aaaffiliationtext: Advanced Instrumentation and Technology Centre, Research
School of Astronomy and Astrophysics, Australian National University,
Canberra, ACT 2611, Australiabbaffiliationtext: Research School of Astronomy
and Astrophysics, Australian National University, Canberra, ACT 2611,
Australiaccaffiliationtext: Australian National University Institute for
Space, Australian National University, Canberra, ACT,
Australiaddaffiliationtext: University of Rennes 1, Rue du Thabor, 35000
Rennes, Franceeeaffiliationtext: Instituto de Astrofísica de Canarias, E-38205
La Laguna, Tenerife, Spainffaffiliationtext: Universidad de La Laguna, Dpto.
Astrofísica, E-38206 La Laguna, Tenerife, Spainggaffiliationtext: ARC Centre
of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Canberra,
ACT 2611, Australia

figure table

# Emu: A Case Study for TDI-like Imaging for Infrared Observation from Space

Joice Mathew  James Gilbert  Robert Sharp  Alexey Grigoriev  Adam D. Rains
Anna M. Moore  Annino Vaccarella  Aurelie Magniez  David Chandler  Ian Price
Luca Casagrande  Maruša Žerjal  Michael Ireland  Michael S. Bessell  Nicholas
Herrald  Shanae King  Thomas Nordlander

###### Abstract

A wide-field zenith-looking telescope operating in a mode similar to Time-
Delay-Integration (TDI) or drift scan imaging can perform an infrared sky
survey without active pointing control but it requires a high-speed, low-noise
infrared detector. Operating from a hosted payload platform on the
International Space Station (ISS), the Emu space telescope employs the
paradigm-changing properties of the Leonardo SAPHIRA electron avalanche
photodiode array to provide powerful new observations of cool stars at the
critical water absorption wavelength (1.4 $\mu$m) largely inaccessible to
ground-based telescopes due to the Earth’s own atmosphere. Cool stars,
especially those of spectral-type M, are important probes across contemporary
astrophysics, from the formation history of the Galaxy to the formation of
rocky exoplanets. Main sequence M-dwarf stars are the most abundant stars in
the Galaxy and evolved M-giant stars are some of the most distant stars that
can be individually observed. The Emu sky survey will deliver critical stellar
properties of these cool stars by inferring oxygen abundances via measurement
of the water absorption band strength at 1.4 $\mu$m. Here we present the TDI-
like imaging capability of Emu mission, its science objectives, instrument
details and simulation results.

###### keywords:

Infrared sky survey, Cool stars, Space instrumentation, SAPHIRA infrared
detector, Time-Delay-Integration

*Corresponding author<EMAIL_ADDRESS>
##  1 Introduction

Even though M-dwarfs are the most abundant stars in our Galaxy[1], relatively
little is known about their make-up (i.e., their abundance patterns of
elements heavier than Hydrogen and Helium) because of their intrinsic
faintness, cool temperatures ($T_{\rm eff}$ $\lesssim$ 4,000 K), and complex
atmospheres. Their low photospheric temperatures result in a stellar spectrum
that contains overlapping atomic and molecular absorption, making meaningful
measurement of bulk stellar metallicity challenging—let alone key elemental
abundance patterns. This complexity makes for a highly degenerate problem,
rendering it difficult to uniquely determine a set of stellar parameters to
describe a given star, something routinely done for Solar-type stars. In such
cool stars properties like temperature ($T_{\rm eff}$), the bulk metallicity
([M/H]), and elemental abundances like [O/H] and [C/H] all prominently affect
the large-scale shape of the observed spectrum and greatly complicate the use
of traditional analysis techniques.

Most of the dominant molecular absorbers in cool atmospheres contain Oxygen
(e.g. TiO in the optical; H2O and CO in the near-infrared) where, in chemical
equilibrium conditions, the amount of Oxygen-free to form such molecules is
sensitive to the Carbon abundance through the formation of energetically
favourable CO [2, 3]. The observational consequence of this is that both
Oxygen and Carbon—elements difficult to measure on their own—have an out-sized
impact on the shape of a spectrum and greatly affect the ability to reliably
measure stellar metallicity [3].

The ability to reliably measure Oxygen would thus aid in resolving this
degeneracy and help to unlock the chemistry of the most common kind of star.
To this end, one particular wavelength region of interest is the H2O band at
1.4 $\mu$m. Unfortunately, this region is exceedingly challenging to observe
from the ground due to moisture in our atmosphere[4, 5]. However, space-based
observations show tremendous promise in opening this unique window into the
physics of stellar atmospheres of cool stars.

The International Space Station (ISS) provides a unique platform to perform
life, physical, Earth, and space science research and technology development.
The ISS, being a science platform, provides all of the resources that a
scientific instrument would expect from an Earth-like laboratory such as
power, cooling, data, and communication needs. The ISS external payload
platform provides a new opportunity to realize space missions extraordinarily
fast and of low cost in comparison to traditional research conducted on-board
the ISS. It provides the flexibility to be replaced with different instruments
or, in some cases, brought back to the Earth. The experiments on these
platforms can fit into short-term funding cycles available on national and
multi-national levels. External payload accommodations are available on the
“Expedite the Processing of Experiments to the Space Station” (ExPRESS)
Logistics Carrier (ELC), “Japanese Experiment Module-Exposed Facility” (JEM-
EF) and the“Columbus-External Payload Facility” (Columbus-EPF) of the ISS[6].
The commercially available external platforms for small payloads include
NanoRacks External Platform [7] (operational from 2016) attached to JEM and
Bartolomeo platform [8] attached to Columbus Module, which is operated by
Airbus Defence and Space. Emu leverages these emerging cost-effective and
reduced mission risk platforms to perform the infrared sky survey, along with
key detector technology demonstration in space.

The Emu mission will undertake its near-infrared sky survey in a band centred
on 1.4 $\mu$m (Emu $W$-band or $W_{\rm E}$) as well as in $J$ band (for cross-
calibration) as a method of estimating oxygen abundance in the atmospheres of
cool stars down to a magnitude mH(AB) $\leq$ 12.5. Emu is a compact wide-field
photometer destined for a 6-month mission on the exterior of the ISS. The Emu
payload conforms to a 6U CubeSat form factor and employs “noise-free” SAPHIRA
infrared detector array[9], and will perform Time-Delay-Integration (TDI) like
imaging from the ISS[10]. The ISS presents a novel platform for a survey
instrument, due to its precessing orbit. It follows that a high-speed imager
with a $1.2^{\circ}$ diagonal field of view (FOV) toward the zenith can map
the sky without active pointing. Therefore, it demands that stars do not
traverse more than one pixel per readout, to avoid smearing. These frames are
then shifted, aligned, and stacked to produce a continuous strip with an
effective exposure time equivalent to the full transit time of the array. Emu
will also demonstrate the near-infrared TDI-like imaging capability of SAPHIRA
in space, which can play a crucial role in future missions such as GaiaNIR[11,
12, 13]. Emu is in the early phase of development and the conceptual design of
the instrument has been completed (at the time of writing). The launch has not
been finalised yet and we are exploring different opportunities to fly this
mission. Critical hardware and subsystems for the mission are being developed
and validated.

