December 2020 arXiv papers — page 58

Sheetal Swain, Rakesh Mohanty, Debasis Dwibedy

Shortest Remaining Processing Time (SRPT) is a well known preemptive scheduling algorithm for uniprocessor and multiprocessor systems. SRPT finds applications in the emerging areas such as scheduling of client's requests that are submitted to a web server for accessing static web pages, managing the access requests to files in multiuser database systems and

R. Rampazzo, P. Mazzei, A. Marino, L. Bianchi

Dorado is a nearby (17.69 Mpc) strongly evolving galaxy group in the Southern Hemisphere. We are investigating the star formation in this group. This paper provides a FUV imaging of NGC 1533, IC 2038 and IC 2039, which form a substructure, south west of the Dorado group barycentre. FUV CaF2-1 UVIT-Astrosat images enrich our knowledge of the system provided b

Cheng Li, Andrew Ingersoll, Scott Bolton, Steven Levin

Oxygen is the most common element after hydrogen and helium in Jupiter's atmosphere, and may have been the primary condensable (as water ice) in the protoplanetary disk. Prior to the Juno mission, in situ measurements of Jupiter's water abundance were obtained from the Galileo Probe, which dropped into a meteorologically anomalous site. The findings of the G

Matthias Kirchhart, Donat Weniger

We present simplified formulae for the analytic integration of the Newton potential of polynomials over boxes in two- and three-dimensional space. These are implemented in an easy-to-use C++ library that allows computations in arbitrary precision arithmetic which is also documented here. We describe how these results can be combined with fast multipole metho

Holger Heitsch, René Henrion

The spherical cap discrepancy is a widely used measure for how uniformly a sample of points on the sphere is distributed. Being hard to compute, this discrepancy measure is typically replaced by some lower or upper estimates when designing optimal sampling schemes for the uniform distribution on the sphere. In this paper, we provide a fully explicit, easy to

Lakshmi Priya

We study nodal component count of the following Gaussian Laplace eigenfunctions: monochromatic random waves (MRW) on $\mathbb{R}^2$, arithmetic random waves (ARW) on $\mathbb{T}^2$ and random spherical harmonics (RSH) on $\mathbb{S}^2$. Exponential concentration for nodal component count of RSH on $\mathbb{S}^2$ and ARW on $\mathbb{T}^2$ were established by

Masha Medvedeva, Martijn Wieling, Michel Vols

In this paper we discuss the implications of using machine learning for judicial decision-making in situations where human rights may be infringed. We argue that the use of such tools in these situations should be limited due to inherent status quo bias and dangers of reverse-engineering. We discuss that these issues already exist in the judicial systems wit

Matthias Templ

Methods of deep learning have become increasingly popular in recent years, but they have not arrived in compositional data analysis. Imputation methods for compositional data are typically applied on additive, centered or isometric log-ratio representations of the data. Generally, methods for compositional data analysis can only be applied to observed positi

Huu-Quang Nguyen, Ruey-Lin Sheu

We study a special class of non-convex quadratic programs subject to two (possibly indefinite) quadratic constraints when the level sets of the constraint functions are {\it not} arranged {\it alternatively.} It is shown in the paper that this class of problems admit strong duality following a tight SDP relaxation, without assuming primal or dual Slater cond

S. Amoroso, J. Fiaschi, F. Giuli, A. Glazov

Charged lepton pairs are produced copiously in high-energy hadron collisions via electroweak gauge boson exchange, and are one of the most precisely measured final states in proton-proton collisions at the Large Hadron Collider (LHC). We propose that measurements of lepton angular distributions can be used to improve the accuracy of theoretical predictions f

J. A. Saenz, T. D. Ringler

We present a prognostic, one-equation model for eddy-mean flow interactions to parameterize the divergence of the Eliassen-Palm flux tensor (EPFT) that arises from thickness-weighted averaging (TWA) the hydrostatic Boussinesq equations. The TWA system of equations does not invoke approximations beyond those for which the hydrostatic Boussinesq equations are

Lam Huynh, Phong Nguyen-Ha, Jiri Matas, Esa Rahtu

In this paper, we propose enhancing monocular depth estimation by adding 3D points as depth guidance. Unlike existing depth completion methods, our approach performs well on extremely sparse and unevenly distributed point clouds, which makes it agnostic to the source of the 3D points. We achieve this by introducing a novel multi-scale 3D point fusion network

