Oxford Centre for High Energy Density Science (OxCHEDS)

Abstract:

Multiscale temperature fluctuations are abundant in the intracluster medium (ICM) outside of galaxy cluster cores (∼100 kpc). Their origin is often attributed to turbulent stirring by subhalos or accreting baryons crossing the virial radius. However, their apparent resistance to mixing and thermal conduction in a collisional medium has not been explained. We propose a new mechanism by which steady-state temperature fluctuations can form and persist outside the cluster core. Local thermal instability, or Field instability, is used to explain filamentary condensates in cluster cores but is usually dismissed outside them because thermal conduction should suppress instability. In weakly collisional or collisionless plasmas, however, thermal conduction can be anomalously suppressed by heat-flux-driven plasma instabilities triggered in the presence of a local magnetic field, leading to two effects: (i) condensates form in a new parameter regime that overlaps with conditions outside the core, and (ii) condensates reach a steady state as in the hydrodynamic limit. This extends the regime of instability-driven fluctuations to over ≳50% (depending on hot plasma temperature) of the cluster. We use one-dimensional hydrodynamic simulations of condensates to test our analytical ideas.

Abstract:

Accurate modeling of heat flux in inertial confinement fusion plasmas requires closures that remain predictive far from local equilibrium and across disparate spatial and temporal resolutions. We develop a resolution-robust machine learning heat flux closure trained on particle-in-cell simulations using a Fourier neural operator. Two nonlocal electron thermal conduction models are trained and tested. When embedded self-consistently into the electron energy equation, the learned closure faithfully reproduces the temperature evolution and shows good temporal extrapolation and generalization capability. Remarkably, models trained on coarse-resolution data accurately predict heat flux when deployed in substantially finer-resolution implicit, iterative solvers of the energy equation, significantly enhancing the practicality of embedding data-driven closures into partial differential equation solvers. These results establish a data-driven closure that bridges kinetic and fluid descriptions and provides a viable pathway for treating machine learning as an iterative solver within the radiation-hydrodynamic simulations of inertial confinement fusion plasma.

Abstract:

The phase stability, crystal structure, and melting of Nb have been examined under high pressure shock compression to 365 GPa using ultrafast x-ray diffraction measurements on two x-ray free electron laser facilities. On compression, Nb remains stable in the bcc phase up to 220 GPa, with coexistence of bcc-Nb and liquid from 249 to 298 GPa, and complete melting at 301 GPa, with melt identified by diffuse liquid diffraction. Melting initiates at higher pressure than expected based on theoretical predictions, and the data consistently excludes the presence of other suggested phases of Nb at these pressures, including and hcp, thereby resolving the long-standing structural discrepancy. Singh-type strength analysis provides experimental evidence for a change in sign of the elastic anisotropy parameter at 121 GPa, consistent with the previously reported heat-induced hardening to heat-induced softening transition in Nb.