Quantum computing developer Rigetti Computing and researchers from Purdue University have published joint research extending Rigetti's quantum preconditioning framework to hard-constrained combinatorial optimization problems. By using two-point variable correlations extracted from shallow Quantum
Quantum computing developer Rigetti Computing and researchers from Purdue University have published joint research extending Rigetti's quantum preconditioning framework to hard-constrained combinatorial optimization problems. By using two-point variable correlations extracted from shallow Quantum Approximate Optimization Algorithm (QAOA) circuits to modify the objective function of commercial Mixed-Integer Programming (MIP) solvers, the team demonstrated that quantum preconditioning [...] The post Rigetti and Purdue University Demonstrate Quantum Preconditioning Framework for Constrained Optimization appeared first on Quantum Computing Report .