Transcript Zero Read Noise Detectors for the TMT Don Figer, Brian Ashe , John Frye, Brandon Hanold, Tom Montagliano, Don Stauffer (RIDL), Brian.

Zero Read Noise Detectors for the TMT
Don Figer, Brian Ashe , John Frye, Brandon Hanold, Tom Montagliano, Don
Stauffer (RIDL), Brian Aull, Bob Reich, Dan Schuette, Jim Gregory, Erik Duerr,
Joseph Donnelly (MIT/LL)
MIT LL No. MS-43282, ESC No. 09-1097
Outline
• Motivation
– Why pursue photon-counting technology?
– Why use Geiger-mode avalanche photodiodes
(APDs)?
• Moore Detector for TMT
• Heritage: LIDAR
• Conclusions
2
Outline
• Motivation
– Why pursue photon-counting technology?
– Why use Geiger-mode avalanche photodiodes
(APDs)?
• Moore Detector for TMT
• Heritage: LIDAR
• Conclusions
3
Why pursue photon-counting
technology?
• Photon-counting detectors effectively have
zero read noise.
• In low light applications, read noise can
dominate signal-to-noise ratio.
• Many applications can become low light
applications with higher resolutions.
– spectroscopy
– time-resolved photometry
– fast wavefront sensing and guiding
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Detectivity (higher is better)
SNR 
S

N
signal flux
signal flux  backgroundflux  (dark noise)2  (read noise)2

F tQE
h




 

F tQE   inst A
Fback , tQE   idark t  N 2read
inst A
h
h

 

inst A

N  tQE
N  tQE  n pix N  ,background tQE  n pixidark t  n pix N 2read
Sensitivity  flux at whichSNR  1
Detectivity 
Detectivity 
1
1

sensitivity N  , SNR 1
2tQE
1  1  4n pix ( N  ,background tQE  idark t  N 2read )
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noise dominated
read

 
tQE
.
N read n pix
Exposure Time to SNR=1
  exposuretimeto reach a particularSNR. Solve SNR equation for t.

SNR2 ( N  QE  n pix N  ,background QE  n pixidark )  SNR4 ( N  QE  n pix N  ,background QE  n pixidark ) 2  4 N 2 n pix (QE N read SNR) 2
2( N  QE) 2
SNR 1 and N
 0 and idark  0
       
