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Optimization of escape kinetics by reflecting and resetting

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arXiv 2023年

作者： Capala, Karol Dybiec, Bartlomiej Personal Health Data Science Group Sano - Centre for Computational Personalised Medicine Czarnowiejska 36 Kraków30-054 Poland Institute of Theoretical Physics Mark Kac Center for Complex Systems Research Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Lojasiewicza 11 Kraków30-348 Poland

Stochastic restarting is a strategy of starting anew. Incorporation of the resetting to the random walks can result in the decrease of the mean first passage time, due to the ability to limit unfavorably meandering, sub-optimal trajectories. In the following manuscript, we examine how stochastic resetting influences escape dynamics from the (−∞, 1) interval in the presence of the single-well power-law |x|κ potentials with κ > 0. Examination of the mean first passage time is complemented by the analysis of the coefficient of variation, which provides a robust and reliable indicator assessing efficiency of stochastic resetting. The restrictive nature of resetting is compared to placing a reflective boundary in the system at hand. In particular, for each potential, the position of the reflecting barrier giving the same mean first passage time as the optimal resetting rate is determined. Finally, in addition to reflecting, we compare effectiveness of other resetting strategies with respect to optimization of the mean first passage time. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

Ground-based and additional science support for SMILE

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Earth and Planetary physics 2024年第1期8卷 275-298页

作者： J.A.Carter M.Dunlop C.Forsyth K.Oksavik E.Donovon A.Kavanagh S.E.Milan T.Sergienko R.C.Fear D.G.Sibeck M.Connors T.Yeoman X.Tan M.G.G.T.Taylor K.McWilliams J.Gjerloev R.Barnes D.D.Billet G.Chisham A.Dimmock M.P.Freeman D.-S.Han M.D.Hartinger S.-Y.W.Hsieh Z.-J.Hu M.K.James L.Juusola K.Kauristie E.A.Kronberg M.Lester J.Manuel J.Matzka I.McCrea Y.Miyoshi J.Rae L.Ren F.Sigernes E.Spanswick K.Sterne A.Steuwer T.Sun M.-T.Walach B.Walsh C.Wang J.Weygand J.Wild J.Yan J.Zhang Q.-H.Zhang Planetary Sciences Group School of Physics and AstronomyUniversity of LeicesterUniversity RoadLeicesterLE17RHUK Rutherford Appleton Laboratory Space Science Technology Facilities CouncilOxfordshireUK School of Space and Environment Beihang UniversityBeijing 100191China Key Laboratory of Space Environment Monitoring and Information Processing Ministry of Industry and Information TechnologyBeijing 100017China Department of Space and Climate Physics UCLMullard Space Science LaboratoryHolmbury St.MaryDorkingSurreyRH56NTUK Birkeland Centre for Space Science Department of Physics and Technology.University of BergenBergenNorway Department of Physics and Astronomy University of Calgary2500 University DriveCalgaryAlbertaCanada T2N 1N4 British Antarctic Survey CambridgeUK Swedish Institute of Space Physics KirunaSweden West Highfield Campus University of SouthamptonUniversity RoadSO171BJUK Goddard Space Flight Center NASAGreenbeltMarylandUSA Athabasca University AthabascaCanada ESTEC European Space AgencyNetherlands University of Saskatchewan SaskatoonCanada The Johns Hopkins University Applied Physics Laboratory LaurelMarylandUSA Swedish Institude of Space Physics UppsalaSE 75121Sweden Tongji University Shanghai 200092China Center for Space Plasma Physics Space Science Institute4765 Walnut Street Suite BBoulderColorado80301USA Polar Research Institute of China Shanghai 200136China Finnish Meteorological Institute(FMI) Finland Department of Earth and Environmental Sciences(Geophysics) Ludwig Maximilian University of Munich(LMU)MunichTheresienstr.41MunichD-80333Germany Canadian Space Agency MontrealCanada GFZ German Research Centre for Geosciences PotsdamGermany Nagoya University Institute for Space Earth Environment ResearchCenter for Integrated Data ScienceNagoyaAichiJP 464-8601 Northumbria University Newcastle upon TyneTyne and WearUK NE18ST National Space Science Center Chinese Academy SciencesBeijing 100190China Arctic Geophysics University Centre in Svalbard

The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere *** these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE ***,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these *** include constructing an online SMILE data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft *** anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.

