March 2020 arXiv papers — page 84

S. E. Harris, Brandon Buscaino

We suggest a technique for using off-resonance spectral comb generation to produce broadband frequency modulated, and therefore, amplitude quieted light. Results include closed-form formulae for the amplitudes and phases of all of the spectral components.

E. Angelico, A. Elagin, H. J. Frisch, E. Spieglan

We have designed and prototyped the process steps for the batch production of large-area micro-channel-plate photomultipliers (MCP-PMT) using the "air-transfer" assembly process developed with single $LAPPD^{\text{TM}}$ modules. Results are presented addressing the challenges of designing a robust package that can transmit large numbers of electrical

Georgios Katsouleas, Efthymios N. Karatzas, Fotios Travlopanos

Motivated by many applications in complex domains with boundaries exposed to large topological changes or deformations, fictitious domain methods regard the actual domain of interest as being embedded in a fixed Cartesian background. This is usually achieved via a geometric parameterization of its boundary via level-set functions. In this note, the a priori

Sergey K. Ivanov, Yaroslav V. Kartashov, Alexander Szameit, Lluis Torner

We introduce topological vector edge solitons in a Floquet insulator, consisting of two honeycomb arrays of helical waveguides with opposite directions of rotation in a focusing nonlinear optical medium. Zigzag edges of two arrays placed in contact create a zigzag-zigzag interface between two structures with different topology. A characteristic feature of su

Bingjiang Qiu, Jiapan Guo, Joep Kraeima, Haye H. Glas

Recently, accurate mandible segmentation in CT scans based on deep learning methods has attracted much attention. However, there still exist two major challenges, namely, metal artifacts among mandibles and large variations in shape or size among individuals. To address these two challenges, we propose a recurrent segmentation convolutional neural network (R

Kan Zhao, Hao Deng, Hua Chen, Kate A. Ross

Spin ices are exotic phases of matter characterized by frustrated spins obeying local ice rules, in analogy with the electric dipoles in water ice. In two dimensions, one can similarly define ice rules for in-plane Ising-like spins arranged on a kagome lattice. These ice rules require each triangle plaquette to have a single monopole, and can lead to various

Sung-Yeon Kim, Dmitri Zaitsev

A solution to the effectiveness problem in Kohn's algorithm for generating subelliptic multipliers is provided for domains that include those given by sums of squares of holomorphic functions (also including infinite sums). These domains are of particular interest due to their relation with complex and algebraic geometry and in particular, seem to includ

Jiaming Wu, Soyoung Ah, Yang Zhou, Pan Liu

This paper presents a "cooperative vehicle sorting" strategy that seeks to optimally sort connected and automated vehicles (CAVs) in a multi-lane platoon to reach an ideally organized platoon. In the proposed method, a CAV platoon is firstly discretized into a grid system, where a CAV moves from one cell to another in the discrete time-space domain.

Faiz Ahmad, Akhlesh Lakhtakia, Peter B. Monk

An optoelectronic optimization was carried out for an AlGaAs solar cell containing (i) an n-AlGaAs absorber layer with a graded bandgap and (ii) a periodically corrugated Ag backreflector combined with localized ohmic Pd-Ge-Au backcontacts. The bandgap of the absorber layer was varied either sinusoidally or linearly. An efficiency of 33.1% with the 2000-nm-t

Christo Kurisummoottil Thomas, Bruno Clerckx, Luca Sanguinetti, Dirk Slock

The spectral efficiency (SE) of Massive MIMO (MaMIMO) systems is affected by low quality channel estimates. Rate-Splitting (RS) has recently gained some interest in multiuser multiple antenna systems as an effective means to mitigate the multi-user interference due to imperfect channel state information. This paper investigates the benefits of RS in the down

Utkarsh Goel, Stephen Ludin, Moritz Steiner

A Web browser utilizes a device's CPU to parse HTML, build a Document Object Model, a Cascading Style Sheets Object Model, and render trees, and parse, compile, and execute computationally-heavy JavaScript. A powerful CPU is required to perform these tasks as quickly as possible and provide the user with a great experience. However, increased CPU perform

Wenyun Ju, Ian Dobson, Kenneth Martin, Kai Sun

This paper develops a comprehensive framework of Area Angle Monitoring (AAM) to monitor the stress of bulk power transfer across an area of a power transmission system in real-time. Area angle is calculated from synchrophasor measurements to provide alert to system operators if the area angle exceeds pre-defined thresholds. This paper proposes general method

