READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG

Name: READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG
Uploaded: 2017-07-18T06:03:01+00:00
Duration: PTM41S57
Channel: Marquis Pringle
Description: READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG

READ NOISE @ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG
SPIE H2RG noise to 1kHz READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG Roger Smith Caltech , Tue 10:50am Slides containing shading such as this box (marked as “Redacted”) contain information concealed by the shading which **may** be ITAR sensitive and if determined as such could incur severe penalties if distributed to non US persons (citizens or Legal Permananent Residents). Therefore it is recommended that this presentation only be distributed to non “US Persons” in PDF format so that the redactions remain in place. Note that the responsibility lies with the person passing the data onwards, not the creator of the information.

Abstract (for reference only)
SPIE H2RG noise to 1kHz A camera operating a Teledyne H2RG in H and Ks bands is under construction to serve as a near-infrared tip-tilt sensor for the Keck-1 Laser Guide Star Adaptive Optics system. After imaging the full field for acquisition, small readout windows are placed around one or more natural guide stars anywhere in the AO corrected field of view. Windowed data may be streamed to RAM in the host for a limited time then written to disk as a single file, analogous to a “film strip”, or be transmitted continuously via a second fiber optic output to a dedicated computer providing real time control of the AO system. The various windows are visited at differing cadences, depending on signal levels. We describe a readout algorithm, which maximizes exposure duty cycle, minimizes latency, and achieves very low noise by resetting infrequently then synthesizing exposures from Sample up the Ramp data. To illustrate which noise sources dominate under various conditions, noise measurements are presented as a function of synthesized frame rate and window sizes for a range of detector temperatures. The consequences of spatial variation in noise properties, and dependence on frame rate and temperature are discussed, together with probable causes of statistical outliers.

Black pixels have low QE
The application SPIE H2RG noise to 1kHz Tip tilt sensing for LGS AO on Keck 1, with OSIRIS integral field spectrograph, Reimage 120 arcsec diameter AO corrected 50 milliarcsec/pixel. H or K bands; dichroic or annular mirror pickoff. Multiple guide stars, No moving probes. H2RG For calibrations and acquisition 4ch readout of Band of Interest 105 arcsec For fast tip-tilt correction multiple windows, typically 4x4, read sequentially through 1 ch. Black pixels have low QE 105 arcsec

The Camera SPIE H2RG noise to 1kHz 0.5mm thick fiberglass cylinders cold bench with intermediate stage for floating shields Light tight detector housing, removable through rear hatch Lens barrel, removable through rear hatch Wheel carries pupil stops + filters, and diagnostic apertures Window is tilted to compensate for astigmatism due to dichroic pick off. Articulated fold mirror, manual at present, motorize later.

Tip Tilt Sensor for Keck-1 AO
Keck AO NIR Tip-Tilt Sensor Laser guide star is insensitive to wavefront tilt. Laser light follows same paths upwards as upon return. So need natural guide star. Better to sense in in NIR than present optical camera (STRAP): Higher strehl in K band = better sensitivity = more guide stars. Higher strehl = better centroiding accuracy for given S/N. Access to regions obscured by dust. Frame rate is fast enough that thermal background does not overwhelm above benefits.

Modeling says K band is best if < 30arcsec off axis.
Keck AO NIR Tip-Tilt Sensor Strehl vs separation of science target and guide star…

When off axis, multiple stars help
Keck AO NIR Tip-Tilt Sensor

Sky fraction improvement

Zenith angle improvement

NIR Tip Tilt Concept Keck AO NIR Tip-Tilt Sensor Pick off mechanism selects dichroic or annular mirror to pass K (or H) band to TRICK. Re-image full AO FoV onto 2K*2K 2.5µm cutoff H2RG sensor Multiple guide stars possible. No mechanisms: fast capture, and offsets are precise. Nyquist sampling in Ks band.

TRICK location on AO bench
Keck AO NIR Tip-Tilt Sensor TRICK dewar Pick off goes here

TRICK location - detail
Keck AO NIR Tip-Tilt Sensor TRICK OSIRIS PICK OFF MECHANISM

Mechanical Keck AO NIR Tip-Tilt Sensor

Simplified block diagram
SPIE H2RG noise to 1kHz Camera System For field acquisition & calibration: Full frame or band of interest readout, only to host. For guiding: Multiple ROIs, typically 4x4 pixels. Different visitation rates for each. Raw data streamed to 2nd fiber link indefinitely, or Buffered in host RAM then written as single FITS file = “film strip”. 2nd data link is unidirectional (no handshaking) since timing is slaved to readout. Configuration descriptor packet is sent on video link (2nd fiber) at every reset. Readout configuration commands accepted in real time, but take effect at next reset.

