Light Response of PPDs Study - GWW @ LCWS 2011

7/31/2019 Light Response of PPDs Study - GWW @ LCWS 2011

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Measuring and Modelling the Light Response ofPixelized Photon Detectors with Significant

Photon-Induced Correlated Noise

Graham W. Wilson

University of Kansas

September 29, 2011

Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 1 / 36
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Introduction

Introduction

Solid-state photon detectors such as those in use by CALICE and T2K are

considered attractive candidates for light detection in a future linearcollider detector when compared with the traditional PMT.

Some advantages

B-field tolerance

Cheap

Apparent photon resolving capability

Low voltage/size/integrability

Some disadvantages

Dark noise rate per mm2 (can be 500 kHz cf 0.5 Hz).

Correlated noise: cross-talk and after-pulsing

Dynamic range

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Introduction

Photo-detector response modelling

Question

Does LED calibration data (points) follow Poisson model (red)?

ch1_ledEntries 108589Mean 523.4RMS 226.5

Integrated Charge (ADC counts)200 400 600 800 1000

Countsperbin

0

1000

2000

3000



ch1_led: MPPC Channel 1

Individual photons often lead to not just 1 fired pixel, but 2, 3, 4 etc. due

to cross-talk and after-pulsing. Technology and device dependent.Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 3 / 36
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Motivation

Noise and Time Structure: Important or Not ?

ILC/CLIC

At ILC with a large inter-bunch spacing (337 ns), a relevant issue is noisewithin a time interval consistent with the BX under consideration. ForCLIC, much tighter specs.Various types of potential detectors: AHCAL, Scint. ECAL,

Muon-detector, scint. fiber tracking have different requirements.

Why this study?

These studies use the 100-pixel Hamamatsu MPPC aimed at highefficiency low light-level detection. I work on the D0 fiber tracker and its

light calibration and have explored instrumenting parts of a LC detectorwith similar instrumentation for time-stamping/TOF. At D0 using VLPCswe have an average threshold per fiber of 1.0 photo-electronscorresponding to 1% dark probability and Poisson distributed LED

distributions....Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 4 / 36

M i i
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Motivation

Literature and this work

Literature

There is a substantial literature from many groups about characterizationmeasurements related to pixelized solid-state photo-multiplier response(see references).

Short-comings

In practice many adopted methods are either approximate, or requirededicated measurements unlikely to be available en masse in situ for LCdetector channel counts, or potentially lose substantial predictive power /precision by using more parameters than warranted by the underlying

effects.

This work

Hopefully helps to put some of the issues better in focus and provides acoherent yet relatively simple integrated experimental method to test the

response modelling and the measurement of associated parameters.Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 5 / 36

M th d
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Method

Experimental Goal and Design

GoalMeasure the photo-detector response under essentially identical conditionsusing identical time intervals for both non-illuminated (dark) data andilluminated (LED) data. Currently using MPPC-S10362-11-100C sensorwith 100 pixels.

Design

Use 100-1000 Hz clock to fire LED on every other cycle.Measure total charge integrated within a 240-300 ns time window using

dual-range QDC (FSR 800 pC).Use single-hit TDC in common start mode to check timing characteristics.Bias will be varied from run-to-run, but use 70.65 V corresponding to 0.72V over-voltage as default setting.


Method


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Method

Experimental Setup

LED Box

Jacketedclear fiber

1mm

Power Supplyand Amplifier

with MPPC-

S10362-11-

100C sensor

Ch1 : Pulses at 2n t (LED trigger)

Ch2 : Pulses at (2n+1) t (Dark count measurement)

HP pulse

generator

(V2)

Lecroy

622

OR

PS744

Linear

FI/FO

V965

QDC

V775

TDC

TDC Start

QDCgate

Ortec

935

CFD

CAEN V993Dual Timer

V1

supply

LabView

interface VM-USB

VM-USB

Linux

DAQ

computer

CAEN

SP5600

Bias andamplification

control

LED intensity control

LED

trigger

pulse


Method


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Method

LED Circuit

Use Kapustinsky [1] type driver circuit to obtain fast time response.

Currently using off-the-shelf green LED ( = 565nm).