Xueting Li, Sifei Liu, Kihwan Kim, Shalini De Mello

We learn a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture and camera pose of a target object with a collection of 2D images and silhouettes. The proposed method does not necessitate 3D supervision, manually annotated keypoints, multi-view images of an object or a prior 3D template. The key insight of our work is

Xiaochen Peng, Shanshi Huang, Hongwu Jiang, Anni Lu

DNN+NeuroSim is an integrated framework to benchmark compute-in-memory (CIM) accelerators for deep neural networks, with hierarchical design options from device-level, to circuit-level and up to algorithm-level. A python wrapper is developed to interface NeuroSim with a popular machine learning platform: Pytorch, to support flexible network structures. The f

Ali Rahmati, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard, Huaiyu Dai

Adversarial examples are known as carefully perturbed images fooling image classifiers. We propose a geometric framework to generate adversarial examples in one of the most challenging black-box settings where the adversary can only generate a small number of queries, each of them returning the top-$1$ label of the classifier. Our framework is based on the o

Elisha Falbel, Irene Pasquinelli

A class of complex hyperbolic lattices in PU(2,1) called the Deligne-Mostow lattices has been reinterpreted by Hirzebruch and others in terms of line arrangements. They use branched covers over a suitable blow up of the complete quadrilateral arrangement of lines in projective 2-space to construct the complex hyperbolic surfaces over the orbifolds associated

Yu-Min Chung, William Cruse, Austin Lawson

Topological Data Analysis (TDA) is a rising field of computational topology in which the topological structure of a data set can be observed by persistent homology. By considering a sequence of sublevel sets, one obtains a filtration that tracks changes in topological information. These changes can be recorded in multi-sets known as {\it persistence diagrams

Talia Ringer, Karl Palmskog, Ilya Sergey, Milos Gligoric

Development of formal proofs of correctness of programs can increase actual and perceived reliability and facilitate better understanding of program specifications and their underlying assumptions. Tools supporting such development have been available for over 40 years, but have only recently seen wide practical use. Projects based on construction of machine

Leszek Skrzypczak, Cyril Tintarev

It is common that a Sobolev space defined on $\mathbb{R}^m$ has a non-compact embedding into an $L^p$-space, but it has subspaces for which this embedding becomes compact. There are three well known cases of such subspaces, the Rellich compactness, for a subspace of functions on a bounded domain (or an unbounded domain, sufficiently thin at infinity), the St

Santu Ghosh, Deepak Nag Ayyala, Rafael Hellebuyck

Testing equality of mean vectors is a very commonly used criterion when comparing two multivariate random variables. Traditional tests such as Hotelling's T-squared become either unusable or output small power when the number of variables is greater than the combined sample size. In this paper, w}e propose a test using both prepivoting and Edgeworth expa

Adolf N. Witt, Thomas S. -Y. Lai

Extended Red Emission (ERE) is a widely observed optical emission process, present in a wide range of circumstellar and interstellar environments in the Milky Way galaxy as well as other galaxies. Definitive identifications of the ERE carriers and the ERE process are still a matter of debate. Numerous models have been proposed in recent decades, often develo

Markus Kuba, Alois Panholzer

In this work we analyze bucket increasing tree families. We introduce two simple stochastic growth processes, generating random bucket increasing trees of size $n$, complementing the earlier result of Mahmoud and Smythe for bucket recursive trees. On the combinatorial side, we define multilabelled generalizations of the tree families $d$-ary increasing trees

Jake A. McCoy, Randall L. McEntaffer, Drew M. Miles

Future observatories utilizing reflection grating spectrometers for extreme ultraviolet (EUV) and soft X-ray (SXR) spectroscopy require high-fidelity gratings with both blazed groove facets and custom groove layouts that are often fanned or feature a slight curvature. While fabrication procedures centering on wet anisotropic etching in monocrystalline silico

Sandhya Chandrasekaran, Bharat B. Tripathi, David Espíndola, Gianmarco F. Pinton

Traumatic brain injury studies on the living human brain are experimentally infeasible. We present a simulation approach that models ultrasound propagation in the human brain while it is moving due to the complex shear shock wave deformation from a traumatic impact. Finite difference simulations can model ultrasound propagation in complex media such as human

Pedro V. P. Cunha, Carlos A. R. Herdeiro

The ringdown and shadow of the astrophysically significant Kerr Black Hole (BH) are both intimately connected to a special set of bound null orbits known as Light Rings (LRs). Does it hold that a generic equilibrium BH must possess such orbits? In this letter we prove the following theorem. A stationary, axi-symmetric, asymptotically flat black hole spacetim

