Next-Generation Beam Cooling and Control with Optical Stochastic Cooling
Description
This program leverages the physics and technology of optical stochastic cooling (OSC) to explore new possibilities in beam control and sensing. The planned architecture and performance of a new OSC system at IOTA should enable turn-by-turn programma
Detailed example
The AI system will continuously infer the state of a circulating beam distribution and then use this inference in the execution of an RL-based control policy. The primary means of control is an advanced optical stochastic cooling system.
AI / analytics pattern
Reinforcement Learning: AI trained through trial and error using rewards and penalties to optimize decision-making policies.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
This effort focuses on enhanced real-time control of the structure of circulating particle beams. The additional performance and capabilities provided may enable substantially greater operational flexibility and science reach at current and future DOE accelerator facilities.
Audit / financial statement impact
The use case does not have an effect on civil rights/liberties/privacy, access to education/housing/insurance/credit/employment, access to critical government resources/services, human health/safety, critical infrastructure/public safety
Controls / human review
ATO: No; PIA: Not published
Data needed
Large-scale simulation data is being used to train the diagnostic and control systems. Online training with experimental data may also be leveraged once the system is operational.