1. 1 The Dark Energy Survey John Peoples Adapted from the P5 presentations by Josh Frieman and Brenna Flaugher

2. 2 The DES Collaboration Fermilab: J. Annis, H. T. Diehl, S. Dodelson, J. Estrada, B. Flaugher, J. Frieman, S. Kent, H. Lin, P. Limon, K. W. Merritt, J. Peoples, V. Scarpine, A. Stebbins, C. Stoughton, D. Tucker, W. Wester University of Illinois at Urbana-Champaign: C. Beldica, R. Brunner, I. Karliner, J. Mohr, R. Plante, P. Ricker, M. Selen, J. Thaler University of Chicago: J. Carlstrom, S. Dodelson, J. Frieman, M. Gladders, W. Hu, S. Kent, R. Kessler, E. Sheldon, R. Wechsler Lawrence Berkeley National Lab: N. Roe, C. Bebek, M. Levi, S. Perlmutter University of Michigan: R. Bernstein, B. Bigelow, M. Campbell, D. Gerdes, A. Evrard, W. Lorenzon, T. McKay, M. Schubnell, G. Tarle, M. Tecchio NOAO/CTIO: T. Abbott, C. Miller, C. Smith, N. Suntzeff, A. Walker CSIC/Institut d'Estudis Espacials de Catalunya (Barcelona): F. Castander, P. Fosalba, E. Gaztañaga, J. Miralda-Escude Institut de Fisica d'Altes Energies (Barcelona): E. Fernández, M. Martínez CIEMAT (Madrid): C. Mana, M. Molla, E. Sanchez, J. Garcia-Bellido University College London: O. Lahav, D. Brooks, P. Doel, M. Barlow, S. Bridle, S. Viti, J. Weller University of Cambridge: G. Efstathiou, R. McMahon, W. Sutherland University of Edinburgh: J. Peacock University of Portsmouth: R. Crittenden, R. Nichol, W. Percival University of Sussex: A. Liddle, K. Romer plus students

3. 3 The Dark Energy Survey Study Dark Energy using 4 complementary* techniques: I. Cluster Counts II. Weak Lensing III. Baryon Acoustic Oscillations IV. Supernovae Two multiband surveys: 5000 deg 2 g, r, i, z 40 deg 2 repeat (SNe) Build new 3 deg 2 camera and Data management sytem Survey 2009-2015 (525 nights) Response to NOAO AO Blanco 4-meter at CTIO *in systematics & in cosmological parameter degeneracies *geometric+structure growth: test Dark Energy vs. Gravity

4. 4 Dark Energy and the Accelerating Universe Brightness of distant Type Ia supernovae, along with CMB and galaxy clustering data, indicates the expansion of the Universe is accelerating, not decelerating. This requires either a new form of stress-energy with negative effective pressure or a breakdown of General Relativity at large distances: DARK ENERGY Characterize by its effective equation of state: w = p/  <  1/3 and its relative contribution to the present density of the Universe:  DE Special case: cosmological constant: w =  1

5. 5 What is the Nature of the Dark Energy? Stress-Energy: G  = 8  G [T  (matter) + T  (dark energy)] Gravity: G  + f(g  ) = 8  G T  (matter) Key Experimental Questions: 1.Is DE observationally distinguishable from a cosmological constant, for which T  (vacuum) =  g  /3, i.e., w =—1? 2.Can we distinguish between gravity and stress-energy? Combine geometric with structure-growth probes 3.Does dark energy evolve: w=w(z)?

6. 6 Probe dark energy through the history of the expansion rate: H 2 (z) = H 2 0 [  M (1+z) 3 +  DE (1+z) 3 (1+w) ] (flat Universe) matter dark energy Comoving distance: Weak Lensing r(z) =  dz/H(z) Standard Candles: Supernovae d L (z) = (1+z) r(z) Standard Rulers: Baryon Oscillations d A (z) = (1+z)  1 r(z) Standard Population: Clusters dV/dzd  = r 2 (z)/H(z) The rate of growth of structure also det’d by H(z) Probing Dark Energy

7. 7 Probe dark energy through the history of the expansion rate: and the growth of large-scale structure: Parametrize DE Evolution: Geometric tests: Comoving distance Weak Lensing Standard Candles Supernovae Standard Rulers Baryon Oscillations Standard Population Clusters Probing Dark Energy

8. 8 Photometric Redshifts Measure relative flux in four filters griz: track the 4000 A break Estimate individual galaxy redshifts with accuracy  (z) < 0.1 (~0.02 for clusters) Precision is sufficient for Dark Energy probes, provided error distributions well measured. Note: good detector response in z band filter needed to reach z>1 Elliptical galaxy spectrum

