Beam Dynamics and Control Optimal Outcome:
To conserve the Brightness of beams from extreme-low MTE linac sources subject to intense Coulomb interactions (
Conserve), increased brightness of beams in storage rings ( Cool), and advanced techniques for the optimization of many-parameter accelerators ( Control). By ensuring that CBB advances in beam production and beam acceleration are realized in brightness at the target, this theme unifies the center’s research.
Download Beam Dynamics and Control Roadmap
Objective 1 (Conserve): Probe the ultimate limits of brightness conservation in the presence of collective effects in low MTE photoinjector beamlines. Deliverable: Experimental demonstration of sub-nanometer emittance in at least one beamline with low bunch current with annual improvements thereafter (Annual, starting 2022).
Deliverable: Identification of beamlines for a potential experimental demonstration of the simultaneous generation of low emittance and high bunch charge, using CBB low-MTE photocathodes and diagnostics, and the development of possible experimental plans for identified beamlines (Spring 2023).
Deliverable: Characterization of the performance of photocathodes in either high field or high current conditions as needed to complete
PHC Deliverables 2.1 and 2.2 (Annual, starting 2023).
Objective 2 (Cool): Develop methods for cooling beams using optical stochastic cooling to increase beam luminosity in next-generation colliders. Deliverable: Proof-of-principle demonstrations of key elements of optical stochastic cooling at IOTA and CESR (Completed Spring 2022).
Deliverable: Proof-of-principle demonstrations of key elements of
active optical stochastic cooling at IOTA or CESR (Summer 2025). Deliverable: Configurations capable of the extremely high cooling rates needed for use in a future collider (Summer 2026).
Objective 3 (Control): Investigate advanced optimization schemes, including Machine Learning (ML) and parameter reduction techniques, for precision phase-space control of particle accelerator systems. Deliverable: Electron Microcsope tuned using ML techniques whose performance is comparable to that of traditional operator tuning (Completed Summer 2022).
Deliverable: Electron Microscope whose higher-order aberrations are tuned using ML techniques, replacing the regular maintenance interventions by microscope company specialists that are required to keep the conventional alignment software operational (Summer 2025).
Deliverable: Methods for efficient tuning of accelerators (Summer 2025).
Deliverable: Summary of the boundaries of applicability of ML in accelerators (Fall 2026, stretch).