December 2020 arXiv papers — page 85

Guido D'Amico, Yaniv Donath, Leonardo Senatore, Pierre Zhang

We apply the Effective Field Theory of Large-Scale Structure (EFTofLSS) to analyze cosmological models with clustering quintessence, which allows us to consistently describe the parameter region in which the quintessence equation of state $w < - 1$. First, we extend the description of biased tracers in redshift space to the presence of clustering quintessenc

Herman Kamper, Benjamin van Niekerk

We investigate segmenting and clustering speech into low-bitrate phone-like sequences without supervision. We specifically constrain pretrained self-supervised vector-quantized (VQ) neural networks so that blocks of contiguous feature vectors are assigned to the same code, thereby giving a variable-rate segmentation of the speech into discrete units. Two seg

Stephen Derenzo, Edith Bourret, Christiane Frank-Rotsch, Stephen Hanrahan

This paper is the first report describing how the concentrations of silicon and boron govern the cryogenic scintillation properties of n-type GaAs. It shows that valence band holes are promptly trapped on radiative centers and then combine radiatively with silicon donor band electrons at rates that increase with the density of free carriers. It also presents

Karla Stepanova, Jakub Rozlivek, Frantisek Puciow, Pavel Krsek

We present a robot kinematic calibration method that combines complementary calibration approaches: self-contact, planar constraints, and self-observation. We analyze the estimation of the end effector parameters, joint offsets of the manipulators, and calibration of the complete kinematic chain (DH parameters). The results are compared with ground truth mea

Qi-Bo Zeng, Rong Lü, Li You

We study topological superconductor in one-dimensional (1D) mosaic lattice whose on-site potentials are modulated for equally spaced sites. When the system is topologically nontrivial, Majorana zero modes appear at the two ends of the 1D lattice. By calculating energy spectra and topological invariant of the system, we find the interval of the mosaic modulat

Miklós Zétényi, Deniz Nitt, Michael Buballa, Tetyana Galatyuk

We present a study of the reaction $\pi^-p \to ne^+e^-$ for $\sqrt{s}=1.49\,\textrm{GeV}$, including non-resonant Born terms and contributions of the $N(1440)$, $N(1520)$, $N(1535)$ resonances ($R$), using an effective-Lagrangian model, which we extended by a phenomenological phase factor at the $RN\rho$ vertex function. We give predictions for both the diff

Konstantinos Yiannopoulos, Nikolaos C. Sagias, Anthony C. Boucouvalas

We present analytical results on the effect of pointing errors on the average bit-error probability (ABEP) of optically pre-amplified pulse-position modulation (PPM) receivers. The results show that the beam width plays a key role in the ABEP and that a significant power penalty is introduced by utilizing sub-optimal widths, especially when pointing errors i

Maxime Douarre, Vicente Martí-Centelles, Cybille Rossy, Arnaud Tron

Inherent movement of a macrocycle comprising a multi-site hydrogen bonding Hamilton-type receptor in a series of [2]rotaxanes was investigated by dynamic and VT NMR. In these rotaxanes the varying nature and number of hydrogen-bond motifs and stations on the molecular axles influenced ring dynamics. Triazole stations interact selectively by hydrogen bonding

Federico Zocco, Seán McLoone

Reducing dimensionality is a key preprocessing step in many data analysis applications to address the negative effects of the curse of dimensionality and collinearity on model performance and computational complexity, to denoise the data or to reduce storage requirements. Moreover, in many applications it is desirable to reduce the input dimensions by choosi

Yijie Mao, Bruno Clerckx

A Non-Orthogonal Unicast and Multicast (NOUM) transmission system allows a multicast stream intended to all receivers to be jointly transmitted with unicast streams in the same time-frequency resource blocks. While the capacity of the two-user multi-antenna NOUM with perfect Channel State Information at the Transmitter (CSIT) is known and achieved by Dirty P

Guangyao Zhai, Xin Kong, Jinhao Cui, Yong Liu

Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability. Although traditional filter-based methods can achieve better results, they are difficult to be endowed with optimal hyperparameters and often fail in varying scenarios. To alleviate these drawbacks, we propose a LiDAR-based 3D MOT framework

Mariam El Oussini

Cells segmentation shows rapid growth in biology. Indeed, using the classical segmentation methods only is not enough to segment this type of images. In this manuscript, we will present a new method of ribosomes segmentation. A pre-treatment phase will precedes the segmentation process and after that a post-processing will proceed.

