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Binary Optimization of Measurement Groupings for Quantum Energy Estimation
Isaac L. Huidobro-Meezs, Rodrigo A. Vargas-Hernández
Repeated measurements can dominate the resources required for quantum energy estimation, making the choice of which Pauli observables to measure together a central optimization pro…
Bottom-Up Design of Quantum Optical Experiments Using Discrete Generative Models
Isaac L. Huidobro-Meezs, Simón Paiva-Ortega, Rodrigo A. Vargas-Hernández
Designing quantum optical experiments requires searching over discrete circuit topologies and continuous parameters, often with multiple realizations of the same target state. Grap…
Reducing quantum measurements in qubit-based overlapping grouping methods for quantum energy estimation through better initializations
Isaac L. Huidobro-Meezs, Rodrigo A. Vargas-Hernández
The measurement cost for estimating expectation values of Hamiltonians is a central bottleneck in variational quantum algorithms. Grouping strategies significantly reduce this cost…
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing
Isaac L. Huidobro-Meezs, Jun Dai, Rodrigo A. Vargas-Hernández
Estimating molecular Hamiltonians to chemical accuracy requires a large number of measurements. Hamiltonian overlapping grouping methods focus on reducing measurement counts, emplo…