November 2018 arXiv papers — page 50

A. Ya. Maltsev, S. P. Novikov

The paper is devoted to the questions connected with the investigation of the S.P. Novikov problem of the description of the geometry of level lines of quasiperiodic functions on a plane with different numbers of quasiperiods. We consider here the history of the question, the current state of research in this field, and a number of applications of this probl

Samaneh Siyar, Hamed Azarnoush, Saeid Rashidi, Alexandre Winkler-Schwartz

Background: Virtual reality simulators and machine learning have the potential to augment understanding, assessment and training of psychomotor performance in neurosurgery residents. Objective: This study outlines the first application of machine learning to distinguish "skilled" and "novice" psychomotor performance during a virtual reality neurosurgical tas

Anne-Caroline Genix, Guilhem P. Baeza, Julian Oberdisse

A large body of experimental work on the microstructure and dynamics of simplifiedindustrial nanocomposites made of disordered silica filler in a styrene-butadiene matrixby solid-phase mixing is regrouped and critically discussed in this feature article. Recentresults encompass systems with varying polymer mass, grafting functionality, and fillercontent. The

Frank Kutzschebauch, Pierre-Marie Poloni

We enlarge the class of open Riemann surfaces known to be holomorphically embeddable into the plane by allowing them to have additional isolated punctures compared to the known embedding results.

Stefan Thurner

Can we describe social systems quantitatively and predictively, when we know all the actions, interactions, and states of individuals? We interpret human societies as co-evolutionary systems of individuals and their interactions. Based on unique data of a society of computer game players, where all actions and interactions between all players are known, we s

Mike Shengbo Wang, Will J. Percival, Santiago Avila, Robert Crittenden

Likelihood fitting to two-point clustering statistics made from galaxy surveys usually assumes a multivariate normal distribution for the measurements, with justification based on the central limit theorem given the large number of overdensity modes. However, this assumption cannot hold on the largest scales where the number of modes is low. Whilst more accu

Antonio Gilardi, Pasquale Arpaia, Luca De Vito, Olav E. Berrig

In particle accelerator components, parasitic resonances must be reduced because they heat up the equipment and cause beam instabilities. In this paper, a method for designing and characterizing Higher Order Mode (HOM) couplers for reducing such resonances in a broad bandwidth is proposed. A case study is considered for a specific component, called QuattroTa

Dionysios Anninos, Damián A. Galante, Diego M. Hofman

We explore asymptotically AdS$_2$ solutions of a particular two-dimensional dilaton-gravity theory. In the deep interior, these solutions flow to the cosmological horizon of dS$_2$. We calculate various matter perturbations at the linearised and non-linear level. We consider both Euclidean and Lorentzian perturbations. The results can be used to characterise

Rohit Gandikota, Deepak Mishra

Convolution Neural Networks is one of the most powerful tools in the present era of science. There has been a lot of research done to improve their performance and robustness while their internal working was left unexplored to much extent. They are often defined as black boxes that can map non-linear data very effectively. This paper tries to show how CNN ha

Soren Galatius, Oscar Randal-Williams

We survey recent work on moduli spaces of manifolds with an emphasis on the role played by (stable and unstable) homotopy theory. The theory is illustrated with several worked examples.

Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling

In this paper, we analyze the effects of depth and width on the quality of local minima, without strong over-parameterization and simplification assumptions in the literature. Without any simplification assumption, for deep nonlinear neural networks with the squared loss, we theoretically show that the quality of local minima tends to improve towards the glo

Anton Kolonin, Ben Goertzel, Deborah Duong, Matt Ikle

Understanding the principles of consensus in communities and finding ways to optimal solutions beneficial for entire community becomes crucial as the speeds and scales of interaction in modern distributed systems increase. Such systems can be both social and information computer networks that unite the masses of people as well as multi-agent computing platfo

Ashutosh Tripathi, Sourabh Nampalliwar, Askar B. Abdikamalov, Dimitry Ayzenberg

Astrophysical black hole systems are the ideal laboratories for testing Einstein's theory of gravity in the strong field regime. We have recently developed a framework which uses the reflection spectrum of black hole systems to perform precision tests of general relativity by testing the Kerr black hole hypothesis. In this paper, we analyze XMM-Newton and Nu

