Black-Box Optimization with Local Generative Surrogates Supplementary Material A Surrogates Implementation Details A.1 GAN Implementation

Original version of FFJORD does not have a support of conditional input. To address this issue we rewrote one of the base layers that were used in FFJORD library. The example of such statistics is presented in Fig 6. Figure 6: An example of monitored statistics during surrogate training for one iteration of optimization. The gradient bias is calculated per component of the gradient vector, i.e., if C.1 Procedure For Mixing Matrix Generation 10-dimensional mixing matrix A could be generated with the following Python code: C.3 Numerical Derivatives To obtain numerical derivatives of R we are using central difference scheme: f Muons are bent by the magnetic field and simultaneously experience stochastic scattering as they pass through the magnet which causes random variations in their trajectories. Color represents number of the hits in a bin.