December 2020 arXiv papers — page 116

Sung-En Chang, Yanyu Li, Mengshu Sun, Runbin Shi

Deep Neural Networks (DNNs) have achieved extraordinary performance in various application domains. To support diverse DNN models, efficient implementations of DNN inference on edge-computing platforms, e.g., ASICs, FPGAs, and embedded systems, are extensively investigated. Due to the huge model size and computation amount, model compression is a critical st

Jingbo Tan, Linglong Dai

Terahertz (THz) massive multiple-input multipleoutput (MIMO) has been considered as one of the promising technologies for future 6G wireless communications. It is essential to obtain channel information by beam tracking scheme to track mobile users in THz massive MIMO systems. However, the existing beam tracking schemes designed for narrowband systems with t

Pedro C. S. Costa

A quantum cellular automaton (QCA) is an abstract model consisting of an array of finite-dimensional quantum systems that evolves in discrete time by local unitary operations. Here we propose a simple coarse-graining map, where the spatial structure of the QCA is merged into effective ones. Starting with a QCA that simulates the Dirac equation, we apply this

Jian-Dong Zhang, Chenglong You, Chuang Li, Shuai Wang

SU(1,1) interferometers, based on the usage of nonlinear elements, are superior to passive interferometers in phase sensitivity. However, the SU(1,1) interferometer cannot make full use of photons carrying phase information as the second nonlinear element annihilates some of the photons inside. Here, we focus on improving phase sensitivity and propose a new

Aaron Brunk, Burkhard Dünweg, Herbert Egger, Oliver Habrich

A new model for viscoelastic phase separation is proposed, based on a systematically derived conservative two-fluid model. Dissipative effects are included by phenomenological viscoelastic terms. By construction, the model is consistent with the second law of thermodynamics, and we study well-posedness of the model, i.e., existence of weak solutions, a weak-

Chunyuan Yuan, Qianwen Ma, Wei Zhou, Jizhong Han

The dissemination of fake news significantly affects personal reputation and public trust. Recently, fake news detection has attracted tremendous attention, and previous studies mainly focused on finding clues from news content or diffusion path. However, the required features of previous models are often unavailable or insufficient in early detection scenar

Vladimir Dergachev, Maria Alessandra Papa

We present the results of an all-sky search for continuous gravitational wave signals with frequencies in the 1700-2000 Hz range from neutron stars with ellipticity of 1e-8. The search employs the Falcon analysis pipeline [citation 5] on LIGO O2 public data. Our results improve by a factor greater than 5 over [citation 11]. This is a huge leap forward: it ta

Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning

Molecule optimization is a critical step in drug development to improve desired properties of drug candidates through chemical modification. We developed a novel deep generative model Modof over molecular graphs for molecule optimization. Modof modifies a given molecule through the prediction of a single site of disconnection at the molecule and the removal

R. N. Lee, A. I. Onishchenko

We calculate master integrals for bipartite cuts of the three-loop propagator QED diagrams. These master integrals determine the spectral density of the photon self energy. Our results are expressed in terms of the iterated integrals, which, apart from the $4m$ cut, reduce to Goncharov's polylogarithms. The master integrals for $4m$ cut have been calculated

Jarrad Courts, Adrian Wills, Thomas Schön, Brett Ninness

This paper considers parameter estimation for nonlinear state-space models, which is an important but challenging problem. We address this challenge by employing a variational inference (VI) approach, which is a principled method that has deep connections to maximum likelihood estimation. This VI approach ultimately provides estimates of the model as solutio

Joseph Cho, Wayne Rossman, Tomoya Seno

We introduce an efficient route to obtaining the discrete potential mKdV equation emerging from a particular discrete motion of discrete planar curves.

Han-Hsien Huang, Mi-Yen Yeh

In this paper, we propose an approach to effectively accelerating the computation of continuous normalizing flow (CNF), which has been proven to be a powerful tool for the tasks such as variational inference and density estimation. The training time cost of CNF can be extremely high because the required number of function evaluations (NFE) for solving corres

Masayo Inoue, Kunihiko Kaneko

Living organisms must respond to environmental changes. Generally, accurate and rapid responses are provided by simple, unidirectional networks that connect inputs with outputs. Besides accuracy and speed, biological responses should also be robust to environmental or intracellular noise and mutations. Furthermore, cells must also respond to unforeseen envir

