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Center for Nonlinear Studies |
Certifying that an n-qubit state synthesized in the lab is close to the target state is a fundamental task in quantum information science. However, existing rigorous protocols either require deep quantum circuits or exponentially many single-qubit measurements. In this work, we prove that almost all n-qubit target states, including those with exponential circuit complexity, can be certified from only O(n^2) single-qubit measurements. This result is established by a new technique that relates certification to the mixing time of a random walk. Our protocol has applications for benchmarking quantum systems, for optimizing quantum circuits to generate a desired target state, and for learning and verifying neural networks, tensor networks, and various other representations of quantum states using only single-qubit measurements. We show that such verified representations can be used to efficiently predict highly non-local properties that would otherwise require an exponential number of measurements. We demonstrate these applications in numerical experiments with up to 120 qubits, and observe advantage over existing methods such as cross-entropy benchmarking (XEB).
Bio: Robert is a Senior Research Scientist at Google Quantum AI and a Visiting Scientist at MIT. In 2025, I he will join Caltech as an Assistant Professor of Theoretical Physics. He received his Ph.D. under the guidance of John Preskill and Thomas Vidick. Robert's doctoral disertation, titled Learning in the Quantum Universe, was honored with the Milton and Francis Clauser Doctoral Prize — an award conferred annually to a single doctoral dissertation across all disciplines at Caltech.
Host: Martin Larocca (CNLS/T-4)