Southwest Quantum Information and Technology

Improving quantum state detection with adaptive sequential observations

Presenting Author: Shawn Geller, National Institute of Standards and Technology, Boulder
Contributing Author(s): Daniel C. Cole, Scott Glancy, and 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, 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. We make available a software package that can be used for exploration of temporally resolved strategies with and without adaptively chosen transformations.

(Session 5 : Thursday from 12:00pm-2:00 pm)