Changeset 5944


Ignore:
Timestamp:
01/22/05 18:30:19 (20 years ago)
Author:
gaug
Message:
*** empty log message ***
File:
1 edited

Legend:

Unmodified
Added
Removed
  • trunk/MagicSoft/TDAS-Extractor/Algorithms.tex

    r5925 r5944  
    397397
    398398\begin{eqnarray}
    399 \chi^2(E, E\tau) &=& \sum_{i,j}(y_i-E g_i-E\tau \dot{g}_i) B^{-1}_{ij} (y_j - E g_j-E\tau \dot{g}_j) \\
     399\chi^2(E, E\tau) &=& \sum_{i,j}(y_i-E g_i-E\tau \dot{g}_i) (\boldsymbol{B}^{-1})_{ij} (y_j - E g_j-E\tau \dot{g}_j) \\
    400400&=& (\boldsymbol{y} - E
    401401\boldsymbol{g} - E\tau \dot{\boldsymbol{g}})^T \boldsymbol{B}^{-1} (\boldsymbol{y} - E \boldsymbol{g}- E\tau \dot{\boldsymbol{g}}) \ ,
     
    403403
    404404where the last expression is matricial. $\chi^2$ is a continuous function of $\tau$ and will have to be discretized itself for a
    405 desired resolution.
     405desired resolution.  $\chi^2$ is also proportional to the auto noise-correlation matrix where increases in the noise level lead to
     406a multiplicative factor for all matrix elements and thus do not affect the position of the maximum of $\chi^2$.
    406407The minimum of $\chi^2$ is obtained for:
    407408
     
    409410\frac{\partial \chi^2(E, E\tau)}{\partial E} = 0 \qquad \text{and} \qquad \frac{\partial \chi^2(E, E\tau)}{\partial(E\tau)} = 0 \ .
    410411\end{equation}
     412
    411413
    412414Taking into account that $\boldsymbol{B}$ is a symmetric matrix, this leads to the following
     
    423425
    424426\begin{equation}
    425 \overline{E}= \boldsymbol{w}_{\text{amp}}^T \boldsymbol{y} \quad \mathrm{with} \quad \boldsymbol{w}_{\text{amp}} = \frac{ (\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) \boldsymbol{B}^{-1} \boldsymbol{g} -(\boldsymbol{g}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}})  \boldsymbol{B}^{-1} \dot{\boldsymbol{g}}}  {(\boldsymbol{g}^T \boldsymbol{B}^{-1} \boldsymbol{g})(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) -(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\boldsymbol{g})^2 } \ ,
    426 \end{equation}
    427 
    428 \begin{equation}
    429 \overline{E\tau}= \boldsymbol{w}_{\text{time}}^T \boldsymbol{y} \quad \mathrm{with} \quad \boldsymbol{w}_{\text{time}} = \frac{ ({\boldsymbol{g}}^T\boldsymbol{B}^{-1}{\boldsymbol{g}}) \boldsymbol{B}^{-1} \dot{\boldsymbol{g}} -(\boldsymbol{g}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}})  \boldsymbol{B}^{-1} {\boldsymbol{g}}}  {(\boldsymbol{g}^T \boldsymbol{B}^{-1} \boldsymbol{g})(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) -(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\boldsymbol{g})^2 } \ .
     427\overline{E}(\tau) = \boldsymbol{w}_{\text{amp}}^T (\tau)\boldsymbol{y} \quad \mathrm{with} \quad \boldsymbol{w}_{\text{amp}} = \frac{ (\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) \boldsymbol{B}^{-1} \boldsymbol{g} -(\boldsymbol{g}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}})  \boldsymbol{B}^{-1} \dot{\boldsymbol{g}}}  {(\boldsymbol{g}^T \boldsymbol{B}^{-1} \boldsymbol{g})(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) -(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\boldsymbol{g})^2 } \ ,
     428\end{equation}
     429
     430\begin{equation}
     431\overline{E\tau}(\tau)= \boldsymbol{w}_{\text{time}}^T(\tau) \boldsymbol{y} \quad \mathrm{with} \quad \boldsymbol{w}_{\text{time}} = \frac{ ({\boldsymbol{g}}^T\boldsymbol{B}^{-1}{\boldsymbol{g}}) \boldsymbol{B}^{-1} \dot{\boldsymbol{g}} -(\boldsymbol{g}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}})  \boldsymbol{B}^{-1} {\boldsymbol{g}}}  {(\boldsymbol{g}^T \boldsymbol{B}^{-1} \boldsymbol{g})(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\dot{\boldsymbol{g}}) -(\dot{\boldsymbol{g}}^T\boldsymbol{B}^{-1}\boldsymbol{g})^2 } \ .
    430432\end{equation}
    431433
    432434
    433435Thus $\overline{E}$ and $\overline{E\tau}$ are given by a weighted sum of the discrete measurements $y_i$
    434 with the digital filtering weights for the amplitude, $w_{\text{amp}}(t)$, and time shift, $w_{\text{time}}(t)$.
     436with the digital filtering weights for the amplitude, $w_{\text{amp}}(\tau)$, and time shift, $w_{\text{time}}(\tau)$
     437where the time dependency gets discretized once again leading to a set of weights samples depending on the
     438discretized time $\tau$.
     439
     440\par
     441\ldots {\textit{\bf IS THIS CORRECT LIKE THIS???}} \ldots
     442\par
     443
    435444Note the remaining time dependence of the two weights which follow from the dependency of $\boldsymbol{g}$ and
    436445$\dot{\boldsymbol{g}}$ on the position of the pulse with respect to the FADC bin positions.
     
    459468
    460469For the MAGIC signals, as implemented in the MC simulations, a pedestal RMS of a single FADC slice of 4 FADC counts introduces an error in the reconstructed signal and time of:
     470
    461471
    462472\begin{equation}\label{of_noise}
Note: See TracChangeset for help on using the changeset viewer.