,background
N read n pix
.
N  QE
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Example for Planet Imaging
• The exposure time required to achieve SNR=1 is
dramatically reduced for a zero noise detector
compared to detectors with state of the art read
noise.
read noise
FOM
0
1
2
3
4
5
6
7
Exposure Time (seconds) for SNR = 1
Quantum Efficiency
10%
6,600
7,159
8,486
10,148
11,954
13,830
15,745
17,684
20%
2,300
2,674
3,457
4,363
5,312
6,281
7,259
8,244
30%
1,311
1,591
2,141
2,760
3,402
4,053
4,709
5,368
40%
900
1,123
1,547
2,016
2,500
2,990
3,484
3,979
50%
680
865
1,209
1,587
1,976
2,369
2,764
3,161
mag_star=5, mag_planet=30, R=100, i_dark=0.0010
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60%
544
703
992
1,309
1,633
1,961
2,291
2,621
70%
453
591
841
1,113
1,392
1,673
1,956
2,239
80%
388
510
730
968
1,212
1,459
1,706
1,954
90%
338
448
645
857
1,074
1,293
1,513
1,734
100%
300
400
577
768
964
1,161
1,359
1,558
Why use Geiger-Mode Avalanche
Photodiodes (GM-APDs)?
• produce easily distinguishable high voltage
pulse per photon
• have zero “excess noise factor”
• allow for hybridization and bonding to nonoptical detecting materials
• allow photon counting inside each pixel for
high frame rates and time tagging
• have demonstrated excellent performance for
LIDAR applications
8
Gain of an APD
M
Ordinary
photodiode
Linear-mode
APD
Geiger-mode
APD
100
10
1
0
Response
to a photon
I(t)
Breakdown
M
1
9
∞
Geiger-Mode Imager: Photon-to-Digital Conversion
Pixel circuit
Digital
timing
circuit
photon
Digitally
encoded
photon
flight time
APD/CMOS array
APD
Lenslet
array
Focal-plane
Quantum-limited sensitivity
Noiseless readout
Photon counting or timing
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Outline
• Motivation
– Why pursue photon-counting technology?
– Why use Geiger-mode avalanche photodiodes
(APDs)?
• Moore Detector for TMT
• Heritage: LIDAR
• Conclusions
11
Moore Detector Project Goals
• Operational
– Photon-counting
– Wide dynamic range: flux limit to 108 photons/pixel/s
– Streaming readout
• adaptive optics imaging
• multiple target tracking
– Time delay and integrate
• Technical
– Backside illumination for high fill factor
– Demonstrate 25 mm pitch imager with streaming, single
photon, readout
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Moore Photon Counting Imager
Optical (Silicon) Detector Performance
Parameter
Phase 1
Goal
Format
Phase 2
Goal
256x256
1024x1024
25 µm
20 µm
zero
zero
Dark Current (@140 K)
<10-3 e-/s/pixel
<10-3 e-/s/pixel
QEa Silicon (350nm,650nm,1000nm)
30%,50%,25%
55%,70%,35%
90 K – 293 K
90 K – 293 K
100%
100%
Pixel Size
Read Noise
Operating Temperature
Fill Factor
aProduct
of internal QE and probability of initiating an event. Assumes
antireflection coating match for wavelength region.
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Moore Photon Counting Imager
Infrared (InGaAs) Detector Performance
Parameter
Phase 1
Goal
Format
Phase 2
Goal
Single pixel
1024x1024
25 µm
20 µm
Read Noise
zero
zero
Dark Current (@140 K)
TBD
<10-3 e-/s/pixel
QEa (1500nm)
50%
60%
90 K – 293 K
90 K – 293 K
NA
100% w/o mlens
Pixel Size
Operating Temperature
Fill Factor
aProduct
of internal QE and probability of initiating an event. Assumes
antireflection coating match for wavelength region.
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Moore Detector Project Status
• A 256x256x25mm readout integrated circuit is being
fabricated.
• InGaAs test diodes are being fabricated.
• Silicon GM-APD arrays have been fabricated and will
be bump-bonded to the new readout circuit.
• Photon-counting electronics are being built.
• Testing will begin later in 2009.
• Depending on results, megapixel silicon or InGaAs
arrays will be developed.
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Overview of Pixel Operation
Pixel Architecture
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ROIC Pixel Layout (2x2 pixels)
metal bump bond
pad
2 pixels, 50 mm
core
(active
quench,
discriminator,
APD latch)
counters (4 pixels)
counter
rollover latch
2 pixels, 50 mm
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InGaAs Development
• 3 APD designs grown and fabricated
– 2-mm-wide avalanche region (all InP)
– 3-mm-wide avalanche region (all InP)
– 2-mm-wide avalanche region (InGaAs absorber)
• Room-temperature CV measurements made
• Devices in packaging for low temperature
measurements
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Outline
• Motivation
– Why pursue photon-counting technology?
– Why use Geiger-mode avalanche photodiodes
(APDs)?
• Moore Detector for TMT
• Heritage: LIDAR
• Conclusions
19
Si APD/CMOS Development History
APD’s
1996
Discrete 4x4 arrays
4x4 arrays
wire bonded to
16-channel
CMOS readout
32x32 arrays
fully integrated with
32x32 CMOS readout
not to scale
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64 x 64 arrays
3D-integrated with
2 tiers of SOI CMOS
256 x 256 arrays
2009
LIDAR Imaging System
Microchip laser
Geigermode APD
array
• Imaging system photon
starved. Each detector must
precisely time a weak optical
pulse.
Color-coded
range image
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A LIDAR Imaging Detector for NASA
Planetary Missions
Parameter
Current
Goal
Space-Qualifiable
NO
YES
Scalable to Large Format
NO
YES
CMOS ROIC Timing Resolution
250 ps
250 ps
Pixel Size
50 mm
50 mm
unknown
<10-3 e-/s/pixel
Multiplied Dark Current (@140 K)
QE (350nm,650nm,1000nm)a
Operating Temperature
Radiation Limit
Technology Readiness Levelc
•
•
•
•
45%,65%,5%
45%,65%,10%
293 K
90 K – 293 K
unknown
50 Krad(Si)b
2
4
High field
multiplier
Medium
low field
Low
field
absorber
These arrays will be fabricated for back-illumination with bump bonding,
enabling high performance in a space-qualifiable focal plane.
The design of the ROIC will be finished by the end of 2009, with
fabrication starting in early 2010.
Funding: $546,000
Duration: 3 years (2008-2010)
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32x32 APD/CMOS Array with
Integrated GaP Microlenses
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Laser Radar Brassboard System
(Gen I)
Taken at noontime on a sunny day
• 4  4 APD array
• External rack-mounted timing circuits
• Doubled Nd:YAG passively Q-switched microchip laser
(produces 30 µJ, 250 ps pulses at  = 532 nm)
• Transmit/receive field of view scanned to generate 128  128 images
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Conventional vs LIDAR Image
Conventional image
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3D Imaging of Model Airplane
Single Frame
3D Display of Processed Image,
Probability of Detection Color-code
Color-code:
1 m range
display
Airplane hanging
on 6 mm rope
• Multiple-frame coincidence processing of ~3-4 frames removes isolated dark
counts
• Image quality excellent due to low optical cross-talk between pixels
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Rotatable 3D Images of Multiple Objects
Color-coded by Distance
Color-coded by Detection Probability
• 128x128 images recorded with scanned 4x4 array at 1.06 mm
• Coincidence processed to remove background/dark counts
• Dark blue equivalent to <2 photon average return (right image)
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Outline
• Motivation
– Why pursue photon-counting technology?
– Why use Geiger-mode avalanche photodiodes
(APDs)?
• Moore Detector for TMT
• Heritage: LIDAR
• Conclusions
28
Conclusions
• Large-format photon-counting imaging
detectors are within reach.
• We are funded to make 256x256 and
megapixel devices.
• A 256x256 detector silicon-based array should
be in testing by the end of the year.
• The devices will be implemented in a broad
range of low light level and LIDAR timing
applications.
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