Choosing an Optimal Pass Set for Quantum Transpilation

In order to increase the fidelity of quantum programs running on NISQ devices, a variety of optimizations have been proposed. These optimizations are usually incorporated into a quantum transpiler as passes. Popular transpilers such as IBM Qiskit, and Google Cirq make use of these extensively.

However, choosing the right set of transpiler passes and the right configuration for each pass is a challenging problem.

Transpilers often make critical decisions using heuristics since the ideal choices are impossible to identify without knowing the target application outcome. Further, the transpiler also makes simplifying assumptions about device noise that often do not hold in the real world. As a result, we often see counter-intuitive effects where the fidelity of a target application decreases despite using state-of-the-art optimizations or a combination of them.

To overcome this challenge, we propose OPTRAN, a framework for Choosing an Optimal Pass Set for Quantum Transpilation. OPTRAN uses efficiently classically simulable quantum circuits, that resemble the target application, to estimate how different transpiler passes interact with each other in the context of the target application. OPTRAN then uses this information to choose the optimal combination of passes that maximizes the target application's fidelity when run on the actual device. Our experiments on IBM machines show that OPTRAN

achieves by 88.68% of the maximum possible fidelity, (a 4.31x improvement over IBM-Qiskit's baseline). We also propose low-cost variants of OPTRAN, called OPTRAN-E-3 and OPTRAN-E-1 that improve fidelity by 70% and 61% of the maximum permissible limit at a 58% and 69% reduction in cost compared to OPTRAN respectively.