura variety. We show that the special subvarieties of the latter cannot all be described in terms of the group subschemes of the former. This provides a counter-example to the relative Manin-Mumford conjecture, but also som

Yuning Chai

Recent advances in single-frame object detection and segmentation techniques have motivated a wide range of works to extend these methods to process video streams. In this paper, we explore the idea of hard attention aimed for latency-sensitive applications. Instead of reasoning about every frame separately, our method selects and only processes a small sub-

Yu-Cheng Chang, Bayan Karimi, Jorden Senior, Alberto Ronzani

Characterizing superconducting microwave resonators with highly dissipative elements is a technical challenge, but a requirement for implementing and understanding the operation of hybrid quantum devices involving dissipative elements, e.g. for thermal engineering and detection. We present experiments on $λ/4$ superconducting niobium coplanar waveguide (CPW)

Alireza Kashir, Hyeon-Woo Jeong, Gil-ho Lee, Pavlo Mikheenko

Here we systematically explore the use of pulsed laser deposition technique (PLD) to grow three basic oxides that have rocksalt structure but different chemical stability in the ambient atmosphere: NiO (stable), MnO (metastable) and EuO (unstable). By tuning laser fluence, an epitaxial single-phase nickel oxide thin-film growth can be achieved in a wide rang

Jinlu Li, Yanghai Yu, Zhaoyang Yin

In this paper, we derive a new smallness hypothesis of initial data for the three-dimensional incompressible Navier-Stokes equations. That is, we prove that there exist two positive constants $c_0,C_0$ such that if \begin{equation*} \|u_0^1+u^2_0,u^3_0\|_{\dot{B}_{p,1}^{-1+\frac{3}{p}}} \|u^1_0,u^2_0\|_{\dot{B}_{p,1}^{-1+\frac{3}{p}}} \exp\{C_0 (\|u_0\|^{2}_

D. Schumann, R. Dressler

We comment here on results of the project aimed at measuring the 7Be(n,x) reactions at SARAF, Israel, in 2016, posted by M. Gai in [arXiv:1812.09914v1] without the knowledge of parts of the collaboration and against the explicit veto of the collaborators and the administration of the Paul Scherrer Institut, Switzerland. We address both the experimental short

M. F. Araujo de Resende, J. P. Ibieta Jimenez, J. Lorca Espiro

In this paper, we investigate how it is possible to define a new class of lattice gauge models based on a dualization procedure of a previous generalization of the Kitaev Quantum Double Models. In the case of this previous generalization that will be used as a basis, it was defined by adding new qudits (which were denoted as matter fields in reference to som

Krishna Somandepalli, Naveen Kumar, Ruchir Travadi, Shrikanth Narayanan

We propose Deep Multiset Canonical Correlation Analysis (dMCCA) as an extension to representation learning using CCA when the underlying signal is observed across multiple (more than two) modalities. We use deep learning framework to learn non-linear transformations from different modalities to a shared subspace such that the representations maximize the rat

Atsuhiro Noguchi, Tatsuya Harada

Thanks to the recent development of deep generative models, it is becoming possible to generate high-quality images with both fidelity and diversity. However, the training of such generative models requires a large dataset. To reduce the amount of data required, we propose a new method for transferring prior knowledge of the pre-trained generator, which is t

Peng Zhou, Long Mai, Jianming Zhang, Ning Xu

Incremental learning targets at achieving good performance on new categories without forgetting old ones. Knowledge distillation has been shown critical in preserving the performance on old classes. Conventional methods, however, sequentially distill knowledge only from the last model, leading to performance degradation on the old classes in later incrementa

Chuanan Wei

In terms of the difference operators, we establish several curious transformation and summation formulas for basic hypergeometric series. When the parameters are specified, they produce $q$-analogues of Ramanujan&#39;s three series for 1/$π$ and other eleven nice $π$-formulas. Meanwhile, $q$-analogues of three beautiful series for $ζ(3)$ are also given in th

Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy

Self-supervised learning has become increasingly important to leverage the abundance of unlabeled data available on platforms like YouTube. Whereas most existing approaches learn low-level representations, we propose a joint visual-linguistic model to learn high-level features without any explicit supervision. In particular, inspired by its recent success in

