July 2022 arXiv papers — page 27

Jiaqi Wang, Xiaohu Yang, Jun Zhang, Hekun Li

Based on a large group/cluster catalog recently constructed from the DESI Legacy Imaging Surveys DR9 using an extended halo-based group finder, we measure and model the group-galaxy weak lensing signals for groups/clusters in a few redshift bins within redshift range $0.1 \leqslant z<0.6$. Here, the background shear signals are obtained based on the DECaLS s

Javier Civit-Masot, Francisco Luna-Perejon, Jose Maria Rodriguez Corral, Manuel Dominguez-Morales

Medical image segmentation can be implemented using Deep Learning methods with fast and efficient segmentation networks. Single-board computers (SBCs) are difficult to use to train deep networks due to their memory and processing limitations. Specific hardware such as Google's Edge TPU makes them suitable for real time predictions using complex pre-trained n

Gaia Forghieri, Paolo Bordone, Andrea Bertoni

Graphene nanoribbons provide an ideal platform for electronic interferometry in the Integer Quantum Hall regime. Here, we solve the time-dependent four-component Schroedinger equation for single carriers in graphene and expose several dynamical effects of the carrier localization on their transport characteristics in pn junctions. We simulate two kinds of Ma

Mia Mohammad Imran, Kostadin Damevski

Context: Recent research indicates that Web queries written by software developers are not very successful in retrieving relevant results, performing measurably worse compared to general purpose Web queries. Most approaches up to this point have addressed this problem with software engineering-specific automated query reformulation techniques, which work wit

Yukai Shi, Hao Li, Sen Zhang, Zhijing Yang

Real-scene image super-resolution aims to restore real-world low-resolution images into their high-quality versions. A typical RealSR framework usually includes the optimization of multiple criteria which are designed for different image properties, by making the implicit assumption that the ground-truth images can provide a good trade-off between different

F. Tavecchio, A. Costa, A. Sciaccaluga

Extreme BL Lacs (EHBL) form a subclass of blazars which challenge standard emission scenarios. In a recent study it has been argued that their peculiar properties can be explained if emitting electrons are accelerated in a series of oblique shocks induced by the recollimation of the relativistic jet. However, new 3D simulations of recollimated, weakly magnet

Yoshito Ishiki

For a metrizable space $X$, we denote by $\mathrm{Met}(X)$ the space of all metric that generate the same topology of $X$. The space $\mathrm{Met}(X)$ is equipped with the supremum distance. In this paper, for every strongly zero-dimensional metrizable space $X$, we prove that the set of all metrics whose ranges are closed totally disconnected subsets of the

Anahita Farhang Ghahfarokhi, Fatemeh Akoochekian, Fareed Zandkarimi, Wil M. P. van der Aalst

Process mining provides various algorithms to analyze process executions based on event data. Process discovery, the most prominent category of process mining techniques, aims to discover process models from event logs, however, it leads to spaghetti models when working with real-life data. Therefore, several clustering techniques have been proposed on top o

Till Hofmann, Vaishak Belle

A robot's actions are inherently stochastic, as its sensors are noisy and its actions do not always have the intended effects. For this reason, the agent language Golog has been extended to models with degrees of belief and stochastic actions. While this allows more precise robot models, the resulting programs are much harder to comprehend, because they need

Mosè Giordano, Milan Klöwer, Valentin Churavy

The Fujitsu A64FX ARM-based processor is used in supercomputers such as Fugaku in Japan and Isambard 2 in the UK and provides an interesting combination of hardware features such as Scalable Vector Extension (SVE), and native support for reduced-precision floating-point arithmetic. The goal of this paper is to explore performance of the Julia programming lan

Changkun Ou, Daniel Buschek, Sven Mayer, Andreas Butz

Interactive AI systems increasingly employ a human-in-the-loop strategy. This creates new challenges for the HCI community when designing such systems. We reveal and investigate some of these challenges in a case study with an industry partner, and developed a prototype human-in-the-loop system for preference-guided 3D model processing. Two 3D artists used i

Jiacheng Tang, Hao Sun, Qiyao Zhang, Xingcan Dai

Understanding the structure of matter or materials and interaction or correlations among the constituent elementary particles are the central tasks of all branches of science, from physics, chemistry, to biology. In physics, this ultimate goal has spurred a constant search for high-order correlated entities or composite particles for nearly all states and fo

