The evolution of detectors:

from photography to CCD’s

Michel Dennefeld

Institut d’Astrophysique de Paris

and

University P. et M. Curie (Paris 6)

and thanks to Henry Mc Cracken ...

Part I : History and progress.....

The human eye: -2.5 cm diameter lens -130 millions pixels -125 M cones (day-time, tri-colour vision) ~ 140˚ FOV, 1’ resolution -5 M rods (night-time, grey vision) -Spectral response: -Daytime: peak at ~ 550 nm -Nightime: slightly bluer

Transparency and energy versus λ …

hν~ GeV-keV ~ 1 eV I=[a(sinωt-φ)]² ?

“Modern” detectors

transform a photon into a (photo)-electron!

What makes the difference, is what happens then to this electron...

hν = Eextr + ½ mv2

Wavelength threshold: λ°(μ) < 1.24/ E(ev)

e.g. Silicon: 1.1 μ; Photo: ~ 0.45 μ

•The principle is the same for all detectors:

-If the electron « escapes » the material, you have

photoelectric systems Requires additional extraction energy (thus less red sensitivity),

but you can then act on the electron (amplification)

-If the electron remains inside, you have

photoconductors Higher efficiency, but more difficult to handle

Photographic plates

• It was the first objective and permanent record of astronomical

phenomena (~ 1880 +...)

• Long exposure times are possible thus faint objects can be detected

• Exists in large format: many sky surveys carried out, as recently as

the 1990s. e.g. the Palomar Sky Surveys (DSS...) in B (103aO) and

R (IIaF); in the South, IIIaJ, etc...

AgBr crystals: Br- + hv gives Br + e- and Ag+ + e- gives (unstable) Ag

The development enhances the quantity of Ag where it exists.

Problems: very non-linear process; impurities and traps compete

for the electrons, hence very low efficiency.

The latter can be improved with sensitising processes, but

the DQE hardly comes over 3%!

But what are QE, DQE, 103aO, etc...??

Fondamental parameters for a detector...

• QE (noted η) = <number of

electrons/photons>, is << 1 !

• DQE = (input S/N)2 / (output S/N)2 thus

DQE is ≤ η (in Poisson statistics, the S/N

is equal to √n )

• Sensitivity: NEP, input power needed to

provide a S/N of 1

• Its dependance with wavelength...

• Linearity, dynamical range, MTF

Parameters of photographic plates

• How to improve sensitivity?

• -Sensitizing (= reduce traps)

•

- Higher energy electrons

(photocathodes + high voltage

= electronographic systems)

Photoelectric detectors

• First application:

Photomultiplier tubes (1950-1990s) = single pixel detectors!

High-voltage (~ 20 kV) acceleration and amplification of electrons.

Initially measured output currents, later used as photon-counting

systems.

• More sensitive than photography (~20% quantum efficiency)

• Extremely stable, linear, broad band devices which made possible

the first highly accurate photometric systems

• Flux calibration of photomultiplier based systems is still more

accurate than modern array imaging detectors!

How to get 2D images with photoelectric systems?

• Electronographic cameras:

• Electrostatic, or magnetic focusing, +photographic plate output

• But photocathodes need to remain in vacuum... (Lallemand, Kron, Spectracon cameras...) •TV tubes, but not very stable, and poor PSF

• Combined systems lead to Photon-Counting devices.

How do Photon Counting systems work ?

• High e- amplification: bright patch of light

at the output

• Centroiding of the light patch, at a fraction

of (output) pixel.

• Coordinates of the event are stored in the

memory: independant of the intensity of

the patch!

• Thus each event has the same weight

• Single photo-electron is detected if

amplification high enough

• No noise, but saturation limit

• Deadtime between events (e.g. decay time

of output phosphor)

Modern photon-counting systems

• Micro-channel plates: more compact, and

lighter than photo-tubes. Various read-

out modes...the best is:

• MAMA (Multi-Anode Multichannel

Arrays)

Photon counting systems:

-Pro’s: - Single photon detected

- Equal weight for each event

- No noise

-Con’s: - Sensitive to high-flux (deadly!!)

