July 2022 arXiv papers — page 134

E. Boffo

In this short note we discuss N-supersymmetric worldlines of relativistic massless particles and review the known result that physical spin-N/2 fields are in the first BRST cohomology group. For N=1,2,4 emphasis is given to particular deformations of the BRST differential, that implement either a covariant derivative for a gauge theory or a metric connection

Riccardo W. Maffucci

We ask which degree sequences admit a unique realisation as a $3$-polytopal graph (polyhedron) on $p$ vertices. We give an exhaustive list of these sequences for the case where one degree equals $p-1$ and exactly two or three of them equal $3$. We also find all $3$-polytopes of radius one with $p\leq 17$, and those with $q\leq 41$ edges, by developing a fast

Weihan Cao, Yifan Zhang, Jianfei Gao, Anda Cheng

Knowledge distillation(KD) is a widely-used technique to train compact models in object detection. However, there is still a lack of study on how to distill between heterogeneous detectors. In this paper, we empirically find that better FPN features from a heterogeneous teacher detector can help the student although their detection heads and label assignment

Tatsuro Kishi, Takeshi Matsumoto, Sadayoshi Toh

We numerically investigate a two-time Lagrangian velocity correlation function (TTLVCF) for particle pairs in two-dimensional energy inverse-cascade turbulence. We consider self similarity of the correlation function by means of incomplete similarity. In this framework, we propose a self-similar form of the correlation function, whose scaling exponents canno

Raul Perea-Causin, Samuel Brem, Ermin Malic

Optical and transport properties of doped monolayer semiconductors are dominated by trions, which are three-particle compounds formed by two electrons and one hole or vice versa. In this work, we investigate the trion-phonon interaction on a microscopic footing and apply our model to the exemplary case of a molybdenum diselenide (MoSe2) monolayer. We determi

Tianle Zhang, Wenjie Ruan, Jonathan E. Fieldsend

In safety-critical deep learning applications robustness measurement is a vital pre-deployment phase. However, existing robustness verification methods are not sufficiently practical for deploying machine learning systems in the real world. On the one hand, these methods attempt to claim that no perturbations can ``fool'' deep neural networks (DNNs), which m

Benedek Gaál, Martin Arentoft Jacobsen, Luca Vannucci, Julien Claudon

An on-going challenge within scalable optical quantum information processing is to increase the collection efficiency $\varepsilon$ and the photon indistinguishability $\eta$ of the single-photon source towards unity. Within quantum dot-based sources, the prospect of increasing the product $\varepsilon \eta$ arbitrarily close to unity was recently questioned

Dimitri Gurevich, Varvara Petrova, Pavel Saponov

By using the notion of a quantum double we introduce analogs of partial derivatives on a Reflection Equation algebra, associated with a Hecke symmetry of GL(N) type. We construct the matrix L=MD, where M is the generating matrix of the Reflection Equation algebra and D is the matrix composed of the quantum partial derivatives and prove that the matrices M, D

Huayi Chen, Atsushi Moriwaki

We establish, in the setting of Arakelov geometry over adelic curves, an arithmetic Hilbert-Samuel theorem describing the asymptotic behaviour of the metrized graded linear series of an adelic line bundle in terms of its arithmetic intersection number. We then study positivity conditions of adelic line bundles.

Thomas Brougham, Daniel K. L. Oi

Terrestrial free-space quantum key distribution is ideally suited for deployment in dense urban environments. The transition from laboratory to commercial deployment, however, raises a number of important engineering and deployment issues. Here, we investigate these issues for efficient BB84 using a weak coherent pulse-decoy state protocol. We calculate expe

Zhe Li, Zerong Zheng, Hongwen Zhang, Chaonan Ji

To address the ill-posed problem caused by partial observations in monocular human volumetric capture, we present AvatarCap, a novel framework that introduces animatable avatars into the capture pipeline for high-fidelity reconstruction in both visible and invisible regions. Our method firstly creates an animatable avatar for the subject from a small number

Lucas Journel, Pierre Monmarché

We study the long-time convergence of a Fleming-Viot process, in the case where the underlying process is a metastable diffusion killed when it reaches some level set. Through a coupling argument, we establish the long-time convergence of the Fleming-Viot process toward some stationary measure at an exponential rate independent of $N$, the size of the system