Sławomir Dadas

Sentence embeddings are commonly used in text clustering and semantic retrieval tasks. State-of-the-art sentence representation methods are based on artificial neural networks fine-tuned on large collections of manually labeled sentence pairs. Sufficient amount of annotated data is available for high-resource languages such as English or Chinese. In less pop

K. G. Anusree, Dipankar Bhattacharya, Varun Bhalerao, Akash Anumarlapudi

The Cadmium Zinc Telluride Imager (CZTI) onboard AstroSat, an open detector above $\sim$100 keV, is a promising tool for the investigation of hard X-ray characteristics of $\gamma$-ray pulsars. A custom algorithm has been developed to detect pulsars from long integration ($\sim$years) of archival data, as reported by us earlier. Here we extend this method to

Chun-Mao Lai, Ming-Hao Hsu, Chao-Wei Huang, Yun-Nung Chen

Prior work has demonstrated that data augmentation is useful for improving dialogue state tracking. However, there are many types of user utterances, while the prior method only considered the simplest one for augmentation, raising the concern about poor generalization capability. In order to better cover diverse dialogue acts and control the generation qual

Piotr Kosinski, Pawel Maslanka

The nongeneric six- and eightdimensional orbits of SO(4,2) are described in explicitly covariant way. The relevant Hamiltonian dynamical systems are constructed and canonically quantized. It is shown that the resulting unitary representations of conformal group fit into the classification described by Mack (G. Mack, Comm. Math. Phys. 55 (1977),1).

Hannah Diamond-Lowe, Laura Kreidberg, C. E. Harman, Eliza M. -R. Kempton

Multi-planet systems orbiting M dwarfs provide valuable tests of theories of small planet formation and evolution. K2-3 is an early M dwarf hosting three small exoplanets (1.5-2.0 Earth radii) at distances of 0.07-0.20 AU. We measure the high-energy spectrum of K2-3 with HST/COS and XMM-Newton, and use empirically-driven estimates of Ly-alpha and extreme ult

Arno Bargerbos, Lukas Johannes Splitthoff, Marta Pita-Vidal, Jaap J. Wesdorp

Quantum error correction will be an essential ingredient in realizing fault-tolerant quantum computing. However, most correction schemes rely on the assumption that errors are sufficiently uncorrelated in space and time. In superconducting qubits this assumption is drastically violated in the presence of ionizing radiation, which creates bursts of high energ

Xiaoning Bai, Qingna Li

The high-dimensional rank lasso (hdr lasso) model is an efficient approach to deal with high-dimensional data analysis. It was proposed as a tuning-free robust approach for the high-dimensional regression and was demonstrated to enjoy several statistical advantages over other approaches. The hdr lasso problem is essentially an $L_1$-regularized optimization

Ming Xu, Xiaoyan Cheng, Yuansheng Tang

For integer $k\geq2$ and prime power $q$, the algebraic bipartite graph $D(k,q)$ proposed by Lazebnik and Ustimenko (1995) is meaningful not only in extremal graph theory but also in coding theory and cryptography. This graph is $q$-regular, edge-transitive and of girth at least $k+4$. For its exact girth $g=g(D(k,q))$, F\"{u}redi et al. (1995) conjectured $

Alexander Kubanek, Anna P. Ovvyan, Lukas Antoniuk, Niklas Lettner

This chapter covers recent developments in the field of hybrid quantum photonics based on color centers in nanodiamonds and Si3N4-photonics towards a technology platform with applications in quantum information processing and quantum information distribution. The methodological approach can be divided in three main tasks. First, the fabrication and optimizat

Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang

Neuromorphic computing is an emerging research field that aims to develop new intelligent systems by integrating theories and technologies from multi-disciplines such as neuroscience and deep learning. Currently, there have been various software frameworks developed for the related fields, but there is a lack of an efficient framework dedicated for spike-bas

Elias Cueto, Francisco Chinesta

Thermodynamics could be seen as an expression of physics at a high epistemic level. As such, its potential as an inductive bias to help machine learning procedures attain accurate and credible predictions has been recently realized in many fields. We review how thermodynamics provides helpful insights in the learning process. At the same time, we study the i

Adrien Raison, Pascal Bourdon, David Helbert

The explainability of deep networks is becoming a central issue in the deep learning community. It is the same for learning on graphs, a data structure present in many real world problems. In this paper, we propose a method that is more optimal, lighter, consistent and better exploits the topology of the evaluated graph than the state-of-the-art methods.