L. Vallini, A. Ferrara, A. Pallottini, S. Carniani

We present a novel method to simultaneously characterise the star formation law and the interstellar medium properties of galaxies in the Epoch of Reionization (EoR) through the combination of [CII] 158$μ$m (and its known relation with star formation rate) and CIII]$λ$1909Å emission line data. The method, based on a Markov Chain Monte Carlo algorithm, allows

Xing Zhao, Shuang Yang, Shiguang Shan, Xilin Chen

Lip reading has received an increasing research interest in recent years due to the rapid development of deep learning and its widespread potential applications. One key point to obtain good performance for the lip reading task depends heavily on how effective the representation can be to capture the lip movement information and meanwhile to resist the noise

Wynn C. G. Ho, M. J. P. Wijngaarden, Nils Andersson, Thomas M. Tauris

The application of standard accretion theory to observations of X-ray binaries provides valuable insights into neutron star properties, such as their spin period and magnetic field. However, most studies concentrate on relatively old systems, where the neutron star is in its late propeller, accretor, or nearly spin equilibrium phase. Here we use an analytic

Hamed Hosseiny, Arman Farhang, Behrouz Farhang-Boroujeny

In this paper, we consider channel estimation problem in the uplink of filter bank multicarrier (FBMC) systems. We propose a pilot structure and a joint multiuser channel estimation method for FBMC. Opposed to the available solutions in the literature, our proposed technique does not rely on the flat-channel condition over each subcarrier band or any require

Shane Sims, Cristina Conati

Encouraged by the success of deep learning in a variety of domains, we investigate a novel application of its methods on the effectiveness of detecting user confusion in eye-tracking data. We introduce an architecture that uses RNN and CNN sub-models in parallel to take advantage of the temporal and visuospatial aspects of our data. Experiments with a datase

M. N. de Oliveira, C. R. A. Augusto, C. E. Navia, A. A. Nepomuceno

We present an analysis of the short-term modulation (one rotation of Bartels-27 days) of the galactic cosmic rays (GCR) by the solar wind, based on the cosmic ray rates observed by the Pierre Auger Observatory (PAO) on their surface detectors in scaler mode. The incidence of GCR with energies below $\sim$ 50 TeV, at the top of the atmosphere, produces more t

Pujan Pokhrel, Elias Ioup, Md Tamjidul Hoque, Julian Simeonov

In this paper, we present a novel approach for the prediction of rogue waves in oceans using statistical machine learning methods. Since the ocean is composed of many wave systems, the change from a bimodal or multimodal directional distribution to unimodal one is taken as the warning criteria. Likewise, we explore various features that help in predicting ro

Ruggero Ragonesi, Riccardo Volpi, Jacopo Cavazza, Vittorio Murino

We are interested in learning data-driven representations that can generalize well, even when trained on inherently biased data. In particular, we face the case where some attributes (bias) of the data, if learned by the model, can severely compromise its generalization properties. We tackle this problem through the lens of information theory, leveraging rec

Chih-Yuan Yang, Ravi Sahita

The damage caused by crypto-ransomware, due to encryption, is difficult to revert and cause data losses. In this paper, a machine learning (ML) classifier was built to early detect ransomware (called crypto-ransomware) that uses cryptography by program behavior. If a signature-based detection was missed, a behavior-based detector can be the last line of defe

Giorgos Anastasiou, Olivera Miskovic, Rodrigo Olea, Ioannis Papadimitriou

We show that the Kounterterms for pure AdS gravity in arbitrary even dimensions coincide with the boundary counterterms obtained through holographic renormalization if and only if the boundary Weyl tensor vanishes. In particular, the Kounterterms lead to a well posed variational problem for generic asymptotically locally AdS manifolds only in four dimensions

İlker Gençtürk

The aim of this paper is to bring together a new type of quantum calculus, namely $p $-calculus, and variational calculus. We develop $p $-variational calculus and obtain a necessary optimality condition of Euler-Lagrange type and a sufficient optimality condition.