###  1.1 TDI-like imaging

TDI or ‘drift scan’ imaging is an electronic scan technique, based on the
concept of the accumulation of cumulative exposures of the same object as it
is moving across the field of view[14]. One of the major telescope facilities
that use the TDI imaging technique is the Sloan Digital Sky Survey (SDSS)
telescope located at Apache Point Observatory[15]. While the CMOS readout
architecture of the Leonardo eAPD precludes conventional TDI imaging
operations, the low effective readout noise of the eAPD (when operated with
avalanche gain) means that quasi-TDI observations can be implemented
effectively by reading the full array at the pixel crossing time and shifting
and stacking images (without avalanche gain, conventional CMOS readout noise
levels would result in a highly read noise limited final observation, with
little to no sensitivity). The major advantage of TDI mode operations is the
avoidance of the need for a beam steering and stabilization tracking mirror.
Conventional CMOS array operations would require the incoming field to be
stabilised onto the focal plane array for the full integration time. This
requires a complex (assumed open-loop) control system, and also introduces
additional demands on image stability and sensitivity variation across the
tracked field. The use of a tracking mirror system would, however, likely
relax requirements on full-field static distortion and reduce the intermediate
data rate. TDI will require considerable parallel onboard data processing to
reduce the value-added frame data volume.

##  2 Scientific Background

The metal content of a star, often referred to as its ‘metallicity’ or [M/H],
is used to describe its chemical composition and refers to the relative amount
of material other than Hydrogen and Helium. Chemical composition—both in terms
of the bulk metallicity and individual elemental abundances—is one of a star’s
fundamental properties (alongside mass, age, and angular momentum), and the
measurement of which has been a critical component of stellar and Galactic
astrophysics for many decades now. There are now many hundreds of thousands of
stars with measured metallicities and elemental abundances in massive
spectroscopic surveys like GALAH[16] and APOGEE[17] but, despite their
prevalence, most of these aren’t M-dwarfs. Indeed, GALAH has a temperature cut
around $\sim$ 4,000 K below which it doesn’t produce stellar parameters as
spectral models become increasingly unreliable and the determination of a
unique set of stellar parameters increasingly challenging.

In the field of stellar astrophysics, the Iron abundance [Fe/H] is commonly
used as a proxy for the stellar bulk metallicity. Iron can be reliably
measured in Solar-type stars, and it typically serves as the entry point for
investigations into stellar chemistry or galactic chemical evolution,
especially when paired with other elemental abundances or stellar properties
like age. However, Iron can be difficult to measure accurately in the
atmospheres of cooler stars like M-dwarfs [18, 19, 20, 21, 22, 23, 24], where
metallicity-abundance degeneracies paired with model limitations pose
substantial barriers. In M-giant stars, the problem becomes worse because of
non-Local Thermodynamic Equilibrium (non-LTE) effects that become so severe
for electronic transitions that even the stellar temperature is difficult to
measure [25]. Oxygen makes up a higher proportion of the “metal” composition
of stars than iron and so is in principle more representative of the
metallicity of stars. However, its atomic abundance is much harder to measure
[26]. It has few spectral lines; the permitted high excitation OI triplet
(0.7771 - 0.7774 $\mu$m) is affected by non-LTE and inhomogeneities in solar-
type and cooler stars, while the extremely weak forbidden lines [OI] at 0.6300
$\mu$m and 0.6363 $\mu$m require high sensitivity and high-resolution
spectroscopy to separate them from the forest of transitions associated with
other elements and is not practical in M stars.

Figure 1: Top: Earth’s atmospheric transmission compared to the 2MASS $J$ and
$H$ bands[27], as well as the proposed Emu $W$-band. Note that it is not
possible to effectively observe the region between $J$ and $H$ from the ground
due to water absorption (Green box in the top panel), thus demonstrating the
strength of Emu. Bottom: MARCS model [28] synthetic spectra for two M dwarfs
in the same wavelength region, one with $T_{\rm eff}=2700\,$K and [Fe/H] =
0.0, and the other with T${}_{\rm eff}=3600\,$K and [Fe/H] = -1. Note how the
targeted wavelengths demonstrate different [Fe/H] sensitivities as compared to
the adjacent $J$ and $H$ bands, useful in constraining stellar parameters.
Figure 2: A synthetic color-color diagram shows the ability of the Emu $W_{\rm
E}$-band photometry (the data product from our all-sky survey) to measure
stellar metallicity. Tracks show the zero-age stellar main sequence for cool-
stars (2700 $\leq$ $T_{\rm eff}$ $\leq$ 4000 K, in steps of 100 K) at the
indicated [Fe/H] metallicity with all elemental ratios such as [O/Fe] fixed to
Solar values. Note how the use of a $J-W$ colour enables the separation of the
stars into distinct metallicity sequences, demonstrating the power of the Emu
$W_{\rm E}$-band. The $i-Ks$ colour on the X-axis is a proxy for stellar
temperature (with some dependence on [Fe/H]), with the $J-W$ colour plotted on
the Y-axis being primarily sensitive to [Fe/H].

The strongest water absorption feature in the coolest ($<$ 3000 K) stars is at
2.7 $\mu$m. Observation at this wavelength is challenging due to the high
thermal background. The strongest absorption feature that can be readily
accessed is between the astronomical $J$ and $H$-band windows at 1.4 $\mu$m.
Its measurement from the ground is challenging due to the dominance, and rapid
variability, of the water absorption column in the Earth’s atmosphere and the
wide field of view required to provide sufficient reference stars for a
differential calibration. Space-based observations are therefore desired. The
$W_{\rm E}$-band centre is at 1.4 $\mu$m with a bandwidth of 0.15 $\mu$m. The
band is strongest in the atmospheres of the coolest stars ($T_{\rm eff}$ =
2700 K is adopted as a functional limit based on currently available model
atmosphere data) and weakest in warmer stars (with $T_{\rm eff}$ = 4000 K
adopted as the functional upper limits for cool stars). The band strength is
also dependent on the relative abundance of heavy elements in the star. Emu
will measure the water abundance by comparing the observed flux of stars in
the Emu $W_{\rm E}$-filter to the expected flux predicted based on broad-band
photometric values available in the literature.

The Emu $W_{\rm E}$-band provides an improved indicator of the underlying
oxygen abundance than other broad-band filters (which blends complex
metallicity signatures) as the dominant molecular absorber at 1.4 $\mu$m is
H2O. Compare this to the optical, where there is a larger contribution from a
much greater range of sources: from atoms, as well as molecules such as oxides
(e.g. TiO, VO, ZrO), and hydrides (e.g. MgH, CaH, SiH), which all contribute
to the complex metallicity and abundance signatures. Two example synthetic
spectra are shown in Fig. 1, showing the variation in the water absorption
strength for two temperature and metal abundance levels. The synthetic
spectrum of a warm (shown in blue, effective temperature, $T_{\rm eff}$ = 3600
K) low-metallicity M-star is shown compared to a cooler star with higher
metallicity (shown in red). The Emu $W$-filter band, indicated by the green
lines, straddles the strong water absorption band in both cool stars, but with
significantly more absorption in the higher metallicity source. O is fully
condensed into H2O in dwarf stars at solar metallicity 3000 K or in giant
stars at 2000 K[29]. For near dwarfs with $T_{\rm eff}$ below 3300 K, the
depth of water features are therefore more of a measure of [O/H] than $T_{\rm
eff}$. A representative Earth’s atmospheric transmission spectrum (for ground-
based astronomy111Infrared spectra of the atmospheric transmission above Mauna
Kea are shown here- https://www.gemini.edu/observing/telescopes-and-
sites/sites) is also shown, as are the canonical and widely used $J$ and $H$
band astronomical filters[30]. The water absorption in the Earth’s atmosphere
hinders these observations from being performed with ground-based
telescopes[5]. A full statistical analysis, using all available photometric
data will of course underpin the measurement of stellar abundance using the
$W_{\rm E}$-band. However, a simple color-color diagram (photometric intensity
ratios in different filter bands) demonstrates the power of our unique Emu
$W_{\rm E}$-band for determining stellar atmospheric abundance (Fig. 2) across
a wider range of stellar parameters. A star’s location in the color-color
space made available by the $W_{\rm E}$-band provides a probe of the
atmospheric water content, and hence oxygen abundance, free from the
degeneracies associated with other broad-band filters alone. Photometric
accuracy at the 3% level (signal-to-noise ratio $\geqslant$ 30) will provide
powerful empirical evidence for the metal abundance of the coolest stars. For
warmer atmospheres and higher metallicities, the brighter sources (with 1%
photometric errors) from the Emu survey will be used. Emu will provide
critical empirical evidence of the validity of the state-of-the-art models,
which have significant uncertainty at high metallicities and for the warmer
stars.

