We prove that
Globally Optimizing QAOA Circuit Depth for Constrained Optimization Problems
We develop a global variable substitution method that reduces n-variable monomials in combinatorial optimization problems to equivalent instances with monomials in fewer variables. We apply this technique to 3-SAT and analyze the optimal quantum unitary circuit depth needed to solve the reduced problem using the quantum approximate optimization algorithm. For benchmark 3-SAT problems, we find that the upper bound of the unitary circuit depth is smaller when the problem is formulated as a product and uses the substitution method to decompose gates than when the problem is written in the linear formulation, which requires no decomposition.
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- Award ID(s):
- 1937008
- NSF-PAR ID:
- 10316458
- Date Published:
- Journal Name:
- Algorithms
- Volume:
- 14
- Issue:
- 10
- ISSN:
- 1999-4893
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/a14100294
