October 2020 arXiv papers — page 44

Sebastian J. Szybka, Syed U. Naqvi

We study the motion of free masses subject to the influence of standing gravitational waves in the polarized Gowdy cosmology with a three-torus topology. We show that antinodes attract freely falling particles and we trace the velocity memory effect.

Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Varun Pandey

Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, approximations are typically only used in a first filtering step to determine a set of candidate spatial objects that may fulfill the query condition. To provide accurate results, the exact geometries of the candidat

Lin Pan, Chung-Wei Hang, Haode Qi, Abhishek Shah

We propose a simple method to align multilingual contextual embeddings as a post-pretraining step for improved zero-shot cross-lingual transferability of the pretrained models. Using parallel data, our method aligns embeddings on the word level through the recently proposed Translation Language Modeling objective as well as on the sentence level via contrast

Erdem Koyuncu

We consider quantizing an $Ld$-dimensional sample, which is obtained by concatenating $L$ vectors from datasets of $d$-dimensional vectors, to a $d$-dimensional cluster center. The distortion measure is the weighted sum of $r$th powers of the distances between the cluster center and the samples. For $L=1$, one recovers the ordinary center based clustering fo

Samson Abramsky

We discuss how mathematical semantics has evolved, and suggest some new directions for future work. As an example, we discuss some recent work on encapsulating model comparison games as comonads, in the context of finite model theory.

Tom Holt, Weiyi Zhang

We show that the almost complex Hodge number $h^{0,1}$ varies with different choices of almost K\"ahler metrics. This answers the almost K\"ahler version of a question of Kodaira and Spencer.

Dulaj Gunasinghe, Dhanushka Kudathanthirige, Gayan Amarasuriya Aruma Baduge

The fundamental performance metrics of an intelligent reflective surface (IRS)-aided wireless system are presented. By optimizing the IRS phase-shift matrix, the received signal-to-noise ratio (SNR) is maximized at the destination in the presence of both reflected and direct channels. The probability distributions of this maximum SNR are tightly approximated

Diluka Loku Galappaththige, Dhanushka Kudathanthirige, Gayan Amarasuriya Aruma Baduge

In this paper, a comprehensive performance analysis of a distributed intelligent reflective surfaces (IRSs)-aided communication system is presented. First, the optimal signal-to-noise ratio (SNR), which is attainable through the direct and reflected channels, is quantified by controlling the phase shifts of the distributed IRS. Next, this optimal SNR is stat

Y. -P. Ma, H. Susanto

We study continuations of topological edge states in the Su-Schrieffer-Heeger model with on-site cubic (Kerr) nonlinearity, which is a 1D nonlinear photonic topological insulator (TI). Based on the topology of the underlying spatial dynamical system, we establish the existence of nonlinear edge states (edge solitons) for all positive energies in the topologi

Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman

The COVID-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries and resulting in widespread lockdowns for emergency containment. Large-scale digital contact tracing (DCT) has emerged as a potential solution to resume economic and social activity while minimizing spread of the virus. Various DCT methods have been prop

Tim Coopmans, Robert Knegjens, Axel Dahlberg, David Maier

In order to bring quantum networks into the real world, we would like to determine the requirements of quantum network protocols including the underlying quantum hardware. Because detailed architecture proposals are generally too complex for mathematical analysis, it is natural to employ numerical simulation. Here we introduce NetSquid, the NETwork Simulator

Valentino Vito

Diagram chasing is a customary proof method used in category theory and homological algebra. It involves an element-theoretic approach to show that certain properties hold for a commutative diagram. When dealing with abelian categories for the first time, one would work using a diagrammatic approach without relying on the notion of elements. However, constan

Mohammed Berkani

In this paper, we define and index for continuous families of semi-Fredholm bounded liner operators. Moreover, we study various regularities and semiregularities of continuous families of bounded linear operators.

