Tuesdays 10:30 - 11:30 | Fridays 11:30 - 12:30
Showing votes from 2017-05-30 11:30 to 2017-06-02 12:30 | Next meeting is Friday May 15th, 11:30 am.
The detectability of gravitational waves originating from primordial black holes or other large macroscopic dark-matter candidates inspiraling into Sagittarius ${\rm A}^{\!*}$ is investigated. It is shown that LISA should be a formidable machine to detect such objects with masses above $\sim10^{20}\,{\rm g}$, especially if they are the main component of the dark matter, and the dark-matter density at Sagittarius ${\rm A}^{\!*}$ exceeds its value in the solar-neighborhood. In particular, the open window of mass $2\times10^{20}\,{\rm g} \leq m_{\rm DM} \leq 4 \times 10^{24}\,{\rm g}$ will be accessible. Forecasts are derived for the event rates and signal strengths as a function of dark-matter mass, assuming that the dark-matter candidates are not tidally disrupted during the inspiral. This is certainly the case for primordial black holes, and it shown that it is also very likely the case for candidate objects of nuclear density.
We introduce a high-performance simulation framework that permits semi-independent, task-based solution of sets of partial differential equations, typically manifesting as updates to a collection of 'patches' in space-time. A hybrid MPI/OpenMP execution model is adopted, where work tasks are generated by a rank-local 'dispatcher', which selects, from a set of tasks generally much larger than the number of physical cores (or hardware threads), tasks that are ready for updating. The definition of a task can vary, for example, with some solving the equations of ideal magnetohydrodynamics (MHD), others non-ideal MHD, radiative transfer, or integrating particle trajectories, and yet others applying particle-in-cell (PIC) methods. Tasks do not have to be grid-based, while tasks that are may use either Cartesian or curvilinear meshes. Patches may be stationary or moving, with geometrical size and orientation fixed or variable. Mesh refinement can be static or dynamic. A feature of decisive importance for the overall performance of the framework is that time steps are determined and applied locally, this allows large reductions in the total number of updates required, and therefore a corresponding reduction in computing time, in cases when the signal speed varies greatly across the computational domain. Another important feature is a load balancing algorithm that operates 'locally' and aims to simultaneously minimize load and communication imbalance. The framework generally relies on already existing solvers, whose performance is augmented when run under the framework, due to more efficient cache usage, vectorization, local time stepping, and near-linear and, in principle, unlimited OpenMP and MPI scaling.