November 2019 arXiv papers — page 48

Zhongqi Yu, Shisheng Chen, Nyuk Hien Wong, Marcel Ignatius

The rising air temperature caused by Urban Heat Island (UHI) effect has become a problem for Singapore, it not only affects the thermal comfort of outdoor microclimate environment, but also increases the cooling energy consumption of buildings. As part of a multiscale and multi-physics urban microclimate model, weather stations were installed at 15 points wi

Rémi Kazeroni, Ernazar Abdikamalov

The explosion of massive stars in core-collapse supernovae may be aided by the convective instabilities that develop in their innermost nuclear burning shells. The resulting fluctuations support the explosion by generating additional turbulence behind the supernova shock. It was suggested that the buoyant density perturbations arising from the interaction of

Laurens Bliek, Sicco Verwer, Mathijs de Weerdt

When a black-box optimization objective can only be evaluated with costly or noisy measurements, most standard optimization algorithms are unsuited to find the optimal solution. Specialized algorithms that deal with exactly this situation make use of surrogate models. These models are usually continuous and smooth, which is beneficial for continuous optimiza

Dong Wang, Yuki Ueda, Raula Gaikovina Kula, Takashi Ishio

Code Review (CR) is the cornerstone for software quality assurance and a crucial practice for software development. As CR research matures, it can be difficult to keep track of the best practices and state-of-the-art in methodology, dataset, and metric. This paper investigates the potential of benchmarking by collecting methodology, dataset, and metric of CR

Minyong Guo, Peng-Cheng Li, Bin Chen

We study the null geodesics extending from the near-horizon region out to the far region in the background of the Schwarzschild and the singly-spinning Myers-Perry black holes in the large dimension limit. We find that in this limit the radial integrals of these geodesics can be obtained by using the method of matched asymptotic expansions. If the motion of

Muhammad Arsath K F, Vinod Ganesan, Rahul Bodduna, Chester Rebeiro

The power consumption of a microprocessor is a huge channel for information leakage. While the most popular exploitation of this channel is to recover cryptographic keys from embedded devices, other applications such as mobile app fingerprinting, reverse engineering of firmware, and password recovery are growing threats. Countermeasures proposed so far are t

Tristan Bice

We unify the Kumjian-Renault Weyl groupoid construction with the Lawson-Lenz version of Exel's tight groupoid construction. We do this by utilising only a weak algebraic fragment of the C*-algebra structure, namely its *-semigroup reduct. Fundamental properties like local compactness are also shown to remain valid in general classes of *-rings.

D. L. Suhas, Jai Sukhatme

The response of a spherical moist shallow water system to tropical imbalances in the presence of inhomogeneous saturation fields is examined. While the initial moist response is similar to the dry reference run, albeit with a reduced equivalent depth, the long time solution depends quite strikingly on the nature of the saturation field. For a saturation fiel

Francisc Bozgan

We prove local well-posedness of partially periodic and periodic modified KP-I equations, namely for $\partial_t u+(-1)^{\frac{l+1}{2}}\partial^l_x u-\partial_x^{-1}\partial_y^2 u+u^2\partial_x u=0$ in the anisotropic Sobolev space $H^{s,s}(\mathbb{R}\times \mathbb{T})$ if $l=3$ and $s>2$, in $H^{s,s}(\mathbb{T}\times \mathbb{T})$ if $l=3$ and $s>\frac{19}{8

Nicola Menga, Daniele Dini, Giuseppe Carbone

In this paper, we investigate the periodic peeling behavior of opposing symmetric peeling fronts involving an elastic tape peeled off from a deformable substrate of finite thickness, backed onto a rigid foundation. We treat the problem by means of an energetic formulation, and we found that, depending on the values of the initial detached length $l$, substra

Liangliang Lu, Lijun Xia, Zhiyu Chen, Leizhen Chen

Entanglement is a counterintuitive feature of quantum physics that is at the heart of quantum technology. High-dimensional quantum states offer unique advantages in various quantum information tasks. Integrated photonic chips have recently emerged as a leading platform for the generation, manipulation and detection of entangled photons. Here, we report a sil

Ravi Kashikar, Mayank Gupta, B. R. K. Nanda

Complex quantum coupling phenomena of halide perovskites are examined through ab-initio calculations and exact diagonalization of model Hamiltonians to formulate a set of fundamental guiding rules to engineer the bandgap through strain. The bandgap tuning in halides is crucial for photovoltaic applications and for establishing non-trivial electronic states.

