English

Quantum stochastic linear quadratic control theory: Closed-loop solvability

Optimization and Control 2025-02-28 v1 Functional Analysis

Abstract

In this paper, we investigate the closed-loop solvability of the quantum stochastic linear quadratic optimal control problem. We derive the Pontryagin maximum principle for the linear quadratic control problem of infinite-dimensional quantum stochastic systems. The equivalence between unique closed-loop solvability for quantum stochastic linear quadratic optimal control problems and the well-posedness of the corresponding quantum Riccati equations is established. Notably, although the quantum Riccati equation is an infinite-dimensional deterministic operator-valued ordinary differential equation, classical methods are not applicable. Inspired by L\"{u} and Zhang's approach [Q. L\"{u} and X. Zhang, Probability Theory and Stochastic Modelling, 101. Springer, Cham, (2021) \& Mem. Amer. Math. Soc. 294 (2024)] to stochastic Riccati equations, we prove the existence and uniqueness of its solutions. The results provide a theoretical foundation for the optimal design of quantum control.

Keywords

Cite

@article{arxiv.2502.19666,
  title  = {Quantum stochastic linear quadratic control theory: Closed-loop solvability},
  author = {Wang Penghui and Wang Shan and Zhao Shengkai},
  journal= {arXiv preprint arXiv:2502.19666},
  year   = {2025}
}

Comments

30 pages; comments are welcome

R2 v1 2026-06-28T21:59:30.662Z