Cosmic microwave background acoustic peaks
Connect coherent photon–baryon oscillations to angular spectra while distinguishing acoustic geometry, transfer physics, and cosmic variance.
On this page
The question for today
What you’ll understand
- Relate an ideal acoustic phase to a projected angular scale.
- Distinguish the acoustic angular scale from the exact first peak location.
- Compute cosmic-variance limits under stated Gaussian and sky-coverage assumptions.
The microwave sky records oscillations that were at different phases when photons last scattered. A coherent relation between those phases creates a sequence of peaks in angular power rather than one preferred temperature on the sky. Reading that sequence requires both a model for the early photon–baryon fluid and a projection through the background geometry. We will first strip the system down to an ideal oscillator, then restore the physical effects that prevent a peak from being a direct ruler measurement independent of all other parameters.
An oscillator explains coherence, not the entire spectrum
In a tightly coupled photon fluid with constant sound speed and no gravitational driving, a Fourier temperature perturbation obeys a harmonic oscillator equation in conformal time. Initial displacement with negligible velocity produces a cosine phase. Modes whose sound-horizon phase reaches an integer multiple of pi are at extrema at last scattering. Their squared amplitudes therefore form a harmonic sequence in this idealization. A random unrelated phase for every mode would erase this simple coherent pattern.
Real baryons add inertia and shift the equilibrium in gravitational potentials, affecting compressions differently from rarefactions. Evolving potentials drive oscillations, radiation and neutrinos affect phases, and photon diffusion damps small scales. A finite visibility width and Doppler terms further modify the observed spectrum. These effects are computed through coupled perturbation and radiative-transfer equations. The elementary oscillator identifies a mechanism but cannot determine baryon density or the complete spectrum from its period alone.
Projection and transfer produce parameter degeneracies
An angular multipole roughly corresponds to a transverse wave number times the distance to last scattering. This gives an acoustic spacing near pi times distance divided by sound horizon. Phase shifts and projection mean that the exact first temperature peak is not simply ell A. Different background and early-time parameter combinations can preserve the acoustic angular scale. Peak heights, damping, polarization, lensing, and external data help distinguish combinations that one angular ruler cannot separate.
Temperature maps also contain foreground emission, instrumental beams, noise, and calibration uncertainty. A likelihood must predict the observed spectra through those effects, with appropriate nuisance parameters and masks. Angular spectra describe ensemble variances, whereas the measured sky supplies only one realization of each multipole’s finite number of modes. More sensitive detectors can reduce instrumental noise, but cannot produce extra independent full-sky realizations of the same primordial temperature field.
Cosmic variance is an ensemble statement
For a Gaussian statistically isotropic field, the full-sky multipole coefficients have variance C ell, and the estimated power has a chi-squared sampling distribution. At low multipoles that distribution is appreciably asymmetric, so a Gaussian error bar is only a summary. Cosmic variance describes uncertainty in recovering an ensemble power from one sky; it is not a claim that the measured map changes randomly when a telescope points at it again.
A mask removes information and mixes angular modes. Dividing a naive mode count by the sky fraction offers intuition for error inflation but does not reproduce every cut-sky covariance or foreground-induced bias. Survey geometry, multipole binning, anisotropic noise, and cross-spectra all matter. Inference of a late-time parameter such as H zero from CMB spectra additionally assumes a cosmological model connecting the measured angular and physical scales. That dependence must accompany any quoted numerical result.
Work it through
Project an ideal acoustic ruler
In a synthetic flat model take last-scattering sound horizon r s = 100 Mpc and transverse comoving distance D M = 10000 Mpc. Find theta star, ell A, and the first nonzero extremum wave number of the ideal cosine. Increase only D M to 12000 Mpc and find the new ell A.
The angular ratio is radians, so . This is the acoustic spacing scale, not an exact prediction for the first measured temperature peak.
The first nonzero extremum satisfies , giving . Positive and negative temperature extrema both contribute peaks in squared amplitude.
The increased distance gives and . At fixed physical ruler, a larger distance shifts the ideal pattern toward higher multipoles and smaller angles.
The initial acoustic scale is 100π, the ideal first extremum has k = π/100 Mpc⁻¹, and increasing the distance gives ell A = 120π.
The living notebook
Explore the model
Interactive lab · oscillator
Compare ideal acoustic phases
Reset, set Damping ratio ζ = 0 and Natural frequency ω₀ = 1, and predict period 2π. For a fresh comparison Reset, set ζ = 0 and ω₀ = 2, and predict period π. Use Play or Step from each fresh start to compare phase advance.
- Displacement x(t)
- 1
- Velocity v(t)
- 0
- Regime
- underdamped
Unit mass, x(0) = 1 and v(0) = 0. The analytic solution includes underdamped, critically damped and overdamped cases; time is measured in seconds. Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.
Look forThe unit-mass oscillator has initial displacement one and velocity zero. It illustrates coherent phase only; it has no expansion, baryon loading, gravity, recombination, or projection into CMB multipoles.
Pause & reason
Check your understanding
Your turn
Try it yourself
For an ideal noise-free Gaussian full sky, let ell = 12 and C ell = 50 square microkelvin. Compute the standard deviation of its power estimate. What does the simple sky-fraction approximation give for f sky = 1/2, and why is that second answer not a complete cut-sky likelihood?
Take a moment to make a prediction or work it out on paper. Open a hint when you need one.
Give me a hint
There are 25 full-sky m modes, and the approximate mask penalty is the inverse square root of sky fraction.
Compare with the solution
Full-sky uncertainty is square microkelvin. The half-sky approximation multiplies this by square root two, giving 20 square microkelvin. A real mask mixes multipoles, and low-multipole power has a non-Gaussian sampling distribution, so this single error estimate does not specify the actual likelihood.
Keep the idea
Take it with you
- Coherent acoustic phases explain a peak sequence within a declared approximation.
- Angular geometry and early-time transfer physics must be inferred together.
- Cosmic variance persists when instrumental noise vanishes, and masks require covariance modeling.
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