May 2022 arXiv papers — page 43

Arturas Acus, Adolfas Dargys

Formulas to calculate multivector exponentials in a base-free representation and in a orthonormal basis are presented for an arbitrary Clifford geometric algebra Cl(p,q). The formulas are based on the analysis of roots of characteristic polynomial of a multivector. Elaborate examples how to use the formulas in practice are presented. The results may be usefu

Yaoyao Zhong, Weihong Deng

While convenient in daily life, face recognition technologies also raise privacy concerns for regular users on the social media since they could be used to analyze face images and videos, efficiently and surreptitiously without any security restrictions. In this paper, we investigate the face privacy protection from a technology standpoint based on a new typ

M. Ghasemi-Nodehi, Fatemeh S. Tabatabaei, Mark Sargent, Eric J. Murphy

Resolved maps of the thermal and nonthermal radio continuum (RC) emission of distant galaxies are a powerful tool for understanding the role of the interstellar medium (ISM) in the evolution of galaxies. We simulate the RC surface brightness of present-day star forming galaxies in the past at $0.15<z<3$ considering two cases of radio size evolution: (1)~no e

Anastasiya Groznova, Ol'ga Sipacheva

An ultrafilter $p$ on $\omega$ is said to be discrete if, given any function $f\colon \omega \to X$ to any completely regular Hausdorff space, there is an $A \in p$ such that $f(A)$ is discrete. Basic properties of discrete ultrafilters are studied. Three intermediate classes of spaces $\mathscr R_1 \subset \mathscr R_2 \subset \mathscr R_3$ between the clas

Hendra I. Nurdin, Madalin Guţǎ

This paper gives an overview of parameter estimation and system identification for quantum input-output systems by continuous observation of the output field. We present recent results on the quantum Fisher information of the output with respect to unknown dynamical parameters. We discuss the structure of continuous-time measurements as solutions of the quan

Shantipriya Parida, Kalyanamalini Sahoo, Atul Kr. Ojha, Saraswati Sahoo

This paper presents the first publicly available treebank of Odia, a morphologically rich low resource Indian language. The treebank contains approx. 1082 tokens (100 sentences) in Odia selected from "Samantar", the largest available parallel corpora collection for Indic languages. All the selected sentences are manually annotated following the ``Universal D

Udai Prakash Tyagi, Partha Goswami

The aim of the paper is to study the electron spin direction dependence on momentum due to the presence of Rashba spin-orbit coupling in the pseudo-gap phase of Bi2212 bilayer. The non-trivial spin texture in k-space is found tuneable by electric field. The dependence is reported earlier by a group of workers in a spin- and angle-resolved photoemission spect

Hassnaa Akil, Nadia Idrissi Fatmi

Breast Cancer is a major public health problem and the most common diagnosed malignancy in woman. There have been significant developments in clinical approaches and theoretical experimental to understand the interactions of cancer cells dynamics with the immune system, also developments on analytical and computational models to help provide insights into cl

Yuan Wang, Huiling Song, Peng Huo, Tao Xu

Extreme multi-label text classification (XMTC) refers to the problem of tagging a given text with the most relevant subset of labels from a large label set. A majority of labels only have a few training instances due to large label dimensionality in XMTC. To solve this data sparsity issue, most existing XMTC methods take advantage of fixed label clusters obt

Hui Li, Ting Gao, Fengli Yan

We investigate tight monogamy relations of multiparty quantum entanglement for any quantum state in this paper. First, we obtain a class of lower bounds for multiparty quantum systems which improve the previous results. Next, we establish a class of tighter monogamy relations in tripartite quantum systems by means of the new inequality. Furthermore, we gener

Yuri Bazlov, Arkady Berenstein, Edward Jones-Healey, Alexander McGaw

We show that braided Cherednik algebras introduced by the first two authors are cocycle twists of rational Cherednik algebras of the imprimitive complex reflection groups $G(m,p,n)$, when $m$ is even. This gives a new construction of mystic reflection groups which have Artin-Schelter regular rings of quantum polynomial invariants. As an application of this r

Keisuke Suzuki

In this paper, we propose a weak approximation of the reflection coupling (RC) for stochastic differential equations (SDEs), and prove it converges weakly to the desired coupling. In contrast to the RC, the proposed approximate reflection coupling (ARC) need not take the hitting time of processes to the diagonal set into consideration and can be defined as t