Pragati Gupta, C. M. Chandrashekar

Digital quantum simulation on quantum systems require algorithms that can be implemented using finite quantum resources. Recent studies have demonstrated digital quantum simulation of open quantum systems on Noisy Intermediate-Scale Quantum (NISQ) devices. In this work, we develop quantum circuits for optimal simulation of Markovian and Non-Markovian open qu

Pinelopi Papalampidi, Frank Keller, Mirella Lapata

We summarize full-length movies by creating shorter videos containing their most informative scenes. We explore the hypothesis that a summary can be created by assembling scenes which are turning points (TPs), i.e., key events in a movie that describe its storyline. We propose a model that identifies TP scenes by building a sparse movie graph that represents

Yuan Yao, Akira Furusaki

We formulate a $\mathbb{Z}_k$-parafermionization/bosonization scheme for one-dimensional lattice models and field theories on a torus, starting from a generalized Jordan-Wigner transformation on a lattice, which extends the Majorana-Ising duality at $k=2$. The $\mathbb{Z}_k$-parafermionization enables us to investigate the critical theories of parafermionic

Yazhou Zhou, Jing Guo, Shu Cai, Genda Gu

Copper oxide superconductors have continually fascinated the communities of condensed matter physics and material sciences because they host the highest ambient-pressure superconducting transition temperature (Tc) and mysterious physics. Searching for the universal correlation between the superconducting state and its normal state or neighboring ground state

Tim Harris, Harvey B. Meyer, Arianna Toniato, Marco Cè

We provide an interpretation of the structure functions of a thermal medium such as the quark-gluon plasma in terms of the scattering of an incoming electron on the medium via the exchange of a spacelike photon. We then focus on the deep-inelastic scattering (DIS) regime, and formulate the corresponding moment sum rules obeyed by the structure functions. Acc

Phillip Lakaschus, Michael Buballa, Dirk H. Rischke

We study the phase structure of the two-flavor Nambu--Jona-Lasinio (NJL) model in the chiral limit, extending a previous study of the competition of an inhomogeneous chiral phase and a two-flavor color-superconducting (2SC) phase [1, 2]. There, an analytic expression for the dispersion relations for quasiparticle excitations in the presence of both a particu

Shouvik Roy Choudhury, Steen Hannestad, Thomas Tram

We have updated the constraints on flavour universal neutrino self-interactions mediated by a heavy scalar, in the effective 4-fermion interaction limit. We use the relaxation time approximation to modify the collisional neutrino Boltzmann equations, which is known to be very accurate for this particular scenario. Based on the latest CMB data from the Planck

Hélène Fleurbaey, Roberto Grilli, Didier Mondelain, Samir Kassi

The recent detections of electric-quadrupole (E2) transitions in water vapor and magnetic-dipole (M1) transitions in carbon dioxide have opened a new field in molecular spectroscopy. While in their present status, the spectroscopic databases provide only electric-dipole (E1) transitions for polyatomic molecules (H2O, CO2, N2O, CH4, O3), the possible impact o

Vladimir Naidenko

Descriptive complexity theory is an important area in the study of computational complexity. In this direction, it is possible to describe combinatorial problems exclusively by logical methods, without resorting to the use of complicated algorithms. The first work in this direction was written in 1974 by the American mathematician Fagin. The article describe

Raanan Y. Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik

We present a sound and complete algorithm for recovering causal graphs from observed, non-interventional data, in the possible presence of latent confounders and selection bias. We rely on the causal Markov and faithfulness assumptions and recover the equivalence class of the underlying causal graph by performing a series of conditional independence (CI) tes

Jianming Xia

In this paper we characterize the niveloidal preferences that satisfy the Weak Order, Monotonicity, Archimedean, and Weak C-Independence Axioms from the point of view of an intra-personal, leader-follower game. We also show that the leader's strategy space can serve as an ambiguity aversion index.

