Iskandar Sitdikov, Jennifer Glick, et al.
APS March Meeting 2023
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.
Iskandar Sitdikov, Jennifer Glick, et al.
APS March Meeting 2023
Kalyan Dasgupta, Binoy Paine
arXiv
Sarah Sheldon
APS March Meeting 2023
Massimiliano Datres, Gian Paolo Leonardi, et al.
NeurIPS 2024