Petr Danecek, James K. Bonfield, Jennifer Liddle, John Marshall

Background SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. Findings The first version appeared online twelve years ago and has been maintained and further developed ever since, with many new features and improvements added over the years. The SAMtools and BCFtools packages represent a unique collec

Martin Dyrba, Moritz Hanzig, Slawek Altenstein, Sebastian Bader

Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN r

Atharva Karnik, Diksha Adke, Pushkar Sathe

The system explained in this paper provides a compact smart surveillance system. Recent years have seen the Internet of Things (IoT) dominating in various fields of applications. With devices getting smarter and insurgence of 5G technology, the connectivity of people with devices is increasing. Smarter surveillance systems are more reliable and accessible. A

Anton Freund

Timothy Carlson's patterns of resemblance employ the notion of $\Sigma_1$-elementarity to describe large computable ordinals. It has been conjectured that a relativization of these patterns to dilators leads to an equivalence with $\Pi^1_1$-comprehension (Question 27 of A. Montalb\'an's "Open questions in reverse mathematics", Bull. Symb. Log. 17(3)2011, 431

S. R. Patel, D. Bose, N. Gupta, M. Zuberi

Blazars, a class of highly variable active galactic nuclei, sometimes exhibit Orphan $\gamma$-ray flares. These flares having high flux only in $\gamma$-ray energies do not show significant variations in flux at lower energies. We study the temporal and spectral profile of these Orphan $\gamma$-ray flares in detail from three $\gamma-ray$ bright blazars, 3C

Eric Ahlqvist

We define stacky building data for stacky covers in the spirit of Pardini and give an equivalence of (2,1)-categories between the category of stacky covers and the category of stacky building data. We show that every stacky cover is a flat root stack in the sense of Olsson and Borne--Vistoli and give an intrinsic description of it as a root stack using stack

Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann

Hate speech is a challenging issue plaguing the online social media. While better models for hate speech detection are continuously being developed, there is little research on the bias and interpretability aspects of hate speech. In this paper, we introduce HateXplain, the first benchmark hate speech dataset covering multiple aspects of the issue. Each post

Lorenzo Gavassino, Marco Antonelli, Brynmor Haskell

We present a geometrical derivation of the relativistic dynamics of the superfluid inner crust of a neutron star. The resulting model is analogous to the Hall-Vinen-Bekarevich-Khalatnikov hydrodynamics for a single-component superfluid at finite temperature, but particular attention should be paid to the fact that some fraction of the neutrons are locked to

Leonid Zelenko

In a real Hilbert spaces H a smooth operator F is studied, whose derivative at each point of its domain is a symmetric operator. In terms of abstract boundary conditions locally self-adjoint extensions of this operator are described. We use some concepts and facts from symplectic differential geometry.

Yoshihiko Abe, Takashi Toma, Koichi Yoshioka

A pseudo Nambu-Goldstone boson (pNGB) is a natural candidate of dark matter in that it avoids the severe direct detection bounds. We show in this paper that the pNGB has another different and interesting face with a higher symmetry breaking scale. Such large symmetry breaking is motivated by various physics beyond the standard model. In this case, the pNGB i

Thomas Winterbottom, Sarah Xiao, Alistair McLean, Noura Al Moubayed

Bilinear pooling (BLP) refers to a family of operations recently developed for fusing features from different modalities predominantly developed for VQA models. A bilinear (outer-product) expansion is thought to encourage models to learn interactions between two feature spaces and has experimentally outperformed `simpler' vector operations (concatenation and

Florio M. Ciaglia, Fabio Di Cosmo, Alberto Ibort, Giuseppe Marmo

Schr\"{o}dinger's famous Gedankenexperiment involving a cat is used as a motivation to discuss the evolution of states of the composition of classical and quantum systems in the groupoid formalism for physical theories introduced recently. It is shown that the notion of classical system, in the sense of Birkhoff and von Neumann, is equivalent, in the case of

Feiyan Hu, Eva Mohedano, Noel O'Connor, Kevin McGuinness

Current deep learning based video classification architectures are typically trained end-to-end on large volumes of data and require extensive computational resources. This paper aims to exploit audio-visual information in video classification with a 1 frame per second sampling rate. We propose Temporal Bilinear Encoding Networks (TBEN) for encoding both aud

Juhi Khalid, Martin Bouchard

Using elementary linear algebra, this paper clarifies and proves some concepts about a recently introduced octonion-like associative division algebra over R. This octonion-like algebra is actually the same as the split-biquaternion algebra, an even subalgebra of Clifford algebra Cl(4,0). For two seminorms described in the paper, it is shown that the octonion

