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Measuring structure — the power spectrum and the correlation function

The density field is described statistically. Its power spectrum P(k) says how much fluctuation there is on each scale, and the two-point correlation function ξ(r) — its Fourier transform — says how strongly galaxies cluster. Requiring every mode to enter the horizon with the same strength gives the scale-invariant (Harrison–Zel'dovich) spectrum P ∝ k (n ≈ 1), which the stagnation of early-entering modes bends over at small scales.

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Full reading path (48 pages)
  1. Vectors (8.01)
  2. Position and velocity in one dimension (8.01)
  3. Acceleration in one dimension (8.01)
  4. Motion in two dimensions and projectiles (8.01)
  5. The homogeneous expanding universe (8.286)
  6. The Doppler effect and special relativity (8.286)
  7. Cosmological redshift (8.286)
  8. Newton's laws of motion (8.01)
  9. The universal law of gravitation (8.01)
  10. Why a static universe cannot work (8.286)
  11. The expanding sphere and the equation for a(t) (8.286)
  12. The Friedmann equation (8.286)
  13. Open, closed and flat universes (8.286)
  14. The closed universe as a cycloid (8.286)
  15. The age of the universe and the Big Bang singularity (8.286)
  16. The age of a closed universe from H and Ω (8.286)
  17. The open universe and the age of any matter universe (8.286)
  18. Non-Euclidean geometry (8.286)
  19. The metric of a sphere and of a closed universe (8.286)
  20. Curvature and expansion — the Robertson–Walker metric (8.286)
  21. The geometry of open universes (8.286)
  22. The spacetime interval (8.286)
  23. The spacetime metric of the universe (8.286)
  24. The geodesic equation (8.286)
  25. Simplifying the geodesic equation (8.286)
  26. Falling into a black hole (8.286)
  27. Mass, energy and the dilution of radiation (8.286)
  28. Matter–radiation equality and the pressure of light (8.286)
  29. The horizon distance (8.286)
  30. The radiation-dominated universe (8.286)
  31. The cosmological constant and vacuum energy (8.286)
  32. The age of the universe with vacuum energy (8.286)
  33. How bright is a distant supernova? (8.286)
  34. The supernova evidence for acceleration (8.286)
  35. The puzzle of the vacuum energy, and Einstein's mistake about Friedmann (8.286)
  36. Black-body radiation (8.286)
  37. Neutrinos and counting particle species (8.286)
  38. The temperature of the early universe and decoupling (8.286)
  39. The horizon problem (8.286)
  40. The flatness problem (8.286)
  41. The Standard Model, gauge theories and grand unification (8.286)
  42. The Higgs field and spontaneous symmetry breaking (8.286)
  43. Topological defects and the magnetic monopole problem (8.286)
  44. The false vacuum and the mechanism of inflation (8.286)
  45. Exponential expansion, de Sitter space and the inflationary scenario (8.286)
  46. How inflation solves the problems of the Big Bang (8.286)
  47. How small ripples grow — linear perturbation theory (8.902)
  48. Why structure formation needs cold dark matter (8.902)
On this page · 7 sections
  1. Fourier modes and the variance
  2. The two-point correlation function
  3. Fluctuations on a given mass scale
  4. Why n ≈ 1: the Harrison–Zel'dovich spectrum
  5. The amplitude: σ₈ and bias
  6. The transfer function: bending the spectrum
  7. Summary

The previous pages followed one perturbation at a time. The real universe contains ripples on every scale at once, with random phases, so no theory can predict where a particular galaxy sits. What theory can predict is the statistics: how strong the fluctuations are on each scale. This page follows the end of the 8.902 Lecture 14 notes (section 2.C) and the start of Lecture 15 (section 2.D), where the notes introduce the power spectrum, the correlation function and the form of the primordial spectrum. [The Lecture 15 notes open by repeating p. 90 of the Lecture 14 notes; citations below use whichever PDF first contains the equation.]