Ivan I. Shevchenko

We consider the chaotic motion of low-mass bodies in two-body high-order mean-motion resonances with planets in model planetary systems, and analytically estimate the Lyapunov and diffusion timescales of the motion in multiplets of interacting subresonances corresponding to the mean-motion resonances. We show that the densely distributed (though not overlapp

Dominik Drees, Simon Leistikow, Xiaoyi Jiang, Lars Linsen

Technological advances for measuring or simulating volume data have led to large data sizes in many research areas such as biology, medicine, physics, and geoscience. Here, large data can refer to individual data sets with high spatial and/or temporal resolution as well as collections of data sets in the sense of cohorts or ensembles. Therefore, general-purp

Rongrong Zhai, Hongwei Yu, Puxun Wu

We study the amplification of the curvature perturbations due to a small sound speed and find that its origin is different completely from that due to the ultraslow-roll inflation. This is because when the sound speed is very small the enhancement of the power spectrum comes from the fact that the curvature perturbations at the scales smaller than the cosmic

Yudi Zhao, Kuangrong Hao, Chaochen Gu, Bing Wei

To address the trade-off problem of quality-diversity for the generated images in imbalanced classification tasks, we research on over-sampling based methods at the feature level instead of the data level and focus on searching the latent feature space for optimal distributions. On this basis, we propose an iMproved Estimation Distribution Algorithm based La

R. San Millán-Castillo, L. Martino, E. Morgado, F. Llorente

In the last decade, soundscapes have become one of the most active topics in Acoustics, providing a holistic approach to the acoustic environment, which involves human perception and context. Soundscapes-elicited emotions are central and substantially subtle and unnoticed (compared to speech or music). Currently, soundscape emotion recognition is a very acti

Sébastien Gouëzel

We report on a formalization of the change of variables formula in integrals, in the mathlib library for Lean. Our version of this theorem is extremely general, and builds on developments in linear algebra, analysis, measure theory and descriptive set theory. The interplay between these domains is transparent thanks to the highly integrated development model

C. Cisowski, S. Franke-Arnold, C. Ross

We introduce a simple mathematical expression based on rational maps to construct ideal paraxial optical skyrmions fields including Neel-type and Bloch-type skyrmions, anti-skyrmions, bimerons and multi-skyrmions, including skyrmion lattices. We review the rules that fully polarized paraxial light fields must obey to be considered as optical skyrmions. This

Aso Validi, Vladislav Kashansky, Jihed Khiari, Hamid Hadian

Hybrid on/off-blockchain vehicle data management approaches have received a lot of attention in recent years. However, there are various technical challenges remained to deal with. In this paper we relied on real-world data from Austria to investigate the effects of connectivity on the transport of personal protective equipment. We proposed a three-step mech

Adel Nabli, Edouard Oyallon

This work introduces DADAO: the first decentralized, accelerated, asynchronous, primal, first-order algorithm to minimize a sum of $L$-smooth and $\mu$-strongly convex functions distributed over a given network of size $n$. Our key insight is based on modeling the local gradient updates and gossip communication procedures with separate independent Poisson Po

Nikola Kamburov, Kelei Wang

We prove the nondegeneracy condition for stable solutions to the one-phase free boundary problem. The proof is by a De Giorgi iteration, where we need the Sobolev inequality of Michael and Simon and, consequently, an integral estimate for the mean curvature of the free boundary. We then apply the nondegeneracy estimate to obtain local curvature bounds for st

Shumpei Masuda, Katsuhiro Nakamura

Speed is the key to further advances in technology. For example, quantum technologies, such as quantum computing, require fast manipulations of quantum systems in order to overcome the effect of decoherence. However, controlling the speed of quantum dynamics is often very difficult due to both the lack of a simple scaling property in the dynamics and the inf

Médéric Motte, Huyên Pham

We investigate propagation of chaos for mean field Markov Decision Process with common noise (CMKV-MDP), and when the optimization is performed over randomized open-loop controls on infinite horizon. We first state a rate of convergence of order $M_N^\gamma$, where $M_N$ is the mean rate of convergence in Wasserstein distance of the empirical measure, and $\

Stefano Marò

We consider the model of a ball elastically bouncing on a racket moving in the vertical direction according to a given periodic function $f(t)$. The gravity force is acting on the ball. We prove that if the function $f(t)$ belongs to a class of trigonometric polynomials of degree $2$ then there exists a one dimensional continuum of initial conditions for whi

