Dynamic Programming Principle and Stabilization for Mean-Field Quantum Filtering Systems
Abstract
Working within the quantum filtering framework, we establish a dynamic programming principle in an infinite-dimensional setting by embedding the state space into the Hilbert-Schmidt space. We then study a stabilization problem for continuously monitored Ising-coupled qubits and, in the mean-field limit, demonstrate quantum state reduction together with exponential convergence toward prescribed eigenstates under suitable feedback laws.
Fields of Study & Subjects
Quantum Information and Cryptography
Quantum Mechanics and Applications
Quantum Computing Algorithms and Architecture
Publication details
- Journal / source
- IEEE International Conference on Quantum Control, Computing and Learning (qCCL)
- Pages
- 1–8
- Publication date
- 1 June 2026
- Language
- EN