Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport. (arXiv:2206.11343v1 [physics.comp-ph])

Web: http://arxiv.org/abs/2206.11343

We consider the Bayesian calibration of models describing the phenomenon of
block copolymer (BCP) self-assembly using image data produced by microscopy or
X-ray scattering techniques. To account for the random long-range disorder in
BCP equilibrium structures, we introduce auxiliary variables to represent this
aleatory uncertainty. These variables, however, result in an integrated
likelihood for high-dimensional image data that is generally intractable to
evaluate. We tackle this challenging Bayesian inference problem using a
likelihood-free approach based on measure transport together with …

arxiv bayesian computation free inference information model physics transport