Luigi Grasselli, Michele Mulazzani

We introduce a representation via (n+1)-colored graphs of compact n-manifolds with (possibly empty) boundary, which appears to be very convenient for computer aided study and tabulation. Our construction is ageneralization to arbitrary dimension of the one recently given by Cristofori and Mulazzani in dimension three, and it is dual to the one given by Pezza

I. F. Shaikhislamov, M. L. Khodachenko, H. Lammer, A. G. Berezutsky

We present a 3D fully selfconsistent multi-fluid hydrodynamic aeronomy model to study the structure of a hydrogen dominated expanding upper atmosphere around the hot Jupiter HD 209458b and the warm Neptune GJ 436b. In comparison to previous studies with 1D and 2D models, the present work finds such 3D features as zonal flows in upper atmosphere reaching up t

Loe Schlicher, Marco Slikker, Willem van Jaarsveld

We study under which circumstances Departments of Defenses should be willing to deploy a joint parts part pooling program for their major weapon systems. Using cooperative game theory and Markov Decision Processes, we demonstrate that the type of pooling strategy plays a crucial role in the success of such a joint spare parts pool. More precisely, we show th

Yannick Mvondo-She, Konstantinos Zoubos

Three-dimensional Topologically Massive Gravity at its critical point has been conjectured to be holographically dual to a Logarithmic CFT. However, many details of this correspondence are still lacking. In this work, we study the 1-loop partition function of Critical Cosmological Topologically Massive Gravity, previously derived by Gaberdiel, Grumiller and

Alessandro Berti, Wil van der Aalst

Much time in process mining projects is spent on finding and understanding data sources and extracting the event data needed. As a result, only a fraction of time is spent actually applying techniques to discover, control and predict the business process. Moreover, there is a lack of techniques to display relationships on top of databases without the need to

Thomas Schick, Mehran Seyedhosseini

In this paper we prove a strengthening of a theorem of Chang, Weinberger and Yu on obstructions to the existence of positive scalar curvature metrics on compact manifolds with boundary. They construct a relative index for the Dirac operator, which lives in a relative K-theory group, measuring the difference between the fundamental group of the boundary and o

L. Abrunheiro, M. Camarinha, J. Clemente-Gallardo, J. C. Cuchí

Quantum splines are curves in a Hilbert space or, equivalently, in the corresponding Hilbert projective space, which generalize the notion of Riemannian cubic splines to the quantum domain. In this paper, we present a generalization of this concept to general density matrices with a Hamiltonian approach and using a geometrical formulation of quantum mechanic

Megu Kubota, Hirokazu Odaka, Toru Tamagawa, Toshio Nakano

We have analyzed X-ray data of SMC X-1 obtained with \textit{Suzaku}, and discovered a combination of an absorption line and an underlying broadened emission line centered at 6.4 keV in an observation performed on May 19, 2012. This absorption line is centered at $6.61_{-0.03}^{+0.02}$~keV with an absorption strength of $5.9_{-1.4}^{+1.7}$, naturally interpr

Sergei Divakov, Ivan Oseledets

We present a novel approach to point set registration which is based on one-shot adversarial learning. The idea of the algorithm is inspired by recent successes of generative adversarial networks. Treating the point clouds as three-dimensional probability distributions, we develop a one-shot adversarial optimization procedure, in which we train a critic neur

Chao Chen, Sheng Zhang, Cuibing Du

Change detection has been a challenging visual task due to the dynamic nature of real-world scenes. Good performance of existing methods depends largely on prior background images or a long-term observation. These methods, however, suffer severe degradation when they are applied to detection of instantaneously occurred changes with only a few preceding frame

Rami Ayoush, Dmitriy Stolyarov, Michal Wojciechowski

We prove a martingale analog of van Schaftingen's theorem and give sharp estimates on the lower Hausdorff dimension of measures in martingale shift invariant spaces. We also provide martingale analogs of trace theorems for Sobolev functions.