##  3 Instrument Overview

Emu is a 6U form factor payload to be hosted on the ISS. The instrument layout
of Emu is shown in Fig. 3.

Figure 3: The Emu conceptual model is shown. The optical elements, including the cold detector assembly and thermal management system, occupy a volume equivalent to 3U. A further 1U is required for the control system electronics. In the baseline design, a further 2U is set aside for a data mass storage system. Table 1: The Emu instrument specifications are shown here. The optimum pixel size for the Emu sky survey is $10^{\prime\prime}$. A Full-Width Half Maximum (FWHM) of 2 pixels is considered to satisfy the Nyquist sampling and this will result in a spatial resolution of $20^{\prime\prime}$ for Emu. Emu uses a low readout noise SAPHIRA detector to enable TDI-like imaging capability. SAPHIRA will be operated in a Correlated Double Sampler (CDS) readout mode resulting in a science frame rate of 25 Hz. In this mode, a Non-Destructive Readout (NDR) reset and exposure frame will be taken, which will result in a 50 Hz NDR frame rate. Emu will fit in a 6U volume and it can achieve a sensitivity around mH(AB) $\sim$ 12.5 in H band with a signal to noise ratio of 10. Instrument | NIR imager
---|---
Imaging mode | TDI-like
Field of view |  $0.71^{\circ}$ $\times$ $0.89^{\circ}$
Aperture size | 83 mm $\times$ 83 mm
Central obstruction |  $\sim$ 12.5 $\%$
Equivalent circular aperture diameter | 93.65 mm
Effective area |  $\sim$ 60 cm2
Focal length | 495 mm
Operating bands |  $W_{\rm E}$ (1.34 - 1.5 $\mu$m) and $J$ (1.17 - 1.33 $\mu$m)
Detector | SAPHIRA eAPD from Leonardo MW Ltd.
Array size | 320 x 256
Spatial resolution | FWHM = $20^{\prime\prime}$ (2 pixels)
Frame rate | 25 Hz CDS, (50 Hz NDR)
Number of field transits | 256
Effective exposure time |  $\sim$ 7.2 sec (in $W_{\rm E}$-band) and $\sim$ 2.4 sec (in $J$-band)
Limiting magnitude (single orbit) | mH (AB) $\leq$ 12.5 in $H$-band (with SNR =10)
Weight |  $\leq$ 8 kg
Dimension (L $\times$ W$\times$ H) |  $300\times 200\times 100$ mm (6U form factor)
Power |  $<50$ W

The optical system is a compact Cassegrain telescope, with a re-imaged pupil
and it will occupy 2U space. The integrated detector cooler assembly (IDCA)
system contains the cold baffle, detector, and Stirling cooler. The IDCA will
fit in a 1U unit. The IDCA holds the filters which are required to achieve the
desired passband and as well as thermal requirements. A further 0.5U is
required for the ANU “Rosella” detector readout electronics system. Rosella is
a modular and compact readout electronics system to read out the SAPHIRA
detector. In the baseline design, a further 2U is set aside for a commercially
available off-the-shelf (COTS) data mass storage system. The different
instrument parameters are shown in Table. 1. The drifts scan survey approach,
enabled by the low readout noise of the SAPHIRA detector at a high frame rate,
removes the mass and complexity associated with a conventional pointing-and-
tracking telescope. The telescope’s primary mirror will be baffled and
sufficient thermal blocking is achieved in the cold section of the instrument.
The SAPHIRA detector will be cooled to 80 K (in principle SAPHIRA can be
operated at a higher temperature, but this will cause an increase in the dark
current[31]), and while this aspect of the project presents a significant
design challenge, the power consumption and waste heat dissipation necessary
are within the scope of capabilities provided by our preferred host platform
on the ISS.

The direction of flight will be along the short axis of the detector (256
pixels) and the transverse field will be along the long axis (320 pixels).
Along with the $W_{\rm E}$-band imaging, Emu will also undertake a sky survey
in the J-band for cross-calibration of data. The simultaneous $W_{\rm E}$ and
J-band imaging is achieved by placing two separate $W_{\rm E}$ and J filters
before the focal plane. The filters will be placed such that they will be
perpendicular to the direction of flight, which would allow scanning the same
portion of the sky in both bands. $J$ and $W_{\rm E}$-band will occupy 60 and
180 pixels with an intermediate dead band of 16 pixels necessary for mounting
the filters at the focal plane ($\sim 0.4$ mm gap between filters). The
mission will operate for 6 months on the ISS with the majority of data
recorded with on-board storage for sample return, due to communication
bandwidth restrictions. We will be able to downlink $\sim$ 1 % of this data
for calibration purposes.

##  4 ISS Platform and Jitter

The ISS is maintained in a nearly circular orbit with an average altitude of
400 km, at an inclination of $\sim$ 51.6 degrees to Earth’s equator. The
orbital period of ISS is $\sim$ 92.68 minutes, with $\sim$ 15.54 orbits per
day[6]. Emu will perform the near-infrared sky survey between $+51.6^{\circ}$
and $-51.6^{\circ}$ declination during its six months of operation and thus
would scan $\sim$78 % of the total sky.

In order to understand the effect on image quality of Emu, due to ISS jitter,
we have simulated a random vibration profile from the power spectral density
(PSD) data available from the External Payloads Proposer’s Guide to the
ISS[6]. This corresponds to around 30 micro radians (RMS) in both axes of the
focal plane and less than one Emu pixel ($10^{\prime\prime}$). The ISS
platform PSD and the random vibrations (in Emu pixel scale) derived from the
PSD are shown in Fig.4. One of the missions which performed the
characterization of the ISS vibration environment is the Optical Payload for
Lasercomm Science (OPALS)[32]. OPALS is a technology demonstration for laser
communication aboard the ISS and it has been utilized for different extended
missions after its primary mission. From this experiment, the ISS jitter has
been estimated to be in 20-30 micro radians range [33]. This is in agreement
with the derived jitter from the ISS power spectral density (PSD) data.

Figure 4: Left: ISS platform PSD. Right: Random vibrations in Emu pixel scale.
Note the ISS jitter is less than one Emu pixel scale and thus it will not be a
critical noise source in the Emu data output.

Thus the ISS jitter will not be a critical noise source in the Emu data and
just be within the tolerance (FWHM= 20”). Also, the jitter does not introduce
significant rotational issues in the data; but does introduce a significant
global translation between frames. We can freeze out the vibration frame to
frame (because of fast frame readout), but they do have an impact on the image
trajectory across multiple frames of the data. Cross-correlation between
successive frames will be performed to shift and stack multiple frames
(details in Section 5).

##  5 Instrument Performance Estimates

Traditionally, TDI uses a CCD technology by shifting the electrical charge
across the detector at the same velocity as the object image to avoid
blurring. The analog of this for CMOS technology such as SAPHIRA is taking
images at a high enough frame-rate, and post-stacking them to produce
effectively long exposures. The conventional CMOS can’t work in TDI mode,
because of the high readout noise at a fast frame rate. However, the low
electronic noise of the SAPHIRA detector allows the camera to read out images
at the same rate that stars transit the image pixel (25 Hz). A series of
images is recorded as the sky crosses the static (with respect to the Space
Station) telescope field of view. The images are then aligned (using integer
pixel shifts) in post-processing and stacked to give a composite image. The
exposure time of each frame is chosen to match the time taken for a star to
traverse one pixel on the detector, such that the next exposure will see the
same image but with everything shifted by one whole column. The frame rate is
set by the drift speed, which is $\sim$$233^{\prime\prime}$ s-1 for the ISS in
a 400 km LEO.

