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Next: High Momentum Limit Up: Vertex Fitting Previous: Vertex Fitting with Error

Inclusion of Geometrical Constraints

In the last subsection, we tried to determine the common vertex of given ntrack tracks without touching the track parameter vectors themselves: these helical tracks do not necessarily pass through the common vertex. Here, we require these tracks to originate from a common vertex:
\begin{displaymath}
\begin{array}
{lll}
\nonumber
 {\bf x}_v = (x_v,y_v,z_v)^T\end{array}\end{displaymath}   
so that i-th track, for instance, can be parametrized as
\begin{displaymath}
\begin{array}
{lll}
\left\{
\begin{array}
{lllll}
 x & = & x...
 ...tan\tilde{\lambda}^i \cdot \phi .\end{array}\right. \end{array}\end{displaymath} (38)
Notice that, for a given trial vertex ${\bf x}_v$, the track parameter vector has now only three components:
\begin{displaymath}
\begin{array}
{lll}
\nonumber 
 \tilde{{\bf a}}_i 
 = (\tilde{\phi}_0^i,\tilde{\kappa}^i,\tan\tilde{\lambda}^i)^T,\end{array}\end{displaymath}   
since the track has to pass through the pivot ${\bf x}_v$ and therefore $\tilde{d}_\rho = \tilde{d}_z = 0$.

In order to calculate the $\chi^2$, we need to transform the pivot of the i-th track from the trial vertex ${\bf x}_v$ to the pivot of the corresponding measured track. This induces the following change of the helix parameters:
\begin{displaymath}
\begin{array}
{lll}
 \begin{array}
{lll}
 d_\rho^i & = & \le...
 ...\lambda^i & = & \tan\tilde{\lambda}^i ,
 \end{array}\end{array}\end{displaymath} (39)
which gives the helix parameter vector:
\begin{displaymath}
\begin{array}
{lll}
\nonumber
 {\bf a}(\tilde{{\bf a}}^i, {\...
 ...\rho^i, \phi_0^i, \kappa^i, d_z^i, \tan\lambda^i )^T\end{array}\end{displaymath}   
to be compared with the corresponding measured track parameter vector ${\bf a}_a$.Thus, we arrive at the $\chi^2$ definition:
\begin{displaymath}
\begin{array}
{lll}
 \chi^2 = \sum_i \Delta{\bf a}_i^T \cdot
 E_{{\bf a}_i}^{-1} \cdot \Delta{\bf a}_i\end{array}\end{displaymath} (40)
with
\begin{displaymath}
\begin{array}
{lll}
\nonumber
 {\bf a}_i = {\bf a}_i - {\bf a}(\tilde{{\bf a}}^i, {\bf x}_v) ,\end{array}\end{displaymath}   
the minimization of which determinies the parameter vector:
\begin{displaymath}
\begin{array}
{lll}
\nonumber
 {\bf A} \equiv \pmatrix{ {\bf...
 ...}_i \cr 
 \vdots \cr 
 \tilde{{\bf a}}_{n_{track}} }\end{array}\end{displaymath}   
containing $3 \cdot \left( n_{track} + 1 \right)$ components. Notice that the necessary calculations of the first and the second derivatives of the $\chi^2$ require only the evaluation of the transformation matrix:
\begin{displaymath}
\begin{array}
{lll}
\nonumber
 \frac{ \partial {\bf a}(\tilde{{\bf a}}^i, {\bf x}_v) }{ \partial {\bf A} }\end{array}\end{displaymath}   
and what then follows is the same as with the last subsection.


next up previous
Next: High Momentum Limit Up: Vertex Fitting Previous: Vertex Fitting with Error
Keisuke Fujii
12/4/1998