- Low QE (limited by photocathode, ~20%)

- DQE ~ 7% (e.g. HST/STIS)

How to improve the Quantum Efficiency?

and its wavelength dependance?

• ~20% QE limit for photo-emissivity,

• and poor red-sensitivity

•Semi-conductors have better QE,

but electrons trapped inside

•One thus needs to find ways

to « read » the electrons...

How a semi-conductor works...

• Exemple of a photo-diode

- Energy diagram

-Read-out mode

Many capacitors in parallel,

thus high read-out noise

(NEC ~Cv/q √[4kTBR1] )

14

How to do it on a 2D image: CCD Readout

Thomson 2048 X 2048 CCD

Horizontal register = Serial register

Digitize via Analog to digital (A/D) converter

Charge Coupled Devices (CCD’s)

•First astronomical use: TI 800 x 800 for HST (~ 1980)

• To reduce Cv: no external connections, and no

physical limit between pixels! Only one connection at

the extremity.

• The free photo-electrons in the conducting band are

then ‘shuffled’ to the output electrodes by applying

electrical pulses.

• The output signal is amplified and converted from

electron units to digital units with a conversion factor

or Gain, “g” (measured in electrons per analogue-to-

digital unit, e-/ADU).

• The Gain is simply a multiplicative factor.

• Number of electrons = Pixel ADU value x Gain

How CCD’s work (II)

• Reading out a CCD can take time,

especially for the largest arrays

with many pixels: the mode is

different for video or astro

• The r.o.n. is ~ 1/ √t

• You can use several amplifiers in

parallel, but it is then difficult to

have the same gain everywhere!

• In drift scanning CCDs are read out

continuously (for example like the

SDSS camera); no read-out time

but integration time is fixed!

• Shuffling charge on CCDs can be a

way to compensate for atmospheric

seeing -- see the orthogonal charge

transfer chips used in the Pann

Starrs project

The positive points of CCD cameras...

• Extremely good quantum

efficiency at redder

wavebands – close to 100%!

• Limiting magnitudes increased

by four to five magnitudes!

• Sensitivity of telescopes is now

limited by light collecting area

and not the detector area.

• CCD’s are linear over a very wide flux range: calibrations are easier!

• Output is digital!

Some problems with CCD detectors

• Poor blue (< ~4500 Å) response (too small

penetration depth of blue photons)

• Megacam (Canada-France Hawaii

Telescope) is one of the few wide-field

detectors with good U* response

• Adequate surface treatment can help solve

this problem, but at the cost of fringing!

• It’s hard to make large monolithic CCD

detectors: make mosaics from ‘buttable’

detectors, but problem of curved focal planes.

• Charge transfer efficiency between wells is

not 100% and degrades over time especially in

space-based detectors.

• Sensitive to Cosmic Rays

• Cryogenic cooling (normally

liquid nitrogen is used) is

necessary to reduce dark

current

• Reading out CCDs can take

time!

Examples of unwanted effects...

Charge transfer bleeding in STIS detector

Diffraction spike (secondary

mirror) Not specific to

CCD’s !

Cosmic ray hits in megacam-u* image

Some real image defects (Hubble/WFPC2):

Ghost

Bleeding

Cosmic ray

Charge Transfer (In)efficiency

CCDs are read out by

clocking charge along

registers. These transfers are

impeded by radiation damage

to the chips.

This effect gets worse with

time and is worse in space,

This image is from the STIS

CCD on Hubble. Note the

vertical tails on stars.

Can degrade photometry and

astrometry

More unwanted effects...

• Fringing : due to « thin » CCD...

• Stronger in red than in blue

• Dead columns

• Non uniform dark current

• (e.g. heating by the amplifier)

All that can (needs to...!) be corrected

during data reductions.

(Flat Fielding!)

Geometric

Distortion

HST/ACS/WFC - a

severe case of distortion

- more than 200 pixels at

the corners. Large skew.