Wadim Gerner

Aronszajn, Krzywicki and Szarski proved in \cite{AKS62} a strong unique continuation result for differential forms, satisfying a certain first order differential inequality, on Riemannian manifolds with empty boundary. The present paper extends this result to the setting of Riemannian manifold with non-empty boundary, assuming suitable boundary conditions on

Mohammad M. Amirian, Andrew J. Irwin, Zoe V. Finkel

Monod's model describes the growth of microorganisms using a hyperbolic function of extracellular resource concentration. Under fluctuating or limited resource concentrations this model performs poorly against experimental data, motivating the more complex Droop model with a time-varying internal storage pool. We extend the Monod model to incorporate memory

Hongyan Xu, Xiu Su, Dadong Wang

Deep learning technology can be used as an assistive technology to help doctors quickly and accurately identify COVID-19 infections. Recently, Vision Transformer (ViT) has shown great potential towards image classification due to its global receptive field. However, due to the lack of inductive biases inherent to CNNs, the ViT-based structure leads to limite

Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha

Big data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary constraints of analytical users. The RO problem is challenging because it involves a set of decisions (the partition count, placement of parallel instances on machines, and resource al

Ashish Tiwari, Shanmuganathan Raman

Photometric stereo, a problem of recovering 3D surface normals using images of an object captured under different lightings, has been of great interest and importance in computer vision research. Despite the success of existing traditional and deep learning-based methods, it is still challenging due to: (i) the requirement of three or more differently illumi

Zhaoyong Guan, Ziyuan An, Yuzheng Jiang, Ya Su

The Co$_2$Ge$_2$Te$_6$ shows intrinsic ferromagnetic (FM) order, which origins from superexchange interaction between Co and Te atoms, with higher Curie temperature ($T_c$) of 161 K. Co$_2$Ge$_2$Te$_6$ monolayer (ML) is half-metal (HM), and spin-$\beta$ electron is a semiconductor with gap of 1.311 eV. Co$_2$Ge$_2$Te$_6$ ML tends in-plane anisotropy (IPA), w

S. V. Feklistov

We study the Hartogs extension phenomenon in noncompact almost homogeneous algebraic varieties and we prove the cohomological and weight criteria for the Hartogs phenomenon. In the case of spherical varieties, we prove a criterion for the Hartogs phenomenon in terms of colored fans.

Geoffrey R. Grimmett

This article is an account of the scientific work of Hugo Duminil-Copin at the time of his award in 2022 of the Fields Medal "for solving longstanding problems in the probabilistic theory of phase transitions in statistical physics, especially in dimensions three and four''.

Fabian Wagner

In this work, we deepen the correspondence between Generalized Uncertainty Principles (GUPs) and quantum dynamics on curved momentum space. In particular, we investigate the linear and quadratic GUP. Similarly to earlier work, the resulting curvature tensor in the dual theory is proportional to the coordinate non-commutativity of the original formulation.

Hang Chen

In this paper, We find that the angular distribution of two-body decay and scattering process that can be studied by introducing the helicity method.It has been argued that the angular distribution only depends on magnitude of the decaying amplitude which final particle momentum is along the $Z$ axis. Therefore, when calculating the angular distribution,we o

Attila Gergely, Bulcsú Sándor, Csaba Paizs, Robert Tötös

Oscillation and collective behavior of diffusion flames is a fascinating phenomena. Considering candle bundles with different sizes in variable oxygen concentration, the flickering dynamics of the flames are experimentally and theoretically investigated. Trends for the flickering frequency as a function of the candle number in the bundle and oxygen concentra

Nicoletta Sanguini, Tommaso Benacchio, Daniele Malacrida, Federico Cipolletta

Rotorcraft technologies pose great scientific and industrial challenges for numerical computing. As available computational resources approach the exascale, finer scales and therefore more accurate simulations of engineering test cases become accessible. However, shifting legacy workflows and optimizing parallel efficiency and scalability of existing softwar

Morten Brun, Lars M. Salbu

We construct a simplicial complex, the rectangle complex of a relation R, and show that it is homotopy equivalent to the Dowker complex of R. This results in a short and conceptual proof of functorial versions of Dowker's Theorem used in topological data analysis.

