Circuit fault diagnosis using quantum annealing and other spin glass solvers
ORAL
Abstract
In this work we present a novel approach to solving circuit fault diagnosis (CFD) problems using quantum annealers and other spin glass solvers, such as simulated annealing and parallel tempering.
The cost function we construct does not minimize the number of faults but rather the distance between real and model circuit outputs: as such it has the attractive property of processing multiple circuit input/output pairs contrary to existing schemes. By showcasing the algorithms' performance through comparison of various metrics, such as time-to-solution, we aim to offer a fresh perspective on using real world-applicative
problems in order to understand the nature of quantum annealing optimizers.
The cost function we construct does not minimize the number of faults but rather the distance between real and model circuit outputs: as such it has the attractive property of processing multiple circuit input/output pairs contrary to existing schemes. By showcasing the algorithms' performance through comparison of various metrics, such as time-to-solution, we aim to offer a fresh perspective on using real world-applicative
problems in order to understand the nature of quantum annealing optimizers.
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Presenters
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Brendan Reid
Information Sciences Institute, University of Southern California
Authors
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Brendan Reid
Information Sciences Institute, University of Southern California
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Elizabeth Crosson
Department of Physics and Astronomy, University of New Mexico, University of New Mexico
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Itay Hen
University of Southern California, Information Sciences Institute, USC, Information Sciences Institute, University of Southern California