MICE TPG Reconstruction

1
MICE TPG Reconstruction

• Cluster finding
• Space point reconstruction
• Track recognition
• Track fit
• GENEVA
  UNIVERSITY
• 31 March 2004
  Voloshyn Olena

2
status end of march
I Cluster finding written, to be tested,
(promised end of march) II Space point
reconstruction almost finished, missing
implemetation of errors on space points III
Track recognition (exists in
HARP code, and in G4MICE for SciFi) IV Track fit
(exists in HARP code and in
G4MICE for SciFi) all promised for end of May.

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Cluster finding

• Cluster algorithm takes as input the digitized
  hits.
• Different digits belong to the same cluster if
  they are neighbourgs in strip number and if their
  signals overlap or are close in time.
• Dimension of cluster is defined by lower and
  upper strip number.
• Cluster position is obtained as the centre of
  gravity of the digits that belong to this cluster
  weighted by their amplitudes.
• Amplitude of cluster is given as the sum of the
  amplitudes of the digits associated with this
  cluster.

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Space Point definition

• Crossing of the clusters close in time gives the
  space point position in plane x-y.
• z coordinate of space point is defined
• zvdrtdr
• U
  X V
  

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Track recognition

• Pattern recognition algoritm groups the space
  point recognized as belonding to the same track
  and searches the following point in the volume of
  a truncated cone with the axis defined by the
  previous points.
• The parameters of the cone will be optimised
  for 200 MeV track.

.
.
.
.
.
a
Forward acceptance
Radius
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Track fit

• Fit is performed in two steps
• circular fit in the x-y plane that alows to
  determine the inverse of the radius of curvature
  r, the impact parameter in the x-y plane d0 and
  the angle between the projection on this plane of
  the particle momentum at the impact point and the
  X axis Fo
• Linear fit in the Sxy-Z plane that alows to
  determine the tangent of the dip angle and the Zo
  coordinate at the impact point.

y
z
tg a
p
Oo
x
Zo
Sxy
do
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• (at a later stage) the calculated helix
  parameters will be used as a seed for a futher
  Kalman fit which handles multiple scattering and
  energy loss.
• The energy loss (which is derived from amplitude)
  and momentum (as derived from curvature and phase
  advance) will be estimated.