1 / 24

Emittance Calculation Progress and Plans

Emittance Calculation Progress and Plans. Chris Rogers MICE CM 24 September 2005. About the Beard… It could have been worse…. Overview. Talk in detail about how we can do the emittance calculation Sample bunch Remove experimental error (PID & tracking) Calculate Emittance

ember
Download Presentation

Emittance Calculation Progress and Plans

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Emittance Calculation Progress and Plans Chris Rogers MICE CM 24 September 2005

  2. About the Beard… • It could have been worse…

  3. Overview • Talk in detail about how we can do the emittance calculation • Sample bunch • Remove experimental error (PID & tracking) • Calculate Emittance • Talk about other useful quantities • Scraping/Aperture • Decay Losses • Single Particle Emittance • Single Particle Amplitude • Holzer Particle Number

  4. Emittance Calculation Roadmap Uimeas PID Understood, tools exist Roughly understood Not really understood Sampled bunch I’ll run through each box in this talk Vmeas Vtrue Emittance(z)+/- error

  5. Beam Matching • The cooling channel is designed to accept a certain distribution of particles • The beta function should be periodic over a cell of the magnetic field • The beta function should be a minimum in the liquid Hydrogen for optimal cooling • The longitudinal distribution should be realistic for the appropriate phase rotation system • My standard approach is to • Do a reasonable job with the beamline (for good efficiency) • Then sample a Gaussian distribution from the available events for the final analysis • Assign each muon some statistical weight w • Matching Condition is usually (b, a) = (333 mm, 0) in the upstream tracker solenoid (MICE Stage VI) • Note b=400 mm for pz = 240 MeV/c

  6. Sampling a bunch - stupid algorithm • Stupid algorithm already exists but fails • Bin particles • Density, rbin = nbin/(bin area) • Apply statistical weight to all particles in bin • Wbin= rrequired/rbin • Fails because number events in each bin goes as • With 106 particles and 10 bins/dimension we have ~ 1 particle in each bin • Atrocious precision • Should be possible to do better • Some algorithms planned but not implemented

  7. Momentum Amplitude Correlation • At least three definitions of the amplitude exist • “Palmer” (FSII) • “Balbekov” (muc258) • “Ecalc9” (muc280) - note units are [mm] • A prescription for generating the correlation exists • Generate transverse phase space in a gaussian as normal • Generate dE or dpz in a gaussian as normal • But add a term to make E or pz like • Nothing more than a handwaving justification in the literature • A prescription we can follow I guess • But many questions remain

  8. More on P-A correlation (FS2) • Build grid in phase space all with pz 200 MeV/c e.g. • (x,px) = (0,5) (0,10) (0,15) … (5,5) (5,10) (5,15) … • Fire it through MICE magnetic fields • No RF/LH2 • We introduce a momentum amplitude correlation!!! <A2> 15 pi <A2> 6 pi

  9. Smeas • We then calculate the covariance matrix using • Where uiare the measured phase space coords, and w is the statistical weight • I haven’t specified whether we use px or x’=px/pz type variables • Recall emittance is related to the determinant of the 2N dimensional covariance matrix according to • Where the additional factor of <pz> is required if we use x’ type variables to normalise the emittance • And S is the matrix with elements sij or

  10. Strue • This gives us the measured covariance matrix • Includes errors due to mis-PID • Includes errors due to detector resolutions • Correct for detector resolutions • Detector resolution introduces an offset in emittance • If we can characterise our detector resolutions well, we can understand and correct the offset • Correct for mis-PID • Mis-PID also introduces an offset • If we can characterise our PID and beam well, we can in principle correct this offset

  11. Measurement Error • The expression for Smeas in terms of the error in the measurement of the phase space variable is given by • For a bit more detail see MICE Note 90 (tracker note) • This is similar to addition in quadrature, except that the error is not independent of the phase space coordinates • Error on emittance not only dependent on the resolution in a single phase space variable • Worry about whether an error in x introduces and error in px • Worry about whether the error in x is greater at different px • E.g. worry that the TOF resolution at the reference plane is highly dependent on the pz resolution of the tracker