Oldřich Kodym, Michal Španěl, Adam Herout

In this work we present a method of automatic segmentation of defective skulls for custom cranial implant design and 3D printing purposes. Since such tissue models are usually required in patient cases with complex anatomical defects and variety of external objects present in the acquired data, most deep learning-based approaches fall short because it is not

Xun-Wei Xu, Chong Ye, Yong Li, Ai-Xi Chen

The spontaneous emission spectrum of a multi-level atom or molecule with nonreciprocal transition is investigated. It is shown that the nonreciprocal transition can lead to the elimination of a spectral line in the spontaneous emission spectrum. As an application, we show that nonreciprocal transition arises from the phase-related driving fields in chiral mo

Oguzhan Ersoy, Stefanie Roos, Zekeriya Erkin

Payment channel networks like Bitcoin's Lightning network are an auspicious approach for realizing high transaction throughput and almost-instant confirmations in blockchain networks. However, the ability to successfully make payments in such networks relies on the willingness of participants to lock collateral in the network. In Lightning, the key finan

Martin Frank, Jonas Kusch, Thomas Camminady, Cory D. Hauck

Solving the radiative transfer equation with the discrete ordinates (S$_N$) method leads to a non-physical imprint of the chosen quadrature set on the solution. To mitigate these so-called ray effects, we propose a modification of the S$_N$ method, which we call artificial scattering S$_N$ (as-S$_N$). The method adds an artificial forward-peaked scattering o

Noe Samano, Mengjie Zhou, Andrew Calway

We present a novel approach to geolocalising panoramic images on a 2-D cartographic map based on learning a low dimensional embedded space, which allows a comparison between an image captured at a location and local neighbourhoods of the map. The representation is not sufficiently discriminatory to allow localisation from a single image, but when concatenate

Wen-Tian Lu, Yawen Zhao, Marco Battiato, Yizheng Wu

The spin- and energy-dependent interface reflectivity of a ferromagnetic (FM) film in contact with a nonmagnetic (NM) film is calculated using a first-principles transport method and incorporated into the superdiffusive spin transport model to study the femtosecond laser-induced ultrafast demagnetization of Fe|NM and Ni|NM (NM= Au, Al & Pt) bilayers. By comp

Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A. Winkler

The screening of novel materials is an important topic in the field of materials science. Although traditional computational modeling, especially first-principles approaches, is a very useful and accurate tool to predict the properties of novel materials, it still demands extensive and expensive state-of-the-art computational resources. Additionally, they ca

Hery Randriamaro

This article computes the Tutte polynomial of the hyperplane arrangements associated to the complex reflection groups. The calculations are based on both formulas of De Concini and Procesi for Tutte polynomial and the normaliser of parabolic subgroups in complex reflection groups determined by Krishnasamy and Taylor.

Jack Saywell, Max Carey, Mohammad Belal, Ilya Kuprov

We present mirror and beamsplitter pulse designs that improve the fidelity of atom interferometry and increase its tolerance of systematic inhomogeneities. These designs are demonstrated experimentally with a cold thermal sample of $^{85}$Rb atoms. We first show a stimulated Raman inversion pulse design that achieves a ground hyperfine state transfer efficie

S. V. Poltavtsev, I. A. Yugova, Ya. A. Babenko, I. A. Akimov

We study the quantum beats in the polarization of the photon echo from donor-bound exciton ensembles in semiconductor quantum wells. To induce these quantum beats, a sequence composed of a circularly polarized and a linearly polarized picosecond laser pulse in combination with an external transverse magnetic field is used. This results in an oscillatory beha

V. Kireyeu, J. Aichelin, E. Bratkovskaya, A. Le Fèvre

Modeling of the process of the formation of nuclear clusters in the hot nuclear matter is a challenging task. We present the novel n-body dynamical transport approach - PHQMD (Parton-Hadron-Quantum-Molecular Dynamics) [1] for the description of heavy-ion collisions as well as clusters and hpernuclei formation. The PHQMD extends well established PHSD (Parton-

M. Friedman, T. Budner, D. Pérez-Loureiro, E. Pollacco

The radionuclide $^{22}$Na is a target of $γ$-ray astronomy searches, predicted to be produced during thermonuclear runaways driving classical novae. The $^{22}$Na(p,$γ$)$^{23}$Mg reaction is the main destruction channel of $^{22}$Na during a nova, hence, its rate is needed to accurately predict the $^{22}$Na yield. However, experimental determinations of th

Luna De Bruyne, Pepa Atanasova, Isabelle Augenstein

Emotion lexica are commonly used resources to combat data poverty in automatic emotion detection. However, vocabulary coverage issues, differences in construction method and discrepancies in emotion framework and representation result in a heterogeneous landscape of emotion detection resources, calling for a unified approach to utilising them. To combat this

Davide di Micco, Tim Van der Linden

We explain how, in the context of a semi-abelian category, the concept of an internal crossed square may be used to set up an intrinsic approach to the Brown-Loday non-abelian tensor product.

