Forward Tracking in the ILD Detector

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Presentation transcript:

Forward Tracking in the ILD Detector Robin Glattauer LCWS11 , 29.09.2011

Forward Tracking Disks

Standalone track search for the FTDs (Forward Tracking Disks) the goal Standalone track search for the FTDs (Forward Tracking Disks)

The Problem

The Solution

Methods Cellular Automaton Kalman Filter Hopfield Neural Network

The Cellular Automaton

The Cellular Automaton

It's about rules

IP

cell ( segment)

state 0

Kalman Filter KalTest + KalDet + MarlinTrk Quality Indicator: χ ² probability

The Hopfield Neural Network Track ↔ Neuron Goal: the global minimum

Once more for the FTDs

And now some reality

Background Inner 2 disks are pixel detectors How many bunch crossings? 100 BX * hit density ≈ 900 hits / pixel disk

Ghost hits Outer 5 disks are strip detectors

At the moment Criteria Analysis tools Step Analyser Criteria Analyser True Track Analyser Jet Analyser Adding flexibility (strategy pattern)

Thanks to Winfried Mitaroff Steve Aplin, Frank Gaede and Jan Engels Rudi Frühwirth And Jakob Lettenbichler (Belle 2)

Thank you!

Back Up

Future staggered / tilted petals Neural Network Intermediate Region: TPC + FTD Robustification (DAF, GSF)

Dependencies FTD drivers and gear Time stamps? Number of integrated bunchcrossings

tracks will Skip a layer Connect directly to the IP

regions