December 2020 arXiv papers — page 60

Nicholas Krämer, Philipp Hennig

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of theoretical analysis. However, these algorithms suffer from numerical instability when run at high order or with small st

Pablo G. Ortega, David R. Entem

Heavy hadron spectroscopy was well understood within the naive quark model until the end of the past century. However, in 2003, the $X(3872)$ was discovered, with puzzling properties difficult to understand in the simple naive quark model picture. This state made clear that excited states of heavy mesons should be coupled to two-meson states in order to unde

Surbhi Beniwal, Ajay Kumar, Preeti Luthra

We introduce and explore the theory of tensor products in the category of local operator systems. Analogous to minimal operator system OMIN and maximal operator system OMAX, minimal and maximal local operator system structures LOMIN and LOMAX, respectively, are also discussed.

Stefano Viaggiu

After a critical overview of the Generalized Uncertainty Principle (GUP) applied to compact objects, we propose a texture of Heisenberg uncertainty principle in curved spacetimes (CHUP). CHUP allows to write down physically motivated STUR (spacetime uncertainty relations) in a generic background for a non commutative spacetime in terms of tetrad variables. I

Xiaozhong Ji, Guangpin Tao, Yun Cao, Ying Tai

Recent deep-learning based Super-Resolution (SR) methods have achieved remarkable performance on images with known degradation. However, these methods always fail in real-world scene, since the Low-Resolution (LR) images after the ideal degradation (e.g., bicubic down-sampling) deviate from real source domain. The domain gap between the LR images and the rea

Walter Boscheri, Giacomo Dimarco, Lorenzo Pareschi

In this work we propose a novel space-dependent multiscale model for the spread of infectious diseases in a two-dimensional spatial context on realistic geographical scenarios. The model couples a system of kinetic transport equations describing a population of commuters moving on a large scale (extra-urban) with a system of diffusion equations characterizin

C. Maitra, F. Haberl, G. Vasilopoulos, L. Ducci

Supergiant fast X-ray transients (SFXTs) are a peculiar class of supergiant high-mass X-ray binary (HMXB) systems characterised by extreme variability in the X-ray domain. In current models, this is mainly attributed to the clumpy nature of the stellar wind coupled with gating mechanisms involving the spin and magnetic field of the neutron star. We studied t

Tingxiang Fan, Dawei Wang, Wenxi Liu, Jia Pan

Navigation in dense crowds is a well-known open problem in robotics with many challenges in mapping, localization, and planning. Traditional solutions consider dense pedestrians as passive/active moving obstacles that are the cause of all troubles: they negatively affect the sensing of static scene landmarks and must be actively avoided for safety. In this p

Ying Lei, Shaoliang Zhang

Superradiant phase transition represents an important quantum phenomenon that shows the collective excitations based on the coupling between atoms and cavity modes. The spin-orbit coupling is another quantum effect which induced from the interaction of the atom internal degrees of freedom and momentum of center-of-mass. In this work, we consider the cavity a

A. -M. Bachmann, P. Muggli, AWAKE Collaboration

In AWAKE a self-modulated proton bunch drives wakefields in a plasma. Recent experiments successfully demonstrated many aspects of the self-modulation of the drive bunch as well as acceleration of test electrons. Next experiments will focus on producing a multi-GeV accelerated electron bunch with low emittance and low energy spread. The experiment requires a

Sunil Kumar, Arvind Singh, Sandeep Kumar, Anand Nivedan

THz conductivity of large area MoS2 and MoSe2 monolayers as well as their vertical heterostructure, MoSe2MoS2 is measured in the 0.3-5 THz frequency range. Compared to the monolayers, the ultrafast THz reflectivity of the MoSe2MoS2 heterobilayer is enhanced many folds when optically excited above the direct band gap energies of the constituting monolayers. T

Humphrey O. Obie, Waqar Hussain, Xin Xia, John Grundy

Ubiquitous technologies such as mobile software applications (mobile apps) have a tremendous influence on the evolution of the social, cultural, economic, and political facets of life in society. Mobile apps fulfil many practical purposes for users including entertainment, transportation, financial management, etc. Given the ubiquity of mobile apps in the li

Yu-Qin Chen, Yi-Cong Zheng, Shengyu Zhang, Chang-Yu Hsieh

With continuing improvements on the quality of fabricated quantum devices, it becomes increasingly crucial to analyze noisy quantum process in greater details such as characterizing the non-Markovianity in a quantitative manner. In this work, we propose an experimental protocol, termed Spectral Transfer Tensor Maps (SpecTTM), to accurately predict the RHP no

