Work

Dynamic Programming Principle and Stabilization for Mean-Field Quantum Filtering Systems

Year: 2026

Type: conference-paper

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.

Source: IEEE International Conference on Quantum Control, Computing and Learning (qCCL)

DOI: 10.1109/qccl70331.2026.11668565

Authors: Sofiane Chalal, Nina H. Amini, Hamed Amini, Mathieu Laurière

Institutions: Université Paris-Saclay, University of Florida, New York University Shanghai, New York University

Language: English

Topic: Quantum Information and Cryptography

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7129023611

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