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Quantum Optimization

Parity Quantum Optimization: Encoding Constraints

DOAJ
Authors: Maike Drieb-Schön, Kilian Ender, Younes Javanmard, Wolfgang Lechner

Year

2023

Paper ID

35602

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

87

Citations

15

Abstract

Constraints make hard optimization problems even harder to solve on quantum devices because they are implemented with large energy penalties and additional qubit overhead. The parity mapping, which has been introduced as an alternative to the spin encoding, translates the problem to a representation using only parity variables that encodes products of spin variables. In combining exchange interaction and single spin flip terms in the parity representation, constraints on sums and products of arbitrary k-body terms can be implemented without additional overhead in two-dimensional quantum systems.

Why This Paper Matters

  • This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • Constraints make hard optimization problems even harder to solve on quantum devices because they are implemented with large energy penalties and additional qubit overhead.

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References & Citation Signals

[1] DOI https://doi.org/10.22331/q-2023-03-17-951 [2] Publisher https://quantum-journal.org/papers/q-2023-03-17-951/pdf/

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