Ming Liu, Kaoru Hisama, Yongjia Zheng, Mina Maruyama

Single- and multi-walled molybdenum disulfide (MoS$_2$) nanotubes have been coaxially grown on small diameter boron nitride nanotubes (BNNTs) which were synthesized from heteronanotubes by removing single-walled carbon nanotubes (SWCNTs), and systematically investigated by optical spectroscopy. The strong photoluminescence (PL) from single-walled MoS$_2$ nan

Noriki Fujisato, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai

Let $\Sigma$ and $\Pi$ be disjoint alphabets, respectively called the static alphabet and the parameterized alphabet. Two strings $x$ and $y$ over $\Sigma \cup \Pi$ of equal length are said to parameterized match (p-match) if there exists a renaming bijection $f$ on $\Sigma$ and $\Pi$ which is identity on $\Sigma$ and maps the characters of $x$ to those of $

Gabriel Moldovan, Guillame Lehnasch, Laurent Cordier, Marcello Meldi

A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid flows is presented in this research work. The main feature of this estimator is that the Kalman filter update, which relies on the determination of the Kalman gain, is performed exploiting the algorithmic features of the numerical solver employed as a model. More precis

Satoshi Hagiwara, Chunping Hu, Satomichi Nishihara, Minoru Otani

We investigate the process by which a water molecule diffuses on the surface of an Al(111) electrode under constant bias voltage by first-principles density functional theory. To understand the diffusion path of the water on the Al(111), we calculated the minimum energy path (MEP) determined by the nudged elastic band method in combination with constant elec

Alexander Lehmann, Alexander Rothkopf

We compute the proper real-time interaction potential between a static quark and antiquark in classical lattice gauge theory at finite temperature. Our central result is the determination of the screened real-part of this potential, and we reconfirm the presence of an imaginary part. The real part is intimately related to the back-reaction of the static sour

Hrvoje Dodig

In 19th century Maxwell derived Maxwell equations from the knowledge of three experimental physical laws: the Coulomb's law, the Ampere's force law and Faraday's law of induction. However, theoretical basis for Ampere's force law and Faraday's law remains unknown to this day. Furthermore, the Lorentz force is considered as experimental phenomena, the theoret

Ting Dong, Jie Luo, Hongchen Chu, Xiang Xiong

Deep-subwavelength all-dielectric composite materials are believed to tightly obey the Maxwell Garnett effective medium theory. Here, we demonstrate that the Maxwell Garnett theory could break down due to evanescent fields in deep-subwavelength dielectric structures. By utilizing two- and three-dimensional dielectric composite materials with inhomogeneities

Eranda Dhananjaya, Wei-Tian Li

A simple graph $G$ is said to admit an antimagic orientation if there exist an orientation on the edges of $G$ and a bijection from $E(G)$ to $\{1,2,\ldots,|E(G)|\}$ such that the vertex sums of vertices are pairwise distinct, where the vertex sum of a vertex is defined to be the sum of the labels of the in-edges minus that of the out-edges incident to the v

Flemming Nielson, Hanne Riis Nielson

This book is an introduction to program analysis that is meant to be considerably more elementary than our advanced book Principles of Program Analysis (Springer, 2005). Rather than using flow charts as the model of programs, the book follows our introductory book Formal Methods an Appetizer (Springer, 2019) using program graphs as the model of programs. In

A. Pietrinferni, S. L. Hidalgo, S. Cassisi, M. Salaris

This is the second paper of a series devoted to present an updated release of the BaSTI ( a Bag of Stellar Tracks and Isochrones) stellar model and isochrone library. Following the publication of the updated solar scaled library, here we present the library for a $\alpha-$enhanced heavy element distribution. These new alpha-enhanced models account for all im

Maryam Daryalal, Merve Bodur

In a telecommunication network, Routing and Wavelength Assignment (RWA) is the problem of finding lightpaths for incoming connection requests. When facing a dynamic traffic, greedy assignment of lightpaths to incoming requests based on predefined deterministic policies leads to a fragmented network that cannot make use of its full capacity due to stranded ba

Hironori Hidaka, Yusuke Monno, Masatoshi Okutomi

A lighting-based multispectral imaging system using an RGB camera and a projector is one of the most practical and low-cost systems to acquire multispectral observations for estimating the scene's spectral reflectance information. However, existing projector-based systems assume that the spectral power distribution (SPD) of each projector primary is known, w

