Abstract

The goal of achieving practical quantum advantage on early fault-tolerant hardware has motivated two repeating themes in the recent design and development of quantum algorithms: (1) splitting large quantum circuits into collections of smaller quantum circuits, and (2) building inherent noise-resilience into algorithms rather than relying solely on error correction. A unique yet largely unexplored opportunity that arises from these properties is the ability to use multiple quantum computers, of differing qubit modalities, for the same problem. In this work, we apply these ideas to Bayesian quantum phase estimation, showing how phase estimation may be accelerated by leveraging the various speed-to-accuracy tradeoffs inherent to different qubit modalities.