Jinyin Chen, Zhen Wang, Haibin Zheng, Jun Xiao

With the successful application of deep learning models in many real-world tasks, the model robustness becomes more and more critical. Often, we evaluate the robustness of the deep models by attacking them with purposely generated adversarial samples, which is computationally costly and dependent on the specific attackers and the model types. This work propo

Amir Abboud, Robert Krauthgamer, Ohad Trabelsi

Every undirected graph $G$ has a (weighted) cut-equivalent tree $T$, commonly named after Gomory and Hu who discovered it in 1961. Both $T$ and $G$ have the same node set, and for every node pair $s,t$, the minimum $(s,t)$-cut in $T$ is also an exact minimum $(s,t)$-cut in $G$. We give the first subcubic-time algorithm that constructs such a tree for a simpl

Yuup van Engelshoven, Stefanie Roos

Payment channels networks drastically increase the throughput and hence scalability of blockchains by performing transactions \emph{off-chain}. In an off-chain payment, parties deposit coins in a channel and then perform transactions without invoking the global consensus mechanism of the blockchain. However, the transaction value is limited by the capacity o

Emmanuel Fricain, Andreas Hartmann, William T. Ross, Dan Timotin

Using an explicit construction, we show that the de Branges-Rovnyak spaces $\mathscr{H}(b)$, corresponding to rational $b$, are contained in their associated Smirnov classes.

Yue Xing, Ruizhi Zhang, Guang Cheng

Adversarially robust learning aims to design algorithms that are robust to small adversarial perturbations on input variables. Beyond the existing studies on the predictive performance to adversarial samples, our goal is to understand statistical properties of adversarially robust estimates and analyze adversarial risk in the setup of linear regression model

Moritz S. Fischer, Marcus Brüggen, Kai Schmidt-Hoberg, Klaus Dolag

Self-interacting dark matter (SIDM) models have the potential to solve the small-scale problems that arise in the cold dark matter paradigm. Simulations are a powerful tool for studying SIDM in the context of astrophysics, but it is numerically challenging to study differential cross-sections that favour small-angle scattering, as in light-mediator models. H

Andrés Sambarino

We classify the (semi-simple parts of the) Lie algebra of the Zariski closure of a discrete subgroup of a split simple real-algebraic Lie group, whose limit sets are minimal and such that the limit set in the space of full flags contains a positive triple of flags (as in Lusztig). We then apply our result to obtain a new proof of Guichard's classification of

Pham Quang Nhat Minh

In this paper, we present an empirical study of using pre-trained BERT models for the relation extraction task at the VLSP 2020 Evaluation Campaign. We applied two state-of-the-art BERT-based models: R-BERT and BERT model with entity starts. For each model, we compared two pre-trained BERT models: FPTAI/vibert and NlpHUST/vibert4news. We found that NlpHUST/v

Habib Ammari, Erik Orvehed Hiltunen

In the field of metamaterials, many intriguing phenomena arise from having a structure which is periodic in space. In time-dependent structures, conceptually similar properties can arise, which nevertheless have fundamentally different physical implications. In this work, we study time-dependent systems in the context of subwavelength metamaterials. The main

V. Lherm, R. Deguen, T. Alboussière, M. Landeau

When a liquid drop strikes a deep pool of a second liquid, an impact crater opens while the liquid of the drop decelerates and spreads on the surface of the crater. If the density of the drop is larger than the surrounding, the interface between the drop liquid layer and its surrounding becomes unstable, producing mushroom-shaped plumes growing radially outw

A. Azarevich, A. Bogach, V. Glushkov, S. Demishev

We have studied the normal and superconductive state characteristics (resistivity, Hall coefficient, heat capacity and magnetization) of model strongly correlated electronic systems LuxZr1-xB12 with cooperative Jahn-Teller instability of the boron rigid cage and with dynamic charge stripes. It was found that these metals are s-wave dirty limit superconductor

Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos, Hans Vandierendonck

Knowledge acquisition is the essential first step of any Knowledge Graph (KG) application. This knowledge can be extracted from a given corpus (KG generation process) or specified from an existing KG (KG specification process). Focusing on domain specific solutions, knowledge acquisition is a labor intensive task usually orchestrated and supervised by subjec

Liang Ma

Expert networks are formed by a group of expert-professionals with different specialties to collaboratively resolve specific queries posted to the network. In such networks, when a query reaches an expert who does not have sufficient expertise, this query needs to be routed to other experts for further processing until it is completely solved; therefore, que