Markus Ahlers

The arrival directions of Galactic cosmic rays exhibit anisotropies up to the level of one per-mille over various angular scales. Recent observations of TeV-PeV cosmic rays show that the dipole anisotropy has a strong energy dependence with a phase-flip around 100 TeV. We argue that this behavior can be well understood by the combination of various effects:

Yinqiao Wang, Liang Hong, Yujie Wang, Walter Schirmacher

Using the example of a two-dimensional macroscopic model glass in which the interparticle forces can be precisely measured, we obtain strong hints for resolving a controversy concerning the origin of the anomalous enhancement of the vibrational spectrum in glasses (boson peak). Whereas many authors attribute this anomaly to the structural disorder, some othe

Alban Reynaud, Gabriel Scherer, Jeremy Yallop

In call-by-value languages, some mutually-recursive value definitions can be safely evaluated to build recursive functions or cyclic data structures, but some definitions (let rec x = x + 1) contain vicious circles and their evaluation fails at runtime. We propose a new static analysis to check the absence of such runtime failures. We present a set of declar

T. Hache, T. Weinhold, K. Schultheiss, J. Stigloher

We demonstrate a combined frequency and time domain investigation of injection-locked, constriction-based spin Hall nano-oscillators by Brillouin light scattering (BLS) and time-resolved magneto-optical Kerr effect (TR-MOKE). This was achieved by applying an alternating current in the GHz regime in addition to the direct current which drives auto-oscillation

Zongxiang Yi, Dingyi Pei, ChunmingTang

A function $f$ from an Abelian group $(A,+)$ to an Abelian group $(B,+)$ is $(n, m, S)$ zero-difference (ZD), if $S=\{\lambda_\alpha \mid \alpha \in A\setminus\{0\}\}$ where $n=|A|$, $m=|f(A)|$ and $\lambda_\alpha=|\{x \in A \mid f(x+\alpha)=f(x)\}|$. A function is called zero-difference balanced (ZDB) if $S=\{\lambda\}$ where $\lambda$ is a constant number.

Sylvain Conchon, Amit Goel, Sava Krstic, Rupak Majumdar

We present a fully automatic algorithm for verifying safety properties of parameterized software systems. This algorithm is based on both IC3 and Lazy Annotation. We implemented it in Cubicle, a model checker for verifying safety properties of array-based systems. Cache-coherence protocols and mutual exclusion algorithms are known examples of such systems. O

Roland Donninger, Ziping Rao

We establish Strichartz estimates for the radial energy-critical wave equation in 5 dimensions in similarity coordinates. Using these, we prove the nonlinear asymptotic stability of the ODE blowup in the energy space.

Pranav A

Ranking functions in information retrieval are often used in search engines to recommend the relevant answers to the query. This paper makes use of this notion of information retrieval and applies onto the problem domain of cognate detection. The main contributions of this paper are: (1) positional segmentation, which incorporates the sequential notion; (2)

Maria Spichkova

This paper presents a formal specification of the Controller Area Network (CAN) protocol using FocusST framework. We formally describe core components of the protocol, which provides a basis for further formal analysis using the Isabelle/HOL theorem prover.

Alireza Abedin Varamin, Ehsan Abbasnejad, Qinfeng Shi, Damith Ranasinghe

Automatic recognition of human activities from time-series sensor data (referred to as HAR) is a growing area of research in ubiquitous computing. Most recent research in the field adopts supervised deep learning paradigms to automate extraction of intrinsic features from raw signal inputs and addresses HAR as a multi-class classification problem where detec

Firas Shama, Roey Mechrez, Alon Shoshan, Lihi Zelnik-Manor

Thanks to their remarkable generative capabilities, GANs have gained great popularity, and are used abundantly in state-of-the-art methods and applications. In a GAN based model, a discriminator is trained to learn the real data distribution. To date, it has been used only for training purposes, where it's utilized to train the generator to provide real-look

Zhi-Xiang Jin, Xianqing Li-Jost, Shao-Ming Fei

Quantum coherence and entanglement are two key features in quantum mechanics and play important roles in quantum information processing and quantum computation. We provide a general triangle-like inequality satisfied by the $l_1$-norm measure of coherence for convex combination of arbitrary $n$ pure states of a quantum state $\rho$. Furthermore, we present t

Jitesh R Bhatt, Hiranmaya Mishra, Balbeer Singh

We study the effect of vorticity present in heavy ion collisions (HICs) on the temperature evolution of hot quark-gluon plasma in the presence of spin-vorticity coupling. The initial global rotation entails a nontrivial dependence of the longitudinal flow velocity on the transverse coordinates and also develops a transverse velocity component that depends up

Dimitri N. Laikov

An approximate relativistic two-component Hamiltonian for use in molecular electronic structure calculations is derived in the form of a sum of fixed atom-centered kinetic and spin-orbit operators added to the non-relativistic Hamiltonian. Starting from the well-known zeroth-order regular approximation, further steps are taken to get rid of its nonlinearity

