Causal State Estimation and Heisenberg Uncertainty Principle

Junxin Chen, Benjamin B. Lane, Su Direkci, Dhruva Ganapathy, Xinghui Yin, Nergis Mavalvala, Yanbei Chen, Vivishek Sudhir

Published 2023-04-27Version 1

The observables of a noisy quantum system can be estimated by appropriately filtering the records of their continuous measurement. Such filtering is relevant for state estimation and measurement-based quantum feedback control. It is therefore imperative that the observables estimated through a causal filter satisfy the Heisenberg uncertainty principle. In the Markovian setting, prior work implicitly guarantees this requirement. We show that any causal estimate of linear observables of a linear, but not necessarily Markovian, system will satisfy the uncertainty principle. In particular, this is true irrespective of any feedback control of the system and of where in the feedback loop -- inside or outside -- the measurement record is accessed. Indeed, causal estimators using the in-loop measurement record can be as precise as those using the out-of-loop record. These results clarify the role of causal estimators to a large class of quantum systems, restores the equanimity of in-loop and out-of-loop measurements in their estimation and control, and simplifies future experiments on measurement-based quantum feedback control.