A.Poklonskiy (SPbSU, MSU), D.Neuffer (FNAL) C.Johnstone (FNAL), M.Berz (MSU), K.Makino (MSU) - PowerPoint PPT Presentation

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Exploring and optimizing A diabatic B uncher and P hase R otator for Neutrino Factory in COSY Infinity. A.Poklonskiy (SPbSU, MSU), D.Neuffer (FNAL) C.Johnstone (FNAL), M.Berz (MSU), K.Makino (MSU). Goal & Problems. Goal:

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A.Poklonskiy (SPbSU, MSU), D.Neuffer (FNAL) C.Johnstone (FNAL), M.Berz (MSU), K.Makino (MSU)

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A poklonskiy spbsu msu d neuffer fnal c johnstone fnal m berz msu k makino msu

Exploring and optimizing Adiabatic Buncher and Phase Rotator for Neutrino Factory in COSY Infinity

A.Poklonskiy (SPbSU, MSU), D.Neuffer (FNAL)

C.Johnstone (FNAL), M.Berz (MSU), K.Makino (MSU)

Goal problems

Goal & Problems


  • Build neutrino factory to study different neutrino-related things and/or muon collider… to collide


  • Muons are short-living particles  compact lattice, fast beam gymnastics

  • Muons are produced with large initial momentum spread  cooling

  • Energy spread is large  energy spread reduction before cooling

  • Some desired beam manipulations requires new types of field configuration  development of such new elements

  • All these  small muons production rate (<0.2) and…PRICE!

R d goal affordable e factory

R&D goal: “affordable” e,  -Factory

  • Improve from baseline:

    • Collection

      • Induction Linac “high-frequency” buncher

    • Cooling

      • Linear Cooling  Ring Coolers

    • Acceleration

      • RLA  “non-scaling FFAG”

–  e– + ne + 

+  e+ + n + e


The Neutrino Factory and Muon Collider Collaboration


Rf cavity and solenoid in pictures

RF Cavity and Solenoid in Pictures

Adiabatic buncher rotator david neuffer

Adiabatic buncher + () Rotator (David Neuffer)

  • Drift (90m)

    •  decay, beam develops  correlation

  • Buncher (60m) (~333Mhz200MHz, 04.8MV/m)

    • Forms beam into string of bunches

  •  Rotator (~12m)(~200MHz, 10 MV/m)

    • Lines bunches into equal energies

  • Cooler (~50m long)(~200 MHz)

    • Fixed frequency transverse cooling system

  • Replaces Induction Linacs with

  • medium-frequency RF (~200MHz)

Longitudinal motion 2d simulations

Longitudinal Motion (2D simulations)



(E) rotator


System would capture both signs(+, -)

Key parameters

Key Parameters

  • Drift

    • Length LD

  • Buncher

    • Length LB

    • RF Gradients EB

    • Final RF frequency RF (LD, LB, RF: (LD + LB) (1/) = RF)

  • Phase Rotator

    • Length LR

    • Vernier offset, spacing NR, V

    • RF gradients ER

Lattice variations

Lattice Variations

  • Shorter bunch trains (for ring cooler, more ’s lost)?

  • Longer bunch trains (more ’s survived)?

  • Different final frequencies? (200,88,44Mhz)

  • Number of different RF frequencies and gradients in buncher and rotator (60…10)?

  • Different central energies (200MeV, 280MeV, optimal)?

  • Matching into cooling channel, accelerator

  • Transverse focusing (150m B=1.25T solenoidal field or…)?

  • Mixed buncher-rotator?

  • Cost/perfomance optimum?


Cosy infinity simulations

COSY Infinity Simulations

  • COSY Infinitycode (M. Berz,K. Makino, et al.)

    • Where M – map of the equations of motion (flow), obtained as a set of DA – vectors (Taylor expansions of final coordinates in terms of initial coordinates)

    • uses DA methods to compute maps toarbitrary order

    • own programming language allows complicatedoptimization scenarios writing

    • internal optimization routines and interface to add more

    • provides DA framework which could significantly simplify use of gradient optimization methods

    • model is simple now, but much more complicated in future and COSY has large library of standard lattice elements

Big problem

Big Problem

Use ofTaylor seriesleads to tricky way of handling beams with large coordinate spread (and that is exactly the case) Relative coordinates should be < 0.5 (empirical fact)

Straightforward division

Straightforward division

Equations of longitudinal motion

Equations of Longitudinal Motion

synchronous particle

equations in deviations from synchronous particle

nonlinear oscillator

COSY Infinity uses similar coordinates

Consequences of equations of motion

Consequences of Equations of Motion

  • Existence of stable regions, where we have oscillatory motion and unstable regions, and, therefore existence of separatrix (depends on frequency, RF gradient, synch. phase, etc… ). Stable area is called the “bucket”.