Julien Chauchat, David Hurther, Thibaud Revil-Baudard, Zhen Cheng

One of the most enigmatic science question concerning inertial particle transport by a turbulent boundary layer flow is the value of the turbulent Schmidt number as the ratio of particle diffusivity and turbulent eddy viscosity. Using direct acoustic measurement of turbulent particle flux profile, and two-phase flow turbulence-resolving numerical simulation,

Adrien Devolder, Paul Brumer, Timur V. Tscherbul

We show that quantum interference-based coherent control is a highly efficient tool for tuning ultracold molecular collision dynamics, and is free from the limitations of commonly used methods that rely on external electromagnetic fields. By varying {the relative populations and} phases of an initial coherent superpositions of degenerate molecular states, we

Daniel Koch, Michael Samodurov, Andrew Projansky, Paul M. Alsing

Quantum Random Walks, which have drawn much attention over the past few decades for their distinctly non-classical behavior, is a promising subfield within Quantum Computing. Theoretical framework and applications for these walks have seen many great mathematical advances, with experimental demonstrations now catching up. In this study, we examine the viabil

Nguyen Manh Duc Tuan, Pham Quang Nhat Minh

In this paper, we present our methods for unrealiable information identification task at VLSP 2020 ReINTEL Challenge. The task is to classify a piece of information into reliable or unreliable category. We propose a novel multimodal ensemble model which combines two multimodal models to solve the task. In each multimodal model, we combined feature representa

Jakub Cimerman, Iurii Karpenko, Boris Tomášik, Barbara Antonina Trzeciak

Description of relativistic heavy-ion collisions at the energies of RHIC Beam Energy Scan program with fluid dynamic approach poses several challenges, one of which being a complex geometry and a longer duration of the pre-hydrodynamic stage. Therefore, existing fluid dynamic models for heavy-ion collisions at the RHIC Beam Energy Scan energies rely on rathe

Gor A. Sarkissian, Vyacheslav P. Spiridonov

A special singular limit $\omega_1/\omega_2\to 1$ is considered for the Faddeev modular quantum dilogarithm (hyperbolic gamma function) and the corresponding hyperbolic integrals. It brings a new class of hypergeometric identities associated with bilateral sums of Mellin-Barnes type integrals of particular Pochhammer symbol products.

Johanna Vielhaben, Nils Strodthoff

Generative neural samplers offer a complementary approach to Monte Carlo methods for problems in statistical physics and quantum field theory. This work tests the ability of generative neural samplers to estimate observables for real-world low-dimensional spin systems. It maps out how autoregressive models can sample configurations of a quantum Heisenberg ch

Pierre L'Ecuyer, Pierre Marion, Maxime Godin, Florian Puchhammer

We present LatNet Builder, a software tool to find good parameters for lattice rules, polynomial lattice rules, and digital nets in base 2, for quasi-Monte Carlo (QMC) and randomized quasi-Monte Carlo (RQMC) sampling over the $s$-dimensional unit hypercube. The selection criteria are figures of merit that give different weights to different subsets of coordi

Ilija I. Zovko

We show that filling an order with a large number of distinct counterparts incurs additional market impact, as opposed to filling the order with a small number of counterparts. For best execution, therefore, it may be beneficial to opportunistically fill orders with as few counterparts as possible in Large-in-scale (LIS) venues. This article introduces the c

Mrdjan Jankovic, Mario Santillo

In this paper we consider multi-agent navigation with collision avoidance using Control Barrier Functions (CBF). In the case of non-communicating agents, we consider trade-offs between level of safety guarantee and liveness - the ability to reach destination in short time without large detours or gridlock. We compare several CBF-based driving policies agains

Giacomo Acciarini, Francesco Pinto, Sascha Metz, Sarah Boufelja

Over 34,000 objects bigger than 10 cm in length are known to orbit Earth. Among them, only a small percentage are active satellites, while the rest of the population is made of dead satellites, rocket bodies, and debris that pose a collision threat to operational spacecraft. Furthermore, the predicted growth of the space sector and the planned launch of mega

S. X. Hu, R. Paul, V. V. Karasiev, R. P. Dias

To understand the most-recent experiment on room-temperature superconductivity in carbonaceous sulfur hydride (CSH) systems under high pressure, we have performed extensive stoichiometry and structure searches of ternary CSH compounds using generic evolutionary algorithms. Judged from the formation enthalpy of different CSH compounds, our studies conclude th