Mahmoud Nazzal, Mehmet Ali Aygul, Huseyin Arslan

Applying compressive sensing (CS) allows for sub-Nyquist sampling in several application areas in 5G and beyond. This reduces the associated training, feedback, and computation overheads in many applications. However, the applicability of CS relies on the validity of a signal sparsity assumption and knowing the exact sparsity level. It is customary to assume

Martianus Frederic Ezerman, John Mark Lampos, San Ling, Buket Ozkaya

Spectral bounds on the minimum distance of quasi-twisted codes over finite fields are proposed, based on eigenvalues of polynomial matrices and the corresponding eigenspaces. They generalize the Semenov-Trifonov and Zeh-Ling bounds in a way similar to how the Roos and shift bounds extend the BCH and HT bounds for cyclic codes. The eigencodes of a quasi-twist

Stefan Floerchinger, Tobias Haas, Ben Hoeber

Quantum uncertainty relations are formulated in terms of relative entropy between distributions of measurement outcomes and suitable reference distributions with maximum entropy. This type of entropic uncertainty relation can be applied directly to observables with either discrete or continuous spectra. We find that a sum of relative entropies is bounded fro

Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li

Network pruning is a widely used technique to reduce computation cost and model size for deep neural networks. However, the typical three-stage pipeline, i.e., training, pruning and retraining (fine-tuning) significantly increases the overall training trails. In this paper, we develop a systematic weight-pruning optimization approach based on Surrogate Lagra

Kai Wang, Yuxin Gu, Xiaojiang Peng, Panpan Zhang

The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which pose an evident challenge for adapting the FER model trained on one dataset to another one. Recent works mainly focus on domain-invariant deep feature learning with adversarial le

Clément de Chaisemartin, Xavier D'Haultfœuille

We study two-way-fixed-effects regressions (TWFE) with several treatment variables. Under a parallel trends assumption, we show that the coefficient on each treatment identifies a weighted sum of that treatment's effect, with possibly negative weights, plus a weighted sum of the effects of the other treatments. Thus, those estimators are not robust to hetero

Kieran Browne, Ben Swift

Recent papers in explainable AI have made a compelling case for counterfactual modes of explanation. While counterfactual explanations appear to be extremely effective in some instances, they are formally equivalent to adversarial examples. This presents an apparent paradox for explainability researchers: if these two procedures are formally equivalent, what

Guorui Chen, Aaron L. Sharpe, Eli J. Fox, Shaoxin Wang

The flat bands resulting from moir\'e superlattices in magic-angle twisted bilayer graphene (MATBG) and ABC-trilayer graphene aligned with hexagonal boron nitride (ABC-TLG/hBN) have been shown to give rise to fascinating correlated electron phenomena such as correlated insulators and superconductivity. More recently, orbital magnetism associated with correla

Jianqiang Ma, Zeyu Yan, Shuai Pang, Yang Zhang

On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slot-filling approach by building several dedicated models for each type of slots. Such modularized systems are not only complex butalso of limited capacity for capturing inter-dependencies among SQL clauses. To solve these problems, this paper proposes a novel extraction-linking

Maxim Olshanskii, Alexander Zhiliakov

The paper discusses a reuse of matrix factorization as a building block in the Augmented Lagrangian (AL) and modified AL preconditioners for non-symmetric saddle point linear algebraic systems. The strategy is applied to solve two-dimensional incompressible fluid problems with efficiency rates independent of the Reynolds number. The solver is then tested to

Satoshi Taguchi, Tetsuro Tsuji

A system of fluid-dynamic-type equations and their boundary conditions derived from a system of the Boltzmann equation is of great importance in kinetic theory when we are concerned with the motion of a slightly rarefied gas. It offers an efficient alternative to solving the Boltzmann equation directly and, more importantly, provides a clear picture of the f

Limin Wang, Zhan Tong, Bin Ji, Gangshan Wu

Temporal modeling still remains challenging for action recognition in videos. To mitigate this issue, this paper presents a new video architecture, termed as Temporal Difference Network (TDN), with a focus on capturing multi-scale temporal information for efficient action recognition. The core of our TDN is to devise an efficient temporal module (TDM) by exp

Zoya Masih, Manouchehr Zaker

The Grundy and the {\rm b}-chromatic number of graphs are two important chromatic parameters. The Grundy number of a graph $G$, denoted by $\Gamma(G)$ is the worst case behavior of greedy (First-Fit) coloring procedure for $G$ and the {\rm b}-chromatic number ${\rm{b}}(G)$ is the maximum number of colors used in any color-dominating coloring of $G$. Because

