Improving the Fidelity of CNOT Circuits on NISQ Hardware
Abstract
We introduce an improved CNOT synthesis algorithm that considers nearest-neighbour interactions and CNOT gate error rates in noisy intermediate-scale quantum (NISQ) hardware. Compared to IBM's Qiskit compiler, it improves the fidelity of a synthesized CNOT circuit by about 2 times on average (up to 9 times). It lowers the synthesized CNOT count by a factor of 13 on average (up to a factor of 162). Our contribution is twofold. First, we define a function by approximating the average gate fidelity . According to the simulation results, fits the error probability of a noisy CNOT circuit, , much tighter than the commonly used cost functions. On IBM's fake Nairobi backend, it matches to within . On other backends, it fits to within . accurately quantifies the dynamic error characteristics and shows remarkable scalability. Second, we propose a noise-aware CNOT routing algorithm, NAPermRowCol, by adapting the leading Steiner-tree-based connectivity-aware CNOT synthesis algorithms. A weighted edge is used to encode a CNOT gate error rate and -instructed heuristics are applied to each reduction step. NAPermRowCol does not use ancillary qubits and is not restricted to certain initial qubit maps. Compared with algorithms that are noise-agnostic, it improves the fidelity of a synthesized CNOT circuit across varied NISQ hardware. Depending on the benchmark circuit and the IBM backend selected, it lowers the synthesized CNOT count up to compared to ROWCOL and up to compared to PermRowCol. It reduces the synthesis up to compared to ROWCOL and up to compared to PermRowCol. Our method can be extended to route a more general quantum circuit, giving a powerful new tool for compiling on NISQ devices.
Cite
@article{arxiv.2405.19891,
title = {Improving the Fidelity of CNOT Circuits on NISQ Hardware},
author = {Dohun Kim and Minyoung Kim and Sarah Meng Li and Michele Mosca},
journal= {arXiv preprint arXiv:2405.19891},
year = {2024}
}
Comments
67 pages, 33 figures, and 9 tables