9. DES griz filters 10  Limiting Magnitudes g24.6 r24.1 i24.0 z23.9 +2% photometric calibration error added in quadrature Key: Photo-z systematic errors under control using existing spectroscopic training sets to DES photometric depth Galaxy Photo-z Simulations +VHS JK Improved Photo-z & Error Estimates and robust methods of outlier rejection DES Cunha, etal DES + VHS on ESO VISTA 4-m enhances science reach

10. 10 I. Clusters and Dark Energy Mohr Volume Growth (geometry) Number of clusters above observable mass threshold Dark Energy equation of state Requirements 1.Understand formation of dark matter halos 2.Cleanly select massive dark matter halos (galaxy clusters) over a range of redshifts 3.Redshift estimates for each cluster 4.Observable proxy that can be used as cluster mass estimate: O =g(M) Primary systematic: Uncertainty in bias & scatter of mass-observable relation

11. 11 Cluster Cosmology with DES 3 Techniques for Cluster Selection and Mass Estimation: Optical galaxy concentration Weak Lensing Sunyaev-Zel’dovich effect (SZE) Cross-compare these techniques to reduce systematic errors Additional cross-checks: shape of mass function; cluster correlations

12. 12 10-m South Pole Telescope (SPT) SPT will carry out 4000 sq. deg. SZE Survey PI: J. Carlstrom (U. Chicago) NSF-OPP funded & scheduled for Nov 2006 deployment DOE (LBNL) funding of readout development Sunyaev-Zel’dovich effect - Compton upscattering of CMB photons by hot gas in clusters - nearly independent of redshift: - can probe to high redshift - need ancillary redshift measurement Dec 2005

13. 13 SZE vs. Cluster Mass: Progress in Realistic Simulations Motl, etal Integrated SZE flux decrement depends only on cluster mass: insensitive to details of gas dynamics/galaxy formation in the cluster core robust scaling relations Nagai SZE flux  Adiabatic ∆ Cooling+Star Formation SPT Observable Kravtsov Future: SCIDAC proposal small (~10%) scatter

14. Argonne 25 Oct 2006 14 Gravitational Lensing by Clusters

15. Weak Lensing of Faint Galaxies: distortion of shapes Background Source shape

16. Foreground Cluster Weak Lensing of Faint Galaxies: distortion of shapes Background Source shape Note: the effect has been greatly exaggerated here

17. Foreground Cluster Lensing of real (elliptically shaped) galaxies Co-add signal around a number of Clusters Background Source shape

18. 18 Statistical Weak Lensing Calibrates Cluster Mass vs. Observable Relation Cluster Mass vs. Number of galaxies they contain For DES, will use this to independently calibrate SZE vs. Mass Johnston, Sheldon, etal, in preparation Statistical Lensing eliminates projection effects of individual cluster mass estimates Johnston, etal astro-ph/0507467 SDSS Data Preliminary z<0.3

19. 19 Observer Dark matter halos Background sources Statistical measure of shear pattern, ~1% distortion Radial distances depend on geometry of Universe Foreground mass distribution depends on growth of structure

20. 20 Cosmic Shear Angular Power Spectrum in 4 Photo-z Slices Shapes of ~300 million galaxies median redshift  z  = 0.7 Primary Systematics: photo-z’s, PSF anisotropy, shear calibration Weak Lensing Tomography DES WL forecasts conservatively assume 0.9” PSF = median delivered to existing Blanco camera: DES should do better & be more stable (see Brenna’s talk) Huterer Statistical errors shown

21. 21 III. Baryon Acoustic Oscillations (BAO) in the CMB Characteristic angular scale set by sound horizon at recombination: standard ruler (geometric probe).

22. 22 Baryon Acoustic Oscillations: CMB & Galaxies CMB Angular Power Spectrum SDSS galaxy correlation function Acoustic series in P(k) becomes a single peak in  (r) Bennett, etal Eisenstein etal

23. 23 BAO in DES: Galaxy Angular Power Spectrum Probe substantially larger volume and redshift range than SDSS Wiggles due to BAO Blake & BridleFosalba & Gaztanaga

24. 24 IV. Supernovae Geometric Probe of Dark Energy Repeat observations of 40 deg 2, using 10% of survey time ~1900 well-measured SN Ia lightcurves, 0.25 < z < 0.75 Larger sample, improved z-band response compared to ESSENCE, SNLS; address issues they raise Improved photometric precision via in- situ photometric response measurements SDSS