X. Dai, R. Trappen, H. Chen, D. Melanson

Landau-Zener tunneling, which describes the transition in a two-level system during a sweep through an anti-crossing, is a model applicable to a wide range of physical phenomena. Realistic quantum systems are affected by dissipation due to coupling to their environments. An important aspect of understanding such open quantum systems is the relative energy sc

Yuan Zhang, Jianhong Wang, Joschka Boedecker

Reinforcement learning (RL) is recognized as lacking generalization and robustness under environmental perturbations, which excessively restricts its application for real-world robotics. Prior work claimed that adding regularization to the value function is equivalent to learning a robust policy with uncertain transitions. Although the regularization-robustn

Adam D. Barwell, Alceste Scalas, Nobuko Yoshida, Fangyi Zhou

Session types enable the specification and verification of communicating systems. However, their theory often assumes that processes never fail. To address this limitation, we present a generalised multiparty session type (MPST) theory with crash-stop failures, where processes can crash arbitrarily. Our new theory validates more protocols and processes w.r.t

Saul Acevedo, Alexander J. Stewart

Prion and prion-like molecules are a type of self replicating aggregate protein that have been implicated in a variety of neurodegenerative diseases. Over recent decades the molecular dynamics of prions have been characterized both empirically and through mathematical models, providing insights into the epidemiology of prion diseases, and the impact of prion

Jiahao Ma, Zicheng Duan, Liang Zheng, Chuong Nguyen

Multiview detection uses multiple calibrated cameras with overlapping fields of views to locate occluded pedestrians. In this field, existing methods typically adopt a ``human modeling - aggregation'' strategy. To find robust pedestrian representations, some intuitively incorporate 2D perception results from each frame, while others use entire frame features

Xiaoshang Jin

Following the work of Li-Shi-Qing, we propose the definition of the relative volume function for an AH manifold. It is not a constant function in general and we study the egularity of this function. We use this function to give an accurate characterization of the height of the geodesic defining function for the AH manifold with a given boundary metric. It is

Conghua Liu, Jin Wang

Based on the equations of state, one can infer the underlying interaction potentials among the black hole molecules in the case of Schwarzschild-AdS and charged AdS black holes. The microscopic molecules with the interaction potential arrange in a specific way to form the mesostructure, whose size is between the macro (black hole system) and the micro (black

Kevin F. Clancey

The family of Cauchy transforms \[C_{g}(z,w) = -\frac{1}{\pi}\int_{\mathbb{C} } \frac{g(u)}{\overline{u-w} (u-z) } da(u ),\] where the measurable function $g$ with compact (essential) support satisfies $0 \leq g\leq 1,$ and suitably defined for all complex $z, w,$ is closely connected to the theory of Hilbert space operators with one-dimensional self-commuta

Maria Kaselimi, Eftychios Protopapadakis, Athanasios Voulodimos, Nikolaos Doulamis

Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into its individual sub-components. Over the years, signal processing and machine learning algorithms have been combined to achieve this. A lot of publications and extensive research works are performed on energy disaggregation or NILM for the state-of-the-art meth

Mario Almagro, David Jiménez, Diego Ortego, Emilio Almazán

Product matching is a fundamental step for the global understanding of consumer behavior in e-commerce. In practice, product matching refers to the task of deciding if two product offers from different data sources (e.g. retailers) represent the same product. Standard pipelines use a previous stage called blocking, where for a given product offer a set of po

Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim

In this paper, we propose a novel benchmark called the StarCraft Multi-Agent Challenges+, where agents learn to perform multi-stage tasks and to use environmental factors without precise reward functions. The previous challenges (SMAC) recognized as a standard benchmark of Multi-Agent Reinforcement Learning are mainly concerned with ensuring that all agents

S. Metti, C. Thomas, D. Xiao, M. J. Manfra

InSb$_{1-x}$As$_{x}$ is a promising material system for exploration of topological superconductivity in hybrid superconductor/semiconductor devices due to large effective g-factor and enhanced spin-orbit coupling when compared to binary InSb and InAs. Much remains to be understood concerning the fundamental properties of the two-dimensional electron gas (2DE

E. I. Kats

In this work we present a simple qualitative model to describe shear rheological behavior of the twist-bend nematic liquid crystals. We find that at relatively low shear rate the effective viscosity decreases with the shear rate manifesting so-called shear-thinning phenomenon. At intermediate shear rate the stress is almost independent of the shear rate (a s

Mikhail Cherniavskii, Boris Goldengorin

As shown by Tang, Denardo [9] the job Sequencing and tool Switching Problem (SSP) can be decomposed into the following two problems. Firstly, the Tool Loading Problem (TLP) - for a given sequence of jobs, find an optimal sequence of magazine states that minimizes the total number of tool switches. Secondly, the Job Sequencing Problem (JeSP) - find a sequence