Fei Qi, Zhaohui Xia, Gaoyang Tang, Hang Yang

As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this

Hongbo Dong, Yunqi Luo

Decades of advances in mixed-integer linear programming (MILP) and recent development in mixed-integer second-order-cone programming (MISOCP) have translated very mildly to progresses in global solving nonconvex mixed-integer quadratically constrained programs (MIQCP). In this paper we propose a new approach, namely Compact Disjunctive Approximation (CDA), t

Swarnajit Chatterjee, Sanjay Puri, Raja Paul

We present a comprehensive Monte Carlo study of the ordering kinetics in the $d=2$ ferromagnetic $q$-state clock model with nonconserved Glauber dynamics. In agreement with previous studies we find that $q \geqslant 5$ is characterized by two phase transitions occurring at temperatures $T_{c}^1$ and $T_{c}^2$ ($T_{c}^2<T_{c}^1$). Phase ordering kinetics is t

Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang

Latent factor models (LFMs) such as matrix factorization achieve the state-of-the-art performance among various Collaborative Filtering (CF) approaches for recommendation. Despite the high recommendation accuracy of LFMs, a critical issue to be resolved is the lack of explainability. Extensive efforts have been made in the literature to incorporate explainab

Wankai Tang, Xiang Li, Jun Yan Dai, Shi Jin

Metasurfaces have drawn significant attentions due to their superior capability in tailoring electromagnetic waves with a wide frequency range, from microwave to visible light. Recently, programmable metasurfaces have demonstrated the ability of manipulating the amplitude or phase of electromagnetic waves in a programmable manner in real time, which renders

G. Franciolini, G. F. Giudice, D. Racco, A. Riotto

The detection of primordial gravitational waves would not only have extraordinary implications for our understanding of early cosmology, but would also give non-trivial constraints on Standard Model parameters, under the assumption that no new physics enters below the Higgs instability scale. We study the resulting bounds on the top quark mass and the strong

Yi Sun, Yan Tian, Yiping Xu, Jianxiang Li

Label noise may affect the generalization of classifiers, and the effective learning of main patterns from samples with noisy labels is an important challenge. Recent studies have shown that deep neural networks tend to prioritize the learning of simple patterns over the memorization of noise patterns. This suggests a possible method to search for the best g

Xiao-Yan Li, Beien Zhu, Yi Gao

In our recent works, we used a nearest-neighbor broken bond (NNBB) model to fit the surface energy of Pt, Pd, and Au surfaces [Adv. Theory Simul. 1800127 (2018)]. It was verified that this model could describe the surface energies of above noble metals with high accuracy. The applications of this model in real-time simulations of equilibrium nanocrystal tran

Hua Chai

Current solutions mostly focus on how to predict traffic, rather than observing traffic characteristics in a specific NFV scenario. So, most of them use a uniform threshold to scale in/out. In real NFV scenario, each VNF may serve the one or more flows, and the characteristics of these flows are completely different, a uniform threshold used in this scenario

Hao Liu, Jingjing Wu, Jianguo Jiang, Meibin Qi

Attribute recognition has become crucial because of its wide applications in many computer vision tasks, such as person re-identification. Like many object recognition problems, variations in viewpoints, illumination, and recognition at far distance, all make this task challenging. In this work, we propose a joint CTC-Attention model (JCM), which maps attrib

Matteo Raffaelli

Given a smooth distribution $\mathscr{D}$ of $m$-dimensional planes along a smooth regular curve $\gamma$ in $\mathbb{R}^{m+n}$, we consider the following problem: to find an $m$-dimensional rank-one submanifold of $\mathbb{R}^{m+n}$, that is, an $(m-1)$-ruled submanifold with constant tangent space along the rulings, such that its tangent bundle along $\gam

Yu-Chen Ding, Towe Wang

Among many modified gravity theories, the Chern-Simons modified gravity stands out as one of the few examples whose Dirichlet boundary problem has been well studied. Known solutions to this theory include the Schwarzschild black hole and a slowly rotating black hole. Making use of the Dirichlet boundary term of this theory, we calculate the late-time action

M. Sharif, Saadia Saba

In this paper, we investigate anisotropic static spherically symmetric solutions in the framework of $f(\mathcal{G})$ gravity through gravitational decoupling approach. For this purpose, we consider Krori and Barua (known solution) isotropic interior solution for static spherically symmetric self-gravitating system and extend it to two types of anisotropic s

