Resistive plasmas are of fundamental importance in the description of physical phenomena such as magnetic reconnection, which has been recently pointed out as an efficient site for particle acceleration. We have implemented a new module for the PLUTO code that solves the Resistive Relativistic MHD equations using an IMplicit-EXplicit Runge-Kutta method for the evolution of the electric field. The divergence-free condition and the conservation of the electric charge can be treated using a constrained transport method (where electric and/or magnetic fields have a staggered representation) or a divergence cleaning method (where one or two Lagrangian multipliers are added in order to preserve the cell-centered formulation). The solution to the Riemann problem is obtained under the frozen limit condition on the direct combination of two Riemann solvers: one for the outermost electromagnetic waves across which only transverse components of electric and magnetic fields can change, and a second one across the sound waves, where only hydrodynamical variables have nontrivial jumps. The RRMHD module has recently been extended to encompass the Taub Equation of State within the IMEX scheme.
The new resistive relativistic module has become available from PLUTO 4.4 under specific collaboration policies.
We compared a particular selection of approximate solutions to the Riemann problem in the context of ideal relativistic magnetohydrodynamics. In particular, we focused on Riemann solvers not requiring a full eigenvector structure. Such solvers recover the solution of the Riemann problem by solving a simplified or reduced set of jump conditions, whose level of complexity depends on the intermediate modes that are included. Five different approaches - namely the HLL, HLLC, HLLD, HLLEM, and GFORCE schemes - are compared in terms of accuracy and robustness against one- and multi-dimensional standard numerical benchmarks. Our results demonstrate that - for weak or moderate magnetizations - the HLLD Riemann solver yields the most accurate results, followed by the HLLC solver(s). The GFORCE approach provides a valid alternative to the HLL solver being less dissipative and equally robust for strongly magnetized environments. Finally, our tests show that the HLLEM Riemann solver is not cost-effective in improving the accuracy of the solution and reducing the numerical dissipation.
I am currently updating the Python module pyPLUTO in order to simplify the production of high-quality scientific plots. Due to the increase in numerical techniques and computational resources, it is necessary to build loading and plotting modules that exploit the most up-to-date Python features. By loading the data through the memory-mapping techniques, both fluid and particle files can be accessed without necessarily loading all the variables. Once the data are loaded, the users can take advantage of the plotting methods, which simplify the creation of figures and subplots, as well as customized plots. At the moment, pyPLUTO has been released alongside the GPU-accelerated version of the PLUTO code (GPLUTO).
(almost) All the plots displayed on this website have been created with pyPLUTO.