Nitin Gupta, Santosh Kumar Chaudhary

In the past six years, a considerable attention has been given to the extropy measure proposed by Lad et al. (2015). Weighted Extropy of Ranked Set Sampling was studied and compared with simple random sampling by Qiu et al. (2022). The general weighted extropy and some results related to it are introduced in this paper. We provide general weighted extropy of

Stefan G. Stanciu, Radu Hristu, George A. Stanciu, Denis E. Tranca

Second Harmonic Generation Microscopy (SHG) is generally acknowledged as a powerful tool for the label-free 3D visualization of tissues and advanced materials, with one of its most popular applications being collagen imaging. Although the great need, progress in super-resolved SHG imaging lags behind the developments reported over the past years in fluoresce

V. Schaffenroth, I. Pelisoli, B. N. Barlow, S. Geier

About a third of the hot subdwarfs of spectral type B, which are mostly core-helium burning objects on the extreme horizontal branch, are found in close binaries with cool, low-mass stellar, substellar, or white dwarf companions. They can show light variations due to different phenomena. We used light curves from the Transiting Exoplanet Survey Satellite and

Enzo Tartaglione, Francesca Gennari, Marco Grangetto

Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. However, little attention has been devoted to connected legal aspects. In 2016, the European Union approved the General Data Protection Regulation which entered into force in 2018. Its main rationale was to protect the privacy and data protection of its citizens

Vitonofrio Crismale, Simone Del Vecchio, Stefano Rossi

The concrete monotone $C^*$-algebra, that is the (unital) $C^*$-algebra generated by monotone independent algebraic random variables of Bernoulli type, is characterized abstractly in terms of generators and relations and is shown to be UHF. Moreover, its Bratteli diagram is explicitly given, which allows for the computation of its $K$-theory.

Jussi Behrndt, Markus Holzmann, Georg Stenzel

In this paper we study the spectrum of self-adjoint Schr\"odinger operators in $L^2(\mathbb{R}^2)$ with a new type of transmission conditions along a smooth closed curve $\Sigma\subseteq \mathbb{R}^2$. Although these $\textit{oblique}$ transmission conditions are formally similar to $\delta'$-conditions on $\Sigma$ (instead of the normal derivative here the

Clementa Alonso-González, Miguel Ángel Navarro-Pérez

Motzkin numbers have been widely studied since they count many different combinatorial objects. In this paper we present a new appearance of this remarkable sequence in the network coding setting through a particular case of multishot codes called flag codes. A flag code is a set of sequences of nested subspaces (flags) of a vector space over the finite fiel

Ge Zhang

Although neural networks can solve very complex machine-learning problems, the theoretical reason for their generalizability is still not fully understood. Here we use Wang-Landau Mote Carlo algorithm to calculate the entropy (logarithm of the volume of a part of the parameter space) at a given test accuracy, and a given training loss function value or train

Robert van Wijk, Andrea Michelle Rios Lazcano, Xabier Carrera Akutain, Barys Shyrokau

Modern Advanced Driver Assistance Systems (ADAS) are limited in their ability to consider the drivers intention, resulting in unnatural guidance and low customer acceptance. In this research, we focus on a novel data-driven approach to predict driver steering torque. In particular, driver behavior is modeled by learning the parameters of a Hidden Markov Mode

Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Multi-label classification is a challenging task, particularly in domains where the number of labels to be predicted is large. Deep neural networks are often effective at multi-label classification of images and textual data. When dealing with tabular data, however, conventional machine learning algorithms, such as tree ensembles, appear to outperform compet

Rahul Singh

Data depth provides a centre-outward ordering for multivariate data. Recently, some univariate GoF tests based on data depth have been studied by Li (2018). This paper discusses some univariate goodness of fit tests based on centre-outward spacings. These tests have similar asymptotic properties (distribution and efficiency) as those based on usual spacings.

