1. Possibilità di tesi presso il CNAO
Marco Pullia per conto del gruppo acceleratori
Dottorato in Fisica “Sapienza” Università di Roma, 4 ottobre 2018 1

2. CNAO More precise, more efficient
A centre dedicated to tumour treatment with protons and carbon ions located in Pavia
IMRT
Hadrontherapy
More precise, more efficient
Carbon ions
Electrons
Photons
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3. Resonant multi-turn extraction
Slow Extraction
A single turn extraction (<1μs) not possible
Resonant multi-turn extraction
Create stable area in phase space → slowly drive particles into resonance → long spill over many thousand turns
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Implementation of RFKO Extraction System

4. Extraction methods
Beam can be driven to the resonance condition by three methods:
Amplitude-momentum selection
Amplitude selection
RF-KO
Q or Δp/p A
(Δp/p)resonance
separatrix
(Δp/p)stack
Un-stable region
Stable region
Q or Δp/p A
(Δp/p)resonance
separatrix
(Δp/p)stack
Q or Δp/p A
(Δp/p)resonance
separatrix
(Δp/p)stack
Un-stable region
Stable
region
The beam is wide in momentum with respect to the stop band. The tune of the particles is then varied by accelerating them with a betatron core while leaving untouched the tune of the machine.
Everything stays constant apart from the beam which is subject to a transverse RF perturbation (noise or single frequency swept through the betatron frequencies) that blows its emittance up. When the particle’s amplitude reaches the separatrix, they become unstable andare extracted.
Not used at CNAO
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5. Project aim
RF-KO extraction implementation (both theoretical and hardware aspects)
Installation and commissioning of the new extraction system
Comparison between RF-KO and Amplitude-momentum systems
Study of implementation of a multi-energy extraction process
The work will be carried out in Pavia
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Implementation of RFKO Extraction System

6. Neural networks for accelerator control
Accelerators should be able to run for extended periods of time with minimal interruptions. Traditional control techniques sometimes are not sufficient. One promising pathi s to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. 
The use of neural network-based modelling and control techniques could be of significant benefit to particle accelerators.
Looking for a collaboration on the subject with groups with previous experience and a candidate with some preliminary knowledge to setup the study.

7. Thanks
“The important thing is not to stop questioning” Albert Einstein