Jing-Xuan Zhang, Zhen-Hua Ling, Yuan Jiang, Li-Juan Liu

This paper presents methods of making using of text supervision to improve the performance of sequence-to-sequence (seq2seq) voice conversion. Compared with conventional frame-to-frame voice conversion approaches, the seq2seq acoustic modeling method proposed in our previous work achieved higher naturalness and similarity. In this paper, we further improve i

Olivier Emile, Janine Emile

The most commonly observed quantity related to light is its power or equivalently its energy. It can be either measured with a bolometer, a photodiode or estimated with the naked eye. Alternatively people can measure the light impulse or linear momentum. However, linear momentum is characterized by its transfer to matter, and its precise value is most of the

Pan Zhou, Xiao-Tong Yuan, Jiashi Feng

SPIDER (Stochastic Path Integrated Differential EstimatoR) is an efficient gradient estimation technique developed for non-convex stochastic optimization. Although having been shown to attain nearly optimal computational complexity bounds, the SPIDER-type methods are limited to linear metric spaces. In this paper, we introduce the Riemannian SPIDER (R-SPIDER

Marvin Brun-Cosme-Bruny, Eric Bertin, Benoît Coasne, Philippe Peyla

The microalga Chlamydomonas Reinhardtii (CR) is used here as a model system to study the effect of complex environments on the swimming of micro-organisms. Its motion can be modelled by a run and tumble mechanism so that it describes a persistent random walk from which we can extract an effective diffusion coefficient for the large-time dynamics. In our expe

Y. Shiomi, H. Watanabe, H. Masuda, H. Takahashi

We have experimentally studied a magnetopiezoelectric effect predicted recently for magnetic metals with low crystal symmetries. In EuMnBi2 with antiferromagnetic Mn moments at 77 K, dynamic displacements emerge along the $a$ direction upon application of ac electric fields in the $c$ direction, and increase in proportion to the applied electric fields. Such

Donghui Sun, Qing Zhang, Jun Yang

In this paper, we investigate the Chinese font synthesis problem and propose a Pyramid Embedded Generative Adversarial Network (PEGAN) to automatically generate Chinese character images. The PEGAN consists of one generator and one discriminator. The generator is built using one encoder-decoder structure with cascaded refinement connections and mirror skip co

A. Chia, M. Hajdusek, R. Fazio, L. C. Kwek

The phase of an optical field inside a linear amplifier is widely known to diffuse with a diffusion coefficient that is inversely proportional to the photon number. The same process occurs in lasers which limits its intrinsic linewidth and makes the phase uncertainty difficult to calculate. The most commonly used simplification is to assume a narrow photon-n

Wanxin Tian, Zixuan Wang, Haifeng Shen, Weihong Deng

The performance of face detectors has been largely improved with the development of convolutional neural network. However, it remains challenging for face detectors to detect tiny, occluded or blurry faces. Besides, most face detectors can't locate face's position precisely and can't achieve high Intersection-over-Union (IoU) scores. We assume that problems

K. L. Emig, P. Salas, F. de Gasperin, J. B. R. Oonk

Recombination lines involving high principal quantum numbers populate the radio spectrum in large numbers. Low-frequency (<1 GHz) observations of radio recombination lines (RRLs) primarily from carbon and hydrogen offer a new, if not unique, way to probe cold, largely atomic gas and warm, ionised gas in other galaxies. Furthermore, RRLs can be used to determ

Yunlong Yu, Zhong Ji, Yanwei Pang, Jichang Guo

Existing generative Zero-Shot Learning (ZSL) methods only consider the unidirectional alignment from the class semantics to the visual features while ignoring the alignment from the visual features to the class semantics, which fails to construct the visual-semantic interactions well. In this paper, we propose to synthesize visual features based on an auto-e

Nora K. Speicher, Nico Pfeifer

Due to the complexity of cancer, clustering algorithms have been used to disentangle the observed heterogeneity and identify cancer subtypes that can be treated specifically. While kernel based clustering approaches allow the use of more than one input matrix, which is an important factor when considering a multidimensional disease like cancer, the clusterin

Ryo Nakamura, Katsuhito Sudoh, Koichiro Yoshino, Satoshi Nakamura

Although generation-based dialogue systems have been widely researched, the response generations by most existing systems have very low diversities. The most likely reason for this problem is Maximum Likelihood Estimation (MLE) with Softmax Cross-Entropy (SCE) loss. MLE trains models to generate the most frequent responses from enormous generation candidates

