V0 Femtoscopy in pPb @ 8.16 TeV

Analysis of V0's at CMS in pPb@8.16TeV. The main idea is to do this analysis using K0s and Lambdas (neutral particles, called V0's) and study the strong iterations. Can be extended to Cascades and Omegas (by including charge dependence)

1. Abstract

Femtoscopy allows measuring the space-time dimensions of the interacting region in a high energy collisions.

2. K0s variables

Here i included the variables (pT, eta, phi, inv. mass) for K0s, without any cut.

mass.pngeta.png

phi.png pT.png

3. Lambda variables

4. Selections

The selections used by Wei Li to reconstruct the V0's (very loose cuts):

  • V0 Reconstruction Cuts :
    • Quality: Loose
Selection used by Dener Lemos to do femtoscopy analysis:
  • Femtoscopy Cuts:
    • |η| < 2.4 (for V0s and daughters)
    • pT > 0.2 GeV (for V0s and daughters)
    • NV0s >= 2
    • Daughters with at least 1 pixel hit (remove some contamination)

This selection showed before are the standart cuts for HBT analysis used in pp. However, we have extra contamination in low qinv (see fig X). This contamination are comming from duplicated V0s (particles comming from the same daughter) or split tracks (bad reconstruction of tracks). We find three methods to remove this contamination:

  • Padova Selection (used in previous HBT analysis in pp at CMS)
    • cos θij < 0.99996
    • ΔpT < 0.04 GeV
    • Padova cuts require qinv > 0.04 GeV
  • Daughter Matching (ΔX = xi - xj, where xi and xj are the daughter with the same charge comming from different V0)
    • ΔpT < 0.04 GeV
    • Δφ < 0.04
    • Δη < 0.04
    • Compatible with Padova cuts (i will include some plots to show that)
  • Ndof cut
    • ndof > 1 (most of duplicated V0s are comming from ndof=1)
    • This cut remove also qinv > 0.1 GeV
We have decided to use the Padova cuts in our case.

5. Mass Fit

To do our analyse, we have to separate our invariante mass histogram in two: i) the peak (signal) region; and ii) the sideband (background) region. In order to remove the background contribution, we perform mass fits, and we find the fraction signal/background in the peak region, and we can use the sideband to estimate the shapes.

  • Mass Signal and Sideband are extracted by mass fits
    • Mean - 2*sigma < Mass Signal < Mean + 2*sigma (peak region)
    • Mean - 5*sigma < Mass Sideband or Mass Sideband > Mean + 5*sigma (sideband region)

We have used a similar fit as used in CMS-AN-[hyperlink]. The signal is discribed by a double gaussian and the background with a 4th order Chebychev polinomial. An example of the fit result for K0s is show in this figure above.

k0smass-1.png

6. Reference Sample

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7.


-> Tests using charged hadrons

-- denerslemos - 2019-04-11

Comments

EDAnalyzer


Topic attachments
I Attachment History Action Size Date Who Comment
PNGpng eta.png r1 manage 37.9 K 2019-04-26 - 17:19 UnknownUser  
PNGpng mass.png r1 manage 41.7 K 2019-04-26 - 17:19 UnknownUser  
PNGpng pT.png r1 manage 36.7 K 2019-04-26 - 17:26 UnknownUser  
PNGpng phi.png r1 manage 45.7 K 2019-04-26 - 17:19 UnknownUser  
Topic revision: r3 - 2020-11-02 - denerslemos
 

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