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Sandbox Physics
Galaxy colors from photons to redshift distributions

L1 · Galaxy photometry

Why a red galaxy can have several possible distances

A galaxy can look red because its light has travelled through an expanding universe, because its brightest blue stars have died, or because dust has removed much of its blue light. A red photograph leaves all three possibilities open. The useful clue is how the brightness changes from one carefully chosen color to the next.

A photograph adds together many wavelengths

Imagine photographing the same galaxy through five colored windows. Each window lets through a different, overlapping range of wavelengths. The camera adds the photons that get through; it does not keep a little label saying which wavelength each photon had. Astronomers call such a window a filter. The result is five brightness measurements, a very compressed description of the incoming light.

The full distribution of light across wavelengths is its spectrum. Two spectra can produce nearly the same five measurements even when their fine details differ. This is why a beautiful color image can give a much less definite distance than a spectrum containing recognizable narrow lines. More detailed measurements cost observing time, especially for faint galaxies.

Reading: Doi et al. · Brammer

Expansion moves features; it does not paint everything red

As the universe expands, travelling light stretches to longer wavelengths. The redshift tells us the stretch factor. A feature emitted near four thousand Angstrom arrives near six thousand Angstrom when the redshift is one half. An Angstrom is one ten-billionth of a metre; visible light occupies several thousand of them.

Many galaxy spectra have a broad change in brightness near four thousand Angstrom. Numerous absorption lines in stellar atmospheres suppress the light on its blue side. As this change crosses a pair of filters, one filter begins to receive light from a different side of the feature. Their brightness ratio can change appreciably. The position of a recognizable change carries more distance information than the statement that the whole galaxy is red.

λobserved=(1+z)λemitted\lambda_{\mathrm{observed}}=(1+z)\lambda_{\mathrm{emitted}}
Here z is redshift and both wavelengths use the same units. A redshift of one half stretches every wavelength by a factor of one and a half.

Reading: Hogg et al. · Bruzual & Charlot

Young stars behind dust can resemble old stars

Massive, hot stars shine strongly in blue light and use their fuel quickly. After a brief episode of star formation, these stars disappear first. Longer-lived stars then supply a redder mixture of light. Changing the mixture also changes the absorption features; the strength of the four-thousand-Angstrom break depends on the population and its chemical composition.

Dust offers another route. Small grains absorb and scatter light, generally reducing the short-wavelength signal more strongly. A young galaxy behind enough dust can have broad-band colors like those of an older, clearer galaxy. Dust changes the slope smoothly across these optical filters; redshift moves the features along the wavelength axis. Five broad measurements can blur that distinction.

The age of a real galaxy is also more complicated than one birthday. New stars may keep forming among old ones. A model in which all stars formed at once is useful for seeing how a spectrum changes with time, but its fitted age describes that model. A real age estimate therefore requires an explicit account of how stars formed over time.

Reading: Bruzual & Charlot · Calzetti et al.

Several distances can survive the same measurement

An astronomer tests many trial redshifts, stellar mixtures and dust amounts. Each trial predicts five filter brightnesses. Trials close to the measured values receive more weight, with the measurement errors setting how close is close enough. Adding the weights of the different stellar and dust explanations produces a probability distribution over redshift.

Sometimes this distribution has two separated hills. One hill may describe an older nearby population; another may move a different spectral shape farther away. Reporting only the tallest hill hides the other explanation. A small calibration change can even swap which hill is tallest, although the measurements have changed very little.

A useful extra filter measures the wavelengths where the competing spectra disagree. A spectrum can identify individual lines and settle the distance more directly. The task is to find the next observation that separates the surviving explanations. That is how a set of colored pictures begins to become a map with depth.

Reading: Brammer · SDSS DR17 imaging fluxes and flux calibration

Try the observation

Compare a dusty young galaxy with an old population

  1. Compare the Young stars behind dust and An old stellar population presets. Notice how similar colors arise from different spectra.
  2. Return to the default and turn off the blue detector. Follow the second hill in the probability curve as the highest peak changes.

Sources and calculation scope

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

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