Derives that the conditional terminal law of the optimal controlled process is a Gibbs measure on a proximally penalized energy, giving potential, averaged-gradient, and barycentric drift formulas with terminal-time gradient recovery and low-temperature global-minimizer attraction.
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Optimal drift optimizer for non-convex optimization
Derives that the conditional terminal law of the optimal controlled process is a Gibbs measure on a proximally penalized energy, giving potential, averaged-gradient, and barycentric drift formulas with terminal-time gradient recovery and low-temperature global-minimizer attraction.