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http://hdl.handle.net/10397/79343
Title: | Quantum projection filtering for open quantum systems | Authors: | Gao, Q Zhang, G |
Issue Date: | 2017 | Source: | IEEE conference on decision and control, Proceedings, 2017, p. 5529-5534 | Abstract: | This paper presents an approximation quantum projection filtering strategy, aiming to reduce the computational cost in calculating the standard quantum filter equation in time. By using a differential geometric approach, the trajectory of the resulting quantum projection filter is constrained to evolve in a finite-dimensional differentiable manifold consisting of an exponential family of quantum density operators. A convenient design of the differentiable manifold is then developed through reduction of the local approximation errors, which allows simplification of the quantum projection filter equations. Finally, simulation results from a two-level quantum system example illustrate the approximation performance of the proposed filtering scheme. The proposed approach is expected to be of practical use in developing more efficient quantum control methods. | Keywords: | Differentiable manifold Open quantum systems Quantum information geometry Quantum projection filtering |
Publisher: | IEEE | Journal: | IEEE conference on decision and control. Proceedings | DOI: | 10.1109/CDC.2017.8264479 | Description: | 56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne, Australia, 12-15 December 2017 | Rights: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Gao, Q., & Zhang, G. (2017, December). Quantum projection filtering for open quantum systems. In 2017 IEEE 56th Annual Conference on Decision and Control (CDC) (pp. 5529-5534). IEEE is available at https://doi.org/10.1109/CDC.2017.8264479 |
Appears in Collections: | Conference Paper |
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