Hideitsu Hino

In supervised learning, acquiring labeled training data for a predictive model can be very costly, but acquiring a large amount of unlabeled data is often quite easy. Active learning is a method of obtaining predictive models with high precision at a limited cost through the adaptive selection of samples for labeling. This paper explains the basic problem se

Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith

Fairness and robustness are two important concerns for federated learning systems. In this work, we identify that robustness to data and model poisoning attacks and fairness, measured as the uniformity of performance across devices, are competing constraints in statistically heterogeneous networks. To address these constraints, we propose employing a simple,

Simon J. D Phoenix, Faisal Shah Khan, Berihu Teklu

The production and manipulation of quantum correlation protocols will play a central role where the quantum nature of the correlation can be used as a resource to yield properties unachievable within a classical framework is a very active and important area of research. In this work, we provide a description of a measure of correlation strength between quant

Hirotaka Kakuhama

In this paper, we determine a constant occurring in a local analogue of the Siegel-Weil formula, and describe the behavior of the formal degrees under the local theta correspondence for quaternionic dual pairs of almost equal rank over a non-Archimedean local field of characteristic $0$. As an application, we prove the formal degree conjecture of Hiraga-Ichi

Yuzhen Qin, Tommaso Menara, Danielle S. Bassett, Fabio Pasqualetti

Phase-amplitude coupling (PAC) describes the phenomenon where the power of a high-frequency oscillation evolves with the phase of a low-frequency one. We propose a model that explains the emergence of PAC in two commonly-accepted architectures in the brain, namely, a high-frequency neural oscillation driven by an external low-frequency input and two interact

Takayuki Ariga, Keito Tateishi, Michio Tomishige, Daisuke Mizuno

The movement of single kinesin molecules was observed while applying noisy external forces that mimic intracellular active fluctuations. We found kinesin accelerates under noise, especially when a large hindering load is added. The behavior quantitatively conformed to a theoretical model that describes the kinesin movement with simple two-state reactions. Th

Ritam Mallick, Shailendra Singh, Rana Nandi

This article studies the maximum mass limit of the quark star formed after the shock-induced phase transition of a cold neutron star. By employing hadronic and quark equation of state that satisfies the current mass bound, we use combustion adiabat conditions to find such a limit. The combustion adiabat condition results in a local or a global maximum pressu

Guangsheng Ma, Hongbo Li

Quantum fully homomorphic encryption (QFHE) allows to evaluate quantum circuits on encrypted data. We present a novel QFHE scheme, which extends Pauli one-time pad encryption by relying on the quaternion representation of SU(2). With the scheme, evaluating 1-qubit gates is more efficient, and evaluating general quantum circuits is polynomially improved in as

Nima Arkani-Hamed, Monica Pate, Ana-Maria Raclariu, Andrew Strominger

Celestial amplitudes represent 4D scattering of particles in boost, rather than the usual energy-momentum, eigenstates and hence are sensitive to both UV and IR physics. We show that known UV and IR properties of quantum gravity translate into powerful constraints on the analytic structure of celestial amplitudes. For example the soft UV behavior of quantum

Sosuke Kobayashi, Sho Yokoi, Jun Suzuki, Kentaro Inui

Understanding the influence of a training instance on a neural network model leads to improving interpretability. However, it is difficult and inefficient to evaluate the influence, which shows how a model's prediction would be changed if a training instance were not used. In this paper, we propose an efficient method for estimating the influence. Our method

Anaëlle Legros, Shang-Shun Zhang, Xiaojian Bai, Hao Zhang

Spin-waves e.g. magnons are the conventional elementary excitations of ordered magnets. However, other possibilities exist. For instance, magnon bound-states can arise due to attractive magnon-magnon interactions and drastically impact the static and dynamic properties of materials. Here, we demonstrate a zoo of distinct multi-magnon quasiparticles in the fr

Jiwei Liu, Bojan Tunguz, Gilberto Titericz

Black-box optimization is essential for tuning complex machine learning algorithms which are easier to experiment with than to understand. In this paper, we show that a simple ensemble of black-box optimization algorithms can outperform any single one of them. However, searching for such an optimal ensemble requires a large number of experiments. We propose

Yan Li, Kun Chen, Jun Yan, Xuebin Zhang

The optimal fingerprinting method for detection and attribution of climate change is based on a multiple regression where each covariate has measurement error whose covariance matrix is the same as that of the regression error up to a known scale. Inferences about the regression coefficients are critical not only for making statements about detection and att