LED

Agilent E3630A

variable supply

voltage

HP 8131A pulse

generator for

trigger pulse


Method


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Method

Typical LED Event 1: prompt 1 pixel event ( 40 ns)


Method


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Method

LED Charge Distribution (gate width = 300 ns)

Measure charge response to LED (black) and dark counts (red). Photon

intensity = 0.22 detected photons/pulse.

ch1_pedEntries 100000Mean 349.4RMS 61.76

IntegratedCharge (ADC counts)300 400 500 600 700 800

Coun

tsperbin

0

500

1000

1500

2000

2500


ch1_ped: MPPC Channel 1 ch1_ledEntries 100000Mean 380.2RMS 94.56


Method
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LED Charge Distribution - Log

Measure charge response to LED (black) and dark counts (red). Photon




Coun

tsperbin

1

10

210

310




Method
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LED Time Distribution

Measure time response to LED (black) and dark counts (red). Photon



Measured TimeAfter Start (TDC counts)150 200 250 300 350 400

Eve

nts

perbin

0

500

1000

1500

2000


ch1_led: MPPC Channel 1 ch1_pedEntries 56495Mean 1905RMS 1158

Find FWHM for this green LED of 5ns. (1 TDC count = 0.3 ns)


Method
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Typical LED Event 2: prompt 2 pixel event


Method
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Typical LED Event 3: prompt 3 pixel event + delayed pulse


Method
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Typical LED Event 4: multiple pixels + likely afterpulses


Method


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Charge Distribution Studies

Standard conditions mostly:

Room temperature (Kansas summer day ....)

Integration time: 270 nsLED supply voltage: 18.25 V. Leading to 4.5 detected photons at 1 Vover-voltage and nominal intrinsic gain of 2.4e6.

Amplifier gain: 38 dB


Method


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Fitting Method

Assume that the measured LED distribution, T(Q), arises from the

convolution of N(qdark) and L(qlight), where Q = qdark + qlight.


IntegratedCharge (ADC counts)

0 200 400 600

Countsperbin

0

5000

10000

15000



Use measured non-illuminated data (red) for N(qdark) and adjust theparameters of the L(qlight) model to give the best fit to the LED data(black) for the additional charge arising from LED photons.


Method


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Light Model: Essentially 2 parameters.

Pixel distribution

Use the simple probability distribution model discussed in Vinogradov etal [2] based on a Poisson distributed random variable for the number ofphotons, , which result in a detected primary avalanche. Each primaryavalanche may then create a secondary avalanche with a duplicationprobability, pD, and likewise a secondary avalanche may create a tertiaryavalanche with the same probability etc, etc ... pD includes both cross-talkand after-pulsing assuming for simplicity equal charge response to bothsources.

Charge Measurement Model Parameters

1 pixel gain, g (ADC counts per pixel)

1 pixel intrinsic fractional gain resolution, 1 = g/g

N-pixel non-linearity, , where qlight = Ng(1 + N)/(1 + )

N-pixel variance non-linearity, , where

2

N = N(1 + N)

2

g)/(1 + )Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 18 / 36

Method
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Light Model Continued

Examplep(nA = 0) = exp{}

p(nA = 1) = exp{}(1 pD)

p(nA = 2) = exp{}{pD(1 pD) +12

2(1 pD)2}

p(nA = 3) =exp{}{p

2D(1 pD) +

2pD(1 pD)2 + 16

3(1 pD)3}

etc ..

Needless to say - currently neglect finite pixel number

Characteristics

Mean pixel count: /(1 pD)

Variance of pixel count: (/(1 pD))(1 + pD)/(1 pD)


Results
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Example Fit (Run6 70.35V 38dB L)

ch1_led

Entries 100000Mean 257.1RMS 103

Integrated Charge (ADC counts)0 200 400 600

Countsperbin

0

1000

2000

3000

ch1_led


ch1_led




Results


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ch1_led



Countsperbin

1

10

210

310

ch1_led


ch1_led




Results


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ch1_ledEntries100000Mean 257.1RMS 103


Countsperbin

0

1000

2000

3000




2.150(7)pD(%) 5.00(25)

g 66.35(6)1 0.113(1) -0.0022(4) 0.007(10)2/dof 936 / 794


Results


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ch1_led

Entries 108589Mean 523.7RMS 226.9


Countsperbin

0

1000

2000

3000

ch1_led


ch1_led



Fit: = 3.36 0.01, pD = 14.0 0.2%,

2

/dof=1921/1594.Graham W. Wilson (University of Kansas) LCWS11 Granada: Calorimetry/Muons September 29, 2011 23 / 36

Results
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Integrated Charge (ADC counts)100 200 300 400 500 600

Countsperbin

0

500

1000

1500

2000

2500


ch1_led: MPPC Channel 1h_fittedEntries 1600

Mean 275.3RMS 90.95


Fit: = 3.36 0.01, pD = 13.0 0.3%, 2/dof=774/794.


