Stefano Mensa, Emre Sahin, et al.
Machine Learning: Science and Tech.
We describe an optimal procedure, as well as its efficient software implementation, for exact and approximate synthesis of two-qubit unitary operations into any prescribed discrete family of XX-type interactions and local gates. This arises from the analysis and manipulation of certain polyhedral subsets of the space of canonical gates. Using this, we analyze which small sets of XX-type interactions cause the greatest improvement in expected infidelity under experimentally-motivated error models. For the exact circuit synthesis of Haar-randomly selected two-qubit operations, we find an improvement in estimated infidelity by 31.4% when including alongside CX its square- and cube-roots, near to the optimal limit of 36.9% obtained by including all fractional applications of CX.
Stefano Mensa, Emre Sahin, et al.
Machine Learning: Science and Tech.
Luke Govia, David McKay, et al.
APS March Meeting 2024
Emanuele Dri, Antonello Aita, et al.
Entropy
Francesco Libbi, Jacopo Rizzo, et al.
APS March Meeting 2023