Nicole Peinelt, Marek Rei, Maria Liakata

Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks. However, BERT is only trained to predict missing words - either behind masks or in the next sentence - and has no knowledge of lexical, syntactic or semantic information beyond what it picks up through unsupervised pre-training. We pro

Youngho Jung, Junho Jeong, Zhongnan Qu, Bin Cui

Vanadium dioxide (VO2) is a phase change material that can reversibly change between high and low resistivity states through electronic and structural phase transitions. Thus far, VO2 memory devices have essentially been volatile at room temperature, and nonvolatile memory has required non-ambient surroundings (e.g., elevated temperatures, electrolytes) and

C. A. Brackley, A. Lips, A. Morozov, W. C. K. Poon

Understanding the interactions between viruses and surfaces or interfaces is important, as they provide the principles underpinning the cleaning and disinfection of contaminated surfaces. Yet, the physics of such interactions is currently poorly understood. For instance, there are longstanding experimental observations suggesting that the presence of air-wat

Luana Ruiz, Zhiyang Wang, Alejandro Ribeiro

Graph neural networks (GNNs) are learning architectures that rely on knowledge of the graph structure to generate meaningful representations of large-scale network data. GNN stability is thus important as in real-world scenarios there are typically uncertainties associated with the graph. We analyze GNN stability using kernel objects called graphons. Graphon

Leonid W. Dworzanski

A dynamical system of points moving along the edges of a graph could be considered as a geometrical discrete dynamical system or as a discrete version of a quantum graph with localized wave packets. We study the set of such systems over metric graphs that can be constructed from a given set of commensurable edges with fixed lengths. It is shown that there al

Peng Qi, Haejun Lee, Oghenetegiri "TG" Sido, Christopher D. Manning

We develop a unified system to answer directly from text open-domain questions that may require a varying number of retrieval steps. We employ a single multi-task transformer model to perform all the necessary subtasks -- retrieving supporting facts, reranking them, and predicting the answer from all retrieved documents -- in an iterative fashion. We avoid c

Mark Schlutow, Georg S. Völker

We investigate strongly nonlinear stationary gravity waves which experience refraction due to a thin vertical shear layer of horizontal background wind. The velocity amplitude of the waves is of the same order of magnitude as the background flow and hence the self-induced mean flow alters the modulation properties to leading order. In this theoretical study,

Duo Xu, Stella S. R. Offner, Robert Gutermuth, Colin Van Oort

We adopt the deep learning method CASI-3D (Convolutional Approach to Structure Identification-3D) to identify protostellar outflows in molecular line spectra. We conduct magneto-hydrodynamics simulations that model forming stars that launch protostellar outflows and use these to generate synthetic observations. We apply the 3D radiation transfer code RADMC-3

Xinliang An, Qing Han

For the study of $3+1$ dimensional Einstein vacuum equations (EVEs), substantial progress has been made recently on the problem of trapped surface formation. However, very limited knowledge of existence and associated properties is acquired on the boundary of the emerged trapped region, i.e., the apparent horizon, which is composed of marginally outer trappe

Jing Lu, Gustavo Hernandez Abrego, Ji Ma, Jianmo Ni

In this paper we explore the effects of negative sampling in dual encoder models used to retrieve passages for automatic question answering. We explore four negative sampling strategies that complement the straightforward random sampling of negatives, typically used to train dual encoder models. Out of the four strategies, three are based on retrieval and on

Fatemeh Ghaderinezhad, Christophe Ley, Ben Serrien

The prior distribution is a crucial building block in Bayesian analysis, and its choice will impact the subsequent inference. It is therefore important to have a convenient way to quantify this impact, as such a measure of prior impact will help us to choose between two or more priors in a given situation. A recently proposed approach consists in determining

Antonello Maruotti, Luca Merlo, Lea Petrella

This paper develops a two-part finite mixture quantile regression model for semi-continuous longitudinal data. The proposed methodology allows heterogeneity sources that influence the model for the binary response variable, to influence also the distribution of the positive outcomes. As is common in the quantile regression literature, estimation and inferenc

Christopher Lee, James Hogan

Crater cataloging is an important yet time-consuming part of geological mapping. We present an automated Crater Detection Algorithm (CDA) that is competitive with expert-human researchers and hundreds of times faster. The CDA uses multiple neural networks to process digital terrain model and thermal infra-red imagery to identify and locate craters across the

Cristhian Garcia-Quintero, Mustapha Ishak, Orion Ning

We constrain deviations from general relativity (GR) including both redshift and scale dependencies in the modified gravity (MG) parameters. In particular, we employ the under-used binning approach and compare the results to functional forms. We use available datasets such as Cosmic Microwave Background (CMB) from Planck 2018, Baryonic Acoustic Oscillations

