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arXiv · astro-ph/9607049

Diffusive Shock Acceleration in Oblique MHD Shocks: Comparison with Monte Carlo Methods and Observations

Abstract

We report simulations of diffusive particle acceleration in oblique magnetohydrodynamical (MHD) shocks. These calculations are based on extension to oblique shocks of a numerical model for ``thermal leakage'' injection of particles at low energy into the cosmic-ray population. That technique, incorporated into a fully dynamical diffusion-convection formalism, was recently introduced for parallel shocks by Kang \& Jones (1995). Here, we have compared results of time dependent numerical simulations using our technique with Monte Carlo simulations by Ellison, Baring \& Jones 1995 and with {\it in situ} observations from the Ulysses spacecraft of oblique interplanetary shocks discussed by Baring \etal (1995). Through the success of these comparisons we have demonstrated that our {diffusion-convection} method and injection techniques provide a practical tool to capture essential physics of the injection process and particle acceleration at oblique MHD shocks. In addition to the diffusion-convection simulations, we have included time dependent two-fluid simulations for a couple of the shocks to demonstrate the basic validity of that formalism in the oblique shock context. Using simple models for the two-fluid closure parameters based on test-particle considerations, we find good agreement with the dynamical properties of the more detailed diffusion-convection results. We emphasize, however, that such two-fluid results can be sensitive to the properties of these closure parameters when the flows are not truly steady. Furthermore, we emphasize through example how the validity of the two-fluid formalism does not necessarily mean that {\it steady-state} two-fluid models provide a reliable tool for predicting the efficiency of particle acceleration in real shocks.

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BibTeXRIS

Hyesung Kang, T. W. Jones. 1996-07-10. Diffusive Shock Acceleration in Oblique MHD Shocks: Comparison with Monte Carlo Methods and Observations. https://doi.org/10.1086/303646

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