Readout modes Optimize for high exposure duty cycle, thus best SNR.
SPIE H2RG noise to 1kHz Readout modes Optimize for high exposure duty cycle, thus best SNR.

Correlated Double Sampling
Let’s review common readout timing options…. Correlated Double Sampling SPIE H2RG noise to 1kHz e = 1 = number of exposures to do …. not shown here r = number of reset scans between exposures m = 1 = number of scans to coadd then store. p = 10 = number of dummy scans between coadded groups k = 2 = number of store cycles per exposure Exposure time Frame time Duty cycle = Frame time Exposure time Reset while idling Ignore p scans At least one reset between frames Initial scan Final scan Exposure delay = p dummy reads for constant self heating Subtract first frame from last frame Equivalent to Fowler sampling with m = 1

Fowler “m” Duty cycle < 1 Frame time Exposure time Coadd m
SPIE H2RG noise to 1kHz e = 1 = number of exposures to do …. not shown here r = number of reset scans between exposures m = 3 = number of scans to coadd then store. p = 6 = number of dummy scans between coadded groups k = 2 = number of store cycles per exposure Duty cycle < 1 Frame time Exposure time Coadd m Ignore p scans Coadd m Subtract means Exposure delay is multiple of dummy read time but need not be multiple of m.

Sample Up the Ramp (SUR)
SPIE H2RG noise to 1kHz e = 1 = number of exposures to do …. not shown here r = number of reset scans between exposures m = 1 = number of scans to coadd then store. p = 0 = number of dummy scans between coadded groups k = 12 = number of stores per exposure Store every scan (no real time coadd) Use post facto least squares fit to measure slope with best S/N Effective exposure duty cycle due to weighting of shot noise by least squares ~ 90%; reduce this to include effect of the reset overhead. Equivalent MultiAccumulate with m=1.

Multi-Accumulate (JWST terminology, variant of SUR)
SPIE H2RG noise to 1kHz e = number of exposures to do …. not shown here r = 2 = number of reset scans between exposures m = 3 = number of scans to coadd then store. p = 0 = number of dummy scans between coadded groups k = 4 = number of stores per exposure Coadd m Coadd m Coadd m Coadd m Reset r scans Coadd m Coadd m Coadd in real time, store every m scans, total exposure duration is multiple of m scan times. Least squares fit of stored (coadded) scans is used to estimate noise. Advantage of coadd over single samples with gaps is lower noise and better cosmic ray detection ( which appears as jump in ramp). One or more reset scans between exposures.

Readout mode used in the noise tests presented hereafter Differential Multi-Accumulate
SPIE H2RG noise to 1kHz Sparse reset allows us to use end of previous frame as baseline for next so duty cycle ~100%, except for a gap when reset occurs. For tip-tilt control interpolating over this data gap is ok since sample rate is typically ten times servo’s closed loop bandwidth. Can use global reset (least overhead) or line by line (least thermal transient). Exposure time Coadd m Coadd m Coadd m Coadd m Coadd m Coadd m Reset Difference = frame 1 Difference = frame 2 Difference = frame 3 Occasional gap ! Difference = frame 4

Pixel timing optimization for ARC Inc. 8ch IR video card
SPIE H2RG noise to 1kHz 10 µs/pixel is standard but can go faster with no penalty. …by reducing overheads to 2.16µs, and overlapped this with signal settling. For 3µs dwell, pixel time is halved sample twice as often with same noise BW.

Pixel Time Optimization
22 Pixel Time Optimization SPIE H2RG noise to 1kHz Is SNR improved more by: increasing settling time above 2µs, or adding more dwell time (noise BW limiting), or coadding more frames ? Moderately small window for fast readout RMS noise (temporal per pixel) mean in 16x16 window(e-) Conventional 10µs pixel 10 Update this with new curves. Use separate plots for settle and dwell time optimizations. 6 More dwell time is better at high frequency, with most gain by 4us 5 4 At low frequency, more coadds are better than more dwell time. 3 Choose 2µs settle + 4µs dwell = 6µs/pixel 2 22

Speed-noise CURVES MEAN NOISE AT DIFFERENT TEMPERATURES
SPIE H2RG noise to 1kHz Speed-noise CURVES MEAN NOISE AT DIFFERENT TEMPERATURES Speed/Noise curves v. Temp from 2011-Oct-28 Standard speed/noise filmstrip data System extremely stable no software or hardware restarts no bias interrupts Relatively short filmstrips (~90 sec) with no inter-frame delay Skip through slides to animate.

