Simulations Working Group Meeting07.10.08

Trigger Studies Using Stacked Pixel Layers

Mark Pesaresihttps://twiki.cern.ch/twiki/bin/view/Main/MarkPesaresi

Mark Pesaresi2

Overview

Construction of Strawman B

Creation of a single stacked pixel layer

Construction of multiple layers and configurability of each

Set up configurable pixel sizes

Studies using Strawman B

Simulations within the geometry

Trigger studies using digis

Mark Pesaresi3

Overview

Strawman B Status

Ported successfully to CMSSW_1_8_4 and available in CVS

Latest version includes patches to missing hit problems (see previous talks)

Simulation studies ongoing – focus here is on trigger studies

Mark Pesaresi4

Attempted to determine the differences in occupancy reported by the Fast and Full simulations

Discovered that for the pixel layers, the differences are small (~3) and are understoodFast sim does not take into simulate out-of-time pileupFast sim places cuts on minimum track pt and loopers by defaultFast sim does not simulate delta rays

Would be beneficial to extend investigation for any layer, both strip and pixel so that any differences can be parameterised.

FullSim FastSim Ratio FullSim (in-time) FastSim (modified) Ratio

PXB Layer 1 0.01731 0.007713 2.2 0.01627 0.01252 1.2

PXB Layer 2 0.01253 0.00495 2.5 0.01138 0.00853 1.3

PXB Layer 3 0.01024 0.00363 2.8 0.00938 0.00697 1.3

Occupancy Review

Occupancy [%] for pixel layers in MinBias events at LHC pileup (~21 interactions/BX) for different Fast and Full simulation scenarios

Mark Pesaresi5

Geometry

0.92.14

2.5

Current Pixel System

Stacked Pixel Layer @ 25cm

Considering a single stacked pixel layer at r=25cm, length=221cm

Current pixel system included in geometry

Outer geometry unnecessary at this point

Using latest version of Strawman B in CMSSW_1_8_4

Mark Pesaresi6

Sensor Geometry

Strawman B parameters modified in pixbar.xml and trackerStructureTopology.xml

Sensor choice: tilted at 23° – to reduce cluster width by minimizing Lorentz drift

100μm thickness

28mm x 72.8cm sensor dimensions

z overlap – to fill gaps in z

100 μm x 2.37mm pixel pitch

256 x 30 pixels per module

Sensor separation varied between 1-4mm

Modification made to geometry to aid trigger studies – not yet part of StrawmanB

z offset – to match columns in top and bottom sensors with increasing eta

23°

z overlap

z offset

Mark Pesaresi7

Tracking Trigger

Aim is to assess the performance and viability of a stacked pixel layer as part of a L1 tracking trigger by the determination of track pt

Study attempts to simulate the implementation of such a trigger

Generation of trigger primitives using digi information

Performance of the algorithm in finding high pt tracks

Investigate methods of sensor readout and hit correlation for the on-detector implementation

Complements previous study reported on in December using a stacked strip layer in the outer tracker

Mark Pesaresi8

Simulation Overview

adc cut & sorting

Sorted Digis[detId, row, column, adc]

correlation algorithm

Stubs[detIdhigh, rowhigh, columnhigh, adctot, row difference, column difference, simTrackIdhigh, simTrackIdlow]

Stacked Layer Digis[detId, row, column, adc]

adcdigi > 30

sorted by detId into modules with upper and lower sensors

hits between upper and lower sensors are correlated to check for high pt tracks

modifiable search window cuts can be applied

Mark Pesaresi9

Correlation Algorithm

Row difference calculation

Since the sensors are tilted, there is a difference between the position of the higher and lower sensor hits for a high pt track which is also dependent on the position of the incident track on the sensor

The fixed offset as a function of the row number can be applied to calculate the true row difference

Equivalent to an on detector map between the hit position on the higher sensor to a set of positions on the lower sensor

Column difference calculation

Column difference is not symmetrical – dependence on whether hit is in detector +/-z. Can be exploited to maximise rate reduction.

0

256

pixel row 114

pixel row 125

Mark Pesaresi10

Correlation Algorithm

Stub generation

A stub is created when both the row and column difference lie within a given range.

e.g. row offset = 30 ≤ row window ≤ +10 ≤ column window ≤ +1

Upper

Lower

Pass Fail

100μm

100μm

Mark Pesaresi11

Algorithm Performance

Separation [mm] Max Efficiency [%] Fake [%] Reduction Factor

1.0 99.35 4.14 22.26

2.0 97.745 17.83 95.99

3.0 96.00 39.08 210.28

4.0 92.95 47.27 254.35

Max Efficiency: Average maximum efficiency for a high pt track to form a stub. Inefficiencies due to sensor doublet acceptances and algorithmic efficiency (window cuts)

Fake: Average fraction of stubs per event generated by correlating hits from different tracks

