Difference: DecayTreeFitter (10 vs. 11)

Revision 112015-12-28 - BarbaraStoraci

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META TOPICPARENT name="LHCbComputing"

Decay-tree-fitter

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  The traditional method to fit a decay tree is 'leaf-by-leaf': one starts by fitting the vertices most downstream in the decay and builds up the tree by propagating information upstream. The advantage of this approach is that it is fast. It also models most closely how we reconstruct decay chains. The disadvantage is that it is relatively hard to propagate information from a 'mother' vertex to its daughters downstream, in particular if the decay tree spans more than one generation. For some vertex fits, like the decay of Ks->pi0pi0, traditional fits simply don't work: There are no tracks to form a Ks vertex from downstream particles. The 'origin' of the mother particle and the known mass constraints of the resonant daughters are essential ingredients in reconstructing the downstream vertex.
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The 'decay tree fitter' was developed in BaBar to deal with Ks->pi0pi0 and similar decays, where essential information of the vertex is obtained by including the origin of the decaying particle and by adding mass constraints that include information from photons.The algorithm takes a complete decay chain, parameterizes it in terms of vertex positions, decay lengths and momentum parameters, and then fits these parameters simultaneously, taking into account the relevant constraints, such as the measured parameters of the final state tracks and photons, 4-momentum conservation at each vertex etc. To perform the fit efficiently a Kalman filter is used. The procedure is described in this NIM paper.
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The 'decay tree fitter' was developed in BaBar to deal with Ks->pi0pi0 and similar decays, where essential information of the vertex is obtained by including the origin of the decaying particle and by adding mass constraints that include information from photons.The algorithm takes a complete decay chain, parameterizes it in terms of vertex positions, decay lengths and momentum parameters, and then fits these parameters simultaneously, taking into account the relevant constraints, such as the measured parameters of the final state tracks and photons, 4-momentum conservation at each vertex etc. To perform the fit efficiently a Kalman filter is used. The procedure is described in this NIM paper.
 

The LHCb package Phys/DecayTreeFitter

 
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