December 2020 arXiv papers — page 74

Robert M. Guralnick, Geoffrey R. Robinson

Motivated in part by representation theoretic questions, we prove that if G is a finite quasi-simple group, then there exists an elementary abelian subgroup of G that intersects every conjugacy class of involutions of G.

Michael Franklin Bosu, Stephen G. MacDonell, Peter Whigham

Software effort estimation (SEE) models are typically developed based on an underlying assumption that all data points are equally relevant to the prediction of effort for future projects. The dynamic nature of several aspects of the software engineering process could mean that this assumption does not hold in at least some cases. This study employs three ke

Jiaxiang Chen, Qinzhi Xia, Libin Fu

We theoretically investigate the spectral caustics of high-order harmonics in solids. We analyze the 1-dimension model of solids HHG and find that, apart from the caustics originated from the van Hove singularities in the energy-band structure, another kind of catastrophe singularities also emerge when the different branches of electron-hole trajectories gen

Nikolai V. Ivanov

The paper is devoted to an adaptation of author's approach to Leray theorems in bounded cohomology theory to infinite chains. The main results are a stronger and more general form of Gromov's Vanishing-finiteness theorem and a generalization of the first part of his Cutting-of theorem. The proofs are elementary.

Chengyang Liang, Zixiang Zhao, Junmin Liu, Jiangshe Zhang

Recently, adversarial-based domain adaptive object detection (DAOD) methods have been developed rapidly. However, there are two issues that need to be resolved urgently. Firstly, numerous methods reduce the distributional shifts only by aligning all the feature between the source and target domain, while ignoring the private information of each domain. Secon

Ivan Feshchenko

We provide a sufficient condition for a finite number of closed subspaces of a Hilbert space to be linearly independent and their sum to be closed. Under this condition a formula for the orthogonal projection onto the sum is given. We also show that this condition is sharp (in a certain sense).

Jinshan Zeng, Qi Chen, Yunxin Liu, Mingwen Wang

The generation of stylish Chinese fonts is an important problem involved in many applications. Most of existing generation methods are based on the deep generative models, particularly, the generative adversarial networks (GAN) based models. However, these deep generative models may suffer from the mode collapse issue, which significantly degrades the divers

J. H. Yoon, Crystal L. Martin, S. Veilleux, M. Melendez

We present deep far-infrared observations of the nearby edge-on galaxy NGC 891 obtained with the Herschel Space Observatory and the Spitzer Space Telescope. The maps confirm the detection of thermal emission from the inner circumgalactic medium (halo) and spatially resolve a dusty superbubble and a dust spur (filament). The dust temperature of the halo compo

Xiaole Su, Hongwei Sun, Yusheng Wang

This paper aims to give a further study on quasi-convex subsets in Alexandrov spaces with lower curvature bound which are introduced in [SSW]. We first provide new insights on quasi-convex subsets (Theorem A and Corollary C), and then as applications of them we explore more properties of quasi-convex subsets.

L. Bugnet, V. Prat, S. Mathis, R. A. García

Stars more massive than $\sim 1.3$ M$_\odot$ are known to develop a convective core during the main-sequence: the dynamo process triggered by this convection could be the origin of a strong magnetic field inside the core of the star, trapped when it becomes stably stratified and for the rest of its evolution. The presence of highly magnetized white dwarfs st

Jeremy Booher, José Felipe Voloch

Let $K$ be the function field of a curve over a finite field of odd characteristic. We investigate using $L$-functions of Galois extensions of $K$ to effectively recover $K$. When $K$ is the function field of the projective line with four rational points removed, we show how to use $L$-functions of a ray class field to effectively recover the removed points

Yuan Feng, Hexiang Wang, Han Yang, Fangbo Wang

Fast and accurate structural dynamics analysis is important for structural design and damage assessment. Structural dynamics analysis leveraging machine learning techniques has become a popular research focus in recent years. Although the basic neural network provides an alternative approach for structural dynamics analysis, the lack of physics law inside th

Eray Unsal Atay, Igor Kadota, Eytan Modiano

We consider a single-hop wireless network with sources transmitting time-sensitive information to the destination over multiple unreliable channels. Packets from each source are generated according to a stochastic process with known statistics and the state of each wireless channel (ON/OFF) varies according to a stochastic process with unknown statistics. Th

