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SURVeys : methods and observations

Lecture #2. SURVeys : methods and observations. Lecture plan. Designing a deep survey I nstruments for deep surveys Observational methods Data processing Databases and information systems Comparing surveys. Designing a survey. Science goals & strategy Survey parameter space

aaron-higgins
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SURVeys : methods and observations

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  1. Lecture #2 SURVeys: methods and observations Olivier Le Fèvre- LAM Cosmology Summer School 2014

  2. Lecture plan • Designing a deepsurvey • Instruments for deepsurveys • Observationalmethods • Data processing • Databases and information systems • Comparingsurveys

  3. Designing a survey • Science goals & strategy • Survey parameterspace • Existing or new instrumentation ? • Examples • SDSS • VVDS • VIPERS • VUDS

  4. How are galaxysurveysdesigned ? The ‘Wedding cake’ approach Deep / smallfield Medium / large field Shallow / all-sky

  5. SomePrinciples • Surveys need to be unbiased • Volume, luminosity/mass, type, environment… • Proper photometric catalogs • Statistically robust • Complete census • Selection function control • Apriori hypotheses • Large deep imaging surveys • Large samples • Multi-wavelength 2 types of surveys: photometric and spectroscopic

  6. Science goals: the starting point • What are the science questions addressed by the survey ? • What are the measurements to be performed ? • What is the desired accuracy ? Star formation rate Merger rate Mass of galaxies in DM Halos Build-up of redsequence Morphology-density Growth rate … As a function of z…

  7. Survey parameterspace Also: spatial resolution

  8. Survey volume • Area depends on telescope+instrument • Etendue A • Instantaneous volume and tiling • One instrument pointing necessarily limited in area • Need tiling to implement survey Single pointingfootprint: Megacam @CFHT Wholeskytiling: Euclid

  9. Etendue (some instrumentation stuff…) • An instrument system is more efficient the larger the Etendue • Etendue: the area of the entrance pupil times the solid angle the source E=A

  10. A: a key element in instrument systems • A = telescopecollecting area • = telescope+instrumentfield of view • The larger the A, the more information canbeaccessed These instrument systems have the sameefficiency

  11. Survey depth • Depends on • Telescopediameter • Instrument throughput (opticalefficiency) • Exposure time • Detector noise • Background • Signal to noise S/N Source Nphotons Source Background Detector Noise Det. Darkcurrent

  12. Survey redshift range The redshift range willdetermine the wavelength range (and vice-versa)

  13. Survey spectral resolution • Ability to separate spectral features • R=/d • The higher R, the betteris the velocityresolution, or velocityaccuracy • Choicedepends on the spectral featuresyou are interestedinto • Broad features (e.g. because of velocity dispersion) or narrow

  14. Survey number of objects • A key number: 104objects Why ?

  15. Nobj ?? • ~105!! • Studyevolution vs. Luminosity, color (type), environnement • Minimise cosmic variance effects: surveyseveralindependantfields • Several time intervals to followevolution • 50 galaxies per measurementbin • Total number of galaxies: 50  10  3  3  4 7> 100000 per bin mag.bin colors env. fields time steps

  16. Science vs. Parameterspace matrix Compile all science goals into one single surveyobservingstrategy

  17. Examples of spectroscopicsurvey design

  18. Which instrument for mysurvey ? • Imaging or spectroscopy ? • Needboth ! • Need more ?

  19. 14 Instruments at the VLT (and VLTI, VISTA, VST)

  20. Imaging cameras • Based on CCDs for the visible domain • Based on HgCdTearrays for 1-5 microns • Otherhybrid detectors in UV and to ~25 microns • Radio and sub-mm recievers • X-ray cameras • …. Key elements • Field of view • Wavelengthdomain • Spatial resolution • Throughput / Quantum efficiency

  21. Visible cameras: CFHT 3.6m+Megacam MegaCam: 256 millions pixels CFHT in Hawaii

  22. IR cameras: on 4m VISTA at ESO

  23. HST imaging ACS • The best resolution • The best sensitivity • The smallestfield WFC3

  24. Throughput for imaging cameras Many VLT Instruments (FORS1+2, ISAAC, NACO, VIMOS, VISIR) are camera which provide direct imagery through sets of filters. Optical filters, are interference filters, can be quite complex multi-layer coatings. Optical filters selectively transmits light in a given bandpass, while blocking the remainder.

