1. Machine Learning for Ground State Preparation via Measurement and Feedback
- Author
-
Wang, Chuanxin and You, Yi-Zhuang
- Subjects
Quantum Physics ,Physics - Computational Physics - Abstract
We present a recurrent neural network-based approach for ground state preparation utilizing mid-circuit measurement and feedback. Unlike previous methods that use machine learning solely as an optimizer, our approach dynamically adjusts quantum circuits based on real-time measurement outcomes and learns distinct preparation protocols for different Hamiltonians. Notably, our machine learning algorithm consistently identifies a state preparation strategy wherein all initial states are first steered toward an intermediate state before transitioning to the target ground state. We demonstrate that performance systematically improves as a larger fraction of ancilla qubits are utilized for measurement and feedback, highlighting the efficacy of mid-circuit measurements in state preparation tasks., Comment: 6 pages, 5 figures, 1 table
- Published
- 2025