Sebastian Szyller, N. Asokan

Nowadays, systems based on machine learning (ML) are widely used in different domains. Given their popularity, ML models have become targets for various attacks. As a result, research at the intersection of security/privacy and ML has flourished. Typically such work has focused on individual types of security/privacy concerns and mitigations thereof. However

Amit Kashi, Amir Michaelis, Yarden Kaminetsky

We carry out a numerical experiment of ejecting winds in a massive colliding wind binary system, and quantifying the accretion onto the secondary star under different primary mass loss rates. We set a binary system comprising a Luminous Blue Variable (LBV) as the primary and a Wolf-Rayet (WR) star as the secondary, and vary the mass loss rate of the LBV to o

Mojtaba Mirakhorlo, Nick Kluft, Barys Shyrokau, Riender Happee

Vibration transmission is essential in the design of comfortable vehicle seats but knowledge is lacking on 3D trunk and head motion and the role of seat back and posture. We hypothesized that head motion is reduced when participants upper back is unsupported, as this stimulates active postural control. We developed an experimental methodology to evaluate 3D

Yashvardhan Didwania, Jayakrishnan Nair, N. Hemachandra

We consider the problem of cost-optimal utilization of a crowdsourcing platform for binary, unsupervised classification of a collection of items, given a prescribed error threshold. Workers on the crowdsourcing platform are assumed to be divided into multiple classes, based on their skill, experience, and/or past performance. We model each worker class via a

Yuheng Lu, Chenfeng Xu, Xiaobao Wei, Xiaodong Xie

Current point-cloud detection methods have difficulty detecting the open-vocabulary objects in the real world, due to their limited generalization capability. Moreover, it is extremely laborious and expensive to collect and fully annotate a point-cloud detection dataset with numerous classes of objects, leading to the limited classes of existing point-cloud

Daria Drozdenko, Michal Knapek, Martin Kružík, Kristián Máthis

We formulate a large-strain model of single-slip crystal elastoplasticity in the framework of energetic solutions. Numerical performance of the model is compared with lab experiments on the compression of a stack of note papers.

Dan Wang, Jiayu Lin, Yuan-Gen Wang

In order to be applicable in real-world scenario, Boundary Attacks (BAs) were proposed and ensured one hundred percent attack success rate with only decision information. However, existing BA methods craft adversarial examples by leveraging a simple random sampling (SRS) to estimate the gradient, consuming a large number of model queries. To overcome the dra

Arnau Padrol, Eva Philippe, Francisco Santos

We show that for fixed $d>3$ and $n$ growing to infinity there are at least $(n!)^{d-2 \pm o(1)}$ different labeled combinatorial types of $d$-polytopes with $n$ vertices. This is about the square of the previous best lower bounds. As an intermediate step, we show that certain neighborly polytopes (such as particular realizations of cyclic polytopes) have at

Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang

The acquisition of the channel covariance matrix is of paramount importance to many strategies in multiple-input-multiple-output (MIMO) communications, such as the minimum mean-square error (MMSE) channel estimation. Therefore, plenty of efficient channel covariance matrix estimation schemes have been proposed in the literature. However, an abrupt change in

Yikun Mei, Zhen Gao, De Mi, Mingyu Zhou

Massive connectivity for extra large-scale multi-input multi-output (XL-MIMO) systems is a challenging issue due to the near-field access channels and the prohibitive cost. In this paper, we propose an uplink grant-free massive access scheme for XL-MIMO systems, in which a mixed-analog-to-digital converters (ADC) architecture is adopted to strike the right b

Najeeb Moharram Jebreel, Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia

Federated learning (FL) provides autonomy and privacy by design to participating peers, who cooperatively build a machine learning (ML) model while keeping their private data in their devices. However, that same autonomy opens the door for malicious peers to poison the model by conducting either untargeted or targeted poisoning attacks. The label-flipping (L

Giuseppe Gaeta, Miguel Angel Rodriguez

It is known that knowledge of a symmetry of a scalar Ito stochastic differential equations leads, thanks to the Kozlov substitution, to its integration. In the present paper we provide a classification of scalar autonomous Ito stochastic differential equations with simple noise possessing symmetries; here "simple noise" means the noise coefficient is of the

TAPS Collaboration, T. Seifen, J. Hartmann, F. Afzal

Measurements of target asymmetries and double-polarization observables for the reaction $\gamma p\to p\pi^0\pi^0$ are reported. The data were taken with the CBELSA/TAPS experiment at the ELSA facility (Bonn University) using the Bonn frozen-spin butanol (C$_4$H$_9$OH) target, which provided transversely polarized protons. Linearly polarized photons were prod

