Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

Variational quantum algorithms are believed to be promising for solving computationally hard problems on noisy intermediate-scale quantum (NISQ) systems. Gaining computational power from these algorithms critically relies on the mitigation of errors during their execution, which for coherence-limite...

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Vydané v:PRX quantum Ročník 1; číslo 2; s. 020304
Hlavní autori: Lacroix, Nathan, Hellings, Christoph, Andersen, Christian Kraglund, Di Paolo, Agustin, Remm, Ants, Lazar, Stefania, Krinner, Sebastian, Norris, Graham J., Gabureac, Mihai, Heinsoo, Johannes, Blais, Alexandre, Eichler, Christopher, Wallraff, Andreas
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: American Physical Society 01.10.2020
ISSN:2691-3399, 2691-3399
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Shrnutí:Variational quantum algorithms are believed to be promising for solving computationally hard problems on noisy intermediate-scale quantum (NISQ) systems. Gaining computational power from these algorithms critically relies on the mitigation of errors during their execution, which for coherence-limited operations is achievable by reducing the gate count. Here, we demonstrate an improvement of up to a factor of 3 in algorithmic performance for the quantum approximate optimization algorithm (QAOA) as measured by the success probability, by implementing a continuous hardware-efficient gate set using superconducting quantum circuits. This gate set allows us to perform the phase separation step in QAOA with a single physical gate for each pair of qubits instead of decomposing it into two CZ gates and single-qubit gates. With this reduced number of physical gates, which scales with the number of layers employed in the algorithm, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances mapped onto three and seven qubits, using up to a total of 399 operations and up to nine layers. Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.
Bibliografia:correction
ISSN:2691-3399
2691-3399
DOI:10.1103/PRXQuantum.1.020304