AC04 · Galaxy photometry
Galaxy colors from photons to redshift distributions
A red photograph leaves several explanations open. Follow the light from a stellar population through dust, expansion and measured filters. Then ask how five uncertain fluxes become several possible redshifts, and how a real survey checks them.
Why a red galaxy can have several possible distances
Redshift, old stars and dust all redden galaxies. Follow a spectral break through five filters to see how astronomers separate them.
02 · L1What a filter measures when a detector counts photons
Derive photon-weighted AB fluxes from spectral densities, keep wavelength units straight and calculate a real SDSS filter count rate.
03 · L2Redshift stretches a spectrum and dust reshapes it
Derive frequency and wavelength redshift factors, a flat-spectrum K correction, and a rest-frame dust model with explicit stellar-age assumptions.
04 · L3Keep both answers when a redshift distribution has two peaks
Build a normalized multimodal redshift posterior, integrate a positive amplitude exactly and distinguish peak height from probability mass.
05 · L3Reproduce redshift distributions for twenty-four real SDSS galaxies
Use fixed SDSS DR17 fluxes, negative measurements and withheld spectroscopic redshifts to reproduce a small photo-z validation with failure cases.
06 · L4Read EAZY and a Euclid calibration paper with the selection visible
Follow pinned EAZY sections and Euclid 2026 figures to separate template fitting, posterior summaries and population redshift calibration.
Sources and calculation scope
- Hogg et al., The K correction, astro-ph/0210394v1 (2002)
Equations (2)–(12): spectral densities, photon response, redshift factors and the AB K correction. We use luminosity distance and define wavelength densities per Angstrom.
- Doi et al., Photometric Response Functions of the SDSS Imager, arXiv:1002.3701v1 (2010)
Table 4 response curves as distributed by speclite at commit 8159ea61f1c8539136660b4c2e87fbbf94a70097. The sdss2010 quantum throughputs already include an atmosphere at airmass 1.3; source files and BSD notice are retained.
- Bruzual & Charlot, Stellar population synthesis at the resolution of 2003, astro-ph/0309134v1
Sections 2–3 describe the stellar-population model and its spectral evolution. The frozen solar-metallicity Salpeter SSP file is distributed by EzGal; this course fixes its model choices rather than inferring a general galaxy age.
- EzGal model distribution, commit 133c62b383fae964701b673e62517293161b41d5
tests/data/bc03_ssp_z_0.02_salp.model, primary image and the vs/ages FITS tables. README acknowledgements explicitly describe the model authors’ redistribution permission; the repository MIT notice is retained. Spectra are converted from fnu at ten parsecs into relative shapes.
- Calzetti et al., The Dust Content and Opacity of Actively Star-forming Galaxies, astro-ph/9911459v1 (2000)
Section 3.3, equations (2)–(5): empirical starburst stellar-continuum attenuation from 0.12 to 2.2 microns, with RV=4.05. The stellar continuum color excess differs from that of nebular gas.
- SDSS DR17 imaging fluxes and flux calibration
The AB-offset and physical-flux sections state the approximate u shift, tentative z shift and their uncertainties. The tutorial freezes TOP 24 clean primary GALAXY spectra with zWarning=0 ordered by specObjID, keeping linear modelFlux values and inverse variances.
- SDSS public-release use and acknowledgement policy
The released catalogue is public data. Credit the Sloan Digital Sky Survey and its collaboration; the tutorial uses catalogue numbers, not survey images.
- Brammer, van Dokkum & Coppi, EAZY: A Fast, Public Photometric Redshift Code, arXiv:0807.1533v1 (2008)
Sections 2.1–2.5: template combinations, template error, priors and output redshifts. Section 3.3 and section 4, especially Figures 8–11, connect the error model and priors to real validation. Our finite SSP posterior is a separate teaching calculation.
- EAZY manual and source, commit f651e94d91042a84906090a66d2a3fec75504e21
Read doc/eazy_manual.tex alongside the pinned paper. Record the filter file indices and the selected definition of z_peak or marginalized output before comparing catalogues. The course does not redistribute its HDFN catalogue or default templates.
- Euclid Collaboration, Improving redshift distribution reconstruction using a deep-to-wide transfer function, arXiv:2601.02005v1 (2026)
Sections 2.1–2.3 define transfer and selection; sections 3.1–3.2 define the Flagship 2.1 mock validation and color-cell calibration. Figures 5–6 compare distribution calibration. These are simulation tests, not a reproduced Euclid sky measurement.