Shunquan Huang, Cong Yu

Rossby wave instabilities (RWIs) usually lead to nonaxisymmetric vortices in protoplanetary discs and some observed sub-structures of these discs can be well explained by RWIs. We explore how the cooling influences the growth rate of unstable RWI modes in terms of the linear perturbation analysis. The cooling associated with the energy equation is treated in

José A. Carrillo, Pierre Roux, Susanne Solem

The existence and characterisation of noise-driven bifurcations from the spatially homogeneous stationary states of a nonlinear, non-local Fokker--Planck type partial differential equation describing stochastic neural fields is established. The resulting theory is extended to a system of partial differential equations modelling noisy grid cells. It is shown

Sanne G. M. van Velzen, Bob D. de Vos, Julia M. H. Noothout, Helena M. Verkooijen

Purpose: Coronary artery calcium (CAC) score, i.e. the amount of CAC quantified in CT, is a strong and independent predictor of coronary heart disease (CHD) events. However, CAC scoring suffers from limited interscan reproducibility, which is mainly due to the clinical definition requiring application of a fixed intensity level threshold for segmentation of

Shai Gretz, Assaf Toledo, Roni Friedman, Dan Lahav

The COVID-19 pandemic has made a huge global impact and cost millions of lives. As COVID-19 vaccines were rolled out, they were quickly met with widespread hesitancy. To address the concerns of hesitant people, we launched VIRA, a public dialogue system aimed at addressing questions and concerns surrounding the COVID-19 vaccines. Here, we release VIRADialogs

E. Rongione, O. Gueckstock, M. Mattern, O. Gomonay

Antiferromagnetic materials have been proposed as new types of narrowband THz spintronic devices owing to their ultrafast spin dynamics. Manipulating coherently their spin dynamics, however, remains a key challenge that is envisioned to be accomplished by spin-orbit torques or direct optical excitations. Here, we demonstrate the combined generation of broadb

Ippei Nagamachi

In the famous paper of Deligne and Mumford, they proved that a proper hyperbolic curve over a discrete valuation field has stable reduction if and only if the Jacobian variety of the curve has stable reduction in the case where the residue field of its valuation ring is algebraically closed. In the proof, the theory of minimal regular models played an import

Milagros Miceli, Julian Posada

Machine learning (ML) depends on data to train and verify models. Very often, organizations outsource processes related to data work (i.e., generating and annotating data and evaluating outputs) through business process outsourcing (BPO) companies and crowdsourcing platforms. This paper investigates outsourced ML data work in Latin America by studying three

Yanling Hao, Zhiyuan Shi, Yuanwei Liu

Human Activity Recognition (HAR) has recently received remarkable attention in numerous applications such as assisted living and remote monitoring. Existing solutions based on sensors and vision technologies have obtained achievements but still suffering from considerable limitations in the environmental requirement. Wireless signals like WiFi-based sensing

Akari Asai, Mohammadreza Salehi, Matthew E. Peters, Hannaneh Hajishirzi

This work introduces a new multi-task, parameter-efficient language model (LM) tuning method that learns to transfer knowledge across different tasks via a mixture of soft prompts-small prefix embedding vectors pre-trained for different tasks. Our method, called ATTEMPT (ATTEntional Mixtures of Prompt Tuning), obtains source prompts as encodings of large-sca

Konstantinos Tsouvalas

Let $\Gamma$ be a finitely generated group and $N$ be a normal subgroup of $\Gamma$. The fiber product of $\Gamma$ with respect to $N$ is the subgroup $\Gamma \times_N \Gamma=\{(\gamma, \gamma w): \gamma \in \Gamma, w \in N\}$ of the direct product $\Gamma \times \Gamma$. For every representation $\rho:\Gamma \times_N \Gamma \rightarrow \mathsf{GL}_d(k)$, wh

V. A. Gavrichkov, S. I. Polukeev

We have studied the superexchange interaction $J_{ij}$ in doped $2D$ cuprates. The AFM interaction strongly depends on the state of the lattice of a CuO$_2$ layer surrounded by two LaO rock salt layers. In a static $U$ and $D$ stripe nanostructure, the homogeneous AFM interaction is impossible due to the $U/D/U...$ periodic stripe sequence and $T_N=0$. In a

Md Hamid, M. A. H. Ahsan

We study two spinless bosons interacting via two-body Gaussian potential subjected to an externally impressed rotation about an axis confined in a harmonic trap in two-spatial dimensions. We obtain a transcendental equation for the relative angular momentum $|m|$ state with various values of the two-body interaction range $\sigma$ and the two-body interactio