Brian A. Freno, Neil R. Matula, William A. Johnson

Though the method-of-moments implementation of the electric-field integral equation plays an important role in computational electromagnetics, it provides many code-verification challenges due to the different sources of numerical error. In this paper, we provide an approach through which we can apply the method of manufactured solutions to isolate and verif

Kexin Pei, Zhou Xuan, Junfeng Yang, Suman Jana

Detecting semantically similar functions -- a crucial analysis capability with broad real-world security usages including vulnerability detection, malware lineage, and forensics -- requires understanding function behaviors and intentions. This task is challenging as semantically similar functions can be implemented differently, run on different architectures

Jin Wang, Jia Hu, Geyong Min, Qiang Ni

Multi-access Edge Computing (MEC) is an emerging computing paradigm that extends cloud computing to the network edge to support resource-intensive applications on mobile devices. As a crucial problem in MEC, service migration needs to decide how to migrate user services for maintaining the Quality-of-Service when users roam between MEC servers with limited c

D. A. Kann, M. Blazek, A. de Ugarte Postigo, C. C. Thöne

The recently discovered rapid transient GN-z11-flash has been suggested to be the prompt-emission ultraviolet flash associated with a gamma-ray burst serendipitously exploding in the ultra-high-$z$ galaxy GN-z11. We here place the flash into the context of the early ultraviolet emission of gamma-ray bursts, and find it is in agreement with the luminosity dis

Peter Washington, Haik Kalantarian, John Kent, Arman Husic

Background: Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However, most computer vision emotion recognition models are trained on adult emotion and therefore underperform when applied to child faces. Objective: We designed a strategy to gamify t

Sheng Yue, Ju Ren, Jiang Xin, Sen Lin

In order to meet the requirements for performance, safety, and latency in many IoT applications, intelligent decisions must be made right here right now at the network edge. However, the constrained resources and limited local data amount pose significant challenges to the development of edge AI. To overcome these challenges, we explore continual edge learni

Giorgos Eleftheriou, Peter West

We briefly recall the procedure for computing the Ward Identities in the presence of a regulator which violates the symmetry being considered. We compute the first non-trivial correction to the supersymmetry Ward Identity of the Wess-Zumino model in the presence of background supergravity using dimensional regularisation. We find that the result can be remov

Gustav Lindmark, Claudio Altafini

Combinations of Gramian-based centrality measures are used for driver node selection in complex networks in order to simultaneously take into account conflicting control energy requirements, like minimizing the average energy needed to steer the state in any direction and the energy needed for the worst direction. The selection strategies that we propose are

Nemanja Rakicevic, Antoine Cully, Petar Kormushev

Diversity-based approaches have recently gained popularity as an alternative paradigm to performance-based policy search. A popular approach from this family, Quality-Diversity (QD), maintains a collection of high-performing policies separated in the diversity-metric space, defined based on policies' rollout behaviours. When policies are parameterised as neu

Emily C. Martin, Andrew J. Skemer, Matthew V. Radovan, Steven L. Allen

Exoplanets are abundant in our galaxy and yet characterizing them remains a technical challenge. Solar System planets provide an opportunity to test the practical limitations of exoplanet observations with high signal-to-noise data that we cannot access for exoplanets. However, data on Solar System planets differ from exoplanets in that Solar System planets

Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu

The primary goal of knowledge distillation (KD) is to encapsulate the information of a model learned from a teacher network into a student network, with the latter being more compact than the former. Existing work, e.g., using Kullback-Leibler divergence for distillation, may fail to capture important structural knowledge in the teacher network and often lac

Linjie Li, Zhe Gan, Jingjing Liu

Large-scale pre-trained multimodal transformers, such as ViLBERT and UNITER, have propelled the state of the art in vision-and-language (V+L) research to a new level. Although achieving impressive performance on standard tasks, to date, it still remains unclear how robust these pre-trained models are. To investigate, we conduct a host of thorough evaluations

Adam G. Frim, Adrianne Zhong, Shi-Fan Chen, Dibyendu Mandal

Engineered swift equilibration (ESE) is a class of driving protocols that enforce an equilibrium distribution with respect to external control parameters at the beginning and end of rapid state transformations of open, classical non-equilibrium systems. ESE protocols have previously been derived and experimentally realized for Brownian particles in simple, o