In Won Yeu, Gyuseung Han, Kun Hee Ye, Cheol Seong Hwang

This work provides the community with an easily executable open-source Python package designed to automize the evaluation of Interfacial Phonons (InterPhon). Its strategy of arbitrarily defining the interfacial region and periodicity alleviates the excessive computational cost in applying ab initio phonon calculations to interfaces and enables efficient extr

Sha Hu, Zeshi Yang, Greg Mori

We consider the problem of optimizing a robot morphology to achieve the best performance for a target task, under computational resource limitations. The evaluation process for each morphological design involves learning a controller for the design, which can consume substantial time and computational resources. To address the challenge of expensive robot mo

Kayoung Ban, Yongsoo Jho, Youngjoon Kwon, Seong Chan Park

We investigate various search strategies for light vector boson $X$ in $\mathcal{O}(10)~{\rm MeV}$ mass range using $J/\Psi$ associated channels at BESIII and Belle II: (i) $J/\Psi \to \eta_c X$ with $10^{10} J/\Psi$s at BESIII, (ii) $J/\Psi (\eta_c +X) +\ell \bar{\ell}$ production at Belle~II, and (iii) $J/\Psi +X$ with the displaced vertex in $X\to e^+e^-$

Kechi Zhang, Wenhan Wang, Huangzhao Zhang, Ge Li

Program source code contains complex structure information, which can be represented in structured data forms like trees or graphs. To acquire the structural information in source code, most existing researches use abstract syntax trees (AST). A group of works add additional edges to ASTs to convert source code into graphs and use graph neural networks to le

M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed

We report a measurement of the observed cross sections of the inclusive $J/\psi$ production in $e^+e^-\rightarrow {J}/\psi{\rm X}$ based on 3.21 fb$^{-1}$ of data accumulated at energies from 3.645 to 3.891 GeV with the BESIII detector operated at the BEPCII collider. The energy-dependent lineshape obtained from the measured cross sections cannot be well des

Yepeng Ding, Hiroyuki Sato

Decentralized systems have been widely developed and applied to address security and privacy issues in centralized systems, especially since the advancement of distributed ledger technology. However, it is challenging to ensure their correct functioning with respect to their designs and minimize the technical risk before the delivery. Although formal methods

Agustin Moreno, Zhengyi Zhou

We define a hierarchy functor from the exact symplectic cobordism category to a totally ordered set from a $BL_\infty$ (Bi-Lie) formalism of the rational symplectic field theory (RSFT). The hierarchy functor consists of three levels of structures, namely algebraic planar torsion, order of semi-dilation and planarity, all taking values in $\mathbb{N}\cup \{\i

Tongxin Zhang, Zhijun Wang, Lilin Wang, Junjie Li

Sea ice growth with lamellar microstructure containing brine channels has been extensively investigated. However, the quantitative growth information of sea ice remains lack due to the uncontrolled crystalline orientation in previous investigations. For the first time, we in-situ observed the unidirectional growth of lamellar sea ice with well-manipulated ic

CMS Collaboration

A search for leptoquarks produced singly and in pairs in proton-proton collisions is presented. We consider the leptoquark (LQ) to be a scalar particle of charge -1/3$e$ coupling to a top quark plus a tau lepton ($\mathrm{t}\tau$) or a bottom quark plus a neutrino ($\mathrm{b}\nu$), or a vector particle of charge +2/3$e$, coupling to $\mathrm{t}\nu$ or $\mat

Motoya Shinozaki, Yui Muto, Takahito Kitada, Takashi Nakajima

We investigate gate voltage dependence of electrical readout noise in high-speed rf reflectometry using gallium arsenide quantum dots. The fast Fourier transform spectrum from the real time measurement reflects build-in device noise and circuit noise including the resonator and the amplifier. We separate their noise spectral components by model analysis. Det

Alex James

The AI chips increasingly focus on implementing neural computing at low power and cost. The intelligent sensing, automation, and edge computing applications have been the market drivers for AI chips. Increasingly, the generalisation, performance, robustness, and scalability of the AI chip solutions are compared with human-like intelligence abilities. Such a

Mishfad Shaikh Veedu, Murti V. Salapaka

This article addresses the problem of reconstructing the topology of a network of agents interacting via linear dynamics, while being excited by exogenous stochastic sources that are possibly correlated across the agents, from time-series measurements alone. It is shown, under the assumption that the correlations are affine in nature, such network of nodal i

