Provable imitation learning for control of instability in partially-observed Vlasov--Poisson equations

ArXi:2605.05081v1 Announce Type: new We consider the stabilization of Vlaso--Poisson plasma dynamics, a central control problem in nuclear fusion. Our focus is the gap between what an ideal controller would use and what experiments can actually observe: while optimal policy may rely on the full phase-space state, practical feedback is typically limited to sparse macroscopic diagnostics. We therefore study imitation learning methods that distill a fully observed expert policy into controllers operating only on macroscopic measurements.