Wei Cheng, Ghulam Murtaza, Aaron Wang

Due to recent breakthroughs in state-of-the-art DNA sequencing technology, genomics data sets have become ubiquitous. The emergence of large-scale data sets provides great opportunities for better understanding of genomics, especially gene regulation. Although each cell in the human body contains the same set of DNA information, gene expression controls the

Purbasha Sharangi, Pierluigi Gargiani, Manuel Valvidares, Subhankar Bedanta

The signature of magnetism without a ferromagnet in a non-magnetic heterostructure is novel as well as fascinating from fundamental research point of view. It has been shown by Al'Mari et al: that magnetism can be induced at the interface of Cu/C60 due to change in density of states. However, the quantification of such interfacial magnetic moment has not bee

Daniel Rosiak

This book provides an inviting tour through sheaf theory, from the perspective of applied category theory and pitched at a less specialized audience than is typical with introductions to sheaves. The book makes it as easy as possible for the reader new to sheaves, by motivating and developing the theory via a broad range of concrete examples and explicit con

Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer

For an AI system to be reliable, the confidence it expresses in its decisions must match its accuracy. To assess the degree of match, examples are typically binned by confidence and the per-bin mean confidence and accuracy are compared. Most research in calibration focuses on techniques to reduce this empirical measure of calibration error, ECE_bin. We inste

Gorana Mijatovic, Yuri Antonacci, Tatjana Loncar-Turukalo, Ludovico Minati

Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumpt

Bahar Acu, Orsola Capovilla-Searle, Agnès Gadbled, Aleksandra Marinković

We study the interactions between toric manifolds and Weinstein handlebodies. We define a partially-centered condition on a Delzant polytope, which we prove ensures that the complement of a corresponding partial smoothing of the toric divisor supports an explicit Weinstein structure. Many examples which fail this condition also fail to have Weinstein (or eve

Mark Huber

The STrauss process is a point process with unnormalized density with respect to a Poisson point process, where each pair of points within a specified distance $r$ of each other contributes a factor $\lambda \in (0, 1)$ to the density. Basic Acceptance Rejection works spectacularly poorly for this problem, which is why several other perfect simulation method

Eunice Y. S. Chan, Robert M. Corless

The chaos game representation (CGR) is an interesting method to visualize one-dimensional sequences. In this paper, we show how to construct a chaos game representation. The applications mentioned here are biological, in which CGR was able to uncover patterns in DNA or proteins that were previously unknown. We also show how CGR might be introduced in the cla

M. Broilo, D. A. Fagundes, E. G. S. Luna, M. Peláez

The LHC has released precise measurements of elastic proton-proton scattering that provide a unique constraint on the asymptotic behavior of the scattering amplitude at high energies. Recent reanalyses of part of these data indicate that the central values of some forward quantities would be different than initially observed. We introduce correlation informa

Ward Struyve

We present the Hamiltonian formulation of a relativistic point-particle coupled to Einstein gravity and its canonical quantization \`a la Wheeler-DeWitt. In the resulting quantum theory, the wave functional is a function of the particle coordinates and the 3-metric. It satisfies a particular Hamiltonian and diffeomorphism constraint, together with a Klein-Go

Mohammad Zaki Zadeh, Ashwin Ramesh Babu, Ashish Jaiswal, Maria Kyrarini

As mobile technologies have become ubiquitous in recent years, computer-based cognitive tests have become more popular and efficient. In this work, we focus on assessing motor function in children by analyzing their gait movements. Although there has been a lot of research on designing automated assessment systems for gait analysis, most of these efforts use

V. N. Duarte, J. B. Lestz, N. N. Gorelenkov, R. B. White

A quasilinear plasma transport theory that incorporates Fokker-Planck dynamical friction (drag) and pitch angle scattering is self-consistently derived from first principles for an isolated, marginally-unstable mode resonating with an energetic minority species. It is found that drag fundamentally changes the structure of the wave-particle resonance, breakin

Sen Lin, Mehmet Dedeoglu, Junshan Zhang

Online meta-learning is emerging as an enabling technique for achieving edge intelligence in the IoT ecosystem. Nevertheless, to learn a good meta-model for within-task fast adaptation, a single agent alone has to learn over many tasks, and this is the so-called 'cold-start' problem. Observing that in a multi-agent network the learning tasks across different

