Hybrid Quantum-Classical Computer for Bayesian Inference with Engineered Likelihood Functions for Robust Amplitude Estimation
Patent №
US 11,615,329
Granted
2023-03-28
Filed 2020
Owner
ZAPATA COMPUTING, INC.
Lab
—
AI components
4
ml · vision · planning · hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
16900947
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.
AI classification
Ownership
ZAPATA COMPUTING, INC.
assignment · 538560498
Assignors
WANG, GUOMING, KOH, ENSHAN DAX, JOHNSON, PETER D., CAO, YUDONG, DALLAIRE-DEMERS, PIERRE-LUC
On an employer assignment, the assignors are typically the inventors.