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The Dark Energy Survey Science

The Dark Energy Survey Science. Alistair Walker (With thanks to Jim Annis, Josh Frieman, Ofer Lahav and Huan Linn ). Blanco 4-meter at CTIO. DES and the Dark Energy Program. Will measure Dark Energy using multiple complementary probes that are robust to systematics in any one technique

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The Dark Energy Survey Science

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  1. The Dark Energy Survey Science Alistair Walker (With thanks to Jim Annis, Josh Frieman, Ofer Lahav and Huan Linn)

  2. Blanco 4-meter at CTIO

  3. DES and the Dark Energy Program • Will measure Dark Energy using multiple complementary probes that are robust to systematics in any one technique • Survey strategy delivers substantial DE science after 2 years • Relatively modest, low-risk, near-term project with high discovery potential: factor 4.6 improvement in DETF Figure of Merit • Complements targeted (BAO) experiments of the late 2010’s such as HETDEX, BigBOSS • Scientific and technical precursor to the more ambitious Stage IV Dark Energy projects of the 2020’s (e.g. LSST, Euclid, WFIRST, BAO at 21 cm) • DES in unique international position to synergize with SPT and VISTA on the DETF Stage III timescale

  4. DES Collaboration >120 scientists from 11 US + 4 International Institutions/Consortia • Fermi National Accelerator Laboratory • University of Illinois at Urbana-Champaign • University of Chicago • Lawrence Berkeley National Laboratory • NOAO/CTIO • University of Michigan • Spain DES Collaboration:Instituto de Ciencias del Espacio (IEEC/CSIC); Institut de Fisica d'Altes Energies (IFAE); CIEMAT, Madrid • United Kingdom DES Collaboration: University College London; University of Cambridge; University of Edinburgh; University of Portsmouth; University of Sussex • University of Pennsylvania • Brazil-DES Consortium: Observatorio Nacional (ON); Centro Brasileiro de Pesquisas Fisicas (CBPF); Universidade Federal do Rio de Janeiro (UFRJ); Universidade Federal do Rio Grande do Sul (UFRGS) • Ohio State University • Argonne National Laboratory • Santa Cruz-SLAC-Stanford DES Consortium: University of California at Santa Cruz; SLAC National Accelerator Laboratory; KIPAC, Stanford University • Texas A&M University • Munich Universities: Ludwig-Maximillians University, Excellence Cluster Universe DES Funding from DOE, NSF, STFC (UK), Ministry of Education and Science (Spain), FINEP (Brazil), and the Collaborating Institutions

  5. DES Project Deliverables • To the Collaboration • DECam reduction pipeline which feeds specialist science pipelines and analysis codes • High level catalogs • To the Community • Raw data has 12 months proprietary time • Reduction pipeline processed data • Object cartalogs at mid-survey and at end-survey

  6. DES Science Organization • Josh Frieman (U. Chicago, FNAL) is the DES Project Director, Rich Kron is Deputy. • Ofer Lahav (UCL) chairs the DES Science Committee • DES Science Working groups • Large scale Structure (Enrique Gaztanaga and Will Percival) • Clusters (Joe Mohr and Tim McKay) • Weak Lensing (Sarah Bridle and Bhuv Jain) • Supernovae (John Marriner and Bob Nichol) • Simulations (Gus Evrard and Andrey Kravtsov) • Photoz (Francisco Castander and Huan Lin) • Ancillary (not aimed at DE) Science Working groups • Galaxy Formation & Evolution • Strong Gravitational Lensing • Quasars • Galactic (Milky Way) Archeology • Combined Probes & Theory

  7. Basic Survey Parameters • Study Dark Energy using • 4 complementary techniques: • I. Cluster Counts • II. Weak Lensing • III. Baryon Acoustic Oscillations • IV. Supernovae • •Two multiband surveys: • 5000 deg2g, r, i, Z,Y to i~24 • 15 deg2 repeat (SNe) • •Build new 3 deg2 camera • and Data management system • Survey 30% of 5 years • Response to NOAO AO Survey Area Overlap with South Pole Telescope Survey (4000 sq deg) Connector region (800 sq deg) Overlap with SDSS equatorial Stripe 82 (200 sq deg)

  8. DES Photometric Redshifts Elliptical galaxy spectrum • Measure relative flux in grizY filters and 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 are well measured • Good detector response in z-band filter needed to reach z~1.5

