A Quantum Extended Kalman Filter
A stochastic filter uses a series of measurements over time to produce estimates of unknown variables based on a dynamic model. For a quantum system, such an algorithm is provided by a quantum filter, which is also known as a stochastic master equation (SME). For a linear quantum system subject to l...
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| description | A stochastic filter uses a series of measurements over time to produce estimates of unknown variables based on a dynamic model. For a quantum system, such an algorithm is provided by a quantum filter, which is also known as a stochastic master equation (SME). For a linear quantum system subject to linear measurements and Gaussian noise, the quantum filter reduces to a quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to non-commutative quantum stochastic differential equations (QSDEs). We will show that there are conditions under which a filter similar to the classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problems with `state-dependent' covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems which involve multiple modes, nonlinear Hamiltonians and simultaneous jump-diffusive measurements. |
| doi_str_mv | 10.48550/arxiv.1603.01890 |
| format | Article |
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| subjects | Algorithms Differential equations Dynamic models Extended Kalman filter Kalman filters Linearization Mathematics - Mathematical Physics Mathematics - Optimization and Control Noise reduction Physics - Mathematical Physics Physics - Quantum Physics Quantum theory Random noise System effectiveness |
| title | A Quantum Extended Kalman Filter |
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