Practical quantum advantage in quantum simulation
Andrew J. Daley (),
Immanuel Bloch,
Christian Kokail,
Stuart Flannigan,
Natalie Pearson,
Matthias Troyer and
Peter Zoller
Additional contact information
Andrew J. Daley: University of Strathclyde
Immanuel Bloch: Max Planck Institute of Quantum Optics
Christian Kokail: Universität Innsbruck
Stuart Flannigan: University of Strathclyde
Natalie Pearson: University of Strathclyde
Matthias Troyer: Microsoft Corporation
Peter Zoller: Universität Innsbruck
Nature, 2022, vol. 607, issue 7920, 667-676
Abstract:
Abstract The development of quantum computing across several technologies and platforms has reached the point of having an advantage over classical computers for an artificial problem, a point known as ‘quantum advantage’. As a next step along the development of this technology, it is now important to discuss ‘practical quantum advantage’, the point at which quantum devices will solve problems of practical interest that are not tractable for traditional supercomputers. Many of the most promising short-term applications of quantum computers fall under the umbrella of quantum simulation: modelling the quantum properties of microscopic particles that are directly relevant to modern materials science, high-energy physics and quantum chemistry. This would impact several important real-world applications, such as developing materials for batteries, industrial catalysis or nitrogen fixing. Much as aerodynamics can be studied either through simulations on a digital computer or in a wind tunnel, quantum simulation can be performed not only on future fault-tolerant digital quantum computers but also already today through special-purpose analogue quantum simulators. Here we overview the state of the art and future perspectives for quantum simulation, arguing that a first practical quantum advantage already exists in the case of specialized applications of analogue devices, and that fully digital devices open a full range of applications but require further development of fault-tolerant hardware. Hybrid digital–analogue devices that exist today already promise substantial flexibility in near-term applications.
Date: 2022
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DOI: 10.1038/s41586-022-04940-6
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