Benjamin Voß, Michael Ruderman, Christoph Weise, Johann Reger

We consider the robust control of a two-mass oscillator with a dominant input delay. Our aim is to compare a fractional-order tuning approach including the partial compensation of non-minimum phase zeros with a classical H-infinity loop-shaping design, since both these designs lead to a relatively high controller order. First of all a detailed physical model

Oskar Allerbo, Rebecka Jörnsten

Most machine learning methods require tuning of hyper-parameters. For kernel ridge regression with the Gaussian kernel, the hyper-parameter is the bandwidth. The bandwidth specifies the length scale of the kernel and has to be carefully selected to obtain a model with good generalization. The default methods for bandwidth selection, cross-validation and marg

Andrés Felipe Ramos Padilla, Lingyu Wang, F. F. S. van der Tak, Scott Trager

Gas cooling processes in the interstellar medium (ISM) are key to understanding how star-formation processes occur in galaxies. Far-infrared (FIR) fine-structure emission lines can be used as a tool to understand the gas conditions and trace the different phases of the ISM. We model the most important far-infrared (FIR) emission lines throughout cosmic time

Lorenzo Tinacci, Aurele Germain, Stefano Pantaleone, Stefano Ferrero

The binding energies (BE) of molecules on the interstellar grains are crucial in the chemical evolution of the interstellar medium (ISM). Both temperature programmed desorption (TPD) laboratory experiments and quantum chemistry computations have often provided, so far, only single values of the BE for each molecule. This is a severe limitation, as the ices e

Mika Meitz, Pentti Saikkonen

In this paper, we consider subgeometric (specifically, polynomial) ergodicity of univariate nonlinear autoregressions with autoregressive conditional heteroskedasticity (ARCH). The notion of subgeometric ergodicity was introduced in the Markov chain literature in 1980s and it means that the transition probability measures converge to the stationary measure a

Jevgenija Rudzusika, Buda Bajić, Thomas Koehler, Ozan Öktem

Deep learning based computed tomography (CT) reconstruction has demonstrated outstanding performance on simulated 2D low-dose CT data. This applies in particular to domain adapted neural networks, which incorporate a handcrafted physics model for CT imaging. Empirical evidence shows that employing such architectures reduces the demand for training data and i

Zhiyao Luo, Hongnan Chen

Reconstructing materials in the real world has always been a difficult problem in computer graphics. Accurately reconstructing the material in the real world is critical in the field of realistic rendering. Traditionally, materials in computer graphics are mapped by an artist, then mapped onto a geometric model by coordinate transformation, and finally rende

Igor N. Karnaukhov

Within the framework of a mean-field approach the Mott-Hubbard phase transition is considered in the Hubbard and Falicov-Kimball models for half-filled occupation. It is shown that a static Z_2-field forms an insulator state on the lattice with a double cell, its strength is determined by the Hubbard interaction. An uniform configuration of the Z_2-field cor

Henri M. J. Boffin, Tereza Jerabkova, Giacomo Beccari, Long Wang

Understanding the exact extent and content of tidal tails of open clusters provide useful clues on how field stars populate the Milky Way. We reanalyse, using Gaia EDR3 data, the tails around the open cluster NGC 752. Compared to previous analyses, we look at a much wider region around the cluster and use first the convergent point method, coupled with a clu

Sai Sagar Jinka, Astitva Srivastava, Chandradeep Pokhariya, Avinash Sharma

Recent advancements in deep learning have enabled 3D human body reconstruction from a monocular image, which has broad applications in multiple domains. In this paper, we propose SHARP (SHape Aware Reconstruction of People in loose clothing), a novel end-to-end trainable network that accurately recovers the 3D geometry and appearance of humans in loose cloth

Kayson Fakhar, Fatemeh Hadaeghi, Claus C. Hilgetag

Echo State Networks (ESN) are versatile recurrent neural network models in which the hidden layer remains unaltered during training. Interactions among nodes of this static backbone produce diverse representations of the given stimuli that are harnessed by a read-out mechanism to perform computations needed for solving a given task. ESNs are accessible model

Alberto Guandalini, Pino D'Amico, Andrea Ferretti, Daniele Varsano

Many-body perturbation theory methods, such as the $G_0W_0$ approximation, are able to accurately predict quasiparticle (QP) properties of several classes of materials. However, the calculation of the QP band structure of two-dimensional (2D) semiconductors is known to require a very dense BZ sampling, due to the sharp $q$-dependence of the dielectric matrix

