(Improved algorithms for the SWAP test through Machine Learning)
Original authors: Lukasz Cincio, Yiğit Subaşı, Andrew T Sornborger and Patrick J Coles \
Link to paper: https://iopscience.iop.org/article/10.1088/1367-2630/aae94a
Notebook by: Óscar Amaro
In this notebook we reproduce Figure 9 for IBM computer ibmq_manila. See the pdf for a print of the notebook.
Abstract: Short-depth algorithms are crucial for reducing computational error on near-term quantum computers, for which decoherence and gate infidelity remain important issues. Here we present a machine-learning approach for discovering such algorithms."..."Here, we find algorithms that have shorter depths than the Swap Test, including one that has a constant depth (independent of problem size)." ..."demonstrate that the shorter algorithms that we derive significantly reduce the error—compared to the Swap Test—on these computers.