Yajun Wang, Wen Chen, Chintha Tellambura

The partial transmit sequence (PTS) technique has received much attention in reducing the high peak to average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, the PTS technique requires an exhaustive search of all combinations of the allowed phase factors, and the search complexity increases exponentially with the nu

Ingrid de Almeida Ribeiro, Maurice de Koning

The viscosity of supercooled water has been a subject of intense study, in particular with respect to its temperature dependence. Much less is known, however, about the influence of dynamical effects on the viscosity in its supercooled state. Here we address this issue for the first time, using molecular dynamics simulations to investigate the shear-rate dep

Gurtej Kanwar, Michael S. Albergo, Denis Boyda, Kyle Cranmer

We define a class of machine-learned flow-based sampling algorithms for lattice gauge theories that are gauge-invariant by construction. We demonstrate the application of this framework to U(1) gauge theory in two spacetime dimensions, and find that near critical points in parameter space the approach is orders of magnitude more efficient at sampling topolog

Soham Chakraborty, Sourav Patel, Murti V. Salapaka

Design and implementation of an optimal and robust single-loop voltage controller is proposed for single-phase grid forming voltage source inverter (VSI). The objective of the proposed controller is to have good reference tracking and disturbance rejection. Uncertain nature of loads can significantly alter system's behavior, especially during heavily loa

Mihai Marciu

The paper studies the physical characteristics for the extended $f(P)$ cubic gravity from a transitive perspective based on dynamical system analysis, by considering the linear stability theory in two specific cases, corresponding to power-law $f(P)=f_0 P^α$ and exponential $f(P)=f_0 e^{αP}$ gravity types, where $f_0$ and $α$ are constant parameters. In thes

Jack Holguin, Jeffrey R. Forshaw, Simon Plätzer

A new parton shower algorithm has been presented with the claim of providing soft-gluon resummation at `full colour' (arXiv:2001.11492). In this paper we show that the algorithm does not succeed in this goal. We show that full colour accuracy requires the Sudakov factors to be defined at amplitude level and that the simple parton-shower unitarity argumen

Serge Sharoff

This paper proposes a novel framework for digital curation of Web corpora in order to provide robust estimation of their parameters, such as their composition and the lexicon. In recent years language models pre-trained on large corpora emerged as clear winners in numerous NLP tasks, but no proper analysis of the corpora which led to their success has been c

R. Jorge, W. Sengupta, M. Landreman

Optimized stellarator configurations and their analytical properties are obtained using a near-axis expansion approach. Such configurations are associated with good confinement as the guiding center particle trajectories and neoclassical transport are isomorphic to those in a tokamak. This makes them appealing as fusion reactor candidates. Using a direct coo

B. Dina, S. Ionica

Up to isomorphism over C, every simple principally polarized abelian variety of dimension 3 is the Jacobian of a smooth projective curve of genus 3. Furthermore, this curve is either a hyperelliptic curve or a plane quartic. Given a sextic CM field K, we show that if there exists a hyperelliptic Jacobian with CM by K, then all principally polarized abelian v

Wenshen Song, Ruixiang Fei, Li Yang

It is of fundamental importance but challenging to simultaneously identify atomic and magnetic configurations of two-dimensional van der Waals materials. In this work, we show that the nonreciprocal second-harmonic generation (SHG) can be a powerful tool to answer this challenge. Despite the preserved lattice inversion symmetry, the interlayer antiferromagne

Maxwell Stolarski

In [Vel94], Velazquez constructed a countable collection of mean curvature flow solutions in $\mathbb{R}^N$ in every dimension $N \ge 8$. Each of these solutions becomes singular in finite time at which time the second fundamental form blows up. In contrast, we confirm here that, in every dimension $N \ge 8$, a nontrivial subset of these solutions has unifor

Yu Yuan, Serge Sharoff

This paper explores the use of Deep Learning methods for automatic estimation of quality of human translations. Automatic estimation can provide useful feedback for translation teaching, examination and quality control. Conventional methods for solving this task rely on manually engineered features and external knowledge. This paper presents an end-to-end ne

Samer Katicha, John Khoury, Gerardo Flintsch

In this paper, the authors evaluate the performance of a spatial multiresolution analysis (SMA) method that behaves like a variable bandwidth kernel density estimation (KDE) method, for hazardous road segments identification (HRSI) and crash risk (expected number of crashes) estimation. The proposed SMA, is similar to the KDE method with the additional benef

Alan D. Freed, Shahla Zamani, Laszlo Szabo, John D. Clayton

Two triangular factorizations of the deformation gradient tensor are studied. The first, termed the Lagrangian formulation, consists of an upper-triangular stretch premultiplied by a rotation tensor. The second, termed the Eulerian formulation, consists of a lower-triangular stretch postmultiplied by a different rotation tensor. The corresponding stretch ten

