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Charge Selection

Charge Selection. Paolo Zuccon Perugia 17/09/2005. Outline. Preselection of clean samples Gain and eta corrections Likelihood functions definition Charge selection. Clean Samples. Seed Threshold S/N>3 Choose only the highest cluster on each ladder/side

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Charge Selection

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  1. Charge Selection Paolo Zuccon Perugia 17/09/2005

  2. Outline • Preselection of clean samples • Gain and eta corrections • Likelihood functions definition • Charge selection

  3. Clean Samples • Seed Threshold S/N>3 • Choose only the highest cluster on each ladder/side • Low Charges == Require no cluster with signal >1000 • Raw alignment between the clusters separately on S and on K sides • Fit with a good chi-square probabilty • Request that the signal on the S side 6th ladder is within the peak of the desired charge (p, He, Li).

  4. Signal Characterization • The response of the silicon detector to the different charges has been studied using the clean samples of p, HeandLi • The signal has been fitted with a Gaussian­Landau + exp tail. • For each ladder 4 fits have been made considering separately for the two sides: two  ranges: Up ( < 0,2 > 0.8) Low (0,4 << 0,6). • For each type of incident particle we have 4 kind of signal: S-up S-low K-up K-low We studied the relative gain in each sample and the amplitude of the  correction for the different ions.

  5. Gain Spread – S Side Relative Gain Ladder

  6. Gain Spread – K Side Relative Gain Ladder

  7. Eta Correction – S Side

  8. Eta Correction – K Side

  9. Probability density functions • Find the typical signal of an AMS-02 ladder corresponding to the various ions ( p, He ,Li) • Use the normalized signal as probability density function (pdf) for a given ion. Our Choice:  Consider as reference the signals S-up and K-up of Ladder 1 • Apply the gain corrections and the  corrections (typical of a given ion hypothesis) to report all the ladders signal to the one of ladder 1  Calculate the probabilty for the energy loss X_{i} to come from a given ion

  10. Likelihood functions • Use the combined probability from 5 ladders to build a likelihood function • Pass to Log Likelihood with a check for underflows: If pdf(x) < 10-50 pdf(x) = 10-50 • Normalize and trasform: L = 1 – L / (n log(10-50)) • Calculated Likelihoods: • LikeSp LikeKp • LikeSHe LikeKHe • LikeSLi LikeKLi

  11. Beryllium Lithium Helium Protons

  12. Lithium Helium Beryllium Protons

  13. Selected samples To understand the real likelihood values taken by the different species we need (almost) pure samples. What we have is: • A/Z = 1 Protons Pure • A/Z = 2 Mostly He but large contribution of p and Li • A/Z=2.25 almost equal amount of p He and Li Selecting only the desired peak on the 6th ladder we obtain an almost pure sample but at which level ? We use the knowledge of the shape of the signal to evaluate it !

  14. A/Z=2 p = 0,02 % He = 99.98 % Li = 1.7 10-9%

  15. A/Z =2,25 p = 0,01 % He = 1,78 % Li = 98,21%

  16. Likelihood Ratio Lp/LHe P selection = 99,91% He selection = 98%

  17. Likelihood Ratio Lp/LHe

  18. Likelihood Ratio LHe/LLi He Eff = 99,7% misidentified as Li = 0,003 % Li Eff = 99,5% misidentified as He= 0,23%

  19. Conclusions • The likelihood method provides an efficient way to select clean samples of the different charges • Need to repeat the exercise for the higher charges

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