Michal Szelezniak – LBL-IPHC meeting – 14-18 May 2007 Cluster finder in the HFT readout...

Michal Szelezniak – LBL-IPHC meeting – 14-18 May 2007

Cluster finder in the HFT readout

Single-hit detection efficiency for a cluster-finder algorithm implemented in the readout chain of the HFT

Michal Szelezniak - LBL-IPHC meeting - 14-18 May 2007

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Goals and tools

Goals:– estimate the single-hit detection efficiency and fake-hit rate as

a function of different threshold criteriaCut on signal in the central pixel (high cut)Cut on ONE of the EIGHT neighbors (low cut)

– Compare results with the classical cluster finder based on two cuts:

Cut on S/N for the central pixelCut on Sum of S/N for the crown

Tools:– Simulations based on data from the beam test runs with

MimoStar2 chips taken at DESY in summer 2006Chip 6, Rad-tol diode, 20 deg C, 4 MHz readout clock,

run 14602 (no beam) and 14546


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Simulations

Frames 15x15 pixels created from available noise samples

Real clusters (5x5 pixels) embedded into centers of frames

Total number of frames: 7588


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Definitions

● Norg– number of clusters detected in the original central 5x5 regions of all entry events,

● NTOT – the total number of clusters embedded in the central regions of entry events equal to the number of frames (NFRAMES=7588).

● NF – number of fake clusters,

● ndet

– number of clusters detected in one frame,

● norg

– number of clusters detected in one frame at the position where the original cluster was embedded,

● NPIX

=160 – number of pixels in one frame that are scanned for clusters, excluding the original cluster of 25 pixels (in addition, two rows at the edges of each frame where not scanned).

[% ]1 001 00 FRAMES

org

TOT

org

N

N

N

Neff

PIXFRAMES

fram esorg

PIXFRAMES

F

NN

nn

NN

NFHR

det


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Processing

scanning direction

0 1

2 3

4

5


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Cluster size and pointing accuracy


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Comparison of algorithms


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Comparison of algorithms

Any one pixel of 8 neighbors passes the lower threshold (described above), Any two pixels of 8 neighbors pass the lower threshold, Any three pixels of 8 neighbors pass the lower threshold, Any 2 adjacent pixels of 8 neighbors pass the lower threshold, Any 1 pixel of 4 neighbors passes the lower threshold (Figure 7b),


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Conclusions

Satisfactory performance for a range of cuts Much simpler algorithm than the classical one –

simpler for hardware implementation (FPGA, on-chip (?) - requires much less resources)

Binary readout gives a pretty good performance, but there is no security margin and the cut has to be precisely adjusted for a high efficiency and low accidental rate

Michal Szelezniak – LBL-IPHC meeting – 14-18 May 2007 Cluster finder in the HFT readout...

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