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Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Design of the Dark Energy Survey James Annis.

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Presentation on theme: "Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Design of the Dark Energy Survey James Annis."— Presentation transcript:

1 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Design of the Dark Energy Survey James Annis

2 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Science Goals to Science Objective To achieve our science goals: –Cluster counting to z > 1 –Spatial angular power spectra of galaxies to z = 1 –Weak lensing, shear-galaxy and shear-shear –2000 z<0.8 supernova light curves We have chosen our science objective: –5000 sq-degree imaging survey Complete cluster catalog to z = 1, photometric redshifts to z=1.3 Overlapping the South Pole Telescope SZ survey 30% telescope time over 5 years –40 sq-degree time domain survey 5 year, 6 months/year, 1 hour/night, 3 day cadence

3 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Science Requirements 1.5000 sq-degrees Significantly overlapping the SPT SZ survey area To be completed in 5 years with a 30% duty cycle 2.4 bandpasses covering 390 to 1100 nm SDSS g,r,i,z z modified with Y cutoff 3.Limiting magnitudes g,r,i,z = 24,24,24,23.6 10σ for small galaxies 4.Photometric calibration to 2% 1% enhanced goal 5.Astrometric calibration to 0.1” 6.Point spread function Seeing < 1.1” FWHM Median seeing <= 0.9” g-band PSF can be 10% worse Stable to 0.1% over 9 sq- arcminute scales From chapter 3 of NOAO proposal; version 3 of requirements. Version 4, under review, will be a formal science requirements document.

4 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Limiting Magnitude Limiting magnitude (10σ for small galaxies) was set by flow down of science goals: ½ L* cluster galaxies at redshift 4000A break leaving blue filter –g,r,i,z = 22.8,23.4,24.0,23.3 –Complete cluster catalog Galaxy catalog completeness –g,r,i,z = 22.8,23.4,24.0,23.6 –Simple selection function Blue galaxy photo-z at faint mags –g,r,i,z = 24.0,24.0,24.0,23.6 –Photo-z for angular power spectra and weak lensing 0 redshift 1.5 Mag of ½ L* galaxy photo-z – spectro-z i = 23-24 Red Galaxy

5 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Photometric Redshifts Resulting limiting magnitudes give very good photometric redshifts Monte Carlo simulations of photometric redshift precision –Evolving old stellar pop. SED –Redshifted and convolved with filter curves. Noise added. –Polynomial fit to photo-z –For clusters, averaging all galaxies in the cluster above limiting magnitude. Template fit for photo-z These are sufficient to achieve our science goals. ½ L*2 L* 1.0x10 14 M 0 Clusters Red galaxies

6 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson The Footprint Requirements Overlap with SPT SZ survey Redshift survey overlap Footprint -60 <= Dec <= -30 SDSS Stripe 82 + VLT surveys Overlap targetRight Ascension (deg) Declinatio n (deg) Area (sq. deg.) SPT-60 to 105 -75 to -60 -30 to -65 -45 to –65 4000 SDSS Stripe 82-50 to 50-1.0 to 1.0200 Connection region 20 to 50-30 to –1.0800 DIRBE dust map, galactic coordinates

7 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Survey Strategy I Design decision 1: area is more important than depth –Image the entire survey area multiple times Design decision 2: tilings are important for calibration –An imaging of the entire area is a tiling –Multiple tilings are a core means of meeting the photometric calibration requirement: offset tilings, not dithers Design decision 3: substantial science with year 2 data –We will aim for substantial science publications jointly with the public release of the year 2 data.

8 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Survey Strategy II Year 2 –g,r,i,z 100 sec exposures –g,r,i,z =24.6, 24.1, 23.6, 23.0 –Calibration: abs=2.5% rel=1.2% –Clusters to z=0.8 –Weak lensing at 12 gals/sq-arcmin Year 5 –z 400 sec exposures –g,r,i,z =24.6, 24.1, 24.3, 23.9 –Calibration: abs=<2% rel=<1% –Clusters to z=1.3 –Weak lensing at 28 gals/sq-arcmin Two tilings/year/bandpass In year 1-2, 100 sec/exp In year 3, drop g,r and devote time to i,z: 200 sec/exp In year 5, drop i and devote time to z: 400 sec/exp If year 1 or 2 include an El Nino event, we lose ~1 tiling, leaving three tilings at the end of year 2. This is sufficient to produce substantial key project science.

9 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson DES Time Allocation Model September: 4 bright+ 4 dark nights 22 nights October: 4 bright+ 5 dark nights 22 nights November: 4 bright+ 4 dark nights 22 nights December: 4 bright+ 4 dark nights 21 nights Telescope shut down Dec 25, 31 January: 4 bright+ 5 dark nights 11 nights and the 2 nd half of all nights February: 3 bright+ 3 dark nights 11 nights and the 2 nd half of all nights March – August all none T otal 257 nights 108 nights Time to the Community and to the Dark Energy Survey

10 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Time Allocation Analytic calculation of time available –30 year CTIO weather statistics –5 year moving averages –Calculate photometric time –Can complete imaging survey and time domain survey with 3 sq-degree field of view camera Simulations of observing process –Use mean weather year –Survey geometry –Observing overhead –NOAO time allocation model –High probability of completing core survey area in time allocated Probability of obtaining 8 tilings per year over survey area. Dark is 100%, light yellow ~50% => DES time allocation model just sufficient to achieve science objective. CTIO mean weather year

11 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Photometric Calibration Strategy Calibrate system response –Convolve calibrated spectrum with system response curves to predict colors to 2% –Dedicated measurement response system integrated into instrument Absolute calibration –Absolute calibration should be good to 0.5% –Per bandpass: magnitudes, not colors –Given flat map, the problem reduces to judiciously spaced standard stars Relative calibration –Photometry good to 2% –Per bandpass: mags, not colors –Use offset tilings to do relative photometry Multiple observations of same stars through different parts of the camera allow reduction of systematic errors Hexagon tiling: –3 tilings at 3x30% overlap –3 more at 2x40% overlap –Aim is to produce rigid flat map of single bandpass –Check using colors Stellar locus principal colors

12 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Survey Simulation We plan a full scale simulation effort –Led by Huan Lin –Centered at Fermilab and Chicago –Using analytic, catalog and full image simulation techniques Over 4 years –Underway, starting with photometric redshift simulations Use the simulations in 3 ways: –Check reduction code Mock data reduction challenge Chris Stoughton –Prepare analysis codes Mock data analysis challenge Josh Frieman –Prepare for science Survey simulations –Jim Annis Catalog level simulations –Lin, Frieman, students for photo-z and galaxy distributions –Risa Weschler’s Hubble Volume n-body –Albert Stebbins’s multi-gaussian approximation –Mike Gladder’s empirical halo model Image level simulations –Erin Sheldon for weak lensing –Doug Tucker and Chris Stoughton Terapix skyMaker Massey’s Shapelets code

13 Jim Annis for the DES Collaboration BIRP Meeting August 12, 2004 Tucson Survey Planning Summary We have well defined science goals and a well defined science objective –A 5000 sq-degree survey substantially overlapping the SPT survey –A time domain survey using 10% of time The science requirements are achievable. –A good seeing, 4 bandpass, 2% calibration, i ~ 24 survey Multiple tilings of the survey area the core of the survey strategy and photometric calibration. The survey can be completed using: –22 nights a month between September and October –21 nights in December –22 half nights a month in January and February


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