Ioannis Mollas, Nick Bassiliades, Ioannis Vlahavas, Grigorios Tsoumakas

Towards a future where machine learning systems will integrate into every aspect of people's lives, researching methods to interpret such systems is necessary, instead of focusing exclusively on enhancing their performance. Enriching the trust between these systems and people will accelerate this integration process. Many medical and retail banking/finance a

Fei Ding, Gang Yang, Jinlu Liu, Jun Wu

The medical image is characterized by the inter-class indistinction, high variability, and noise, where the recognition of pixels is challenging. Unlike previous self-attention based methods that capture context information from one level, we reformulate the self-attention mechanism from the view of the high-order graph and propose a novel method, namely Hie

Siyu Yao, Ruijie Wang, Shen Sun, Derui Bu

As an efficient model for knowledge organization, the knowledge graph has been widely adopted in several fields, e.g., biomedicine, sociology, and education. And there is a steady trend of learning embedding representations of knowledge graphs to facilitate knowledge graph construction and downstream tasks. In general, knowledge graph embedding techniques ai

Lutz Bornmann, Sitaram Devarakonda, Alexander Tekles, George Chacko

Recently, Wu, Wang, and Evans (2019) and Bu, Waltman, and Huang (2019) proposed a new family of indicators, which measure whether a scientific publication is disruptive to a field or tradition of research. Such disruptive influences are characterized by citations to a focal paper, but not its cited references. In this study, we are interested in the question

Xuepeng Fan, Peng Li, Yulong Zeng, Xiaoping Zhou

We study the liquid democracy problem, where each voter can either directly vote to a candidate or delegate his voting power to a proxy. We consider the implementation of liquid democracy on the blockchain through Ethereum smart contract and to be compatible with the realtime self-tallying property, where the contract itself can record ballots and update vot

Mazhar Ali

Most studies of collective dephasing for bipartite as well as multipartite quantum systems focus on a very specific orientation of magnetic field, that is, z-orientation. However, in practical situations, there are always small fluctuations in stochastic field and it is necessary that more general orientations of fields should be considered. We extend this p

Kurusch Ebrahimi-Fard, Frederic Patras

Gian-Carlo Rota mentioned in one of his last articles the problem of developing a theory around the notion of integration algebras, which should be dual to the one of differential algebras. This idea has been developed historically along three lines: using properties of iterated integrals and generalisations thereof, as in the theory of rough paths; using th

R. P. de Groote, J. Billowes, C. L. Binnersley, M. L. Bissell

The mesoscopic nature of the atomic nucleus gives rise to a wide array of macroscopic and microscopic phenomena. The size of the nucleus is a window into this duality: while the charge radii globally scale as $A^{1/3}$, their evolution across isotopic chains reveals unanticipated structural phenomena [1-3]. The most ubiquitous of these is perhaps the Odd-Eve

Yong Fang

Polar codes are a class of {\bf structured} channel codes proposed by Arıkan based on the principle of {\bf channel polarization}, and can {\bf achieve} the symmetric capacity of any Binary-input Discrete Memoryless Channel (B-DMC). The Soft CANcellation (SCAN) is a {\bf low-complexity} {\bf iterative} decoding algorithm of polar codes outperforming the wide

WonTae Hwang, Keunyoung Jeong

We count the number of isomorphism classes of degree $d$-twists of some polarized abelian varieties over finite fields of odd prime dimension. This can be seen as a higher dimensional analogue of the counting problem for elliptic curves case.