Konstantinos Karampelas, James A. McLaughlin, Gert J. J. Botha, Stéphane Régnier

Oscillatory reconnection can manifest through the interaction between the ubiquitous MHD waves and omnipresent null points in the solar atmosphere and is characterized by an inherent periodicity. In the current study, we focus on the relationship between the period of oscillatory reconnection and the strength of the wave pulse initially perturbing the null p

Mihai Marciu

The paper proposes a novel cosmological model based on a two-field scenario, where the two fields are independently coupled with a specific invariant, based on cubic contractions of the Riemann tensor. After obtaining the modified Friedmann equations and the specific Klein-Gordon relations, the investigation studies the corresponding physical features by ado

Jia Kan, Jie Zhang, Xin Huang

The development of blockchain applications increased the demand for blockchain performance. Among the attempts of many blockchain scale-out solutions, sharding can improve performance and reduce the storage requirements of each node. Sharding enhances the throughput of the entire blockchain. Most sharding solutions have a fixed number of shards. We propose W

Shu-Cheng Yang, Huijiao Luo, Yuan-Hao Zhang, Chen Zhang

In the Galaxy, extremely large mass-ratio inspirals(X-MRIs) composed of brown dwarfs and the massive black hole at the Galactic Center are expected to be promising gravitational wave sources for space-borne detectors. In this work, we simulate the gravitational wave signals from twenty X-MRI systems by an axisymmetric Konoplya-Rezzolla-Zhidenko metric with v

Erik Spånberg

Dynamic factor models are often estimated by point-estimation methods, disregarding parameter uncertainty. We propose a method accounting for parameter uncertainty by means of posterior approximation, using variational inference. Our approach allows for any arbitrary pattern of missing data, including different sample sizes and mixed frequencies. It also yie

Yasar Abbas Ur Rehman, Yan Gao, Jiajun Shen, Pedro Porto Buarque de Gusmao

The ubiquity of camera-enabled mobile devices has lead to large amounts of unlabelled video data being produced at the edge. Although various self-supervised learning (SSL) methods have been proposed to harvest their latent spatio-temporal representations for task-specific training, practical challenges including privacy concerns and communication costs prev

Denis Brazke, Hans Knüpfer, Anna Marciniak-Czochra

We derive a macroscopic limit for a sharp interface version of a model proposed in [29] to investigate pattern formation due to competition of chemical and mechanical forces in biomembranes. We identify sub- and supercrital parameter regimes and show with the introduction of the autocorrelation function that the ground state energy leads to the isoperimetric

Taylan Kabbani, Ekrem Duman

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with th

Mohammed Alaloul, Jacob B Khurgin, Ibrahim Al-Ani, Khalil As'ham

Monolayer transition metal dichalcogenides (TMDCs), like MoS$_2$, MoSe$_2$, WS$_2$, and WSe$_2$, feature direct bandgaps, strong spin-orbit coupling, and exciton-polariton interactions at the atomic scale, which could be harnessed for efficient light emission, valleytronics, and polaritonic lasing, respectively. Nevertheless, to build next-generation photoni

Agus Gunawan, Xu Yin, Kang Zhang

Various normalization layers have been proposed to help the training of neural networks. Group Normalization (GN) is one of the effective and attractive studies that achieved significant performances in the visual recognition task. Despite the great success achieved, GN still has several issues that may negatively impact neural network training. In this pape

Yan Zhao, Ruihai Wu, Zhehuan Chen, Yourong Zhang

It is essential yet challenging for future home-assistant robots to understand and manipulate diverse 3D objects in daily human environments. Towards building scalable systems that can perform diverse manipulation tasks over various 3D shapes, recent works have advocated and demonstrated promising results learning visual actionable affordance, which labels e

Siddharth Barman, Anand Krishna, Y. Narahari, Soumyarup Sadhukhan

We study coverage problems in which, for a set of agents and a given threshold $T$, the goal is to select $T$ subsets (of the agents) that, while satisfying combinatorial constraints, achieve fair and efficient coverage among the agents. In this setting, the valuation of each agent is equated to the number of selected subsets that contain it, plus one. The c

Mutsumi Sugizaki, Tatehiro Mihara, Kohei Kobayashi, Hitoshi Negoro

We report on the discovery of a new supergiant fast X-ray transient (SFXT), MAXI J0709$-$159, and its identification with LY CMa (also known as HD 54786). On 2022 January 25, a new flaring X-ray object named MAXI J0709$-$159, was detected by Monitor of All-sky X-ray Image (MAXI). Two flaring activities were observed in the two scans of $\sim 3$ hours apart,