Fourier modes and the variance#

Write the density contrast as a sum of plane waves, exactly as for the single modes on the earlier pages:

Fourier transform pair
δ(x⃗)=∫d3k(2π)3 δ^(k⃗) e−ik⃗⋅x⃗,δ^(k⃗)=∫d3x δ(x⃗) e+ik⃗⋅x⃗\delta(\vec x) = \int\frac{d^3k}{(2\pi)^3}\,\hat\delta(\vec k)\,e^{-i\vec k\cdot\vec x}, \qquad \hat\delta(\vec k) = \int d^3x\,\delta(\vec x)\,e^{+i\vec k\cdot\vec x}
In words

delta ( vector x ) equals the integral of d cubed k over (2 pi ) cubed delta hat ( vector k ) e to the power minus i vector k dot vector x , delta hat ( vector k ) equals the integral of d cubed x delta ( vector x ) e to the power plus i vector k dot vector x

By construction the average of δ\delta over space is zero — it measures departures from the mean density. The simplest non-trivial number is therefore the variance, the mean of δ2\delta^2:

Mean and variance
⟨δ⟩=0,σ2=⟨δ2⟩−⟨δ⟩2=⟨δ2⟩=∫d3k(2π)3 ∣δ^(k⃗)∣2\langle\delta\rangle = 0, \qquad \sigma^2 = \langle\delta^2\rangle - \langle\delta\rangle^2 = \langle\delta^2\rangle = \int\frac{d^3k}{(2\pi)^3}\,|\hat\delta(\vec k)|^2
In words

the average of delta equals 0, sigma squared equals the average of delta squared minus the average of delta squared equals the average of delta squared equals the integral of d cubed k over (2 pi ) cubed | delta hat ( vector k )| squared

Source: 8.902 Lecture 14 notes (M. Vogelsberger, Fall 2023), eqs. (403)–(404), p. 88

[The notes write the averages as plain integrals ∫d3x\int d^3x; an average needs a factor 1/V1/V, the volume, so strictly P(k)=∣δ^(k)∣2/VP(k) = |\hat\delta(k)|^2/V; the same applies to ξ\xi in eq. (408) below. The step to kk-space is Parseval's theorem.]

If the universe is statistically homogeneous and isotropic, ∣δ^∣2|\hat\delta|^2 can depend only on the length k=∣k⃗∣k = |\vec k|, not on direction, and d3k=4πk2 dkd^3k = 4\pi k^2\,dk. Then

Power spectrum
σ2=12π2∫∣δ^(k)∣2 k2 dk  =:  12π2∫P(k) k2 dk,P(k)=∣δ^(k)∣2\sigma^2 = \frac{1}{2\pi^2}\int|\hat\delta(k)|^2\,k^2\,dk \;=:\; \frac{1}{2\pi^2}\int P(k)\,k^2\,dk, \qquad P(k) = |\hat\delta(k)|^2
In words

sigma squared equals 1 over 2 pi squared the integral of | delta hat (k)| squared k squared dk equals : 1 over 2 pi squared the integral of P(k) k squared dk, P(k) equals | delta hat (k)| squared

using 4π/(2π)3=1/(2π2)4\pi/(2\pi)^3 = 1/(2\pi^2). The power spectrum P(k)P(k) says how much of the total variance sits in waves of wavenumber kk — that is, on length scales around 2π/k2\pi/k. Two remarks from the notes:

  • P(k)P(k) and σ\sigma change with time, because every δ^(k)\hat\delta(k) grows. In the linear regime all large-scale modes grow by the same growth factor DD from the earlier page, so σ=D σ0\sigma = D\,\sigma_0.
  • The starting point is the primordial power spectrum left at the end of inflation. Its general form is a power law,
Primordial power spectrum
P(k)=A knP(k) = A\,k^n
In words

P(k) equals A k to the power n

which has no preferred scale ("scale-free"). Inflation predicts n≈1n \approx 1; section 2.D below shows why that value is natural.