Table 2: Simulation input parameters Telescope effective collecting area | 55.1 cm2
---|---
Plate scale |  $\sim 416.7^{\prime\prime}$ mm-1
Optics efficiency | $\sim 0.8$
Wavelength bands |  $W_{\rm E}$ and $J$
Number of pixels in the direction of flight | 256 pixels
Number of pixels in the transverse direction | 320 pixels
Pixel size | 24 $\mu$m
Avalanche gain | 45
Effective readout noise | 0.978 $e^{-}$
Dark current | 8.4 $e^{-}$ s-1
Quantum efficiency | 0.7 in $W_{\rm E}$-band and 0.6 in $J$-band[34]
Thermal background rate | 1 $e^{-}$ s-1
Single frame exposure time | 0.04 s
Angular speed of the platform |  $\sim$$233^{\prime\prime}$ s-1

The exposure time per individual integration is then calculated from the pixel
size, $S_{Pix}$, (in units of arc seconds) and drift speed, $R_{p}$.

$\tau_{exp}=\frac{S_{Pix}}{R_{p}}$ (1)

The frame rate is given by

$\mathrm{Frame}\,\mathrm{rate}\ =\frac{1}{\tau_{exp}}$ (2)

The frame rate for a $10^{\prime\prime}$ pixel based on Equation. 2 is 23.3
Hz. For simplicity, for the Emu baseline design we have considered 25 Hz frame
rate.

The full effective exposure time is then a function of the number of pixels
along the flight path of the platform, $N_{x}$

$\tau_{eff}=N_{x}\,\tau_{exp}$ (3)

A simulation has been performed to recreate the effects of the SAPHIRA
detector, ROSELLA electronics, optical elements, background noises, ISS
vibrations, TDI-like imaging, and stars. The different input parameters to
simulate Emu mission data are shown in Table. 2. The simulation input
parameters provide high flexibility and would allow simulating similar TDI-
like mission (for example, GaiaNIR mission - see Section 13 for more details).

The thermal background at the focal plane is another input parameter which is
discussed in section 11. Orbital and spacecraft platform parameters for the
simulation consist of the angular speed of the ISS and the data on vibrations
on the ISS external platform (discussed in section 4). To simulate the star-
field we have used the 2MASS star catalog data[35].

The different processing steps and logical flow of the simulator is
schematically shown as a flowchart in Fig. 22 (see section 15). The SAPHIRA
operates on correlated double sample (CDS) readout mode over the full array
with a resulting science framerate of $\sim$ 25 Hz. In this process Non-
Destructive Readout Zero (NDR0) frame or reset frame will be generated
followed by an exposed frame or Non-Destructive Readout One (NDR1) frame. Each
of these frames requires two readouts (one after reset and one after exposure)
that are differenced to produce a CDS science image.

In order to simulate the vibrations on the ISS external platform, a random
vibration profile is generated as mentioned in Section 4 and it is then added
to the trajectory. Based on the resulted trajectory coordinates, a region of
interest (ROI) is selected from the 2MASS star catalog[27]. From this ROI, the
stellar coordinates and magnitude data are extracted for stars that would fall
in the Emu FOV. In order to add these selected stars to the frame, a
coordinate transformation is applied to convert the world coordinates to pixel
coordinates.

In this simulation 2MASS, $J$, and $H$ band magnitudes are used to simulate
the flux of stars. The 2MASS $J$ and $H$-band Vega-based magnitudes are
converted to the AB system using the Equation. 4 and 5

$M_{AB}=J-0.91$ (4)

$M_{AB}=H-1.39$ (5)

where MAB [36] is defined in SI unit as

$M_{AB}=-2.5\;\log_{10}(f_{\nu})-56.10\,\,\,\,\,f_{\nu}\,\mathrm{in}\,\mathrm{W}\,\mathrm{m}^{-2}\,\mathrm{Hz}^{-1}$
(6)

The energy of the photons that the telescope received can be expressed as a
function of the flux spectral density $f_{\nu}$. For the purpose of
simulation, we approximated a flat spectrum in the corresponding wavelength
band. By dividing this energy by the the energy of a photon $h\nu_{eff}$, we
can obtain the number of photons collected by the telescope for one star as a
function of $f_{\nu}$, and then, as a function of $m_{AB}$

$N_{\gamma}=\frac{E_{W}}{E_{\gamma}}=\frac{1}{h\,\nu_{eff}}\sideset{}{{}_{\nu_{1}}^{\nu_{2}}}{\int}f_{\nu}\,d\nu\,A\,T=\frac{1}{h\,\nu_{eff}}f_{\nu}\,\Delta\nu\,A\,T$
(7)

where A is the telescope’s collecting area, $\Delta\nu$ is the spectral
bandwidth of observation, T is the exposure time. By substituting the
$f_{\nu}$ expression from Equation. 6 in Equation. 7, we obtain

$N_{\gamma}=\frac{1}{h\,\nu_{eff}}\,A\,\Delta\nu\,T\,10^{\left(-\frac{m_{AB}+56.10}{2.5}\right)}$
(8)

Using Equation. 8, the number of photons corresponding to each star is
calculated. A null flux map frame is generated and each star is added as a
Poisson distribution. The thermal background photons are also added as Poisson
distribution to this flux map.

Figure 5: An example of Emu single frame with exposure time $\sim$0.04 s using
the 2MASS catalog at the Galactic anti-center. Here the blue, green and red
box represents $J$, $W_{\rm E}$ bands and dead space between the bands
respectively.  Figure 6: The image shown is a Emu $W_{\rm E}$-band data
simulation based on the current Emu baseline design and the 2MASS $H$-band
input catalogue (extrapolated to the 1.4 $\mu$m Emu W-band). This image was
produced by shift and stacking $\sim$ 1200 frames, over one orbit pass at mid-
latitude. The effective exposure time is individual pixel exposure time (0.04
seconds) $\times$ number of pixels in $W_{\rm E}$-band (180) = 7.2 seconds.
Figure 7: The image shown is a Emu $J$-band simulation based on the current
Emu baseline design and the 2MASS $H$-band input catalogue. This image was
produced by shift and stacking $\sim$ 1200 frames, over one orbit pass at mid-
latitude. The effective exposure time is individual pixel exposure time (0.04
seconds) $\times$ number of pixels in $J$-band (60) = 2.4 seconds.

In order to find the relative shift between frames due to the vibrations on
the ISS external platform, a cross-correlation between successive frames is
performed. The offset obtained from this cross-correlation is used to correct
for the relative shift between the frames. These $W_{\rm E}$-band and $J$-band
frames are then shifted (each pixel by one column, based on the TDI
technique), aligned, and co-added separately to produce a continuous strip
with an effective exposure of the time taken for a target to cross the entire
array. A weight map is also created in parallel corresponding to the number of
shifts in order to correct the exposure gradient. The shift and the co-added
frame are then divided with this white map to create the strip of the Emu
star-field. An example of a single exposure simulated frame (with $J$ and
$W_{\rm E}$ bands) is shown in Fig.5. A simulated sky strip that Emu will
deliver in $W_{\rm E}$ and $J$ bands are shown in Fig.6 and Fig.7
respectively.

