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.

Machine learningVisionPlanningAI hardwareG06N 7/01G06N 10/60G06N 5/04G06N 10/00G06N 10/70

AI classification

AI hardware0.97
Planning0.97
Vision0.75
Machine learning0.71
Speech0.02
Knowledge representation0.02
Evolutionary computation0.00
Natural language0.00

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.

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