Wei Huang, Tianrui Li, Dexian Wang, Shengdong Du

In the federated learning setting, multiple clients jointly train a model under the coordination of the central server, while the training data is kept on the client to ensure privacy. Normally, inconsistent distribution of data across different devices in a federated network and limited communication bandwidth between end devices impose both statistical het

Manoj Kumar, Syed Abbas

Quarantine of those individuals who are suspected of being infected is one of the intervention measures to contain the spread of an infectious disease. We propose an age structured SEQIR (S-Susceptible, E-Exposed, Q-Quarantine, I-Infected, R-Recovered) model with vaccination of susceptible and exposed individuals. Firstly without vaccination, basic reproduct

V. Vilfred Kamalappan

Circulant graphs $C_n(R)$ and $C_n(S)$ are said to be \emph{Adam's isomorphic} if there exist some $a\in \mathbb{Z}_n^*$ such that $S = a R$ under arithmetic reflexive modulo $n$. In 1970, Elspas and Turner \cite{eltu} raised a question on the isomorphism of $C_{16}(1, 3, 7)$ and $C_{16}(2, 3, 5)$ and Vilfred \cite{v96} gave its answer by defining Type-2 iso

Philipp Werner, Steven Johnston, Martin Eckstein

Resonant inelastic X-ray scattering (RIXS) detects various types of high- and low-energy elementary excitations in correlated solids, and this tool will play an increasingly important role in investigations of time-dependent phenomena in photo-excited systems. While theoretical frameworks for the computation of equilibrium RIXS spectra are well established,

Fan Lu, Guang Chen, Sanqing Qu, Zhijun Li

LiDAR point cloud streams are usually sparse in time dimension, which is limited by hardware performance. Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras. To overcome the temporal limitations of LiDAR sensors, a novel task named Point Cloud Frame Interpolation is studie

Rongxin Luo, Jong-Hak Woo, Marios Karouzos, Hyun-Jin Bae

There is an ongoing debate on whether feedback from active galactic nuclei (AGNs) can effectively regulate the star formation activities in their host galaxies. To investigate the feedback effect of AGN-driven outflows, we perform integral-field spectroscopic observations of 40 moderate-luminosity (10$^{41.5}$ $<$ L$_{\rm [OIII];cor}$ $<$ 10$^{43.1}$ erg s$^

N. Karjanto, F. Beauducel

A perpetual calendar, a calendar designed to find out the day of the week for a given date, employs a rich arithmetical calculation using congruence. Zeller's congruence is a well-known algorithm to calculate the day of the week for any Julian or Gregorian calendar date. Another rather infamous perpetual calendar has been used for nearly four centuries among

S. Christina, T. Ibungochouba Singh

In this paper, the tunneling of vector boson particles across the event horizon of Kerr-Newman-de Sitter (KNdS) black hole is investigated using the WKB approximation and Hamilton-Jacobi ansatz to Proca equation. The tunneling probability and radiation spectrum at the event horizon of KNdS black hole is obtained. The modified Hawking radiation of stationary

Xiong Liu, Luca A. Finelli, Greg L. Hersch, Iya Khalil

COVID-19 clinical trial design is a critical task in developing therapeutics for the prevention and treatment of COVID-19. In this study, we apply a deep learning approach to extract eligibility criteria variables from COVID-19 trials to enable quantitative analysis of trial design and optimization. Specifically, we train attention-based bidirectional Long S

Haoran Wang, Jun Zhang, Hekun Li, Zhi Shen

In image processing, source detections are inevitably affected by the presence of the geometric boundaries in the images, including the physical boundaries of the CCD, and the boundaries of masked regions due to column defects, bright diffraction spikes, etc.. These boundary conditions make the source detection process not statistically isotropic. It can lea

Rohith K. Thiruvalluru, Manas Gaur, Krishnaprasad Thirunarayan, Amit Sheth

Suicide is the 10th leading cause of death in the US and the 2nd leading cause of death among teenagers. Clinical and psychosocial factors contribute to suicide risk (SRFs), although documentation and self-expression of such factors in EHRs and social networks vary. This study investigates the degree of variance across EHRs and social networks. We performed

Ray P. Norris, Barnaby R. M. Norris

There are two puzzles surrounding the Pleiades, or Seven Sisters. First, why are the mythological stories surrounding them, typically involving seven young girls being chased by a man associated with the constellation Orion, so similar in vastly separated cultures, such as the Australian Aboriginal cultures and Greek mythology? Second, why do most cultures c