L. Zurek, E. A. Coello Pérez, S. K. Bogner, R. J. Furnstahl

Empirical energy density functionals (EDFs) are generally successful in describing nuclear properties across the table of nuclides. But their limitations motivate using the density-matrix expansion (DME) to embed long-range pion interactions into a Skyrme functional. Recent results on the impact of the pion were both encouraging and puzzling, necessitating a

Christopher J. Sarabalis, Raphaël Van Laer, Rishi N. Patel, Yanni D. Dahmani

We demonstrate a collinear acousto-optic modulator in a suspended film of lithium niobate employing a high-confinement, wavelength-scale waveguide. By strongly confining the optical and mechanical waves, this modulator improves by orders of magnitude a figure-of-merit that accounts for both acousto-optic and electro-mechanical efficiency. Our device demonstr

Sheng Zhong, Zhenyuan Zhang, Nima Fazeli, Dmitry Berenson

We propose an approach to online model adaptation and control in the challenging case of hybrid and discontinuous dynamics where actions may lead to difficult-to-escape "trap" states, under a given controller. We first learn dynamics for a system without traps from a randomly collected training set (since we do not know what traps will be encountered online)

I. Díaz-Saldaña, M. Sabido, J. C. López-Domínguez, J. E. Rosales-Quintero

In this work we study the symmetry breaking conditions, given by a (anti)de Sitter-valued vector field, of a full (anti)de Sitter-invariant MacDowell-Mansouri inspired action. We show that under these conditions the action breaks down to General Relativity with a cosmological constant, the four dimensional topological invariants, as well as the Holst term. W

James E. Johndrow, Natesh S. Pillai, Aaron Smith

It is widely known that the performance of Markov chain Monte Carlo (MCMC) can degrade quickly when targeting computationally expensive posterior distributions, such as when the sample size is large. This has motivated the search for MCMC variants that scale well to large datasets. One popular general approach has been to look at only a subsample of the data

Andreas Gottscholl, Matthias Diez, Victor Soltamov, Christian Kasper

Optically active defects in solids with accessible spin states are promising candidates for solid state quantum information and sensing applications. To employ these defects as quantum building blocks, coherent manipulation of their spin state is required. Here we realize coherent control of ensembles of boron vacancy (V$_B^-$) centers in hexagonal boron nit

Linyi Yang, Eoin M. Kenny, Tin Lok James Ng, Yi Yang

Corporate mergers and acquisitions (M&A) account for billions of dollars of investment globally every year, and offer an interesting and challenging domain for artificial intelligence. However, in these highly sensitive domains, it is crucial to not only have a highly robust and accurate model, but be able to generate useful explanations to garner a user's t

Giovanni Mongardi, Claudio Onorati

In this paper we analyse the birational geometry of O'Grady ten dimensional manifolds, giving a characterisation of Kaehler classes and lagrangian fibrations. Moreover, we study symplectic compactifications of intermediate jacobian fibrations of smooth cubic fourfolds.

Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig

Our interest is in scientific problems with the following characteristics: (1) Data are naturally represented as graphs; (2) The amount of data available is typically small; and (3) There is significant domain-knowledge, usually expressed in some symbolic form. These kinds of problems have been addressed effectively in the past by Inductive Logic Programming

Nafise Sadat Moosavi, Marcel de Boer, Prasetya Ajie Utama, Iryna Gurevych

Existing NLP datasets contain various biases, and models tend to quickly learn those biases, which in turn limits their robustness. Existing approaches to improve robustness against dataset biases mostly focus on changing the training objective so that models learn less from biased examples. Besides, they mostly focus on addressing a specific bias, and while

Min-cheol Kim, Namyoung Ahn, Diyi Cheng, Mingjie Xu

Perovskite solar cells have drawn much attention in recent years, owing to its world-record setting photovoltaic performances. Despite its promising use in tandem applications and flexible devices, its practicality is still limited by its structural instability often arising from ion migration and defect formation. While it is generally understood that ion i

Samson Abramsky

We give an overview and conceptual discussion of some of our results on contextuality and non-locality. We focus in particular on connections with the work of Itamar Pitowsky on correlation polytopes, Bell inequalities, and Boole's "conditions of possible experience".

