It is shown that a class of binary optimization problems with complex non-quadratic objectives or constraints can be reformulated as multi-objective quadratic unconstrained binary optimization problems and evaluated classically on Pareto-optimal candidates rather than encoded as penalties.
Andres D. Ruiz, Soumyadip Ghosh, S. Woerner· 1 citation
This work introduces a reweighting strategy for QPDs for circuits with the same variational structure across parameter settings, reusing samples and thereby reducing the sampling overhead, and finds that this method outperforms other standard estimation techniques.
Sara Santos, S. Woerner, V. Savona et al.· 0 citations
This work presents a simplified analytical characterization of DQI, and provides new empirical evidence that classical sampling algorithms can closely match DQI's optimization performance, offering a more nuanced perspective on the practical advantage of DQI.
Elies Gil-Fuster, Matan Ninio, Lennart Bittel et al.· 1 citation
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