Southwest Quantum Information and Technology

Improving quantum state detection with adaptive sequential observations

Presenting Author: Shawn Geller, University of Colorado
Contributing Author(s): Daniel C Cole, Scott Glancy, Emanuel Knill

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 in a fixed time interval, 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 study 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 an ion example, where we see improvements in some regimes. We provide a software package that can be used for exploration of temporally resolved strategies with and without adaptively chosen transformations.

Read this article online: https://iopscience.iop.org/article/10.1088/2058-9565/ac6972/meta, https://arxiv.org/abs/2204.00710v2

(Session 9c : Friday from 4:15 pm - 4:45 pm)