Theoretical astrophysics and plasma physics at RPC

Abstract:

The classical theory of cluster relaxation is unsatisfactory because it involves the Coulomb logarithm. The Balescu–Lenard (BL) equation provides a rigorous alternative that has no ill-defined parameter. Moreover, the BL equation, unlike classical theory, includes the cluster’s self-gravity. A heuristic argument is given that indicates that relaxation does not occur predominantly through two-particle scattering and is enhanced by self-gravity. The BL equation is adapted to a spherical system and used to estimate the flux through the action space of isochrone clusters with different velocity anisotropies. A range of fairly different secular behaviours is found depending on the fraction of radial orbits. Classical theory is also used to compute the corresponding classical fluxes. The BL and classical fluxes are very different because (a) the classical theory materially underestimates the impact of large-scale collectively amplified fluctuations and (b) only the leading terms in an infinite sum for the BL flux are computed. A complete theory of cluster relaxation likely requires that the sum in the BL equation be decomposed into a sum over a finite number of small wavenumbers complemented by an integral over large wavenumbers analogous to classical theory.

Abstract:

Magnetic field measurements in turbulent plasmas are often difficult to perform. Here we show that for ⩾ kG magnetic fields, a time-resolved Faraday rotation measurement can be made at the OMEGA laser facility. This diagnostic has been implemented using the Thomson scattering probe beam and the resultant path-integrated magnetic field has been compared with that of proton radiography. Accurate measurement of magnetic fields is essential for satisfying the scientific goals of many current laser–plasma experiments.

Abstract:

Gaussian processes are the ideal tool for modelling the Galactic ISM, combining statistical flexibility with a good match to the underlying physics. In an earlier paper we outlined how they can be employed to construct three-dimensional maps of dust extinction from stellar surveys. Gaussian processes scale poorly to large datasets though, which put the analysis of realistic catalogues out of reach. Here we show how a novel combination of the Expectation Propagation method and certain sparse matrix approximations can be used to accelerate the dust mapping problem. We demonstrate, using simulated Gaia data, that the resultant algorithm is fast, accurate and precise. Critically, it can be scaled up to map the Gaia catalogue.