Yuji Saito, Taku Nonomura, Keigo Yamada, Kumi Nakai

In this paper, the sparse sensor placement problem for least-squares estimation is considered, and the previous novel approach of the sparse sensor selection algorithm is extended. The maximization of the determinant of the matrix which appears in pseudo-inverse matrix operations is employed as an objective function of the problem in the present extended app

Jaromír Janisch, Tomáš Pevný, Viliam Lisý

Classification with Costly Features (CwCF) is a classification problem that includes the cost of features in the optimization criteria. Individually for each sample, its features are sequentially acquired to maximize accuracy while minimizing the acquired features' cost. However, existing approaches can only process data that can be expressed as vectors of f

Cong Li, Xianxin Wu, Le Wang, Defa Liu

The iron-based superconductor FeSe has attracted much recent attention because of its simple crystal structure, distinct electronic structure and rich physics exhibited by itself and its derivatives. Determination of its intrinsic electronic structure is crucial to understand its physical properties and superconductivity mechanism. Both theoretical and exper

Jorge Mello, Min Sha

In this paper, for an elliptic curve $E$ defined over the algebraic numbers and for any subfield $F$ of algebraic numbers, we say that $E$ has the Northcott property over $F$ if there are at most finitely many $F$-rational points on $E$ of uniformly bounded height, and we say that $E$ has the property (P) over $F$ if for any infinite subset $S$ of $F$-ration

Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr

This paper presents a novel learning framework to construct Koopman eigenfunctions for unknown, nonlinear dynamics using data gathered from experiments. The learning framework can extract spectral information from the full nonlinear dynamics by learning the eigenvalues and eigenfunctions of the associated Koopman operator. We then exploit the learned Koopman

Peter A. Hogan, Dirk Puetzfeld

We present an alternative derivation of the gravitational clock compass and show how such a device can be used for the detection of gravitational waves. Explicit compass setups are constructed in special types of space--times, namely for exact plane gravitational waves and for waves moving radially relative to an observer.

David Brook, Varghese Mathai

We consider representations of the Cuntz algebras ${\mathcal O}_N$ as constructed by Bratteli-Jorgensen and use these to define a faithful action of the analytic loop group $L_{\text{an}}U(n)$ on ${\mathcal O}_N$ for $N \geq n$. This extends to a faithful action on the infinite Cuntz algebra ${\mathcal O}_{\infty}$, and we show that this action can be used t

Yuyao Shi, Mohan Rajesh Elara, Anh Vu Le, Veerajagadheswar Prabakaran

The research interest in mobile robots with independent steering wheels has been increasing over recent years due to their high mobility and better payload capacity over the systems using omnidirectional wheels. However, with more controllable degrees of freedom, almost all of the platforms include redundancy which is modeled using the instantaneous center o

Amir Farzad, T. Aaron Gulliver

Log messages are now widely used in software systems. They are important for classification as millions of logs are generated each day. Most logs are unstructured which makes classification a challenge. In this paper, Deep Learning (DL) methods called Auto-LSTM, Auto-BLSTM and Auto-GRU are developed for anomaly detection and log classification. These models

Kwang-Seob Kim, Joachim König

We study the inverse Galois problem with local conditions. In particular, we ask whether every finite group occurs as the Galois group of a Galois extension of $\mathbb{Q}$ all of whose decomposition groups are cyclic (resp., abelian). This property is known for all solvable groups due to Shafarevich's solution of the inverse Galois problem for those groups.

Xiaojun Cui, Liang Jin, Xifeng Su

On a complete, connected, locally compact, non-compact geodesic space $(X,d)$, we assign each compact set a distance-like function. With the help of these functions, we obtain a pseudo-metric on the space of (non-empty) compact subsets of $X$ which is less than the Hausdorff distance. The quotient metric space is closely related to the large scale geometry o

Luca Esposito, Prosenjit Roy, Firoj Sk

We analyze the asymptotic behavior of the eigenvalues of nonlinear elliptic problems under Dirichlet boundary conditions and mixed (Dirichlet, Neumann) boundary conditions on domains becoming unbounded. We make intensive use of Picone identity to overcome nonlinearity complications. Altogether the use of Picone identity makes the proof easier with respect to

HyungJoo Kim, Philipp Gubler

The dispersion relation of the $ϕ$ meson in nuclear matter is studied in a QCD sum rule approach. In a dense medium, longitudinal and transverse modes of vector particles can have independently modified dispersion relations due to broken Lorentz invariance. Employing the full set of independent operators and corresponding Wilson coefficients up to operator d

Yiming Zhang, Zeyu Mao, Qi Han, Youbing Li

MAX phases are a family of layered, hexagonal-structure ternary carbides or nitrides of a transitional metal and an A-group element. What makes this type of material fascinating and potentially useful is their remarkable combinations of metallic and ceramic characteristics; as well as the indispensable role in 'top-down' synthesis of their 2D counterparts, M

