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Improving quantum state detection with adaptive sequential observations

Published

Author(s)

Emanuel Knill, Scott Glancy, Daniel Cole, Shawn Geller

Abstract

For many quantum systems intended for information processing, one detects the logical state of a qubit by integrating a continuously observed quantity over time. For example, ion and atom qubits are typically measured by driving a cycling transition and counting the number of photons observed from the resulting fluorescence. Instead of recording only the total observed count, one can observe the photon arrival times and get a state detection advantage by using the temporal structure in a model such as a Hidden Markov Model. We initiate the study of what further advantage may be achieved by applying pulses to adaptively transform the state during the observation. We give a three-state example where adaptively chosen transformations yield a clear advantage, and we compare performances on a prototypical ion example, where we see improvements in some regimes. We make available a software package that can be used for exploration of temporally resolved strategies with and without adaptively chosen transformations.
Citation
Quantum Science and Technology
Volume
7

Keywords

quantum bit measurement, hidden Markov models

Citation

Knill, E. , Glancy, S. , Cole, D. and Geller, S. (2022), Improving quantum state detection with adaptive sequential observations, Quantum Science and Technology, [online], https://doi.org/10.1088/2058-9565/ac6972, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933559 (Accessed May 21, 2024)

Issues

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Created May 13, 2022, Updated June 7, 2023