Quantum annealing with special drivers for circuit fault diagnostics

Abstract

We present a very general construction for quantum annealing protocols to solve Combinational Circuit Fault Diagnosis 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.

Adiabatic Quantum Power Flow

“…This duration is not feasible for specific applications, such as stochastic optimal power flow 25 , where a large number of calculations should be completed within a few minutes. Consequently, the power systems community is increasingly interested in exploring novel approaches, including quantum computing [26][27][28] , which have shown promising results in various applications and are, therefore, expected to revolutionize the field of PF analysis in the near future 29 .…”