一句话：提出 DARE，一个把 qubit 计算编译并优化为 qutrit 电路的编译器，通过分解与重写降低电路深度并提升保真度。
量子硬件受噪声与退相干限制，电路规模与复杂度难以提升。近期 qutrit 硬件可利用 |2⟩ 高能态临时存储信息以降低电路深度，但此类使用高阶态的量子电路目前仍需硬件设计者手工构造。本文提出 DARE，一个面向实现 qubit 计算的 qutrit 电路的优化编译器，包含 qutrit 电路分解算法与重写引擎，用于自动构造并优化 qutrit 电路。作者将 DARE 与手工优化的 qutrit 电路及 qubit 电路进行对比评估，结果显示 DARE 相对手工 qutrit 实现最多降低 65% 深度，相对 qubit 电路降低 43%–75% 深度；保真度分析进一步表明，DARE 优化后的 qutrit 电路保真度最高可达手工实现对应电路的 8.9 倍。
Quantum computers are a revolutionary class of computational platforms that are capable of solving computationally hard problems. However, today’s quantum hardware is subject to noise and decoherence issues that together limit the scale and complexity of the quantum circuits that can be implemented. Recently, practitioners have developed qutrit-based quantum hardware platforms that compute over ∣ 0 ⟩ , ∣ 1 ⟩ , and ∣ 2 ⟩ states, and have presented circuit depth reduction techniques using qutrits’ higher energy ∣ 2 ⟩ states to temporarily store information. However, thus far, such quantum circuits that use higher order states for temporary storage need to be manually crafted by hardware designers. We present D are , an optimizing compiler for qutrit circuits that implement qubit computations. D are deploys a qutrit circuit decomposition algorithm and a rewrite engine to construct and optimize qutrit circuits. We evaluate D are against hand-optimized qutrit circuits and qubit circuits, and find D are delivers up to 65 % depth improvement over manual qutrit implementations, and 43-75% depth improvement over qubit circuits. We also perform a fidelity analysis and find DARE-optimized qutrit circuits deliver up to 8.9 × higher fidelity circuits than their manually implemented counterparts.
@article{SharmaA24,
title = {Compilation of Qubit Circuits to Optimized Qutrit Circuits},
author = {Ritvik Sharma and Sara Achour},
journal = {Proceedings of the ACM on Programming Languages},
volume = {8},
number = {PLDI},
year = {2024},
doi = {10.1145/3656388}
}