Masatomo Sawahara

Cylinders in projective varieties play an important role in connection with unipotent group actions on certain affine algebraic varieties. The previous work due to Dubouloz and Kishimoto deals with the condition for a del Pezzo fibration to contain a vertical cylinder. In the present work, as a generalization in the sense of singularities, we shall determine

M. Leconte

Nonlinear relaxation oscillations of flow-shear induced transport barriers can be qualitatively reproduced using a phenomenological critical-gradient model [M. Leconte, Y.M. Jeon and G.S. Yun, \emph{Contrib. Plasma Phys.} 56, 736 (2016]. Here, we give a more in-depth analysis of the mechanism of these nonlinear oscillations, associated to nonlinear \emph{pha

Dalmau Reig-i-Plessis, Alannah M. Hallas

Pyrochlore lattices, which are found in two important classes of materials -- the $A_2B_2X_7$ pyrochlore family and the $AB_2X_4$ spinel family -- are the quintessential 3-dimensional frustrated lattice architecture. While historically oxides ($X =$~O) have played the starring role in this field, the past decade has seen materials synthesis breakthroughs tha

Sonal Saxena, Suman Bagchi, Mohammad Tayyab, Juzer Ali Chakera

We report enhanced broadband Terahertz (THz) generation and detailed characterization from the interaction of femtosecond two colour laser pulses with thin transparent dielectric tape target in ambient air. The proposed source is easy to implement, exhibits excellent scalability with laser energy. Spectral characterization using Fourier transform spectromete

Yu-Wen Chen, Sourav Medya, Yi-Chun Chen

Tropospheric ozone (O3) is a greenhouse gas which can absorb heat and make the weather even hotter during extreme heatwaves. Besides, it is an influential ground-level air pollutant which can severely damage the environment. Thus evaluating the importance of various factors related to the O3 formation process is essential. However, O3 simulated by the availa

Akihiro Suzuki, Keiichi Maeda

We present the results of two-dimensional radiation-hydrodynamic simulations of expanding supernova ejecta with a central energy source. As suggested in previous multi-dimensional hydrodynamic simulations, a sufficiently powerful central energy source can blow away the expanding supernova ejecta, leading to efficient mixing of stratified layers in the ejecta

Karthik Bhat, Manan Bhandari, ChangSeok Oh, Sujin Kim

With the enhancement of Machine Learning, many tools are being designed to assist developers to easily create their Machine Learning models. In this paper, we propose a novel method for auto creation of such custom models for constraint devices using transfer learning without the need to write any machine learning code. We share the architecture of our autom

Shota Horiguchi, Paola Garcia, Yusuke Fujita, Shinji Watanabe

This paper investigates the utilization of an end-to-end diarization model as post-processing of conventional clustering-based diarization. Clustering-based diarization methods partition frames into clusters of the number of speakers; thus, they typically cannot handle overlapping speech because each frame is assigned to one speaker. On the other hand, some

Bo Peng, Cody Lamarche, Gordon Stacey, Thomas Nikola

The Nitrogen-to-Oxygen (N/O) abundance ratio is an important diagnostic of galaxy evolution since the ratio is closely tied to the growth of metallicity and the star formation history in galaxies. Estimates for the N/O ratio are traditionally accomplished with optical lines that could suffer from extinction and excitation effects, so the N/O ratio is arguabl

Yuan Sun, Samuel Esler, Dhananjay Thiruvady, Andreas T. Ernst

We investigate an important research question for solving the car sequencing problem, that is, which characteristics make an instance hard to solve? To do so, we carry out an instance space analysis for the car sequencing problem, by extracting a vector of problem features to characterize an instance. In order to visualize the instance space, the feature vec

Ayush Kaushal, Tejas Vaidhya

Twitter has acted as an important source of information during disasters and pandemic, especially during the times of COVID-19. In this paper, we describe our system entry for WNUT 2020 Shared Task-3. The task was aimed at automating the extraction of a variety of COVID-19 related events from Twitter, such as individuals who recently contracted the virus, so

D. Stern, S. G. Djorgovski, A. Krone-Martins, D. Sluse

Combining the exquisite angular resolution of Gaia with optical light curves and WISE photometry, the Gaia Gravitational Lenses group (GraL) uses machine learning techniques to identify candidate strongly lensed quasars, and has confirmed over two dozen new strongly lensed quasars from the Gaia Data Release 2. This paper reports on the 12 quadruply-imaged qu

