Study Galactic Cosmic Ray Modulation with AMS-02 observation

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  • <p>ICRC</p>

    ICRC

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  • uploaded June 25, 2021

Discussion timeslot (ZOOM-Meeting): 14. July 2021 - 12:00
ZOOM-Meeting URL: https://desy.zoom.us/j/96969970711
ZOOM-Meeting ID: 96969970711
ZOOM-Meeting Passcode: ICRC2021
Corresponding Session: https://icrc2021-venue.desy.de/channel/20-GCR-long-term-modulation-SH/103
Live-Stream URL: https://icrc2021-venue.desy.de/livestream/Discussion-07/8

Abstract:
'The accurate measurements of the galactic cosmic ray (GCR) fluxes as function of time and energy by the Alpha Magnetic Spectrometer (AMS) give us unique information to search dark matter, to study the dynamics of solar modulation, to constraint the parameters in modulation model, to improve the precision of radiation dose prediction in the ongoing deep space exploration.rnThe transport of low rigidity GCRs ( smaller 30GV) in the heliosphere is described by the Parker equation. This equation is solved by stochastic differential equation approach in numerical model. The input parameters in the model (solar wind speed, tilt angle, magnetic intensity and polarity) are obtained by the observation near the Earth. The time varying parameters (diffusion coefficient, drift coefficient) is usually tuned manually. This method only gives result what looks good, but cannot gives the uncertainty of parameters.rnIn this study, the Markov chain Monte Carlo (MCMC) technique is used to determine the time varying posterior probability distribution of parameters related to the GCR transport equation. In Bayesian statistics, MCMC is a class of samplers in which we can simulate draws that are slightly dependent and are approximately from a posterior distribution. The Metropolis-Hastings algorithm is used to implement the MCMC sampler. Compared to the traditional method where the likelihood function is evaluated on the grid of points in parameter space, the MCMC sampler is low resource consumption as it is insensitive to the dimensionality of the parameter space.'

Authors: xiaojian song | xi luo | weiwei xu
Indico-ID: 1090
Proceeding URL: https://pos.sissa.it/395/1354

Tags:
Presenter: xiaojian song

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