Yanling Hao, Zhiyuan Shi, Xidong Mu, Yuanwei Liu

WiFi-based human action recognition (HAR) has been regarded as a promising solution in applications such as smart living and remote monitoring due to the pervasive and unobtrusive nature of WiFi signals. However, the efficacy of WiFi signals is prone to be influenced by the change in the ambient environment and varies over different sub-carriers. To remedy t

A. G. Campos, Luca Fabbri

The Relativistic Dynamical Inversion technique, a novel tool for finding analytical solutions to the Dirac equation, is written in explicitly covariant form. It is then shown how the technique can be used to make a change from Cartesian to spherical coordinates of a given Dirac spinor. Moreover the most remarkable feature of the new method, which is the ease

Paulo Debiagi, Rodolfo Cavaliere da Rocha, Arne Scholtissek, Johannes Janicka

As a result of the 2021 United Nations Climate Change Conference (COP26), several countries committed to phasing down coal electricity as soon as possible, deactivating hundreds of power plants in the near future. CO$_2$-free electricity can be generated in these plants by retrofitting them for iron combustion. Iron oxides produced during the process can be

Hiroshi Kihara

We formulate and study the notion of $d$-skeletal diffeology, which generalizes that of wire diffeology, introducing the dual notion of $d$-coskeletal diffeology. We first show that paracompact finite-dimensional $C^\infty$-manifolds $M_d$ with $d$-skeletal diffeology inherit good topologies and smooth paracompactness from $M$. We then study the pathology of

Mark Chambers, Christopher Drovandi

Studies of alcohol and drug use are often interested in the number of days that people use the substance of interest over an interval, such as 28 days before a survey date. Although count models are often used for this purpose, they are not strictly appropriate for this type of data because the response variable is bounded above. Furthermore, if some peoples

Luigi Quaranta

The massive trend of integrating data-driven AI capabilities into traditional software systems is rising new intriguing challenges. One of such challenges is achieving a smooth transition from the explorative phase of Machine Learning projects - in which data scientists build prototypical models in the lab - to their production phase - in which software engi

Da Zhang, David Barral, Yanpeng Zhang, Min Xiao

Triple-photon states generated by three-mode spontaneous parametric down-conversion are the paradigm of unconditional non-Gaussian states, essential assets for quantum advantage. How to fully characterize their non-Gaussian entanglement remains however elusive. We propose here a hierarchy of sufficient and necessary conditions for separability of the broad f

Bugra Caskurlu, Fatih Erdem Kizilkaya

Hedonic games are a prominent model of coalition formation, in which each agent's utility only depends on the coalition she resides. The subclass of hedonic games that models the formation of general partnerships, where output is shared equally among affiliates, is referred to as hedonic games with common ranking property (HGCRP). Aside from their economic m

LISA Pathfinder Collaboration

We present an in depth analysis of the transient events, or glitches, detected at a rate of about one per day in the differential acceleration data of LISA Pathfinder. We show that these glitches fall in two rather distinct categories: fast transients in the interferometric motion readout on one side, and true force transient events on the other. The former

Lais Soares Lavra

This document presents eight recent and new analyses from the LHCb experiment covering results on CKM angle $\gamma$ and high precision measurements on charm mixing parameters. In addition, the latest CP violation measurements in charm and beauty decays are reported.

Julian Lopez-Gomez, Pierpaolo Omari

A refined version of the strong maximum principle is proven for a class of second order ordinary differential equations with possibly discontinuous non-monotone nonlinearities. Then, exploiting this tool, some optimal regularity results recently established by Lopez-Gomez and Omari, for the bounded variation solutions of non-autonomous quasilinear equations

Roman Walch, Samuel Sousa, Lukas Helminger, Stefanie Lindstaedt

Big data has been a pervasive catchphrase in recent years, but dealing with data scarcity has become a crucial question for many real-world deep learning (DL) applications. A popular methodology to efficiently enable the training of DL models to perform tasks in scenarios with low availability of data is transfer learning (TL). TL allows to transfer knowledg

Luigi Quaranta, Fabio Calefato, Filippo Lanubile

Jupyter Notebook is the tool of choice of many data scientists in the early stages of ML workflows. The notebook format, however, has been criticized for inducing bad programming practices; indeed, researchers have already shown that open-source repositories are inundated by poor-quality notebooks. Low-quality output from the prototypical stages of ML workfl

Ido Efrat

For a prime number $p$ and a free pro-$p$ group $G$ on a totally ordered basis $X$, we consider closed normal subgroups $G^\Phi$ of $G$ which are generated by $p$-powers of iterated commutators associated with Lyndon words in the alphabet $X$. We express the profinite cohomology group $H^2(G/G^\Phi)$ combinatorically, in terms of the shuffle algebra on $X$.