25. 25 DES Forecasts: Power of Multiple Techniques Ma, Weller, Huterer, etal Assumptions: Clusters:  8 =0.75, z max =1.5, WL mass calibration (no clustering) BAO: l max =300 WL: l max =1000 (no bispectrum) Statistical+photo-z systematic errors only Spatial curvature, galaxy bias marginalized Planck CMB prior w(z) =w 0 +w a (1–a) 68% CL geometric geometric+ growth Clusters if  8 =0.9

26. 26 Will measure Dark Energy using multiple complementary probes, developing these techniques and exploring their systematic error floors Survey strategy delivers substantial DE science after 2 years Relatively modest, low-risk, near-term project with high discovery potential Scientific and technical precursor to the more ambitious Stage IV Dark Energy projects to follow: LSST and JDEM DES in unique international position to synergize with SPT and VISTA on the DETF Stage III timescale (PanSTARRS is in the Northern hemisphere; cannot be done with existing facilities in the South) DES and a Dark Energy Program

27. 27 From Scientific Goals to Science Quality Data The Camera, the telescope and data management Brenna Flaugher DECam Project Manager Fermilab

28. 28 DES Science and Technical Requirements 5000 deg 2 of the So. Galactic Cap in 525 nights (5 yrs) photometric-redshifts to z=1.3 with dz < 0.02. A small and stable point spread function (PSF) < 0.9'' FWHM median A large camera, on the Blanco 4m – 3 deg 2 camera with ≥ 2.2 deg FOV Data Management system – 300GB/night, automated processing – Publicly available data archive after 1 yr Filters, CCDs, Read noise – SDSS g,r,i,z filters; 400 - 1100nm – QE > 50% in the z band (825-1100nm) – Read noise <10 e- Optical Corrector with excellent images – Pixel size <0.3” /pixel – < 0.4” FWHM in the i and z bands Science Requirements Technical Requirements

29. 29 The DES Instrument: DECam 3556 mm 1575 mm Hexapod Optical Lenses F8 Mirror CCD Read out DECam will replace the prime focus cage on the Blanco Filters Shutter Prime Focus Instrument -in optical path -space and thermal constraints

30. 30 DES CCDs LBNL Design: fully depleted 2kx4k CCDs –QE> 50% at 1000 nm, 250 microns thick –15  m pixels, 0.27”/pixel –readout 250 kpix/sec, readout time ~17sec LBNL CCDs in use on WIYN telescope. From S. Holland et al, LBNL-49992 IEEE Trans. Elec. Dev. Vol.50, No 1, 225- 338, Jan. 2003 LBNL CCDs are much more efficient than the SITE CCDs in Mosaic II at high wavelengths To reach redshifts of ~1.3 DES will spend 46% of survey time in z –band DES CCD design has already been used on telescopes in small numbers (3) DES is the 1 st production quantity application for LBNL CCDs z band

31. 31 CCD Fabrication and Packaging Business model developed by LBNL: Foundry delivers partially processed wafers to LBNL (~650 microns thick) LBNL finishes wafers (250 microns thick), tests, dices (production rate 5 wafers/month FNAL builds up the CCD packages and tests CCD – will match CCD delivery rate Preconceptual R&D: 44 Eng. grade 2kx4k CCDs in hand, plus 20 in Dec used to develop focal plane packages, characterize CCD performance, test CCD readout electronics FY07: establish CCD processing and packaging yield –preliminary est. 25% yield (SNAP devices) –implies 18 months and $1.6M for 70 good devices –CCD yield is a cost and schedule driver DES Wafers – June 2005!

32. 32 Front End Electronics: CCD Readout FNAL, Barcelona, Madrid, UIUC Spanish consortium is participating in the FEE development and has been funded to provide production FEE. Status: –UIUC has purchased prototype readout systems for testing –have already achieved 6.5e noise at ~200 kpix/sec, –have a design that fits in 3 temp. controlled crates in PF cage –Test of readout of multiple CCDs is in progress Part of Fermilab Team in the testing lab LN2 Dewars Readout racks Filter and shutter controls 3 operational CCD testing setups

33. 33 Camera Vessel Prototype 10 slot thermally controlled crate for CCD readout electronics Cryo and Vacuum controls Focal plane Feed-through board for CCD signals Full size prototype was built by U. Chicago and it being used to test multi-CCD readout

34. 34 Survey Image System Process Integration (SISPI) CTIO will upgrade the Telescope Control System (TCS) Data Management (DM): U. Illinois-Astro/NCSA U Illinois-HEP (J. Thaler) is leading the SISPI development - similar to HEP-DAQ systems