ZhenHao Tang, XiaoBing Zhang, Zi Long, XiangHua Fu

Recently, numbers of works shows that the performance of neural machine translation (NMT) can be improved to a certain extent with using visual information. However, most of these conclusions are drawn from the analysis of experimental results based on a limited set of bilingual sentence-image pairs, such as Multi30K. In these kinds of datasets, the content

Jiangwei Xue, Chia-Fu Yu

Let $D$ be a quaternion algebra over a number field $F$, and $\mathscr{G}$ be an arbitrary genus of $O_F$-orders of full rank in $D$. Let $K$ be a quadratic field extension of $F$ that embeds into $D$, and $B$ be an $O_F$-order in $K$ that can be optimally embedded into some member of $\mathscr{G}$. We provide a necessary and sufficient condition for $B$ to

Yang Xu, Julien Scheibert, Nikolaj Gadegaard, Daniel M. Mulvihill

Contact mechanics-based models for the friction of nominally flat rough surfaces have not been able to adequately capture certain key experimentally observed phenomenona, such as the transition from a static friction peak to a lower level of sliding friction and the shear-induced contact area reduction that has been observed in the pre-sliding regime especia

Arnaud Descours, Arnaud Guillin, Manon Michel, Boris Nectoux

In this work, we consider a wide two-layer neural network and study the behavior of its empirical weights under a dynamics set by a stochastic gradient descent along the quadratic loss with mini-batches and noise. Our goal is to prove a trajectorial law of large number as well as a central limit theorem for their evolution. When the noise is scaling as 1/N $

Sebastian Ruland, Malte Lochau

Unit testing is one of the most established quality-assurance techniques for software development. One major advantage of unit testing is the adjustable trade-off between efficiency (i.e., testing effort) and effectiveness (i.e., fault-detection probability). To this end, various strategies have been proposed to exploit this trade-off. In particular, test-su

Ionut Danaila, Francky Luddens, Cécile Legrand

The purpose of this article is to study the convergence of a low order finite element approximation for a natural convection problem. We prove that the discretization based on P1 polynomials for every variable (velocity, pressure and temperature) is well-posed if used with a penalty term in the divergence equation, to compensate the loss of an inf-sup condit

Jürgen Blum, Dorothea Bischoff, Bastian Gundlach

Questions regarding how primordial or pristine the comets of the solar system are have been an ongoing controversy. In this review, we describe comets' physical evolution from dust and ice grains in the solar nebula to the contemporary small bodies in the outer solar system. This includes the phases of dust agglomeration, the formation of planetesimals, thei

Jiang Bian, Xuhong Li, Tao Wang, Qingzhong Wang

While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging. In this work, we release yet another sports video benchmark \TheName{} for \emph{\underline{P}}ing \emph{\underline{P}}ong-\emph{\underline{A}}ction detectio

Yves Achdou, Guillaume Carlier, Quentin Petit, Daniela Tonon

We propose a simple semi-discrete spatial model where rents, wages and the density of population in a city can be deduced from free-mobility and equilibrium conditions on the labour and residential housing markets. We prove existence and (under stronger assumptions) uniqueness of the equilibrium. We extend our model to the case where teleworking is introduce

A. Hashemi, K. Busch, D. N. Christodoulides, S. K. Ozdemir

Understanding the linear response of any system is the first step towards analyzing its linear and nonlinear dynamics, stability properties, as well as its behavior in the presence of noise. In non-Hermitian Hamiltonian systems, calculating the linear response is complicated due to the non-orthogonality of their eigenmodes, and the presence of exceptional po

Alejandro J. Castro, Amin Esfahani, Lyailya Zhapsarbayeva

In this paper we establish the persistence property for solutions of the quartic generalized Korteweg-de Vries equation with initial data in weighted Sobolev spaces $H^{s}(\mathbb{R})\cap L^2(|x|^{2r}dx)$ for $s =1/12 + \varepsilon$ and any $r\in (0,R)$, for some $0 < \varepsilon < 1/4$ and $0<R<s/2$.