Ching Hung Lam, Hiromichi Yamada

An irreducible module for the parafermion vertex operator algebra $K(\mathfrak{sl}_2,k)$ is said to be of $\sigma$-type if an automorphism of the fusion algebra of $K(\mathfrak{sl}_2,k)$ of order $k$ is trivial on it. For any integer $k \ge 3$, we show that there exists an automorphism of order $2$ of the subalgebra of the fusion algebra of $K(\mathfrak{sl}_

Puneet Bakshi, Sukumar Nandi

Recently, Government of India has taken several initiatives to make India digitally strong such as to provide each resident a unique digital identity, referred to as Aadhaar, and to provide several online e-Governance services based on Aadhaar such as DigiLocker. DigiLocker is an online service which provides a shareable private storage space on public cloud

Ryan Goh, Tasso J. Kaper, Theodore Vo

In this article, the phenomenon of delayed Hopf bifurcations (DHB) in reaction-diffusion PDEs is analyzed in the cubic Complex Ginzburg-Landau equation with a slowly-varying parameter. We use the classical asymptotic methods of stationary phase and steepest descents to show that solutions which approach the attracting quasi-steady state (QSS) before the Hopf

Sifan Wang, Hanwen Wang, Paris Perdikaris

Physics-informed neural networks (PINNs) are demonstrating remarkable promise in integrating physical models with gappy and noisy observational data, but they still struggle in cases where the target functions to be approximated exhibit high-frequency or multi-scale features. In this work we investigate this limitation through the lens of Neural Tangent Kern

Yian Chen, Yuehaw Khoo, Michael Lindsey

We consider the optimization of pairwise objective functions, i.e., objective functions of the form $H(\mathbf{x}) = H(x_1,\ldots,x_N) = \sum_{1\leq i<j \leq N} H_{ij}(x_i,x_j)$ for $x_i$ in some continuous state spaces $\mathcal{X}_i$. Global optimization in this setting is generally confounded by the possible existence of spurious local minima and the impo

Garima Arora, P Bandyopadhyay, M G Hariprasad, A Sen

Pinned solitons are a special class of nonlinear solutions created by a supersonically moving object in a fluid. They move with the same velocity as the moving object and thereby remain pinned to the object. A well known hydrodynamical phenomenon, they have been shown to exist in numerical simulation studies but to date have not been observed experimentally

Daniel Stern, Dominic Walton

MG 1131+0456 is a radio-selected gravitational lens, and is the first known Einstein ring. Discovered in 1988, the system consists of a bright radio source imaged into a ring and two compact, flat-spectrum components separated by 2.1 arcsec. The ring is optically faint (R = 23.3), rising steeply into the near- and mid-infrared (K = 17.8; W2 = 13.4). The syst

Peter Schaldenbrand, Jean Oh

The objective of most Reinforcement Learning painting agents is to minimize the loss between a target image and the paint canvas. Human painter artistry emphasizes important features of the target image rather than simply reproducing it (DiPaola 2007). Using adversarial or L2 losses in the RL painting models, although its final output is generally a work of

Zelin Xu, Ke Chen, Kangjun Liu, Changxing Ding

Object point cloud classification has drawn great research attention since the release of benchmarking datasets, such as the ModelNet and the ShapeNet. These benchmarks assume point clouds covering complete surfaces of object instances, for which plenty of high-performing methods have been developed. However, their settings deviate from those often met in pr

Himani Sharma

For an operator generating a group on $L^p$ spaces transference results give bounds on the Phillips functional calculus also known as spectral multiplier estimates. In this paper we consider specific group generators which are abstraction of first order differential operators and prove similar spectral multiplier estimates assuming only that the group is bou

Zhao Wang, Aron Culotta

Spurious correlations threaten the validity of statistical classifiers. While model accuracy may appear high when the test data is from the same distribution as the training data, it can quickly degrade when the test distribution changes. For example, it has been shown that classifiers perform poorly when humans make minor modifications to change the label o

Feimin Huang, Jie Kuang, Dehua Wang, Wei Xiang

We consider the stability of transonic contact discontinuity for the two-dimensional steady compressible Euler flows in a finitely long nozzle. This is the first work on the mixed-type problem of transonic flows across a contact discontinuity as a free boundary in nozzles. We start with the Euler-Lagrangian transformation to straighten the contact discontinu

Yaguang Li, Timothy R. Bedding, Dennis Stello, Sanjib Sharma

Asteroseismic scaling relations are often used to derive stellar masses and radii, particulaly for stellar, exoplanet, and Galactic studies. It is therefore important that their precisions are known. Here we measure the intrinsic scatter of the underlying seismic scaling relations for $\Delta\nu$ and $\nu_{\rm max}$, using two sharp features that are formed