Constantinos Kalapotharakos, Alice K. Harding, Demosthenes Kazanas, Zorawar Wadiasingh

We show that the $γ$-ray pulsar observables, i.e., their total $γ$-ray luminosity, $L_γ$, spectral cut-off energy, $ε_{\rm cut}$, stellar surface magnetic field, $B_{\star}$, and spin-down power $\dot{\mathcal{E}}$, obey a relation of the form $L_γ=f(ε_{\rm cut},B_{\star},\dot{\mathcal{E}})$, which represents a 3D plane in their 4D log-space. Fitting the dat

Zijun Gao, Yanjun Han, Zhimei Ren, Zhengqing Zhou

In this paper, we study the multi-armed bandit problem in the batched setting where the employed policy must split data into a small number of batches. While the minimax regret for the two-armed stochastic bandits has been completely characterized in \cite{perchet2016batched}, the effect of the number of arms on the regret for the multi-armed case is still o

Yudong Cui, Ruizhi Yang, Xinbo He, P. H. Thomas Tam

The supernova remnant (SNR) HESS J1731-347 is a young SNR which displays a non-thermal X-ray and TeV shell structure. A molecular cloud at a distance of 3.2 kpc is spatially coincident with the western part of the SNR, and it is likely hit by the SNR. The X-ray emission from this part of the shell is much lower than from the rest of the SNR. Moreover, a comp

Lipu Zhou, Shengze Wang, Jiamin Ye, Michael Kaess

Estimating pose from given 3D correspondences, including point-to-point, point-to-line and point-to-plane correspondences, is a fundamental task in computer vision with many applications. We present a complete solution for this task, including a solution for the minimal problem and the least-squares problem of this task. Previous works mainly focused on find

Lin Wu, Richang Hong, Yang Wang, Meng Wang

Person re-identification (re-ID) is a task of matching pedestrians under disjoint camera views. To recognise paired snapshots, it has to cope with large cross-view variations caused by the camera view shift. Supervised deep neural networks are effective in producing a set of non-linear projections that can transform cross-view images into a common feature sp

Benjamin Loriot, Fernanda Madeiral, Martin Monperrus

Ensuring the consistent usage of formatting conventions is an important aspect of modern software quality assurance. While formatting convention violations can be automatically detected by format checkers implemented in linters, there is no satisfactory solution for repairing them. Manually fixing formatting convention violations is a waste of developer time

Haoting Xu, Zhiqi Huang, Na Zhang, Yundong Jiang

When photons from distant galaxies and stars pass through our neighboring environment, the wavelengths of the photons would be shifted by our local gravitational potential. This local gravitational redshift effect can potentially have an impact on the measurement of cosmological distance-redshift relation. Using available supernovae data, Wojtak et al [1] fo

Ting Sun, Lei Tai, Zhihan Gao, Ming Liu

This paper proposes a novel weakly-supervised semantic segmentation method using image-level label only. The class-specific activation maps from the well-trained classifiers are used as cues to train a segmentation network. The well-known defects of these cues are coarseness and incompleteness. We use super-pixel to refine them, and fuse the cues extracted f

Jin-Ren Yao, Hua-Jun Zhang, Ruo-Nan Wang, Jian-Dong Cai

Light influenced by the turbulent ocean can be fully characterized with the help of the power spectrum of the water&#39;s refractive index fluctuations, resulting from the combined effect of two scalars, temperature and salinity concentration advected by the velocity field. The Nikishovs&#39; model [ Fluid Mech. Res. 27, 8298 (2000)] frequently used in the a

Naotomo Takemura, Masato Takiguchi, Masaya Notomi

Nanocavity lasers are commonly characterized by the spontaneous coupling coefficient $β$ that represents the fraction of photons emitted into the lasing mode. While $β$ is conventionally discussed in semiconductor lasers where the photon lifetime is much shorter than the carrier lifetime (class-B lasers), little is known about $β$ in atomic lasers where the