Ninad Jadhav, Weiying Wang, Diana Zhang, Oussama Khatib

In this paper we develop the analytical framework for a novel Wireless signal-based Sensing capability for Robotics (WSR) by leveraging robots' mobility. It allows robots to primarily measure relative direction, or Angle-of-Arrival (AOA), to other robots, while operating in non-line-of-sight unmapped environments and without requiring external infrastructure

Jaime Cisternas, Paula Mellado, Felipe Urbina, Cristóbal Portilla

In classical mechanics, solutions can be classified according to their stability. Each of them is part of the possible trajectories of the system. However, the signatures of unstable solutions are hard to observe in an experiment, and most of the times if the experimental realization is adiabatic, they are considered just a nuisance. Here we use a small numb

Joshua C. Chang, Patrick Fletcher, Jungmin Han, Ted L. Chang

Dimensionality reduction methods for count data are critical to a wide range of applications in medical informatics and other fields where model interpretability is paramount. For such data, hierarchical Poisson matrix factorization (HPF) and other sparse probabilistic non-negative matrix factorization (NMF) methods are considered to be interpretable generat

Elizabeth Bailey, David J. Stevenson

Interior models of Uranus and Neptune often assume discrete layers, but sharp interfaces are expected only if major constituents are immiscible. Diffuse interfaces could arise if accretion favored a central concentration of the least volatile constituents (also incidentally the most dense); compositional gradients arising in such a structure would likely inh

George Anton, Jessen A. Malathu, Shelby Stinson

In a recent paper the team of Cogdell, Jorgenson and Smajlovi\'c develop infinite series representations for the logarithmic Mahler measure of a complex linear form, with 4 or more variables. We establish the case of 3 variables, by bounding an integral with integrand involving the random walk probability density $a\displaystyle\int_0^\infty tJ_0(at) \displa

Junyu Gao, Tao Han, Qi Wang, Yuan Yuan

Accurately locating each head's position in the crowd scenes is a crucial task in the field of crowd analysis. However, traditional density-based methods only predict coarse prediction, and segmentation/detection-based methods cannot handle extremely dense scenes and large-range scale-variations crowds. To this end, we propose an end-to-end and straightforwa

Michael Röckner, Guohuan Zhao

We prove the unique weak solvability of time-inhomogeneous stochastic differential equations with additive noises and drifts in critical Lebsgue space $L^q([0,T]; L^{p}(\mathbb{R}^d))$ with $d/p+2/q=1$. The weak uniqueness is obtained by solving corresponding Kolmogorov's backward equations in some second order Sobolev spaces, which is analytically interesti

Joan S. Muthu, Aditya Jyoti Paul, P. Murali

In this paper, a rigorous analysis of the behavior of the standard logistic map, Logistic Tent system (LTS), Logistic-Sine system (LSS) and Tent-Sine system (TSS) is performed using 0-1 test and three state test (3ST). In this work, it has been proved that the strength of the chaotic behavior is not uniform. Through extensive experiment and analysis, the str

Mason Haberle, Abhijit Chowdhary, Qiliang Wu

We investigate the dynamics of roll solutions at the zigzag boundary of the planar Swift-Hohenberg equation. Linear analysis shows an algebraic decay of small perturbation with a $t^{- 1/4}$ rate, instead of the classical $t^{- 1/2}$ diffusive decay rate, due to the degeneracy of the quadratic term of the continuation of the translational mode of the lineari

Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Hongwei Zhang

Arbitrary-oriented objects widely appear in natural scenes, aerial photographs, remote sensing images, etc., thus arbitrary-oriented object detection has received considerable attention. Many current rotation detectors use plenty of anchors with different orientations to achieve spatial alignment with ground truth boxes, then Intersection-over-Union (IoU) is

Aleksandr Romanov, James Santucci, Giulio Stancari, Alexander Valishev

We present the results of experimental studies on the transverse and longitudinal dynamics of a single electron in the IOTA storage ring. IOTA is a flexible machine dedicated to beam physics experiments with electrons and protons. A method was developed to reliably inject and circulate a controlled number of electrons in the ring. A key beam diagnostic syste

C. Q. Geng, Chia-Wei Liu, Tien-Hsueh Tsai

We systematically study the semileptonic decays of ${\bf B_c} \to {\bf B_n}\ell^+ \nu_{\ell}$ in the light-front constituent quark model, where ${\bf B_c}$ represent the anti-triplet charmed baryons of $(\Xi_c^0,\Xi_c^+,\Lambda_c^+)$ and ${\bf B_n}$ correspond to the octet ones. We determine the spin-flavor structures of the constituents in the baryons with