Marco Padovani, Daniele Galli

Understanding the role of magnetic fields in star-forming regions is of fundamental importance. In the near future, the exceptional sensitivity of SKA will offer a unique opportunity to evaluate the magnetic field strength in molecular clouds and cloud cores through synchrotron emission observations. The most recent Voyager 1 data, together with Galactic syn

Joontae Kim, Seongchan Kim, Myeonggi Kwon

The aim of this article is to apply a Floer theory to study symmetric periodic Reeb orbits. We define positive equivariant wrapped Floer homology using a (anti-)symplectic involution on a Liouville domain and investigate its algebraic properties. By a careful analysis of index iterations, we obtain a non-trivial lower bound on the minimal number of geometric

Nima Hoda, Daniel T. Wise, Daniel J. Woodhouse

A tubular group $G$ is a finite graph of groups with $\mathbb{Z}^2$ vertex groups and $\mathbb{Z}$ edge groups. We characterize residually finite tubular groups: $G$ is residually finite if and only if its edge groups are separable. Methods are provided to determine if $G$ is residually finite. When $G$ has a single vertex group an algorithm is given to dete

Akinori Hosoyamada, Yu Sasaki, Seiichiro Tani, Keita Xagawa

The current paper improves the number of queries of the previous quantum multi-collision finding algorithms presented by Hosoyamada et al. at Asiacrypt 2017. Let an $l$-collision be a tuple of $l$ distinct inputs that result in the same output of a target function. In cryptology, it is important to study how many queries are required to find $l$-collisions f

Tenghui Wang, Zhenxing Zhang, Liang Xiang, Zhilong Jia

For a frequency-tunable two-qubit system, a controlled-Z (CZ) gate can be realized by adiabatically driving the qubit system through an avoided level crossing between an auxiliary state and computational levels. Here, we theoretically propose a fast CZ gate using a shortcut-to-adiabaticity (STA). Experimentally, the STA CZ gate is implemented with a 52 ns co

Ting-Wai Chiu

We perform hybrid Monte-Carlo simulation of $N_f=2+1+1 $ lattice QCD with domain-wall quarks at the physical point. The simulation is carried out on the $ L^3 \times T = 64^3 \times 64 $ lattice with lattice spacing $a \sim 0.064 $ fm ($ L > 4 $ fm, and $ M_\pi L > 3 $), using the Nvidia DGX-1 (8 V100 GPUs interconnected by the NVLink). To attain the maximal

Nicolae Paladi, Christian Gehrmann

The evolution of Software-Defined Networking (SDN) has so far been predominantly geared towards defining and refining the abstractions on the forwarding and control planes. However, despite a maturing south-bound interface and a range of proposed network operating systems, the network management application layer is yet to be specified and standardized. It h

Akio Kawasaki, Boris Braverman, Edwin Pedrozo-Peñafiel, Chi Shu

Optical cavities are widely used to enhance the interaction between atoms and light. Typical designs using a geometrically symmetric structure in the near-concentric regime face a tradeoff between mechanical stability and high single-atom cooperativity. To overcome this limitation, we design and implement a geometrically asymmetric standing-wave cavity. This

Abhik Basu, Jayanta K Bhattacharjee

We revisit the scaling properties of the energy spectra in fully developed incompressible homogeneous turbulence in forced magnetofluids (MHD) in three dimensions (3D), which are believed to be characterised by {\em universal scaling exponents} in the inertial range. Enumerating these universal scaling exponents that characterise the energy spectra remains a

Katie Lim, Jonathan Balkind, David Wentzlaff

Energy efficiency has become an increasingly important concern in computer architecture due to the end of Dennard scaling. Heterogeneity has been explored as a way to achieve better energy efficiency and heterogeneous microarchitecture chips have become common in the mobile setting. Recent research has explored using heterogeneous-ISA, heterogeneous microarc

Alex Chandler

In the spirit of Bar Natan's construction of Khovanov homology, we give a categorification of the Vandermonde determinant. Given a sequence of positive integers $\vec{x}=(x_1,...,x_n)$, we construct a commutative diagram in the shape of the Bruhat order on $S_n$ whose nodes are colored smoothings of the $2$-strand torus link $T_{2,n}$, and whose arrows are c

Conrad Sanderson, Ryan Curtin

Despite the importance of sparse matrices in numerous fields of science, software implementations remain difficult to use for non-expert users, generally requiring the understanding of underlying details of the chosen sparse matrix storage format. In addition, to achieve good performance, several formats may need to be used in one program, requiring explicit

