Self-similar multishock implosions for ultrahigh compression of matter
M. Murakami
TL;DR
The paper addresses achieving ultrahigh compression of uniform-density solid targets by synchronizing multiple converging shocks. It develops a class of self-similar solutions that generalize the Guderley problem to $N$ stacked shocks and derives a density-scaling law $\rho_r/\rho_0 \propto \hat{P}^{\beta(N-1)}$ with a $\beta(\gamma)$ exponent determined from perturbation theory. The results, verified by 1D hydrodynamic simulations, show robust agreement across perturbative and strongly nonlinear regimes up to $\hat{P} \sim 70$, with a saturation set by the asymptotic strong-shock limit; the approach inherently suppresses Rayleigh–Taylor instabilities due to its volumetric geometry. This analytic framework provides a principled route to instability-free, high-density compression designs in inertial confinement fusion and may inform advanced fusion concepts such as proton–boron where ultrahigh densities are desirable.
Abstract
We present a class of self-similar solutions describing ultrahigh compression of a uniform-density target by spherically converging, stacked shock waves. Extending the classical Guderley model, we derive a scaling law for the final density of the form $ρ_{r}/ρ_{0} \propto \hat{P}^{β(N-1)}$, where $N$ is the number of shocks, $\hat{P}$ the stage pressure ratio, and $β$ a numerical exponent determined by the adiabatic index $γ$. One-dimensional hydrodynamic simulations confirm the validity of this scaling across a broad parameter range. Notably, the relation remains accurate even in the strongly nonlinear regime up to $\hat{P} \sim 70$, well beyond the perturbative limit, highlighting the robustness and practical relevance of the model. Owing to its volumetric geometry, this compression scheme inherently avoids the Rayleigh--Taylor instability, which typically compromises shell-based implosions, and thereby establishes a theoretical benchmark for instability-free compression in inertial confinement fusion.