S. Sarkar, F. Cossu, P. Kumari, A. G. Moghaddam

In this work, we report on an $ab-initio$ computational study of the electronic and magnetic properties of transition metal adatoms on a monolayer of NbSe$_2$. We demonstrate that Cr, Mn, Fe and Co prefer all to sit above the Nb atom, where the $d$ states experience a substantial hybridization. The inter-atomic exchange coupling is shown to have an oscillato

Juan De Gregorio, David Sanchez, Raul Toral

We investigate the memory properties of discrete sequences built upon a finite number of states. We find that the block entropy can reliably determine the memory for systems modeled as Markov chains of arbitrary finite order. Further, we provide an entropy estimator that remarkably gives accurate results when correlations are present. To illustrate our findi

Kawin Ethayarajh, Dan Jurafsky

Human ratings are the gold standard in NLG evaluation. The standard protocol is to collect ratings of generated text, average across annotators, and rank NLG systems by their average scores. However, little consideration has been given as to whether this approach faithfully captures human preferences. Analyzing this standard protocol through the lens of util

Maximilian Kiessler, Valentin Haag, Benedikt Pittl, Erich Schikuta

Today's cloud infrastructure landscape offers a broad range of services to build and operate software applications. The myriad of options, however, has also brought along a new layer of complexity. When it comes to procuring cloud computing resources, consumers can purchase their virtual machines from different providers on different marketspaces to form so

Jürg Fröhlich

After recalling some puzzles in cosmology and briefly reviewing the Friedmann-Lema\^itre cosmos a simple unified model of the ``Dark Sector'' is described. This model involves a scalar field and a pseudo-scalar axion field that give rise to Dark Energy in the form of ``quintessence'' and to ``fuzzy'' Dark Matter, respectively. Predictions of the model concer

Xin He, Zhihao Gong, Baihua Wu, Jian Liu

The celebrated Meyer-Miller mapping model has been a useful approach for generating practical trajectory-based nonadiabatic dynamics methods. It is generally assumed that the zero-point-energy (ZPE) parameter is positive. The constraint implied in the conventional Meyer-Miller mapping Hamiltonian for an F-electronic-state system actually requires that parame

B. A. Jacobs

Partial differential equations have recently garnered substantial attention as an image processing framework due to their extensibility, the ability to rigorously engineer and analyse the governing dynamics as well as the ease of implementation using numerical methods. This paper explores a novel approach to image trinarization with a concrete real-world app

Minghui Li, Wei Wang, Zikang Tang, Hou Ian

A scheme to encode arbitrarily long integer pairs on degenerate optical parametric oscillations multiplexed in time is proposed. The classical entanglement between the polarization directions and the phases of the oscillating pulses, regarded as two computational registers, furnishes the integer correlations within each pair. We show the major algorithmic st

Aldi Piroli, Vinzenz Dallabetta, Marc Walessa, Daniel Meissner

Adverse weather conditions can negatively affect LiDAR-based object detectors. In this work, we focus on the phenomenon of vehicle gas exhaust condensation in cold weather conditions. This everyday effect can influence the estimation of object sizes, orientations and introduce ghost object detections, compromising the reliability of the state of the art obje

Adrien Le Boudec, Nicolás Matte Bon

Given a finitely generated group $G$, we are interested in common geometric properties of all graphs of faithful actions of $G$. In this article we focus on their growth. We say that a group $G$ has a Schreier growth gap $f(n)$ if every faithful $G$-set $X$ satisfies $\mathrm{vol}_{G, X}(n)\succcurlyeq f(n)$, where $\mathrm{vol}_{G, X}(n)$ is the growth of t

Jessica Illiano, Michele Viscardi, Seid Koudia, Marcello Caleffi

Multipartite entanglement plays a crucial role for the design of the Quantum Internet, due to its potentiality of significantly increasing the network performance. In this paper, we design an entanglement access control protocol for multipartite state, which exhibits several attractive features. Specifically, the designed protocol is able to jointly extract

Yan Sun, Bo Zhang, Mark J. Reid, Shuangjing Xu

We report VLBA observations of 22 GHz H$_{2}$O and 43 GHz SiO masers toward the Mira variable RR Aql. By fitting the SiO maser emission to a circular ring, we estimate the absolute stellar position of RR Aql and find agreement with Gaia astrometry to within the joint uncertainty of $\approx1$ mas. Using the maser astrometry we measure a stellar parallax of 2