Ondřej Hubáček, Gustav Šír

It is a common misconception that in order to make consistent profits as a trader, one needs to posses some extra information leading to an asset value estimation more accurate than that reflected by the current market price. While the idea makes intuitive sense and is also well substantiated by the widely popular Kelly criterion, we prove that it is general

G. Seibold, M. Udina, C. Castellani, L. Benfatto

Recent experiments with strong THz fields in both conventional and unconventional superconductors have clearly evidenced a marked third-harmonic generation below the superconducting temperature $T_c$. Its interpretation challenged substantial theoretical work aimed at establishing the relative efficiency of quasiparticle excitations and collective modes in t

Jacek Jendrej, Andrew Lawrie

We consider the energy-critical wave maps equation from 1+2 dimensional Minkowski space into the 2-sphere, in the equivariant case. We prove that if a wave map decomposes, along a sequence of times, into a superposition of at most two rescaled harmonic maps (bubbles) and radiation, then such a decomposition holds for continuous time. If the equivariance degr

Özlem Salehi, Zeki Seskir, İlknur Tepe

Contribution: In this study, an alternative educational approach for introducing quantum computing to a wider audience is highlighted. The proposed methodology considers quantum computing as a generalized probability theory rather than a field emanating from physics and utilizes quantum programming as an educational tool to reinforce the learning process. Ba

Xianchao Wu

It is reported that financial news, especially financial events expressed in news, provide information to investors' long/short decisions and influence the movements of stock markets. Motivated by this, we leverage financial event streams to train a classification neural network that detects latent event-stock linkages and stock markets' systematic behaviour

Rajendra P. Gupta

We have used the recently published varying physical constants (VPC) approach to resolve the primordial lithium abundance problem. The value of the ratio of $7Li$ to hydrogen $7Li/H=1.400(\pm 0.023){\times}10^{-10}$ we have calculated using this approach is about four times lower than that estimated using the standard lambda cold dark matter (${\Lambda}$CDM)

Tim Draws, Jody Liu, Nava Tintarev

Support or opposition concerning a debated claim such as abortion should be legal can have different underlying reasons, which we call perspectives. This paper explores how opinion mining can be enhanced with joint topic modeling, to identify distinct perspectives within the topic, providing an informative overview from unstructured text. We evaluate four jo

Masahiro Sato, Jacques Garrigue

Werner's set-theoretical model is one of the simplest models of CIC. It combines a functional view of predicative universes with a collapsed view of the impredicative sort Prop. However this model of Prop is so coarse that the principle of excluded middle holds. Following our previous work, we interpret Prop into a topological space (a special case of Heytin

Cristina Sanz-Fernández, Martín Molezuelas, Jon Lasa-Alonso, Nuno de Sousa

High refractive index dielectric spheres present remarkable light-scattering properties in the spectral range dominated by dipolar modes. However, most of these properties are absent for larger spheres under plane wave illumination. Here, we propose to unravel dipolar regimes regardless of the sphere size and refractive index by illuminating with a pure dipo

Gonzalo Seco-Granados, David Gomez-Casco, Jose A. Lopez-Salcedo, Ignacio Fernandez-Hernandez

Intentional interference, and in particular GNSS spoofing, is currently one of the most significant concerns of the Positioning, Navigation and Timing (PNT) community. With the adoption of Open Service Navigation Message Authentication (OSNMA) in Galileo, the E1B signal component will continuously broadcast unpredictable cryptographic data. This allows GNSS

Xiao-Li Huang, En-Wei Liang, Ruo-Yu Liu, Ji-Gui Cheng

Bimodal spectral energy distributions (SEDs) of gamma-ray burst (GRB) afterglow of GRBs 190114C, 130427A and 180720B confirm that they are originated from the synchrotron emission (Syn) and synchrotron self-Compton Scattering process (SSC) of electrons accelerated in the jets. The radiation mechanism and the physics of the observed spectrum-luminosity/energy

Myriam Bontonou, Giulia Lioi, Nicolas Farrugia, Vincent Gripon

Few-shot learning addresses problems for which a limited number of training examples are available. So far, the field has been mostly driven by applications in computer vision. Here, we are interested in adapting recently introduced few-shot methods to solve problems dealing with neuroimaging data, a promising application field. To this end, we create a neur

Nicolas Moreau, Boris Brun, Sowmya Somanchi, Kenji Watanabe

The quantum Hall effect is the seminal example of topological protection, as charge carriers are transmitted through one-dimensional edge channels where backscattering is prohibited. Graphene has made its marks as an exceptional platform to reveal new facets of this remarkable property. However, in conventional Hall bar geometries, topological protection of