  12. Uncorrected 4D Emittance (Ellis)

  13. Corrected 4D Emittance (Ellis)

  14. Calculating the Error • Calculate the values of R, C using G4MICE • Verify G4MICE in stage I & II • Knowing the error is more important to the baseline analysis than the actual size of the error • Requires some care • Once we are beyond MICE stage I & II it will be difficult to re-verify G4MICE • If the detector errors change we will be blind • E.g. the spectrometer field drifts, a fibre dies, etc… • So we should understand the errors in detail • So, for example, if the B-field drifts during the experiment we can spot it • We should be actively checking sources of error • Check spectrometer field between runs, etc…

  15. PID • Error introduced on covariance measurement by mis-PID is something like • bs is background identified as signal, sb is signal identified as background • This should be after the bunch sampling • We should be able to estimate this offset • We can measure the distribution of incoming particles • We can calculate the probability of mis-identification (from e.g. Monte Carlo simulation) • In the case that Vijbs, Vijsb ~ Vijtrue emittance is not changed • Nmeas=Ntrue+Nbs-Nsb • We should also worry about measurement of transmission • Perhaps this is more important for PID • We need to understand what analysis is required for scraping • These ideas need to be verified by simulation

  16. Useful Quantities - Scraping • There exists a closed surface in phase space beyond which particles strike the walls • Surface in 6D phase space • We should be able to measure this surface • Transmission, radiation damage, ?dynamic aperture?, ?rf bucket? • We should be able to measure the effects on the muon of striking the walls • Are all particles lost? • This means that we must have sufficient acceptance in the detectors etc that the entire scraped surface makes it to the first absorber • It would also be useful to distinguish between scraping losses and decay losses • Is this possible?

  17. Useful Quantities - Decay Losses • We may also want to get at decay losses • Expect ~ 20% or more loss in a FS2 style neutrino factory cooling channel due to decays • But should be easily calculable

  18. Useful Quantities - SPE • Single Particle Emittance ei • V is the matrix of covariances • U is particle position • O is the matrix of measured optical functions a, b, etc • V=enO • Can be calculated in G4MICE Analysis SPE is area of this ellipse Position of particle RMS contour of bunch

  19. Constancy of SPE • Fire a 5 p beam through MICE stage VI with only magnetic fields • No RF/liquid Hydrogen • Individual SPE’s change by ~10 %, <SPE> ~ constant

  20. Cooling ito SPE • Now add RF (electrostatic?) and LH2 • Note <SPE> decreases by ~10% … Cooling!! (e~<SPE>/2n)

  21. Useful Quantities - SPA • SPA single particle amplitude ~ Ecalc9f amplitude above • Calculate optical functions Oc • SPE-like quantity independent of bunch measurement • Can be calculated in G4MICE Analysis • Note Oc is not uniquely defined (depends on input beam) • One powerful use of this method is to look at phase space without requiring any bunch • Good for simulation • Possibly use as an experimental technique? • Get much higher statistics in particular regions of phase space • Get back to “bunch amplitude” ~ bunch emittance • Use

  22. Example use - nonlinear optics D(A2)/A2 • Build grid in phase space as above • Fire it through MICE magnetic fields • Examine change in amplitude upstream vs downstream • No RF/LH2 • Show nice features • Dynamic aperture? • Emittance growth vs (x,px,y,py)? DA2/A2 Initial x Initial A2

  23. Useful Quantities - Holzer Emittance • Calculate the maximum number of particles sitting in an arbritrary hyper-ellipsoid of a given volume • Holzer suggests using a minimising algorithm to find the hyper-ellipsoid of a particular volume that has the most particles in it • To first approximation, this will be similar to the hyper-ellipsoid given by UTV-1U • Then this becomes the number of particles with SPE lower than some value ~ the volume of the hyper-ellipsoid

  24. Unanswered Questions • How do we do the offline bunching? • I have some ideas • This is the next thing to tackle • Analysis of longitudinal dynamics • We need to understand the TOF resolution ito 6D emittance measurement • How do we do the 6D emittance measurement? • How good is the PID in terms of emittance? • Do we need the correction/will it really work? • Does there exist a serious understanding of momentum-amplitude correlation? • We cannot really talk about this without understanding • We need a detailed analysis of the non-linear beam dynamics of the cooling channel • More detail on the scraping/transmission analysis

More Related