The fidelity of quantum programs in the NISQ era is limited by high levels of device noise. To increase the fidelity of quantum programs running on NISQ devices, a variety of optimizations have been proposed. These include mapping passes, routing passes, scheduling methods and standalone optimisations which are usually incorporated into a transpiler as passes. Popular transpilers such as those proposed by Qiskit, Cirq and Cambridge Quantum Computing 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 effects where the fidelity of a target application decreases despite using state-of-the-art optimisations. To overcome this challenge, we propose OPTRAN, a framework for Choosing an Optimal Pass Set for Quantum Transpilation. OPTRAN uses classically simulable quantum circuits composed entirely of Clifford gates, that resemble the target application, to estimate how different 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 improves fidelity by 87.66% of the maximum possible limit over the baseline used by IBM Qiskit. We also propose low-cost variants of OPTRAN, called OPTRAN-E-3 and OPTRAN-E-1 that improve fidelity by 78.33% and 76.66% of the maximum permissible limit over the baseline at a 58.33% and 69.44% reduction in cost compared to OPTRAN respectively.

翻译：在NISQ时代，量子程序的保真度受限于高水平的器件噪声。为提升运行在NISQ器件上的量子程序保真度，研究者提出了多种优化方法，包括映射通道、路由通道、调度方法以及独立优化技术，这些通常以编译通道的形式集成到编译器中。Qiskit、Cirq和Cambridge Quantum Computing等主流编译器广泛采用了这些技术。然而，选择正确的编译通道集合及每个通道的配置仍是一个具有挑战性的问题。由于无法在不了解目标应用结果的情况下确定理想选择，编译器常依赖启发式算法做出关键决策。此外，编译器还会对器件噪声做出简化假设，这些假设在实际场景中往往不成立。因此，我们常观察到即使采用最先进的优化，目标应用的保真度仍会下降。为克服这一挑战，我们提出OPTRAN框架，用于选择量子编译的最优通道集。OPTRAN利用完全由克利福德门构成的经典可模拟量子电路（其结构类似目标应用），来评估不同通道在目标应用上下文中的相互作用。随后，OPTRAN利用这些信息选择最优通道组合，以最大化目标应用在实际器件上运行时的保真度。在IBM机器上的实验表明，相较于IBM Qiskit使用的基线，OPTRAN将保真度提升至理论最大极限的87.66%。我们还提出了OPTRAN的低成本变体——OPTRAN-E-3和OPTRAN-E-1，相较于基线分别将保真度提升至理论最大极限的78.33%和76.66%，同时相比OPTRAN分别降低58.33%和69.44%的成本。