35. 35 Optical Corrector Design Preliminary Design complete (UMich, FNAL, UCL) –Image quality fwhm: ~ 0.33” (<0.4” required) March 2006, PPARC Council announced that it “will seek participation in DES” –The UK Consortium funded by PPARC to lead the procurement of the optics subject to US approval –1.47 M pound proposal to cover cost of polishing, mounting, and alignment of the lenses in the barrel –P. Doel at U. College London Optical Science Lab will manage the procurement and fabrication Additional UK funding ($0.4M ) available through Portsmouth (SRIF3): ~60% of the blanks US Universities will fund the remainder. Procurement of the optics is ~2 years CRITICAL PATH filter Dewar window C1 has 940 mm diameter C2 C3 C4 5 elements, fused silica

36. 36 U. Michigan will –handle procurement and testing of the filters –match SDSS – g,r,i,z and introduce a well defined cut-off at high wavelength –design and fabricate or procure a combined filter changer and shutter DES Filters Filter changer will be a cartridge system similar to PanStarrs design

37. 37 The Blanco Telescope Commissioned in 1974 primary mirror quality (D80 = 0.25 arcsec) defined state-of-the-art. The critical observations for the discovery of Dark Energy were made with this telescope. Extensive set of improvements in the 90’s –Primary mirror active support system (active optics), to replace the passive support system. –Environmental improvements, e.g. windows in the dome to promote air flow, removal of heat sources. THE SITE: - October to January - weather improving, nights get shorter (av. 6.8 hr/night useable) - Mean site seeing at 5m above ground = 0.65 arcsec

38. 38 DECam & CTIO High-quality primary, D80 at manufacture: 0.25” Active Optics –33-pad system, LUT driven, updated every few months –DECam will provide in-line updates (via “donut”) possibly allowing us to close the loop during observations

39. 39 DECam & CTIO Primary mirror repositioned 2.3mm in z- direction Primary mirror is now centered in cell –Coma was dominant and variable, is now the third most significant aberration and stable. Image Quality obtained by the SuperMacho program, 2005B, airmass corrected, VR filter. Dates: 2005-09-05 to 2005-12- 31, Blue: pre-shutdown, red: post-shutdown, approx equal number (~580) exposures each.

40. 40 2004 Level 0 Image Simulations → DM Challenge 0: Done! –Reformatted SDSS data used to simulate DES images 2005-06 Level 1 Catalog &Image Sim. → DM Chal. 1: Done! –500 sq. deg. catalog; 500 GB of images; FNAL and UChicago computing used 2006-07 Level 2 Catalog and Image Sim. In progress –5000 sq. deg. catalog; 5 TB of images –FermiGrid & MareNostrum SuperComputer (Barcelona) –Higher resolution N-body simulation, more realistic galaxy properties, and more sophisticated atmosphere and instrument models (noise, ghosts) –Recover input cosmology from catalogs using 4 DES key project methods 2007-8 Level 3 Catalog and Image Simulations –Suite of full-DES catalogs (i.e., different input cosmologies) –Synergy with DOE SciDAC proposal (with many DES collaborators) to produce large cosmological simulations for dark energy studies –1 year of DES imaging data –Recovery of input cosmologies from catalogs and images –Stress test of full data processing system DES Simulations Feed DM Challenges

41. 41 DES Data Management Project U. Illinois and NCSA lead the DM project –Joe Mohr (U. Illinois) is the project leader –Cristina Beldica (NCSA) is the project manager DM System Requirements –Reliably transfer ~300GB/night for 525 nights from CTIO to U.Illinois/National Center for Supercomputing Applications (NCSA) –Automatically process data with built-in quality assurance –Archive the data products and serve the processed data to collaboration –Provide community access to the archive 1 year after images were collected DM Team –U Illinois/NCSA, Fermilab and NOAO –Additional DES collaborators Deliverables to DES and astronomical community –DM System ( High Performance Computing platforms and workstations )  Pipeline middleware  Astronomy modules  Catalog database  Image Archive –Archived science ready DES data U Illinois/NCSA DES DM Team

42. 42 This grid-based, modular and flexible data management system was deployed and tested in Data Challenge 1 (Oct ‘05-Jan ‘06)

43. 43 DM Schedule and Status Pursuing iterative development strategy ‘04-’09 –Yearly data challenges Oct-Jan ‘05-’08 –Development targets full delivery in 2009  DC1: base level system in place  DC2: data quality, stress test  DC3: deploy and test outside NCSA  DC4: final validation and stress test Data Challenge 1 Results (Oct 1 ‘05-Jan 31 ‘06) –DM system deployed and tested –Automated reduction (500GB raw reduced into 5TB) –Catalogued and calibrated 50 million objects –Confirmed photometry and astrometry Reduced, pseudo-color DC1 Image