  9. Galaxy Photo-z Simulations +VHS* DES DES griz DES griZY +VHS JHKs on ESO VISTA 4-m enhances science reach 10 Limiting Magnitudes g 24.6 r 24.1 i 24.0 z 23.9 +2% photometric calibration error added in quadrature Key: Photo-z systematic errors under control using existing spectroscopic training sets to DES photometric depth: low-risk J 20.3 H 19.4 Ks 18.3 *Vista Hemisphere Survey PI: R. McMahon, Cambridge DES collaborator (approved by ESO 11/06) Cunha et al.; Banerji et al. (2008)

  10. Sunyaev-Zel’dovich effect (SZE) • Compton upscattering of CMB photons • by hot gas in clusters • - nearly independent of redshift: • - can probe to high redshift • - need ancillary redshift measurement from DES 10-m South Pole Telescope (SPT) DES survey area encompasses 4000 sq. deg. SPT SZE Survey Survey PI: J. Carlstrom (U. Chicago)

  11. Proposes to make precision measurements of Dark Energy Cluster counting, weak lensing, baryon acoustic oscillations, and supernovae Complementary* techniques Map the cosmological density field to z = 1 Measuring 300 million galaxies Spread over 5000 sq-degrees Using DECam, a 520 Megapixel camera New corrector, 3 sq. deg. field Installed on the existing CTIO 4m *in systematics & in cosmological parameter degeneracies *geometric+structure growth: test Dark Energy vs. Gravity The Dark Energy Survey

  12. Dark energy is the dominant constituent of the Universe (70%) Dark matter is next (25%) 95% of the Universe is in forms unknown to us The Big Problems: Dark Energy and Dark Matter The nature of the Dark Energy is one of the outstandingunsolved problems of fundamental physics.

  13. Measuring Dark Energy • One measures dark energy through how it affects the universe expansion rate, H(z): H(z) = H0 [ M (1+z) 3 + R (1+z) 4 + DE (1+z) 3 (1+w) ]0.5 matter radiation dark energy • Note the parameter w, which describes the evolution of the density of dark energy with redshift. A cosmological constant has w = 1. • wis currently constrained to ~20% by WMAP, SDSS, and supernovae • Measurements are usually integrals over H(z) r(z) =  dz/H(z) • Standard Candles (e.g., supernova) measure dL(z) = (1+z) r(z) • Standard Rulers measure da(z) = (1+z)1 r(z) • Volume Markers measure dV/dzd = r2(z)/H(z) • The rate of growth of structure is a more complicated function of H(z)

  14. Equation of State parameter w determines Cosmic Evolution Conservation of Energy-Momentum =Log[a0/a(t)]

  15. Interpreting Dark Energy… • The “Cosmological Constant” Problem Particle physics theory currently provides no understanding of why the vacuum energy density is so small: DE(Theory) /DE(obs) = 10120 • The Cosmic Coincidence Problem Theory provides no understanding of why the Dark Energy density is just now comparable to the matter density. • So? Is dark energy the vacuum energy? A light scalar field? A breakdown of General Relativity on large scales? Evidence for extra dimensions? Progress requires more precise probes of Dark Energy.

  16. DES Dark Energy Measurements • Four Probes of Dark Energy • Galaxy Clusters • ~100,000 clusters to z>1 • ~10,000 with SZ measurements from SPT • Sensitive to growth of structure and geometry • Weak Lensing • Shape measurements of 300 million galaxies • Sensitive to growth of structure and geometry • Baryon Acoustic Oscillations • 300 million galaxies to z = 1 and beyond • Sensitive to geometry • Supernovae • 15 sq deg time-domain survey (2 deep, 3 shallow fields) • ~3000 well-sampled SNe Ia to z ~1 • Sensitive to geometry

  17. w(z) =w0+wa(1–a) Each method has assumptions Planck CMB prior Simulations show that DES expects a factor 4.6 relative to Stage II (DETF nomenclature) DES Forecasts: Power of Multiple Techniques geometric+ growth DETF Figure of Merit: inverse area of ellipse geometric

  18. Type 1a Supernovae magnitudes and redshifts provide a direct means to probe dark energy Standard candles DES will make the next logical step in this program: Image 15 sq-degree repeatedly 5000 supernovae at z < 0.8 Well measured light curves 20% spectroscopic followup DES Supernova Current projects: “Union2” Compilation with 557 SN