Ajai Choudhry

In this paper we obtain four new parametric ideal solutions of the Tarry-Escott problem of degree 7, that is, of the simultaneous diophantine equations, $\sum_{i=1}^8x_i^r=\sum_{i=1}^8y_i^r,\;r=1,\,2,\,\dots,\,7$. While all the known parametric solutions of the problem, with one exception, are given by polynomials of degrees $ \geq 5$, the solutions obtained

Naijia Liu, Lixin Yan

Let $G\cong\mathbb{R}^{d} \ltimes \mathbb{R}$ be a finite-dimensional two-step nilpotent group with the group multiplication $(x,u)\cdot(y,v)\rightarrow(x+y,u+v+x^{T}Jy)$ where $J$ is a skew-symmetric matrix satisfying a degeneracy condition with $2\leq {\rm rank}\, J <d$. Consider the maximal function defined by $$ {\frak M}f(x, u)=\sup_{t>0}\big|\int_{\Sig

Agastya Sridharan, Natarajan S

Traditional approaches to classify the political bias of news articles have failed to generate accurate, generalizable results. Existing networks premised on CNNs and DNNs lack a model to identify and extrapolate subtle indicators of bias like word choice, context, and presentation. In this paper, we propose a network architecture that achieves human-level a

Cyrille Solaro, Clément Debavelaere, Pierre Cladé, Saïda Guellati-Khelifa

We demonstrate a light-pulse atom interferometer based on the diffraction of free-falling atoms by a picosecond frequency-comb laser. More specifically, we coherently split and recombine wave packets of cold $^{87}$Rb atoms by driving stimulated Raman transitions between the $|5s~^2S_{1/2},F=1\rangle$ and $|5s~^2S_{1/2},F=2\rangle$ hyperfine states, using tw

Artur M. Schweidtmann, Dominik Bongartz, Alexander Mitsos

Trained ML models are commonly embedded in optimization problems. In many cases, this leads to large-scale NLPs that are difficult to solve to global optimality. While ML models frequently lead to large problems, they also exhibit homogeneous structures and repeating patterns (e.g., layers in ANNs). Thus, specialized solution strategies can be used for large

Enrique Álvarez, Jesús Anero, Eduardo Velasco-Aja

We have studied a lagrangian in which the Einstein-Hilbert term is deformed by the Weyl cube operator, which is the lowest-dimension operator that is non-vanishing on shell and appears as a two-loop counterterm. There is a tension between the Schwarzschild de Sitter (SdS) spacetime and this operator, which we study in some detail.

Marco Boresta, Tommaso Colombo, Alberto De Santis

Quality control of apparel items is mandatory in modern textile industry, as consumer's awareness and expectations about the highest possible standard is constantly increasing in favor of sustainable and ethical textile products. Such a level of quality is achieved by checking the product throughout its life cycle, from raw materials to boxed stock. Checks m

Tahar Z Boulmezaoud, Boualem Khouider

A new mathematical formulation for the constitutive laws governing elastic perfectly plastic materials is proposed here. In particular, it is shown that the elastic strain rate and the plastic strain rate form an orthogonal decomposition with respect to the tangent cone and the normal cone of the yield domain. It is also shown that the stress rate can be see

Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han

In light of the growing popularity of Exploratory Data Analysis (EDA), understanding the underlying causes of the knowledge acquired by EDA is crucial. However, it remains under-researched. This study promotes a transparent and explicable perspective on data analysis, called eXplainable Data Analysis (XDA). For this reason, we present XInsight, a general fra

Edouard Pauwels, Samuel Vaiter

We show that the derivatives of the Sinkhorn-Knopp algorithm, or iterative proportional fitting procedure, converge towards the derivatives of the entropic regularization of the optimal transport problem with a locally uniform linear convergence rate.

Tai Wang, Qing Lian, Chenming Zhu, Xinge Zhu

In this technical report, we present our solution, dubbed MV-FCOS3D++, for the Camera-Only 3D Detection track in Waymo Open Dataset Challenge 2022. For multi-view camera-only 3D detection, methods based on bird-eye-view or 3D geometric representations can leverage the stereo cues from overlapped regions between adjacent views and directly perform 3D detectio

Soham Bhosale

The incidence rate for skin cancer has been steadily increasing throughout the world, leading to it being a serious issue. Diagnosis at an early stage has the potential to drastically reduce the harm caused by the disease, however, the traditional biopsy is a labor-intensive and invasive procedure. In addition, numerous rural communities do not have easy acc

Pan Liu, Sidy Fall, Serge Metanbou, Olivier Balédent

Cerebral arterial blood flow (CABF) can be investigated in few seconds without any synchronization by Real-Time phase contrast. Significant changes in CABF were found between expiration and inspiration during normal breathing of healthy volunteers. Synopsis (100/100) Real-time phase contrast MRI has been applied to investigate cerebral arterial blood flow (C