Javier Hernandez-Ortega, Javier Galbally, Julian Fierrez, Rudolf Haraksim

In this paper we develop a Quality Assessment approach for face recognition based on deep learning. The method consists of a Convolutional Neural Network, FaceQnet, that is used to predict the suitability of a specific input image for face recognition purposes. The training of FaceQnet is done using the VGGFace2 database. We employ the BioLab-ICAO framework

Zheng Zhang, Guo-sen Xie, Yang Li, Sheng Li

Due to its low storage cost and fast query speed, hashing has been recognized to accomplish similarity search in large-scale multimedia retrieval applications. Particularly supervised hashing has recently received considerable research attention by leveraging the label information to preserve the pairwise similarities of data points in the Hamming space. How

S. James Gates,, Yangrui Hu, Kory Stiffler

An adinkra is a graph-theoretic representation of spacetime supersymmetry. Minimal four-color valise adinkras have been extensively studied due to their relations to minimal 4D, $\cal N$ = 1 supermultiplets. Valise adinkras, although an important subclass, do not encode all the information present when a 4D supermultiplet is reduced to 1D. Eigenvalue equival

Jianbo Lu, Yan Wang, Xin Zhao

The generalized Brans-Dicke (abbreviated as GBD) theory is obtained by replacing the Ricci scalar $R$ in the original Brans-Dicke (BD) action with an arbitrary function $f(R)$. Comparing with other theories, some interesting properties have been found or some problems existing in other theories could be solved in the GBD theory. For example, (1) the state pa

Sheeraz A. Alvi, Xiangyun Zhou, Salman Durrani, Duy T. Ngo

In this paper, we propose joint sequencing and scheduling optimization for uplink machine-type communication (MTC). We consider multiple energy-constrained MTC devices that transmit data to a base station following the time division multiple access (TDMA) protocol. Conventionally, the energy efficiency performance in TDMA is optimized through multi-user sche

Koji Tsukuda

Let $K(=K_{n,θ})$ be a positive integer-valued random variable whose distribution is given by ${\rm P}(K = x) = \bar{s}(n,x) θ^x/(θ)_n$ $(x=1,\ldots,n) $, where $θ$ is a positive number, $n$ is a positive integer, $(θ)_n=θ(θ+1)\cdots(θ+n-1)$ and $\bar{s}(n,x)$ is the coefficient of $θ^x$ in $(θ)_n$ for $x=1,\ldots,n$. This formula describes the distribution

Riddhipratim Basu, Shirshendu Ganguly, Alan Hammond

In last passage percolation models lying in the Kardar-Parisi-Zhang universality class, maximizing paths that travel over distances of order $n$ accrue energy that fluctuates on scale $n^{1/3}$; and these paths deviate from the linear interpolation of their endpoints on scale $n^{2/3}$. These maximizing paths and their energies may be viewed via a coordinate

Yifan Jing, Souktik Roy, Chieu-Minh Tran

We begin a generalized study of sum-product type phenomenon in different fields by considering pairs $P(x,y)$ and $Q(x,y)$ of two variable polynomials that simultaneously exhibit small symmetric expansion. Our first result is that such $P(x,y)$ and $Q(x,y)$ over $\mathbb{R}$ and $\mathbb{C}$ have very similar structure, obtained by employing semi-algebraic g

Roshan Gopalakrishnan, Yansong Chua, Ashish Jith Sreejith Kumar

The hardware-software co-optimization of neural network architectures is becoming a major stream of research especially due to the emergence of commercial neuromorphic chips such as the IBM Truenorth and Intel Loihi. Development of specific neural network architectures in tandem with the design of the neuromorphic hardware considering the hardware constraint

Sophie Crommelinck, Mila Koeva, Michael Ying Yang, George Vosselman

The extraction of object outlines has been a research topic during the last decades. In spite of advances in photogrammetry, remote sensing and computer vision, this task remains challenging due to object and data complexity. The development of object extraction approaches is promoted through publically available benchmark datasets and evaluation frameworks.

