Transcript HIP rate measurement

The Effect of Highly Ionising Particles
on the APV25 Readout Chip
R. Bainbridge on behalf of the CMS Tracker collaboration
Colmar, 11th September 2002
Highly Ionising events



Interactions between incident particles and silicon sensors can produce
Highly Ionising Particles (i.e, recoiling nuclei and/or nuclear fragments)
HIP events result in signals equivalent of up to 1000 minimum ionising
particles, which can saturate the FE electronics and result in signal loss
Estimate of +Si interaction rate in the CMS Tracker:

(+p)  200 mb  (+Si)  2.6 barn (E = 300 MeV)
 mean free path (+ in Si) = 7.7 cm
 rate  5  10-3 per BX per plane per % occupancy
Rate at which these interactions saturate the FE electronics?…
Duration of this saturated state?… Resulting inefficiency?…
First observation of the HIP effect

X5 test beam (Oct 2001) saw 6 TOB
modules exposed to 120 GeV pion
beam with 25 ns bunch structure



APV analogue data exhibit large
(truncated) signals and suppressed
output in all other channels (i.e,
negative common mode shifts)
A sufficiently large signal will fully
suppress the output of all 128 channels
 APV insensitive to MIP signals
“Deadtime” is the period for which an
APV is insensitive to MIP signals
Raw analogue
output from 6
modules
(4 APV25s per
module)
Disabled APV
+ activity
downstream
Origin of problem

Inverter stage powering scheme:



All 128 inverter FETs draw from V250
via external hybrid resistor, RINV
On-chip CM subtraction (VR  VCM)
Large signals drive down output on
all other channels


Inverter FETs seeing HIP signal draw
largest current possible
 VR pulled down
 output of all channels suppressed
Output remains suppressed until
signal dissipates

Possible solution:

Reduce RINV from 100  to 50 
 more current available at
inverter stage (reduces effect of
large signals pulling down VR)
Identifying HIP events


Large signals result in negative
tail in CM distribution
Peak at -150 is a consequence of
limited APV dynamic range
Common mode
distribution
[ADC counts]
-140

CMMAX
Cluster charge
distribution
for CM  -150
[ADC counts]
500


APV still sensitive to MIP
signals for intermediate
CM shifts
Only fully suppressed
baselines result in
deadtime
HIP events that result in
deadtime are identified
by:
CM  -140 & Qclu  500
HIP rate measurement (X5)

“HIP rate” = rate at which +Si interactions result in deadtime
(not rate of +Si interactions!)
HIP rate [per pion per plane] =
NHIPs
Ntriggers  Nplanes  Multiplicity
Beam
Ntriggers
Nplanes
Multiplicity
NHIPs
Rate ( stat. error)
Pion
247500
6
1.9
1051
(3.7  0.1) · 10-4
Pion
288077
5
2.0
1142
(4.0  0.1) · 10-4
Muon
225000
5
1.9
7
(3.3  1.2) · 10-6
X5 beam structure

SPS orbit = 23.1 s
(924 RF buckets)
Pions delivered to X5 area in trains of
~60 consecutive RF buckets
1 train per
SPS orbit
1 train per SPS orbit  trains spaced
by empty gaps of ~22 s

Triggers were distributed uniformly
throughout train (for these particular
run conditions / trigger requirements)
X5
Train length  60  25 ns
10
3

25 ns bunch structure, with 924 RF
buckets per SPS orbit (23.1 s)
Number of triggers [10 ]

8
Distribution
of triggers
in trains
6
4
2
0
-20
0
20
40
60
80
Trigger position in SPS orbit (BX modulo 924)
HIP rate measurement (X5)

Normalise distribution of “HIP
events” to trigger distribution to
obtain:
“probability of trigger containing
HIP event” as function of trigger
position in train
Probability of trigger containing
HIP event is constant: ~4  10-3
 4  10-4 per pion per plane
1142 entries
Distribution of
HIP events in
particle trains
40
30
20
10
0
-20
0
20
40
60
80
Trigger position in SPS orbit (BX modulo 924)
–2

Number of HIP events
Alternative HIP rate measurement:
P(trigger with HIP event) [10 ]

50
2.0
Probability of
trigger containing
HIP event as
function of trigger
position
1.5
1.0
0.5
0.0
-20
0
20
40
60
80
Trigger position in SPS orbit (BX modulo 924)
Identifying disabled APVs

APVs experiencing deadtime can also
be identified:


Spread = ADCMAX – ADCMIN
If a trigger shortly follows a HIP event,
then an APV may be read out when in
a saturated state
No signal and pedestal structure are
observed in APVs experiencing
deadtime
 criteria for selecting disabled APVs:
CM
 -140 ADC counts,
spread  10 ADC counts
Peak at ~70
ADC counts
and tail due
to MIP signals
Disabled APVs
0
25
50
75
100 125 150 175 200
Spread [ADC counts]
Deadtime measurement (X5)

Normalise distribution of “disabled
APVs” to trigger distribution to
obtain:
“probability of trigger containing
disabled APV” as function of trigger
position in train
Number of disabled APVs
Deadtime measurement:
Distribution of
disabled APVs
in trains
6549 entries
200
150
100
50
0
-20
0
20
40
60
80
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
Probability of disabled APV is small
at start of train as cannot be HIP
events in preceding RF buckets
Probability saturates later in train
due to finite deadtime
“Risetime” provides measure of
average deadtime: ~300 ns
P(trigger with disabled APV) [10 ]
Trigger position in SPS orbit (BX modulo 924)
–2