Cameras normally have

some distortion, typically a

few pixels towards the

edges,

It is important to understand

and characterise it to allow it

to be removed if necessary,

particular when combining

multiple images.

Distortion may be a function

of time, filter and colour.

Due to optics, not CCD!

Characterising CCD detectors

• Quantum efficiency (QE): Can be as high as

90% in visible wavelengths for the best detectors

today. Specific treatments to improve blue (or

red) response.

•Resolution/pixel size: typical pixel sizes from

10 to 30 microns. For the images to be properly

sampled, there must be at least two resolution

elements per PSF (point spread function), and

better three... otherwise the images are

undersampled.

Characteristics of CCD’s (II)

• Dynamic range/full well capacity/saturation level.

• Around 105e-. Close to saturation level, non-linearity effects start to show up.

• It’s important to choose an exposure time short enough so that objects of interest are not saturated! (But long enough so you are sky-noise limited).

• Multiply exposures to be able to remove CR !

• Even in the absence of illumination, CCDs produce a thermal signal or ‘dark’ current.

Measure during bad weather...

Sources of noise in CCD observations

• Dark current

• Even in the absence of illumination, CCDs produce a signal or ‘dark’ current. Typical values are ≤ 10 e- /hr if cooled to ~ -140° (LN)

• Readout noise

• This is an electronic noise (amplifier, or else), usually quoted in electrons per pixel. It does not depend on exposure time.

• Photon noise (object, or sky)

• Photon noise follows a Poissonian distribution (counting statistics): σ = √n

• For bright objects, object photon noise dominates

• For faint objects, the photon noise from the sky dominates. Sky background increases at longer and longer wavelengths.

• In order to avoid being dominated by read noise, CCD exposures should

be long enough to accumulate enough counts in the sky background to

be sky noise dominated. Usually difficult in spectroscopy !!

Sky background

Night sky from Paranal • Moonlight is yellow, so better to observe in redder

bandpasses near the full moon

• At longer wavelengths airglow lines cause significant

variations in sky brightness

The CCD equation

• Object Signal: Sobj = E* D2 Δλ η τ t

• E in ergs/cm2/s/Å or W/m2/Å, flux from object

• D Diameter of telescope, Δλ (bandpass), η (quantum efficiency), τ (transmission), t exposure time

• Total signal: Stot = (E* + (2)Esα2) D2Δλητt + dark. t + n2R2

• (α seeing, n number of pixels corresponding to α)

Astronomical

Source

Sky

background Dark current

Read noise

Total counts

per pixel, in

electrons

N(oise) = square root of total signal

Carefull! if calculation made in ADU or in electrons, or in photons...

per pixel, or per total area of object!

A rough calculation of signal to noise

• Usually, Dark Current is negligible

• We assume the read-out noise is negligible also

• IF object brighter than sky, then:

• S/N = [ (E* . D2Δλητt ]1/2 (~ independant of seeing)

• and Limiting magnitude Elim is ~ (S/N)2 1/ [D2 Δλητt]

• goes as 1/D2 or 1/t for a given S/N

• IF object fainter than sky, AND r.o.n. negligible, then:

• S/N = E* . D/α. [Δλ η τ t /Ec]1/2 or:

• Limiting magnitude: E* = S/N . α/D . [ES / (Δλ η τ t)]1/2

• Goes as 1/D, or 1/√t only

• and Seeing is as important as diameter of telescope...!

• This explains the performance of the HST despite its only 2.4m diameter.

“How long should I integrate for” ??

• You use the above equation...but you have to know the parameters!!

• Most observatories will offer “exposure time calculators” which will allow you to

estimate how long to integrate to reach a given S/N

• But you need some critical eye...input parameters can be wrong, software have

bugs, etc...so always have a rough check with the above equation yourself.

• But if you have (or can get) real data taken with the same instrumental setup, it’s

almost always better to use this, and to scale it up to your particular application.