Zhi Hu, Siqi Xu, Chandan Mondal, Xingbo Zhao

We investigate the leading-twist transverse momentum-dependent distribution functions (TMDs) for a physical electron, a spin-1/2 composite system consisting of a bare electron and a photon, using the Basis Light-front Quantization (BLFQ) framework. The light-front wave functions of the physical electron are obtained from the eigenvectors of the light-front Q

Omid Ghahabi, Volker Fischer

This technical report describes the EML submission to the first VoxCeleb speaker diarization challenge. Although the aim of the challenge has been the offline processing of the signals, the submitted system is basically the EML online algorithm which decides about the speaker labels in runtime approximately every 1.2 sec. For the first phase of the challenge

Chaoning Zhang, Philipp Benz, Dawit Mureja Argaw, Seokju Lee

ResNet or DenseNet? Nowadays, most deep learning based approaches are implemented with seminal backbone networks, among them the two arguably most famous ones are ResNet and DenseNet. Despite their competitive performance and overwhelming popularity, inherent drawbacks exist for both of them. For ResNet, the identity shortcut that stabilizes training also li

Daniel Deutsch, Dan Roth

Reference-based metrics such as ROUGE or BERTScore evaluate the content quality of a summary by comparing the summary to a reference. Ideally, this comparison should measure the summary's information quality by calculating how much information the summaries have in common. In this work, we analyze the token alignments used by ROUGE and BERTScore to compare s

Pavel Kos, Bruno Bertini, Tomaž Prosen

We study the time evolution operator in a family of local quantum circuits with random fields in a fixed direction. We argue that the presence of quantum chaos implies that at large times the time evolution operator becomes effectively a random matrix in the many-body Hilbert space. To quantify this phenomenon we compute analytically the squared magnitude of

Chenxi Sun, Shenda Hong, Moxian Song, Hongyan Li

Irregularly sampled time series (ISTS) data has irregular temporal intervals between observations and different sampling rates between sequences. ISTS commonly appears in healthcare, economics, and geoscience. Especially in the medical environment, the widely used Electronic Health Records (EHRs) have abundant typical irregularly sampled medical time series

Mingjie Shao, Wing-Kin Ma

Adopting one-bit analog-to-digital convertors (ADCs) for massive multiple-input multiple-output (MIMO) implementations has great potential in reducing the hardware cost and power consumption. However, distortions caused by quantization raise great challenges. In MIMO orthogonal frequency-division modulation (OFDM) detection, coarse quantization renders the o

Samuel Stern, Giacomo Livan

We investigate the impact of noise and topology on opinion diversity in social networks. We do so by extending well-established models of opinion dynamics to a stochastic setting where agents are subject both to assimilative forces by their local social interactions, as well as to idiosyncratic factors preventing their population from reaching consensus. We

Christoforos Neofytidis

We classify in terms of Hopf-type properties mapping tori of residually finite Poincar\'e Duality groups with non-zero Euler characteristic. This generalises and gives a new proof of the analogous classification for fibered 3-manifolds. Various applications are given. In particular, we deduce that rigidity results for Gromov hyperbolic groups hold for the ab

Maria N. Drozdovskaya, Isaac R. H. G. Schroeder, Martin Rubin, Kathrin Altwegg

Deuterated methanol is one of the most robust windows astrochemists have on the individual chemical reactions forming deuterium-bearing molecules and the physicochemical history of the regions where they reside. The first-time detection of mono- and di-deuterated methanol in a cometary coma is presented for comet 67P/Churyumov-Gerasimenko using Rosetta-ROSIN

Jianren Wang, Yujie Lu, Hang Zhao

Developing agents that can perform complex control tasks from high dimensional observations such as pixels is challenging due to difficulties in learning dynamics efficiently. In this work, we propose to learn forward and inverse dynamics in a fully unsupervised manner via contrastive estimation. Specifically, we train a forward dynamics model and an inverse

Dina Mardaoui, Damien Garreau

Text data are increasingly handled in an automated fashion by machine learning algorithms. But the models handling these data are not always well-understood due to their complexity and are more and more often referred to as "black-boxes." Interpretability methods aim to explain how these models operate. Among them, LIME has become one of the most popular in