Axel Nilsson, Xavier Bresson

Spectral graph convolutional networks are generalizations of standard convolutional networks for graph-structured data using the Laplacian operator. A common misconception is the instability of spectral filters, i.e. the impossibility to transfer spectral filters between graphs of variable size and topology. This misbelief has limited the development of spec

Aleksander Ćwiszewski, Grzegorz Gabor, Wojciech Kryszewski

Sufficient conditions for the invariance of evolution problems governed by perturbations of (possibly nonlinear) $m$-accretive operators are provided. The conditions for the invariance with respect to sublevel sets of a constraint functional are expressed in terms of the Dini derivative of that functional, outside the considered sublevel set in directions de

Rui Yang, Joschua Hellemeier, Paul Hickson

This paper reviews atoms and ions in the upper atmosphere, including the mesospheric metals Na, Fe, Mg$^+$, Si$^+$, Ca$^+$, K and also non-metallic species N, N$^+$, O, H, considering their potential for astronomical adaptive optics. Na and Fe are the best candidates for the creation of polychromatic laser guide stars, with the strongest returns coming from

Mikhail Danilov

We present new preliminary DANSS results based on 3.5 million Inverse Beta Decay (IBD) events collected at 3 distances (10.9 m, 11.9 m, and 12.9 m) from the detector center to the reactor core center. The detector position is changed typically 3 times a week. Therefore many systematic uncertainties are canceled out. A new analysis that uses information about

H. E. S. S. Collaboration, H. Abdalla, R. Adam, F. Aharonian

The flat spectrum radio quasar (FSRQ) PKS 1510-089 is known for its complex multiwavelength behavior, and is one of only a few FSRQs detected at very high energy (VHE, $E>100\,$GeV) $\gamma$-rays. VHE $\gamma$-ray observations with H.E.S.S. and MAGIC during late May and early June 2016 resulted in the detection of an unprecedented flare, which reveals for th

E. Karaarslan, E. Konacaklı

We have entered an era where the importance of decentralized solutions has become more obvious. Blockchain technology and its derivatives are distributed ledger technologies that keep the registry of data between peers of a network. This ledger is secured within a successive over looping cryptographic chain. The accomplishment of the Bitcoin cryptocurrency p

Saja AL-Tawalbeh, Mohammad AL-Smadi

Language comprehension and commonsense knowledge validation by machines are challenging tasks that are still under researched and evaluated for Arabic text. In this paper, we present a benchmark Arabic dataset for commonsense explanation. The dataset consists of Arabic sentences that does not make sense along with three choices to select among them the one t

Shahram Aghaei, Abolghasem Daeichian, Vicenç Puig

This paper proposes a hierarchical decentralized reference governor for constrained cascade systems. The reference governor (RG) approach is reformulated in terms of receding horizon strategy such that a locally receding horizon optimization is obtained for each subsystem with a pre-established prediction horizon. The algorithm guarantees that not only the n

Carlos Llosa-Vite, Ranjan Maitra

Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend the classical multivariate regression model to exploit such structure in two ways: first, we impose four types of low-rank tensor formats on the regression coefficients. Second, we

Piero Truini, Alessio Marrani, Michael Rios, Klee Irwin

In our investigation on quantum gravity, we introduce an infinite dimensional complex Lie algebra $\textbf{${\mathfrak g}_{\mathsf u}$}$ that extends $\mathbf{e_9}$. It is defined through a symmetric Cartan matrix of a rank 12 Borcherds algebra. We turn $\textbf{${\mathfrak g}_{\mathsf u}$}$ into a Lie superalgebra $\textbf{$\mathfrak {sg}_{\mathsf u}$}$ wit

Antonin Billaud, David Allioux, Nicolas Laurenchet, Pu Jian

In this work, we study the effect of beam deviation angle at the reception side and calculate the theoretical demultiplexed collected energy for up to 15 modes, investigating the influence of the ratio between incoming beam size and fundamental HG mode's waist. We show this approach greatly enhances the collection efficiency, tolerating tip-tilt error of mor

Tom T. B. Wester, Johannes Krauss, Lars Neuhaus, Agnieszka Hölling

Wind turbines operate under constantly changing turbulent inflow conditions. In the rotating system, wind gusts lead to variations in the angle of attack at local blade segments resulting in dynamic effects such as dynamic stall. Such highly non-linear effects are known to produce a significant overshoot in the lift and thus an increase in loads acting on th