To understand the sensitivity of the simulated data, we ran a source extractor
algorithm[37] on the simulated image. The source extractor algorithm extracts
the flux value and signal to noise ratio (SNR) of each star in the simulated
star-field. The extracted stars from the simulation are then cross-matched
with the stars in the 2MASS catalog, to understand the sensitivity of the
simulated star-field. Fig. 8 shows the SNR of each star in the simulated sky
strip. To estimate Emu $W_{\rm E}$-band sensitivity we used 2MASS $H$-band
data assuming a flat spectrum source. It is clear from this figure that a
limiting magnitude of $m_{AB}$ = $\sim$ 12.4 ($H$-band) and $m_{AB}$ = $\sim$
12.6 ($J$-band) can be detected with an SNR of 10 with the Emu sky survey. The
simulation shows that we can achieve the necessary sensitivity without a
pointing and tracking system, by performing TDI from the ISS platform.

Figure 8: Left: Emu $W_{\rm E}$-band sensitivity. To estimate Emu $W_{\rm
E}$-band sensitivity we used 2MASS $H$-band data assuming a flat spectrum
source. Right: Emu $J$-band sensitivity based on 2MASS $J$-band catalogue.

###  5.1 Cosmic Ray Event Rate

To understand the cosmic ray (CR) events experienced by Emu we have used the
data from the Wide Field Camera 3 infrared channel (WFC3/IR) on the Hubble
Space Telescope [38]. The WFC3 IR detector is a HgCdTe 1024 $\times$ 1024
array, with 18-micron pixels. As per the WFC3 instrument handbook [39], the
WFC3/IR camera has a CR event rate of 5 events/second/camera. The WFC3/IR
detector area is 3.39 cm2 and this corresponds to 0.68 events/second/cm2. For
SAPHIRA, the detector area is 0.472 cm2. And this will result in a CR event
rate of 0.32 events/second for Emu. At 25 frames/second frame rate, this
corresponds to 0.012 events/frames. This implies that the CR event rate has a
little direct impact on Emu observations. However, the tolerance of SAPHIRA to
such events is as yet unknown (indeed this is an important technical
demonstration goal of the Emu mission), as are the implications for the
control system electronics.

##  6 Optimum pixel size for the mission

For the Emu mission, a critical mission parameter is the selection of pixel
size. A larger pixel size provides a wider field of view for a detector with a
fixed number of pixels as well as leads to a greater TDI crossing time (hence
increased integration time). This is important for sensitivity and frame to
frame alignment. However larger pixel size would also increase the potential
for source confusion (multiple sources in a single pixel). The optimum pixel
size is depending upon the field alignment requirement for the single frame as
well the confusion limit of the co-added frames.

Figure 9: Left: Stellar density at the Galactic anti-centre. Right: Stellar
density at the Galactic North pole. The stellar density information is used to
estimate the probability of more than three stars in Emu field of view and to
estimate the confusion limit. Figure 10: Probability of more than three stars
in a single frame field of view at the Galactic anti-centre (left) and the
Galactic North pole (right). A pixel size greater than or equal to
$10^{\prime\prime}$ is required to satisfy the minimum 3 stars per frame
condition for alignment purposes. Figure 11: Probability of more than one star
in photometric aperture at the Galactic anti-centre (left) and the Galactic
North pole (right). With the $\sim$ $5^{\prime\prime}$ pixel, the probability
of more than one star in photometric aperture is high at the Galactic anti-
centre, a $10^{\prime\prime}$ pixel is optimal.

To perform alignment between different frames, it is required that every
single frame has three or more guide stars detected to a significant level.
The point spread function (PSF) of the final stack of the image ($PSF_{Out}$)
should be blurred by no more than 10 % of the input PSF ($PSF_{In}$) for an
individual frame.

Centroid error in terms of Full Width Half Maximum (FWHM) and Signal to Noise
Ratio (SNR) can be expressed as,

$\displaystyle\begin{aligned} \sigma(centroid\;error)=\frac{FWHM}{SNR}\,,\\\
\end{aligned}$

and FWHM is,

$\displaystyle\begin{aligned} FWHM=2.35\times\sigma(PSF_{In})\end{aligned}$

So centroid error can be expressed as,

$\displaystyle\sigma(centroid\;error)=2.35\times\frac{\sigma(PSF_{In})}{SNR}\,,$
(9)

The output PSF would be 110 % of input PSF and it can be expressed in terms of
its standard deviation ($\sigma$) as,

And also,

i.e.

$\displaystyle{\sigma(centroid\;error)}^{2}=({1.1}^{2}-1)\times{\sigma(PSF_{In})}^{2}$
(10)

By substituting Equation. 9 in Equation. 10, we will get,

$\displaystyle\begin{aligned} SNR\sim 5\end{aligned}$

From this analysis, it can be estimated that a SNR of $\geq$ 5$\sigma$ is
required to limit the output PSF blur to less than 10 % of input PSF.

This implies guide stars’ magnitude in every single frame should be at least
10 mag (2MASS $H$ (Vega)). So to Nyquist sample the image inputs, the full
width half maximum (FWHM) is assumed as two pixels. In order to understand the
best pixel size approximate for Emu, we have assumed a fiducial reference
mission with three different pixels sizes, such as 5, 10, and 20 arcseconds.
To estimate the optimum pixel size for the mission, the stellar density was
derived empirically from representative fields at the Galactic anti-center and
the Galactic pole as extremely high and low density cases. The Galactic center
has a highly crowded stellar field, and the effect of source confusion is high
compared to other regions of the sky[40]. To reduce the effect of source
confusion we chose a sky field in the Galactic anti centre instead of the
Galactic center. The stellar density estimated using 2MASS catalog data[35] at
the Galactic-anti center and the Galactic north pole is shown in Fig. 9. The
fiducial reference values such as the Emu pixel size and photometric aperture
size (twice of FWHM) are also shown.

From the stellar density information, the Poisson probability of more than
three stars in the field of view was estimated and it is shown in Fig. 10. It
can be concluded that a pixel size greater than or equal to
$10^{\prime\prime}$ is required to satisfy the – minimum 3 stars per frame-
condition for alignment purposes. To estimate the confusion limit, the Poisson
probability of more than one star in the photometric aperture was derived and
this is shown in Fig. 11. From Fig. 10 and Fig. 11, it can be concluded that a
pixel size of $\sim$ $10^{\prime\prime}$ would be optimal for the Emu mission
(when constrained to a single SAPHIRA focal plane array).

##  7 The SAPHIRA electron Avalanche Photodiode Detector

The Emu mission concept was developed based on the groundbreaking sensitivity
of the SAPHIRA detector from Leonardo MW Ltd [41]. The SAPHIRA adds an
electron Avalanche Photodiode (eAPD) region below a traditional HgCdTe
absorption layer, as part of a hybridized assembly with a CMOS readout
integrated circuit (ROIC) with 32 parallel readout channels, each supporting a
pixel rate of up to 10 MHz. The array has 320$\times$256 24 $\mu$m pixels. The
detector is sensitive to a nominal wavelength range of 0.8–3.5 $\mu$m, with
the effective quantum efficiency in the range 2.5–3.5$\mu$m depending on the
selected avalanche gain[9]. A quantum efficiency of $>$ 60% has been
demonstrated for the SAPHIRA in Emu’s wavelength band[34].

Figure 12: The fully integrated SAPHIRA with flex cable and cryogenic
preamplifiers

The avalanche gain is tunable via manipulation of bias voltages; and provides
a near-noise-free signal gain of up to several hundred. This linear signal
amplification results in an effective readout noise contribution of $\leq$ 1
electron per pixel per CDS image pair [42]. This near-zero readout noise
regime is critical to implementing the TDI-like observation mode for the Emu
mission.

An avalanche gain of 45 was chosen for Emu to obtain a system readout noise
$\leq$ 1 $e^{-}$. Increasing the gain would reduce the dynamic range of the
system. Emu’s bright magnitude limit is 4.5 mH (AB) and this is basically set
by the gain choice of 45. The gain can be controlled by setting the readout
electronics reset voltage; thus, different modes of operation with different
gain (thus different dynamic ranges) are possible.