Michael Polyntsov, Valentin Grigorev, Kirill Smirnov, George Chernishev

In the age of big data, sorting is an indispensable operation for DBMSes and similar systems. Having data sorted can help produce query plans with significantly lower run times. It also can provide other benefits like having non-blocking operators which will produce data steadily (without bursts), or operators with reduced memory footprint. Sorting may be re

Pan Liu, Sidy Fall, Olivier Balédent

Flow 2.0 is an end-to-end easy-of-use software that allows us to quickly, robustly and accurately perform a batch process real-time phase contrast data and multivariate analysis of the effect of respiration on cerebral fluids circulation. Synopsis (99/100) Real-time phase contrast sequences (RT-PC) have potential value as a scientific and clinical tool in qu

Yiling Yang, Engui Fan, Yue Liu

Consideration in the present paper is the existence of global solutions for the modified Camassa-Holm (mCH) equation with a nonzero background initial value. The mCH equation is completely integrable and can be considered as a model for the unidirectional propagation of shallow-water waves. By applying the inverse scattering transform with an application of

Christoffer Loeffler, Kion Fallah, Stefano Fenu, Dario Zanca

Humans innately measure distance between instances in an unlabeled dataset using an unknown similarity function. Distance metrics can only serve as proxy for similarity in information retrieval of similar instances. Learning a good similarity function from human annotations improves the quality of retrievals. This work uses deep metric learning to learn thes

Xin Zhang, Shenghui Song

The asymptotic mutual information (MI) analysis for multiple-input multiple-output (MIMO) systems over double-scattering channels has achieved engaging results, but the convergence rates of the mean, variance, and the distribution of the MI are not yet available in the literature. In this paper, by utilizing the large random matrix theory (RMT), we give a ce

A. V. Syromyatnikov

We discuss spin-$\frac12$ $J_1$--$J_2$ model on the triangular lattice using recently proposed bond-operator theory (BOT). In agreement with previous discussions of this system, we obtain four phases upon $J_2$ increasing: the phase with $120^\circ$ ordering of three sublattices, the spin-liquid phase, the state with the collinear stripe order, and the spira

Konstantin Sonntag, Sebastian Peitz

We derive efficient algorithms to compute weakly Pareto optimal solutions for smooth, convex and unconstrained multiobjective optimization problems in general Hilbert spaces. To this end, we define a novel inertial gradient-like dynamical system in the multiobjective setting, whose trajectories converge weakly to Pareto optimal solutions. Discretization of t

Naeem Akhtar, Barry C. Sanders, Gao Xianlong

We investigate the sub-Planck-scale structures associated with the SU(1,1) group by establishing that the Planck scale on the hyperbolic plane can be considered as the inverse of the Bargmann index $k$. Our discussion involves SU(1,1) versions of Wigner functions, and the quantum-interference effect is easily visualized through plots of these Wigner function

Stephen Berg, Hyebin Song

In this paper, we study the problem of estimating the autocovariance sequence resulting from a reversible Markov chain. A motivating application for studying this problem is the estimation of the asymptotic variance in central limit theorems for Markov chains. We propose a novel shape-constrained estimator of the autocovariance sequence, which is based on th

Jan-Hendrik Bastek, Dennis M. Kochmann

The numerical modeling of thin shell structures is a challenge, which has been met by a variety of finite element (FE) and other formulations -- many of which give rise to new challenges, from complex implementations to artificial locking. As a potential alternative, we use machine learning and present a Physics-Informed Neural Network (PINN) to predict the

Kevin Kappelmann, Jonas Rädle, Lukas Stevens

Worldwide, computer science departments have experienced a dramatic increase in the number of student enrolments. Moreover, the ongoing COVID-19 pandemic requires institutions to radically replace the traditional way of on-site teaching, moving interaction from physical to virtual space. We report on our strategies and experience tackling these issues as par

Matthew Farrugia-Roberts, Bryn Jeffries, Harald Søndergaard

In recent years we have explored using Haskell alongside a traditional mathematical formalism in our large-enrolment university course on topics including logic and formal languages, aiming to offer our students a programming perspective on these mathematical topics. We have found it possible to offer almost all formative and summative assessment through an

Marc Feeley, Olivier Melançon

Teaching programming to novices is best done with tools with simpler user interfaces than professional IDEs that are tailored for experienced programmers. In a distance learning situation it is also important to have a development environment that is easy to explain and use, and that integrates well with the variety of course material used (slides, homework,

Padma Pasupathi, Christopher W. Schankula, Nicole DiVincenzo, Sarah Coker

To make computational thinking appealing to young learners, initial programming instruction looks very different now than a decade ago, with increasing use of graphics and robots both real and virtual. After the first steps, children want to create interactive programs, and they need a model for this. State diagrams provide such a model. This paper documents

