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Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

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The boundary for quantum advantage in Gaussian boson sampling.

Jacob F F Bulmer¹, Bryn A Bell², Rachel S Chadwick^1,3

¹Quantum Engineering Technology Labs, University of Bristol, Bristol, UK.

Science Advances

|January 26, 2022

Summary

Researchers developed faster classical simulation methods for Gaussian boson sampling (GBS), significantly reducing the time needed to verify quantum advantage. This breakthrough accelerates the exploration of quantum computing

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Area of Science:

Quantum Computing
Computational Complexity
Quantum Information Science

Background:

Determining the threshold for quantum computational advantage is essential for assessing quantum machine utility.
Gaussian boson sampling (GBS) is a key quantum advantage candidate, involving photon measurements from entangled Gaussian states.

Purpose of the Study:

To develop significantly faster classical simulation methods for GBS experiments.
To improve the accuracy and speed of calculating loop hafnians for GBS simulations.

Main Methods:

Implementation of improved classical algorithms for GBS simulation.
Utilizing a large-scale supercomputer (∼100,000 cores) for emulation.
Development of a classically efficient sampling distribution for GBS validation.

Main Results:

Reduced simulation time for state-of-the-art GBS experiments from an estimated 600 million years to several months.
Achieved a nine-orders of magnitude improvement in classical simulation efficiency.
Successfully emulated GBS experiments with up to 100 modes and 92 photons.

Conclusions:

The developed methods provide a substantial acceleration in classical GBS simulations.
This advancement aids in verifying quantum advantage claims in GBS experiments.
Introduced a novel, classically efficient distribution for GBS validation.