C. A. Cremonini, P. A. Grassi

Recent results of A. Sen on quantum field theory models with self-dual field strengths use string field theory as a starting point. In the present work, we show that combining string field theory and supergeometry we can provide a constructive method for all these models, for any superspace representation and for any given background. The analysis is based o

Noboru Ito

In this paper, we give a definition of $\mathbb{Z}$-valued functions from the ambient isotopy classes of spherical/plane curves derived from chord diagrams, denoted by $\sum_i \alpha_i x_i$. Then, we introduce certain elements of the free $\mathbb{Z}$-module generated by the chord diagrams with at most $l$ chords, called relators of Type (I) ((SII), (WII), (

Guangqian Jiao, Shoubao Zhu, Jizhou He, Yongli Ma

We derive cooling rate and coefficient of performance as well as their variances for a quantum Otto engine proceeding in finite-time cycle period. This machine consists of two driven strokes, where the system isolated from the heat reservoir undergoes finite-time unitary transformation, and two isochoric steps, where the finite-time system-bath interaction d

Archak Purkayastha, Giacomo Guarnieri, Steve Campbell, Javier Prior

Obtaining dynamics of an interacting quantum many-body system connected to multiple baths initially at different, finite, temperatures and chemical potentials is a challenging problem. This is due to a combination of the prevalence of strong correlations in the system, the infinite nature of the baths and the long time to reach steady state. In this work we

Zhihong Shao, Zitao Liu, Jiyong Zhang, Zhongqin Wu

Adversarial examples are vital to expose the vulnerability of machine learning models. Despite the success of the most popular substitution-based methods which substitutes some characters or words in the original examples, only substitution is insufficient to uncover all robustness issues of models. In this paper, we present AdvExpander, a method that crafts

Choukri Derbazi, Zidane Baitiche

The principal aim of the present paper is to establish the uniqueness and Ulam-Hyers Mittag-Leffler (UHML) stability of solutions for a new class of multi-terms fractional time-delay differential equations in the context of the $\Phi$-Caputo fractional derivative. To achieve this purpose, the generalized Laplace transform method alongside facet with properti

Yulan Gao, Chao Yong, Zehui Xiong, Dusit Niyato

This paper investigates an intelligent reflecting surface (IRS) aided cooperative communication network, where the IRS exploits large reflecting elements to proactively steer the incident radio-frequency wave towards destination terminals (DTs). As the number of reflecting elements increases, the reflection resource allocation (RRA) will become urgently need

Pei-Pin Yang, Mai-Ying Duan, Fu-Hu Liu

We collected the experimental data of transverse momentum spectra of identified particles produced in proton-proton ($p$-$p$), deuteron-gold ($d$-Au or $d$-$A$), gold-gold (Au-Au or $A$-$A$), proton-lead ($p$-Pb or $p$-$A$), and lead-lead (Pb-Pb or $A$-$A$) collisions measured by the ALICE, CMS, LHCb, NA49, NA61/SHINE, PHENIX, and STAR collaborations at diff

Piero Truini, Alessio Marrani, Michael Rios, Klee Irwin

We introduce a quantum model for the Universe at its early stages, formulating a mechanism for the expansion of space and matter from a quantum initial condition, with particle interactions and creation driven by algebraic extensions of the Kac-Moody Lie algebra $\mathbf{e_9}$. We investigate Kac-Moody and Borcherds algebras, and we propose a generalization

Omkar Gurjar, Manish Gupta

Although several automatic itinerary generation services have made travel planning easy, often times travellers find themselves in unique situations where they cannot make the best out of their trip. Visitors differ in terms of many factors such as suffering from a disability, being of a particular dietary preference, travelling with a toddler, etc. While mo

E. Vahapoglu, J. P. Slack-Smith, R. C. C. Leon, W. H. Lim

Spin-based silicon quantum electronic circuits offer a scalable platform for quantum computation, combining the manufacturability of semiconductor devices with the long coherence times afforded by spins in silicon. Advancing from current few-qubit devices to silicon quantum processors with upwards of a million qubits, as required for fault-tolerant operation

Yuan Miao, Jules Lamers, Vincent Pasquier

The spin-1/2 Heisenberg XXZ chain is a paradigmatic quantum integrable model. Although it can be solved exactly via Bethe ansatz techniques, there are still open issues regarding the spectrum at root of unity values of the anisotropy. We construct Baxter's Q operator at arbitrary anisotropy from a two-parameter transfer matrix associated to a complex-spin au