Dong Wang, Di Hu, Xingjian Li, Dejing Dou

Temporal relational modeling in video is essential for human action understanding, such as action recognition and action segmentation. Although Graph Convolution Networks (GCNs) have shown promising advantages in relation reasoning on many tasks, it is still a challenge to apply graph convolution networks on long video sequences effectively. The main reason

Qianli Zhou, Yong Deng

For a certain moment, the information volume represented in a probability space can be accurately measured by Shannon entropy. But in real life, the results of things usually change over time, and the prediction of the information volume contained in the future is still an open question. Deng entropy proposed by Deng in recent years is widely applied on meas

Bosiljka Tadic, Neelima Gupte

Recent studies of networks representing complex systems from the brain to social graphs have revealed their higher-order architecture, which can be described by aggregates of simplexes (triangles, tetrahedrons, and higher cliques). Current research aims at quantifying these hidden geometries by the algebraic topology methods and deep graph theory and underst

Alfredo D. Miravet, Antonio L. Maroto

We study the effects of ultralight vector field (ULVF) dark matter on gravitational-wave propagation. We find that the coherent oscillations of the vector field induce an anisotropic suppression of the gravitational-wave amplitude as compared to the $\Lambda$CDM prediction. The effect is enhanced for smaller vector field masses and peaks for modes around $k=

Kira Maag, Matthias Rottmann, Serin Varghese, Fabian Hueger

Instance segmentation with neural networks is an essential task in environment perception. In many works, it has been observed that neural networks can predict false positive instances with high confidence values and true positives with low ones. Thus, it is important to accurately model the uncertainties of neural networks in order to prevent safety issues

Gianluca Favre, Marlies Pirner, Christian Schmeiser

The thermalization of a gas towards a Maxwellian velocity distribution with the background temperature is described by a kinetic relaxation model. The sum of the kinetic energy of the gas and the thermal energy of the background are conserved, and the heat flow in the background is governed by the Fourier law. For the coupled nonlinear system of the kinetic

Bing Huang, O. Anatole von Lilienfeld

Chemical compound space (CCS), the set of all theoretically conceivable combinations of chemical elements and (meta-)stable geometries that make up matter, is colossal. The first principles based virtual sampling of this space, for example in search of novel molecules or materials which exhibit desirable properties, is therefore prohibitive for all but the s

Ya-Ping Xie, Victor P. Goncalves

In this paper we investigate the possibility of searching for the hidden-bottom pentaquark states in photon-induced interactions at the LHC. We consider the presence of the $P_b$ resonance in the $s$-channel of the $\gamma p \rightarrow \Upsilon p$ reaction and estimate its contribution for the exclusive $\Upsilon$ photoproduction in the fixed-target mode of

Amal Mattoo, Melissa Sherman-Bennett

We study Newton polytopes for cluster variables in cluster algebras $\mathcal{A}(\Sigma)$ of types A and D. A famous property of cluster algebras is the Laurent phenomenon: each cluster variable can be written as a Laurent polynomial in the cluster variables of the initial seed $\Sigma$. The cluster variable Newton polytopes are the Newton polytopes of these

Petar Milin, Benjamin V. Tucker, Dagmar Divjak

In the present paper we use a range of modeling techniques to investigate whether an abstract phone could emerge from exposure to speech sounds. In effect, the study represents an attempt for operationalize a theoretical device of Usage-based Linguistics of emergence of an abstraction from language use. Our quest focuses on the simplest of such hypothesized

Wenbin Zhao, Jiabao Lei, Yuxin Wen, Jianguo Zhang

Shape modeling and reconstruction from raw point clouds of objects stand as a fundamental challenge in vision and graphics research. Classical methods consider analytic shape priors; however, their performance degraded when the scanned points deviate from the ideal conditions of cleanness and completeness. Important progress has been recently made by data-dr

Saulo Queiroz, João P. Vilela, Edmundo Monteiro

In this paper, we study the impact of computational complexity on the throughput limits of the {\color{black}fast Fourier transform (FFT)} algorithm for {\color{black}orthogonal frequency division multiplexing(OFDM)} waveforms. Based on the spectro-computational {\color{\corcorrecao}complexity} (SC) analysis, {\color{\corcorrecao} we verify that the complexi

Adam Chapman, Mathieu Florence, Kelly McKinnie

We study the common splitting fields of symbol algebras of degree $p^m$ over fields $F$ of $\operatorname{char}(F)=p$. We first show that if any finite number of such algebras share a degree $p^m$ simple purely inseparable splitting field, then they share a cyclic splitting field of the same degree. As a consequence, we conclude that every finite number of s

Alain Tremeau, Sixiang Xu, Damien Muselet

Recognizing material from color images is still a challenging problem today. While deep neural networks provide very good results on object recognition and has been the topic of a huge amount of papers in the last decade, their adaptation to material images still requires some works to reach equivalent accuracies. Nevertheless, recent studies achieve very go

J. F. Jesus, A. A. Escobal, D. Benndorf, S. H. Pereira

In this paper we study a model of interacting dark energy - dark matter where the ratio between these components is not constant, changing from early to late times in such a way that the model can solve or alleviate the cosmic coincidence problem (CP). The interaction arises from an assumed relation of the form $\rho_x \propto \rho_d^\alpha$, where $\rho_x$