Results


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ch1_led


IntegratedCharge (ADC counts)100 200 300

Countsperbin

0

500

1000

1500

2000

ch1_led


ch1_led



Fit: = 1.268 0.006, pD = 0, 2/dof=510/394.


Results


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Example Fit (Run11 70.65V 38dB 0.3L)


Integrated Charge (ADC counts)200 400 600

Countsperbin

0

1000

2000

3000

4000




Fit: = 0.961 0.004, pD = 15.0 0.3%, 2/dof=1424/1194.


Results
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Example Fit (Run12 70.65V 38dB 1.6L)

ch1_ledEntries 100000Mean 746RMS 293.9

Integrated Charge (ADC counts)500 1000 1500

Countsperbin

0

500

1000

1500




Fit: = 5.22 0.02, pD = 13.4 0.2%, 2/dof=2327/1994.


Results
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Bias Scan

Bias Voltage (V)70 70.2 70.4 70.6 70.8 71

G

ain(ADCc

ountsperfiredpixel)

0

50

100

150

2002.5 (ADC counts/V)Slope = 153.6

0.01 (V)= 69.93BDV

2/ndf = 8.6 / 4

Bias Scan


Results


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Measured Photon Number

Measure the Poisson parameter of the detected primary LED photons, .

(gives relative photon detection efficiency vs V).

Over-Voltage (V)0.2 0.4 0.6 0.8 1

LED

phot

onnumber

0

1

2

3

4

0.11 (photons/V)Linear term = 5.41

0.13 (photons/V^2)NL term = -0.97

2/ndf = 10.3 / 4

Bias Scan


Results

D li P b bili


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Duplicate Probability

Over-Voltage (V)0.2 0.4 0.6 0.8 1

Pulseduplication

probability(%

)

0

10

20

30 0.80 (V^-2)Quadratic term = 27.54

2/ndf = 4.5 / 5

Bias Scan


Results

Ph R l i Q li


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Photon Resolving Quality

Over-Voltage (V)

0 0.2 0.4 0.6 0.8 1 1.2 1.4

GainDispe

rsionParamet

er

0

0.05

0.1

0.15

0.2

0.25

Pixel Number Resolution


Results

D k C t P b bilit


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Dark Count Probability

Can measure charge exceeding arbitrary threshold in charge integration

window (has not been the focus of this work so far) using measurednon-illuminated ADC spectrum.


Results

F t R fi t


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Future Refinements

Adjust LED intensity at each bias voltage to keep number of detectedphotons approximately constant. Should be a better method formeasuring the photon-induced noise dependence on over-voltage.

Incorporate after-pulsing time structure together with pulse shapetime constant and resolve cross-talk and after-pulsing importance.

Improve/better characterize charge measurement systematics -amplifier/ADC linearity.

Improvements in the fitting, statistical method and convolution.


Conclusions

C l si s


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Conclusions

Summary

Find that measured pixel number distributions can be well modelledusing a simple light-detection model including duplicate avalanches.Important for understanding particle detection efficiency close tothreshold.

Experimental technique allows simultaneous determination of gain,duplicate probability, relative PDE, dark rate and pixel resolvingcapability for this particular sensor.

Conclusions

New PPDs have significant noise which is sometimes correlated andneeds to be taken into account when evaluating detector/sensoroptions, predicting performance and measuring performance.

Correlated noise makes the standard procedure of setting a thresholdat 1.5 photo-electrons not as useful as might be expected.


References
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J.S. Kapustinsky et al.A Fast Timing Light Pulser for Scintillation Detectors

NIM A, 241 (1985) 612.S. Vinogradov et al.Probability Distribution and Noise Factor of Solid StatePhotomultiplier Signals with Cross-Talk and Afterpulsing2009 IEEE Nuclear Science Symposium, N25-111.

Y. Du and F. Retiere,After-pulsing and cross-talk in multi-pixel photon countersNIM A, 596 (2008) 396.

A. Vacheret et al.,Characterization and simulation of the response of MPPCs to lowlight levelsNIM A, 656 (2011) 69.


References


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H. Oide et al.,Studies on multiplication effect of noises on PPD, and a proposal of anew structure to improve performanceNIM A, 613 (2010) 23.


Backup Slides
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Backup Slides

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Documents

Light Response of PPDs Study - GWW @ LCWS 2011