Núria Salvador-Rusiñol, Anna Ferré-Mateu, Alexandre Vazdekis, Michael A. Beasley

Near-ultraviolet (NUV) spectroscopic studies have suggested that passively evolving massive, early-type galaxies host sub-one percent fractions of young stars in their innermost regions. We shed light on the origin of these stars by analysing NGC 1277, a widely studied nearby prototypical massive compact relic galaxy. These are rare galaxies that have surviv

El Mehdi Cherradi

We make use of a higher version of the Yoneda embedding to construct, from a given quasicategory, a tribe, as a subcategory of a well-behaved simplicial model category, that presents the same $(\infty,1)$-category as the former quasicategory. We then show that, when the quasicategory is locally cartesian closed, it is possible to further endow such a tribe w

Richard Healey

This paper compares and contrasts relational quantum mechanics (RQM) with a pragmatist view of quantum theory (DP). I'll first explain important points of agreement. Then I'll point to two problems faced by RQM and sketch DP's solutions to analogous problems. Since both RQM and DP have taken the Born rule to require relative facts I next say what these might

Bojan Magajna

We consider pairs of operators $A,B\in B(H)$, where $H$ is a Hilbert space, such that there exist a linear isometry $f$ from the span of $\{A,B\}$ into $\mathbb{C}^2$ mapping $A,B$ into orthonormal vectors. We prove some necessary conditions for the existence of such an $f$ and determine all such pairs among commuting normal operators. Then we characterize a

Fabian Kreppel, Christian Melzer, Diego Olvera Millán, Janis Wagner

The increasing capabilities of quantum computing hardware and the challenge of realizing deep quantum circuits require fully automated and efficient tools for compiling quantum circuits. To express arbitrary circuits in a sequence of native gates specific to the quantum computer architecture, it is necessary to make algorithms portable across the landscape o

Corentin Puffay, Jana Van Canneyt, Jonas Vanthornhout, Hugo Van Hamme

To investigate how speech is processed in the brain, we can model the relation between features of a natural speech signal and the corresponding recorded electroencephalogram (EEG). Usually, linear models are used in regression tasks. Either EEG is predicted, or speech is reconstructed, and the correlation between predicted and actual signal is used to measu

Abram Rodgers, Daniele Venturi

Explicit step-truncation tensor methods have recently proven successful in integrating initial value problems for high-dimensional partial differential equations (PDEs). However, the combination of non-linearity and stiffness may introduce time-step restrictions which could make explicit integration computationally infeasible. To overcome this problem, we de

Sobirjon Shoyimardonov

In this paper, we study discrete-time model of phytoplankton-zooplankton with Holling type II predator functional response. It is shown that Neimark-Sacker bifurcation occurs at the one of positive fixed points for certain parameter chosen as a bifurcation parameter. The existence and local stability of the positive fixed points of the model are proved. By c

Zhi Yang, Yadong Yan, Haitao Gan, Jing Zhao

In the semi-supervised learning field, Graph Convolution Network (GCN), as a variant model of GNN, has achieved promising results for non-Euclidean data by introducing convolution into GNN. However, GCN and its variant models fail to safely use the information of risk unlabeled data, which will degrade the performance of semi-supervised learning. Therefore,

Kastytis Zubovas, Jonas Bialopetravičius, Monika Kazlauskaitė

Large-scale outflows driven by active galactic nuclei (AGN) can have a profound influence on their host galaxies. The outflow properties themselves depend sensitively on the history of AGN energy injection during the lifetime of the outflow. Most observed outflows have dynamical timescales longer than the typical AGN episode duration, i.e. they have been inf

Z. Rapti, J. Cuevas-Maraver, E. Kontou, S. Liu

Metapopulation models have been a popular tool for the study of epidemic spread over a network of highly populated nodes (cities, provinces, countries) and have been extensively used in the context of the ongoing COVID-19 pandemic. In the present work, we revisit such a model, bearing a particular case example in mind, namely that of the region of Andalusia

Bojan Magajna

For a state $\omega$ on a C$^*$-algebra $A$ we characterize all states $\rho$ in the weak* closure of the set of all states of the form $\omega\circ\varphi$, where $\varphi$ is a map on $A$ of the form $\varphi(x)=\sum_{i=1}^na_i^*xa_i,$ $\sum_{i=1}^na_i^*a_i=1$ ($a_i\in A$, $n=1,2,...$). These are precisely the states $\rho$ that satisfy $\|\rho|J\|\leq\|\o

