  We study numerically the 6D (2,0) superconformal bootstrap using the
soft-Actor-Critic (SAC) algorithm as a stochastic optimizer. We focus on the
four-point functions of scalar superconformal primaries in the energy-momentum
multiplet. Starting from the supergravity limit, we perform searches for
adiabatically varied central charges and derive two curves for a collection of
80 CFT data (70 of these data correspond to unprotected long multiplets and 10
to protected short multiplets). We conjecture that the two curves capture the
A- and D-series (2,0) theories. Our results are competitive when compared to
the existing bounds coming from standard numerical bootstrap methods, and data
obtained using the OPE inversion formula. With this paper we are also releasing
our Python implementation of the SAC algorithm, BootSTOP. The paper discusses
the main functionality features of this package.
