Evidence for the utility of quantum computing before fault tolerance

By Youngseok Kim, A. Eddins, Sajant Anand, K. X. Wei, Ewout van den Berg, S. Rosenblatt, Hasan Nayfeh, Yantao Wu, M. Zaletel, Kristan Temme and 1 more. Nature, 2023

1,339 citations recorded by the source corpus.

Quantum computing promises to offer substantial speed-ups over its classical counterpart for certain problems. However, the greatest impediment to realizing its full potential is noise that is inherent to these systems. The widely accepted solution to this challenge is the implementation of fault-tolerant quantum circuits, which is out of reach for current processors. Here we report experiments on a noisy 127-qubit processor and demonstrate the measurement of accurate expectation values for circuit volumes at a scale beyond brute-force classical computation. We argue that this represents evidence for the utility of quantum computing in a pre-fault-tolerant era. These experimental results are enabled by advances in the coherence and calibration of a superconducting processor at this scale and the ability to characterize^ 1 and controllably manipulate noise across such a large device. We establish the accuracy of the measured expectation values by comparing them with the output of exactly verifiable circuits. In the regime of strong entanglement, the quantum computer provides correct results for which leading classical approximations such as pure-state-based 1D (matrix product states, MPS) and 2D (isometric tensor network states, isoTNS) tensor network methods^ 2 , 3 break down. These experiments demonstrate a foundational tool for the realization of near-term quantum applications^ 4 , 5 . Experiments on a noisy 127-qubit superconducting quantum processor report the accurate measurement of expectation values beyond the reach of current brute-force classical computation, demonstrating evidence for the utility of quantum computing before fault tolerance.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/f9253a3e2627f1c2a0a7e2cea320a4ec4e4d2ff9

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Citations in the corpus

Challenges and opportunities in quantum optimization (2023, neutral): “We have highlighted key problem classes in optimization, reviewed existing algorithms and suggested new research directions.”
Quantum computing with Qiskit (2024, methodology): “For example, Qiskit was used in a recent paper that showed evidence of utility for quantum computers by using error mitigation [51].”
Logical quantum processor based on reconfigurable atom arrays (2023, background): “Because in the two-copy measurements for each error-detection threshold we also measure the overall system purity, we can extrapolate our expectation values to the case of unit purity (zero noise) 54 .”
Quantum error mitigation (2022, methodology): “However, while this will work well with depolarising gate noise, it may change the gate error model for more general gate noise such that the factor of increase in the error strength is no longer well-defined (Kim et al. , 2023b).”