Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size


Journal article


Jahan Claes, W. V. Dam
Quantum, 2021

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APA   Click to copy
Claes, J., & Dam, W. V. (2021). Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size. Quantum.


Chicago/Turabian   Click to copy
Claes, Jahan, and W. V. Dam. “Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size.” Quantum (2021).


MLA   Click to copy
Claes, Jahan, and W. V. Dam. “Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size.” Quantum, 2021.


BibTeX   Click to copy

@article{jahan2021a,
  title = {Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size},
  year = {2021},
  journal = {Quantum},
  author = {Claes, Jahan and Dam, W. V.}
}

Abstract

This paper studies the application of the Quantum Approximate Optimization Algorithm (QAOA) to spin-glass models with random multi-body couplings in the limit of a large number of spins. We show that for such mixed-spin models the performance of depth 1 QAOA is independent of the specific instance in the limit of infinite sized systems and we give an explicit formula for the expected performance. We also give explicit expressions for the higher moments of the expected energy, thereby proving that the expected performance of QAOA concentrates.


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