John Bourke

Categorical structures and their pseudomaps rarely form locally presentable 2-categories in the sense of Cat-enriched category theory. However, we show that if the categorical structure in question is sufficiently weak (such as the structure of monoidal, but not strict monoidal, categories) then the 2-category in question is accessible. Furthermore, we explo

Rafael A. Molina, Victor A. Gopar

In models of hopping disorder in the absence of external fields and at the band center, the electrons are less localized in space than the standard exponential Anderson localization. A signature of this anomalous localization is the square root dependence of the logarithmic average of the conductance on the system length, in contrast to the linear length dep

J. A. Toalá, M. A. Guerrero, H. Todt, L. Sabin

We present a multiwavelength study of the iconic Bubble Nebula (NGC 7635) and its ionising star BD$+$60$^{\circ}$2522. We obtained XMM-Newton EPIC X-ray observations to search for extended X-ray emission as in other similar wind-blown bubbles around massive stars. We also obtained San Pedro Mártir spectroscopic observations with the Manchester Echelle Spectr

Xilu Wang, Brian D. Fields, Matthew Mumpower, Trevor Sprouse

Neutron star mergers (NSMs) are rapid neutron capture (r-process) nucleosynthesis sites, which eject materials at high velocities, from 0.1c to as high as 0.6c. Thus the r-process nuclei ejected from a NSM event are sufficiently energetic to initiate spallation reactions with the interstellar medium (ISM) particles. With a thick-target model for the propagat

Jeffery Hart, Taeryon Choi, Naveed Merchant

We propose a non-parametric, two-sample Bayesian test for checking whether or not two data sets share a common distribution. The test makes use of data splitting ideas and does not require priors for high-dimensional parameter vectors as do other nonparametric Bayesian procedures. We provide evidence that the new procedure provides more stable Bayes factors

Ziming Gao, Yuan Gao, Yi Hu, Zhengyong Jiang

Machine Learning algorithms and Neural Networks are widely applied to many different areas such as stock market prediction, face recognition and population analysis. This paper will introduce a strategy based on the classic Deep Reinforcement Learning algorithm, Deep Q-Network, for portfolio management in stock market. It is a type of deep neural network whi

Michał Cieśla, Konrad Kozubek, Piotr Kubala, Adrian Baule

Saturated random sequential adsorption packings built of two-dimensional ellipses, spherocylinders, rectangles, and dimers placed on a one-dimensional line are studied to check analytical prediction concerning packing growth kinetics [A. Baule, Phys. Rev. Let. 119, 028003 (2017)]. The results show that the kinetics is governed by the power-law with the expon

Xingqin Lin, Anders Furuskär, Olof Liberg, Sebastian Euler

Today, mobile operators are starting to deploy Fifth-Generation (5G) networks to expand the coverage ubiquity of broadband wireless service. In contrast, in-flight connectivity remains limited and its quality of service does not always meet the expectations. Embracing 5G New Radio (NR) in Air-to-Ground (A2G) communication systems can help narrow the gap betw

Andjelka B. Kovacevic, Tignfeng Yi, Xinyu Dai, Xing Yang

Here we confirm the short periodic variability of a subparsec supermassive binary black hole (SMBBH) candidate Mrk 231 in the extended optical photometric data set collected by the Catalina Real-Time Transient Survey (CRTS) and All-Sky Automated Survey for Supernovae (ASAS-SN). Using the Lomb-Scargle periodogram and 2DHybrid method, we detected the significa

Julia Mokdad, Georg Knebel, Christophe Marin, Jean-Pascal Brison

In addition to its promising potential for applications, GaV4S8 shows very interesting physical properties with temperature and magnetic field. These properties can be tuned by applying hydrostatic pressure in order to reveal and understand the physics of these materials. Not only pressure induces an insulator-to-metal transition in GaV4S8 but it also has an

Muhammad Ali Farooq, Asma Khatoon, Viktor Varkarakis, Peter Corcoran

Technology-assisted platforms provide reliable solutions in almost every field these days. One such important application in the medical field is the skin cancer classification in preliminary stages that need sensitive and precise data analysis. For the proposed study the Kaggle skin cancer dataset is utilized. The proposed study consists of two main phases.