Marco T. Morazán

Students introduced to programming using a design-based approach and a functional programming language become familiar with first-class functions. They rarely, however, connect first-class functions to objects and object-oriented program design. This is a missed opportunity because students inevitably go on to courses using an object-oriented programming lan

Frederik Krogsdal Jacobsen, Jørgen Villadsen

We present a novel approach for teaching logic and the metatheory of logic to students who have some experience with functional programming. We define concepts in logic as a series of functional programs in the language of the proof assistant Isabelle/HOL. This allows us to make notions which are often unclear in textbooks precise, to experiment with definit

Daniil Berezun, Dmitry Boulytchev

We report on a one-semester compiler construction course based on the idea of implementing a small self-contained compiler for a small model language from scratch, not using other compiler construction frameworks. The course is built around an evolving family of languages with increasing expressiveness and complexity, which finally is crowned by a language w

Marco T. Morazán

The use of functional programming languages in the first programming course at many universities is well-established and effective. Invariably, however, students must progress to study object-oriented programming. This article presents how the first steps of this transition have been successfully implemented at Seton Hall University. The developed methodolog

Ye Wang, Jingbo Liao, Hong Yu, Guoyin Wang

Currently end-to-end deep learning based open-domain dialogue systems remain black box models, making it easy to generate irrelevant contents with data-driven models. Specifically, latent variables are highly entangled with different semantics in the latent space due to the lack of priori knowledge to guide the training. To address this problem, this paper p

Tim Engels, Ivo Adan, Onno Boxma, Jacques Resing

This paper derives exact expressions for the Laplace-Stieltjes transform of the order picking time in single- and 2-block warehouses. We consider manual warehouses that deploy return routing and assume that order sizes follow a Poisson distribution. The results in this paper apply to a wide range of storage policies, including but not restricted to class-bas

Jean-Luc Marichal, Naïm Zenaïdi

In its additive version, Bohr-Mollerup's remarkable theorem states that the unique (up to an additive constant) convex solution $f(x)$ to the equation $\Delta f(x)=\ln x$ on the open half-line $(0,\infty)$ is the log-gamma function $f(x)=\ln\Gamma(x)$, where $\Delta$ denotes the classical difference operator and $\Gamma(x)$ denotes the Euler gamma function.

Zhao-An Wang, Bo-Fu Xie, Fei Ming, Yi-Tao Wang

Entropic uncertainty relation (EUR) formulates the restriction of the inherent uncertainty of quantum mechanics from the information-theoretic perspective. A tighter lower bound for uncertainty relations can provide information-theoretic security to quantum communication protocols. Recently, a generalized EUR (GEUR) for the measurement of multiple observable

P. L. Krapivsky, Ohad Vilk, Baruch Meerson

We introduce and study analytically and numerically a simple model of inter-agent competition, where underachievement is strongly discouraged. We consider $N\gg 1$ particles performing independent Brownian motions on the line. Two particles are selected at random and at random times, and the particle closest to the origin is reset to it. We show that, in the

Hui-Xian Cheng, Xian-Feng Han, Guo-Qiang Xiao

Accurate and fast scene understanding is one of the challenging task for autonomous driving, which requires to take full advantage of LiDAR point clouds for semantic segmentation. In this paper, we present a \textbf{concise} and \textbf{efficient} image-based semantic segmentation network, named \textbf{CENet}. In order to improve the descriptive power of le

Ruming Zhang

In this paper, we propose a new spectral decomposition method to simulate waves propagating in complicated waveguides. For the numerical solutions of waveguide scattering problems, an important task is to approximate the Dirichlet-to-Neumann map efficiently. From previous results, the physical solution can be decomposed into a family of generalized eigenfunc

Zhenzhen Lou, Lu Lu, Xueyi Huang

Let $\mathcal{G}(m,k)$ be the set of graphs with size $m$ and odd girth (the length of shortest odd cycle) $k$. In this paper, we determine the graph maximizing the spectral radius among $\mathcal{G}(m,k)$ when $m$ is odd. As byproducts, we show that, there is a number $\eta(m)>\sqrt{m-k+3}$ such that every non-bipartite graph $G$ with size $m$ and spectral