Vikas S. Krishnamurthy, Miles H. Wheeler, Darren G. Crowdy, Adrian Constantin

A large class of new exact solutions to the steady, incompressible Euler equation on the plane is presented. These hybrid solutions consist of a set of stationary point vortices embedded in a background sea of Liouville-type vorticity that is exponentially related to the stream function. The input to the construction is a "pure" point vortex equilibrium in a

Yogeshwar Prasad, Arti Garg

We study many-body localization (MBL) in a one-dimensional system of spinless fermions with a deterministic aperiodic potential in the presence of long-range interactions decaying as power-law $V_{ij}/(r_i-r_j)^\alpha$ with distance and having random coefficients $V_{ij}$. We demonstrate that MBL survives even for $\alpha <1$ and is preceded by a broad non-e

Xu Tan, Xiao-Lei Zhang

Robust voice activity detection (VAD) is a challenging task in low signal-to-noise (SNR) environments. Recent studies show that speech enhancement is helpful to VAD, but the performance improvement is limited. To address this issue, here we propose a speech enhancement aided end-to-end multi-task model for VAD. The model has two decoders, one for speech enha

K. Kefala, G. P. Kodaxis, I. D. Stamou, N. Tetradis

We discuss features of the inflaton potential that can lead to a strong enhancement of the power spectrum of curvature perturbations. We show that a steep decrease of the potential induces an enhancement of the spectrum by several orders of magnitude, which may lead to the production of primordial black holes. The same feature can also create a distinctive o

Jin Liu, Robert A. Perera

Researchers continue to be interested in exploring the effects that covariates have on the heterogeneity in trajectories. The inclusion of covariates associated with latent classes allows for a more clear understanding of individual differences and a more meaningful interpretation of latent class membership. Many theoretical and empirical studies have focuse

Fernanda Perez-Verdugo, Jean-Francois Joanny, Rodrigo Soto

The vertex model is widely used to describe the dynamics of epithelial tissues, because of its simplicity and versatility and the direct inclusion of biophysical parameters. Here, it is shown that quite generally, when cells modify their equilibrium perimeter due to their activity, or the tissue is subject to external stresses, the tissue becomes unstable wi

Muhammad Fitrah Alfian Rangga Sakti, Freddy Permana Zen

We demonstrate that Kerr/CFT duality can be extended to rotating charged black hole solution surrounded by quintessence in Rastall gravity. Since Rastall gravity can be considered as $F(R,T) = R + \beta T $ theory with the addition of a matter term, so the gravitational Lagrangian is resemblant to Einstein general relativity. In fact, the resulting central t

Maël Le Treust, Tristan Tomala

We propose a strategic formulation for the joint source-channel coding problem in which the encoder and the decoder are endowed with distinct distortion functions. We provide the solutions in four different scenarios. First, we assume that the encoder and the decoder cooperate in order to achieve a certain pair of distortion values. Second, we suppose that t

Artem Kramov, Olexandr Bauzha

An implementation of the remote pulse monitoring system which allows observing of the patient's pulse in a real-time mode via browser is offered in this work. The result of the work is the development of the complex system, which contains the hardware components for the pulse measurement and the software component for the data processing and visualization in

L. Bonne, S. Bontemps, N. Schneider, S. D. Clarke

Context. Dense molecular filaments are ubiquituous in the interstellar medium, yet their internal physical conditions and formation mechanism remain debated. Aims. We study the kinematics and physical conditions in the Musca filament and the Chamaeleon-Musca complex to constrain the physics of filament formation. Methods. We produced CO(2-1) isotopologue map

Masahiro Kato, Yusuke Kaneko

The goal of off-policy evaluation (OPE) is to evaluate a new policy using historical data obtained via a behavior policy. However, because the contextual bandit algorithm updates the policy based on past observations, the samples are not independent and identically distributed (i.i.d.). This paper tackles this problem by constructing an estimator from a mart

Marcin Copik, Tobias Grosser, Torsten Hoefler, Paolo Bientinesi

Parallelism patterns (e.g., map or reduce) have proven to be effective tools for parallelizing high-performance applications. In this paper, we study the recursive registration of a series of electron microscopy images - a time consuming and imbalanced computation necessary for nano-scale microscopy analysis. We show that by translating the image registratio

