ACD Recon update to sorting and selecting associations

This pages describes changes to how we decide which associations are most important

 Sorting track-hit associations

Currently all the associations are stored on a single collection of AcdTkrHitPoca objects.  These are sorted by active distance.   This means that AcdTkrHitPoca's from later tracks can be placed before ones from the best track.  

In the new algorithm the  AcdTkrHitPoca are sorted by VetoProbabliity.  This is constructed by adding terms for the geometry and terms for the signal size
   VetoSigmaProj = active3D < 0 ? 0 :  active3D / activeDist3DErrProj;
   VetoSigmaHit = 2. / pocaData.m_cosTheta < totalMips ? 0 :  (( 2. / pocaData.m_cosTheta) - totalMips)/0.45  [ tiles ]
   VetoSigmaHit =1.5 < totalMips ? 0 :  (1.5 - totalMips)

Both terms are constructed so that:

1. They are 0. for anything that looks like a good MIP (ie, track point at hit tile, signal is at MIP peak)
2. They become positive as the event looks less MIP like (ie, track missed hit tile, signal is below MIP peak) 

Then we can combine them in quadrature
  VetoSigma = sqrt( VetoSigmaProj*VetoSigmaProj + VetoSigmaHit*VetoSigmaHit)

This means that for tiles there is some contribution for expected signals less that a mip.  From ribbons this contribution only gets up to 1.5 sigma.

 Sorting track-gap associations

Currently all the associations are stored on a single collection of AcdTkrGapPoca objects.  These are sorted by active distance.   This means that AcdTkrGapPoca's from later tracks can be placed before ones from the best track.  

In the new algorithm the  AcdTkrGapPoca are sorted by VetoProbabliity.  This is constructed by adding terms for the geometry and terms for the signal size
   VetoSigmaProj = Prob inside gap expressed in Sigma
   VetoSigmaHit =1.5  [ gaps covered by ribbons ]
   VetoSigmaHit = 0 [ gaps not covered by ribbons ]

Both terms are constructed so that:

1. They are 0. for anything that looks it really went into a gap  (ie, track points at gap)
2. They become positive as the event looks less MIP like (ie, track missed gap, gap is covered by ribbon) 

Then we can combine them in quadrature
  VetoSigma = sqrt( VetoSigmaProj*VetoSigmaProj + VetoSigmaHit*VetoSigmaHit)

 Associations between tracks and hit tiles

In AcdValsTool there is a test if a track comes close to a tile,  this is defined as -300./sqrt(CAL_EnergyRaw/100).  For those tiles the algorithm then selects the
AcdTkrHitPoca with the largest energy that passed the distance cut.

For each track the new algorithm sorts all AcdTkrHitPoca by increasing VetoSigma.  In AcdValsTool we select the AcdTkrHitPoca with the smallest veto sigma, making sure to only use those AcdTkrHitPoca that actually have a hit in the tile. 

So, if a track comes close to two tiles with signal, we may expect to see a different tile selected.  Note however that with the new algorithm the energy will always be lower.  

 Best Track

 All Tracks

 Associations between tracks and hit ribbons

In AcdValsTool we simply select the ribbon with the largest active distance. 

With the new algorithm this changes a little bit since we are now using the active distance / the error projection. 

Best Track

 All Tracks

 Assocations between tracks and gaps

In AcdValsTool we simply select the gap with the largest active distance.

 With the new algorithm this changes a little bit since we are now using the active distance / the error projection. 

Best Track

 All Tracks