Efthyvoulos Drousiotis, Paul G. Spirakis

Decision trees are highly famous in machine learning and usually acquire state-of-the-art performance. Despite that, well-known variants like CART, ID3, random forest, and boosted trees miss a probabilistic version that encodes prior assumptions about tree structures and shares statistical strength between node parameters. Existing work on Bayesian decision

Martha Paskin, Daniel Baum, Mason N. Dean, Christoph von Tycowicz

3D shapes provide substantially more information than 2D images. However, the acquisition of 3D shapes is sometimes very difficult or even impossible in comparison with acquiring 2D images, making it necessary to derive the 3D shape from 2D images. Although this is, in general, a mathematically ill-posed problem, it might be solved by constraining the proble

Grégory Faye, L. Miguel Rodrigues

For strictly entropic Riemann shock solutions of strictly hyperbolic systems of balance laws, we prove that exponential spectral stability implies large-time asymptotic orbital stability. As a preparation, we also prove similar results for constant solutions of initial value and initial boundary value problems, that seem to be new in this generality. Main ke

Bai Cui, Ahmed Zamzam, Andrey Bernstein

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With the new FERC 2222 order, DER aggregations are allowed to participate in energy market. To enable market participation, these virtual power plants need to provide their generation c

Raphael S. Steiner

We show that arithmetic lattices in $\mathrm{SL}_{2}(\mathbb{R})$, stemming from the proper units of an Eichler order in an indefinite quaternion algebra over $\mathbb{Q}$, admit a `small' covering set. In particular, we give bounds on the diameter if the quotient space is co-compact. Consequently, we show that these lattices admit small generators. Our tech

Valentin Rapenne

We study the asymptotic behaviour of the martingale ($\psi$ n (o)) n$\in$N associated with the Vertex Reinforced Jump Process (VRJP). We show that it is bounded in L p for every p > 1 on trees and uniformly integrable on Z d in all the transient phase of the VRJP. Moreover, when the VRJP is recurrent on trees, we have good estimates on the moments of $\psi$

José M. Mazón, Julián Toledo

In this paper we study a nonlocal Cahn-Hilliard model (CHE) in the framework of random walk spaces, which includes as particular cases, the CHE on locally finite weighted connected graphs, the CHE determined by finite Markov chains or the Cahn-Hilliard Equations driven by convolution integrable kernels. We consider different transitions for the phase and the

Yuan Zhong

We report a two-dimensional (2D) gravitating kink model, for which both the background field equations and the linear perturbation equation are exactly solvable. The background solution describes a sine-Gordon kink that interpolating between two asymptotic AdS$_2$ spaces, and can be regarded as a 2D thick brane world solution. The linear perturbation equatio

Sébastien Thévenin, Nicolas Valade, Benoit-Joseph Gréa, Gilles Kluth

We propose two-equations models in order to capture the dynamics of a turbulent plasma undergoing compression and experiencing large viscosity variations. The models account for possible relaminarization phases and rapid viscosity changes through closures dependent on the turbulent Reynolds and on the viscosity Froude numbers. These closures are determined f

Qihong Wu, Rongkun Liu, Zhanjun Qiu, Dengfeng Li

Two-dimensional ferromagnetic (FM) half-metals are promising candidates for advanced spintronic devices with small-size and high-capacity. Motivated by recent report on controlling synthesis of FM Cr$_3$Te$_4$ nanosheet, herein, to explore the potential application in spintronics, we designed spintronic devices based on Cr$_3$X$_4$ (X=Se, Te) monolayers and

Zhouzi Li, Zixuan Wang, Jian Li

Recent findings (e.g., arXiv:2103.00065) demonstrate that modern neural networks trained by full-batch gradient descent typically enter a regime called Edge of Stability (EOS). In this regime, the sharpness, i.e., the maximum Hessian eigenvalue, first increases to the value 2/(step size) (the progressive sharpening phase) and then oscillates around this valu

Pan Liu, Ariston Reis, Paulo J. S. Gonçalves

The paper proposes a novel medical device based on a 9 dof IMU to help health professionals performing more precisely the electrode placement task in EEG exams. The tool precisely tells the operator if the 10-20 electrode placement system is being correctly followed. The manual task is of major importance and time consuming, because all the electrodes must b

Liehong Liao, Ying Ding, Fei Wan, Jiayan Zhang

We study the band structure and transport properties of ferromagnetic tetragonal silicene nanoribbons by using the non-equilibrium Green's function method. The band structure and spin-dependent conductance are discussed under the combined effect of the external electric field, potential energy, exchange field and the spin-orbit coupling. One can easily reali