  19. Rely on mapping the cosmological density field Up to the decoupling of the radiation, the evolution depends on the interactions of the matter and radiation fields - ‘CMB physics’ After decoupling, the evolution depends only on the cosmology - ‘large-scale structure in the linear regime’. Eventually the evolution becomes non-linear and complex structures like galaxies and clusters form - ‘non-linear structure formation’. Other Probes of Dark Energy z = 0 z = 30

  20. 3 Techniques for Cluster Selection and Mass Estimation: Optical galaxy concentration Weak Lensing Sunyaev-Zel’dovich effect (SPT) Cross-compare these techniques to reduce systematic errors Additional cross-checks: shape of mass function N(M,z) cluster spatial correlations M(r;z) Cluster Cosmology with DES

  21. Our mass estimators Galaxy count/luminosity Weak lensing Sunyaev-Zeldovich The South Pole Telescope project of J. Carlstrom et al. DES and SPT cover the same area of sky Self calibration Mass function shape allows independent checks Angular power spectrum of clusters Allows an approach at systematic error reduction Cluster Masses Optical Lensing Mass SZ X-ray

  22. Weak lensing is the statistical measurement of shear due to foreground masses A shear map is a map of the shapes of background galaxies Dls distance from lens to source Background galaxy shear maps Lensing galaxies Dl distance to lens Light path Ds distance to source Weak Lensing

  23. The strength of weak lensing by the same foreground galaxies varies with the distance to the background galaxies. Measure amplitude of shear vs. z shear-galaxy correlations shear-shear correlations DES will Image 5000 sq-degrees Photo-z accuracy of z < 0.1 to z = 1 10-20 galaxies/sq-arcminute Weak Lensing

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

  25. SDSS Galaxy Distribution Luminous Red Galaxies Their distribution shows imprint of the sound horizon SDSS Galaxy Distribution

  26. Baryon Acoustic Oscillations:CMB and Galaxies Acoustic series in P(k) becomes a single peak in (r) CMB Angular Power Spectrum SDSS galaxy correlation function Bennett et al. Eisenstein et al. Current surveys: WiggleZ, BOSS Future: HETDEX, BigBOSS,…

  27. BAO in DES: Galaxy Angular Power Spectrum Wiggles due to BAO Probe larger volume and redshift range than SDSS Systematics: photo-z’s, photometric errors Fosalba & Gaztanaga Blake & Bridle

  28. Recent Dark Energy Constraints Constraints from Supernovae, Cosmic Microwave Background Anisotropy (WMAP) and Large-scale Structure (Baryon Acoustic Oscillations, SDSS) Only statistical errors shown Only statistical errors shown assuming w = −1

  29. Much weaker current constraints on Time-varying Dark Energy 3-parameter model marginalized over Kowalski et al 08 Assumes flat Universe

  30. Forecast Constraints DETF FoM • Consistent with DETF range for Stage III DES-like project • DES+Stage II combined = Factor 4.6 improvement over Stage II combined • Large uncertainties in systematics remain, but FoM is robust to uncertainties in any one probe, and we haven’t made use of all the information

  31. DES Ancilliary Science • Formed 5 Study Groups in mid-2008: • Theory and Combined Dark Energy Probes: W. Hu, J. Weller • Quasars: P. Martini, R. McMahon • Galaxy Formation and Evolution: D. Thomas, R. Wechsler • Strong Gravitational Lensing: E. Buckley-Geer, M. Makler • Milky Way Structure and Archaeology: B. Santiago, B. Yanny • White Papers delivered late 2008-early 2009 • SC recommended formation of new Working Groups

  32. Strong Lensing: simulating lensed galaxies source size (half-light) high local magnifcation “Sextracted” arc “postage stamp”  arc parameters “truth table” PSF convolved image Projected lens plane caustic sources close to caustic WCS Implementing simulated arcs in DC 4 images With Poisson noise Final image: DC-4 cluster with added arc

  33. Galaxy Evolution Science • Evolution of global properties of galaxies • Stellar masses, ages, metal contents, star formation histories, SF rates • Luminosity and mass functions, luminosity and mass densities of massive galaxies, size distributions, colours, morphology • Galaxies in their cosmological context • Connecting galaxies with dark matter halos • Galaxy populations in galaxy clusters and intracluster light • Galaxy evolution across the Hubble Time • Massive galaxies at reionization and the galaxy-quasar connection • Strongly lensed galaxies at high redshifts • Interacting galaxies and merger rates at intermediate redshifts • Supernova host galaxies • Statistical studies of local dwarf galaxies and the Local Group