SAPHIRA detectors are already used in ground-based astronomical instruments
for fast wavefront sensing and fringe tracking applications[43, 44, 45, 46],
but their utility in space applications is yet to be exploited. Specifically,
their suitability for high-speed and/or photon-starved applications has
profound implications for space-based near-infrared instruments, including
TDI-like surveys of the sky from a Low Earth Orbit platform. This removes the
need for a complex fully steerable (pointing and tracking) telescope that
would add significant cost and risk to the project. This principle can also be
applied to near-infrared (NIR) and short-wave infrared (SWIR) remote sensing
Earth Observation applications.

The SAPHIRA detector has also undergone radiation testing, with a gamma and
proton radiation campaign by the European Space Agency showing no permanent
damage to the device[31]. A fully integrated SAPHIRA focal plane built at ANU
is shown in Fig. 12. One of the goals of the Emu mission is to advance the
SAPHIRA detector and ANU ‘Rosella’ control electronics to Technology Readiness
Level 9 (TRL9). The use of the ISS as the orbital platform circumvents many of
the engineering risks associated with small space missions as it removes the
need for a full free-flying satellite bus, and offers features such as active
cooling and payload return.

##  8 Rosella detector control electronics

Rosella is a high-performance detector controller for space, developed by ANU
to address the lack of space-compatible pixel digitisation options for science
grade optical sensors, which typically have no on-board analogue-to-digital
converters (ADCs).

Figure 13: Rosella electronics architecture

The Rosella system is compact and easily re-configurable for a wide range of
visible and IR CMOS detectors including the Leonardo SAPHIRA and Teledyne HxRG
family of infrared arrays. The Rosella architecture features a preamplifier
board, bias board, video board, and a timing board based on a field
programmable gate array (FPGA). The preamplifier board provides early
amplification of the detector output signals very close to their origin[47],
reducing the influence of electrical noise induced further down the signal
chain. The bias board generates accurate and stable DC voltages for the
detector, including the SAPHIRA’s variable avalanche gain bias.

Figure 14: Breadboard prototype of Rosella electronics including a commercial
FPGA evaluation board, one of two 16-channel video boards for analog-to-
digital pixel conversion, and a bias board for detector biases and clock
conditioning Figure 15: Left: Rosella engineering model ‘FlatSat’; the inter-
board connectors are temporary for testing, but will be a continuous flex
connection on the flight model. Right: Rosella 0.5 U enclosure mock-up showing
interleaved PCBs and aluminium enclosure walls; not shown are the inter-board
flex circuit connections, which bend to allow folding and unfolding of the
entire rigid-flex assembly.

The video boards host 32 analog-to-digital converters (ADC) channels for
digitising the incoming pixel stream. These devices are selected for low noise
performance. The timing board manages the entire system, including bias
configurations, clock pattern generation, ADC triggering, image processing,
and communication with an external host computer through one of several
standard protocols (e.g. Ethernet). Although the Emu mission requires a 50 Hz
frame rate, the Rosella controller has been designed with high-resolution
Earth Observation missions in mind, with frame rates approaching 1 kHz. A
breadboard prototype of Rosella (Fig. 15) has been successfully demonstrated
on-sky at the ANU 2.3 m Telescope.

Rosella’s final version will occupy a volume of approximately 0.5 U,
comprising a connector-less printed circuit board (PCB) assembly based on
rigid-flex technology. Each rigid PCB section features an outer thermal
conduction region that interfaces with an aluminium wall that forms a
contiguous and enclosed board stack by folding the flex circuit sections. The
enclosure also provides light-tightness for payloads sensitive to infrared
emission (thermal ‘glow’). Fig. 15 shows a ‘FlatSat’ engineering model of
Rosella and a mock-up of the PCB and enclosure assembly.

##  9 Integrated Detector Cooler Assembly

The Integrated Detector Cooler Assembly (IDCA) system contains the cold
optics, detector, cooling system, and mount. It is required to maintain the
detector and cold optics at specified temperatures to meet the instrument
performance requirements. The IDCA layout is shown in Fig. 16.

Figure 16: IDCA and cold baffle concept layout.

The assembly must also make provisions for trapping volatile contamination in
order to avoid degradation of the performance of the cold optics and detector.
The operating temperature requirement for the SAPHIRA detector is 80 K and
this will be provided by a miniature split-Stirling cooler UP8497/01 from
Thales Cryogenics. There is no Dewar, so the Stirling may work only when Emu
is in a vacuum. This means Emu can be operated only under an external vacuum.
Almost one hundred electrical wires (thin narrow tracks of the Flexible Cable)
are coming from the 80 K zone to the detector control electronics operating at
approximately room temperature. The Regenerator with the Cold Finger is a part
of the Stirling cooler. The detector (80 K) and the Cold Baffle ($\sim$ 200 K)
are mechanically held only by the Cold Finger and don’t touch any other
constructions. The Rigid-Flex PCB includes the Thin Flexible Cable (with 4
wings) and connects electrically SAPHIRA with the Pre-Amplifier PCB. The Thin
Flexible Cable has low thermo-conductivity so the total heat load to the Cold
Finger’s tip is within our miniature Stirling’s possibility to lift heat. The
metal cold baffle is a truncated 4-side pyramid glued to the rim of the
SAPHIRA package. At the tip of the Cold Finger, there are detector, Cold
Baffle, Cold Filter and mounts. The rest of the Emu subsystems will operate at
room temperature. The total mass of this assembly is around 10 grams. We have
performed vibration tests with a dummy Cold Finger and dummy mass to be sure
that the Cold Finger of our Stirling is strong enough not to crack during
launch vibrations. These vibration tests have been performed at the National
Space Test Facility, at the Mount Stromlo Campus of the Australian National
University (ANU). The qualification test was based on General Environmental
Verification Specification (GEVS) standard and yielded compliant results. The
inner truncated 4-side pyramid (metal) holds the Cold Filter and the Teflon
tube. This pyramid is glued to the SAPHIRA’s rim and gets cold from it. The
outer pyramid’s base (metal) is glued to the base of the inner one.

##  10 Optics

Emu optics have been designed such that they will have control over the
thermal background and will block the unwanted radiations from all directions,
except for light passing through the telescope pupil. This is achieved by re-
imaging the telescope’s input pupil at an intermediate pupil plane cold stop.
A cold aperture placed in this pupil image will block all the unwanted
radiation not coming through the telescope. A set of four relay lenses (Anti-
Reflection coated) are used to reimage the pupil to the cold stop and
subsequently focus the light rays on the detector focal plane. A cold filter
along with a science filter close to the detector focal plane will provide the
necessary transmission and suppression for Emu. A Deuterated Potassium
Dihydrogen Phosphate (DKDP) based filter is used as a cold filter to block
long-wavelength thermal emission (see Section. 11 for details). A ray trace of
the optical system is shown in Fig. 17.

Figure 17: The optical layout of the Emu payload. The primary mirror and
secondary mirror together act as a Cassegrain telescope and its focus is
reimaged by the relay lenses L1, L2, L3, and L4 to form a reimaged pupil at
the cold stop. The science filters along with a cold filter (F) close to the
detector focal plane will provide the required passbands for Emu.

The entrance aperture of the optical system is an 83 $\times$ 83 mm and the
system focal length is 495 mm, yielding a plate scale of
$10^{\prime\prime}$/pixel (at the 24 $\mu$m pixel pitch of the SAPHIRA eAPD
detector). The diagonal FoV is $\sim$ $1.2^{\circ}$ (Fig. 18). The mirrors
will be made from low thermal expansion Zerodur material and will be coated
with Gold for maximum reflectivity at 1.4 $\mu$m. The field lenses are of Zinc
Selenide (ZnSe) and Zinc Sulfide (ZnS) materials. The spatial resolution
requirement of the system is 2 pixels FWHM. The distortion of the optical
system is less than 0.1 %. The axial length of the optical system is around
190 mm, and this restriction is imposed by the 2U volume requirement on the
optical unit. The throughput requirement of the optical system is $\sim$ 80 %.