Hashem Zoubi

We study many-particle phenomena of propagating multi-mode photons and phonons interacting through Brillouin scattering-type Hamiltonian in nanoscale waveguides. We derive photon and phonon retarded Green's functions and extract their spectral functions in applying the factorization approximation of the mean-field theory. The real part of the self-energy

S. Kaufmann, J. Simonis, S. Bacca, J. Billowes

We present the first laser spectroscopic measurement of the neutron-rich nucleus $^{68}$Ni at the \mbox{$N=40$} subshell closure and extract its nuclear charge radius. Since this is the only short-lived isotope for which the dipole polarizability $α_{\rm D}$ has been measured, the combination of these observables provides a benchmark for nuclear structure th

W. Fox, D. B. Schaeffer, M. J. Rosenberg, G. Fiksel

Fast magnetic reconnection was observed between magnetized laser-produced plasmas at the National Ignition Facility. Two highly-elongated plasma plumes were produced by tiling two rows of lasers, with magnetic fields generated in each plume by the Biermann battery effect. Detailed magnetic field observations, obtained from proton radiography using a D$^3$He

Emmanuel Bengio, Joelle Pineau, Doina Precup

We study the link between generalization and interference in temporal-difference (TD) learning. Interference is defined as the inner product of two different gradients, representing their alignment. This quantity emerges as being of interest from a variety of observations about neural networks, parameter sharing and the dynamics of learning. We find that TD

Georgiy Karev

Evolution of distribution of strategies in game theory is an interesting question that has been studied only for specific cases. Here I develop a general method to extend analysis of the evolution of continuous strategy distributions given bi-linear and quadratic payoff functions for any initial distribution to answer the following question: given the initia

Jennifer Renoux, Uwe Köckemann, Amy Loutfi

Smart home environments equipped with distributed sensor networks are capable of helping people by providing services related to health, emergency detection or daily routine management. A backbone to these systems relies often on the system's ability to track and detect activities performed by the users in their home. Despite the continuous progress in t

Agnessa Kovaleva

In this work, we develop an analytical framework to explain the influence of dissipation and detuning parameters on the emergence and stability of autoresonance in a strongly nonlinear weakly damped chain subjected to harmonic forcing with a slowly-varying frequency. Using the asymptotic procedures, we construct the evolutionary equations, which describe the

Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu

Botnets are now a major source for many network attacks, such as DDoS attacks and spam. However, most traditional detection methods heavily rely on heuristically designed multi-stage detection criteria. In this paper, we consider the neural network design challenges of using modern deep learning techniques to learn policies for botnet detection automatically

Sergio E. Galindo, Pablo Toharia, Oscar D. Robles, Eduardo Ros

Computational modeling is becoming a widely used methodology in modern neuroscience. However, as the complexity of the phenomena under study increases, the analysis of the results emerging from the simulations concomitantly becomes more challenging. In particular, the configuration and validation of brain circuits involving learning often require the process

Gerald Kuba

Let A be an arbitrary countable set of reals, for example A=Q. Let g be an arbitrary mapping from A into the positive reals, for example g(a)=2^a. We show how a strictly increasing real function f can be constructed such that f'(x)=g(x) for every x in the set A and f'(x)=0 for almost all real numbers x.

François Arleo, Florian Cougoulic, Stéphane Peigné

We single out the role of fully coherent induced gluon radiation on light hadron production in pA collisions. The effect has the same general features as for quarkonium production, however with a richer color structure as the induced radiation depends on the global color charge of the partonic subprocess final state. Baseline predictions for light hadron nuc

Renato Martins, Dhiego Bersan, Mario F. M. Campos, Erickson R. Nascimento

This paper addresses the problem of building augmented metric representations of scenes with semantic information from RGB-D images. We propose a complete framework to create an enhanced map representation of the environment with object-level information to be used in several applications such as human-robot interaction, assistive robotics, visual navigation

Akseli Mansikkamäki, Zhishou Huang, Naoya Iwahara, Liviu F. Chibotaru

The applicability of a broken symmetry version of the $G_0W_0$ approximation to the calculation of isotropic exchange coupling constants has been studied. Using a simple H--He--H model system the results show a significant and consistent improvement of the results over both broken symmetry Hartree--Fock and broken symmetry density functional theory. In the c

Yasir K. Al-Nadawi, Hothaifa Al-Qassab, Daniel Kent, Su Pang

In the real-world, self-driving vehicles are required to achieve steering maneuvers in both uncontrolled and uncertain environments while maintaining high levels of safety and passengers' comfort. Ignoring these requirements would inherently cause a significant degradation in the performance of the control system, and consequently, could lead to life-thr