Sonika Johri, Shantanu Debnath, Avinash Mocherla, Alexandros Singh

Quantum machine learning has seen considerable theoretical and practical developments in recent years and has become a promising area for finding real world applications of quantum computers. In pursuit of this goal, here we combine state-of-the-art algorithms and quantum hardware to provide an experimental demonstration of a quantum machine learning applica

John Harwell, Maria Gini

We present a set of metrics intended to supplement designer intuitions when designing swarm-robotic systems, increase accuracy in extrapolating swarm behavior from algorithmic descriptions and small test experiments, and lead to faster and less costly design cycles. We build on previous works studying self-organizing behaviors in autonomous systems to derive

Maoran Zhu, Yuanxin Wu, Shitu Luo

Foot-mounted inertial sensors become popular in many indoor or GPS-denied applications, including but not limited to medical monitoring, gait analysis, soldier and first responder positioning. However, the foot-mounted inertial navigation relies largely on the aid of Zero Velocity Update (ZUPT) and has encountered inherent problems such as heading drift. Thi

Ram Sewak Dubey, Giorgio Laguzzi

We propose an extended version of Gini index defined on the set of infinite utility streams, $X=Y^\mathbb{N}$ where $Y\subset \mathbb{R}$. For $Y$ containing at most finitely many elements, the index satisfies the generalized Pigou-Dalton transfer principles in addition to the anonymity axiom.

Irvin Martinez, Amanda Weltman

Using the effective field theory framework for extended objects we describe the evolution of spinning compact objects in the late inspiral of the coalescence of a binary, before the plunge and merger, by including leading order corrections due to spin, tides, dissipation and gravitational wave radiation. Our implementation is of particular relevance for prob

Bogdan A. Dobrescu, Patrick J. Fox

We solve Diophantine equations of the type $ a \, (x^3 \!+ \! y^3 \!+ \! z^3 ) = (x \! + \! y \! + \! z)^3$, where $x,y,z$ are integer variables, and the coefficient $a\neq 0$ is rational. We show that there are infinite families of such equations, including those where $a$ is any cube or certain rational fractions, that have nontrivial solutions. There are

Akira Kubo, Masaki Shimizu

Despite the low dimensionalities of dissipative viscous fluids, reinforcement learning (RL) requires many observables in fluid control problems. This is because the observables are assumed to follow a policy-independent Markov decision process in the RL framework. By including policy parameters as arguments of a value function, we construct a consistent algo

Kayla X. Nguyen, Yi Jiang, Michael C. Cao, Prafull Purohit

Orbital angular momentum and torque transfer play central roles in a wide range of magnetic textures and devices including skyrmions and spin-torque electronics(1-4). Analogous topological structures are now also being explored in ferroelectrics, including polarization vortex arrays in ferroelectric/dielectric superlattices(5). Unlike magnetic toroidal order

Neehar Kondapaneni, Pietro Perona

The ability to understand and manipulate numbers and quantities emerges during childhood, but the mechanism through which humans acquire and develop this ability is still poorly understood. We explore this question through a model, assuming that the learner is able to pick up and place small objects from, and to, locations of its choosing, and will spontaneo

Julia Gehrlein, Martin Spinrath

Sum rules in the lepton sector provide an extremely valuable tool to classify flavour models in terms of relations between neutrino masses and mixing parameters testable in a plethora of experiments. In this manuscript we identify new leptonic sum rules arising in models with modular symmetries with residual symmetries. These models simultaneously present ne

Peter Ashwin, Claire M Postlethwaite

Continuous time recurrent neural networks (CTRNN) are systems of coupled ordinary differential equations that are simple enough to be insightful for describing learning and computation, from both biological and machine learning viewpoints. We describe a direct constructive method of realising finite state input-dependent computations on an arbitrary directed

Egecan Cogulu, Nahuel N. Statuto, Yang Cheng, Fengyuan Yang

We report the direct observation of switching of the N\'eel vector of antiferromagnetic (AFM) domains in response to electrical pulses in micron-scale Pt/$\alpha$-Fe$_2$O$_3$ Hall bars using photoemission electron microscopy. Current pulses lead to reversible and repeatable switching, with the current direction determining the final state, consistent with Ha