Figure 18: The Emu FOV. The direction of flight is along the short FOV axis,
with a diagonal FOV of $\sim$ 1.2 degree

##  11 Thermal emission analysis

Emu will be operating in $W_{\rm E}$ and $J$ bands and it will be sensitive to
the thermal emission from other parts of the instrument. This can be further
complicated by two factors: the use of the SAPHIRA detector which has
significant long-wavelength quantum efficiency in some modes of operation;
and, the likely high telescope operating temperature ($\leq$ 50 ∘C). This
results in a careful balance of operating requirements for the Emu system. We
have developed a thermal model to understand the various contribution of
thermal noise to the detector plane.

The SAPHIRA eAPD detector was originally developed for high-speed wavefront
sensing with adaptive optics systems, An application in which dark current is
not a major concern due to the high frame rate. While device characteristic
has improved in later implementation of the Leonardo eAPD detector family, the
SAPHIRA detector available to the Emu project in the early phase has a
relatively high dark current of $\sim 21$ $e^{-}$ s-1, or approximately 1
electron per Emu frame (for the flight version we will use SAPHIRA with lower
dark current $\sim 8.4$ $e^{-}$ s-1). So for the thermal analysis, a worst-
case scenario of dark $\sim 21$ $e^{-}$ s-1 current is assumed. This sets a
fiducial reference against which to develop the allowable thermal background
noise budget for Emu. It is comparable to the assumed effective readout noise
of $\approx 1$ electron per pixel derived from selecting an avalanche gain
setting that maintains sufficient dynamic range while still suppressing
intrinsic readout noise.

The thermal model for Emu assumes an uncooled telescope structure at an
equilibrium reference temperate of 50∘ C. The combined warm optical train is
assumed to have an effective emissivity of $\epsilon\leq$ 0.15 (based on
commercial grade infrared gold coatings for the two telescope mirrors and
anti-reflection coatings on each surface of the four lens elements. Science
and short-pass blocking filters are cooled to 150 K resulting in negligible
thermal emission in the $J$ and $W_{\rm E}$ bands. There is an additional
contribution (assumed unit emissivity) from the central obstruction which
occupies 12.5 % of the pupil in the current configuration. The current optical
design includes baffling for the central obstruction in the cold stop
structure, ensuring a lower emission temperature for this component. This
component is also cooled to 150 K and hence is also negligible when fully
masked. The thermal background provides a hard lower limit on the thermal
background (with equilibrium temperature and effective emissivity dictated by
external design considerations for Emu).

Figure 19: The measured DKDP filter transmission profile. It has high short-
wavelength transmission, and has good suppression beyond 2.5 $\mu$m, which is
required to realise Emu pass bands.

The Emu optical design includes an intermediate pupil image and associated
optical stop. As discussed earlier in Section 9 and Fig. 16, this cold stop is
part of the cooled detector cold baffle, and hence blocks thermal radiation
from outside the telescope pupil reaching the detector. The Cold stop modeled
to achieve an equilibrium temperature of 200 K. It remains undecided as to
whether the cold stop will be provided with occluding structure to mask the
Central obstruction, as the performance gain would be marginal due to the
current analysis.

A cold short-pass filter is required to block long-wavelength thermal emission
(from the detector enclosure and from any low transmission red leak associated
with the science filters). The design of conventional interference filters for
this role can be challenging due to the possibility of the same transmission
overtones the filter is designed to suppress in the primary science filer. A
common practice in infrared instrumentation has been to use the crystalline
material DKDP. DKDP has high short-wavelength transmission, and fine-tuning
the level of deuteration, functionally zero transmission beyond 2.5 $\mu$m can
be achieved with compromised performance in the transition region 1.8-2.5
$\mu$m, see Fig. 19 (DKDP filter transmission measurement shown here was done
at the ANU Research School of Physics using the FTIR spectrophotmeter in
vacuum mode). The DKDP filter will be mounted close to the detector (bonded to
the detector carrier plate) to provide wide angle suppression of thermal
emission. This optical arrangement is predicted to result in a thermal
background of $\leq$ 7.5 $e^{-}$ s-1 per pixel, of $\approx 0.3$ $e^{-}$ per
Emu frame at 25 Hz, with the dominant source of thermal background being the
direct thermal emission from the optical system in the longer wavelength Emu
$W_{\rm E}$-band. This will require experimental verification as is it remains
a critical performance risk for the Emu system sensitivity.

##  12 Observation Strategy

The ISS provides a novel platform for the Emu payload to perform sky surveys
in the water absorption band. A relatively wide field zenith-looking telescope
with TDI capability can perform the Near IR sky survey without active
pointing. The detector clock has to be synchronized with the transit speed of
ISS. There is a significant field overlap ($\sim$ 74 %) between observations
in adjacent orbits. This would enable to shift and stack multiple orbits of
data, thereby increasing the sensitivity of the final data product. The field
overlap is shown in Fig.20, the arrow indicates the moving direction of ISS.

Figure 20: The field overlap between successive orbits is shown. The green box
corresponds to the field of view in initial orbit and red boxes corresponds to
the field of view in the successive orbits with 0.5 s time difference

Emu’s commissioning begins soon after Emu is mounted on the ISS platform. The
duration of the commissioning period is 4 weeks and it will generate raw data
of 7.5 TB. In the first week of commissioning, Emu outgasses itself and the
detector won’t be operated. All data during this period will be downloaded. In
the next 3 weeks, the normal operation will start. The main science operation
will begin after the commissioning period. The total data generated during
this period will be around 55 TB and with at least one additional data
downlink session/week, 0.3% of the data can be downlinked. Emu will perform
the astronomical observations only in the dark portion of the ISS orbit. In
the default mode, it will acquire images at 50 Hz NDR, (25 Hz CDS pairs) and
will store the data in the onboard solid-state memory. The raw data rate of
Emu is 66 Mbits/sec and this corresponds to $>$300 GB per day. The available
downlink rate is around 1 Mbits/sec and with only one uplink/downlink session
per week available, for 8 hours. Emu has an onboard storage module with 60 TB
of solid-state memory, to store the data corresponding to six months of
operation. With the available downlink capability, we will be able to downlink
only 1% of this data to Earth for the purpose of quality control and
monitoring. The solid-state memory will be returned to Earth for post-
processing when Emu’s 6-month mission is completed.

##  13 TDI-like imaging in the context of GaiaNIR mission

GaiaNIR is a new all-sky near IR astrometry mission under consideration by the
European Space Agency (ESA) as a part of its Voyage 2050 future science
mission program. One of the significant technical challenges for GaiaNIR is
the requirement for low noise NIR detectors which can perform TDI-like
imaging[11].

Figure 21:  The image shown is a simulation for GaiaNIR like mission based on
TDI concept. Star field at the Galactic-anti center was simulated based on the
the 2MASS H-band input catalogue. Also shown is the simulated GaiaNIR concept
simulation signal-to-noise model.

Emu will be performing a TDI-like NIR sky survey using the Leonardo SAPHIRA
eAPD 320 X 256 detector array. Leonardo MW Ltd. is developing large format 2K
x 2K eAPD detector arrays and could be a potential detector for the GaiaNIR
mission. The metallicity information derived from the proposed Emu $W$-band
filter will be useful in interpreting the GaiaNIR data; since no onboard
spectroscopy is planned in the latter mission. The Emu simulation suite as
outlined in section 5, has been modified, to present TDI-like imaging
simulations relevant to the GaiaNIR mission concept. A single 2K x 2K
detector, with a pixel sampling scale 0.3′′ per pixel and an exposure time of
3.75 milliseconds per frame is assumed for this simulation. The simulation in
Fig. 21 is not an actual representative of a the GaiaIR mission, but it shows
that the Emu simulation can be modified by changing the input parameters to
analyse the sensitivity of TDI-like GAIA NIR mission based on low noise
SAPHIRA like eAPD detector arrays.