Yogesh Kumar, Rabia Sultana, V. P. S. Awana

Here, we report the magneto-conductivity (up to 14Tesla and down to 5K) analysis of Bi2Te3 single-crystal. A sharp magneto-conductivity (MC) rise (inverted v-type cusp) is observed near H=0 due to the weak antilocalization (WAL) effect, while a linear curve is observed at higher fields. We account for magneto-conductivity (MC) over the entire range of applie

Giovanni Ferioli, Antoine Glicenstein, Loic Henriet, Igor Ferrier-Barbut

We report the observation of subradiance in dense ensembles of cold $^{87}$Rb atoms operating near Dicke's regime of a large number of atoms in a volume with dimensions smaller than the transition wavelength. We validate that the atom number is the only cooperativity parameter governing subradiance. We probe the dynamics in the many-body regime and support t

Erica Lastufka, Säm Krucker

Mercury mission MESSENGER's %(MErcury Surface, Space ENvironment, GEochemistry, and Ranging Solar Assembly for X-rays (SAX) observed almost 700 solar flares between May 28, 2007 and August 19, 2013, as cataloged by \citet{dennisSOLARFLAREELEMENT2015}. The SAX instrument, part of the X-ray Spectrometer (XRS), operated at 1 -- 10 keV, partially overlapping the

V. Reboud, D. Buca, H. Sigg, J. M. Hartmann

Silicon photonics in the near-Infra-Red, up to 1.6 um, is already one of key technologies in optical data communications, particularly short-range. It is also being prospected for applications in quantum computing, artificial intelligence, optical signal processing, where complex photonic integration is to be combined with large-volume fabrication. However,

Fidan Mehmeti, Thomas F. La Porta

Providing a high-quality real-time video streaming experience to mobile users is one of the biggest challenges in cellular networks. This is due to the need of these services for high rates with low variability, which is not easy to accomplish given the competition among (usually a high number of) users for constrained network resources and the high variabil

David Langlois, Karim Noui, Hugo Roussille

We present a novel and remarkably simple formulation of degenerate higher-order scalar-tensor (DHOST) theories whose Lagrangian is quadratic in second derivatives of some scalar field. Using disformal transformations of the metric, we identify a special "frame" (or metric) for which the Lagrangian of quadratic DHOST theories reduces to the usual Einstein-Hil

An Tao, Yueqi Duan, Yi Wei, Jiwen Lu

Most existing point cloud instance and semantic segmentation methods rely heavily on strong supervision signals, which require point-level labels for every point in the scene. However, such strong supervision suffers from large annotation costs, arousing the need to study efficient annotating. In this paper, we discover that the locations of instances matter

Anilesh K. Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng

Standard approaches to group-based notions of fairness, such as \emph{parity} and \emph{equalized odds}, try to equalize absolute measures of performance across known groups (based on race, gender, etc.). Consequently, a group that is inherently harder to classify may hold back the performance on other groups; and no guarantees can be provided for unforeseen

Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa

Investors try to predict returns of financial assets to make successful investment. Many quantitative analysts have used machine learning-based methods to find unknown profitable market rules from large amounts of market data. However, there are several challenges in financial markets hindering practical applications of machine learning-based models. First,

Philipp M. Mutter, Guido Burkard

Flopping mode qubits in double quantum dots (DQDs) allow for coherent spin-photon hybridization and fast qubit gates when coupled to either an alternating external or a quantized cavity electric field. To achieve this, however, electronic systems rely on synthetic spin-orbit interaction (SOI) by means of a magnetic field gradient as a coupling mechanism. Her

Quentin Vigneron

We perform a covariant 1+3 split of the Newton-Cartan equations. The resulting 3-dimensional system of equations, called \textit{the 1+3-Newton-Cartan equations}, is structurally equivalent to the 1+3-Einstein equations. In particular it features the momentum constraint, and a choice of adapted coordinates corresponds to a choice of shift vector. We show tha

Ana Silva, Jasper van Wezel

One of the hallmarks of topological insulators is the correspondence between the value of its bulk topological invariant and the number of topologically protected edge modes observed in a finite-sized sample. This bulk-boundary correspondence has been well-tested for strong topological invariants, and forms the basis for all proposed technological applicatio

Thomas Winterbottom, Sarah Xiao, Alistair McLean, Noura Al Moubayed

TVQA is a large scale video question answering (video-QA) dataset based on popular TV shows. The questions were specifically designed to require "both vision and language understanding to answer". In this work, we demonstrate an inherent bias in the dataset towards the textual subtitle modality. We infer said bias both directly and indirectly, notably findin