Yohei Chiba, Yoshiko Kanada-En'yo, Yuki Shikata

We investigated cluster correlation and nuclear voricity in low-lying $1^-$ states of $^{24}$Mg within antisymmetrized molecular dynamics framework. We found that the toroidal and compressional dipole modes separately appear as the $K=1$ and $K=0$ states. The $1^-$ ($K=1$) state is the toroidal dipole state with the strong nuclear vorticity but no prominent

Jennifer Morse, Jianping Pan, Wencin Poh, Anne Schilling

We introduce a type $A$ crystal structure on decreasing factorizations of fully-commutative elements in the 0-Hecke monoid which we call $\star$-crystal. This crystal is a $K$-theoretic generalization of the crystal on decreasing factorizations in the symmetric group of the first and last author. We prove that under the residue map the $\star$-crystal intert

Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang

Overparameterized neural networks can be highly accurate on average on an i.i.d. test set yet consistently fail on atypical groups of the data (e.g., by learning spurious correlations that hold on average but not in such groups). Distributionally robust optimization (DRO) allows us to learn models that instead minimize the worst-case training loss over a set

Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao

To reduce the long training time of large deep neural network (DNN) models, distributed synchronous stochastic gradient descent (S-SGD) is commonly used on a cluster of workers. However, the speedup brought by multiple workers is limited by the communication overhead. Two approaches, namely pipelining and gradient sparsification, have been separately propose

Colin MacLaurin

I investigate the relativistic mechanics of an extended "cable" in an arbitrary static, spherically symmetric spacetime. Such hypothetical bodies have been proposed as tests of energy and thermodynamics: by lowering objects toward a black hole, scooping up Hawking radiation, or mining energy from the expansion of the universe. I review existing work on stati

Taylor M. Hernandez, Roel Van Beeumen, Mark A. Caprio, Chao Yang

We present a greedy algorithm for computing selected eigenpairs of a large sparse matrix $H$ that can exploit localization features of the eigenvector. When the eigenvector to be computed is localized, meaning only a small number of its components have large magnitudes, the proposed algorithm identifies the location of these components in a greedy manner, an

Changkeun Oh

We obtain sharp small cap decoupling inequalities associated to the moment curve for certain range of exponents $p$. Our method is based on the bilinearization argument due to Bourgain and Bourgain-Demeter. Our result generalizes theirs to all higher dimensions.

Kingman Cheung, Zeren Simon Wang

We study displaced vertex signatures of long-lived particles (LLPs) from exotic Higgs decays in the context of a Higgs-portal model and a neutral-naturalness model at the CEPC and FCC-ee. Such two models feature two representative mass ranges for LLPs, which show very different behavior in their decay signatures. The Higgs-portal model contains a very light

Akihiro Higashitani, Yusuke Nakajima

The $F$-signature is a numerical invariant defined by the number of free direct summands in the Frobenius push-forward, and it measures singularities in positive characteristic. It can be generalized by focussing on the number of non-free direct summands. In this paper, we provide several methods to compute the (generalized) $F$-signature of a Hibi ring whic

Xiaodong Cun, Chi-Man Pun, Cheng Shi

Shadow removal is an essential task for scene understanding. Many studies consider only matching the image contents, which often causes two types of ghosts: color in-consistencies in shadow regions or artifacts on shadow boundaries. In this paper, we tackle these issues in two ways. First, to carefully learn the border artifacts-free image, we propose a nove

Junliang Guo, Xu Tan, Linli Xu, Tao Qin

Non-autoregressive translation (NAT) models remove the dependence on previous target tokens and generate all target tokens in parallel, resulting in significant inference speedup but at the cost of inferior translation accuracy compared to autoregressive translation (AT) models. Considering that AT models have higher accuracy and are easier to train than NAT

Stefan Evans, Johann Rafelski

We study the response of the electron mass to an externally applied electrical field. As a consequence of nonlinear electromagnetic (EM) effective action, the mass of a particle diminishes in the presence of an externally applied electric field. We consider modification of the muon anomalous magnetic moment $g-2$ due to electron loop insert in higher order.