Kyle Beloy, Vladimir A. Dzuba, Samuel M. Brewer

We identify Ba$^{4+}$ (Te-like) as a promising candidate for a high-accuracy optical clock. The lowest-lying electronic states are part of a $^3P_J$ fine structure manifold with anomalous energy ordering, being non-monotonic in $J$. We propose a clock based on the 338.8 THz electric quadrupole transition between the ground ($^3P_2$) and first-excited ($^3P_0

Adam S. Caldwell, Grigorios Itskos, Kenneth H. Sandhage

A dramatic reduction in man-made CO2 emissions could be achieved if the cost of electricity generated from concentrated solar power (CSP) plants could become competitive with fossil-fuel-derived electricity. The solar heat-to-electricity conversion efficiency of CSP plants may be significantly increased (and the associated electricity cost decreased) by oper

Andreas Aste

The concept of spontaneous symmetry breaking (SSB) generally lacks a simple and intuitive introduction in the literature. This gap is filled by defining SSB in a universal context beyond its usual applications in physics and by discussing some very simple, but stunning examples of the phenomenon.

Soraia Pereira, Raquel Menezes, Maria Manuel Angélico, Tiago Marques

Understanding the spatial distribution of animals, during all their life phases, as well as how the distributions are influenced by environmental covariates, is a fundamental requirement for the effective management of animal populations. Several geostatistical models have been proposed in the literature, however often the data structure presents an excess o

Henning Wachsmuth, Till Werner

Several quality dimensions of natural language arguments have been investigated. Some are likely to be reflected in linguistic features (e.g., an argument's arrangement), whereas others depend on context (e.g., relevance) or topic knowledge (e.g., acceptability). In this paper, we study the intrinsic computational assessment of 15 dimensions, i.e., only lear

Tommaso Caselli, Valerio Basile, Jelena Mitrović, Michael Granitzer

In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in English. The model was trained on RAL-E, a large-scale dataset of Reddit comments in English from communities banned for being offensive, abusive, or hateful that we have collected and made available to the public. We present the results of a detailed comparison b

Bangyao Zhao, Lili Zhao

Vaccine safety is a concerning problem of the public, and many signal detecting methods have been developed to identify relative risks between vaccines and adverse events (AEs). Those methods usually focus on individual AEs, where the randomness of data is high. The results often turn out to be inaccurate and lack of clinical meaning. The AE ontology contain

Anders Ryd, Louise Skinnari

Hardware-based track reconstruction in the CMS and ATLAS trigger systems for the High-Luminosity LHC upgrade will provide unique capabilities. An overview is presented of earlier track trigger systems at hadron colliders, in particular for the Tevatron CDF and D0 experiments. We discuss the plans of the CMS and ATLAS experiments to implement hardware-based t

Andrea Tesei, Domenico Lattuca, Paolo Pagano, Marco Luise

Among the available communication systems, vehicular networks are emerging as one of the most promising and yet most challenging instantiations of mobile ad-hoc network technologies. The deployment of such networks in large scale requires the enforcement of stringent security mechanisms that need to abide by the technical, societal, legal, and economical req

Masahiro Kato, Kenshi Abe, Kaito Ariu, Shota Yasui

Off-policy evaluation (OPE) is the problem of estimating the value of a target policy from samples obtained via different policies. Recently, applying OPE methods for bandit problems has garnered attention. For the theoretical guarantees of an estimator of the policy value, the OPE methods require various conditions on the target policy and policy used for g

Chun-Lu Huang

Heavy-flavour hadrons, containing open or hidden charm and beauty flavours, are considered as hard probes of the quark-gluon plasma (QGP), which is a hot and dense phase state of quantum chromodynamics (QCD) matter. Production of heavy flavours involves large momentum transfer processes during collisions. Heavy quarks are expected to be produced in the initi

Jenthe Thienpondt, Brecht Desplanques, Kris Demuynck

In this technical report we describe the IDLAB top-scoring submissions for the VoxCeleb Speaker Recognition Challenge 2020 (VoxSRC-20) in the supervised and unsupervised speaker verification tracks. For the supervised verification tracks we trained 6 state-of-the-art ECAPA-TDNN systems and 4 Resnet34 based systems with architectural variations. On all models

