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## Vertex FittingComplete: | ||||||||

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The task of the VertexFitter is to control all the steps of the vertex fit from the input of the initial information to the output of the estimated quantities. Depending on the implementation of the concrete VertexFitter, the different objects which perform the different steps are either hard-coded or have to be given at construction time. This page describes all available vertex fitting algorithms.
The fitters can be used easily via the ConfigurableVertexFitter. | ||||||||

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> > | ## Usage example | |||||||

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< < | To learn more: | |||||||

> > | A simple example of the use of a VertexFitter is given on the WorkBook page. A more detailed description is given here. | |||||||

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< < | ## Vertex fitting algorithmsVertex fitting algorithms can be divided into least-squares algorithms and robust algorithms. | |||||||

> > | ## Implementation detailsImplementation details, are given in the following pages: | |||||||

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< < | In least-squares algorithms all tracks are used, with a weight 1. The KalmanVertexFitter is such a fitter. | |||||||

> > | ## Vertex fitting algorithms | |||||||

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< < | Robust fitters are able to downweight tracks, and are thus less sensitive to outliers (mismeasured tracks (type 1 outliers) or tracks from another vertex (type 2 outliers)). A common measure of the of the robustness is the break-down point, i.e. the fraction of outliers below which the vertex fit is not affected. | |||||||

> > | Vertex fitting algorithms can be divided into least-squares algorithms and robust algorithms. In least-squares algorithms all tracks are used, with a weight 1. The KalmanVertexFitter is such a fitter. Robust fitters are able to downweight tracks, and are thus less sensitive to outliers (mismeasured tracks (type 1 outliers) or tracks from another vertex (type 2 outliers)). A common measure of the of the robustness is the break-down point, i.e. the fraction of outliers below which the vertex fit is not affected. | |||||||

The fitters now available are: | ||||||||

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< < | - The KalmanVertexFitter
- The AdaptiveVertexFitter
- The TrimmedVertexFitter (not yet ready)
- The GaussianSumFitter
- The AdaptiveGsfVertexFitter
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> > | - The KalmanVertexFitter: the simple least-squares algorithm
- The AdaptiveVertexFitter: iterative re-weighted KalmanFitter which down-weights tracks according to their distance to the vertex
- The TrimmedVertexFitter: conventional robust version of the Kalman fitter, which removes tracks incompatible with the vertex
- The GaussianSumFitter: fitter using the non-Gaussian distributions of measurement errors
- The AdaptiveGsfVertexFitter: a combination of the adaptive fitter and the Gaussian-sum fitter
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## Track refitting after Vertex fit |

View topic | History: r19 < r18 < r17 < r16 | More topic actions...

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