1. Stochastic Optimization of Quantum Programs
- Author
-
Chun-Fu Chen, Shaohan Hu, Peng Liu, Marco Pistoia, and Jay M. Gambetta
- Subjects
Quantum programming ,Mathematical optimization ,Correctness ,General Computer Science ,Computer science ,Monte Carlo method ,TheoryofComputation_GENERAL ,Markov process ,Markov chain Monte Carlo ,symbols.namesake ,ComputerSystemsOrganization_MISCELLANEOUS ,Qubit ,symbols ,Computer Science::Programming Languages ,Stochastic optimization ,Quantum ,computer ,computer.programming_language ,Quantum computer - Abstract
We introduce Markov chain Monte Carlo quantum (MCMCQ), a novel compiler-level optimization of quantum programs that accounts for the emerging quantum programming mode. MCMCQ is the first systematic approach for stochastic quantum-program optimization, targeting program performance, correctness, and noise tolerance. An evaluation of MCMCQ over 500 quantum programs confirms its effectiveness.
- Published
- 2019
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