Terence Tao

Sendov's conjecture asserts that if a complex polynomial $f$ of degree $n \geq 2$ has all of its zeroes in closed unit disk $\{ z: |z| \leq 1 \}$, then for each such zero $\lambda_0$ there is a zero of the derivative $f'$ in the closed unit disk $\{ z: |z-\lambda_0| \leq 1 \}$. This conjecture is known for $n < 9$, but only partial results are available for

Sangho Lee, Youngjae Yu, Gunhee Kim, Thomas Breuel

The recent success of Transformers in the language domain has motivated adapting it to a multimodal setting, where a new visual model is trained in tandem with an already pretrained language model. However, due to the excessive memory requirements from Transformers, existing work typically fixes the language model and train only the vision module, which limi

Reza Khodayi-mehr, Matthew W. Urban, Michael M. Zavlanos, Wilkins Aquino

In this paper, we propose Plane Wave Elastography (PWE), a novel ultrasound shear wave elastography (SWE) approach. Currently, commercial methods for SWE rely on directional filtering based on the prior knowledge of the wave propagation direction, to remove complicated wave patterns formed due to reflection and refraction. The result is a set of decomposed d

CMS Collaboration

Events containing one or more top quarks produced with additional prompt leptons are used to search for new physics within the framework of an effective field theory (EFT). The data correspond to an integrated luminosity of 41.5 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, collected by the CMS experiment in 2017. The

Tomas Langer, Natalia Fedorova, Ron Hagensieker

Climate change is expected to reshuffle the settlement landscape: forcing people in affected areas to migrate, to change their lifeways, and continuing to affect demographic change throughout the world. Changes to the geographic distribution of population will have dramatic impacts on land use and land cover and thus constitute one of the major challenges of

Xiangyu Li, Yonghong Hou, Pichao Wang, Zhimin Gao

Existing unsupervised visual odometry (VO) methods either match pairwise images or integrate the temporal information using recurrent neural networks over a long sequence of images. They are either not accurate, time-consuming in training or error accumulative. In this paper, we propose a method consisting of two camera pose estimators that deal with the inf

David Kane

Our introductory classes in statistics and data science use too much mathematics. The key causal effect which our students want our classes to have is to improve their future performance and opportunities. The more professional their computing skills (in the context of data analysis), the greater their likely success. Introductory courses should feature almo

Sanjay Sarma O, Ramviyas Parasuraman, Ramana Pidaparti

Many species in nature demonstrate symbiotic relationships leading to emergent behaviors through cooperation, which are sometimes beyond the scope of the partnerships within the same species. These symbiotic relationships are classified as mutualism, commensalism, and parasitism based on the benefit levels involved. While these partnerships are ubiquitous in

Fatih Nar, Adrián Pérez-Suay, José Antonio Padrón, Gustau Camps-Valls

This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been extended to nonlinear distributions using kernel methods. While the kernel RX can cope with complex clutters, it requires a considerable amount of computational resources as the number

José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar, Gustau Camps-Valls

In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach. A regressor between images is used to discover the most {\em influential points} in the observed data. Typically, the pixels with largest residuals are decided to be anomalous changes. In order to find the anomalous pixels we consider the C

Adrián Pérez-Suay, Julia Amorós-López, Luis Gómez-Chova, Jordi Muñoz-Marí

Landmark recognition and matching is a critical step in many Image Navigation and Registration (INR) models for geostationary satellite services, as well as to maintain the geometric quality assessment (GQA) in the instrument data processing chain of Earth observation satellites. Matching the landmark accurately is of paramount relevance, and the process can

Daria Popova-Gorelova, Robin Santra

We investigate laser-driven electron dynamics in solids on the atomic scale and in real space within Floquet formalism, and develop a method based on subcycle-resolved x-ray-optical wave mixing to reconstruct those dynamics. We analyze how time-reversal and inversion symmetries influence properties of optically-induced charge distributions and microscopic el

Shingo Tagami, Maya Takechi, Jun Matsui, Tomotsugu Wakasa

Background: Using the chiral (Kyushu) $g$-matrix folding model with the densities calculated with Gogny-HFB (GHFB) with the angular momentum projection (AMP), we determined the central values of matter radius and neutron skin from the central values of reaction cross sections $σ_{\rm R}({\rm EXP})$ of p+$^{40,48}$Ca and p+$^{208}$Pb scattering. As for p+$^{5