Li Chen

My research lies in the intersection of security and machine learning. This overview summarizes one component of my research: combining computer vision with malware exploit detection for enhanced security solutions. I will present the perspectives of efficacy, reliability and resiliency to formulate threat detection as computer vision problems and develop st

Alison Callahan, Jason A Fries, Christopher Ré, James I Huddleston

Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real world evidence to assess device safety and track device-related patient outcomes over time. However, distilling this evidence remains challenging, as information is fractured acros

Huatian Wang, Qinbing Fu, Hongxin Wang, Jigen Peng

Insects use visual information to estimate angular velocity of retinal image motion, which determines a variety of flight behaviours including speed regulation, tunnel centring and visual navigation. For angular velocity estimation, honeybees show large spatial-independence against visual stimuli, whereas the previous models have not fulfilled such an abilit

V. N. Smolyaninova, W. Korzi, W. Zimmerman, S. Searfoss

Recent experiments have demonstrated that the superconducting critical temperature may be improved in various metamaterial superconductor geometries. Here, we present the results of a study of tin-based metamaterial superconductors in the epsilon-near-zero (ENZ) and hyperbolic metamaterial configurations. It was observed that Tc enhancement is significantly

Valeriy V. Dvoeglazov

In the present article we investigate the spin-1/2 and spin-1 cases in different bases. Next, we look for relations with the Majorana-like field operator. We show explicitly incompatibility of the Majorana anzatzen with the Dirac-like field operators in both the original Majorana theory and its generalizations. Several explicit examples are presented for hig

Valeriy V. Dvoeglazov

We discuss relations between Dirac and Majorana-like field operators with self/antiself charge-conjugate states. The connections with recent models of several authors were found. KEYWORDS: Dirac; field operators; Majorana; Neutral particles; QFT.

Jan Kocoń, Michał Gawor

The article introduces a new set of Polish word embeddings, built using KGR10 corpus, which contains more than 4 billion words. These embeddings are evaluated in the problem of recognition of temporal expressions (timexes) for the Polish language. We described the process of KGR10 corpus creation and a new approach to the recognition problem using Bidirectio

Newlyn N. Joseph, Raktim N. Roy, Thomas A. Steitz

Summary: The advent of Web-based tools that assist in the analysis and visualization of macromolecules require application programming interfaces (APIs) designed for modern web frameworks. To this end, we have developed a Node.js module pdbmine that allows any user to generate faster data-request queries to the RCSB Protein Data Bank (PDB). This JavaScript A

I. K. Mirzoeva, S. G. Chefranov

Data obtained in the framework of the INTERBALL-Tail Probe (1995-2000) and RHESSI (from 2002 to the present) projects have revealed variations in the X-ray intensity of the solar corona in the photon energy range of 2-15 keV during the period of the quiet Sun. Previously, a hypothesis was proposed that this phenomenon could be associated with the effect of c

Maya Mohsin Ahmed

In this article, we prove that every integer can be written as an integer combination of exactly 4 tetrahedral numbers. Moreover, we compute the modular periodicity of platonic numbers.

Renchi Yang, Xiaokui Xiao, Zhewei Wei, Sourav S Bhowmick

Given an undirected graph G and a seed node s, the local clustering problem aims to identify a high-quality cluster containing s in time roughly proportional to the size of the cluster, regardless of the size of G. This problem finds numerous applications on large-scale graphs. Recently, heat kernel PageRank (HKPR), which is a measure of the proximity of nod

Noelia Oses, Aritz Legarretaetxebarria, Marco Quartulli, Igor García

Industrial process control systems try to keep an output variable within a given tolerance around a target value. PID control systems have been widely used in industry to control input variables in order to reach this goal. However, this kind of Transfer Function based approach cannot be extended to complex processes where input data might be non-numeric, hi

A. Indra, S. Mukherjee, S. Majumdar, O. Gutowski

The high-temperature ferroelectric order and a remarkable magnetoelectric effect driven by the magnetic field cooling are reported in R2BaCuO5 (R = Er, Dy, Sm) series. The ferroelectric (FE) orders are observed at much higher temperatures than their magnetic orders for all three members. The value of FE Curie temperature (TFE) is considerably high as ~ 235 K