Reduction Factor: Average data rate reduction factor per event (NStubs / NDigis) where NDigis is number of hits with charge >adcdigi for the whole stacked layer

Performance of a detector stack at r=25cm for sensors with pitch 100μmx2.37mm. Correlation cuts optimised for high efficiency

Mark Pesaresi12

Algorithm Performance

Separation [mm] Max Efficiency [%] Fake [%] Reduction Factor

1.0 99.35 4.14 22.26

2.0 97.745 17.83 95.99

3.0 96.00 39.08 210.28

4.0 92.95 47.27 254.35

Performance of a detector stack at r=25cm for sensors with pitch 100 μmx2.37mm. Correlation cuts optimised for high efficiency

Max Efficiency calculated using 20,000 single 50GeV Muon/Antimuon events with smearing

Fake/Reduction Factor calculated using 100 MinBias events with an average of 400 interactions per bunch crossing with smearing

Results optimised for high efficiency: Row window = 2 pixelsColumn window = 3 pixels @ 1mm, 2mm

4 pixels @ 3mm6 pixels @ 4mm

Mark Pesaresi13

Algorithm Performance

Cuts optimised for high efficiency:

Row window = 2 pixelsColumn window = 3 pixels @ 1mm, 2mm; 4 pixels @ 3mm; 6 pixels @ 4mm

pT discriminating performance of a stacked layer at r=25cm for various sensor separations using 10,000 di-muon events with smearing

Sensor separation is again an effective cut on pt – as with the stacked strips

Again, the width of the transition region increases with separation. Due to:

- pixel pitch- sensor thickness- charge sharing- track impact point

Efficiencies decrease with sensor separation due to the larger column window cuts – sensor acceptances and fake containment are issues

Mark Pesaresi14

Algorithm Performance

Effect of changing window cuts on discrimination curves

Efficiencies are unchanged with larger column windows

Efficiencies are recovered (at larger separations) when row window is increased but also has the effect of decreasing the pt cut

pT discriminating performance of a stacked layer at r=25cm for a sensor separation of 4mm and various algorithm cuts using 10,000 di-muon events with smearing

Mark Pesaresi15

Algorithm Performance

1 2 3

1 19.05 41.96 42.085

2 44.075 95.585 95.89

3 45.155 97.745 98.07

RowWidth

ColumnWidth

Efficiency of a 50 GeV muon/antimuon generating a stub in the stacked layer [%]

Data rate reduction factor achieved on MinBias events at SLHC pileup

100 MinBias events with an average of 400 interactions per bunch crossing with smearing

20,000 single 50GeV Muon/Antimuon events with smearing

2 3

2 104.6 94.4

3 96.4 86.0

RowWidth

ColumnWidth

Choosing a sensor separation of 2mm, the effect of the window cuts has been determined

Mark Pesaresi16

Implications

In order to reduce Lorentz drift, sensors have been tilted – correlation requires that an offset must be programmed in order to match hits from high pt tracks

- At its most basic, a calibration constant must be uploaded for each pixel row on a sensor

- If technology changes, sensors may not need to be tilted

Instead of the correlator performing a difference analysis on two hits, a programmable map between an address on the upper sensor and multiple addresses on the lower sensor would simplify implementation and reduce rate & fakes. Is this possible?

If layer is part of a multi-stack detector, a high efficiency is preferable to large rate reductions. We only need to remove the majority of low pt tracks. Multiple stacks should remove the fakes if combinatorics are not too high. A 2mm separation at 25cm seems reasonable.

To maintain high efficiencies, the column window cut must be kept wide. Can such a column window cut be implemented on detector?

Mark Pesaresi17

Some Numbers

Typical MinBias event at SLHC luminosity:

1455 tracks > 2 GeV

4 tracks > 8 GeV

(in region |eta| < 2.14)

Using a stacked pixel layer at 25cm (|eta| < 2.14) with pixel pitch 100μmx2.37mm and 2mm sensor separation [row window=2, column window=3]

140 stubs • includes 25 fake stubs• includes 20 duplicate stubs

Every event is triggered

A second stacked layer would reduce the number of fakes, the number of tracks (if pt threshold is raised) and allow sufficient resolution for matching to other sub-detectors.

Mark Pesaresi18

Sensor Readout

A method for reading out stacked sensors for hit correlation is required

- Readout and decision every bunch crossing

- Low power

G.Hall – July 2008

Mark Pesaresi19

Sensor Readout

Module divided into 64 blocks of 4 rows per column

Requires minimum 10 address lines:

6 bit block address4 bit patterne.g. x000,00x0,0xx0, etc.