关键词： magnetosphere ionosphere magnetosphere-ionosphere coupling ground-based experimentation SMILE conjunctions missions

Machine-learning interatomic potential for molecular dynamics simulation of ferroelectric KNbO3 perovskite

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arXiv 2022年

作者： Thong, Hao-Cheng Wang, XiaoYang Wang, Han Zhang, Linfeng Wang, Ke Xu, Ben State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing100084 China Graduate School China Academy of Engineering Physics Beijing100193 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Beijing Institute of Big Data Research Beijing100871 China

Ferroelectric perovskites have been ubiquitously applied in piezoelectric devices for decades, among which, eco-friendly lead-free (K,Na)NbO3-based materials have been recently demonstrated to be an excellent candidate for sustainable development. Molecular dynamics is a versatile theoretical calculation approach for the investigation of the dynamical properties of ferroelectric perovskites. However, molecular dynamics simulation of ferroelectric perovskites has been limited to simple systems, since the conventional construction of interatomic potential is rather difficult and inefficient. In the present study, we construct a machine-learning interatomic potential of KNbO3 (as a representative system of (K,Na)NbO3) by using a deep neural network model. Including first-principles calculation data into the training dataset ensures the quantum-mechanics accuracy of the interatomic potential. The molecular dynamics based on machine-learning interatomic potential shows good agreement with the first-principles calculations, which can accurately predict multiple fundamental properties, e.g., atomic force, energy, elastic properties, and phonon dispersion. In addition, the interatomic potential exhibits satisfactory performance in the simulation of domain wall and temperature-dependent phase transition. The construction of interatomic potential based on machine learning could potentially be transferred to other ferroelectric perovskites and consequently benefits the theoretical study of ferroelectrics. © 2022, CC BY.

关键词： Molecular dynamics

LLT: An R package for Linear Law-based Feature Space Transformation

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arXiv 2023年

作者： Kurbucz, Marcell T. Pósfay, Péter Jakovác, Antal Department of Computational Sciences Wigner Research Centre for Physics 29-33 Konkoly-Thege Miklós Street BudapestH-1121 Hungary Institute of Data Analytics and Information Systems Corvinus University of Budapest 8 Fővám Square BudapestH-1093 Hungary

The goal of the linear law-based feature space transformation (LLT) algorithm is to assist with the classification of univariate and multivariate time series. The presented R package, called LLT, implements this algorithm in a flexible yet user-friendly way. This package first splits the instances into training and test sets. It then utilizes time-delay embedding and spectral decomposition techniques to identify the governing patterns (called linear laws) of each input sequence (initial feature) within the training set. Finally, it applies the linear laws of the training set to transform the initial features of the test set. These steps are performed by three separate functions called trainTest, trainLaw, and testTrans. Their application requires a predefined data structure;however, for fast calculation, they use only built-in functions. The LLT R package and a sample dataset with the appropriate data structure are publicly available on *** Codes 62H30, 68T10, 62M10, 60-04 © 2023, CC BY.

关键词： Linear transformations

Magnetically threaded accretion disks in resistive magnetohydrodynamic simulations and asymptotic expansion

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arXiv 2023年

作者： Čemeljić, Miljenko Kluźniak, W. Parthasarathy, V. Research Centre for Computational Physics and Data Processing Institute of Physics Silesian University in Opava Bezručovo nám. 13 OpavaCZ-746 01 Czech Republic Nicolaus Copernicus Astronomical Center Polish Academy of Sciences Bartycka 18 Warsaw00-716 Poland Academia Sinica Institute of Astronomy and Astrophysics P.O. Box 23-141 Taipei106 Taiwan Höchstleistungsrechenzentrum Stuttgart Nobelstraße 19 Stuttgart70569 Germany

Aims. A realistic model of magnetic linkage between a central object and its accretion disk is a prerequisite for understanding the spin history of stars and stellar remnants. To this end, we aim to provide an analytic model in agreement with magnetohydrodynamic (MHD) simulations. Methods. For the first time, we wrote a full set of stationary asymptotic expansion equations of a thin magnetic accretion disk, including the induction and energy equations. We also performed a resistive MHD simulation of an accretion disk around a star endowed with a magnetic dipole, using the publicly available code PLUTO. We compared the analytical results with the numerical solutions, and discussed the results in the context of previous solutions of the induction equation describing the star-disk magnetospheric interaction. Results. We found that the magnetic field threading the disk is suppressed by orders of magnitude inside thin disks, so the presence of the stellar magnetic field does not strongly affect the velocity field, nor the density profile inside the disk. Density and velocity fields found in the MHD simulations match the radial and vertical profiles of the analytic solution. Qualitatively, the MHD simulations result in an internal magnetic field similar to the solutions previously obtained by solving the induction equation in the disk alone. However, the magnetic field configuration is quantitatively affected by magnetic field inflation outside the disk;this is reflected in the net torque. The torque on the star is an order of magnitude larger in the magnetic than in the non-magnetic case. Spin-up of the star occurs on a timescale comparable to the accretion timescale in the MHD case, and is an order of magnitude slower in the absence of a stellar magnetic field. © 2023, CC BY.

