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Numerical integration of stochastic differential equations: a parallel cosmic ray modulation implementation on Africa’s fastest computer

dc.contributor.authorMoloto, K.D.
dc.contributor.authorEngelbrecht, N.E.
dc.contributor.authorStrauss, R.D.
dc.contributor.authorVan den Berg, J.P.
dc.contributor.authorMoeketsi, D.M.
dc.contributor.researchID20661533 - Moloto, Katlego Daniel
dc.contributor.researchID12580996 - Engelbrecht, Nicholas Eugene
dc.contributor.researchID13065440 - Strauss, Roelf Du Toit
dc.contributor.researchID24182869 - Van den Berg, Jacobus Petrus
dc.date.accessioned2018-10-22T12:45:21Z
dc.date.available2018-10-22T12:45:21Z
dc.date.issued2019
dc.description.abstractThree-dimensional studies of the transport and modulation of cosmic ray particles in turbulent astrospheres require large-scale simulations using specialized scientific codes. Essentially, a multi-dimensional Fokker-Planck type equation (a parabolic diffusion equation) must be integrated numerically. One such approach is to convert the relevant transport equation into a set of stochastic differential equations (SDEs), with the latter much easier to handle numerically. Due to the growing demand for high performance computing resources, research into the application of effective and suitable numerical algorithms to solve such equations is needed. We present a case study of the performance of a custom-written FORTRAN SDE numerical solver on the CHPC (Centre for High Performance Computing) Lengau cluster in South Africa for a realistic test problem with different set-ups. It is shown that SDE codes can scale very well on large parallel computing platforms. Finally, we consider an extremely computationally expensive application of the SDE approach to cosmic ray modulation, studying the behaviour of galactic cosmic ray proton latitude gradients and relative amplitudes in a physics-first manner. This is done using a modulation code that employs diffusion coefficients derived from first principles, which in turn are functions of turbulence quantities in reasonable agreement with spacecraft observations and modelled using a two-component turbulence transport model (TTM). We show that this approach leads to reduced latitude gradients qualitatively in line with spacecraft observations of the same, without making ad hoc assumptions as to anisotropic perpendicular diffusion coefficients as are often made in many cosmic ray modulation studiesen_US
dc.identifier.citationMoloto, K.D. et al. 2019. Numerical integration of stochastic differential equations: a parallel cosmic ray modulation implementation on Africa’s fastest computer. Advances in space research, 63(1):626-639. [https://doi.org/10.1016/j.asr.2018.08.048]en_US
dc.identifier.issn0273-1177
dc.identifier.issn1879-1948 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/31478
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0273117718306793
dc.identifier.urihttps://doi.org/10.1016/j.asr.2018.08.048
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCosmic raysen_US
dc.subjectStochastic differential equationsen_US
dc.subjectParallel computingen_US
dc.subjectCode scaling and efficiencyen_US
dc.subjectMPIen_US
dc.subjectFortran 90en_US
dc.titleNumerical integration of stochastic differential equations: a parallel cosmic ray modulation implementation on Africa’s fastest computeren_US
dc.typeArticleen_US

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