Lakshya Malhotra, Robert Golub, Eva Kraegeloh, Nima Nouri

A relativistic particle undergoing successive boosts which are non collinear will experience a rotation of its coordinate axes with respect to the boosted frame. This rotation of coordinate axes is caused by a relativistic phenomenon called Thomas Rotation. We assess the importance of Thomas rotation in the calculation of physical quantities like electromagn

Kasthuri Jayarajah, Vigneshwaran Subbaraju, Noel Athaide, Lakmal Meegahapola

With the increased focus on making cities &#34;smarter&#34;, we see an upsurge in investment in sensing technologies embedded in the urban infrastructure. The deployment of GPS sensors aboard taxis and buses, smartcards replacing paper tickets, and other similar initiatives have led to an abundance of data on human mobility, generated at scale and available

Vincent Sacksteder

The GW Approximation is an ab initio approach to calculating electronic structure which avoids using the Local Density (LDA) Approximation, the Generalized Gradient (GGA) Approximation, or similar density functionals. It goes beyond the Hartree-Fock approximation by including screening and excited state effects, and shares conceptual similarities with MP2 an

Olga Kuryatnikova, Juan C. Vera

The seminal theorem of I.J. Schoenberg characterizes positive definite (p.d.) kernels on the unit sphere $S^{n-1}$ invariant under the automorphisms of the sphere. We obtain two generalizations of this theorem for p.d. kernels on fiber bundles. Our first theorem characterizes invariant p.d. kernels on bundles whose fiber is a product of a compact set and the

V. Bouet, A. Y. Klimenko

The present work investigates clustering of a graph-based representation of industrial connections derived from international trade data by Hidalgo et al (2007) and confirms existence of around ten industrial clusters that are reasonably consistent with expected historical patterns of diffusion of innovation and technology. This supports the notion that tech

Sándor Bozóki

The eccentric pie chart, a generalization of the traditional pie chart is introduced. An arbitrary point is fixed within the circle and rays are drawn from it. A sector is bounded by a pair of neighboring rays and the arc between them, The sector&#39;s area, aimed to be equal to a given proportion, is calculated from some well known equations in coordinate g

Placido Mursia, Italo Atzeni, David Gesbert, Mari Kobayashi

Multicast services, whereby a common valuable message needs to reach a whole population of user equipments (UEs), are gaining attention on account of new applications such as vehicular networks. As it proves challenging to guarantee decodability by every UE in a large population, service reliability is indeed the Achilles&#39; heel of multicast transmissions

Eric Heim

Generative Adversarial Networks (GANs) have received a great deal of attention due in part to recent success in generating original, high-quality samples from visual domains. However, most current methods only allow for users to guide this image generation process through limited interactions. In this work we develop a novel GAN framework that allows humans

Pavel Rojtberg, Benjamin Audenrith

We connect X3D to the state of the art OGRE renderer using our prototypical x3ogre implementation. At this we perform a comparison of both on a conceptual level, highlighting similarities and differences. Our implementation allows swapping X3D concepts for OGRE concepts and vice versa. We take advantage of this to analyse current shortcomings in X3D and prop

Xi-Wen Guan, Feng He

In the 60&#39;s Professor Chen Ping Yang with Professor Chen Ning Yang published several seminal papers on the study of Bethe&#39;s hypothesis for various problems of physics. The works on the lattice gas model, critical behaviour in liquid-gas transition, the one-dimensional (1D) Heisenberg spin chain, and the thermodynamics of 1D delta-function interacting

Youren Hu, Xiao-Shan Gao

In this paper, the tropical differential Gröbner basis is studied, which is a natural generalization of the tropical Gröbner basis to the recently introduced tropical differential algebra. Like the differential Gröbner basis, the tropical differential Gröbner basis generally contains an infinite number of elements. We give a Buchberger style criterion for th

Scott Mills, Anna Gura, Kenji Watanabe, Takashi Taniguchi

The ability to localize and manipulate individual quasiparticles in mesoscopic structures is critical in experimental studies of quantum mechanics and thermodynamics, and in potential quantum information devices, e.g., for topological schemes of quantum computation. In strong magnetic field, the quantum Hall edge modes can be confined around the circumferenc

