Quantum control
RL for Quantum Gate Control in Noisy Environments
Ongoing research on reinforcement-learning methods for robust quantum gate control under noise.
- Year
- 2026
- Status
- Ongoing
- Topics
- Reinforcement learning · Quantum control · Robustness
A conceptual illustration of the mathematical idea, not a plot of measured experimental results.
The question
How can reinforcement learning improve quantum gate control in noisy environments?
Central insight
Noise changes the relationship between a control action and the quantum operation it produces. Robust control must account for that uncertainty when choosing actions.
Approach
- 01
Formulate quantum gate control as a reinforcement-learning problem under noisy dynamics.
- 02
Study how learned control methods respond to noise.
My contribution
- Developed reinforcement-learning methods for robust quantum gate control under noisy conditions.
Result
The research is ongoing, with robust control under noise as its central objective.
What remains
A possible next investigation is transfer to noise conditions outside the training setting.