Hybrid quantum-classical computer for Bayesian inference with engineered likelihood functions for robust amplitude estimation
US11615329B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 14, 2020 |
| Grant date | Mar 28, 2023 |
| Priority date | — |
| Expiry date | Apr 21, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N10/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A hybrid quantum-classical (HQC) computer takes advantage of the available quantum coherence to maximally enhance the power of sampling on noisy quantum devices, reducing measurement number and runtime compared to VQE. The HQC computer derives inspiration from quantum metrology, phase estimation, and the more recent “alpha-VQE” proposal, arriving at a general formulation that is robust to error and does not require ancilla qubits. The HQC computer uses the “engineered likelihood function” (ELF) to carry out Bayesian inference. The ELF formalism enhances the quantum advantage in sampling as the physical hardware transitions from the regime of noisy intermediate-scale quantum computers into that of quantum error corrected ones. This technique speeds up a central component of many quantum algorithms, with applications including chemistry, materials, finance, and beyond.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.