V. V. Flambaum, I. B. Samsonov, H. B. Tran Tan

Dark photon is a massive vector particle which couples to the physical photon through the kinetic mixing term. Such particles, if exist, are produced in photon beams and, in particular, in laser radiation. Due to the oscillations between the physical photon and the dark photon, the latter may be, in principle, detected in the light-shining-through-a-wall exp

Ryan E. Scott, Paul M. Alsing, A. Matthew Smith, Michael L. Fanto

We propose a scalable version of a KLM CNOT gate based upon integrated waveguide microring resonators (MRR), vs the original KLM-approach using beam splitters (BS). The core element of our CNOT gate is a nonlinear phase-shift gate (NLPSG) using three MRRs, which we examine in detail. We find an expanded parameter space for the NLPSG over that of the conventi

C. Bouratzis, A. Hillaris, C. E. Alissandrakis, P. Preka-Papadema

Aims. We examined the characteristics of isolated intermediate drift bursts (IMDs) and their morphologies on dynamic spectra, in particular the positioning of emission and absorption ridges and the repetition rate of fiber groups. These were compared with a model in order to determine the conditions under which the IMDs appear and exhibit the above character

L. Duong, M. Asplund, D. M. Nataf, K. C. Freeman

This work explores the detailed chemistry of the Milky Way bulge using the HERMES spectrograph on the Anglo-Australian Telescope. Here we present the abundance ratios of 13 elements for 832 red giant branch and clump stars along the minor bulge axis at latitudes $b=-10^{\circ}, -7.5$ and $-5^{\circ}$. Our results show that none of the abundance ratios vary s

Andrei Jaikin-Zapirain, Mark Shusterman

We confirm the Hanna Neumann conjecture for topologically finitely generated closed subgroups $U$ and $W$ of a nonsolvable Demushkin group $G$. Namely, we show that \begin{equation*} \sum_{g \in U \backslash G/W} \bar d(U \cap gWg^{-1}) \leq \bar d(U) \bar d(W) \end{equation*} where $\bar d(K) = \max\{d(K) - 1, 0\}$ and $d(K)$ is the least cardinality of a t

Ayush Saurabh, Tanmay Vachaspati

The interaction of a magnetic monopole-antimonopole pair depends on their separation as well as on a second &#34;twist&#34; degree of freedom. This novel interaction leads to a non-trivial bound state solution known as a sphaleron and to scattering in which the monopole-antimonopole bounce off each other and do not annihilate. The twist degree of freedom als

Gyuho Song, Vladislav Borisov, William R. Meier, Mingyu Xu

Intermetallic compounds possess unique atomic arrangements that often lead to exceptional material properties, but their extreme brittleness usually causes fracture at a limited strain of less than 1% and prevents their practical use. Therefore, it is critical for them to exhibit either plasticity or some form of structural transition to absorb and release a

Jesper Sören Dramsch, Gustavo Corte, Hamed Amini, Colin MacBeth

Geoscience data often have to rely on strong priors in the face of uncertainty. Additionally, we often try to detect or model anomalous sparse data that can appear as an outlier in machine learning models. These are classic examples of imbalanced learning. Approaching these problems can benefit from including prior information from physics models or transfor

Alex Alspach, Kunimatsu Hashimoto, Naveen Kuppuswamy, Russ Tedrake

Incorporating effective tactile sensing and mechanical compliance is key towards enabling robust and safe operation of robots in unknown, uncertain and cluttered environments. Towards realizing this goal, we present a lightweight, easy-to-build, highly compliant dense geometry sensor and end effector that comprises an inflated latex membrane with a depth sen

Lajos Horváth, Curtis Miller, Gregory Rice

A new class of change point test statistics is proposed that utilizes a weighting and trimming scheme for the cumulative sum (CUSUM) process inspired by Rényi (1953). A thorough asymptotic analysis and simulations both demonstrate that this new class of statistics possess superior power compared to traditional change point statistics based on the CUSUM proce