Griffin Adams, Sarguna Janani Padmanabhan, Shivang Shekhar

We address two major challenges of implicit coordination in multi-agent deep reinforcement learning: non-stationarity and exponential growth of state-action space, by combining Deep-Q Networks for policy learning with Nash equilibrium for action selection. Q-values proxy as payoffs in Nash settings, and mutual best responses define joint action selection. Co

A. M. Baranov

A new approach to obtaining open Universes models as exact solutions of gravitational equations is considered. The proposed method is based on an analogy between electrostatics of conductors and open cosmological models which have a conformally-flat 4-metric in the Fock form. These cosmological models are solutions of the Einstein equations with the energy-m

Varanya Chaubey

This article is a response to a question many economists ask: how can I improve my first draft? The first section addresses a common approach to doing this: treating problems visible on the surface. This paper presents six such symptoms along with treatments for them. The second section addresses another approach, one that often turns out to be more effectiv

Ananda Das, Partha Pratim Das

Topical Segmentation poses a great role in reducing search space of the topics taught in a lecture video specially when the video metadata lacks topic wise segmentation information. This segmentation information eases user efforts of searching, locating and browsing a topic inside a lecture video. In this work we propose an algorithm, that combines state-of-

Asaf Kay, Barbara Scherrer, Yifat Piekner, Kirtiman Deo Malviya

Optical interference is used to enhance light-matter interaction and harvest broadband light in ultrathin semiconductor absorber films on specular back-reflectors. However, the high-temperature processing in oxygen atmosphere required for oxide absorbers often degrades metallic back-reflectors and their specular reflectance. In order to overcome this problem

Chance Haycock, Edward Thorpe-Woods, James Walsh, Patrick O&#39;Hara

One of the Greater London Authority&#39;s (GLA) response to the COVID-19 pandemic brings together multiple large-scale and heterogeneous datasets capturing mobility, transportation and traffic activity over the city of London to better understand &#39;busyness&#39; and enable targeted interventions and effective policy-making. As part of Project Odysseus we

Lipsy Gupta, S. Kundu

A function between two metric spaces is said to be totally bounded regular if it preserves totally bounded sets. These functions need not be continuous in general. Hence the purpose of this article is to study such functions vis-á-vis continuous functions and functions that are stronger than the continuous functions such as Cauchy continuous functions, some

C. -X. Wang, J. Huang, H. Wang, X. Gao

In this article, we first present our vision on the application scenarios, performance metrics, and potential key technologies of the sixth generation (6G) wireless communication networks. Then, 6G wireless channel measurements, characteristics, and models are comprehensively surveyed for all frequency bands and all scenarios, focusing on millimeter wave (mm

John Antoniadis

The Early Gaia Data Release 3 (EDR3) provides precise astrometry for nearly 1.5 billion sources across the entire sky. A few tens of these are associated with neutron stars in the Milky Way and Magellanic Clouds. Here, we report on a search for EDR3 counterparts to known rotation-powered pulsars using the method outlined in Antoniadis (2021). A cross-correla

Jakob Hansen, Thomas Gebhart

We present a generalization of graph convolutional networks by generalizing the diffusion operation underlying this class of graph neural networks. These sheaf neural networks are based on the sheaf Laplacian, a generalization of the graph Laplacian that encodes additional relational structure parameterized by the underlying graph. The sheaf Laplacian and as

Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang

Federated learning (FL) is a popular distributed learning framework that can reduce privacy risks by not explicitly sharing private data. However, recent works demonstrated that sharing model updates makes FL vulnerable to inference attacks. In this work, we show our key observation that the data representation leakage from gradients is the essential cause o

Barbara Scherrer, Tong Li, Anton Tsyganok, Max Döbeli

Optimising the photoelectrochemical performance of hematite photoanodes for solar water splitting requires better understanding of the relationships between dopant distribution, structural defects and photoelectrochemical properties. Here, we use complementary characterisation techniques including electron microscopy, conductive atomic force microscopy (CAFM

Daniel A. Grave, Natav Yatom, David S. Ellis, Maytal Caspary Toroker

In recent years, hematite potential as a photoanode material for solar hydrogen production has ignited a renewed interest in its physical and interfacial properties, which continues to be an active field of research. Research on hematite photoanodes provides new insights on the correlations between electronic structure, transport properties, excited state dy