250
4
Deadtime ~300 ns
3
2
1
0
-20
0
20
40
Trigger position in SPS orbit (BX modulo 924)
Laboratory deadtime measurements

Measure sensitivity of APV25 to normal
signals after simulated “HIP”

Inject & measure amplitude of MIP signal

Sweep injection time of “HIP” signal
MIP
signal
Vary HIP injection time
Trigger on
MIP signal
Deadtime as a
function of HIP
signal (Edep)
Latency
t
Deadtime
Response to
MIP signal
after HIP


Measured deadtime  350 ns
Threshold Edep ~10 MeV required
before deadtime is observed
Simulation* of pion-Si interactions




Predicts Edep up to ~100 MeV
Probability of Edep  10 MeV is ~10-3
Predicts comparable HIP rates for X5
and CMS
Only inelastic collisions contribute
significantly to P(Edep  1 MeV)
 negligible HIP rate with muons
* CMS NOTE 2002/011 (M. Huhtinen)
P(Eion = Edep) per 500 um Si
X5 data provide no information on
signal magnitude and spatial
distribution  simulation required
10
10
10
10
10
120 GeV pions (X5)
200 MeV pions (CMS)
-3
-4
-5
Differential
energy
deposition
spectrum
-6
-7
-8
0.1
10
P(Eion > Edep) per 500 um Si

10
10
10
10
10
10
10
-2
1
10
100
Energy deposition Edep [MeV]
120 GeV pions (X5)
200 MeV pions (CMS)
-3
-4
-5
Cumulative
energy
deposition
spectrum
-6
-7
-8
0.1
1
10
100
Energy deposition Edep [MeV]
PSI beam test
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Aims for dedicated HIP study:


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Verification of previous HIP rate measurements at X5
Observation of full APV25 recovery after HIPs to allow direct deadtime
measurement
Rate / deadtime measurements with reduced RINV values
Hardware/trigger requirements for PSI



Trigger logic providing particle-vetoes before triggers (clean measurements)
Trigger card providing multiple triggers (every 75 ns)
+ APV25 multi-mode operation (peak mode readout, 3 frames per trigger)
 data every 25 ns for 750 ns after initial trigger
6 TOB + 3 TIB + 3 TEC modules exposed to 300 MeV pion beam
HIP rate measurement (PSI)

Criteria for selecting HIPs as for X5
Type RINV [] HIP rate

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Rates in agreement with simulation
and X5 results
Observe factor ~0.6 between rates
for 500 m and 320 m sensors
Slightly reduced HIP rate for lower
values of RINV
320 m thick sensors:
TIB
50
(2.3 ± 0.1) 10-4
TIB
100
(3.7 ± 0.1) 10-4
500 m thick sensors:
TEC
100
(6.2 ± 0.1) 10-4
TOB
50
(5.5 ± 0.1) 10-4
TOB
75
(5.8 ± 0.2) 10-4
TOB
100
(6.2 ± 0.1) 10-4
Example of APV25 recovery
Top:
raw analogue data (peak mode)
Bottom: numerical deconvolution of raw data
t=
0 ns:
300
HIP event
t = 125 ns:
Baselines begin to recover
t = 200 ns:
Baseline flat in deconvolution mode
t = 275 ns:
Nominal baseline position in decon mode
Continued slow recovery in peak mode
t = 650 ns:
Peak
(raw data)
0 ns
25
50
75
100
125
150
175
200
225
250
275
300
325
350
375
400
425
450
475
500
525
550
575
600
625
650
Baseline still recovering in peak mode
Slow time-varying signals filtered out by
deconvolution algorithm
 improved baseline behaviour (~flat and
shorter recovery period)
Digital
zero
100
200
Nominal
baseline
pos.
0
Deconvolution
(numerical calc)

Average baseline position as
function of time after HIP
(peak mode)



Curves grouped according to
module type and resistor value
Baseline position
Baseline recovery
Nominal
position
Modules equipped with lower
RINV values recover first
Expect quicker recovery and
no overshoot in decon mode
Disabled
APVs?
Fully
saturated
0
125
250
375
500
Time [ns]
625
750
Inefficiency due to HIP effect
 (E)  128  occ.  P ( E ) 
“Hit reconstruction efficiency in
hipped APV” as function of time
after HIP event
(E)
Ineff    (E)
E
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
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Simulation provides probability of a
given energy deposition, P(E)
Deadtime dependence on energy,
(E), provided by lab measurements
Efficiency
25 ns
-30
-90<
<CM
CM<
<0-30
-60
-60
<
CM
<
-30
0
0
100 200
300 400 500 600 700
Time [ns]

Resulting inefficiency (per plane per
% occupancy) is sub-% level
Less than inefficiency due to
unbonded or noisy strips
1.0
0.8
0.6
0.4
0.2
0.0


Using PSI data, perform efficiency
scans for various CM shifts and
convert into “effective deadtime”,
’(CM)
Calculate probability of observing
CM shift, P’(CM), from PSI data
Inefficiency again sub-% level
Conclusions


Large signals, resulting from rare interactions between incident hadrons
and silicon sensors, can saturate the FE electronics and result in
inefficiencies (per plane per % occupancy) at sub-% level
Encouraging that we are investigating effects in the readout chain that
affect the performance of the Tracker at 10-3 level