Birth process of electron-positron pairs inside supercritical fields

Abstract We propose a computational quantum field theoretical approach to obtain microscopic insight into the creation process of electrons and positrons as well their subsequent motion inside supercritical external with space-time resolution. A machine-learning–based method permits us address fundamental questions such where interaction region particles are being created what initial velocity distribution is. It suggests that particles' most likely birth positions change in time during dynamics. At early times density is roughly proportional square force field, but long-time steady state production regime possible locations narrow down significantly. Counterintuitively, this leads for longer occurrence “birth-free” zones within no even though electric maximal there. The genetic-programming–based symbolic regression algorithms first learn multiple sequences partially dressed positronic spatial probability densities training data then exploit features function dressing strength order predict true space momentum.