Early-time velocity autocorrelation for charged particles diffusion and drift in static magnetic turbulence

F. Fraschetti, J. Giacalone

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Using test-particle simulations, we investigate the temporal dependence of the two-point velocity correlation function for charged particles scattering in a time-independent spatially fluctuating magnetic field derived from a three-dimensional isotropic turbulence power spectrum. Such a correlation function allowed us to compute the spatial coefficients of diffusion both parallel and perpendicular to the average magnetic field. Our simulations confirm the dependence of the perpendicular diffusion coefficient on turbulence energy density and particle energy predicted previously by a model for early-time charged particle transport. Using the computed diffusion coefficients, we exploit the particle velocity autocorrelation to investigate the timescale over which the particles "decorrelate" from the solution to the unperturbed equation of motion. Decorrelation timescales are evaluated for parallel and perpendicular motions, including the drift of the particles from the local magnetic field line. The regimes of strong and weak magnetic turbulence are compared for various values of the ratio of the particle gyroradius to the correlation length of the magnetic turbulence. Our simulation parameters can be applied to energetic particles in the interplanetary space, cosmic rays at the supernova shocks, and cosmic-rays transport in the intergalactic medium.

Original languageEnglish (US)
Article number114
JournalAstrophysical Journal
Volume755
Issue number2
DOIs
StatePublished - Aug 20 2012

Keywords

  • ISM: magnetic fields
  • cosmic rays
  • turbulence

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Fingerprint Dive into the research topics of 'Early-time velocity autocorrelation for charged particles diffusion and drift in static magnetic turbulence'. Together they form a unique fingerprint.

Cite this