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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.
RENORMALIZATION-GROUP, Quantum Physics, Quantum Gases (cond-mat.quant-gas), Atomic Physics (physics.atom-ph), SIMULATION, 500, FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Quantum Gases, Quantum Physics (quant-ph), 004, Physics - Atomic Physics
RENORMALIZATION-GROUP, Quantum Physics, Quantum Gases (cond-mat.quant-gas), Atomic Physics (physics.atom-ph), SIMULATION, 500, FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Quantum Gases, Quantum Physics (quant-ph), 004, Physics - Atomic Physics
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