Seth R. Meeker, Tuan N. Truong, Jennifer E. Roberts, J. Chris Shelton

PALM-3000 (P3K), the second generation adaptive optics (AO) instrument for the 5.1 meter Hale telescope at Palomar Observatory, was released as a facility class instrument in October 2011 and has since been used on-sky for over 600 nights as a workhorse science instrument and testbed for coronagraph and detector development. In late 2019 P3K underwent a sign

Caelan Brooks, Allison Brattley, Kunal K. Das

We consider ultracold atoms trapped in a toroidal trap with an azimuthal lattice for utility as a macroscopic simulator of quantum optics phenomena. We examine the dynamics induced by the adiabatic introduction of the lattice that serves to couple the normal modes, as an analog of a laser field coupling electronic states. The system is found to display two d

Prabudhya Roy Chowdhury, Xiulin Ruan

While machine learning (ML) has shown increasing effectiveness in optimizing materials properties under known physics, its application in challenging conventional wisdom and discovering new physics still remains challenging due to its interpolative nature. In this work, we demonstrate the potential of using ML for such applications by implementing an adaptiv

Barbara C. Benato, Italos E. de Souza, Felipe L. Galvão, Alexandre X. Falcão

A technique named Feature Learning from Image Markers (FLIM) was recently proposed to estimate convolutional filters, with no backpropagation, from strokes drawn by a user on very few images (e.g., 1-3) per class, and demonstrated for coconut-tree image classification. This paper extends FLIM for fully connected layers and demonstrates it on different image

Alin Bostan, Sergey Yurkevich

In 1977, Strassen invented a famous baby-step/giant-step algorithm that computes the factorial $N!$ in arithmetic complexity quasi-linear in $\sqrt{N}$. In 1988, the Chudnovsky brothers generalized Strassen's algorithm to the computation of the $N$-th term of any holonomic sequence in essentially the same arithmetic complexity. We design $q$-analogues of the

Elian Malkin, Arturo Deza, Tomaso Poggio

The spatially-varying field of the human visual system has recently received a resurgence of interest with the development of virtual reality (VR) and neural networks. The computational demands of high resolution rendering desired for VR can be offset by savings in the periphery, while neural networks trained with foveated input have shown perceptual gains i

Farzad B. Faramarzi, Peter K. Day, Jacob Glasby, Sasha Sypkens

Superconducting qubits are widely used in quantum computing research and industry. We describe a superconducting kinetic inductance qubit (and introduce the term Kineticon to describe it) operating at W-band frequencies with a nonlinear nanowire section that provides the anharmonicity required for two distinct quantum energy states. Operating the qubits at h

Antonio B. Mei, Ivan Milosavljevic, Amanda L. Simpson, Valerie A. Smetanka

Precise nanofabrication represents a critical challenge to developing semiconductor quantum-dot qubits for practical quantum computation. Here, we design and train a convolutional neural network to interpret in-line scanning electron micrographs and quantify qualitative features affecting device functionality. The high-throughput strategy is exemplified by o

German A. Villalba, Xu Liang, Yao Liang

A fundamental challenge in estimations of daily streamflow time series at sites with incomplete records is how to effectively and efficiently select reference or donor gauges from an existing gauge network to infer the missing data. While research on estimating missing streamflow time series is not new, the existing approaches either use a single reference s

Alvaro Diaz-Flores, José Fernández, Leonard Vance, Himangshu Kalita

The recent, rapid advancement in space exploration is thanks to the accelerated miniaturization of electronics components on a spacecraft that is reducing the mass, volume and cost of satellites. Yet, access to space remains a distant dream as there is growing complexity in what is required of satellites and increasing space traffic. Interplanetary explorati

Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara

Recommender systems have shown to be a successful representative of how data availability can ease our everyday digital life. However, data privacy is one of the most prominent concerns in the digital era. After several data breaches and privacy scandals, the users are now worried about sharing their data. In the last decade, Federated Learning has emerged a

T. R. Kirkpatrick, D. Belitz, J. R. Dorfman

In the 1980s it was theoretically predicted that correlations of various observables in a fluid in a non-equilibrium steady state (NESS) are extraordinarily long-ranged, extending, in a well-defined sense, over the size of the system. This is to be contrasted with correlations in an equilibrium fluid, whose range is typically just a few particle diameters. T