The two-point correlation function#

We cannot measure δ\delta for the dark matter directly, but we can count galaxies. Suppose galaxies trace the mass, with mean number density n0n_0. The probability of finding one galaxy in a small volume dV1dV_1 and another in dV2dV_2 a distance rr away is

Pair probability (averaged over positions)
dP=n0[1+δ(x⃗)] dV1⋅n0[1+δ(x⃗+r⃗)] dV2=n02 [1+ξ(r)] dV1 dV2dP = n_0[1 + \delta(\vec x)]\,dV_1 \cdot n_0[1 + \delta(\vec x + \vec r)]\,dV_2 = n_0^2\,[1 + \xi(r)]\,dV_1\,dV_2
In words

dP equals n sub 0 [1 plus delta ( vector x )] dV sub 1 times n sub 0 [1 plus delta ( vector x plus vector r )] dV sub 2 equals n sub 0 squared [1 plus xi (r)] dV sub 1 dV sub 2

On averaging, the terms linear in δ\delta vanish, and the product ⟨δ(x⃗) δ(x⃗+r⃗)⟩\langle\delta(\vec x)\,\delta(\vec x + \vec r)\rangle is left. It depends only on the distance rr (isotropy), and is called the two-point correlation function ξ(r)\xi(r). For a random (Poisson) scattering of galaxies ξ=0\xi = 0; ξ>0\xi > 0 means pairs at that separation are more common than random — the galaxies cluster.

Substituting the Fourier expansion twice and using ∫d3x ei(k⃗−k⃗′)⋅x⃗=(2π)3δD(k⃗−k⃗′)\int d^3x\,e^{i(\vec k - \vec k')\cdot\vec x} = (2\pi)^3\delta_D(\vec k - \vec k') collapses the double integral to a single one:

Correlation function and power spectrum
ξ(r)=⟨δ(x⃗) δ(x⃗+r⃗)⟩=1(2π)3∫P(k) eik⃗⋅r⃗ d3k\xi(r) = \langle\delta(\vec x)\,\delta(\vec x + \vec r)\rangle = \frac{1}{(2\pi)^3}\int P(k)\,e^{i\vec k\cdot\vec r}\,d^3k
In words

xi (r) equals the average of delta ( vector x ) delta ( vector x plus vector r ) equals 1 over (2 pi ) cubed the integral of P(k) e to the power i vector k dot vector r d cubed k

So ξ and P are a Fourier pair: the same information, one in real space and one in wavenumber space. (Here δD\delta_D is the Dirac delta, not the density contrast.) At r=0r = 0 the correlation function is just the variance, ξ(0)=σ2\xi(0) = \sigma^2.

Galaxy surveys find, over a wide range of separations, a power law:

Observed galaxy correlation function
ξ(r)≈(rr0)−1.8,r0≈5 h−1 Mpc\xi(r) \approx \left(\frac{r}{r_0}\right)^{-1.8}, \qquad r_0 \approx 5\,h^{-1}\ \text{Mpc}
In words

xi (r) is approximately ( r over r sub 0 ) to the power minus 1.8 , r sub 0 is approximately 5 h to the power minus 1 Mpc

The correlation length r0r_0 is where ξ=1\xi = 1: pairs are twice as common as random. (h≈0.7h \approx 0.7 is the Hubble constant in units of 100 km/s/Mpc.) Different kinds of object have different r0r_0, and more massive objects cluster more strongly: the notes quote ξcc≈20 ξgg\xi_{cc} \approx 20\,\xi_{gg} for the cluster–cluster compared with the galaxy–galaxy correlation function.

Computed from ξ(r) = (r/r₀)^(−γ), with the notes' r₀ = 5 h⁻¹ Mpc and γ = 1.8 as defaults, and the cluster curve 20 times higher. On log–log axes a power law is a straight line of slope −γ; it crosses ξ = 1 at r = r₀. (The marked point stays at the default r₀.)
Worked example

Reading a correlation function

Using ξgg(r)=(r/5 h−1 Mpc)−1.8\xi_{gg}(r) = (r/5\,h^{-1}\,\text{Mpc})^{-1.8}: (a) how many times more likely than random is a galaxy pair at 2 h−12\,h^{-1} Mpc, and at 20 h−120\,h^{-1} Mpc? (b) If ξcc=20 ξgg\xi_{cc} = 20\,\xi_{gg} with the same slope, what is the clusters' correlation length?

(a) Small and large separations

At 2 h−12\,h^{-1} Mpc: ξ=(0.4)−1.8=5.2\xi = (0.4)^{-1.8} = 5.2, so 1+ξ=6.21 + \xi = 6.2 times the random rate. At 20 h−120\,h^{-1} Mpc: ξ=4−1.8=0.082\xi = 4^{-1.8} = 0.082, only 8% above random. Clustering is strong on small scales and fades on large ones.

