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Quantum approximate optimization of non-planar graph problems on a planar superconducting processor
- Source :
- Nature Physics. 17(3):332-336
-
Abstract
- We demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the (planar) connectivity graph of our hardware; however, we also apply the QAOA to the Sherrington-Kirkpatrick model and MaxCut, both high dimensional graph problems for which the QAOA requires significant compilation. Experimental scans of the QAOA energy landscape show good agreement with theory across even the largest instances studied (23 qubits) and we are able to perform variational optimization successfully. For problems defined on our hardware graph we obtain an approximation ratio that is independent of problem size and observe, for the first time, that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size but still provides an advantage over random guessing for circuits involving several thousand gates. This behavior highlights the challenge of using near-term quantum computers to optimize problems on graphs differing from hardware connectivity. As these graphs are more representative of real world instances, our results advocate for more emphasis on such problems in the developing tradition of using the QAOA as a holistic, device-level benchmark of quantum processors.<br />19 pages, 15 figures
- Subjects :
- Physics
Quantum Physics
Optimization problem
FOS: Physical sciences
General Physics and Astronomy
01 natural sciences
010305 fluids & plasmas
Planar graph
Quantum technology
symbols.namesake
Qubit
0103 physical sciences
Benchmark (computing)
symbols
Combinatorial optimization
Quantum Physics (quant-ph)
010306 general physics
Algorithm
Quantum
Quantum computer
Subjects
Details
- Language :
- English
- ISSN :
- 17452481 and 17452473
- Volume :
- 17
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Nature Physics
- Accession number :
- edsair.doi.dedup.....3ae4995f932e726117dcfdc72a573944
- Full Text :
- https://doi.org/10.1038/s41567-020-01105-y