一句话：提出利用硬件噪声与校准数据的NISQ量子程序编译器映射方法，显著提升执行成功率。
当前量子计算原型受噪声和硬件参数波动影响，NISQ系统量子比特少且无法纠错，因而需要高效可靠的映射。论文从量子程序的LLVM中间表示出发，构建后端编译器，将高层量子程序映射并优化为可在IBM Q公共机器上执行的代码。框架实现并评估多种最优与启发式映射方法，分别考虑动态校准数据、噪声参数重要性、路由策略以及编译时可扩展性与运行时成功的权衡。基于真实系统测量，方法利用硬件参数细粒度时空变化，相较IBM Qiskit编译器平均提升2.9倍、最高18倍成功率，有助于加速实现量子优越性。
A massive gap exists between current quantum computing (QC) prototypes, and the size and scale required for many proposed QC algorithms. Current QC implementations are prone to noise and variability which affect their reliability, and yet with less than 80 quantum bits (qubits) total, they are too resource-constrained to implement error correction. The term Noisy Intermediate-Scale Quantum (NISQ) refers to these current and near-term systems of 1000 qubits or less. Given NISQ's severe resource constraints, low reliability, and high variability in physical characteristics such as coherence time or error rates, it is of pressing importance to map computations onto them in ways that use resources efficiently and maximize the likelihood of successful runs. This paper proposes and evaluates backend compiler approaches to map and optimize high-level QC programs to execute with high reliability on NISQ systems with diverse hardware characteristics. Our techniques all start from an LLVM intermediate representation of the quantum program (such as would be generated from high-level QC languages like Scaffold) and generate QC executables runnable on the IBM Q public QC machine. We then use this framework to implement and evaluate several optimal and heuristic mapping methods. These methods vary in how they account for the availability of dynamic machine calibration data, the relative importance of various noise parameters, the different possible routing strategies, and the relative importance of compile-time scalability versus runtime success. Using real-system measurements, we show that fine grained spatial and temporal variations in hardware parameters can be exploited to obtain an average 2.9x (and up to 18x) improvement in program success rate over the industry standard IBM Qiskit compiler. Despite small qubit counts, NISQ systems will soon be large enough to demonstrate "quantum supremacy", i.e., an advantage over classical computing. Tools like ours provide significant improvements in program reliability and execution time, and offer high leverage in accelerating progress towards quantum supremacy.
@inproceedings{paperbot4880,
title = {Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers},
author = {Prakash Murali and Jonathan M. Baker and Ali Javadi-Abhari and Frederic T. Chong and Margaret Martonosi},
booktitle = {ASPLOS},
year = {2019},
doi = {10.1145/3297858.3304075}
}