(b) Cluster correlation length

We need 20 (r0cc/5)−1.8=120\,(r_0^{cc}/5)^{-1.8} = 1, so r0cc=5×201/1.8=5×5.28≈26 h−1r_0^{cc} = 5 \times 20^{1/1.8} = 5 \times 5.28 \approx 26\,h^{-1} Mpc. Clusters are correlated over distances five times larger than galaxies.

Fluctuations on a given mass scale#

Section 2.D asks what nn and AA are. First, how big are the fluctuations on a given scale? Smoothing the field over a region of size RR removes waves shorter than RR, so roughly only modes up to kmax∼1/Rk_\text{max} \sim 1/R contribute (small kk = large scales):

Variance up to a maximum wavenumber
σ2≈∫0kmaxP(k) k2 dk=∫0kmaxA kn+2 dk∝kmax n+3  ⇒  σ∝k12(n+3)\sigma^2 \approx \int_0^{k_\text{max}} P(k)\,k^2\,dk = \int_0^{k_\text{max}} A\,k^{n+2}\,dk \propto k_\text{max}^{\,n+3} \;\Rightarrow\; \sigma \propto k^{\frac12(n+3)}
In words

sigma squared is approximately the integral of sub 0 to the power k sub max P(k) k squared dk equals the integral of sub 0 to the power k sub max A k to the power n plus 2 dk is proportional to k sub max to the power n plus 3 which gives sigma is proportional to k to the power one half (n plus 3)

(the integral converges at k=0k = 0 only for n>−3n > -3). A region of size RR holds a mass M∝R3∝k−3M \propto R^3 \propto k^{-3}, so k∝M−1/3k \propto M^{-1/3} and

Fluctuation amplitude versus mass
σ∝{k12(n+3)M−16(n+3)\sigma \propto \begin{cases} k^{\frac12(n+3)} \\[0.5ex] M^{-\frac16(n+3)} \end{cases}
In words

sigma is proportional to k to the power one half (n plus 3) ; or M to the power minus 1 over 6 (n plus 3)

Source: 8.902 Lecture 14 notes (M. Vogelsberger, Fall 2023), eqs. (411)–(412), p. 90

For n=1n = 1, σ∝M−2/3\sigma \propto M^{-2/3}: a region with 1000 times more mass has fluctuations 100 times smaller. Small masses fluctuate most — the root of hierarchical ("bottom-up") structure formation, in which small objects form first.

Why n ≈ 1: the Harrison–Zel'dovich spectrum#

Outside the horizon every mode grows. The notes' argument is that no mass scale should be special: every mode should have the same fluctuation strength σ\sigma at the moment it enters the horizon. What does that demand of nn?

The mass inside the horizon is Mh∝ρmrh3M_h \propto \rho_m r_h^3, with ρm∝(1+z)3\rho_m \propto (1+z)^3. The physical horizon grows as rh∝tr_h \propto t, i.e. as a2a^2 in the radiation era and a3/2a^{3/2} in the matter era, so

Horizon mass
Mh∝ρmrh3,ρm∝(1+z)3,rh∝{a2=(1+z)−2radiationa3/2=(1+z)−3/2matter  ⇒  Mh∝{(1+zh)−3radiation(1+zh)−3/2matterM_h \propto \rho_m r_h^3, \quad \rho_m \propto (1+z)^3, \quad r_h \propto \begin{cases} a^2 = (1+z)^{-2} & \text{radiation} \\ a^{3/2} = (1+z)^{-3/2} & \text{matter} \end{cases} \;\Rightarrow\; M_h \propto \begin{cases} (1+z_h)^{-3} & \text{radiation} \\ (1+z_h)^{-3/2} & \text{matter} \end{cases}
In words

M sub h is proportional to rho sub m r sub h cubed , rho sub m is proportional to (1 plus z) cubed , r sub h is proportional to a squared equals (1 plus z) to the power minus 2 when radiation ; or a to the power 3/2 equals (1 plus z) to the power minus 3/2 when matter which gives M sub h is proportional to (1 plus z sub h ) to the power minus 3 when radiation ; or (1 plus z sub h ) to the power minus 3/2 when matter