Max Zimmer, Christoph Spiegel, Sebastian Pokutta

Many existing Neural Network pruning approaches rely on either retraining or inducing a strong bias in order to converge to a sparse solution throughout training. A third paradigm, 'compression-aware' training, aims to obtain state-of-the-art dense models that are robust to a wide range of compression ratios using a single dense training run while also avoid

Honglei Li, Huayang Song, Shufang Su, Wei Su

The high precision measurements of the Higgs mass and couplings at the future Higgs factories are sensitive to the parameter space of the Minimal Supersymmetric Standard Model (MSSM). Focused on the dominant stop sector contributions, we study the implication of the Higgs precision measurements on MSSM using multi-variable $\chi^2$ fit. The results show nice

Tomohiro Abe, Yu Hamada

A model of the pseudo-Nambu-Goldstone (pNG) dark matter (DM) is proposed. We assume that there is an $SU(2)_g$ global symmetry and a $U(1)_X$ gauge symmetry in the dark sector, and they are spontaneously broken into a $U(1)_D$ global symmetry after a scalar field develops a vacuum expectation value. We add a soft symmetry breaking term that breaks the $SU(2)

Riccardo Di Dio, Michaël Brunengo, Benjamin Mauroy

We develop a mathematical model of the lung that can estimate independently the air flows and pressures in the upper bronchi. It accounts for the lung multi-scale properties and for the air-tissue interactions. The model equations are solved using the Discrete Fourier Transform, which allows quasi instantaneous solving, in the limit of the model hypotheses.

Yuhan Li, Wei Shen, Jianbo Gao, Yadong Wang

Community Question Answering (CQA) platforms contain plenty of CQA texts (i.e., questions and answers corresponding to the question) where named entities appear ubiquitously. In this paper, we define a new task of CQA entity linking (CQAEL) as linking the textual entity mentions detected from CQA texts with their corresponding entities in a knowledge base. T

Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo

Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars. Notably, chain of thought (CoT) prompting, a recent technique for eliciting complex multi-step reasoning through step-by-step answer examples, achieved the state-of-th

Muhammad Salman Khan, Adnan Ahmad, Muhammad Humayoun

Assessments help in evaluating the knowledge gained by a learner at any specific point as well as in continuous improvement of the curriculum design and the whole learning process. However, with the increase in students' enrollment at University level in either conventional or distance education environment, traditional ways of assessing students' work are b

Lang Qian, Shengjie Zheng, Chunshan Deng, Cheng Yang

Brain-computer interfaces (BCIs), is ways for electronic devices to communicate directly with the brain. For most medical-type brain-computer interface tasks, the activity of multiple units of neurons or local field potentials is sufficient for decoding. But for BCIs used in neuroscience research, it is important to separate out the activity of individual ne

Wei Gao, Qinghao Hu, Zhisheng Ye, Peng Sun

Deep learning (DL) shows its prosperity in a wide variety of fields. The development of a DL model is a time-consuming and resource-intensive procedure. Hence, dedicated GPU accelerators have been collectively constructed into a GPU datacenter. An efficient scheduler design for such GPU datacenter is crucially important to reduce the operational cost and imp

Masanobu Horie, Naoto Mitsume

Graph neural network (GNN) is a promising approach to learning and predicting physical phenomena described in boundary value problems, such as partial differential equations (PDEs) with boundary conditions. However, existing models inadequately treat boundary conditions essential for the reliable prediction of such problems. In addition, because of the local

Chengbo Zheng, Xiaojuan Ma

Misinformation has disruptive effects on our lives. Many researchers have looked into means to identify and combat misinformation in text or data visualization. However, there is still a lack of understanding of how misinformation can be introduced when text and visualization are combined to tell data stories, not to mention how to improve the lay public's a

Przemysław Gawroński, Alfio Borzì, Krzysztof Kułakowski

The system of two resources $R_1$, $R_2$ and one consumer $C$ is investigated within the Rosenzweig-MacArthur model with Holling type II functional response. The rates $\beta_i$ of consumption of resources $i=1,2$ are coupled by the condition $\beta_1+\beta_2=1$. The dynamic switching is introduced by a maximization of $C$: $d\beta_1/dt=(1/\tau) dC/d\beta_1$

Amit Kumar, Debasisha Mishra

If $a$ and $b$ are a pair of invertible elements, then $ab$ is also invertible and the inverse of the product $ab$ satisfying $$(ab)^{-1}=a^{-1}b^{-1}$$ is known as the {\it forward-order law}. This article establishes a few sufficient conditions of the forward-order law for the core inverse of elements in rings with involution. It also presents the forward-

