Quantum computing with qudits is an emerging approach that exploits a larger, more connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are typically afflicted by more complex errors and suffer greater noise sensitivity which renders their scaling difficult. In this work, we introduce techniques to tailor arbitrary qudit Markovian noise to stochastic Weyl–Heisenberg channels and mitigate noise that commutes with our Clifford and universal two-qudit gate in generic qudit circuits. We experimentally demonstrate these methods on a superconducting transmon qutrit processor, and benchmark their effectiveness for multipartite qutrit entanglement and random circuit sampling, obtaining up to 3× improvement in our results. To the best of our knowledge, this constitutes the first-ever error mitigation experiment performed on qutrits. Our work shows that despite the intrinsic complexity of manipulating higher-dimensional quantum systems, noise tailoring and error mitigation can significantly extend the computational reach of today’s qudit processors.

使用 qudits 的量子计算是一种新兴方法，它利用更大、更互联的计算空间，为许多应用程序提供优势，包括量子模拟和量子纠错。尽管如此，qudit 通常会受到更复杂的错误的影响，并且具有更高的噪声敏感性，这使得它们难以缩放。在这项工作中，我们介绍了将任意 qudit 马尔可夫噪声定制为随机 Weyl-Heisenberg 通道的技术，并减轻了在通用 qudit 电路中与我们的 Clifford 和通用双 qudit 门交换的噪声。我们在超导 transmon qutrit 处理器上实验演示了这些方法，并对它们在多方 qutrit 纠缠和随机电路采样方面的有效性进行了基准测试，我们的结果提高了 3×。据我们所知，这构成了有史以来第一次对 qutrit 进行的错误缓解实验。我们的工作表明，尽管操纵高维量子系统具有内在的复杂性，但噪声定制和错误缓解可以显着扩展当今 qudit 处理器的计算范围。