Abdulaziz D. Alhaidari, Hocine Bahlouli, Carlos P. Aparicio, Saeed M. Al-Marzoug

The J-matrix method of scattering was developed to handle regular short-range potentials with applications in atomic, nuclear and molecular physics. Its accuracy, stability, and convergence properties compare favorably with other successful scattering methods. It is an algebraic method, which is built on the utilization of orthogonal polynomials that satisfy

Peiyi Cui

Let p be an arbitrary prime number and k be an algebraically closed field of characteristic l different from p. We construct maximal simple k-types of Levi subgroups M' of SLn(F), when F is a non-archimedean locally compact field of residual characteristic p, which is to say that any cuspidal k-representation of M' can be compactly induced from an irreducibl

Shotaro Yagishita, Jun-ya Gotoh

Network Lasso (NL for short) is a methodology for estimating models by simultaneously clustering data samples and fitting the models to the samples. It often succeeds in forming clusters thanks to the geometry of the $\ell_1$-regularizer employed therein, but there might be limitations because of the convexity of the regularizer. This paper focuses on the cl

Raoul Nigmatullin, Alexander Ivchenko, Semyon Dorokhin

We propose a new approach to traffic preprocessing called Differentiation of Sliding Rescaled Ranges (DSRR) expanding the ideas laid down by H.E. Hurst. We apply proposed approach on the characterizing encrypted and unencrypted traffic on the well-known ISCXVPN2016 dataset. We deploy DSRR for flow-base features and then solve the task VPN vs nonVPN with basi

Shipra Jain, Danda Paudel Pani, Martin Danelljan, Luc Van Gool

The state-of-the-art object detection and image classification methods can perform impressively on more than 9k and 10k classes, respectively. In contrast, the number of classes in semantic segmentation datasets is relatively limited. This is not surprising when the restrictions caused by the lack of labeled data and high computation demand for segmentation

Marko Znidaric

There has been interest in the spin transport properties of the Aubry-Andre-Harper model at high temperatures under weak integrability breaking, in particular for small interactions or small fields. We present old unpublished and new results that show that the model is diffusive, meaning that the claimed superdiffusion [1,2] is a finite-size effect.

Yamila Barrera, Leonardo Boechi, Matthieu Jonckheere, Vincent Lefieux

The Reseau de Transport d'Electricit\'e (RTE) is the French main electricity network operational manager and dedicates large number of resources and efforts towards understanding climate time series data. We discuss here the problem and the methodology of grouping and selecting representatives of possible climate scenarios among a large number of climate sim

Sambunath Das, Dayasindhu Dey, Manoranjan Kumar, S. Ramasesha

The quantum phases in a spin-1 skewed ladder system formed by alternately fusing five- and seven-membered rings are studied numerically using the exact diagonalization technique up to 16 spins and using the density matrix renormalization group method for larger system sizes. The ladder has a fixed isotropic antiferromagnetic (AF) exchange interaction ($J_2 =

Jai-Hua Yen, Chun-Huo Chiu

Richness estimation of an interesting area is always a challenge statistical work due to small sample size or species identity error. In the literatures, most richness estimators were only proposed to tackle the underestimation of the size-limited sample. However, species identity error almost occurs in each species survey and seriously reduces the accuracy

Shuang Chen, Jinqiao Duan

We study the existence and stability of small-amplitude periodic waves emerging from fold-Hopf equilibria in a system of one reaction-diffusion equation coupled with one ordinary differential equation. This coupled system includes the FitzHugh-Nagumo system, caricature calcium models, consumer-resource models and other models in the real-world applications.

Katharina Bieker, Bennet Gebken, Sebastian Peitz

We present a novel algorithm that allows us to gain detailed insight into the effects of sparsity in linear and nonlinear optimization, which is of great importance in many scientific areas such as image and signal processing, medical imaging, compressed sensing, and machine learning (e.g., for the training of neural networks). Sparsity is an important featu

Xi Chen, Ke Xiao, Rui Ma, Xuezheng Cao

Both biological and artificial nanochannels in crooked shape exhibit unusual transportational characteristics, bringing about a challenge to the traditional theoretical analysis of nanofluidics, partly due to their complicated boundary description. In this paper, by developing a curvilinear coordinate system for crooked nanochannels, we successfully solve th