44. 44 DECam critical paths: CCDs & Optics CCDs: LBNL can deliver CCDs at a rate of 20/month after 3 month startup We need 70 CCDs for the FP including spares Preliminary yield estimate of 25% implies ~18 months Construction start of Jan 08 implies last CCD is finished July ’10 Install last CCD and test full camera ~ 2 months Ready to ship to Chile ~ Fall ’10 Optics: Order glass blanks and seek tenders for finishing lenses (Feb 07) Assembly and alignment into corrector ~ 6 months Ready to ship to Chile ~ 3 yrs after procurement begins (Feb ’10)

45. 45 DES Project Approval Status ● Collaboration formed Dec. 2003 ● June 2004 Fermilab Directors Review #1 ● July 2004: Fermilab Director gives DES Stage 1 approval – Collaboration can submit a proposal to NOAO with Fermilab support ● Aug 2004: NOAO Director accepts DES proposal for partnership – 525 nights of CTIO 4m time in return for new instrument and archive ● May 2005: Science working groups form – submit white paper (astro-ph/0510346) to Dark Energy Task Force ● May 2006: DETF recommends a Stage III experiment like DES ● July 2006: P5 recommends that DES start construction in FY2008 and HEPAP endorses the P5 report and sends it to DOE and NSF ● July 2006: Fermilab Director’s Review #2 ● October 2006: NSF and DOE request a plan describing the entire experiment “end-to-end” that they will review jointly

46. 46 DECam Project Status and Forecast ● FY05 and 06 were generic R&D years ● CCDs: set up production with LBNL, develop CCD test systems, & demonstrate packaging ● 25 wafers in FY2005 and FY2006 ● Optics: finalized design, firm cost estimate developed ● DECam and DESDM conceptual design completed ● FY07 project R&D – `CCD yield determination and system tests – Front end electronic board development and systems tests – Data Challenge 3 ● FY08, FY 09 & FY10 are construction years ● Winter 2010: ship instrument to Chile ● Fall 2010: start survey

47. 47 Conclusions DES provides the next logical step in both technology and science –Builds on existing technology and infrastructure, and capitalizes on collaboration’s experience with large DAQ systems, silicon vertex detectors, and data handling –3 deg 2 camera: x7 larger area and x7 faster readout than existing Mosaic camera on the Blanco –1PB total processed images available to the public; data released 1 year after images taken –Development and implementation of data analysis techniques for photo-z’s, cluster masses, weak lensing, baryon oscillations, and supernovae are the next steps toward the science of the Stage IV projects of the future (LSST, SNAP)

48. 48 DECam at CTIO

49. 49

50. 50 extras

51. Argonne 25 Oct 2006 51 Evolution of Structure Robustness of the paradigm recommends its use as a Dark Energy probe Price: additional cosmological and structure formation parameters Bonus: additional structure formation Parameters Methods: WL, Clusters

52. 52 CCD Requirements

53. 53 Side view

54. 54 Front view

55. 55 Isometric view camera end

56. Photo-z Error Distributions & Error Estimates

57. Robustly Reducing Catastrophic Errors Remove 10% of objects via color cuts 30% improvement Original10% Cut

58. 58 Supernovae and photo-z errors Huterer

59. 59 Improving Corrections for Anisotropic PSF Whisker plots for three BTC camera exposures; ~10% ellipticity Left and right are most extreme variations, middle is more typical. Correlated variation in the different exposures: PCA analysis --> can use stars in all the images: much better PSF interpolation Focus too lowFocus (roughly) correctFocus too high Jarvis and Jain

60. 60 PCA Analysis Remaining ellipticities are essentially uncorrelated. Measurement error is the cause of the residual shapes. 1st improvement: higher order polynomial means PSF accurate to smaller scales 2nd: Much lower correlated residuals on all scales Focus too low Focus (roughly) correctFocus too high

61. 61 Reducing WL Shear Systematics See Brenna’s talk for DECam+Blanco hardware improvements that will reduce raw lensing systematics Red: expected signal Results from 75 sq. deg. WL Survey with Mosaic II and BTC on the Blanco 4-m Bernstein, etal DES: comparable depth: source galaxies well resolved & bright: low-risk (improved systematic) (signal) Shear systematics under control at level needed for DES (old systematic) Cosmic Shear