关键词： Stars

Predicting the Price Movement of Cryptocurrencies Using Linear Law-based Transformation

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arXiv 2023年

The aim of this paper is to investigate the effect of a novel method called linear law-based feature space transformation (LLT) on the accuracy of intraday price movement prediction of cryptocurrencies. To do this, the 1-minute interval price data of Bitcoin, Ethereum, Binance Coin, and Ripple between 1 January 2019 and 22 October 2022 were collected from the Binance cryptocurrency exchange. Then, 14-hour nonoverlapping time windows were applied to sample the price data. The classification was based on the first 12 hours, and the two classes were determined based on whether the closing price rose or fell after the next 2 hours. These price data were first transformed with the LLT, then they were classified by traditional machine learning algorithms with 10-fold cross-validation. Based on the results, LLT greatly increased the accuracy for all cryptocurrencies, which emphasizes the potential of the LLT algorithm in predicting price *** Codes 68T10, 91B84, 62M10, 91-08 © 2023, CC BY.

关键词： Linear transformations

Involution game with spatio-temporal heterogeneity of social resources

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arXiv 2022年

作者： Wang, Chaoqian Szolnoki, Attila Program for Computational Social Science Department of Computational and Data Sciences George Mason University FairfaxVA22030 United States Institute of Technical Physics and Materials Science Centre for Energy Research P.O. Box 49 BudapestH-1525 Hungary

When group members claim a portion of limited resources, it is tempting to invest more effort to get a larger share. However, if everyone acts similarly, they all get the same piece they would obtain without extra effort. This is the involution game dilemma that can be detected in several real-life situations. It is also a realistic assumption that resources are not uniform in space and time, which may influence the system's resulting involution level. We here introduce spatio-temporal heterogeneity of social resources and explore their consequences on involution. When spatial heterogeneity is applied, network reciprocity can mitigate the involution for rich resources, which would be critical otherwise in a homogeneous population. Interestingly, when the resource level is modest, spatial heterogeneity causes more intensive involution in a system where most cooperator agents, who want to keep investment at a low level, are present. This picture is partly the opposite in the extreme case when more investment is less effective. Spatial heterogeneity can also produce a counterintuitive effect when the presence of alternative resource levels cannot explain the emergence of involution. If we apply temporal heterogeneity additionally, then the impact of spatial heterogeneity practically vanishes, and we turn back to the behavior observed in a homogeneous population earlier. Our observations are also supported by solving the corresponding replicator equations numerically. © 2022, CC BY.

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When greediness and self-confidence meet in a social dilemma

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arXiv 2023年

作者： Wang, Chaoqian Zhu, Wenqiang Szolnoki, Attila Department of Computational and Data Sciences George Mason University FairfaxVA22030 United States Institute of Artificial Intelligence Beihang University Beijing100191 China Institute of Technical Physics and Materials Science Centre for Energy Research P.O. Box 49 BudapestH-1525 Hungary

A greedy personality is usually accompanied by arrogance and confidence. This work investigates the cooperation success condition in the context of biased payoff allocation and self-confidence. The first component allows the organizer in a spatial public goods game to receive a different proportion of goods than other participants. The second aspect influences the micro-level dynamics of strategy updates, wherein players can maintain their strategy with a certain weight. Analytical results are obtained on square lattices under the weak selection limit. If the organizer attempts to monopolize the public goods, cooperation becomes more attainable. If the confidence increases, cooperation is inhibited. Consequently, these elements have conflicting effects on cooperation, and their simultaneous presence can result in a heterogeneous change of the critical synergy factor. Our theoretical findings underscore the subtle implications of a mutual trait that may manifest as greediness or self-confidence under different circumstances, which are validated through Monte Carlo simulations. © 2023, CC0.

关键词： Game theory

Energy dissipation in astrophysical simulations: results of the Orszag-Tang test problem

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arXiv 2023年

作者： Kayanikhoo, Fatemeh Čemeljić, Miljenko Wielgus, Maciek Kluz, Wlodek Nicolaus Copernicus Astronomical Center Bartycka 18 Warszaw00-716 Poland Research Centre for Computational Physics and Data Processing Institute of Physics Silesian University in Opava Bezručovo nám. 13 OpavaCZ-746 01 Czech Republic Academia Sinica Institute of Astronomy and Astrophysics P.O. Box 23-141 Taipei106 Taiwan Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany

MSC Codes 85-08The magnetic field through the magnetic reconnection process affects the dynamics and structure of astrophysical systems. Numerical simulations are the tools to study the evolution of these systems. However, the resolution, dimensions, resistivity, and turbulence of the system are some important parameters to take into account in the simulations. In this paper, we investigate the evolution of magnetic energy in astrophysical simulations by performing a standard test problem for MHD codes, Orszag-Tang. We estimate the numerical dissipation in the simulations using state-of-the-art numerical simulation code in astrophysics, PLUTO. The estimated numerical resistivity in 2D simulations corresponds to the Lundquist number ≈ 104 in the resolution of 512 × 512 grid cells. It is also shown that the plasmoid unstable reconnection layer can be resolved with sufficient resolutions. Our analysis demonstrates that in non-relativistic magnetohydrodynamics simulations, magnetic and kinetic energies undergo conversion into internal energy, resulting in plasma heating. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy dissipation