Source: 8.902 Lecture 14 notes (M. Vogelsberger, Fall 2023), eqs. (413)–(414), p. 90

Meanwhile, outside the horizon, σ\sigma grows like δ\delta — as a2a^2 in the radiation era and aa in the matter era (the super-horizon growth of the previous page):

Super-horizon growth of σ
σ∝δ∝{a2=(1+z)−2radiationa=(1+z)−1matter\sigma \propto \delta \propto \begin{cases} a^2 = (1+z)^{-2} & \text{radiation} \\ a = (1+z)^{-1} & \text{matter} \end{cases}
In words

sigma is proportional to delta is proportional to a squared equals (1 plus z) to the power minus 2 when radiation ; or a equals (1 plus z) to the power minus 1 when matter

[The notes print a3/2a^{3/2} for the matter case; (1+z)−1(1+z)^{-1}, which they also print, is aa, consistent with δ∝a\delta \propto a in the matter era.]

Take a mode of mass MM that enters during the radiation era, at redshift zhz_h. From the end of inflation, at zpz_p, until then it grows as a2a^2:

Amplitude at horizon entry (radiation era)
σ(zh)=σ(zp)(1+zp1+zh)2∝σ(zp) (1+zh)−2\sigma(z_h) = \sigma(z_p)\left(\frac{1+z_p}{1+z_h}\right)^2 \propto \sigma(z_p)\,(1+z_h)^{-2}
In words

sigma (z sub h ) equals sigma (z sub p ) ( 1 plus z sub p over 1 plus z sub h ) squared is proportional to sigma (z sub p ) (1 plus z sub h ) to the power minus 2

The primordial amplitude is σ(zp)∝M−(n+3)/6\sigma(z_p) \propto M^{-(n+3)/6} from eq. (412), and the mode enters when Mh=M∝(1+zh)−3M_h = M \propto (1+z_h)^{-3}, so (1+zh)−2∝M2/3(1+z_h)^{-2} \propto M^{2/3}:

Horizon-entry amplitude
σ(zh)∝M−16(n+3) M2/3=M−(12+n−46)=M−n−16\sigma(z_h) \propto M^{-\frac16(n+3)}\,M^{2/3} = M^{-\left(\frac12 + \frac{n-4}{6}\right)} = M^{-\frac{n-1}{6}}
In words

sigma (z sub h ) is proportional to M to the power minus 1 over 6 (n plus 3) M to the power 2/3 equals M to the power minus ( one half plus n-4 over 6 ) equals M to the power minus n-1 over 6

Source: 8.902 Lecture 15 notes (M. Vogelsberger, Fall 2023), eqs. (417)–(418), p. 91

For a mode entering in the matter era the notes say only that the calculation is the same, giving the same result (eq. 419). Filling in the step (this page's own): Mh∝(1+zh)−3/2M_h \propto (1+z_h)^{-3/2} gives (1+zh)−1∝M2/3(1+z_h)^{-1} \propto M^{2/3} again, and the earlier growth through the radiation era is the same factor for every such mode, so it does not change the MM-dependence. The last form, M−(n−1)/6M^{-(n-1)/6}, is this page's simplification of the notes' exponent. For the horizon-entry amplitude to be the same for every mass, the exponent must vanish: no special scale means n=1n = 1.

This is the Harrison–Zel'dovich (scale-invariant) spectrum, proposed around 1970 by Edward Harrison and Yakov Zel'dovich (and independently Peebles and Yu), before inflation. [The notes say σ(z_h) "should not depend on n"; the requirement is that it should not depend on MM, which then fixes nn.] Inflation, on the 8.286 pages, produces almost exactly this spectrum.