##  14 Summary

TDI-like imaging has great potential for near-infrared observations from
space, and this is possible with the low-readout noise and high-speed SAPHIRA
detectors. Emu is a proposed mission on the ISS and will demonstrate this key
capability in space along with performing an infrared sky survey in a novel
$W_{\rm E}$-band at 1.4 $\mu$m, inaccessible from the ground. The Emu survey
will provide a unique new photometric measurement which, when properly
combined in a statistical sense with the full suite of contemporary data, will
allow a wide range of questions in stellar atmospheric research to be
addressed. The measurement of the critical oxygen-to-hydrogen abundance of
both dwarf and giant cool-stars (as probed by their water absorption band)
will provide critical new empirical constraints to state-of-the-art
astrophysical models. It has the potential to advance not only our
observational understanding of the chemodynamical evolution of our Galaxy
through the study of its coolest–and most common–stars and their planets, but
will also facilitate the development of state-of-the-art stellar atmosphere
models. Combined with the revolutionary data released from missions such as
the European Space Agency’s (ESA) Gaia survey, this work enables the powerful
development of stellar atmosphere modeling. Also, this mission will be the
first in-orbit demonstration of SAPHIRA, elevating its space-readiness to TRL9
along with our Rosella readout electronics. The Emu W-band survey mission will
be the first science program to demonstrate the power of these new devices for
astronomy and science in general. The Emu mission passed its Conceptual Design
Review in May 2019 and prototyping of critical and high-risk systems is
underway.

###### Acknowledgements.

The authors pay their respect to the traditional and rightful custodians of
the land on which this project takes place: the Ngunnawal and Ngambri peoples.
We extend our respect to all First Nation people, their continuing resilience,
culture and contribution. A significant funding for the development of the
Rosella electronics system for Emu was provided by ANU InSpace. Thanks to
Patrick Kluth and Lan Fu at the ANU Research School of Physics for assisting
in the DKDP filter transmission measurement. This work makes use of data
products from the Two Micron All Sky Survey (2MASS), which is a joint project
of the University of Massachusetts and the Infrared Processing and Analysis
Center/California Institute of Technology, funded by the National Aeronautics
and Space Administration and the National Science Foundation. This work made
use of Astropy[48], SciPy[49] and NumPy[50] python packages. LC is the
recipient of an ARC Future Fellowship (project number FT160100402). MŽ
acknowledges funding from the Australian Research Council (grant DP170102233)
and support from the Consejería de Economía, Conocimiento y Empleo del
Gobierno de Canarias and the European Regional Development Fund (ERDF) under
grant with reference PROID2020010052.

##  15 Appendix

Figure 22: Flow chart of Emu simulation

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Dr Joice Mathew is an instrumentation scientist at the Australian National
University (ANU). His research interests include electro-optical payload
development, UV and IR instrumentation, systems engineering, space
instrumentation, and qualification. Joice obtained his Ph.D. in astronomical
space instrumentation from the Indian Institute of Astrophysics, Bangalore.
Before joining ANU, he worked as an instrument scientist for the Solar Orbiter
mission at the Max Planck Institute for Solar System Research, Germany.

Dr James Gilbert leads the optical detector program at the ANU Research School
of Astronomy and Astrophysics, where his group specialises in ground and
space-based focal planes and control systems. He holds a DPhil in astrophysics
from the University of Oxford and an MEng in Electronics with Space Science
and Technology from the University of Bath.

Prof Robert Sharp is an astronomer with over 20 years of experience in
delivering instrumentation for infrared, integral field spectroscopy and
multi-object spectroscopy. He is the principal investigator for Giant Magellan
Telescope Integral Field Spectrograph, GMTIFS.

Alexey Grigoriev got his Master of Science in Astronomy degree from the
Department of Physics, Lomonosov Moscow State University, in 1978. He worked
at Russian Space Research Institute for more than 40 years, creating
scientific space spectrometers (UV to thermal IR). They operated on Venus’s
surface, near Comet Halley, and in Martian orbits. He is the technical chief
of Fourier-spectrometer TIRVIM (Exo-Mars mission). Since 2018 he works as
Project Engineer at Australian National University.

Adam Rains completed his PhD in astronomy and astrophysics at the Australian
National University in 2021 and is now a Postdoctoral Researcher at Uppsala
University in Sweden. His research interests sit at the intersection of
stellar and exoplanetary astrophysics, particularly the characterisation of
low-mass stars and their planets.

Prof Anna Moore is the Director of the Australian National University
Institute for Space and Vice-Chancellor’s Entrepreneurial Professor. She was
Director of the Advanced Instrumentation and Technology Centre (AITC) from
2017-2021 and was a member of the federal government space expert reference
group to form the Australian Space Agency. She is the Chief Investigator of
the Dynamic Red All Sky Monitoring System (DREAMS). Professor Moore’s special
interests are in instrumentation, Antarctic astronomy and transient infrared
astronomy.

Aurelie Magniez is a PhD candidate at Durham University. She completed a
Master degree in Space instrumentation at Université Toulouse III in 2017 then
another in signal processing at Université Rennes 1 in 2019. Her research
interest includes instrumentation in astronomy, adaptive optics and
superconductor detectors.

A/Prof Luca Casagrande works in stellar and Galactic astronomy, focusing on
the determination of stellar parameters and the use of stellar populations to
understand the formation and evolution of the Milky Way. Among his results, he
has solved the decade long problem of firmly setting the zero-point of the
stellar effective temperature scale, and provided the first observational
evidence that stellar radial migration is responsible for broadening the
metallicity distribution of stars as a function of age.

Dr Maruša Žerjal studies young stars near the Sun and investigates their
membership in open clusters and associations based on their motions in space.
She is using spectroscopic youth indicators and stellar kinematics to
constrain their age.

Prof Michael Ireland is a Professor of Astrophysics and Instrumentation
Science at the Australian National University. He obtained his PhD from the
University of Sydney in 2006, and has since held positions at the California
Insititute of Technology, the Australian Astronomical Observatory, Macquarie
University and the University of Sydney. His research focuses on stellar
astrophysics, exoplanet formation, the search for life on other worlds and
technologies needed to support these endeavours.

Prof Michael Bessell is a Professor Emeritus at ANU specializes in the study
and evolution of stars, through spectroscopy, photometry and
spectrophotometry. A leading expert of photometric systems and their
calibration, and the temperature scale of stars, especially stars cooler than
the sun.

Nicholas Herald is an opto-mechanical engineer with 11 years experience,
working for Research School of Astrophysics and Astronomy at the Australian
National University.

Shanae King is an electronics and embedded systems engineer with experience in
the Australian space and defence industry. In 2014, she obtained a bachelor’s
degree in Systems Engineering majoring in Mechatronics, and Science majoring
in Computer Science, from the Australian National University. Her interests
lie in the application of Field Programmable Gate Array (FPGA) and related
technologies in space and satellite systems.

Dr Thomas Nordlander is a Stromlo Fellow at the Australian National University
(ANU). He previously worked at Uppsala University in Sweden, where he obtained
his PhD in 2017. His research is focused on stellar spectroscopy and in
particular the chemical composition of the oldest stars in the galaxy, as well
as cool stars, atomic properties for spectroscopy, and advanced 3D radiative
transfer.

Biographies of the other authors are not available.