Joseph Paki, Hanna Terletska, Sergei Iskakov, Emanuel Gull

We study the extended Hubbard model on a two-dimensional half-filled square lattice using the dynamical cluster approximation. We present results on the phase boundaries between the paramagnetic metallic (normal) state and the insulating antiferromagnetic state, as well as between the antiferromagnetic and charge order states. We find hysteresis along the an

Wei-Cheng Huang

Thakur (2010) showed that, for $r,$ $s\in \mathbb{N}$, a product of two Carlitz zeta values $ζ_A(r)$ and $ζ_A(s)$ can be expressed as an $\mathbb{F}_p$-linear combination of $ζ_A(r+s)$ and double zeta values of weight $r+s$. Such an expression is called shuffle relation by Thakur. Fixing $r,$ $s\in \mathbb{N}$, we construct a $t$-module $E&#39;$. To determin

Madhavan Varadarajan

Two desireable properties of a quantum dynamics for Loop Quantum Gravity (LQG) are that its generators provide an anomaly free representation of the classical constraint algebra and that physical states which lie in the kernel of these generators encode propagation. A physical state in LQG is expected to be a sum over graphical $SU(2)$ spin network states. B

Hikaru Omori, Mamoru Komachi

An event-noun is a noun that has an argument structure similar to a predicate. Recent works, including those considered state-of-the-art, ignore event-nouns or build a single model for solving both Japanese predicate argument structure analysis (PASA) and event-noun argument structure analysis (ENASA). However, because there are interactions between predicat

Emily E Storey, Amr S. Helmy

Raman spectroscopy&#39;s capability to provide meaningful composition predictions is heavily reliant on a pre-processing step to remove insignificant spectral variation. This is crucial in biofluid analysis. Widespread adoption of diagnostics using Raman requires a robust model which can withstand routine spectra discrepancies due to unavoidable variations s

Adam Nyberg, Abdelrahman Eldesokey, David Bergström, David Gustafsson

Thermal Infrared (TIR) cameras are gaining popularity in many computer vision applications due to their ability to operate under low-light conditions. Images produced by TIR cameras are usually difficult for humans to perceive visually, which limits their usability. Several methods in the literature were proposed to address this problem by transforming TIR i

Xuhao Chen

Efficient Graph processing is challenging because of the irregularity of graph algorithms. Using GPUs to accelerate irregular graph algorithms is even more difficult to be efficient, since GPU&#39;s highly structured SIMT architecture is not a natural fit for irregular applications. With lots of previous efforts spent on subtly mapping graph algorithms onto

Alan C. Calder, Don E. Willcox, Christopher J. DeGrendele, Desmond Shangase

Thermonuclear (type Ia) supernovae are bright stellar explosions with the unique property that the light curves can be standardized, allowing them to be used as distance indicators for cosmological studies. Many fundamental questions bout these events remain, however. We provide a critique of our present understanding of these and present results of simulati

Alexander Peysakhovich, Christian Kroer, Adam Lerer

We consider the problem of using logged data to make predictions about what would happen if we changed the `rules of the game&#39; in a multi-agent system. This task is difficult because in many cases we observe actions individuals take but not their private information or their full reward functions. In addition, agents are strategic, so when the rules chan

Maria Chiara Angelini, Federico Ricci-Tersenghi

The effectiveness of stochastic algorithms based on Monte Carlo dynamics in solving hard optimization problems is mostly unknown. Beyond the basic statement that at a dynamical phase transition the ergodicity breaks and a Monte Carlo dynamics cannot sample correctly the probability distribution in times linear in the system size, there are almost no predicti

Andrew Torok, Matthew Nicol

We consider exponential large deviations estimates for unbounded observables on uniformly expanding dynamical systems. We show that uniform expansion does not imply the existence of a rate function for unbounded observables no matter the tail behavior of the cumulative distribution function. We give examples of unbounded observables with exponential decay of

Sebastian Burciu

A criterion for Müger centralizer of a fusion subcategory of a braided non-degenerate fusion category is given. Along the way we extend some identities on the space of class functions of a fusion category introduced by Shimizu in \cite{scalg}. We also show that in a modular tensor category the product of two conjugacy class sums is a linear combination of co