T=80K 100 Mean in window for per pixel RMS (temporal) noise (e-) 10 1
SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 ,000 Synthesized frame rate (Hz)

Deliberately left blank.
SPIE H2RG noise to 1kHz Deliberately left blank.

NOISE mechanisms Same plots again but now
SPIE H2RG noise to 1kHz Same plots again but now identify effects of dark current, RTS, 1/f, white NOISE mechanisms

T=80K Mux glow, CDS noise, i.e. no coadds
SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) ,000 Synthesized frame rate (Hz) 10 1 100 Mux glow, not dark current since depends on # reads not frame rate CDS noise, i.e. no coadds Smaller ROI = more coadd at given frame rate

T=90K Hot pixels included Mux glow dominates when hot pixels excluded
SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 Hot pixels included Mux glow dominates when hot pixels excluded ,000 Synthesized frame rate (Hz)

T=100K Hot pixels? climbing as T increases Mux glow
SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 Hot pixels? climbing as T increases Mux glow not increasing with T ,000 Synthesized frame rate (Hz)

T=110K SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 Must be RTS noise Since rises and falls again with T as characteristic frequency changes. At high frequency noise is white, so scales as ~1/√(coadds) Prevent this turn up at low frame rates by putting time delay between samples instead of reading more often ,000 Synthesized frame rate (Hz)

T=120K SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 RTS noise kink ,000 Synthesized frame rate (Hz)

T=130K Dark current starts to manifest itself at longer exposure times
SPIE H2RG noise to 1kHz Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 Dark current starts to manifest itself at longer exposure times White noise drops very slightly at higher temperature ,000 Synthesized frame rate (Hz)

Scales faster than 1/√(frame_time) …why?
T=140K SPIE H2RG noise to 1kHz Dark current dominates: Depends mostly on frame rate not # reads Mean in window for per pixel RMS (temporal) noise (e-) 10 1 100 Scales faster than 1/√(frame_time) …why? ,000 Synthesized frame rate (Hz)

Mux glow 2.5µm H2RG-220 @ 80K Idark = 0.004 e-/s (SUR at 2s/sample)
40 SPIE H2RG noise to 1kHz Idark = e-/s (SUR at 2s/sample) Greater for fast read of small windows due to self heating … see next slide. Mux glow= e-/read at 6µs/pixel. 4x4 8x8 Change x axis Skip this slide leaving it for Dave’s talk. 16x16 32x32 Time (s) Frame number

Self-heating can masquerade as mux glow
SPIE H2RG noise to 1kHz As window size is reduced same power is concentrated in smaller area so temperature rises: dark current increases with number of reads rather like mux glow, but more steeply than mux glow. 8x8 window After160,000 frame SUR in 75s 5e-/s or e-/read 8x8 Hot spot in next readout 32x32 window After 10,000 frame SUR in 75s …weaker since thermal footprint of previous 8x8 window is decaying. Glow ~0.0035e-/read

Noise model Model parameters Low noise ground based astronomy recipe
SPIE H2RG noise to 1kHz Low noise ground based astronomy recipe At 80K, for pixels with negligible RTS Model parameters Would be good to verify that this model scales to other window sizes. See how much parameters vary from pixel to pixel. Extend to lower frame rates to better test model for mux glow. 10.9*(coadds)-0.47 XX* 1/f floor=2.4e- 0.0034e-/read

Noise model – 1/f suppressed
SPIE H2RG noise to 1kHz Low noise ground based astronomy recipe Model parameters XX* 10.9*(coadds)-0.47 1/f suppressed 0.0034e-/read

noise MAPS AT DIFFERENT TEMPERATURES SPIE 8453-35 H2RG noise to 1kHz
noise MAPS AT DIFFERENT TEMPERATURES

Noise Maps, sparsely sampled
4x4 windows evenly spaced across detector 128 pixels in from edge 256 pixel inter-ROI separation. Packed into 32x32 pixel array

Noise maps vs. Frame rate and Temperature
SPIE H2RG noise to 1kHz 1kHz 100Hz Redacted 10Hz 80K K K K

Histograms vs. Frame rate and Temperature
SPIE H2RG noise to 1kHz 1kHz 100Hz 10Hz 80K K K K

Using data from noise maps on previous slide: Noise Histograms vs
Using data from noise maps on previous slide: Noise Histograms vs. Frame rate and Temperature SPIE H2RG noise to 1kHz 80K Redacted 10Hz 100Hz 1kHz

Speed-noise CURVES FOR SELECTED PIXELS
SPIE H2RG noise to 1kHz Speed-noise CURVES FOR SELECTED PIXELS AT DIFFERENT TEMPERATURES Differentiate RTS and hot pixels.