Aming Wu, Yahong Han, Linchao Zhu, Yi Yang

Most state-of-the-art methods of object detection suffer from poor generalization ability when the training and test data are from different domains, e.g., with different styles. To address this problem, previous methods mainly use holistic representations to align feature-level and pixel-level distributions of different domains, which may neglect the instan

J. Socorro, S. Pérez-Payán, Abraham Espinoza-García, Luis Rey Díaz-Barrón

Under the premise that the current observations of the cosmic microwave background radiation set a very stringent limit to the anisotropy of the universe, we consider an anistropic model in the presence of a barotropic perfect fluid and a homogeneous scalar field, which transits to a flat FRW cosmology for late times in a dust epoch, presenting an accelerate

Uttaran Bhattacharya, Christian Roncal, Trisha Mittal, Rohan Chandra

We present an autoencoder-based semi-supervised approach to classify perceived human emotions from walking styles obtained from videos or motion-captured data and represented as sequences of 3D poses. Given the motion on each joint in the pose at each time step extracted from 3D pose sequences, we hierarchically pool these joint motions in a bottom-up manner

Xing Niu, Marine Carpuat

This work aims to produce translations that convey source language content at a formality level that is appropriate for a particular audience. Framing this problem as a neural sequence-to-sequence task ideally requires training triplets consisting of a bilingual sentence pair labeled with target language formality. However, in practice, available training ex

Dimitris Fotakis, Vardis Kandiros, Thanasis Lianeas, Nikos Mouzakis

In this work, we seek a more refined understanding of the complexity of local optimum computation for Max-Cut and pure Nash equilibrium (PNE) computation for congestion games with weighted players and linear latency functions. We show that computing a PNE of linear weighted congestion games is PLS-complete either for very restricted strategy spaces, namely w

Kaito Shimamura, Shuichi Kawano

Sparse convex clustering is to cluster observations and conduct variable selection simultaneously in the framework of convex clustering. Although a weighted $L_1$ norm is usually employed for the regularization term in sparse convex clustering, its use increases the dependence on the data and reduces the estimation accuracy if the sample size is not sufficie

Masao Jinzenji, Yu Tajima

In this paper, we first propose a cohomological derivation of the celebrated Euler's Pentagonal Number Theorem. Then we prove an identity that corresponds to a bosonic extension of the theorem. The proof corresponds to a cohomological re-derivation of Euler's another celebrated identity.

S. B. Dubovichenko, N. A. Burkova, A. V. Dzhazairov-Kakhramanov

Within the framework of the modified potential cluster model with a classification of orbital states according to Young diagrams, the possibility of data description of the radiative neutron capture on 11B to the second excited state of 12B at 1.67365 MeV (2-) and prediction absentee of experimental data for the total cross sections to the third and fourth e

William Dawson, Stephan Mohr, Laura E. Ratcliff, Takahito Nakajima

With the development of low order scaling methods for performing Kohn-Sham Density Functional Theory, it is now possible to perform fully quantum mechanical calculations of systems containing tens of thousands of atoms. However, with an increase in the size of system treated comes an increase in complexity, making it challenging to analyze such large systems

Qintong Li, Hongshen Chen, Zhaochun Ren, Pengjie Ren

A humanized dialogue system is expected to generate empathetic replies, which should be sensitive to the users' expressed emotion. The task of empathetic dialogue generation is proposed to address this problem. The essential challenges lie in accurately capturing the nuances of human emotion and considering the potential of user feedback, which are overlooke

Yiqiu Ma, Xiang Li, Shengjun Yang, Yanbei Chen

The theory of linear quantum measurement has been developed for analysing the sensitivities of experimental devices that measure extremely weak signals, such as gravitational waves. It has successfully contributed to the theoretical understanding of laser interferometer gravitational-wave detectors (used by LIGO, VIRGO and KaGRA) and helped many important ex

Sheng-Wen Li, Fu Li, Tao Peng, G. S. Agarwal

When a laser beam passes through a rotating ground glass (RGG), the scattered light exhibits thermal statistics. This is extensively used in speckle imaging. This scattering process has not been addressed in photon picture and is especially relevant if non-classical light is scattered by the RGG. We develop the photon picture for the scattering process using

Yuwen Li, Ludmil T. Zikatanov

We present residual-based a posteriori error estimates of mixed finite element methods for the three-field formulation of Biot's consolidation model. The error estimator is an upper and lower bound of the space time discretization error up to data oscillation. As a by-product, we also obtain new a posteriori error estimate of mixed finite element methods for

Xiaolong Hu, Zhulin An, Chuanguang Yang, Hui Zhu

Convolutional neural networks (ConvNets) are widely used in real life. People usually use ConvNets which pre-trained on a fixed number of classes. However, for different application scenarios, we usually do not need all of the classes, which means ConvNets are redundant when dealing with these tasks. This paper focuses on the redundancy of ConvNet channels.

Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun

We initiate the study of multi-stage episodic reinforcement learning under adversarial corruptions in both the rewards and the transition probabilities of the underlying system extending recent results for the special case of stochastic bandits. We provide a framework which modifies the aggressive exploration enjoyed by existing reinforcement learning approa

Ran Han, Yu-Feng Li, Xin Mao

An accurate prediction of the geo-neutrino signal from the crust serves as a necessary prerequisite in the determination of the geo-neutrino flux from the mantle. In this work we report the non-negligible effect associated to the exact three-flavor antineutrino survival probability in the calculation of the crustal geo-neutrino signal, which was usually appr

Guanying Liu, An Liu, Rui Zhang, Min-Jian Zhao

In this paper, we consider a mmWave massive multiple-input multiple-output (MIMO) communication system with one static base station (BS) serving a fast-moving user, both equipped with a very large array. The transmitted signal arrives at the user through multiple paths, each with a different angle of-arrival and hence Doppler frequency offset, thus resulting

Haema Nilakanta, Zack W. Almquist, Galin L. Jones

The literature in social network analysis has largely focused on methods and models which require complete network data; however there exist many networks which can only be studied via sampling methods due to the scale or complexity of the network, access limitations, or the population of interest is hard to reach. In such cases, the application of random wa

Yousef Atoum, Mao Ye, Liu Ren, Ying Tai

Absence of nearby light sources while capturing an image will degrade the visibility and quality of the captured image, making computer vision tasks difficult. In this paper, a color-wise attention network (CWAN) is proposed for low-light image enhancement based on convolutional neural networks. Motivated by the human visual system when looking at dark image

Oussama Abderrahmane Dambri, Soumaya Cherkaoui

Nanomachines promise to enable new medical applications, including drug delivery and real time chemical reactions' detection inside the human body. Such complex tasks need cooperation between nanomachines using a communication network. Wireless Ad hoc networks, using molecular or electromagnetic-based communication have been proposed in the literature to

Zuchao Li, Hai Zhao, Kevin Parnow

Most syntactic dependency parsing models may fall into one of two categories: transition- and graph-based models. The former models enjoy high inference efficiency with linear time complexity, but they rely on the stacking or re-ranking of partially-built parse trees to build a complete parse tree and are stuck with slower training for the necessity of dynam

Mingkang Wang, Vladimir Aksyuk

Thermodynamic fluctuations in mechanical resonators cause uncertainty in their frequency measurement, fundamentally limiting performance of frequency-based sensors. Recently, integrating nanophotonic motion readout with micro- and nano-mechanical resonators allowed practical chip-scale sensors to routinely operate near this limit in high-bandwidth measuremen

Hamid Reza Vaezi Joze, Amirreza Shaban, Michael L. Iuzzolino, Kazuhito Koishida

In late fusion, each modality is processed in a separate unimodal Convolutional Neural Network (CNN) stream and the scores of each modality are fused at the end. Due to its simplicity late fusion is still the predominant approach in many state-of-the-art multimodal applications. In this paper, we present a simple neural network module for leveraging the know

Hai-Cheng. Feng, H. T. Liu, J. M. Bai, L. F. Xing

In order to study short timescale optical variability of $\gamma$-ray blazar S5 0716+714, quasi-simultaneous spectroscopic and multi-band photometric observations were performed from 2018 November to 2019 March with the 2.4 m optical telescope located at Lijiang Observatory of Yunnan Observatories. The observed spectra are well fitted with a power-law $F_{\l

Pavana Prabhakar, Ricardo Garcia, Muhammad Ali Imam, Vinay Damodaran

The adverse effects of sea water environment on the fatigue life of woven carbon fiber/vinyl ester composites are established at room temperature in view of long-term survivability of offshore structures. It is observed that the influence of sea water saturation on the fatigue life is more pronounced when the maximum cyclic displacement approaches maximum qu

Kōsaku Takanashi, Kenichiro McAlinn

We discuss the finite sample theoretical properties of online predictions in non-stationary time series under model misspecification. To analyze the theoretical predictive properties of statistical methods under this setting, we first define the Kullback-Leibler risk, in order to place the problem within a decision theoretic framework. Under this framework,