Siddhartha

In recent years neural networks have achieved state-of-the-art accuracy for various tasks but the the interpretation of the generated outputs still remains difficult. In this work we attempt to provide a method to understand the learnt weights in the final fully connected layer in image classification models. We motivate our method by drawing a connection be

Sofie Marie Koksbang, Asta Heinesen

We consider the redshift drift and position drift associated with astrophysical sources in a formalism that is suitable for describing emitters and observers of light in an arbitrary spacetime geometry, while identifying emitters of a given null-geodesic bundle that arrives at the observer worldline. We then restrict the situation to the special case of a Le

Erjuan Fu

Let $S$ be a complex projective surface. Lefschetz originally proved Lefschetz $(1, 1)$--Theorem by studying a Lefschetz pencil of hyperplane sections of $S$ and the Abel--Jacobi mapping. In this paper, we attack Lefschetz $(1, 1)$--Theorem by constructing certain two-parameter families of twice hyperplane sections of $S$ and then applying the topological Ab

Franz Kamutzki, Sven Schneider, Maged Bekeet, A Gurlo

This study aims to shed light on processing pathways towards functional silicate ceramics, which show some promise in various emerging applications, including dielectrics and bioactive implant materials. Polycrystalline silicate ceramics of Neso, Soro and Inosilicate families were synthesised by three different techniques: (i) a co-precipitation method, (ii)

Tamás Varga

We introduce the quantum-house effect, a non-local phenomenon which apparently does not require quantum discord to be present. It suffices for the effect if neither subsystem of a bipartite system is in a pure state. This way, the quantum-house effect completely fills the gap between trivial correlations and quantum discord. However, we discuss why the situa

Rui Yang, Ercai Chen, Xiaoyao Zhou

Firstly, we answer the problem 1 asked by Gutman and $\rm \acute{\ S}$piewak in \cite{gs20}, then we establish a double variational principle for mean dimension in terms of R$\bar{e}$nyi information dimension and show the order of $\sup$ and $\limsup$ (or $\liminf$) of the variational principle for the metric mean dimension in terms of R$\bar{e}$nyi informat

Tomás Manzaneque, Murali K. Ghatkesar, Farbod Alijani, Minxing Xu

The resolution of resonant sensors is fundamentally limited by the presence of noise. Thermomechanical noise, intrinsic to the resonator, sets the ultimate sensor performance when all other noise sources have been eliminated. For linear resonators, the sensing resolution can always be further improved by increasing the driving power. However, this trend cann

Tommaso Polonelli, Hanna Müller, Weikang Kong, Raphael Fischer

This paper presents a low-power, self-sustainable, and modular wireless sensor node for aerodynamic and acoustic measurements on wind turbines and other industrial structures. It includes 40 high-accuracy barometers, 10 microphones, 5 differential pressure sensors, and implements a lossy and a lossless on-board data compression algorithm to decrease the tran

Elisabeth Zeyen, Marta Victoria, Tom Brown

Many studies have shown that hydrogen could play a large role in the energy transition for hard-to-electrify sectors, but previous modelling has not included the necessary features to assess its role. They have either left out important sectors of hydrogen demand, ignored the temporal variability in the system or neglected the dynamics of learning effects. W

Wenlong Li, Xue Dong, Guofeng Zhang, Re-Bing Wu

The control of flying qubits is at the core of quantum networks. As often carried by single-photon fields, the flying-qubit control involves not only their logical states but also their shapes. In this paper, we explore a variety of flying-qubit control problems using a three-level atom with time-varying tunable couplings to two input-output channels. It is

Akash Garg, Ranjeev Misra, Somasri Sen

Previous analysis of AstroSat observations of the black hole system MAXI J1535-571, have revealed the presence of a strong Quasi-Periodic Oscillation (QPO) whose frequency is correlated with the high energy spectral index. Here, we fit the spectra as emitted from a truncated disc with an inner hot corona, study the QPO frequency dependence on other spectral

Zhenhe Cui, Weidu Kuang, Yongmei Liu

Generalized planning studies the computation of general solutions for a set of planning problems. Computing general solutions with correctness guarantee has long been a key issue in generalized planning. Abstractions are widely used to solve generalized planning problems. Solutions of sound abstractions are those with correctness guarantees for generalized p