Enrique Barrajón, Laura Barrajón

Kaplan-Meier survival analysis represents the most objective measure of treatment efficacy in oncology, though subjected to potential bias, which is worrisome in an era of precision medicine. Independent of the bias inherent to the design and execution of clinical trials, bias may be the result of patient censoring, or incomplete observation. Unlike disease/

Kirthevasan Kandasamy, Gur-Eyal Sela, Joseph E Gonzalez, Michael I Jordan

We describe mechanisms for the allocation of a scarce resource among multiple users in a way that is efficient, fair, and strategy-proof, but when users do not know their resource requirements. The mechanism is repeated for multiple rounds and a user's requirements can change on each round. At the end of each round, users provide feedback about the allocatio

Adam B Kashlak, Weicong Yuan

Measures of local and global spatial association are key tools for exploratory spatial data analysis. Many such measures exist including Moran's $I$, Geary's $C$, and the Getis-Ord $G$ and $G^*$ statistics. A parametric approach to testing for significance relies on strong assumptions, which are often not met by real world data. Alternatively, the most popul

Laurent Cantier

We define a notion of ideal for objects in the category of abstract unitary Cuntz semigroups introduced in [3] and termed Cu$^\sim$. We show that the set of ideals of a Cu$^\sim$-semigroup has a complete lattice structure. In fact, we prove that for any C$^*$-algebra of stable rank one $A$, the assignment $I\longmapsto$Cu$_1(I)$ defines a complete lattice is

Collins Edet

In this article, the Yukawa potential is scrutinized taking into consideration the effects of magnetic and AB flux fields within the non-relativistic regime using the factorization method. The energy equation and wave function of the system are obtained in close form. We find that the all-encompassing effects result in a strongly attractive system and conseq

Tianchen Ji, Sri Theja Vuppala, Girish Chowdhary, Katherine Driggs-Campbell

To achieve high-levels of autonomy, modern robots require the ability to detect and recover from anomalies and failures with minimal human supervision. Multi-modal sensor signals could provide more information for such anomaly detection tasks; however, the fusion of high-dimensional and heterogeneous sensor modalities remains a challenging problem. We propos

Christopher M. McKenney, Jason E. Austermann, James A. Beall, Nils W. Halverson

Large imaging arrays of detectors at millimeter and submillimeter wavelengths have applications that include measurements of the faint polarization signal in the Cosmic Microwave Background (CMB), and submillimeter astrophysics. We are developing planar lenslet arrays for millimeter-wavelength imaging using metamaterials microlithically fabricated using sili

Jorge Aguayo, Hugo Carrillo

From the steady Stokes and Navier-Stokes models, a penalization method has been considered by several authors for approximating those fluid equations around obstacles. In this work, we present a justification for using fictitious domains to study obstacles immersed in incompressible viscous fluids through a simplified version of Brinkman's law for porous med

Mojtaba Raouf, Rory Smith, Habib G. Khosroshahi, Jesse van de Sande

We study the stellar and gas kinematics of the brightest group galaxies (BGGs) in dynamically relaxed and unrelaxed galaxy groups for a sample of 154 galaxies in the SAMI galaxy survey. We characterize the dynamical state of the groups using the luminosity gap between the two most luminous galaxies and the BGG offset from the luminosity centroid of the group

J. Lawrence, I. P. Silva

We describe a bijection between oriented cubes and adjoints of cross-polytopes. This correspondence is used to prove that the real affine cube is, up to reorientation in the same class, the unique oriented cube that is realizable. Moreover, its underlying matroid is, up to isomorphism, the unique combinatorial cube that is realizable over the reals.

Gabriel Ferreira Barros, Bruno Pasqualotto Cavalar, Yoshiharu Kohayakawa, Tássio Naia

If $G$ is a graph and $\vec H$ is an oriented graph, we write $G\to \vec H$ to say that every orientation of the edges of $G$ contains $\vec H$ as a subdigraph. We consider the case in which $G=G(n,p)$, the binomial random graph. We determine the threshold $p_{\vec H}=p_{\vec H}(n)$ for the property $G(n,p)\to \vec H$ for the cases in which $\vec H$ is an ac

Steven Chaplick, Fabian Klute, Irene Parada, Jonathan Rollin

For a class $\mathcal{D}$ of drawings of loopless (multi-)graphs in the plane, a drawing $D \in \mathcal{D}$ is \emph{saturated} when the addition of any edge to $D$ results in $D' \notin \mathcal{D}$ - this is analogous to saturated graphs in a graph class as introduced by Tur\'an (1941) and Erd\H{o}s, Hajnal, and Moon (1964). We focus on $k$-planar drawing

Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins

Problems of cooperation--in which agents seek ways to jointly improve their welfare--are ubiquitous and important. They can be found at scales ranging from our daily routines--such as driving on highways, scheduling meetings, and working collaboratively--to our global challenges--such as peace, commerce, and pandemic preparedness. Arguably, the success of th

Ying Zu, Huanyuan Shan, Jun Zhang, Sukhdeep Singh

Concentration is one of the key dark matter halo properties that could drive the scatter in the stellar-to-halo mass relation of massive clusters. We derive robust photometric stellar masses for a sample of brightest central galaxies (BCGs) in SDSS redMaPPer clusters at $0.17<z<0.3$, and split the clusters into two equal-halo mass subsamples by their BCG ste

Vestislav Apostolov, David M. J. Calderbank, Eveline Legendre

We use the correspondence between extremal Sasaki structures and weighted extremal Kahler metrics defined on a regular quotient of a Sasaki manifold, established by the first two authors, and Lahdili's theory of weighted K-stability in order to define a suitable notion of (relative) weighted K-stability for compact Sasaki manifolds of regular type. We show t

Elsa Ghandour, Sigmundur Gudmundsson, Victor Ottosson

We study left-invariant foliations ${\mathcal F}$ on semi-Riemannian Lie groups $G$ generated by a subgroup $K$. We are interested in such foliations which are conformal and with minimal leaves of codimension two. We classify such foliations ${\mathcal F}$ when the subgroup $K$ is one of the important $\text{SU}(2)$, $\text{SL}_{2}(\mathbb R)$, $\text{SU}(2)

Giorgio Audrito, Roberto Casadei, Ferruccio Damiani, Mirko Viroli

Recent works in contexts like the Internet of Things (IoT) and large-scale Cyber-Physical Systems (CPS) propose the idea of programming distributed systems by focussing on their global behaviour across space and time. In this view, a potentially vast and heterogeneous set of devices is considered as an "aggregate" to be programmed as a whole, while abstracti

Benjamin Elder, Matthew Arnold, Anupama Murthi, Jiri Navratil

Understanding model performance on unlabeled data is a fundamental challenge of developing, deploying, and maintaining AI systems. Model performance is typically evaluated using test sets or periodic manual quality assessments, both of which require laborious manual data labeling. Automated performance prediction techniques aim to mitigate this burden, but p

Quoc Dung Cao, Youngjun Choe

Gaining timely and reliable situation awareness after hazard events such as a hurricane is crucial to emergency managers and first responders. One effective way to achieve that goal is through damage assessment. Recently, disaster researchers have been utilizing imagery captured through satellites or drones to quantify the number of flooded/damaged buildings

Ming Yang, Alceste Z. Bonanos, Biwei Jiang, Jian Gao

We present a clean, magnitude-limited (IRAC1 or WISE1$\leq$15.0 mag) multiwavelength source catalog for the LMC. The catalog was built upon crossmatching ($1''$) and deblending ($3''$) between the SEIP source list and Gaia DR2, with strict constraints on the Gaia astrometric solution to remove the foreground contamination. The catalog contains 197,004 target

Ali Yazdizadeh, Bilal Farooq

Ontology is the explicit and formal representation of the concepts in a domain and relations among them. Transportation science is a wide domain dealing with mobility over various complex and interconnected transportation systems, such as land, aviation, and maritime transport, and can take considerable advantage from ontology development. While several stud

Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu

Efficient exploration under sparse rewards remains a key challenge in deep reinforcement learning. To guide exploration, previous work makes extensive use of intrinsic reward (IR). There are many heuristics for IR, including visitation counts, curiosity, and state-difference. In this paper, we analyze the pros and cons of each method and propose the regulate

Valentin Kasper, Torsten V. Zache, Fred Jendrzejewski, Maciej Lewenstein

Lattice gauge theories are fundamental to such distinct fields as particle physics, condensed matter or quantum information theory. The recent progress in the control of artificial quantum systems already allows for studying Abelian lattice gauge theories in table-top experiments. However, the realization of non-Abelian models remains challenging. Here, we e