Beam evolution

Beam Evolution

Clever division

Clever Division

  • Use central energies as centres of boxes, use RF period as ranges for the box

  • Add “jumping” between intervals after each step. We change buckets and particles could be lost in one bucket and re-captured in another

Still a problem

Still a Problem

  • 50 central energies x 60 RF cavities in Buncher = 300 maps…

  • We are using DA arithmetic, everything is a DA-vector, including elementary functions (sin), so we need relatively high expansion order. Use 2 times more intervals + 5th orderleads to natural advantage in buncher… maybe.

  • Use COSY’s ability to generate parameter-dependent maps with ease and special law of bunches central energies distribution (smaller energies tends to be closer to each other)

    40-50 maps  12-15 maps

    Potential calculation time reduction. Implementing.

  • 6000 particles, 50 central energies, 70 RFs

    • 1st order: 0 hrs 10 min

    • 7th order: 8 hrs some mins


Sin taylor expansion

Sin Taylor expansion

Different order simualtions

Different Order Simualtions

Different order simualtions1

Different Order Simualtions



  • Model is implemented in COSY Infinity and checked for consistency with other codes

  • Some removal of the obstacles is done

  • Brute-force optimization still seems to be infeasible. Looking for some more sophisticated method.

Yet unanswered questions

Yet Unanswered Questions

  • Should longitudinal motion be studied separately, or should it be included on the very early stages?

  • Are there any map-dependent criterias which could be used for map-based optimization?

Second optimization approach

Second Optimization Approach

  • From synchronism condition one could derive following relation for kinetic energies of synch particles:

Final kinetic energy relation

Final Kinetic Energy Relation

  • From the rotator concept one could derive amount of energy gained by n-th synchronous particle in RF

  • So for final energy n-th particle has after the rotator consists of m RFs we have

Evolution of central energies shape t n m

Evolution of central energies shape T(n,m)

Energies shape in buncher and amount of kick they get in rotator

Energies shape in buncher and amount of kick they get in rotator

Energy shape evolution in rotator

Energy Shape Evolution in Rotator

Objective functions

Objective Functions

  • The idea of the whole structure is to reduce overall beam energy spread and to put particles energies around some central energy. So we have general objective function:

  • First, we can set and get

Different optimized paremters n vs t fin

Different optimized paremters (n vs T_fin)

Different optimized paremters t 0 vs t fin

Different optimized paremters (T_0 vs T_fin)

Evolution of central energies shape unoptimized

Evolution of central energies shape (unoptimized)

Evolution of central energies shape optimized

Evolution of central energies shape (optimized)

Evolution of central energies shape optimized1

Evolution of central energies shape (optimized)

Different optimized paremters t 0 vs t fin energies distribution

Different optimized paremters (T_0 vs T_fin) + energies distribution

Objective functions1

Objective Functions

  • For calculating we can use particle’s energies distribution

  • n energy particles %

  • ----------------------------------------------

  • -12 963.96 1023 17.050000

  • -11 510.85 692 11.533333

  • -10 374.64 537 8.950000

  • -9 302.98 412 6.866667

Different optimized paremters n vs t fin1

Different optimized paremters (n vs T_fin)



  • Model of buncher and phase rotator was written inCOSY Infinity

  • Simulations of particle dynamics in lattice with different orders and different initial distributions were performed

  • Comparisons with previous simulations (David Neuffer’s code, ICOOL, others) shows good agreement

  • Several variations of lattice parameters were studied

  • Model of lattice optimization using control theory is proposed

  • Model of central energies distribution is developed. Some results for parameters have been obtained

Future plans

Future Plans

  • Finish central energies optimizations, try changing more parameters, check optimized parameters for whole distribution (COSY, ICOOL?)

  • Develop some criteria for simultaneous optimization of central energies and energies of all paritcles in a beam or use control theory approach for the whole longitudinal motion optimization

  • Study transverse motion and particles loss because of decay and aperture, final emittance cut

  • Different lattices for different cooling sections/targets/whatever proposed (project is on R&D status)

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