S. P. Moschou, I. V. Sokolov, O. Cohen, G. Toth

Heliospheric plasmas require multi-scale and multi-physics considerations. On one hand, MHD codes are widely used for global simulations of the solar-terrestrial environments, but do not provide the most elaborate physical description of space plasmas. Hybrid codes, on the other hand, capture important physical processes, such as electric currents and effect

Vicente Cortés, Calin Lazaroiu, C. S. Shahbazi

We develop a new framework for the study of generalized Killing spinors, where generalized Killing spinor equations, possibly with constraints, can be formulated equivalently as systems of partial differential equations for a polyform satisfying algebraic relations in the K\"ahler-Atiyah bundle constructed by quantizing the exterior algebra bundle of the und

Kwang-Hyun Uhm, Seung-Wook Kim, Seo-Won Ji, Sung-Jin Cho

Recent research on learning a mapping between raw Bayer images and RGB images has progressed with the development of deep convolutional neural networks. A challenging data set namely the Zurich Raw-to-RGB data set (ZRR) has been released in the AIM 2019 raw-to-RGB mapping challenge. In ZRR, input raw and target RGB images are captured by two different camera

Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert

While deep learning has shown tremendous success in a wide range of domains, it remains a grand challenge to incorporate physical principles in a systematic manner to the design, training, and inference of such models. In this paper, we aim to predict turbulent flow by learning its highly nonlinear dynamics from spatiotemporal velocity fields of large-scale

Maurizio Carbone, Michele Iovieno, Andrew D Bragg

Analyzing the fluid velocity gradients in a Lagrangian reference frame provides an insightful way to study the small-scale dynamics of turbulent flows, and further insight is provided by considering the equations in the eigenframe of the strain-rate tensor. The dynamics of the velocity gradient tensor is governed in part by the anisotropic pressure Hessian,

Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen

Person re-identification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras, of which it is of great importance to learn multifaceted features expressed in different parts of a person, e.g., clothes, bags, and other accessories in the main body, appearance in the head, and shoes in the foot. To learn such features, existi

Tommy Jones

This research proposes a new (old) metric for evaluating goodness of fit in topic models, the coefficient of determination, or $R^2$. Within the context of topic modeling, $R^2$ has the same interpretation that it does when used in a broader class of statistical models. Reporting $R^2$ with topic models addresses two current problems in topic modeling: a lac

Gennadi V. Glinsky

Gene set enrichment analyses of 8,405 genes linked with 35,074 human-specific (hs) regulatory single-nucleotide changes (SNCs) revealed the staggering breadth of significant associations with morphological structures, physiological processes, and pathological conditions of Modern Humans. Significant enrichment traits include more than 1,000 anatomically-dist

A. I. Molev, E. Ragoucy

We introduce a new family of Poisson vertex algebras $\mathcal{W}(\mathfrak{a})$ analogous to the classical $\mathcal{W}$-algebras. The algebra $\mathcal{W}(\mathfrak{a})$ is associated with the centralizer $\mathfrak{a}$ of an arbitrary nilpotent element in $\mathfrak{gl}_N$. We show that $\mathcal{W}(\mathfrak{a})$ is an algebra of polynomials in infinitel

Jiye Yuan, Tengfei Zhao, Jiqiang Zheng

This article studies the pointwise convergence for the fractional Schr\"odinger operator $P^{t}_{a,\gamma}$ with complex time in one spatial dimension. Through establishing $L^2$-maximal estimates for initial datum in $H^{s}(\mathbb{R})$, we see that the solution converges to the initial data almost everywhere with $s>\frac14 a(1-\frac1\gamma)_+$ when $0<a<1

Tsuyoshi Yoshida, Mikael Mazur, Jochen Schröder, Magnus Karlsson

Performance monitoring is an essential function for margin measurements in live systems. Historically, system budgets have been described by the Q-factor converted from the bit error rate (BER) under binary modulation and direct detection. The introduction of hard-decision forward error correction (FEC) did not change this. In recent years technologies have

L. H. Quiroga-Nuñez, H. T. Intema, J. R. Callingham, J. Villadsen

Serendipitously, we have rediscovered radio emission from the binary system Ross 867 (M4.5V) and Ross 868 (M3.5V) while inspecting archival Giant Metrewave Radio Telescope (GMRT) observations. The binary system consists of two M-dwarf stars that share common characteristics such as spectral type, astrometric parameters, age and emission at infrared, optical