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The Mid-rapidity code

Module: Mid-rapidity tracklet code for dN/deta

Introduction

The code in this section defines methods to measure the charged-particle pseudorapidity density over \(|\eta|<2\) using SPD tracklets.

The input to this analysis is the ESD information from the SPD, and SPD clusters (Rec-points). The code is derived from Ruben's original code plus modifications from Roberto for reweighing the simulation input.

Analysis flow

The analysis requires real data and simulated data, anchored to the real data runs being processed. For both real and simulated data, the analysis progresses through two steps:

  • A pass over ESD plus clusters to generate an AOD branch containing a TClonesArray of AliAODTracklet objects. In this pass, there are no selections imposed on the events. In this pass, the SPD clusters are reprocesed and the tracklets are re-reconstructed.

    In this pass, we also form so-called injection events. In these events, a real cluster is removed and a new cluster put in at some other location in the detector. The tracklets of the event is then reconstructed and stored. This procedure is repeated as many times as possible. The injection events are therefore superpositions of many events - each with a real cluster removed and replaced by a fake cluster. The injection events are used later for background estimates.

    When processing simulated data, the tracklets are also inspected for their origin. A tracklet can have three distinct classes of origins:

    • The tracklet is formed from two clusters generated by the same primary particle.
    • The tracklet is formed from two clusters generated by the same secondary particle.
    • The tracklet is formed from two clusters generated by two different particles (primary or secondary).

    The last class is the background from combinations of clusters that does not correspond to true particles. This background must be removed from the measurements.

    The second class, tracklets from secondaries, also form a background, but these tracklets are suppressed by cuts on the sum-of-square residuals

\[ \Delta = \left[\frac{\Delta_{\theta}^2\sin^2\theta}{\sigma_{\theta}^2}+ \frac{(\Delta_{\phi}-\delta_{\phi})^2}{\sigma_{\phi}^2}\right] \]

  • In the second pass, the tracklets are read from the AOD events and processed in \(\eta,\mathrm{IP}_z\) bins. The measured tracklets ( \(M\) or \(M'\)), tracklets from injection events ( \( I\) or \( I'\)) - and for simulated data - tracklets corresponding to primary ( \( P'\)), secondary ( \( S'\)), and combinatorial background ( \( C'\)), as well as the pseudo-tracklets corresponding to the generated charged, primary paricles ( \( G'\)), are histogrammed to form

\[ \frac{d^2N_X}{d\eta d\mathrm{IP}_z}\quad, \]

where \( X\) is \( M\) or \( I\) for real data, or \( M',I',P',S',C'\) or \( G'\) for simulated data.

For each of these tracklet samples, except \( G'\), we also form the 3-dimensional differential \(\Delta\) distributions

\[ \frac{d^3N_X}{d\eta d\mathrm{IP}_z d\Delta}\quad, \]

which are later used to estimate the background due to wrong combinations of clusters into tracks.

Once both the real and simulated data has passed these two steps, we combine the to data sets into the final measurement. The final measurement is given by

\[ R = \frac{G'}{(1-\beta')M'}(1-\beta)M, \]

where

\[ \beta' = \frac{C'}{M'}\quad\mathrm{and}\quad \beta = k\beta'\quad. \]

Here, \( k\) is some scaling derived from the 3-dimensional differential \(\Delta_M\) and \(\Delta_{M'}\) distributions .

Structure

There are classes for containing data, classes that represent analysis tasks, and classes that perform calculations, as well as specialized classes for analysis of simulation (MC) output.

Data structures

The classes AliAODTracklet and AliAODMCTracklet stores individual tracklet parameters. The difference between the two are that AliAODMCTracklet also stores the PDG code(s) and transverse momentum (momenta) of the mother primary particle (which may be the particle it self).

Tasks

The pass over the ESD is done by the classes AliTrackletAODTask and AliTrackletAODMCTask. These tasks generated the array of tracklets in the AOD events. The difference between the two is that AliTrackletAODMCTask inspects and groups each tracklet according to it's origin, and create pseudo-tracklets corresponding to the generated primary, charged particles.

The second pass is done by one of the three classes AliTrackletAODdNdeta, AliTrackletAODMCdNdeta, or AliTrackletAODWeightedMCdNdeta. These tasks build the ditributions

\[ \frac{d^2N_X}{d\eta d\mathrm{IP}_z}\quad, \]

and

\[ \frac{d^3N_X}{d\eta d\mathrm{IP}_z d\Delta}\quad. \]

The first task does this for \( X=M\) and \( I\), while the second and thhird tasks does this for \( X=M',I',P',S',C'\) and \( G'\). The third task reweighs all tracklets according to the particle specie(s) and transverse momentum (momenta) of the mother primary particle(s). AliTrackletWeights defines the interface used for reqeighing the data.

Misc.