• In practice, CCDs have finite “full well capacity” and the non-zero sky background

means that integrating infinitely long is impractical (images would saturate on the

sky). Also detectors have bad pixels / columns, so it is in general better to take

several shorter exposures which are then dithered or offsetted on the sky and

which can then be combined afterwards. This also helps to remove C.R.

Important to choose large enough dithers to overcome detector defects.

• This is however only practicable for imaging, not always for spectroscopy......

CCDs and CCD mosaics

The next generation of large mosaic detectors...

Image Area Image Area (Architecture unchanged)

Serial register Serial register {

Gain register

On-Chip

Amplifier

On-Chip

Amplifier

The Gain Register can be added to any existing design

Conventional CCD EMCCD

Electron Multiplying CCDs.

On-Chip

Amplifier

CCD60 128 x 128 CCD87/97 512x512 CCD201 1K x 1K

Image Area Store Area

Nor

mal

Seri

al r

egi

ster

Multiplication register

Multiplication

registe

r

Multiplication register

Standard MOSFET amplifier

1e- in

1000e- signal out

Avalanche multiplication takes

place in Multiplication Register,

using an HV clock (40-45Volts).

Devices used :

Electron Multiplying CCDs.

52

0 m

ultiplication stages

Multiplication Noise

EMCCD Photon Transfer Plot

The EMCCD multiplication process increases the Poissonian noise in the image

Electron Multiplying CCDs.

Benefits : 1) Negligible read noise, therefore capable of seeing single photons 2) Read noise independent of read-out rate Disadvantages : 1) At present only available in small formats. 2) Suffer from ‘Multiplication Noise’ that limits performance at high signals.

Applications : Low signal regimes where detector read noise is the limiting factor. This could be an intrinsically faint source or a brighter source observed at very high frame rates. -> Adaptive optics wave front sensing -> High time resolution spectroscopy

QUCAM2 : an EMCCD camera on ISIS.

1k x 1k pixel image area. 3.2second full frame read out. Frame Transfer design

Superconductive Tunnel Junction

• ESA tests (M. Perryman, 2009)

• Charge proportionnal to the

incoming photon energy

• R (spectral resolution) limited

by the statistics of the generated electrons (R ~ √E , a few 10)

• Working at very low

temperature, in photon-counting

mode

• Tests made at the WHT

• Developing a 2D array, and

searching for “ higher” T

semiconductor material:

S-Cam, 10 x 12, ESA 1m, R~15

(Martin et al. 2006)

Photon Energy

R

40

Image courtesy of J. Allington-Smith (CfAI - U. of Durham)

Photonic Multi-object spectroscopy ?

Use of photonic lanterns

to transfer multi– into single-- mode fibers (p=V²/4, V=kₒ a sinθ) (kₒ=2π/λ)

41

The PIMMS instrument concept

J. Bland-Hawthorn et al,

Proc. SPIE 7735, 77350N (2010)

The photonic integrated multimode

micro-spectrograph (PIMMS)

Optical/NIR Microwave Kinetic

Inductance Detectors

Rupert Dodkins University of Oxford

DARKNESS 10,000 pixel

MKID array ARCONS 2024 pixel

MKID array

MKID’s

Operating Principle

Incident photons briefly change the total

inductance of superconductors through the

Kinetic Inductance effect

1 MKID pixel

(microresonator)

Optical/NIR MKIDs

MKIDs background: 2/3

Resonant frequency

(and amplitude) shifts

P. Day et al., Nature 2003

Specifics of IR detectors

• The thermal background could rapidly

saturate the detector…thus separate

the detection area from the reading

area.