Jérôme Carrand

We give a short proof that the ergodic sums of $\mathcal{C}^1$ observables for a $\mathcal{C}^1$ flow on $\mathbb{T}^2$ admitting a closed transversal curve whose Poincar\'e map has constant type rotation number have growth deviating at most logarithmically from a linear one. For this, we relate the latter integral to the Birkhoff sum of a well-chosen observ

Luca Beltramelli, Aamir Mahmood, Paolo Ferrari, Patrik Österberg

Many new narrowband low-power wide-area networks (LPWANs) (e.g., LoRaWAN, Sigfox) have opted to use pure ALOHA-like access for its reduced control overhead and asynchronous transmissions. Although asynchronous access reduces the energy consumption of IoT devices, the network performance suffers from high intra-network interference in dense deployments. Contr

Yi Chu, Ross Donaldson, Rupesh Kumar, David Grace

This paper presents the feasibility study of deploying Quantum Key Distribution (QKD) from High Altitude Platforms (HAPs), as a way of securing future communications applications and services. The paper provides a thorough review of the state of the art HAP technologies and summarises the benefits that HAPs can bring to the QKD services. A detailed link budg

Anastasia Kokori, Angelos Tsiaras, Billy Edwards, Marco Rocchetto

The Ariel mission will observe spectroscopically around 1000 exoplanets to further characterise their atmospheres. For the mission to be as efficient as possible, a good knowledge of the planets' ephemerides is needed before its launch in 2028. While ephemerides for some planets are being refined on a per-case basis, an organised effort to collectively verif

Jiuwen Zhu, Yuexiang Li, S. Kevin Zhou

Self-supervised learning (SSL) is an efficient approach that addresses the issue of limited training data and annotation shortage. The key part in SSL is its proxy task that defines the supervisory signals and drives the learning toward effective feature representations. However, most SSL approaches usually focus on a single proxy task, which greatly limits

Dominic Breit, Eduard Feireisl, Martina Hofmanova

We are concerned with the long time behavior of the stochastic Navier--Stokes system for compressible fluids in dimension two and three. In this setting, the part of the phase space occupied by the solution depends sensitively on the choice of the initial state. Our main results are threefold. (i) The kinetic energy of a solution is universally and asymptoti

Matias Apa, Maria Cecilia Faini, Mohammad Aliannejadi, Maria Soledad Pera

The potential threat that domestic animals pose to the health of human populations tends to be overlooked. We posit that positive steps forward can be made in this area, via suitable state-wide public policy. In this paper, we describe the data collection process that took place in Casilda (a city in Argentina), in the context of a canine census. We outline

Hassan Ali, Surya Nepal, Salil S. Kanhere, Sanjay Jha

We have witnessed the continuing arms race between backdoor attacks and the corresponding defense strategies on Deep Neural Networks (DNNs). Most state-of-the-art defenses rely on the statistical sanitization of the "inputs" or "latent DNN representations" to capture trojan behaviour. In this paper, we first challenge the robustness of such recently reported

Pekka Koskela, Alexander Ukhlov, Zheng Zhu

Let $n\geq 2$ and $1\leq q<p<\fz$. We prove that if $\Omega\subset\mathbb R^n$ is a Sobolev $(p, q)$-extension domain, with additional capacitory restrictions on boundary in the case $q\leq n-1$, $n>2$, then $|\partial\Omega|=0$. In the case $1\leq q<n-1$, we give an example of a Sobolev $(p,q)$-extension domain with $|\partial\Omega|>0$.

Tobias Jenke, Joachim Bosina, Jakob Micko, Mario Pitschmann

Spectroscopic methods allow to measure energy differences with unrivaled precision. In the case of gravity resonance spectroscopy, energy differences of different gravitational states are measured without recourse to the electromagnetic interaction. This provides a very pure and background free look at gravitation and topics related to the central problem of

Milica Milivojević Danas

In this paper extremal values of the difference between several graph invariants related to the metric dimension are studied: mixed metric dimension, edge metric dimension and strong metric dimension. These non-trivial extremal values are computed over all connected graphs of given order. To obtain such extremal values several techniques are developed. They

Péter Lajkó, Ferenc Iglói

The antiferromagnetic quantum Ising chain has a quantum critical point which belongs to the universality class of the transverse Ising model (TIM). When a longitudinal field ($h$) is switched on, the phase transition is preserved, which turns to first-order for $h/\Gamma \to \infty$, $\Gamma$ being the strength of the transverse field. Here we will re-examin

