Non-linear dynamics Yannis PAPAPHILIPPOU CERN

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Non-linear dynamics Yannis PAPAPHILIPPOU CERN United States Particle Accelerator School, University of California - Santa-Cruz, Santa Rosa, CA 14 th 18 th January 2008 1

Summary Driven oscillators and resonance condition Field imperfections and normalized field errors Perturbation treatment for a sextupole Poincaré section Chaotic motion Singe-particle diffusion Dynamics aperture Frequency maps 2

Damped and driven harmonic oscillator Damped harmonic oscillator: Q is the damping coefficient (amplitude decreases with time) ω 0 is the Eigenfrequency of the harmonic oscillator An external force can pump energy into the system General solution ω the frequency of the driven oscillation with Amplitude U(ω) can become large for certain frequencies 3

Resonance effect U(ω) Q>1/2 α(ω) Q>1/2 Q<1/2 π/2 Q<1/2 ω ω ω 0 0 ω Without or with weak damping a resonance condition occurs for Infamous example: Tacoma Narrow bridge 1940 excitation by strong wind on the eigenfrequencies! =! 0 4

Perturbation in Hills equations Hill s equations with driven harmonic force where the F is the Lorentz force from perturbing fields Linear magnet imperfections: derivation from the design dipole and quadrupole fields due to powering and alignment errors Time varying fields: feedback systems (damper) and wake fields due to collective effects (wall currents) Non-linear magnets: sextupole magnets for chromaticity correction and octupole magnets for Landau damping Beam-beam interactions: strongly non-linear field Space charge effects: very important for high intensity beams non-linear magnetic field imperfections: particularly difficult to control for super conducting magnets where the field quality is entirely determined by the coil winding accuracy 5

Localized Perturbation Periodic delta function { " ( s! s ) 1 for s = s 0 L 0 = and "# ( s! s0 ) ds = 1 0 otherwise L Equation of motion for a single perturbation in the storage ring Expanding in Fourier series the delta function Infinite number of driving frequencies!!! Recall that the driving force can be the result of any multi-pole 6

Resonance conditions and tune diagram Equations of motion (u = x or y) including all multi-pole errors Solved with perturbation theory approach with At first order Resonance condition There are resonance lines everywhere!!! 7

Choice of the working point Regions with few resonances: Q y 9 th 4 th & 8 th 11 th 7 th Avoid low order resonances < 12 th order for a proton beam without damping < 3 rd 5 th order for electron beams with damping Close to coupling resonances: regions without low order resonances but relatively small! Q x 8

Single Sextupole Perturbation Consider a thin sextupole perturbation Equations of motion With The equation is written Resonance conditions integer third integer No exact solution Need numerical tools to integrate equations of motion 9

Poincaré Section Record the particle coordinates at one location (BPM) Unperturbed motion lies on a circle (simple rotation) Resonance is described by fixed points For a sextupole The particle does not lie on a circle! The change of tune per turn is Poincaré Section: y s x x" /! 0 x x" /! 0! R x 2 3 x" /! 0 "! turn 1 x x" /! 0 2! Q 0 R+ΔR x 10

Topology of a sextupole resonance Small amplitude, regular motion Large amplitude, instability, chaotic motion and particle loss Q < r/3 x" /! 0 Separatrix: barrier between stable and unstable motion (location of unstable fixed points) 1 2 x R fp 3 x x Octupole 11

Sextupole effects 12

Optimization of Dynamic aperture Keep chromaticity sextupole strength low Include sextupoles in quadrupoles for more flexibility Try an interleaved sextupole scheme (-I transformer) Choose working point far from systematic resonances Iterate between linear and non-linear lattice 13

Frequency Map analysis Oscillating electrons in storage ring generally obey quasi-harmonic motion close to the origin for a good working point Large amplitudes sample more non-linear fields and motion becomes chaotic - i.e., the frequency of oscillation (tune) changes with turn number. Motion close to a resonance also exhibits diffusion Frequency map analysis examines dynamics in frequency space rather than configuration space. Regular or quasi-regular periodic motion is associated to unique tune values in frequency space Irregular motion exhibits diffusion in frequency space, i.e. tunes change The mapping of configuration space (x and y) to frequency space (Q x and Q y ) is regular for regular motion and irregular for chaotic motion. Numerically integrate the equations of motion for a set of initial conditions (x, y, x,y ) and compute the frequencies as a function of time Small amplitude, regular motion Large amplitude, chaotic motion and particle loss 14

NAFF algorithm Quasi-periodic approximation through NAFF algorithm of a complex phase space function defined over for each degree of freedom with and Advantages of NAFF: a) Very accurate representation of the signal (if quasi-periodic) and thus of the amplitudes b) Determination of frequency vector with high precision for Hanning Filter 15

Aspects of frequency map analysis Construction of frequency map Determination of tune diffusion vector and construction of diffusion map LHC Simulations Papaphilippou PAC99 ALS Measurements Robin et al. PRL2000 Determination of resonance driving terms associated with amplitudes Bengtsson PhD thesis CERN88-05 SPS Measurements Bartolini et al. PAC99 LHC Simulations Papaphilippou PAC99 16

Building the frequency map Choose coordinates (xi, yi) with px and py=0 Numerically integrate the phase trajectories through the lattice for sufficient number of turns Compute through NAFF Qx and Qy after sufficient number of turns Plot them in the tune diagram 17

Frequency Map for the ESRF All dynamics represented in these two plots Regular motion represented by blue colors (close to zero amplitude particles or working point) Resonances appear as distorted lines in frequency space (or curves in initial condition space Chaotic motion is represented by red scattered particles and defines dynamic aperture of the machine 18

References O. Bruning, Non-linear dynamics, JUAS courses, 2006. 19