Seiseki Akibue, Go Kato, Naoki Marumo

The indistinguishability of non-orthogonal pure states lies at the heart of quantum information processing. Although the indistinguishability reflects the impossibility of measuring complementary physical quantities by a single measurement, we demonstrate that the distinguishability can be perfectly retrieved simply with the help of posterior classical parti

Tanmoy Modak, Eibun Senaha

We consider a scenario in which an extra bottom Yukawa coupling can drive electroweak baryogenesis in the general two-Higgs doublet model. It is found that the new bottom Yukawa coupling with $\mathcal{O}(0.1)$ in magnitude can generate the sufficient baryon asymmetry without conflicting existing data. We point out that future measurements of the bottom Yuka

Yury Solyaev, Sergey Lurie

Semi-inverse analytical solution of a pure bending problem for piezoelectric layer is developed in the framework of linear electroelasticity theory with strain gradient and electric field gradient effects. Two-dimensional solution is derived assuming plane strain state of a layer. It is shown that obtained solution can be used for the validation of size-depe

Arpit Agarwal, Katharina Muelling, Katerina Fragkiadaki

We propose an exploration method that incorporates look-ahead search over basic learnt skills and their dynamics, and use it for reinforcement learning (RL) of manipulation policies . Our skills are multi-goal policies learned in isolation in simpler environments using existing multigoal RL formulations, analogous to options or macroactions. Coarse skill dyn

Jannick Rolland, Ozan Cakmakci, Jeff Covelli, Cali Fidopiastis

The emergence of several trends, including the increased availability of wireless networks, miniaturization of electronics and sensing technologies, and novel input and output devices, is creating a demand for integrated, full-time displays for use across a wide range of applications, including collaborative environments. In this paper, we present and discus

Elmehdi Zaouche

This paper is concerned with an uniqueness of solution of the weak formulation of an evolution dam problem related to a compressible fluid flow through a two-dimensional, rectangular and heterogeneous porous medium. Note that our problem associated with the equation a(x_1)(u_{x_2}+\chi)_{x_2}-(u+\chi)_t=0. Our technique is based on the idea that we transform

Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto

We propose a new formulation of Multiple-Instance Learning (MIL). In typical MIL settings, a unit of data is given as a set of instances called a bag and the goal is to find a good classifier of bags based on similarity from a single or finitely many "shapelets" (or patterns), where the similarity of the bag from a shapelet is the maximum similarity of insta

Seojeong Lee, Youngki Shin

We propose a two-stage least squares (2SLS) estimator whose first stage is the equal-weighted average over a complete subset with $k$ instruments among $K$ available, which we call the complete subset averaging (CSA) 2SLS. The approximate mean squared error (MSE) is derived as a function of the subset size $k$ by the Nagar (1959) expansion. The subset size i

M. Suman Kalyan, Rajeev Kapri

The unzipping of a double stranded DNA whose ends are subjected to a time dependent periodic force with frequency $\omega$ and amplitude $G$ is studied using Monte Carlo simulations. We obtain the dynamical order parameter, $Q$, defined as the time average extension between the end monomers of two strands of the DNA over a period, and its probability distrib

Safwan Hossain, Kiarash Jamali, Yuchen Li, Frank Rudzicz

We propose a new architecture and training methodology for generative adversarial networks. Current approaches attempt to learn the transformation from a noise sample to a generated data sample in one shot. Our proposed generator architecture, called $\textit{ChainGAN}$, uses a two-step process. It first attempts to transform a noise vector into a crude samp

Hajime Ono, Tsubasa Takahashi, Kazuya Kakizaki

How can we make machine learning provably robust against adversarial examples in a scalable way? Since certified defense methods, which ensure $\epsilon$-robust, consume huge resources, they can only achieve small degree of robustness in practice. Lipschitz margin training (LMT) is a scalable certified defense, but it can also only achieve small robustness d

T. Akutsu, M. Ando, K. Arai, Y. Arai

The recent detections of gravitational waves (GWs) reported by LIGO/Virgo collaborations have made significant impact on physics and astronomy. A global network of GW detectors will play a key role to solve the unknown nature of the sources in coordinated observations with astronomical telescopes and detectors. Here we introduce KAGRA (former name LCGT; Larg

Sinh Vu Trong, Minh Nguyen Le

Many approaches have been proposed to tackle the problem of Abstract Meaning Representation (AMR) parsing, helps solving various natural language processing issues recently. In our paper, we provide an overview of different methods in AMR parsing and their performances when analyzing legal documents. We conduct experiments of different AMR parsers on our ann

Soumalya Joardar, Arnab Mandal

We compute all the quantum symmetries of a graph with n- disjoint loops at the critical inverse temperature. We show that the set of non-isomorphic CQG's appearing as quantum symmetry at the critical inverse temperature has a one to one correspondence with the cardinality of the set of partitions of the number of vertices.