Litian Liu, Amit Solomon, Salman Salamatian, Muriel Medard

In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point-to-poi

Robert R. Tucci

The goal of this paper is to generalize classical d-separation and classical Belief Propagation (BP) to the quantum realm. Classical d-separation is an essential ingredient of most of Judea Pearl's work. It is crucial to all 3 rungs of what Pearl calls the 3 rungs of Causation. So having a quantum version of d-separation and BP probably implies that most of

Alvin C. M. Shek, Ciro Semprebon, Jack R. Panter, Halim Kusumaatmaja

We numerically study two-component capillary bridges formed when a liquid droplet is placed in between two liquid infused surfaces (LIS). In contrast to commonly studied one-component capillary bridges on non-infused solid surfaces, two-component liquid bridges can exhibit a range of different morphologies where the liquid droplet is directly in contact with

Peter J. Forrester

The problem of calculating the scaled limit of the joint moments of the characteristic polynomial, and the derivative of the characteristic polynomial, for matrices from the unitary group with Haar measure first arose in studies relating to the Riemann zeta function in the thesis of Hughes. Subsequently, Winn showed that these joint moments can equivalently

H. Grebel

Optical and thermal effects in asymmetric supercapacitors, whose active-carbon (AC) electrodes were embedded with nano-Si (n-Si) quantum dots (QD), are reported. We describe two structures: (1) p-n like, obtained by using a polyethylimine (PEI) binder for the n-like electrode and a polyvinylpyrrolidone (PVP) binder for the p-like electrode; (2) a single comp

Haider Al-Lawati, Stark C. Draper

Distributed optimization is widely deployed in practice to solve a broad range of problems. In a typical asynchronous scheme, workers calculate gradients with respect to out-of-date optimization parameters while the master uses stale (i.e., delayed) gradients to update the parameters. While using stale gradients can slow the convergence, asynchronous methods

Tingyi Zhou, Fabien Scalzo, Bahram Jalali

Alternative machine learning approaches that are computationally light with low latency and can work with only a small training dataset are needed for applications where the insatiable demand of deep learning methods for computing power and large training data cannot be met. We show that spectral mapping of data onto femtosecond optical pulses and a projecti

John Acosta, Cezary Gonera

A Hamiltonian dynamics defined on the two-dimensional hyperbolic plane by coupling the Morse and Rosen-Morse potentials is analyzed. It is demonstrated that orbits of all bounded motions are closed iff the product of the parameter $\tilde a$ of the Morse potential and the square root of the absolute value of the curvature is a rational number. This property

Aobo Chen, Francesco Monticone

Most optical systems involve a combination of lenses separated by free-space regions where light acquires the required angle-dependent phase delay for a certain functionality. Very recently, flat-optics structures have been proposed to compress these large free-space volumes and miniaturize the overall optical system. However, these early designs can only re

Andrea Passamonti, Nils Andersson, Pantelis Pnigouras

We consider the dynamical tidal response of a neutron star in an inspiralling binary, focussing on the impact of the star's elastic crust. Within the context of Newtonian gravity, we add the elastic aspects to the theoretical formulation of the problem and quantify the dynamical excitation of different classes of oscillation modes. The results demonstrate th

B. Riaz, J. Bally

We present a near-infrared study of accretion and outflow activity in 6 Class 0/I proto-brown dwarfs (proto-BDs) using VLT/SINFONI spectroscopy and spectro-imaging observations. The spectra show emission in several [FeII] and H$_{2}$ lines associated with jet/outflow activity, and in the accretion diagnostics of Pa$\beta$ and Br$\gamma$ lines. The peak veloc

Guanyu Lu, Marko Tadjer, Joshua D. Caldwell, Thomas G. Folland

Long-range spatial coherence can be induced in thermal emitters by embedding a periodic grating into a material supporting propagating polaritons or dielectric modes. However, the emission angle and frequency cannot be defined simultaneously and uniquely, resulting in emission at unusable angles or frequencies. Here, we explore superstructure gratings (SSGs)

Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson

Deep Learning is becoming an increasingly important way to produce accurate hydrological predictions across a wide range of spatial and temporal scales. Uncertainty estimations are critical for actionable hydrological forecasting, and while standardized community benchmarks are becoming an increasingly important part of hydrological model development and res