• In the near-IR (λ <~ 2.5 µ), one uses

Hg-Cd-Te (variable proportions)

• For longer wavelengths, material

changes (InSb, SiGa, GeGa, etc…)

• In the thermal IR, necessity of rapid

read-out, and wobbling (background

subtraction: the background is much

more important than the signal, and

can change rapidly)

Various IR detectors

Hg (1-x) Cd (x)Te:

-0.85-2.5μ, 2k x 2k (e.g. VISTA)

20μ pix, 78 ᵒK

-0.6-5.3μ, 18μ, 37 ᵒK, (JWST)

InSb

0.6-5.5μ, 2k x 2k, 25μ, 32 ᵒK

SiAs (IBC)

5-28μ, 1k x 1k, 18μ, 8 ᵒK, (WISE)

5-28μ, 1k x 1k, 25μ, 7 ᵒK (JWST)

JWST Detectors

Hawaii 2k x 2k MIRI 1k x 1k

End of Part I

• Questions?

Part-II: Reducing CCD observations

CCD calibration frames

• Raw images from CCD detectors are not immediately

usable for scientific exploitation but are instead

contaminated by several instrumental effects. which need to

be removed.

• Bias frame: There is a fixed offset level applied to all

data. There may also be structure in the bias. It can be

measured by examining the “overscan” region of each

CCD, or take a zero-exposure (= bias) frame.

• Dark frame: Even without any signal, a “dark current” of

a few electrons may be present. Ideally, one should take

a dark frame of the same exposure time as the real data.

• Flat field: the pixel-to-pixel sensitivity of the detector is

not constant. A uniformly (Flat...) illuminated exposure

can measure this. Flat-field is wavelength dependent.

• Fringe frame: Thinned CCDs do produce interference

fringes at longer wavelengths. The amplitude and

separation of the fringes can be time-dependent, making

it difficult to remove them (night-sky variations...)

Megacam data with badly

removed fringe pattern

Typical CCD pre-reduction steps

• Subtract bias or overscan

• Master bias can be computed from median of many frames. The “overscan”

region can be used to compute the bias level

• Subtract dark frame

• Master dark frame should be computed from many observations of several

tens of minutes scaled up to the appropriate exposure time

• Divide by twilight or dome flat-field (filter dependent; imaging only)

• Dome flat-fields are almost always not flat enough for wide-field cameras.

• Sky flats are time limited...the best is to use “super-flats” (imaging only)

• Make sure that there are enough counts in the flat-fields so they are

effectively sky-noise limited.

• Subtract sky flat / fringe frame

• At each stage in the reductions you should verify that the noise per pixel in the

individual frames decreases. It should approach the Poisson limit.

• If the reduction steps add noise, then you are doing something wrong!

Other calibration frames you may need

(for imaging)

• A bad pixel mask is computed from a

single image and identifies where the

stuck pixels, bad columns and cosmic rays

and satellite trails are in each image.

• A weight map or coverage map which is

computed from the normalised flat-field.

• The weight map is necessary to compute

magnitude errors and detection thresholds

correctly in a stacked image. Weight maps

are less important for single detector

cameras.

• Not all sections of the image will receive

equal exposure time (vignetting..., shutter

problems, etc...)

Megacam single image weight map (flat-field +

bad pixel mask + cosmic ray mask)

FITS: the standard for astronomical images

• FITS=flexible image transport system

• FITS is an architecture independent way to store and

transfer astronomical data

• Simplest FITS file consists of a primary header

comprising of n(36x80) ASCII characters followed by

binary data

• FITS files can also contain tables or spectra.

• In ‘multi-extension-FITS’ there are several extensions,

which can be useful for mosaic camera data.

• topcat, ds9, fv can be used to manipulate and inspect

fits tables

Complete reduction step for CCD imaging data

• Carry out the pre-reductions described previously.

• If you have a series of images on the same part of the sky you will need to separately flux calibrate and astrometrically calibrate them.

• Images which are dithered around the sky will need to be re-aligned. For small detectors, linear shifts are sufficient; for wide-field imaging detectors interpolation and reprojection will have to be carried out

• Next the images need to be combined to produce a single, stacked image.

• The last step involves the extraction of catalogues.

• Spectroscopy: next talk !!

CCDPROC (iraf)

SCAMP (Terapix)

SWARP (Terapix) or

IMSHIFT (IRAF)

SWARP (Terapix) or

IMCOMBINE (IRAF)

Sextractor or PHOT