  25. Limiting magnitudes: imaging Example of the COSMOS survey

  26. MOS: multi-objectspectrographs • A key invention for Cosmology ! • Principle: observe more than one objectat once • Multiplex Nobj • The multiplex islikehavingNobjtelescopeseachobserving 1 object • Different types of MOS • Multi-slit: betterskysubtraction • Multi-fiber: widefield • Multi-IFU: velocityfields Key elements • Field of view • Wavelengthdomain • Spectral resolution • Multiplex • Throughput

  27. Spectra, one by one E. Hubble

  28. Multi-object spectroscopy • Target selection • Multi-object spectroscopy • Deep multi-color imaging Today MOS have Nobj>> 100 Multiplies the efficiency of yourtelescope by Nobj !

  29. Multi-Object Spectrograph have become the work-horse of manyobservatories VIMOS • In all major observatories: CFHT-MOS/SIS, Keck-LRIS, VLT-FORS, GMOS, Keck-DEIMOS, VLT-VIMOS, IMACS … • Now going to the IR: MOSFIRE, VLT-KMOS DEIMOS IMACS FORS2

  30. VIMOS on the VLT VIMOS wasbuild by a consortium of french+italian institutes, led by LAM

  31. VIMOS • 4 tons • 80cm beam Optical train

  32. VIMOS: 1000 spectra in one shot Vertical trace: one galaxyspectrum Horizontal lines: night skyemission

  33. DEIMOS on Keck

  34. SDSS spectrograph

  35. MOS in the IR: MOSFIRE on Keck

  36. KMOS: a multiple IR IFU on the VLT IFU: Integral Field Unit

  37. Integralfieldspectroscopy: velocityfields MASSIV surveyat z~1.5 10kpc

  38. Instrument design and development • Instrument makingisfundamental to astrophysics • Relies on new & improvedtechnology • Optics, detectors, mechanics, control (active) • Spacetechnology • Software: data processing, databases • Professional projectdevelopment • Skilled instrument scientists and specialtyengineers • Project management • Expensivetelescopes (~1B€) and instruments (~15M€ ground-based / ~150M€ space-based)

  39. Instrument development cycle T0 T0+1y T0+2y T0+4y T0+5y T0+6-7y • Define science goals: science requirements • Survey volume, number of objects, redshift • Derive technical requirements • Field of view, wavelength, resolution, throughput • Global performances • Produce strawmanopto-mechanical design • Identify new technology developments: grating, detectors,… • Produce prototypes • Manufacture all parts • Assembly, integration and tests • Measure performances, calibrate • First light SPACE instruments: 2x longer !

  40. Example: a MOS for the EELT DIORAMAS Multi-slit Phase A completed in 2011 Call for tender: mid-2014 7y development First light 2022 ? 40

  41. Observationalmethods • Sampleselection • Observations preparation and follow-up • Measuring the sampleselectionfunction

  42. Sampleselection • Magnitude or flux selection • Colorselection • Color-colorselection • Photometricredshiftselection

  43. Magnitude / flux selection Observe all galaxies brighter than a limit Here: IAB≤24

  44. Colorselection • Apply a colorcut • Color=differencebetweentwophotometric bands • Here (magenta) select the red galaxies with Mu-Mr>1.4 • Can add a magnitude selection on top (green): select all red and bright galaxies

  45. Color-colorselection • Select objects in a part of a color-colordiagram • Most known: Lyman-break galaxyselection (LBG) • Hereisshown a gzKdiagram to select galaxies at z~2

  46. Lyman-break galaxyselection • Use predictedgalaxytracks vs. Redshift to isolate galaxies in color-colorspace Different types of galaxies z=3.4 z=2.7 z=0

  47. MOS observations preparation and follow-up • Produce a reference photometric catalog based on your selection • The “parent catalog” • Produce a list of objects to be observed in MOS • Based on geometric constraints of the instrument • Produce “Observing blocks” to be executed at the observatory

  48. Observing blocks at VLT

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