Hanlei Zhang, Hua Xu, Ting-En Lin

Open intent classification is a challenging task in dialogue systems. On the one hand, it should ensure the quality of known intent identification. On the other hand, it needs to detect the open (unknown) intent without prior knowledge. Current models are limited in finding the appropriate decision boundary to balance the performances of both known intents a

Julia Auernhammer, Tom Keil, Binbin Lin, Jan-Lukas Schäfer

Modelling of single cellulose fibres is usually performed by assuming homogenous properties, such as strength and Young s modulus, for the whole fibre. Additionally, the inhomogeneity in size and swelling behaviour along the fibre is often disregarded. For better numerical models, a more detailed characterization of the fibre is required. Herein, we report a

Michael Schröder, Jürgen Cito

The interactive command line, also known as the shell, is a prominent mechanism used extensively by a wide range of software professionals (engineers, system administrators, data scientists, etc.). Shell customizations can therefore provide insight into the tasks they repeatedly perform, how well the standard environment supports those tasks, and ways in whi

Daniel Andrén, Denis G. Baranov, Steven Jones, Giovanni Volpe

Nanostructured dielectric metasurfaces offer unprecedented opportunities to manipulate light by imprinting an arbitrary phase-gradient on an impinging wavefront. This has resulted in the realization of a range of flat analogs to classical optical components like lenses, waveplates and axicons. However, the change in linear and angular optical momentum associ

Kunmin Wu, Thomas L. Schmidt, M. Belén Farias

We study the phenomenon of quantum friction in a system consisting of a polarizable atom moving at a constant speed parallel to a metallic plate. The metal is described using a charged hydrodynamic model for the electrons. This model featuring long-range interactions is appropriate for a clean metal in a temperature range where scattering due to Coulomb inte

Anilesh K. Krishnaswamy, Haoming Li, David Rein, Hanrui Zhang

Machine learning techniques can be useful in applications such as credit approval and college admission. However, to be classified more favorably in such contexts, an agent may decide to strategically withhold some of her features, such as bad test scores. This is a missing data problem with a twist: which data is missing {\em depends on the chosen classifie

C. M. Ekpo, E. B. Ettah

In this paper, we solve analytically the Schrodinger equation for s-wave and arbitrary angular momenta with the Hua potential is investigated respectively. The wave function as well as energy equation are obtained in an exact analytical manner via the Nikiforov Uvarov method using two approximations scheme. Some special cases of this potentials are also stud

Mårten Schultzberg, Oskar Kjellin, Johan Rydberg

Randomized experiments is a key part of product development in the tech industry. It is often necessary to run programs of exclusive experiments, i.e., experiments that cannot be run on the same units during the same time. These programs implies restriction on the random sampling, as units that are currently in an experiment cannot be sampled into a new one.

Komla Domelevo, Spyridon Kakaroumpas, Stefanie Petermichl, Odí Soler i Gibert

We characterize dyadic little BMO via the boundedness of the tensor commutator with a single well chosen dyadic shift. It is shown that several proof strategies work for this problem, both in the unweighted case as well as with Bloom weights. Moreover, we address the flexibility of one of our methods.

Sultan Javed Majeed, Marcus Hutter

The reinforcement learning (RL) framework formalizes the notion of learning with interactions. Many real-world problems have large state-spaces and/or action-spaces such as in Go, StarCraft, protein folding, and robotics or are non-Markovian, which cause significant challenges to RL algorithms. In this work we address the large action-space problem by sequen

J. Gomes da Silva, N. C. Santos, V. Adibekyan, S. G. Sousa

We present a catalogue of homogeneous determined chromospheric emission (CE), stellar atmospheric parameters and ages for 1,674 FGK main sequence (MS), subgiant, and giant stars. The analysis of CE level and variability is also performed. We measured CE in the CaII lines using more than 180,000 high-resolution spectra from the HARPS spectrograph, as compiled

D. Liang, J. Hure, A. Courcelle, S. El Shawish

Irradiation Assisted Stress Corrosion Cracking (IASCC) is a material degradation phenomenon affecting austenitic stainless steels used in nuclear Pressurized Water Reactors (PWR), leading to the initiation and propagation of intergranular cracks. Such phenomenon belongs to the broader class of InterGranular Stress Corrosion Cracking (IGSCC). A micromechanica