Assumes that only 1 block is hit per column – reasonable since <1 pixel hit per column on average

4 x 100μm

2.37mm

Correlator Correlator

Block1

Block0

Mark Pesaresi20

Sensor Readout

Analysis modified to simulate this method of correlation

Sort data into blocks

Correlate hit blocks

Readout block stubs and

pattern data

Run original

algorithm

Correlate blocks with pattern data

Readout stubs

On-detector Off-detector

Blocks are correlated in a similar way to before with a block (row) difference and a column difference. As before, an offset is required to match the blocks correctly

Cuts can be placed on the window width for both blocks and columns

Investigated how well top method worked and the data rate reductions possible

Mark Pesaresi21

1 2 3

1 49.38 59.64 60.03

2 78.72 95.03 95.59

3 80..57 97.18 97.75

BlockWidth

ColumnWidth

Efficiency of a 50 GeV muon/antimuon generating a stub in the stacked layer [%]

Data rate reduction factor achieved on MinBias events at SLHC pileup

100 MinBias events with an average of 400 interactions per bunch crossing with smearing

20,000 single 50GeV Muon/Antimuon events with smearing

2 3

2 9.20 4.78

3 8.37 4.47

BlockWidth

ColumnWidth

Choosing a sensor separation of 2mm, the effect of block cuts have been determined

Results are for block correlation followed by standard algorithm with [row window=2, column window=3]

Sensor Readout

Mark Pesaresi22

Implications

Require at least a factor 10 reduction in rate to read out detector. Achievable with a block width cut of 2.

For reasonable efficiencies, a column width cut of at least 2 is still required. How can this be performed easily on detector?

Offsets are still needed when applying correlation to blocks – can this be implemented on detector?

A small fraction of columns contain more than one hit per BX (in some cases up to 6 hits). Is this important, can it be reduced or ignored?

Largest cause is due to hits on block boundariese.g. |0000|000x|x000|0000|

Mark Pesaresi23

Alternative Readout Designs

Instead of reading out column-wise each row or block, could we read out row-wise?

Occupancy must be low enough (or module must be small). Is this an issue?

Removes need for large column window comparisons

Cut could be sufficient for cutting data rate off detector by x10

If column address is kept, further processing off-detector should cut this down and remove fakes due to pileup

Correlator

Mark Pesaresi24

Extra Stacked Layers

A stacked strip layer could be constructed

Feasibility of using stacked strip layers in the outer tracker was investigated earlier this year

- high pt stubs were generated

1.0 mm Separation1.5 mm Separation2.0 mm Separation2.5 mm Separation3.0 mm Separation4.0 mm Separation5.0 mm Separation

Aim is to add this layer to the geometry and investigate possibility of correlating stubs in each layer

Mark Pesaresi25

Summary

Strawman B has been used as the basis to commence trigger studies using a stacked pixel layer at 25cm

Algorithm to correlate digi hits from high pt tracks has been writtenPerformance of algorithm in ideal conditions measured - ~95% maximum efficiency of detecting high pt tracks, ~ x100 reduction in data rate

Next step will be to correlate stubs from this layer to those from a layer further out – such as a stacked strip layer at large radius or a stacked pixel layer at mid radius

Will be possible to then estimate pt resolutions, trigger rates etc

Possible methods of reading out sensor data have been looked atBlock correlation is successful but needs some refiningOther methods still need analysing

Still plenty to investigate…Effect of occupancy on performanceEffect of changing layer radiiEffect of changing pixel pitch, short/long pixel stripsPossibility to extend layers to high eta…

Mark Pesaresi26

Backup

Fast Sim gives an average occupancy of 0.05% (up to 0.15% instantaneous) at an average of 400 interactions per event for a layer at 25cm extending to |eta| < 2.14

Assume Full Sim will give x3 occupancy0.15% x 17,448,960 channels = 26,173 hit channels

30k channels require 2813, 2.56Gbps links assuming 12bit address per channel at 20MHzLink Power: 5.6 kW (322uW/ch) – Geoff suggests a budget of 300μW/ch for the pt layers

Cutting the number of channels to readout by x10 using hit correlation brings link power for the pt layers down to reasonable values

Total Hits

Block Stubs

Pixel Stubs

Mark Pesaresi27

Backup

Layer Occupancy(No. digi hits in layer /

total channels in layer)

Module Occupancy(No. digi hits in occupied module /

total channels in module)

Note: Full Sim occupancies estimated at 3x these values

100 MinBias events, ~400 interactions per bx with smearing

Mark Pesaresi28

Backup

Pixel block statistics

< 6

100 MinBias events, ~400 interactions per bx with smearing

using block width=2, column width=3, row width=2, column width=3

Mark Pesaresi29

Backup

Max Efficiency vs Eta

20,000 single 50 GeV muon/antimuon events

using block width=2, column width=3, row width=2, column width=3

Does not take pileup into account

Mark Pesaresi30

Backup

Number of pixel hits per block

Effect of placing track width cut in each block

No cut

>2 Consecutive Hits

>1 Consecutive Hit

Effect is small400 MinBias pileup (50 um sensor)