  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 and mitigate arbitrary Markovian noise in 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 3x 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.
