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Power spectral density of a single Brownian trajectory

  • The power spectral density (PSD) of any time-dependent stochastic processX (t) is ameaningful feature of its spectral content. In its text-book definition, the PSD is the Fourier transform of the covariance function of X-t over an infinitely large observation timeT, that is, it is defined as an ensemble-averaged property taken in the limitT -> infinity. Alegitimate question is what information on the PSD can be reliably obtained from single-trajectory experiments, if one goes beyond the standard definition and analyzes the PSD of a single trajectory recorded for a finite observation timeT. In quest for this answer, for a d-dimensional Brownian motion (BM) we calculate the probability density function of a single-trajectory PSD for arbitrary frequency f, finite observation time T and arbitrary number k of projections of the trajectory on different axes. We show analytically that the scaling exponent for the frequency-dependence of the PSD specific to an ensemble of BM trajectories can be already obtained from a single trajectory, whileThe power spectral density (PSD) of any time-dependent stochastic processX (t) is ameaningful feature of its spectral content. In its text-book definition, the PSD is the Fourier transform of the covariance function of X-t over an infinitely large observation timeT, that is, it is defined as an ensemble-averaged property taken in the limitT -> infinity. Alegitimate question is what information on the PSD can be reliably obtained from single-trajectory experiments, if one goes beyond the standard definition and analyzes the PSD of a single trajectory recorded for a finite observation timeT. In quest for this answer, for a d-dimensional Brownian motion (BM) we calculate the probability density function of a single-trajectory PSD for arbitrary frequency f, finite observation time T and arbitrary number k of projections of the trajectory on different axes. We show analytically that the scaling exponent for the frequency-dependence of the PSD specific to an ensemble of BM trajectories can be already obtained from a single trajectory, while the numerical amplitude in the relation between the ensemble-averaged and single-trajectory PSDs is afluctuating property which varies from realization to realization. The distribution of this amplitude is calculated exactly and is discussed in detail. Our results are confirmed by numerical simulations and single-particle tracking experiments, with remarkably good agreement. In addition we consider a truncated Wiener representation of BM, and the case of a discrete-time lattice random walk. We highlight some differences in the behavior of a single-trajectory PSD for BM and for the two latter situations. The framework developed herein will allow for meaningful physical analysis of experimental stochastic trajectories.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Diego KrapfORCiD, Enzo MarinariORCiD, Ralf MetzlerORCiDGND, Gleb OshaninORCiDGND, Xinran Xu, Alessio SquarciniORCiD
DOI:https://doi.org/10.1088/1367-2630/aaa67c
ISSN:1367-2630
Titel des übergeordneten Werks (Englisch):New journal of physics : the open-access journal for physics
Untertitel (Englisch):what one can and cannot learn from it
Verlag:IOP Publ. Ltd.
Verlagsort:Bristol
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:09.02.2018
Erscheinungsjahr:2018
Datum der Freischaltung:24.01.2022
Freies Schlagwort / Tag:exact results; power spectral density; probability density function; single-trajectory analysis
Band:20
Seitenanzahl:30
Fördernde Institution:NSFNational Science Foundation (NSF) [1401432]; European Research Council (ERC) under the European Union Horizon research and innovation program [694925]
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Peer Review:Referiert
Publikationsweg:Open Access / Gold Open-Access
DOAJ gelistet
Lizenz (Deutsch):License LogoCreative Commons - Namensnennung, 3.0 Deutschland
Externe Anmerkung:Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 655
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