Tianhao Shao, Jinhui Chen, Che Ming Ko, Zi-Wei Lin

We introduce additional coalescence factors for the production of strange baryons in a multiphase transport (AMPT) model in order to describe the enhanced production of multistrange hadrons observed in Pb-Pb collisions at $\rm \sqrt{s_{NN}}$ = 2.76 TeV at the Large hadron Collider (LHC) and Au+Au collisions at $\rm \sqrt{s_{NN}}$ = 200 GeV at Relativistic He

Palash Dey, Suman Kalyan Maity, Sourav Medya, Arlei Silva

Network robustness is a measure a network's ability to survive adversarial attacks. But not all parts of a network are equal. K-cores, which are dense subgraphs, are known to capture some of the key properties of many real-life networks. Therefore, previous work has attempted to model network robustness via the stability of its k-core. However, these approac

Li-Chin Yeh, Ing-Guey Jiang

The photometric light curves of BRITE satellites were examined through a machine learning technique to investigate whether there are possible exoplanets moving around nearby bright stars. Focusing on different transit periods, several convolutional neural networks were constructed to search for transit candidates. The convolutional neural networks were train

Hezam Albaqami, Ghulam Mubashar Hassan, Abdulhamit Subasi, Amitava Datta

Electroencephalography is frequently used for diagnostic evaluation of various brain-related disorders due to its excellent resolution, non-invasive nature and low cost. However, manual analysis of EEG signals could be strenuous and a time-consuming process for experts. It requires long training time for physicians to develop expertise in it and additionally

Jerry Zikun Chen, Shi Yu, Haoran Wang

Query reformulation aims to alter noisy or ambiguous text sequences into coherent ones closer to natural language questions. This is to prevent errors from propagating in a client-facing pipeline and promote better communication with users. Besides, it is crucial to maintain performance in downstream environments like question answering when rephrased querie

Qing Mai, Xin Zhang, Yuqing Pan, Kai Deng

Modern scientific studies often collect data sets in the forms of tensors, which call for innovative statistical analysis methods. In particular, there is a pressing need for tensor clustering methods to understand the heterogeneity in the data. We propose a tensor normal mixture model (TNMM) approach to enable probabilistic interpretation and computational

Darrell Cox, Sourangshu Ghosh, Eldar Sultanow

In this paper, we shall find a new connection between $n$th degree polynomial mod $p$ congruence with $n$ roots and higher-order Fibonacci and Lucas sequences. We shall first discuss the recent work been done in sequences and their connection to polynomial congruence and then find out new relations between particular recurrence relation and the congruence of

Kyri Baker

Using machine learning to obtain solutions to AC optimal power flow has recently been a very active area of research due to the astounding speedups that result from bypassing traditional optimization techniques. However, generally ensuring feasibility of the resulting predictions while maintaining these speedups is a challenging, unsolved problem. In this pa

Zhenzhong Wang, Abolfazl Safikhani, Zhengyuan Zhu, David S. Matteson

A Vector Auto-Regressive (VAR) model is commonly used to model multivariate time series, and there are many penalized methods to handle high dimensionality. However in terms of spatio-temporal data, most methods do not take the spatial and temporal structure of the data into consideration, which may lead to unreliable network detection and inaccurate forecas

Yanxia Liu, Yongjian Wang, Zuohuan Zheng, Shu Chen

We analytically determine the non-Hermitian mobility edges of a one-dimensional quasiperiodic lattice model with exponential decaying hopping and complex potentials as well as its dual model, which is just a non-Hermitian generalization of the Ganeshan-Pixley-Das Sarma model with nonreciprocal nearest-neighboring hopping. The presence of non-Hermitian term d

Elizabeth Paul, Matt Landreman, Thomas Antonsen

Using recently developed adjoint methods for computing the shape derivatives of functions that depend on MHD equilibria (Antonsen et al. 2019; Paul et al. 2020), we present the first example of analytic gradient-based optimization of fixed-boundary stellarator equilibria. We take advantage of gradient information to optimize figures of merit of relevance for

Rahil N. Valani, Anja C. Slim, David M. Paganin, Tapio P. Simula

A droplet bouncing on the surface of a vertically vibrating liquid bath can walk horizontally, guided by the waves it generates on each impact. This results in a self-propelled classical particle-wave entity. By using a one-dimensional theoretical pilot-wave model with a generalized wave form, we investigate the dynamics of this particle-wave entity. We empl