Serge Kernbach

This paper briefly describes the device - the phytosensor - for measuring physiological and electrophysiological parameters of plants. This system is developed as a bio-physiological sensor in precise agriculture, as a tool in plant research and environmental biology, and for plant enthusiasts in smart home or entertainment applications. The phytosentor meas

Peter Kaiser

The aim of this paper is to determine the asymptotic growth rate of the complexity function of cut-and-project sets in the non-abelian case. In the case of model sets of polytopal type in homogeneous two-step nilpotent Lie groups we can establish that the complexity function asymptotically behaves like $r^{homdim(G) dim(H)}$. Further we generalize the concep

Eduardo B. Molinero, Rui E. F. Silva

The use of intense tailored light fields is the perfect tool to achieve ultrafast control of electronic properties in quantum materials. Among them, Mott insulators are materials in which strong electron-electron interactions drive the material into an insulating phase. When shinning a Mott insulator with a strong laser pulse, the electric field may induce t

Hala Ajmi, Fakhreddine Zayer, Amira Hadj Fredj, Belgacem Hamdi

The paper proposes in-memory computing (IMC) solution for the design and implementation of the Advanced Encryption Standard (AES) based cryptographic algorithm. This research aims at increasing the cyber security of autonomous driverless cars or robotic autonomous vehicles. The memristor (MR) designs are proposed in order to emulate the AES algorithm phases

Yuqi Xu, Weihua Yang

Let $V_{8}+e$ denote the unique graph obtained from the Wagner graph, also known as $V_{8}$, by adding an edge between two vertices of distance 3 on the Hamilton cycle, which is exactly a split of a minor of the Petersen graph. A complete characterization of all internally 4-connected graphs with no $V_{8}$ minor is given in [J. Maharry and N. Robertson, The

Çağatay Yıldız, Melih Kandemir, Barbara Rakitsch

We study time uncertainty-aware modeling of continuous-time dynamics of interacting objects. We introduce a new model that decomposes independent dynamics of single objects accurately from their interactions. By employing latent Gaussian process ordinary differential equations, our model infers both independent dynamics and their interactions with reliable u

Alessio Squarcini, Enzo Marinari, Gleb Oshanin, Luca Peliti

We investigate the stochastic behavior of the single-trajectory spectral density $S(\omega,\mathcal{T})$ of several Gaussian stochastic processes, i.e., Brownian motion, the Ornstein-Uhlenbeck process, the Brownian gyrator model and fractional Brownian motion, as a function of the frequency $\omega$ and the observation time $\mathcal{T}$. We evaluate in part

Guojun Yang

Every Finsler metric naturally induces a spray but not so for the converse. The notion for sprays of scalar (resp. isotropic) curvature has been known as a generalization for Finsler metrics of scalar (resp. isotropic) flag curvature. In this paper, a new notion, sprays of constant curvature, is introduced and especially it shows that a spray of isotropic cu

P. Prelovšek, S. Nandy, Z. Lenarčič, M. Mierzejewski

The anomalous spin diffusion of the integrable easy-axis Heisenberg chain originates in the ballistic transport of symmetry sectors with nonzero magnetization. Ballistic transport is replaced by normal dissipative transport in all magnetization sectors upon introducing the integrability-breaking perturbations, including external driving. Such behavior implie

Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman

Driven by several successful applications such as in stochastic gradient descent or in Bayesian computation, control variates have become a major tool for Monte Carlo integration. However, standard methods do not allow the distribution of the particles to evolve during the algorithm, as is the case in sequential simulation methods. Within the standard adapti

Gabriele Sbaiz

In the present thesis, we are interested in the description of the dynamics of flows on large scales. In this context, the fluids are governed by rotational, weak compressibility and stratification effects, whose importance is measured by adimensional numbers: the Rossby, Mach and Froude numbers. The first part of the thesis is dedicated to the analysis of a

Zixian Su, Kai Yao, Xi Yang, Qiufeng Wang

Unsupervised cross-modality medical image adaptation aims to alleviate the severe domain gap between different imaging modalities without using the target domain label. A key in this campaign relies upon aligning the distributions of source and target domain. One common attempt is to enforce the global alignment between two domains, which, however, ignores t

Yinhe Zheng, Guanyi Chen

We have noticed that Marek et al. (2021) try to re-implement our paper Zheng et al. (2020a) in their work "OodGAN: Generative Adversarial Network for Out-of-Domain Data Generation". Our paper proposes a model to generate pseudo OOD samples that are akin to IN-Domain (IND) input utterances. These pseudo OOD samples can be used to improve the OOD detection per