The amplitude: σ₈ and bias#

Inflation predicts the shape, but in practice the amplitude AA is measured. The standard yardstick is σ8\sigma_8, the rms density fluctuation in spheres of radius 8 h−18\,h^{-1} Mpc. Galaxies need not trace the mass exactly; their fluctuations differ by the bias bb:

Galaxy bias
σ8,gal=b σ8,mass\sigma_{8,\text{gal}} = b\,\sigma_{8,\text{mass}}
In words

sigma sub 8, gal equals b sigma sub 8, mass

Observed galaxies have σ8,gal≈1\sigma_{8,\text{gal}} \approx 1. The notes quote the combined WMAP and SDSS values

Measured index and amplitude (WMAP + SDSS, as quoted in the notes)
n=0.953±0.016,σ8=0.756±0.035n = 0.953 \pm 0.016, \qquad \sigma_8 = 0.756 \pm 0.035
In words

n equals 0.953 plus or minus 0.016, sigma sub 8 equals 0.756 plus or minus 0.035

So nn is close to 1 but slightly smaller — a small "tilt" that simple inflation models predict. Since the mass σ8\sigma_8 is below 1 while σ8,gal≈1\sigma_{8,\text{gal}} \approx 1, these galaxies are biased, b>1b > 1. (A standard explanation, not given in the notes: galaxies form preferentially in the higher peaks of the density field, and clusters, in the highest peaks, are even more biased.)

The transfer function: bending the spectrum#

The primordial spectrum is not what we see today. On the previous page, dark matter modes that entered the horizon during the radiation era stagnated until matter–radiation equality, while those entering later grew without interruption. Small scales entered earliest and lost the most growth. The notes describe this with a transfer function T(k)T(k):

Processed power spectrum
P0(k)=(A k) T2(k),T(k)≈{1,1/k≫L01/k2,1/k≪L0P_0(k) = (A\,k)\,T^2(k), \qquad T(k) \approx \begin{cases} 1, & 1/k \gg L_0 \\[0.5ex] 1/k^2, & 1/k \ll L_0 \end{cases}
In words

P sub 0 (k) equals (A k) T squared (k), T(k) is approximately 1, when 1/k is much greater than L sub 0 ; or 1/k squared , when 1/k is much less than L sub 0

where L0L_0 is the comoving horizon at matter–radiation equality, and n=1n = 1 has been used. [The notes write T(K)T(K); the second case is meant up to normalisation, T∝(kL0)−2T \propto (kL_0)^{-2}.] Large scales (k≪1/L0k \ll 1/L_0) entered after equality and keep the primordial P∝kP \propto k. Small scales are suppressed by T2∝k−4T^2 \propto k^{-4}, giving P0∝k−3P_0 \propto k^{-3}. The spectrum therefore rises, peaks near k0∼1/L0k_0 \sim 1/L_0, and falls — the turnover is a fossil of the moment matter took over from radiation.

Computed from P₀ = A kⁿ T²(k) with the interpolating form T = 1/(1 + (kL₀)²), which reproduces the notes' two limits T ≈ 1 and T ≈ (kL₀)⁻². With n = 1 the processed spectrum rises as k, peaks at kL₀ = 1/√3 ≈ 0.58 for this particular T, and falls as k⁻³. A schematic: the real transfer function, computed numerically, bends more gently (only logarithmic growth during stagnation).

Summary#

  • The density field is described statistically: σ2=12π2∫P(k) k2 dk\sigma^2 = \frac{1}{2\pi^2}\int P(k)\,k^2\,dk with the power spectrum P(k)=∣δ^(k)∣2P(k) = |\hat\delta(k)|^2. It grows in time as σ=Dσ0\sigma = D\sigma_0.
  • The two-point correlation function ξ(r)\xi(r) is the excess probability of finding pairs at separation rr; it is the Fourier transform of P(k)P(k). Galaxies show ξ≈(r/5 h−1Mpc)−1.8\xi \approx (r/5\,h^{-1}\text{Mpc})^{-1.8}; massive objects cluster more.
  • For P=AknP = Ak^n, σ∝M−(n+3)/6\sigma \propto M^{-(n+3)/6}, and the amplitude at horizon entry is ∝M−(n−1)/6\propto M^{-(n-1)/6}. Requiring no special scale gives the Harrison–Zel'dovich spectrum n=1n = 1; measurements give nn slightly below 1.
  • The amplitude is measured as σ8\sigma_8; galaxies are biased tracers, σ8,gal=b σ8,mass\sigma_{8,\text{gal}} = b\,\sigma_{8,\text{mass}}.
  • Stagnation of modes that entered the horizon before matter–radiation equality bends the spectrum: P0=Ak T2(k)P_0 = Ak\,T^2(k) rises as kk on large scales and falls as k−3k^{-3} on small ones, peaking near the horizon scale at equality.

