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}
}