Jan Pachl

The embedding theorem of Roelcke and Dierolf for the completions of four standard uniform structures on topological groups and their quotients holds more generally for spaces of uniform measures. The natural mappings between the four spaces of uniform measures on a topological group are injective and their restrictions to positive cones are topological embed

Shunyu Liu, Kaixuan Chen, Na Yu, Jie Song

Despite the promising results achieved, state-of-the-art interactive reinforcement learning schemes rely on passively receiving supervision signals from advisor experts, in the form of either continuous monitoring or pre-defined rules, which inevitably result in a cumbersome and expensive learning process. In this paper, we introduce a novel initiative advis

Alastair Kay

When creating a quantum system whose natural dynamics provide useful computational operations, designers have two key tools at their disposal: the (constrained) choice of both the Hamiltonian and the the initial state of the system (an encoding). Typically, we fix the design, and utilise encodings post factum to tolerate experimental imperfections. In this p

Marco Marín-Suárez, Yuri A. Pashkin, Joonas T. Peltonen, Jukka P. Pekola

Accuracy of single-electron currents produced in hybrid turnstiles at high operation frequencies is, among other errors, limited by electrons tunnelling in the wrong direction. Increasing the barrier transparency between the island and the leads, and the source-drain bias helps to suppress these events in a larger frequency range, although they lead to some

Claudio Corianò, Paul H. Frampton

The most efficient way to extend the Standard Model of particle theory so that it accommodates the observed B anomalies is the hypothesis of a leptoquark which is a color-triplet weak-singlet boson with electric charge $Q=+\frac{2}{3}$. We point out that SU(15) grand unification with a scalar leptoquark in the adjoint representation gives a natural explanati

Jędrzej Garnek

In this note we study the associated adelic representation of a product of hyperelliptic Jacobians. We give a simple criterion that assures that this representation has maximal Galois image in a certain sense. As an application, we provide a method of constructing products of Jacobians with division fields as disjoint as they can be.

Z. Garofalaki, D. Kosmanos, S. Moschoyiannis, D. Kallergis

The increased use of smart Electric Vehicles (EVs) and Plug-in Electric Vehicles (PEV) opened a new area of research and development. The number of EV charging sites has considerably increased in residential as well as in public areas. Within these EV charging sites, various entities need to communicate in a secure and efficient way. The Open Charge Point Pr

Takuya Koriyama, Takeru Matsuda, Fumiyasu Komaki

This paper investigates the asymptotic properties of parameter estimation for the Ewens--Pitman partition with parameters $0<\alpha<1$ and $\theta>-\alpha$. Especially, we show that the maximum likelihood estimator (MLE) of $\alpha$ is $n^{\alpha/2}$-consistent and converges to a variance mixture of normal distributions, where the variance is governed by the

Dominik Harmim, Vladimír Marcin, Lucie Svobodová, Tomáš Vojnar

We present a novel scalable deadlock analyser L2D2 capable of handling C code with low-level unstructured lock manipulation. L2D2 runs along the call tree of a program, starting from its leaves, and analyses each function just once, without any knowledge of the call context. L2D2 builds function summaries recording information about locks that are assumed or

Elnaz Shafaei-Bajestan, Peter Uhrig, R. Harald Baayen

Distributional semantics offers new ways to study the semantics of morphology. This study focuses on the semantics of noun singulars and their plural inflectional variants in English. Our goal is to compare two models for the conceptualization of plurality. One model (FRACSS) proposes that all singular-plural pairs should be taken into account when predictin

P. Gavras, L. Rimoldini, K. Nienartowicz, G. Jevardat de Fombelle

Context. In the current ever increasing data volumes of astronomical surveys, automated methods are essential. Objects of known classes from the literature are necessary for training supervised machine learning algorithms, as well as for verification/validation of their results. Aims.The primary goal of this work is to provide a comprehensive data set of kno

G. V. Tushavin, A. I. Trifanov, E. V. Zaitseva

The eigenvalues of the complete commuting set of self-adjoint operators determine the classification of states. We construct a classification for the image of the Jordan-Schwinger mapping of the su(2) algebra. We use the ladder operator approach to construct a canonical basis of irreducible representations and define the self-adjoint operators of the complet