Hans-Joachim Baues, Martin Frankland

We study track categories (i.e., groupoid-enriched categories) endowed with additive structure similar to that of a 1-truncated DG-category, except that composition is not assumed right linear. We show that if such a track category is right linear up to suitably coherent correction tracks, then it is weakly equivalent to a 1-truncated DG-category. This gener

Farid Manuchehrfar, Wei Tian, Tom Chou, Jie Liang

Coagulation and fragmentation (CF) is a fundamental process by which particles attach to each other to form clusters while existing clusters break up into smaller ones. It is a ubiquitous process that plays a key role in many physical and biological phenomena. CF is typically a stochastic process that often occurs in confined spaces with a limited number of

Hai-Chuan Xu, Wei-Xing Zhou

Price changes are induced by aggressive market orders in stock market. We introduce a bivariate marked Hawkes process to model aggressive market order arrivals at the microstructural level. The order arrival intensity is marked by an exogenous part and two endogenous processes reflecting the self-excitation and cross-excitation respectively. We calibrate the

Weilin Cong, William Wang, Wang-Chien Lee

Despite the great success object detection and segmentation models have achieved in recognizing individual objects in images, performance on cognitive tasks such as image caption, semantic image retrieval, and visual QA is far from satisfactory. To achieve better performance on these cognitive tasks, merely recognizing individual object instances is insuffic

Akhil Dass, Sateesh Gedupudi

The study of heat exchangers with both the hot and cold fluid sides driven by buoyancy forces is an area of considerable interest due to their inherent passivity and non-existence of moving parts. The current study aims to study such heat exchange devices employing the basic Coupled Natural Circulation Loop (CNCL) systems. A 1-D Fourier series based semi-ana

Pengyuan Ren, Jianmin Li

Person re-identification (ReID) is aimed at identifying the same person across videos captured from different cameras. In the view that networks extracting global features using ordinary network architectures are difficult to extract local features due to their weak attention mechanisms, researchers have proposed a lot of elaborately designed ReID networks,

DE Trilling, M Mommert, JL Hora, D Farnocchia

1I/`Oumuamua is the first confirmed interstellar body in our Solar System. Here we report on observations of `Oumuamua made with the Spitzer Space Telescope on 2017 November 21--22 (UT). We integrated for 30.2~hours at 4.5 micron (IRAC channel 2). We did not detect the object and place an upper limit on the flux of 0.3 uJy (3sigma). This implies an effective

Éva Czabarka, Josiah Reiswig, László Székely, Zhiyu Wang

For positive integers $n$ and $e$, let $\kappa(n,e)$ be the minimum crossing number (the standard planar crossing number) taken over all graphs with $n$ vertices and at least $e$ edges. Pach, Spencer and T\'oth [Discrete and Computational Geometry 24 623--644, (2000)] showed that $\kappa(n,e) n^2/e^3$ tends to a positive constant (called midrange crossing co

Omur Ozel, Bruno Sinopoli, Osman Yagan

Motivated by reliability of networks in critical infrastructures, we consider optimal robustness of a class of flow networks against a \textit{targeted} attack, namely max-load targeted attack, that triggers cascading failures due to removal of largest load carrying portion of lines. The setup involves a network of $N$ lines with initial loads $L_1, \ldots,

Ka-Ho Chow, Anish Hiranandani, Yifeng Zhang, S. -H. Gary Chan

Representation learning of pedestrian trajectories transforms variable-length timestamp-coordinate tuples of a trajectory into a fixed-length vector representation that summarizes spatiotemporal characteristics. It is a crucial technique to connect feature-based data mining with trajectory data. Trajectory representation is a challenging problem, because bot

X. Liu, P. Sanz-Leon, P. A. Robinson

Neural field theory is used to quantitatively analyze the two-dimensional spatiotemporal correlation properties of gamma-band (30 -- 70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex (V1), and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically under different