From photons to catalogs Slide 2 Cosmological survey in
visible/near IR light using 4 complementary techniques to
characterize dark energy: I. Cluster Counts II. Weak Lensing III.
Large-scale Structure IV. Supernovae Two multiband (photometric)
surveys: 5000 deg 2 grizY to 24th mag AB griz 10-30 deg 2 repeat
(SNe) Build new 3 deg 2 FOV multi-CCD camera, Data management
system, improve Blanco facilities Blanco 4-meter at CTIO 2/29
11/08/2011 APS-DPF 2011 DESDM I.Sevilla Credit:NOAO Slide 3
11/08/2011APS-DPF 2011 DESDM I.Sevilla 3/29 SDSS-IIDES
Area100005000 Nb. of CCDs2262 Resolution120 Mpix570 Mpix Raw
data/night200 GB/night300 GB/night Catalog size18 TB100 TB (est.)
Total data volume60 TB4 PB (est.) Credit: Kotwani et al. (2010)
Slide 4 Transfer Process Archive Distribute 4/29 11/08/2011 APS-DPF
2011 DESDM I.Sevilla Slide 5 Transfer CTIO NCSA 300 GB/night in 18
h Process Archive Distribute 5/29 11/08/2011 APS-DPF 2011 DESDM
I.Sevilla Slide 6 Transfer Process Orchestration: NCSA HPC nodes
Archive Distribute 6/29 11/08/2011 APS-DPF 2011 DESDM I.Sevilla
Slide 7 Transfer Process Archive Results Archive nodes Oracle DB
Distribute 7/29 11/08/2011 APS-DPF 2011 DESDM I.Sevilla Slide 8
Transfer Process Archive Distribute Through web portals 8/29
11/08/2011 APS-DPF 2011 DESDM I.Sevilla Slide 9 Fermilab Team Huan
Lin Svetlana Lebedeva Nelly Stanfield Douglas Tucker Munich Team
Gurvan Bazin Art Carlson Joe Mohr (Project Scientist) SWG
Development links Mike Jarvis + WL SWG (WL pipeline) John Marriner
+ SNe SWG (Diff Imaging) Molly Swanson + LSS SWG (Survey Masks)
I.S. + LSS SWG (cosmic rays, satellites) SWG Testing links
Clusters- Sarah Hansen, Wayne Barkhouse LSS- I.S. 11/08/2011APS-DPF
2011 DESDM I.Sevilla 9/29 Slide 10 Exposure consists of 62+ CCD
images 570 Mpix - 3deg 2 Survey is ~150,000 100-sec exposures over
525 nights Auxiliary CCDs record images for autoguiding and
calibration 11/08/2011APS-DPF 2011 DESDM I.Sevilla 10/29 X 300 +
calib. = RAW DATA we send this to NCSA Slide 11 Correct for
cross-talk among CCDs. Correct for bias levels, non-uniformities,
other optical and electrical effects. 11/08/2011APS-DPF 2011 DESDM
I.Sevilla 11/29 DETRENDED DATA Credit:NOAO Slide 12
11/08/2011APS-DPF 2011 DESDM I.Sevilla 12/29 We need reference star
catalogs Full focal plane is fit to single solution Correct optical
distortion at focal plane Credit: E.Bertin We use Sextractor, SCAMP
software by E.Bertin Slide 13 REDUCED DATA 11/08/2011APS-DPF 2011
DESDM I.Sevilla 13/29 Use standard star fields at different angles
in the sky (X) with known fluxes (m_std and color_std) and relate
with instrumental flux (m_inst): Make big least squares solution
for a,b,k; apply results to science images. input output Slide 14
At this point we have, for every night, approx. 300 exposures
corrected by: Instrumental effects Absolute position Absolute
photometry This is the nightly processing. We store these in the
archive (+ auxiliary images, info). 11/08/2011APS-DPF 2011 DESDM
I.Sevilla 14/29 Slide 15 11/08/2011APS-DPF 2011 DESDM I.Sevilla
15/29 COADDED DATA Go deeper; calibrate better BUT Point spread
function is inhomogeneous: each exposure has different quality
single exposure single exposure single exposure single exposure
single exposure single exposure single exposure Slide 16
11/08/2011APS-DPF 2011 DESDM I.Sevilla 16/29 COADDED DATA Find PSF
in each image Homogeneize per coadd tile PSF HOMOGENEIZED 0.77 1.32
0.94 Slide 17 It takes 30x more time for coaddition with respect to
nightly: PSF has to be extracted PSF has to be homogeneized Actual
addition of image and recomputation of errors Additionally: Global
photometric calibration among all images of the season We store
these in the archive (+ auxiliary images, info). 11/08/2011APS-DPF
2011 DESDM I.Sevilla 17/29 Slide 18 11/08/2011APS-DPF 2011 DESDM
I.Sevilla 18/29 CATALOGS E.Bertin This step is performed with the
SExtractor package Position, shape and photometry is calculated.