Hidetoshi Miyazaki, Tomoyuki Tamura, Masashi Mikami, Kosuke Watanabe

The half-Heusler compound has drawn attention in a variety of fields as a candidate material for thermoelectric energy conversion and spintronics technology. This is because it has various electronic structures, such as semi-metals, semiconductors, and a topological insulator. When the half-Heusler compound is incorporated into the device, the control of hig

Maud Galametz, Anaelle Maury, Josep M. Girart, Ramprasad Rao

To assess the potential role of magnetic fields in regulating the envelope rotation and the fragmentation of Class 0 protostars, we carried out observations of the dust polarized emission at 0.87 mm with the SMA, in the envelopes of a large sample of 20 Class 0 protostars. We estimate the mean magnetic field orientation over the central 1000 au envelope scal

Pooja Arya, Maren Umlandt, Joachim Jelken, David Feldmann

We consider sedimented at a solid wall particles that are immersed in water containing small additives of photosensitive ionic surfactants. It is shown that illumination with an appropriate wavelength, a beam intensity profile, shape and size could lead to a variety of dynamic, both unsteady and steady-state, configurations of particles. These dynamic, well-

Alex Mansbridge, Gregory Barbour, Davide Piras, Michael Murray

The collection of individuals' data has become commonplace in many industries. Local differential privacy (LDP) offers a rigorous approach to preserving privacy whereby the individual privatises their data locally, allowing only their perturbed datum to leave their possession. LDP thus provides a provable privacy guarantee to the individual against both adve

Serafino Cicerone, Gabriele Di Stefano, Alfredo Navarra

Following the wide investigation in distributed computing issues by mobile entities of the last two decades, we consider the need of a structured methodology to tackle the arisen problems. The aim is to simplify both the design of the resolution algorithms and the writing of the required correctness proofs. We would encourage the usage of a common framework

T. H. A. van der Reep, B. Looman, H. W. Chan, C. W. Hagen

We measure the transmission secondary electron yield of nanometer-thick Al$_2$O$_3$/TiN/Al$_2$O$_3$ films using a prototype version of a Timed Photon Counter (TiPC). We discuss the method to measure the yield extensively. The yield is then measured as a function of landing energy between $1.2$ and $1.8$ keV and found to be in the range of $0.1$ ($1.2$ keV) t

Harald Bayerlein, Mirco Theile, Marco Caccamo, David Gesbert

Harvesting data from distributed Internet of Things (IoT) devices with multiple autonomous unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning methods. We propose a multi-agent reinforcement learning (MARL) approach that, in contrast to previous work, can adapt to profound changes in the scenario parameters defining the

Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh

Many communication-efficient variants of SGD use gradient quantization schemes. These schemes are often heuristic and fixed over the course of training. We empirically observe that the statistics of gradients of deep models change during the training. Motivated by this observation, we introduce two adaptive quantization schemes, ALQ and AMQ. In both schemes,

Diego Blas, Jorge Martin Camalich, Jose Antonio Oller

A method to unitarize the scattering amplitude produced by infinite-range forces is developed and applied to Born terms. In order to apply $S$-matrix techniques, based on unitarity and analyticity, we first derive an $S$-matrix free of infrared divergences. This is achieved by removing a divergent phase factor due to the interactions mediated by the massless

Uiara Celine de Moura, Francesco Da Ros, Ann Margareth Rosa Brusin, Andrea Carena

Optical communication systems are always evolving to support the need for ever-increasing transmission rates. This demand is supported by the growth in complexity of communication systems which are moving towards ultra-wideband transmission and space-division multiplexing. Both directions will challenge the design, modeling, and optimization of devices, subs

Agne Ciuciulkaite, Oliver Gueckstock, Anna Ravensburg, Merlin Pohlit

We investigate the THz emission characteristics of ferromagnetic/non-magnetic metallic heterostructures, focusing on thin Fe/Pt bilayers. In particular, we report on the impact of optimized crystal growth of the epitaxial Fe layers on the THz emission amplitude and spectral bandwidth. We demonstrate an enhancement of the emitted intensity along with an expan

Catie McEntee, Ning Lu, David Lubkeman

This paper presents a regression-based method for estimating voltages and voltage sensitivities for volt-var control on distribution circuits with limited data. The estimator uses power flow results for representative load and PV output scenarios as training data. Using linear regressions on power flow results, the voltages at critical nodes are calculated o