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Parity Quantum Optimization: Benchmarks
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AI
DOI：10.22331/q-2023-03-17-952.png)
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Abstract
En 中文
We present benchmarks of the parity trans-formation for the Quantum Approximate Op-timization Algorithm (QAOA). We analyse the gate resources required to implement a single QAOA cycle for toy models of real-world sce-narios. In particular, we consider random spin models with higher order terms, as well as the problems of predicting financial crashes and finding the ground states of electronic struc-ture Hamiltonians. For the spin models stud-ied our findings imply a significant advantage of the parity mapping compared to the stan-dard gate model in terms of the number of CNOT gates required on a square lattice with nearest-neighbor connectivity, at the cost of an increased number of qubits. Our results sug-gest that in combination with its full paralleliz-ability of gates, the parity architecture has the potential to boost the race for demonstrating quantum advantage.