16x16 ROI, single pixel speed-noise curves
SPIE H2RG noise to 1kHz Column 1 pixels 1000e- 120K 100e- 10e- 1e- Redacted 1000e- 110K 100e- 10e- 1e- Speed-noise curve

Random Telegraph Signal
SPIE H2RG noise to 1kHz Gain of the pixel buffer MOSFET is bistable when there is a single electron trap located in or near the channel.

RTS frequency vs. T Same pixels 80 K 110 K Normal RTS
SPIE H2RG noise to 1kHz Same pixels 80 K 110 K Normal RTS

Fixed patterns Dominated by self heating
SPIE H2RG noise to 1kHz Dominated by self heating Power dissipation (only) when pixel addressed. Addressing one pixel continuously when idle creates hot spot. Starting up at a new window location, setup overheads exceed thermal settling time. Settling is benign provided that you idle the way you read! Effect of moving window Must move window to compensate for atmospheric dispersion differential w.r.t. science target, or for non-sidereal science target. Self heating profile across window changes….

Jog 4x4 window 2 pixels to left
100Hz synth frame Repeats no binning. Time progresses L-R, one frame per column (9.786 msec). The four rows are the first four fly-back positions. White indicates pixels are cooler than average. Time last frame before move First frame after move

Jog 4x4 window 2 pixels to left
exponential decay 1kHz synthesized frame rate Repeats no binning. Dark spot at upper left is due to above average self-heating caused by an inadvertent delay (tens of microsecs) between flyback and start of active rastering during which the initial pixel is heated continuously. Time last frame before move First frame after move

Transients settle in 6 milliseconds
1kHz synthesized frame rate 6 ms Column 2 Column 1 Columns 3 and 4

Anomalies These may be skipped due to lack of time.
SPIE H2RG noise to 1kHz These may be skipped due to lack of time. Anomalies

Column offset where window addressed
SPIE H2RG noise to 1kHz Full frame CDS image of field of spots after global reset of single 64×64 window. Before the “fix” f0200_0-3 intensity increases dark-to-light Entire column is offset while ROI is addressed during full frame readout

Fixed by changing window address
SPIE H2RG noise to 1kHz Full frame CDS image of field of spots after global reset of single 64×64 window After the “fix” f0201_0-3 intensity increases dark-to-light Offset goes away when ROI pointers are moved to lower left corner.

Race condition for window reset.
SPIE H2RG noise to 1kHz To illustrate the effect 3 windows on diagonal are reset sequentially in the sequence {1,2,1,3,1}, then full frame is read out. 3 Spurious resets due to race condition in mux column select logic for window reset. 2 1

Reset “ghosts” fixed. SPIE H2RG noise to 1kHz Window ghosts are moved to line 1 after each target window is reset, by resetting a second time with window start and end at (1,1) The ghost still occurs but in line one, where it can be ignored.

Line skip fault in engineering grade mux
SPIE H2RG noise to 1kHz Line advances two or more lines per vertical clock pulse when a particular range of lines is addressed. Which lines are affected depends on temperature, supply voltages and number of channels being read out. Pixels in windows not overlapping with affected bands are addressed correctly so the band of ~100 lines can be treated as bad pixels for window mode but in full frame all trailing lines are effectively lost. Scan bottom to top, H2RG-222 Scan top to bottom, H2RG-222 Pinhole grid imaged onto detector with pixel pitch in X and Y No change when clocking direction is reversed source = cooelab1:/data/TRICK/det222/ /test/test0027.fits cropped  test27cm Vertical skips occur when addressing these lines

SPIE H2RG noise to 1kHz Additonal SLIDES

Raw pixel values vs Time (no coadding)
SPIE H2RG noise to 1kHz Noisiest pixels exhibit “Random Telegraph Signal” a bimodal noise distribution due to single traps in or channel near buffer FET. Number of such traps and distance from channel produce a spectrum of amplitudes. Characteristic time constants vary widely. All silicon transistors suffer from this to some extent. In big transistors many traps are in play and it accounts for 1/f noise. In small transistors one or a few traps produce RTS noise. Cooling increases the time constant. Slow traps become so slow they become invisible, but fast traps which would average to zero now move into signal passband. Quiet pixel Raw value minus 1st frame (ADU) Noisy pixel Frame number Excess noise is due to RTS in mux

Histogram of RTS noise for the nasty case of two traps about the same size
SPIE H2RG noise to 1kHz Time series

Same after coadd and subtract (100 coadds)
SPIE H2RG noise to 1kHz For time series on previous slide Differencing turns steps into spikes. Coadding helps but noise is still significantly degraded by RTS. Better to reject outliers than try to average them away

READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG

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READ 1 to 1000 Hz for a 2.5µm cutoff Teledyne H2RG

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