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Quantum Machine Learning Quantum Simulation

Leveraging Secondary Storage to Simulate Deep 54-qubit Sycamore Circuits

arXiv

Authors: Edwin Pednault, John A. Gunnels, Giacomo Nannicini, Lior Horesh, Robert Wisnieff

Year

2019

Paper ID

15411

Status

Preprint

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~2 min

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Abstract

In a recent paper, we showed that secondary storage can extend the range of quantum circuits that can be practically simulated with classical algorithms. Here we refine those techniques and apply them to the simulation of Sycamore circuits with 53 and 54 qubits, with the entanglement pattern ABCDCDAB that has proven difficult to classically simulate with other approaches. Our analysis shows that on the Summit supercomputer at Oak Ridge National Laboratories, such circuits can be simulated with high fidelity to arbitrary depth in a matter of days, outputting all the amplitudes.

Why This Paper Matters

This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
It adds a 2019 reference point for readers tracking recent quantum research.
In a recent paper, we showed that secondary storage can extend the range of quantum circuits that can be practically simulated with classical algorithms.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:1910.09534 [2] arXiv https://arxiv.org/abs/1910.09534 [3] Publisher https://arxiv.org/abs/1910.09534

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