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We consider a simple Monte Carlo-based optimization algorithm, which is restricted to the solution space, and we demonstrate that sampling the equilibrium distribution of a biased measure improving on $α_d$ is still possible even beyond the ergodicity breaking point for the uniform measure, where other algorithms hopelessly enter the out-of-equilibrium regime.

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We consider a simple Monte Carlo-based optimization algorithm, which is restricted to the solution space, and we demons…○ uncheckedyes0.5502.0—

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