  34. Milky Way Science • Galactic Structure through Star counts (~108 stars) by Spectral Type • Low-luminosity stars in thick disk and halo; L and T dwarfs • Structure of outer stellar halo • Photometric metallicity calibration via Cluster fiducial sequences • Substructure in the Stellar halo (streams, local dwarf galaxies) • Stellar populations in outer regions of the LMC • Proper motion catalog • First “official” DES paper: The Dark Energy Survey : Perspectives for Resolved Stellar Populations, by Rossetto et al.

  35. 19 Eduardo Balbinot

  36. 20

  37. Quasar Science • Evolution of QSO space density to z=7.5 • SMBH growth in the early Universe • Probe baryon content of the Universe during epoch of reionization through the identification of bright QSOs with z=7 • Role of QSOs in reionization; follow-up spectroscopy of QSOALS • Cosmic evolution of supermassive black holes with QSO clustering over the redshift range 4 to 6 • Probe QSO lifetimes, accretion rates, host-halo masses • Synergy with VISTA VHS: grizYJHK observations to identify QSOs as drop-outs in increasingly redder passbands

  38. Predicted QSO numbers for DES • 1,000,000 with 0 < z < 3; g[AB] < 24 • 50,000 with 3 < z < 4; i[AB] < 24 • 10,000 with 4 < z < 5; i < 24 • 1,000-2,000 with 5 < z < 6.0; z < 23 • 50-100 with 6 < z < 7; Y < 21 • 10-50 with 7 < z < 8; Y < 21.5-22

  39. Theory and Combined Probes • Statistical inference: e.g. cross-terms of DES probes • Combining with other probes: e.g. SPT, Planck • Alternatives to Dark Energy: e.g. Modified Gravity, Inhomogeneous Universe

  40. The End To learn more about DECam and DES: • Please visit the DES WWW site at http://www.darkenergysurvey.org • Attend the DES Special Session at the AAS (Jan 11, 1000-1130) • Attend the Community Use of DECam Splinter Meeting at the AAS (Jan 11, 1730-1900) • Advertise the soon-to-be-announced 2-day DECam & The Community Workshop (~August 2011, Tucson) • This talk: anon ftp to ftp.ctio.noao.edu , cd pub/walker/ObsCouncil, get *.pdf • And, to see DECam on the Simulator at Fermilab Lab A: http://decamlaba.fnal.gov/index.html?size=2&mode=3

  41. Extra Slides

  42. Light Scalar Fields as Dark Energy Perhaps the Universe is not yet in its ground state. The `true’ vacuum energy (Λ) could be zero (for reasons yet unknown). Transient vacuum energy can exist if there is a field that takes a cosmologically long time to reach its ground state. This was the reasoning behind inflation. For this reasoning to apply now, we must postulate the existence of an extremely light scalar field, since the dynamical evolution of such a field is governed by JF, Hill, Stebbins, Waga 1995

  43. Dark Energy: Alternatives to Λ The smoothness of the Universe and the large-scale structure of galaxies can be neatly explained if there was a much earlier epoch of cosmic acceleration that occurred a tiny fraction of a second after the Big Bang: Primordial Inflation Inflation ended, so it was not driven by the cosmological constant. This is a caution against theoretical prejudice for Λ as the cause of current acceleration (i.e., as the identity of dark energy).

  44. Scalar Field as Dark Energy(inspired by inflation) • Dark Energy could be due to a very light scalar field j, slowly evolving in a potential, V(j): • Density & pressure: • Slow roll: V(j) j

  45. Variance and Bias of Photo-z Estimates Bias Variance Cunha etal

  46. Spectroscopic Redshift Training Sets for DES Training Sets to the DES photometric depth in place (advantage of a `relatively’ shallow survey)

  47. Clusters and Photo-z Systematics

  48. (w0)/(w0|pz fixed) (wa)/(wa|pz fixed) Weak Lensing & Photo-z Systematics Ma

  49. BAO & Photo-z Systematics (w0)/(w0|pz fixed) (wa)/(wa|pz fixed) Ma

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