Quantum optimization of maximum independent set using Rydberg atom arrays
- Department of Physics, Harvard University, Cambridge, MA 02138, USA.
- Department of Physics, Harvard University, Cambridge, MA 02138, USA.; QuEra Computing Inc., Boston, MA 02135, USA.
- QuEra Computing Inc., Boston, MA 02135, USA.; Department of Physics and Astronomy, University of Waterloo, Waterloo N2L 3G1, Canada.; Perimeter Institute for Theoretical Physics, Waterloo, Ontario N2L 2Y5, Canada.
- School of Engineering and Applied Science, Harvard University, Cambridge, MA 02138, USA.
- Google Quantum AI, Venice, CA 90291, USA.; Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
- Department of Physics, Harvard University, Cambridge, MA 02138, USA.; School of Natural Sciences, Institute for Advanced Study, Princeton, NJ 08540, USA.
- QuEra Computing Inc., Boston, MA 02135, USA.
- Department of Physics, Harvard University, Cambridge, MA 02138, USA.; Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA 91125, USA.
- Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
- Institute for Theoretical Physics, University of Innsbruck, A-6020 Innsbruck, Austria.; Institute for Quantum Optics and Quantum Information, Austrian Academy of Sciences, A-6020 Innsbruck, Austria.
- Department of Physics and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Realizing quantum speedup for practically relevant, computationally hard problems is a central challenge in quantum information science. Using Rydberg atom arrays with up to 289 qubits in two spatial dimensions, we experimentally investigate quantum algorithms for solving the maximum independent set problem. We use a hardware-efficient encoding associated with Rydberg blockade, realize closed-loop optimization to test several variational algorithms, and subsequently apply them to systematically explore a class of graphs with programmable connectivity. We find that the problem hardness is controlled by the solution degeneracy and number of local minima, and we experimentally benchmark the quantum algorithm’s performance against classical simulated annealing. On the hardest graphs, we observe a superlinear quantum speedup in finding exact solutions in the deep circuit regime and analyze its origins.
- Research Organization:
- Harvard Univ., Cambridge, MA (United States); Krell Institute, Ames, IA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- SC0019030; SC0020347; SC0021013; SC0022199
- OSTI ID:
- 1980748
- Journal Information:
- Science, Vol. 376, Issue 6598; ISSN 0036-8075
- Publisher:
- AAAS
- Country of Publication:
- United States
- Language:
- English
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