A nonlinear custom penalty without slack variables plus CVaR sampling improves optimality gaps and consistency on knapsack instances for quantum constrained optimization.
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A protocol extracts scaling dimensions of d=3 CFTs from the spectrum of qubit Hamiltonians on polyhedral lattices, achieving few-percent accuracy on the 3D Ising model with 20 qubits.
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CVaR-Assisted Custom Penalty Function for Constrained Optimization
A nonlinear custom penalty without slack variables plus CVaR sampling improves optimality gaps and consistency on knapsack instances for quantum constrained optimization.
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Qubit discretizations of d=3 conformal field theories
A protocol extracts scaling dimensions of d=3 CFTs from the spectrum of qubit Hamiltonians on polyhedral lattices, achieving few-percent accuracy on the 3D Ising model with 20 qubits.