Qi Huang, Lucas Jordao, et al.
APS March Meeting 2024
Quasiprobabilistic cutting techniques allow us to partition large quantum circuits into smaller subcircuits by replacing non-local gates with probabilistic mixtures of local gates. The cost of this method is a sampling overhead that scales exponentially in the number of cuts. It is crucial to determine the minimal cost for gate cutting and to understand whether allowing for classical communication between subcircuits can improve the sampling overhead. In this work, we derive a closed formula for the optimal sampling overhead for cutting an arbitrary number of two-qubit unitaries and provide the corresponding decomposition. We find that cutting several arbitrary two-qubit unitaries together is cheaper than cutting them individually and classical communication does not give any advantage.
Qi Huang, Lucas Jordao, et al.
APS March Meeting 2024
Gian Gentinetta, David Sutter, et al.
QCE 2023
Daniel Egger, Claudio Gambella, et al.
IEEE TQE
Stefano Mensa, Emre Sahin, et al.
Machine Learning: Science and Tech.