Erik Conser, Kennedy Hahn, Chandler M. Watson, Melanie Mitchell

We revisit a particular visual grounding method: the &#34;Image Retrieval Using Scene Graphs&#34; (IRSG) system of Johnson et al. (2015). Our experiments indicate that the system does not effectively use its learned object-relationship models. We also look closely at the IRSG dataset, as well as the widely used Visual Relationship Dataset (VRD) that is adapt

T. Goldman, G. J. Stephenson,

We follow the example of Cabibbo by revising the Standard Model (SM) to present a universal mass structure for fermions. A universal Higgs coupling for each species of fundamental fermions moves the SM towards a Theory of Matter, albeit without correctly describing the observed mass spectrum. It exposes a need for a complete Theory of Matter to include compo

Antonio Pereyra, Julio C. Tello

We present the first scientific results of the program on short term period variable stars observed using the OAUNI facility at the peruvian Andes. These results include good quality light curves of delta Scuti stars, rapidly oscillating stars along with eclipsing and cataclysmic binaries. The photometric precision reached by the available instrumental and e

Elena Castilla, Abhik Ghosh, Nirian Martin, Leandro Pardo

Analyzing polytomous response from a complex survey scheme, like stratified or cluster sampling is very crucial in several socio-economics applications. We present a class of minimum quasi weighted density power divergence estimators for the polytomous logistic regression model with such a complex survey. This family of semiparametric estimators is a robust

Peter Weiderer, Ana Maria Tomé, Elmar Wolfgang Lang

During the fabrication of casting parts sensor data is typically automatically recorded and accumulated for process monitoring and defect diagnosis. As casting is a thermal process with many interacting process parameters, root cause analysis tends to be tedious and ineffective. We show how a decomposition based on non-negative matrix factorization (NMF), wh

Hanchao Li, Pengfei Xiong, Haoqiang Fan, Jian Sun

This paper introduces an extremely efficient CNN architecture named DFANet for semantic segmentation under resource constraints. Our proposed network starts from a single lightweight backbone and aggregates discriminative features through sub-network and sub-stage cascade respectively. Based on the multi-scale feature propagation, DFANet substantially reduce

Oliver Adams, Matthew Wiesner, Shinji Watanabe, David Yarowsky

We report on adaptation of multilingual end-to-end speech recognition models trained on as many as 100 languages. Our findings shed light on the relative importance of similarity between the target and pretraining languages along the dimensions of phonetics, phonology, language family, geographical location, and orthography. In this context, experiments demo

Audrey Thirouin, Scott S. Sheppard

We present a survey on the rotational and physical properties of the dynamically low inclination Cold Classical trans-Neptunian objects. The Cold Classicals (CCs) are primordial planetesimals and contain relevant information about the early phase of our Solar System and planet formation over the first 100 million years after the formation of the Sun. Our pro

Gabriel V. de la Cruz, Yunshu Du, Matthew E. Taylor

Deep Reinforcement Learning (DRL) algorithms are known to be data inefficient. One reason is that a DRL agent learns both the feature and the policy tabula rasa. Integrating prior knowledge into DRL algorithms is one way to improve learning efficiency since it helps to build helpful representations. In this work, we consider incorporating human knowledge to

David Hartmann, Michael Wand

A plethora of recent research has focused on improving the memory footprint and inference speed of deep networks by reducing the complexity of (i) numerical representations (for example, by deterministic or stochastic quantization) and (ii) arithmetic operations (for example, by binarization of weights). We propose a stochastic binarization scheme for deep n

Cheng-Zhen Wang, Chen-Di Han, Hong-Ya Xu, Ying-Cheng Lai

The geometric or Berry phase, a characteristic of quasiparticles, is fundamental to the underlying quantum materials. The discoveries of new materials at a rapid pace nowadays call for efficient detection of the Berry phase. Utilizing $α$-T$_3$ lattice as a paradigm, we find that, in the Dirac electron optics regime, the semiclassical decay of the quasiparti