Discussion Session 5: Christian Wolf Should we invest more into photo-z or spectroscopic surveys? - PowerPoint PPT Presentation

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Discussion Session 5: Christian Wolf Should we invest more into photo-z or spectroscopic surveys? PowerPoint Presentation
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Discussion Session 5: Christian Wolf Should we invest more into photo-z or spectroscopic surveys?

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Discussion Session 5: Christian Wolf Should we invest more into photo-z or spectroscopic surveys?
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Discussion Session 5: Christian Wolf Should we invest more into photo-z or spectroscopic surveys?

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  1. Discussion Session 5:Christian WolfShould we invest more into photo-z or spectroscopic surveys?

  2. Exposure Times • Well established 8-m instrumentation (last ~5 years) • VLT 8m + VIMOS • Subaru 8m + SuprimeCam Method z Accuracy Exposure time Broad-band photo-z 0.03 1 Medium-band photo-z 0.01 5 Spectroscopy <0.001 50-100 More area / depth for less precision

  3. Global galaxy evolution 1999+: optical HiFi photo-z, e.g. COMBO-17: 104.5 obj. Now: Focus on environment needs z/(1+z) ~ 0.001 At z > 1 not at Poisson limit Flux-calibrated photometry SED from constant physical footprint, while PSF = f() Large-scale structure Photo-z: 2D in z slices Volume selection for spectroscopic surveys Efficiency increase Super-cluster environments Try FMOS / FAST-SOUND at z = [1.3,1.7] without pre-selection (success <10%?) Weak gravitational lensing Need accurate z distribution 2010+ lensing surveys want bias z/(1+z) ~ 0.001 Huge training effort (spec!) Photo-Z Attractive For… Stand-alone Cross-fertilization

  4. Dis- / Advantage Property PhotometrySpectroscopy Area / depth + Z accuracy + SED accuracy + Z reliability ~ ~ Blended objects (+)

  5. Improved SED analysis Spectroscopic redshift prior Rest-frame SED known:age and dust more reliable Talk by Christian Wolf Improved composite stellar population analysis Line indices & SED together break some degeneracy Fix old population better and see young population as left-over SED difference Talk by Daniel Thomas Kinney et al. templates 25% z outliers Age  Abell 901 z ~ 0.17 Dust  Combine SEDs + Spectra