Ander Lamaison

For a fixed infinite graph $H$, we study the largest density of a monochromatic subgraph isomorphic to $H$ that can be found in every two-coloring of the edges of $K_{\mathbb{N}}$. This is called the Ramsey upper density of $H$, and was introduced by Erdős and Galvin. Recently, the Ramsey upper density of the infinite path was determined. Here, we find the v

Bastian Hagedorn, Archibald Samuel Elliott, Henrik Barthels, Rastislav Bodik

Achieving high-performance GPU kernels requires optimizing algorithm implementations to the targeted GPU architecture. It is of utmost importance to fully use the compute and memory hierarchy, as well as available specialised hardware. Currently, vendor libraries like cuBLAS and cuDNN provide the best performing implementations of GPU algorithms. However the

Andreas Komninos, Kyriakos Katsaris, Emma Nicol, Mark Dunlop

Text entry in smartphones remains a critical element of mobile HCI. It has been widely studied in lab settings, using primarily transcription tasks, and to a far lesser extent through in-the-wild (field) experiments. So far it remains unknown how well user behaviour during lab transcription tasks approximates real use. In this paper, we present a study that

A. Ya. Helemskii

We obtain a far-reaching generalization (in several directions) of the theorem of A. Lambert on the existence of the projective tensor product of operator sequence spaces. This result is obtained in the context of spaces, generalizing $p$-multinormed spaces of Dales et al. which are based on an arbitrary, perhaps non-discrete measure.

Tarun Kathuria, Satyaki Mukherjee, Nikhil Srivastava

Consider $n$ complex random matrices $X_1,\ldots,X_n$ of size $d\times d$ sampled i.i.d. from a distribution with mean $E[X]=μ$. While the concentration of averages of these matrices is well-studied, the concentration of other functions of such matrices is less clear. One function which arises in the context of stochastic iterative algorithms, like Oja's

Andreas Komninos, Emma Nicol, Mark Dunlop

During lab studies of text entry methods it is typical to observer very few errors in participants' typing - users tend to type very carefully in labs. This is a problem when investigating methods to support error awareness or correction as support mechanisms are not tested. We designed a novel evaluation method based around injection of errors into the

Martin J Dyer

The detection of the first electromagnetic counterpart to a gravitational-wave signal in August 2017 marked the start of a new era of multi-messenger astrophysics. An unprecedented number of telescopes around the world were involved in hunting for the source of the signal, and although more gravitational-wave signals have been since detected, no further elec

Maria Santamaria, Ebroul Izquierdo, Saverio Blasi, Marta Mrak

Rate-control is essential to ensure efficient video delivery. Typical rate-control algorithms rely on bit allocation strategies, to appropriately distribute bits among frames. As reference frames are essential for exploiting temporal redundancies, intra frames are usually assigned a larger portion of the available bits. In this paper, an accurate method to e

Samuli Autti, Petri J. Heikkinen, Jere T. Mäkinen, Grigori E. Volovik

Quantum time crystals are systems characterised by spontaneously emerging periodic order in the time domain. A range of such phases has been reported. The concept has even been discussed in popular literature, and deservedly so: while the first speculation on a phase of broken time translation symmetry did not use the name "time crystal", it was late

Manoj Joshi, Andrew Elvidge, Robin Wordsworth, Denis Sergeev

A key factor in determining the potential habitability of synchronously rotating planets is the strength of the atmospheric boundary layer inversion between the dark side surface and the free atmosphere. Here we analyse data obtained from polar night measurements at the South Pole and Alert Canada, which are the closest analogues on Earth to conditions on th

Suat Gumussoy, Ahmet Arda Ozdemir, Tomas McKelvey, Lennart Ljung

An estimated state-space model can possibly be improved by further iterations with estimation data. This contribution specifically studies if models obtained by subspace estimation can be improved by subsequent re-estimation of the B, C, and D matrices (which involves linear estimation problems). Several tests are performed, which shows that it is generally

Jorge Caravantes, J. Rafael Sendra, David Sevilla, Carlos Villarino

We present an algorithm that transforms, if possible, a given ODE or PDE with radical function coefficients into one with rational coefficients by means of a rational change of variables. It also applies to systems of linear ODEs. It is based on previous work on reparametrization of radical algebraic varieties.