Mark van der Boor, Sem Borst, Johan van Leeuwaarden

Load balancing plays a critical role in efficiently dispatching jobs in parallel-server systems such as cloud networks and data centers. A fundamental challenge in the design of load balancing algorithms is to achieve an optimal trade-off between delay performance and implementation overhead (e.g. communication or memory usage). This trade-off has primarily

Shafqat Riaz, Askar B. Abdikamalov, Dimitry Ayzenberg, Cosimo Bambi

Relativistic reflection features in the X-ray spectra of black hole binaries and AGNs are thought to be produced through illumination of a cold accretion disk by a hot corona. In this work, we assume that the corona has the shape of an infinitesimally thin disk with its central axis the same as the rotational axis of the black hole. The corona can either be

Runlin Zhang

Let G be a semisimple linear algebraic group defined over rational numbers, K be a maximal compact subgroup of its real points and {\Gamma} be an arithmetic lattice. One can associate a probability measure {\mu}(H) on {\Gamma}\G for each subgroup H of G defined over Q with no non-trivial rational characters. As G acts on {\Gamma}\G from the right, we can pus

George Sterpu, Naomi Harte

In recent years, Automatic Speech Recognition (ASR) technology has approached human-level performance on conversational speech under relatively clean listening conditions. In more demanding situations involving distant microphones, overlapped speech, background noise, or natural dialogue structures, the ASR error rate is at least an order of magnitude higher

Julian Reichert, Leon Granz, Thomas Voigtmann

We discuss recent advances in developing a mode-coupling theory of the glass transition (MCT) of two-dimensional systems of active Brownian particles (ABP). We specifically discuss the case of a single ABP tracer in a glass-forming passive host suspension; a case that has recently been studied in experiments on colloidal Janus particles. We employ event-driv

Qianqian Wang, Liemao Cao, Shi-Jun Liang, Weikang Wu

Metal contacts to two-dimensional (2D) semiconductors are ubiquitous in modern electronic and optoelectronic devices. Such contacts are, however, often plagued by strong Fermi level pinning (FLP) effect which reduces the tunability of the Schottky barrier height (SBH) and degrades the performance of 2D-semiconductor-based devices. In this work, we show that

Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, Guillem Alenyà

Recognition in planning seeks to find agent intentions, goals or activities given a set of observations and a knowledge library (e.g. goal states, plans or domain theories). In this work we introduce the problem of Online Action Recognition. It consists in recognizing, in an open world, the planning action that best explains a partially observable state tran

Demi Guo, Alexander M. Rush, Yoon Kim

While task-specific finetuning of pretrained networks has led to significant empirical advances in NLP, the large size of networks makes finetuning difficult to deploy in multi-task, memory-constrained settings. We propose diff pruning as a simple approach to enable parameter-efficient transfer learning within the pretrain-finetune framework. This approach v

David Alexandre, Hsueh-Ming Hang

This paper proposes a learning-based video codec, specifically used for Challenge on Learned Image Compression (CLIC, CVPRWorkshop) 2020 P-frame coding. More specifically, we designed a compressor network with Refine-Net for coding residual signals and motion vectors. Also, for motion estimation, we introduced a hierarchical, attention-based ME-Net. To verif

András Kalapos, Csaba Gór, Róbert Moni, István Harmati

In this work, we study vision-based end-to-end reinforcement learning on vehicle control problems, such as lane following and collision avoidance. Our controller policy is able to control a small-scale robot to follow the right-hand lane of a real two-lane road, while its training was solely carried out in a simulation. Our model, realized by a simple, convo

Xurong Xie, Xunying Liu, Tan Lee, Lan Wang

A key task for speech recognition systems is to reduce the mismatch between training and evaluation data that is often attributable to speaker differences. Speaker adaptation techniques play a vital role to reduce the mismatch. Model-based speaker adaptation approaches often require sufficient amounts of target speaker data to ensure robustness. When the amo

Jordan McMahon

A celebrated result in representation theory is that of higher Auslander correspondence. Let $\Lambda$ an Artin algebra and $X$ a $d$-cluster-tilting module. Iyama has shown that the endomorphism ring $\Gamma$ of $X$ is a $d$-Auslander algebra, and moreover this gives a correspondence between $d$-cluster-tilting modules and $d$-Auslander algebras. We present

Lorenzo Guerrieri, Jerzy Weyman

We produce some interesting families of resolutions of length three by describing certain open subsets of the spectrum of the generic ring for such resolutions constructed in a recent paper by Weyman.

Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam

We introduce LRT-NG, a set of techniques and an associated toolset that computes a reachtube (an over-approximation of the set of reachable states over a given time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the state-of-the-art Langrangian Reachability and its associated tool LRT. From a theoretical perspective, LRT-NG is superi

Robert Ganian, Thekla Hamm, Fabian Klute, Irene Parada

In extension problems of partial graph drawings one is given an incomplete drawing of an input graph $G$ and is asked to complete the drawing while maintaining certain properties. A prominent area where such problems arise is that of crossing minimization. For plane drawings and various relaxations of these, there is a number of tractability as well as lower

E. E. Davies, C. Möstl, M. J. Owens, A. J. Weiss

On 2020 April 19 a coronal mass ejection (CME) was detected in situ by Solar Orbiter at a heliocentric distance of about 0.8 AU. The CME was later observed in situ on April 20th by the Wind and BepiColombo spacecraft whilst BepiColombo was located very close to Earth. This CME presents a good opportunity for a triple radial alignment study, as the spacecraft

Juan Lopez-Moraña, Xavier Viñas

The ability of the Gogny forces of the D1 family to describe the nucleon-nucleus scattering is studied. To this end, we use an optical model potential built up using a semi-microscopic nuclear matter approach. The real and imaginary parts of the optical model are provided by the first and second-order terms, respectively, of the Taylor expansion of the mass

Rohan E. Louis, Julia K. Thalmann

Sunspot light bridges are known to exhibit a variety of dynamic and persistent phenomena such as surges, small-scale jets etc. in the chromosphere and transition region. While it has generally been proposed that magnetic reconnection is responsible for this small-scale dynamism, persistent flaring activity lasting several hours from the same spatial location

Hui Li, Jun Wang, Xiao Yao, Zhuan Ye

Let $f_\omega(z)=\sum\limits_{j=0}^{\infty}\chi_j(\omega) a_j z^j$ be a random entire function, where $\chi_j(\omega)$ are independent and identically distributed random variables defined on a probability space $(\Omega, \mathcal{F}, \mu)$. In this paper, we first define a family of random entire functions, which includes Gaussian, Rademacher, Steinhaus enti

Nina Korshunova, Gianluca Alaimo, Seyyed Bahram Hosseini, Massimo Carraturo

The production of lightweight metal lattice structures has received much attention due to the recent developments in additive manufacturing (AM). The design flexibility comes, however, with the complexity of the underlying physics. In fact, metal additive manufacturing introduces process-induced geometrical defects that mainly result in deviations of the eff

Cristian Tatino, Nikolaos Pappas, Di Yuan

In this paper, we consider the motion energy minimization problem for a robot that uses millimeter-wave (mm-wave) communications assisted by an intelligent reflective surface (IRS). The robot must perform tasks within given deadlines and it is subject to uplink quality of service (QoS) constraints. This problem is crucial for fully automated factories that a

Qiong Wu, Xu Chen, Zhi Zhou, Junshan Zhang

In-home health monitoring has attracted great attention for the ageing population worldwide. With the abundant user health data accessed by Internet of Things (IoT) devices and recent development in machine learning, smart healthcare has seen many successful stories. However, existing approaches for in-home health monitoring do not pay sufficient attention t

Christopher Briggs, Zhong Fan, Peter Andras

In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations. High resolution smart meter data can expose many private aspects of a consumer's household such as occupancy, habits and individual appliance usage. Yet smart metering infrastructure has the po

Jacques Kluska, Rik Claes, Akke Corporaal, Hans Van Winckel

The new generation of VLTI instruments (GRAVITY, MATISSE) aims to produce routinely interferometric images to uncover the morphological complexity of different objects at high angular resolution. Image reconstruction is, however, not a fully automated process. Here we focus on a specific science case, namely the complex circumbinary environments of a subset

Ivan Bochkov, Vsevolod Evtushevsky

Among central measures on the path space of the Young--Fibonacci lattice the so-called Plancherel measure has a special role. Its ergodicity was proved by Kerov and Gnedin. The goal of this cycle of two articles is to prove that remaining measures from the Martin boundary of this graph (which were described by Kerov and Goodman) are also ergodic. The measure

M. Litsgård, K. Nyström

We consider the operators \[ \nabla_X\cdot(A(X)\nabla_X),\ \nabla_X\cdot(A(X)\nabla_X)-\partial_t,\ \nabla_X\cdot(A(X)\nabla_X)+X\cdot\nabla_Y-\partial_t, \] where $X\in \Omega$, $(X,t)\in \Omega\times \mathbb R$ and $(X,Y,t)\in \Omega\times \mathbb R^m\times \mathbb R$, respectively, and where $\Omega\subset\mathbb R^m$ is a (unbounded) Lipschitz domain wit