Symbols on this page

Show the 28 symbols used here
γ\gamma gamma
The slope of the correlation function, ξ ∝ r^(−γ). Say it: “gamma”.
δ\delta delta
The density contrast, δ = (ρ − ρ̄)/ρ̄; δ_D (with subscript D) is the Dirac delta. Say it: “delta”.
ξ\xi xi
The two-point correlation function ξ(r): the excess chance of finding two galaxies a distance r apart. Say it: “xi” (sounds like “ksee or zye”).
π\pi pi
The ratio of a circle's circumference to its diameter, π ≈ 3.14159. Say it: “pi”.
ρ\rho rho
Density: mass (or energy divided by c²) per unit volume. ρ_c is the critical density, ρ̄ the mean density. Say it: “rho”.
σ\sigma sigma
The rms density fluctuation; σ₈ is its value in spheres of radius 8 h⁻¹ Mpc. Say it: “sigma”.
≈\approx approximately equal
Is approximately equal to. Say it: “is approximately”.
∼\sim tilde (similar)
Is of the order of: roughly equal, to within a factor of a few. Say it: “is of order”.
∝\propto proportional to
Is proportional to: doubling one doubles the other. Say it: “is proportional to”.
≪\ll much less than
Is much less than. Say it: “is much less than”.
≫\gg much greater than
Is much greater than. Say it: “is much greater than”.
⇒\Rightarrow implies
Implies: what follows is a consequence of what came before. Say it: “which gives”.
±\pm plus or minus
Plus or minus: both signs, or an uncertainty (67.3 ± 1.2). Say it: “plus or minus”.
×\times times
Times (multiplication). Between two vectors: the cross product. Say it: “times”.
⋅\cdot dot
Times (multiplication). Between two vectors: the dot product. Say it: “times”.
⟨\langle angle brackets
The average (mean value) of what is inside, ⟨…⟩. Say it: “the average of”.
∫\int integral
Integral: the sum of infinitely many small pieces, such as the area under a curve. Say it: “the integral of”.
v⃗\vec v vector arrow
A vector: a quantity with a size and a direction. Say it: “vector”.
ı^\hat\imath hat
A Fourier-transformed quantity, such as δ̂(k) or Ŵ(k). Say it: “hat”.
aa a
The scale factor a(t): how much the universe has expanded (a = 1 today, 1/(1 + z) in the past). Say it: “a”.
zz z
Redshift: 1 + z = a(observed)/a(emitted), how much the universe has stretched since the light left. Say it: “z”.
cc c
In r₀^cc the letters cc label cluster–cluster correlations; elsewhere c is the speed of light. Say it: “c”.
kk k
The (comoving) wavenumber of a Fourier mode: waves of length 2π/k. Say it: “k”.
TT T
The transfer function T(k): how much each mode's growth was held back. Say it: “T”.
ρm\rho_{m} matter density
The mass density of matter (dark matter and baryons). Say it: “rho m”.
σ8\sigma_{8} sigma eight
The rms density fluctuation in spheres of radius 8 h⁻¹ Mpc: the standard measure of how clumpy matter is (about 0.8). Say it: “sigma 8”.
nsn_{s} spectral index
The spectral index (tilt) of the primordial power spectrum, P ∝ kⁿ; measured n_s ≈ 0.965. Say it: “n s”.
kmaxk_{\text{max}} maximum wavenumber
The largest wavenumber included: a cut-off at the smallest length scale. Say it: “k max”.

Tap or click a symbol in a formula to see the same explanation. All symbols: symbols and notation.

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Check your understanding

  1. How is the power spectrum P(k)P(k) related to the Fourier modes δ^(k)\hat\delta(k) of the density contrast?
  2. Galaxies have ξ(r)≈(r/r0)−1.8\xi(r) \approx (r/r_0)^{-1.8} with r0≈5 h−1r_0 \approx 5\,h^{-1} Mpc. What is ξ\xi at r=10 h−1r = 10\,h^{-1} Mpc?
  3. For a primordial spectrum P∝knP \propto k^n, how does the rms fluctuation on mass scale MM scale?
  4. Why is n=1n = 1 (the Harrison–Zel'dovich spectrum) special?
  5. Why does the present-day matter power spectrum turn over at small scales?
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