Zite Jiang, Tao Liu, Shuai Zhang, Zhen Guan

In the big data era, graph computing is widely used to exploit the hidden value in real-world graphs in various scenarios such as social networks, knowledge graphs, web searching, and recommendation systems. However, the random memory accesses result in inefficient use of cache and the irregular degree distribution leads to substantial load imbalance. Breadt

Joshua Foo, Robert B. Mann, Magdalena Zych

Quantum gravity is expected to contain descriptions of semiclassical spacetime geometries in quantum superpositions. To date, no framework for modelling such superpositions has been devised. Here, we provide a new phenomenological description for the response of quantum probes (i.e. Unruh-deWitt detectors) on a spacetime manifold in quantum superposition. By

Xiang Li, Danhao Ding, Ben Kao, Yizhou Sun

A heterogeneous information network (HIN) has as vertices objects of different types and as edges the relations between objects, which are also of various types. We study the problem of classifying objects in HINs. Most existing methods perform poorly when given scarce labeled objects as training sets, and methods that improve classification accuracy under s

Tran Dinh Cuong, Anh D. Phan

Iron represents the principal constituent of the Earth's core, but its high-pressure melting diagram remains ambiguous. Here we present a simple analytical approach to predict the melting properties of iron under deep-Earth conditions. In our model, anharmonic free energies of the solid phase are directly determined by the moment expansion technique in quant

James McCoy, Glen Wheeler, Yuhan Wu

A recent article by the first two authors together with B Andrews and V-M Wheeler considered the so-called `ideal curve flow', a sixth order curvature flow that seeks to deform closed planar curves to curves with least variation of total geodesic curvature in the $L^2$ sense. Critical in the analysis there was a length bound on the evolving curves. It is nat

Paul N. Patrone, Anthony J. Kearsley

Formulating accurate and robust classification strategies is a key challenge of developing diagnostic and antibody tests. Methods that do not explicitly account for disease prevalence and uncertainty therein can lead to significant classification errors. We present a novel method that leverages optimal decision theory to address this problem. As a preliminar

Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin

Researchers require timely access to real-world longitudinal electronic health records (EHR) to develop, test, validate, and implement machine learning solutions that improve the quality and efficiency of healthcare. In contrast, health systems value deeply patient privacy and data security. De-identified EHRs do not adequately address the needs of health sy

Xiwen Liu, Jeffrey Zheng, Dixiong Wang, Pariasadat Musavigharavi

We report a complementary metal oxide semiconductor (CMOS) technology compatible ferroelectric tunnel junction memristor grown directly on top of a Silicon substrate using a scandium doped aluminum nitride as the ferroelectric layer.

Geraint F. Lewis, Luke A. Barnes

In Einstein's Special Theory of Relativity, all observers measure the speed of light, $c$, to be the same. However, this refers to the round trip speed, where a clock at the origin times the outward and return trip of light reflecting off a distant mirror. Measuring the one-way speed of light is fraught with issues of clock synchronisation, and, as long as t

Chengqi Zhao, Mingxuan Wang, Qianqian Dong, Rong Ye

NeurST is an open-source toolkit for neural speech translation. The toolkit mainly focuses on end-to-end speech translation, which is easy to use, modify, and extend to advanced speech translation research and products. NeurST aims at facilitating the speech translation research for NLP researchers and building reliable benchmarks for this field. It provides

Zhengeng Yang, Hongshan Yu, Yong He, Zhi-Hong Mao

Although deep learning based methods have achieved great success in many computer vision tasks, their performance relies on a large number of densely annotated samples that are typically difficult to obtain. In this paper, we focus on the problem of learning representation from unlabeled data for semantic segmentation. Inspired by two patch-based methods, we

Hiram H. López, Ivan Soprunov, Rafael H. Villarreal

The aim of this work is to study the dual and the algebraic dual of an evaluation code using standard monomials and indicator functions. We show that the dual of an evaluation code is the evaluation code of the algebraic dual. We develop an algorithm for computing a basis for the algebraic dual. Let $C_1$ and $C_2$ be linear codes spanned by standard monomia

Ellen Eischen, Stephan Ramon Garcia

Gaussian periods are certain sums of roots of unity whose study dates back to Gauss's seminal work in algebra and number theory. Recently, large scale plots of Gaussian periods have been revealed to exhibit striking visual patterns, some of which have been explored in the second named author's prior work. In 2020, the first named author produced a new app, \