Toward automated design of optimized high energy density material science experiments on the Z Machine

High energy density dynamic compression materials science experiments in the Mbar regime can only be performed on a limited number of experimental facilities and thus often consist of one-off experimental designs. Due to the bespoke nature of such experiments, design is done via an expert process that is guided by high fidelity multiphysics computation. In a typical dynamic materials properties experiment, a tailored current pulse shape is generated by the Z Machine that quasi-isentropically compresses a sample material to high energy density states. Minor fluctuations in the firing time of laser-triggered gas switches (LTGS) – used to create the custom pulse shape – can result in undesirable shocked compression of samples. A computational framework has been developed that analyses the statistical spread in LTGS timings to calculate the probability of experiment failure. Recent additions to this framework have opened the possibility of automated experiment design that meets designated target metrics that has never before been achieved at the Z Facility. Exciting possibilities lay before us to optimize not only to intuitive metrics (sample input pressure, shockless compression probability, sample dimensions, etc.) but to non-intuitive metrics such as minimizing possible damage to the vacuum/insulator stack. Progress towards fully automated design of a candidate experiment will be presented to the data science community for broader engagement.