MAPS readout Systems Christoph Schrader

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MAPS readout Systems Christoph Schrader. Dresden -26.09.2007. Micro- Vertex Detector MAPS (“Monolithic Area Pixel Sensors”). Micro- Vertex Detector: consists of two MAPS detector stations ~ 20µs integration time ~ 20µm pixel pitch  20 Gb/cm 2 raw data. - PowerPoint PPT Presentation

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MAPS readout Systems

Christoph Schrader

Dresden -26.09.2007

Micro- Vertex Detector

MAPS (“Monolithic Area Pixel Sensors”)

Fig.1: Sketch of the proposed CBM experiment

Micro- Vertex Detector:• consists of two MAPS detector stations• ~ 20µs integration time• ~ 20µm pixel pitch 20 Gb/cm2 raw data

Vertex Demonstrator

in 12 seconds 1 Gb

Fig.2: Example for MAPS-chip with 4 matrices

Our MAPS-Chip (Mimosa-17):• consists of four matrices with parallel readout • 256 x 256 pixel/matrix• pixel by pixel readout• 1 ms readout speed/frame

TRBv2 and the add-on concept

TRBv2:• Etrax-FS-Processor • Ethernet-connectivity • an optical link with 2 Gbit/s• programmable logic (Vertex 4)

Fig.3: The general-propose trigger and readout board (TRBv2)

Fig.4: The MDC-add-on mounted on the TRBv2 – back side

Duties and responsibilities of the TRBv2 for the MAPS add-on

• High data-rate digital interface connector (15Gbit/s)

• FPGA configuration

• High data transfer with optical link (2Gbit/s)

• Application process interface (API)

• Power supply +5V,10A

• Clock distribution

System configuration of MAPS readout

serves as supportfor the various versionsof MAPS devices

adapts/convertsthe signals

control and collectmeasurement data

Fig.5: A block diagram of system configuration for MAPS readout

Add-on board design

AUXILIARY BOARD

ADD-ON BOARD

TRBv2Fig.6: Diagram of the add-on components

• Correlated double sampling

• Data compression

• Threshold

Data processing

Pipelining as data processing

Fig.7: Data processing way

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1005 1010 1015 1020 1025 1030

pixel with hit

pixel without hit

readout cycle

AD

C u

nit

s∆

AD

C

acquisition cycle

Fig.8: The behaviour of SB-pixels is observed by frames. The constant current leakage in the capacitoris compensate through a diode. After hit the diode re-fill the capacitor

Fig.10: After CDS clear hit identification is possible

fx:px

fx-1:px

(fx:px - fx-1:px)

(fx-1:px - fx-2:px)

hit

Correlated double sampling by Self-Bias-Pixel

Fig.9: Equivalent circuit diagram of SB-Pixel

1900

threshold

threshold

Correlated double samplingand data compression

Correlated double sampling:• for noise reduction • difference between the actual frame and the frame beforeFig.11: Different between the pixel by FIFO and SDRAM

Data compression

Threshold

The hit and the 8 neighbour pixel are important

Result: not the complete matrix is readout, only the hit with the neighbour pixel

Fig.12: Data selection with threshold

Project status

• Board design (schematics)

• Layout is advanced

• Test the board hardware

• Data processing concept

• Data processing code (simulation)

THANK YOU

Add-on board design

Fig.11: Add-on board

Simulation of Self-Bias-Pixel readout

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1010 1015 1020 1025 1030

pixel with hit

pixel without hit

readouto cycle

AD

C u

nit

s

∆ A

DC

cycle

Fig.9: The behaviour of 3T-pixels is observed by frames. The constant wastage is produced from the current leakage in the capacitor.

Fig.10: Past baseline the leakage current is cut out

fx:px

fx-1:px

(fx:px - fx-1:px)

(fx-1:px - fx-2:px)

hit

Correlated double samplingby 3T-Pixel

Fig.8: Equivalent circuit diagram

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