Slide 19 11/08/2011APS-DPF 2011 DESDM I.Sevilla 19/29 Hundreds of
millions of objects with hundreds of columns each: Slide 20
11/08/2011APS-DPF 2011 DESDM I.Sevilla 20/29 Hundreds of millions
of objects with hundreds of columns each: Slide 21
11/08/2011APS-DPF 2011 DESDM I.Sevilla 21/29 Hundreds of millions
of objects with hundreds of columns each: Slide 22
11/08/2011APS-DPF 2011 DESDM I.Sevilla 22/29 Photometric redshift
pipeline: take fluxes in five bands -> estimate redshift Weak
lensing pipeline: identify stars and construct PSF -> deconvolve
from galaxies to obtain shear. Difference imaging pipeline (SN):
subtract images from different epochs to look for transient
phenomena. mag_band_g = 20.7 mag_band_r = 19.2 mag_band_i = 18.5 +
errors, other estimates (this only one kind of photo-z! More
estimations foreseen) DESDM Photoz pipeline (neural network) Slide
23 11/08/2011APS-DPF 2011 DESDM I.Sevilla 23/29 Photometric
redshift pipeline: take fluxes in five bands -> estimate
redshift Weak lensing pipeline: identify stars and construct PSF
-> deconvolve from galaxies to obtain shear. Difference imaging
pipeline (SN): subtract images from different epochs to look for
transient phenomena. Eliminate instrumental signature Obtain true
shape (intrinsic galaxy shape+ shear) DESDM WL pipeline local PSF
Slide 24 11/08/2011APS-DPF 2011 DESDM I.Sevilla 24/29 Photometric
redshift pipeline: take fluxes in five bands -> estimate
redshift Weak lensing pipeline: identify stars and construct PSF
-> deconvolve from galaxies to obtain shear. Difference imaging
pipeline (SN): subtract images from different epochs to look for
transient phenomena. Credit: Pan-STARRS Slide 25 11/08/2011APS-DPF
2011 DESDM I.Sevilla Produce cosmological simulations Process
through atmosphere, detectors, include nasty stuff 25/29 Slide 26
11/08/2011 APS-DPF 2011 DESDM I.Sevilla 26/29 Galaxies Stars Slide
27 11/08/2011APS-DPF 2011 DESDM I.Sevilla 27/29 BCS Images of First
SPT Clusters Credit: Blanco Cosmology Survey Real data sets from
the Blanco Cosmology Survey, SPT, SCS (Mosaic2 camera). Large scale
management with SDSS data. Slide 28 11/08/2011APS-DPF 2011 DESDM
I.Sevilla The Dark Energy Survey (next talks!) will make use of a
large, scalable data management system to process and archive raw
images and science ready data products. Acceptance of the system is
underway (results end of year). Tests on real DES data expected for
first months of 2012. Raw and reduced images to be released yearly,
catalogs at midpoint and end of survey. Community pipeline getting
ready for usage of the DES camera starting May 2012. 28/29 Slide 29
11/08/2011APS-DPF 2011 DESDM I.Sevilla Slide 30 Slide 31
11/08/2011APS-DPF 2011 DESDM I.Sevilla Development Funding ~$6M
Development Funding ~$6M $4 million from NSF $4 million from NSF
$1.78 million (in kind) from NCSA/U Illinois, Fermilab, IAP and
Munich $1.78 million (in kind) from NCSA/U Illinois, Fermilab, IAP
and Munich $300K from DES collaboration for Community Pipeline
$300K from DES collaboration for Community Pipeline Slide 32 (new
simulations with more DES-like systematics coming up by Stanford
team) Carnero et al. 2010 Slide 33 Slide 34 Slide 35 Slide 36
Perform full-depth observations in 100 sq.deg. Area is off main
survey Overlap existing datasets when possible Run acceptance tests
on data Slide 37 Slide 38
