Quantum Annealer Calibration for Intrinsic Error Reduction

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Solution Overview

Problem

Quantum annealing processors face intrinsic/control errors due to limitations in representing Ising spin glass parameters, leading to inaccuracies in solving optimization problems, which are exacerbated by physical errors in qubit persistent currents and mutual inductances.

Innovation Solution

A method involving calibration of local bias terms and coupling terms in quantum processors to correct biases, using iterative calibration and polynomial regression models to adjust parameters, ensuring accurate representation of problem Hamiltonians and reducing errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If quantum annealing is performed with standard hardware parameters, then quantum processing can be executed, but intrinsic/control errors occur due to limitations in representing Ising spin glass parameters

Engineering Contradiction:

Improveaccuracy of quantum annealing solutionsVSAvoidprecision of local bias terms and coupling terms

Core Design Contradiction:

ReliabilityVSManufacturing precision

Solution Approach 1:

The patent applies preliminary calibration actions before executing quantum annealing computations. The system performs iterative calibration of local bias terms and coupling terms using polynomial regression models to establish accurate reference values beforehand, thereby eliminating intrinsic/control errors during the actual quantum processing

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements a feedback mechanism where measurement results from quantum annealing are compared against expected outcomes, and the discrepancies are used to iteratively adjust and refine the local bias terms and coupling terms. This closed-loop feedback process continuously improves the precision of hardware parameters

Inventive Principle:

Principle #23Feedback

2Manufacturing precision

If polynomial regression models are used to calibrate local bias terms and coupling terms, then intrinsic/control errors are reduced, but calibration time and computational overhead increase

Engineering Contradiction:

Improveprecision of local bias terms and coupling termsVSAvoidcalibration time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent transforms the calibration problem from direct physical measurement to a mathematical parameter optimization problem. By fitting polynomial regression models to the relationship between control parameters and measured outcomes, the system efficiently determines optimal bias and coupling terms without time-consuming iterative physical adjustments

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces traditional mechanical/physical calibration methods with computational polynomial regression analysis. Instead of manually adjusting hardware parameters through trial and error, the system uses mathematical modeling to predict and establish optimal parameter values, significantly reducing calibration time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10552755B2Systems and methods for improving the performance of a quantum processor to reduce intrinsic/control errors

Publication Date: 2020.02.04 D WAVE SYSTEMS INC

AI summary

Techniques for improving the performance of a quantum processor are described. Some techniques employ reducing intrinsic/control errors by using quantum processor-wide problems specifically crafted to reveal errors so that corrections may be applied. Corrections may be applied to physical qubits, logical qubits, and couplers so that problems may be solved using quantum processors with greater accuracy.