The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Several researchers from Google AI Quantum, University of Massachusetts Amherst, NASA Ames Research Center, Institute for Quantum Information and Matter at Caltech, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Quantum Computing Institute at Oak Ridge National Laboratory and Department of Electrical Engineering and Computer Science at University of Michigan report the use of a processor with programmable superconducting qubits to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 253 (about 1016). Measurements from repeated experiments sample the resulting probability distribution, which the researchers verify using classical simulations.
The Google Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—the benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy for this specific computational task, heralding a much-anticipated computing paradigm.
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