Shahid Sattar, J. Andreas Larsson

We use first-principles calculations to show that van der Waals (vdW) heterostructures consisting of few-layer Bi$_2$Se$_3$ and PtSe$_2$ exhibit electronic and spintronics properties that can be tuned by varying the constituent layers. Type-II band alignment with layer-tunable band gaps and type-III band alignment with spin-splittings have been found. Most n

S. De Palo, E. Orignac, M. L. Chiofalo, R. Citro

Probing the radial collective oscillation of a trapped quantum system is an accurate experimental tool to investigate interactions and dimensionality effects. We consider a fully polarized quasi-one dimensional dipolar quantum gas of bosonic dysprosium atoms in a parabolic trap at zero temperature. We model the dipolar gas with an effective quasi-one dimensi

Z. Amirabi, S. Habib Mazharimousavi

The nonlinear Maxwell Lagrangian preserving both conformal and SO(2) duality-rotation invariance has been introduced very recently. Here, in the context of Einstein's theory of gravity minimally coupled with this nonlinear electrodynamics, we obtain a black hole solution which is the Reissner-Nordstr\"{o}m black hole with one additional parameter that is com

Sun-Sig Byun, Jeongmin Han, Jehan Oh

This paper concerns fully nonlinear elliptic obstacle problems with oblique boundary conditions. We investigate the existence, uniqueness and $W^{2,p}$-regularity results by finding approximate non-obstacle problems with the same oblique boundary condition and then making a suitable limiting process.

Teresa A. M. Braun, Hsi-Wei Yen, Patrick M. Koch, Carlo F. Manara

We analysed archival molecular line data of pre-main sequence (PMS) stars in the Lupus and Taurus star-forming regions obtained with ALMA surveys with an integration time of a few minutes per source. We stacked the data of $^{13}$CO and C$^{18}$O (J = 2-1 & 3-2) and CN (N = 3-2, J = 7/2-5/2) lines to enhance the signal-to-noise ratios, and measured the stell

Mariano Zeron, Ignacio Ruiz

Inspired by a series of remarkable papers in recent years that use Deep Neural Nets to substantially speed up the calibration of pricing models, we investigate the use of Chebyshev Tensors instead of Deep Neural Nets. Given that Chebyshev Tensors can be, under certain circumstances, more efficient than Deep Neural Nets at exploring the input space of the fun

Carlos Lassance

In recent years, Deep Learning methods have achieved state of the art performance in a vast range of machine learning tasks, including image classification and multilingual automatic text translation. These architectures are trained to solve machine learning tasks in an end-to-end fashion. In order to reach top-tier performance, these architectures often req

Rodolfo Smiljanic, Mateusz G. Zych, Luca Pasquini

Abundances of beryllium in metal-poor stars scale linearly with metallicity down to [Fe/H] ~ -3.0. In the stars where Be has been detected at this extremely metal-poor regime, an increased abundance scatter has been previously reported. This scatter could indicate a flattening of the relation between Be and [Fe/H]. Our aim is to perform a new investigation o

Deli Chen, Yankai Lin, Lei Li, Xuancheng Ren

Graph Contrastive Learning (GCL) has proven highly effective in promoting the performance of Semi-Supervised Node Classification (SSNC). However, existing GCL methods are generally transferred from other fields like CV or NLP, whose underlying working mechanism remains under-explored. In this work, we first deeply probe the working mechanism of GCL in SSNC,

Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang

Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a high prediction capacity of the model, which is the ability to capture precise long-range dependency coupling between output and input efficiently. Recent studies have shown the pot

Sun-Sig Byun, Jeongmin Han

We study fully nonlinear parabolic equations in nondivergence form with oblique boundary conditions. An optimal and global Calder\'{o}n-Zygmund estimate is obtained by proving that the Hessian of the viscosity solution to the oblique boundary problem is as integrable as the nonhomogeneous term in $L^{p}$ spaces under minimal regularity requirement on the non

Federico Zocco, Seán McLoone

Motivated by the potential for parallel implementation of batch-based algorithms and the accelerated convergence achievable with approximated second order information a limited memory version of the BFGS algorithm has been receiving increasing attention in recent years for large neural network training problems. As the shape of the cost function is generally