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KMOS Instrument Overview &
Data Processing
Richard Davies
Max Planck Institute for Extraterrestrial Physics
 What does KMOS do?
 When will it do it?
 What does the data look like?
 How is the data processed?
What & When?
• Phase B start July 2004
• Preliminary Design
Review May 2006
• Final Design Review
July 2007
• Preliminary Acceptance
Europe Spring 2010
• Preliminary Acceptance
Chile Autumn 2010
2m
2800kg
Science Drivers
•
•
•
Investigate the physical processes which drive galaxy formation and evolution
over redshift range 1<z<10
Map the variations in star formation histories, spatially resolved star-formation
properties, and merger rates
Obtain dynamical masses of well-defined samples of galaxies across a wide
range of environments at a series of progressively earlier epochs
need: multiplexing (large numbers of sources), NIR (optical diagnostics at z>1),
moderate spectral resolution (kinematics), integral field (mergers vs disks)
Instrumental Features
roof mirror
pick off mirror
(covered)
multiple-object cryogenic
integral field spectrograph
to K-mirror & filter wheel
• R~3500 spectroscopy at
0.8-2.5m
• 7.2arcmin patrol field
• 24 robotic pickoff arms,
each with a 2.8”×2.8” FoV
sampled at 0.2 arcsec
• IFUs are consolidated in
groups of 8
• each set feeds one of 3
identical spectrographs
Instrumental Features
• 24 arms in 2 layers, 20mm above & below focal plane
• positioning within 0.1” (<60μm)
• mass ~4.5kg each
• size ~30cm
• each path has 45 optical surfaces
• in total 1080 optical surfaces and 60 cryogenic motors
Instrumental Configuration(s)
Fixed instrument configuration:
Non-configurable item
Options available
Pixel scale
0.2arcsec x 0.2arcsec
Field of View
2.8arcsec x 2.8arcsec
Observing mode
integral field spectroscopy
Spatial resolution mode
seeing limited
Instrument configuration options:
Configurable item
Options available
Filter (bandpass)
K
H
YJ
Iz
HK
1.95-2.50μm
1.45-1.85μm
0.975-1.33μm
0.80-1.15μm
1.5-2.38μm
R
R
R
R
R
~
~
~
~
~
3700
3900
3300
2800
2200
Raw Data Format
wavelength
first RTD: raw data from the 3 2k×2k detectors
spatial
position
14 pixels per slitlet
(plus a gap)
14 slitlets per IFU
8 IFUs per detector
3 detectors
IFU 1
IFU 2
Reconstructed Images
second RTD: reconstructed images for each of the 24 IFUs
either arrayed in a grid
Reconstructed Images
second RTD: reconstructed images for each of the 24 IFUs
or positioned in the 7.2’ patrol field
Association Map
Templates & Recipes
calibration templates & recipes:
KMOS_spec_cal_dark
KMOS_spec_cal_calunit
KMOS_spec_cal_skyflat
KMOS_spec_tec_verticalslit
KMOS_spec_cal_wave
KMOS_spec_cal_std
kmo_dark
kmo_flat
kmo_illumination
kmo_spec_align
kmo_wave_cal
kmo_std_star
science templates & recipes:
any acquisition frame
kmo_rtd_image
KMOS_spec_obs_nodtosky
KMOS_spec_obs_stare
KMOS_spec_obs_mapping
kmo_sci_red
note: reconstruction
works on 1 IFU at a
time (i.e. in effect
recipe runs 24 times
for each data set).
other Recipes
• Modular design also useful to observer when re-processing
their data back home
Basic Tools used in
recipes:
More Complex Tools
used in recipes:
Additional (Advanced) Tools:
kmo_create_cube
kmo_set_value
kmo_arithmetic
kmo_stats
kmo_copy
kmo_rotate
kmo_shift
kmo_flip_axis
kmo_euro3D_convert
kmo_reconstruct
kmo_make_image
kmo_extract_spec
kmo_combine
kmo_sky_mask*
kmo_sky_tweak*
kmo_bkg_sub*
kmo_fit_profile
kmo_cosmic*†
kmo_extract_pv*
kmo_fit_continuum
kmo_extract_moments*
kmo_convolve
kmo_median
kmo_voronoi*
* = prototype version in use for SINFONI data
† = based on ‘L.A.Cosmic’ by P. van Dokkum
Recipe Hierarchy
What KMOS will & won’t do
Things we will do (and think are a good idea)
 keep everything modular so astronomers can add in their own extra
processing steps or leave some out
 provide basic tools so astronomer can manipulate their datacubes
 provide some more advanced tools to extract information from a datacube
(e.g. emission line kinematics, Voronoi binning, etc)
Things we won’t be providing
 a 3D data viewing tool (since there are already many good ones,
e.g. QFitsView)
 tools for deconvolution, line deblending, extracting stellar kinematics,
etc (because they’re very user/data/model dependent)
 mosaicing tool – it will be possible to combine datacubes with the right
offsets to make a larger field, but no scaling/background
adjustments will be made