Shinji Hirano, Masaki Shigemori

We study the random geometry approach to the $T\bar{T}$ deformation of 2d conformal field theory developed by Cardy and discuss its realization in a gravity dual. In this representation, the gravity dual of the $T\bar{T}$ deformation becomes a straightforward translation of the field theory language. Namely, the dual geometry is an ensemble of AdS$_3$ spaces

Tor Inge Reigstad, Kjetil Uhlen

This paper proposes a hydraulic model based on the Euler turbine equations suitable for the purpose of grid integration studies of variable speed hydropower (VSHP). The work was motivated by the need to assess how the dynamic performance might change when a hydropower plant is operated at variable speed. The Euler model considers the water flow dependency on

Chaoqi Chen, Zebiao Zheng, Xinghao Ding, Yue Huang

Recent advances in adaptive object detection have achieved compelling results in virtue of adversarial feature adaptation to mitigate the distributional shifts along the detection pipeline. Whilst adversarial adaptation significantly enhances the transferability of feature representations, the feature discriminability of object detectors remains less investi

Ahmet Arda Ozdemir, Suat Gumussoy

This paper considers black- and grey-box continuous-time transfer function estimation from frequency response measurements. The first contribution is a bilinear mapping of the original problem from the imaginary axis onto the unitdisk. This improves the numerics of the underlying Sanathanan-Koerner iterations and the more recent instrumental-variable iterati

A. N. Popov, S. V. Bobashev, N. O. Bezverkhnii, A. A. Sorokin

The possibility of performing the experimental research in the field of fundamental physics based on the unique instrument -- European X-ray Free Electron Laser (E-XFEL) is considered in this paper. The calculations of the reaction $γ+ γ\to e^{+} + e^{-}$ cross section for gamma quanta with $E \sim~(1-100)\,\mbox{GeV}$ energy with X-ray photons are performed

George Perrakis, Anna C. Tasolamprou, George Kenanakis, Eleftherios N. Economou

We investigate and evaluate the contribution of the ultraviolet radiation spectrum on the temperature and efficiency of commercial crystalline silicon-based photovoltaics (PVs) that operate outdoors. The investigation is performed by employing a comprehensive thermal-electrical modeling approach which takes into account all the major processes affected by th

Muhammad Ali Farooq, Muhammad Aatif Mobeen Azhar, Rana Hammad Raza

Technology aided platforms provide reliable tools in almost every field these days. These tools being supported by computational power are significant for applications that need sensitive and precise data analysis. One such important application in the medical field is Automatic Lesion Detection System (ALDS) for skin cancer classification. Computer aided di

Michel Lavrauw, Tomasz Popiel, John Sheekey

We classify nets of conics in Desarguesian projective planes over finite fields of odd order, namely, two-dimensional linear systems of conics containing a repeated line. Our proof is geometric in the sense that we solve the equivalent problem of classifying the orbits of planes in $\text{PG}(5,q)$ which meet the quadric Veronesean in at least one point, und

E. Bonnassieux, A. Edge, L. Morabito, A. Bonafede

We show that the use of a superstation (a phased array created using multiple stations of an interferometric array) created in post-processing for LOFAR-VLBI observations introduces a direction-dependent loss of signal in the image. We show this effect using simulations and real data. Using the RIME formalism, we characterise it fully, and give limits under

Tor Inge Reigstad, Kjetil Uhlen

This paper deals with the design of controllers for variable speed hydropower (VSHP) plants with the objective of optimize the plants' performance. The control objectives imply enabling fast responses to frequency deviations while keeping the electric and hydraulic variables within their constraints. A model predictive controller (MPC) was developed to c

Cheng-Cheng Guo, Jin-Yuan Liao, Shu Zhang, Juan Zhang

The Medium Energy X-ray Telescope (ME) is one of the main payloads of the Hard X-ray Modulation Telescope (dubbed as Insight-HXMT). The background of Insight-HXMT/ME is mainly caused by the environmental charged particles and the background intensity is modulated remarkably by the geomagnetic field, as well as the geographical location. At the same geographi

Yunhao Tang, Michal Valko, Rémi Munos

In this work, we investigate the application of Taylor expansions in reinforcement learning. In particular, we propose Taylor expansion policy optimization, a policy optimization formalism that generalizes prior work (e.g., TRPO) as a first-order special case. We also show that Taylor expansions intimately relate to off-policy evaluation. Finally, we show th

Patrick Knöbelreiter, Christian Sormann, Alexander Shekhovtsov, Friedrich Fraundorfer

It has been proposed by many researchers that combining deep neural networks with graphical models can create more efficient and better regularized composite models. The main difficulties in implementing this in practice are associated with a discrepancy in suitable learning objectives as well as with the necessity of approximations for the inference. In thi