Quantum Annealing with Special Drivers for Circuit Fault Diagnostics

TL;DR

This paper introduces a novel quantum annealing protocol with special drivers for circuit fault diagnosis, demonstrating improved performance and insights into energy gaps and degeneracy effects through simulations.

Contribution

It develops a general quantum annealing approach with specialized local drivers for circuit fault diagnosis, enhancing performance insights and schedule optimization.

Findings

Degeneracy can improve quantum annealing performance.

Energy gap analysis shows a generic form with the minimum gap in the last third.

Improved annealing schedule enhances simulation results.

Abstract

We present a very general construction for quantum annealing protocols to solve Combinational Circuit Fault Diagnosis (CCFD) problems that restricts the evolution to the space of valid diagnoses. This is accomplished by using special local drivers that induce a transition graph on the space of feasible configurations that is regular and instance independent for each given circuit topology. Analysis of small instances shows that the energy gap has a generic form, and that the minimum gap occurs in the last third of the evolution. We used these features to construct an improved annealing schedule and benchmarked its performance through closed system simulations. We found that degeneracy can help the performance of quantum annealing, especially for instances with a higher number of faults in their minimum fault diagnosis. This contrasts with the performance of classical approaches based on brute force search that are used in industry for large scale circuits.