Finally, this project was a very fun collaboration with Dmitrii, who is an amazing undergraduate student at Duke, and Ken, without whom this would not have been possible.

Our method represents a resource-efficient way to estimate observables and has applications in both fault-tolerant and near-term quantum computing. Please check it out (arxiv.org/abs/2505.11486) — we welcome any comments!

and use this to build unbiased estimators from weighted expectation values. We then analyze when this method works and validate it via simulations, including time evolution under the Ising Hamiltonian.

Unitary errors, e.g., from fault-tolerant compilation, systematically bias observable estimates. The usual way to correct this bias is to use more non-Clifford gates. Here, we present an alternative strategy: decompose the ideal channel into a probabilistic mixture of noisy channels

Congrats Dr. @gkwt.bsky.social!! 🥂

In a different world, she could have had a long and illustrious career as a particle physicist.

To know more about her, read this excellent interview: ias.edu/ideas/redisc...