Tensor Networks

Tensor networks is a family of classical algorithms used to drastically increase tensor contraction performance. It has been conjectured that such methods can be used to quickly approximate quantum circuits rapidly, and provide a benchmark for quantum supremacy.

Abstract

Google's Sycamore paper(2019) was the first paper to demonstrate quantum supremacy, calculating a 53 qubit gate circuit in 600s, where a classical algorithm was estimated to take 500 trillion hours. However a recent 2022 paper has claimed that Google's fidelity score can be bested by tensor network methods. The aim of the project is to reproduce their results with a full 53 qubit lattice, instead of the simplified lattice in the paper, thus increasing understanding of tensor network methods.

References

[1] Arute, F., Arya, K., Babbush, R. et al. Quantum supremacy using a programmable superconducting processor. Nature 574, 505–510 (2019). https://doi.org/10.1038/s41586-019-1666-5

[2] Feng Pan, Keyang Chen, and Pan Zhang, Solving the Sampling Problem of the Sycamore Quantum Circuits, Phys. Rev. Lett. 129, 090502