Pedro Cisneros-Velarde, Francesco Bullo

Consider a multi-agent system whereby each agent has an initial probability measure. In this paper, we propose a distributed algorithm based upon stochastic, asynchronous and pairwise exchange of information and displacement interpolation in the Wasserstein space. We characterize the evolution of this algorithm and prove it computes the Wasserstein barycente

Dorothea Bahns, Detlev Buchholz

The virtues of resolvent algebras, compared to other approaches for the treatment of canonical quantum systems, are exemplified by infinite systems of non-relativistic bosons. Within this framework, equilibrium states of trapped and untrapped bosons are defined on a fixed C*-algebra for all physically meaningful values of the temperature and chemical potenti

Patrick Serafin, German Kolmakov

Using a computational approach based on the driven diffusion equation for dipolariton wave packets, we simulate the diffusive dynamics of dipolaritons in an optical microcavity embedded with a transition-metal dichalcogenide (TMDC) heterogeneous bilayer encompassing a {\Psi}-shaped channel. By considering exciton-dipolaritons, which are a three way superposi

Indrajit Kurmi, David C. Schedl, Oliver Bimber

Airborne optical sectioning, an effective aerial synthetic aperture imaging technique for revealing artifacts occluded by forests, requires precise measurements of drone poses. In this article we present a new approach for reducing pose estimation errors beyond the possibilities of conventional Perspective-n-Point solutions by considering the underlying opti

Lisong Chen, Ayres Freitas

Measurements of electroweak precision observables at future electron-positron colliders, such as the CEPC, FCC-ee, and ILC, will be sensitive to physics at multi-TeV scales. To achieve this sensitivity, precise predictions for the Standard Model expectations of these observables are needed, including corrections at the three- and four-loop level. In this art

Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu

As deep learning technologies advance, increasingly more data is necessary to generate general and robust models for various tasks. In the medical domain, however, large-scale and multi-parties data training and analyses are infeasible due to the privacy and data security concerns. In this paper, we propose an extendable and elastic learning framework to pre

Stephon Alexander, Gabriel Herczeg, Joao Magueijo

The Hartle-Hawking wave function is known to be the Fourier dual of the Chern-Simons or Kodama state reduced to mini-superspace, using an integration contour covering the whole real line. But since the Chern-Simons state is a general solution of the Hamiltonian constraint (with a given ordering), its Fourier dual should provide the general solution (i.e. bey

Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, Cristina M. Pinotti

In this paper, we study the feasibility of sending drones to deliver goods from a depot to a customer by solving what we call the Mission-Feasibility Problem (MFP). Due to payload constraints, the drone can serve only one customer at a time. To this end, we propose a novel framework based on time-dependent cost graphs to properly model the MFP and tackle the

George Livadiotis, George Nicolaou, Frederic Allegrini

We develop the theoretical basis for the connection of the variety of anisotropic distributions with the statistical correlations among particles velocity components. By examining the most common anisotropic distribution, we derive the correlation coefficient among particle energies, show how this correlation is connected to the effective dimensionality of t

CMS Collaboration

A search for phenomena beyond the standard model in final states with two oppositely charged same-flavor leptons and missing transverse momentum is presented. The search uses a data sample of proton-proton collisions at $\sqrt{s} =$ 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$, collected by the CMS experiment at the LHC. Three potential

Francesco Betti Sorbelli, Cristina M. Pinotti, Simone Silvestri, Sajal K. Das

Localizing ground devices (GDs) is an important requirement for a wide variety of applications, such as infrastructure monitoring, precision agriculture, search and rescue operations, to name a few. To this end, unmanned aerial vehicles (UAVs) or drones offer a promising technology due to their flexibility. However, the distance measurements performed using

F. Dell'Agli, E. Marini, F. D'Antona, P. Ventura

Modelling dust formation in single stars evolving through the carbon-star stage of the asymptotic giant branch (AGB) reproduces well the mid-infrared colours and magnitudes of most of the C-rich sources in the Large Magellanic Cloud (LMC), apart from a small subset of extremely red objects (EROs). The analysis of EROs spectral energy distribution suggests th

Binbin Lin, Julia Auernhammer, Jan-Lukas Schäfer, Robert Stark

Paper materials are natural composite materials and well-known to be hydrophilic unless chemical and mechanical processing treatments are undertaken. The relative humidity impacts the fiber elasticity, the fiber-fiber bonds and the failure mechanism. In this work, we present a comprehensive experimental and computational study on the mechanical and failure b