Anton Tsyganok, Dino Klotz, Kirtiman Deo Malviya, Avner Rothschild

Transparent Fe1-xNixOOH overlayers (~2 nm thick) were deposited photoelectrochemically on (001) oriented heteroepitaxial Sn- and Zn-doped hematite (Fe2O3) thin film photoanodes. In both cases, the water photo-oxidation performance was improved by the co-catalyst overlayers. Intensity modulated photocurrent spectroscopy (IMPS) was applied to study the changes

Victor Parque, Wataru Suzaki, Satoshi Miura, Ayako Torisaka

Elucidating versatile configurations of spiral folding, and investigating the deployment performance is of relevant interest to extend the applicability of deployable membranes towards large-scale and functional configurations. In this paper we propose new schemes to package flat and curved membranes of finite thickness by using multiple spirals, whose gover

Dino Klotz, Daniel A. Grave, Hen Dotan, Avner Rothschild

Photoelectrochemical impedance spectroscopy (PEIS) is a useful tool for the characterization of photoelectrodes for solar water splitting. However, the analysis of PEIS spectra often involves a priori assumptions that might bias the results. This work puts forward an empirical method that analyzes the distribution of relaxation times (DRT), obtained directly

Gideon Segev, Hen Dotan, David S. Ellis, Yifat Piekner

The spatial collection efficiency portrays the driving forces and loss mechanisms in photovoltaic and photoelectrochemical devices. It is defined as the fraction of photogenerated charge carriers created at a specific point within the device that contribute to the photocurrent. In stratified planar structures, the spatial collection efficiency can be extract

Asaf Kay, Daniel A Grave, Kirtiman D Malviya, David S Ellis

The photoelectrochemical behavior of a planar 1 cm2 thick Ti-doped hematite film deposited on F:SnO2 coated glass was studied with both front and back illumination. Despite low quantum efficiency, photocurrent was observed upon back illumination with low wavelengths, indicating that some photogenerated holes are able to traverse at least 700 nm across the he

Michael A. Kuhn, Lynne A. Hillenbrand

The Bajamar Star is an early O star that ionizes the North America/Pelican Nebulae. In projection, it is near the geometric center of the H II region, but appears to lie outside any of the main stellar subgroups. Furthermore, in Gaia DR2, there were slight discrepancies between this star and the rest of the system in parallax (2$σ$ larger) and relative tange

Alastair Jamieson-Lane, Bernd Blasius

Bacteria, in contrast to eukaryotic cells contain two types of genes: chromosomal genes that are fixed to the cell, and plasmids that are mobile genes, easily shared to other cells. The sharing of plasmid genes between individual bacteria and between bacterial lineages has contributed vastly to bacterial evolution, allowing specialized traits to `jump ship&#

Zhibo Zhang, Chen Zeng, Maulikkumar Dhameliya, Souma Chowdhury

This paper proposes a multi-sensor based approach to detect, track, and localize a quadcopter unmanned aerial vehicle (UAV). Specifically, a pipeline is developed to process monocular RGB and thermal video (captured from a fixed platform) to detect and track the UAV in our FoV. Subsequently, a 2D planar lidar is used to allow conversion of pixel data to actu

John Maclean, Elaine T Spiller

Many recent advances in sequential assimilation of data into nonlinear high-dimensional models are modifications to particle filters which employ efficient searches of a high-dimensional state space. In this work, we present a complementary strategy that combines statistical emulators and particle filters. The emulators are used to learn and offer a computat

Benjamin Harrop-Griffiths, Rowan Killip, Monica Visan

We consider two discrete completely integrable evolutions: the Toda Lattice and the Ablowitz-Ladik system. The principal thrust of the paper is the development of microscopic conservation laws that witness the conservation of the perturbation determinant under these dynamics. In this way, we obtain discrete analogues of objects that we found essential in our

Seher Fişekci, Lucile Vandembroucq

We determine the Lusternik-Schnirelmann category of the projective product spaces introduced by D. Davis. We also obtained an upper bound for the topological complexity of these spaces, which improves the estimate given by J. González, M. Grant, E. Torres-Giese, and M. Xicoténcatl.

Chenfeng Xiong, Aref Darzi, Yixuan Pan, Sepehr Ghader

While benefiting people&#39;s daily life in so many ways, smartphones and their location-based services are generating massive mobile device location data that has great potential to help us understand travel demand patterns and make transportation planning for the future. While recent studies have analyzed human travel behavior using such new data sources,