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The topic of "Power Spectrum" involves many intermingling concepts. This "Introduction" is an attempt to clarify the ideas before going into the details. It can also serve as a brief summary for those who do not want to go into the nitty gritty of the subject. It covers 2 different cosmic structures, namely, the CMB (Cosmic Microwave Background) and CDF (Cosmic Density Fluctuation). They may look different, but basically from the same "Quantum Fluctuations" at the very beginning of the Universe. Their theoretical foundations also share the same kind of formalism. |
Table 00 Introduction to Power Spectrum and Beyond [view large image] |
K. It is plotted in galactic coordinates which presents a two dimensional view of the whole sky. ![]() |
looks homogenous (almost the same color at every point) showing low correlation between the color of any 2 points; while the CDF image displays marked difference between the wall and void of the galactic clusters meaning high correlation (or fluctuation). This is somewhat similar to the Pearson Correlation between 2 points (x and y in Figure 00a) with the coefficient R = 1 for prefect correlation and R = 0 for no correlation. |
Figure 00a Pearson Correlation |
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. The corresponding formula for the 2-point correlation function in Table 00 is the equivalence of Fourier transform (Figure 00b) but in terms of the multipole moment . The C is essentially the amplitude of the Fourier component andP (cos ) the phase. (k) is the amplitude and sin(kr)/kr is the phase. |
Figure 00b Fourier Transform [view large image] |
For zero separation, the correlation becomes variance of the function. Then P (cos ) = 1, and sin(kr)/kr = 1 for CMB and CDF respectively. It represents the statistical variance of each point in the sky map. |
value for a given multipole moment
from the huge volume of data.
and sky map of tiny temperature variation. The CDF observation is in density fluctuation; r is identified to the size of the astronomical system (e.g., cluster of galaxies, the galaxy is the basic unit in this case).![]() |
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Figure 00c CMB |
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Figure 00d CDF Simulation |
Figure 00d is a computer simulation, see Figure 10 or column 4, Table 00 for measurement in density fluctuation (r). See Figure 10a for an illustration of the relationship between density fluctuation and two-point correlation function. |
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The two-point correlation function in statistics can be defined as the probability of relating (multiplying) a function f(x) to another function f(y) at the spatial vector r in excess of the random distribution (Figure 01a1). This statement is valid only when it is averaged over a large number of such configurations in space. It is expressed as < f(x)f(y) > in mathematical notation and sometimes denoted as (x,y) or (r). The amplitude f(k) in the Fourier transform to k-space (k = 2 / ) of the two-point correlation function with r = 0 (or x = y) is related to the Power Spectrum. Following is a brief sketch of the mathematics involved. BTW, the formulas become simpler in cosmology, which assumes an isotopic (rotational invariance) and homogeneous (translational invariance) mass-energy distribution so that the formulas depend only on the distance r and the absolute value of k, i.e., k = |k|.
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Figure 01a1 |
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Figure 01a2 Bessel Function, |
![]() where j 0(kr) = sin(kr)/kr is the Spherical Bessel Function of the First Kind (Figure 01a2). |
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Figure 01a4 Power Spectrum Evolution [view large image] |
in which, n = ns and A = As. |
as an indicator for fluctuation, uncertainty, spread, ... of the measurements on certain variable x,
where
is the mean (average) value, and N the total number of measurements. See a graphic illustration in Figure 03a in which f(x)dx = (ni/N)dx where ni is the number of measurements within the range dx at xi.
(x) = [d(x) - d0] / d0, where d0 is the average value. Then the correlation
(r) = <
(x)
(y)>. The fluctuation (when r = 0) can be the matter density
, the temperature T, or the gravitational potential
. For the cases of
and T, the correlation can be measured
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directly from observation of the fluctuations. In fitting observational data, it is often assumed a particular form of the Power Spectrum P(k) = Akn. The power index n = 1 is found to be suitable for CMB data. Such form can also prevent the divergence of the gravitational potential fluctuations on both large and small scales. The primordial fluctuation is heavily modified on the short wave portion once the matter and radiation de-coupled at cosmic age of about 0.3 Myr corresponding to the Hubble horizon dH ~ 10 Mpc (in comoving distance scale to remove the effect of cosmic expansion). Examples of the CMB and density power spectrums, and correlation function are illustrated in Figure 01a5,a,b. |
Figure 01a5 Power Spectrum |
CMB Data Reduction (2019 Edition)
CMB discovery via 1% of the TV static, circa 1964.
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Figure 01a6 |
The 22 LFI horns are arranged around the edge of the HFI instrument, as shown by the insert in upper left of Figure 01a6, the insert on the upper right is the PLanck satellite in action at L2. |

/
is 0.2 for LFI and 0.33 for HFI.
,
and a 1080p HD TV screen shot
.![]() |
The pixels are then arranged to match the elliptical shape of the map similar to the TV screen pixel format such as 1920x1080 (width x height), but with a varying width for the CMB map. With the monopole, dipole, and Milkyway foregrounds removed (see "CMBR Fluctuations"), the 9 frequency bands are merged into one map, in which the data for each pixel would contain contributions from all 9 frequency bands (Figure 01a7,b). It is the task in the next step to plot the data as a function of frequency (or its equivalance of wavelength , wave number k=2 / , or multipole number ).
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Figure 01a7 CMB Data Reduction |
The very large CMB data sets requires innovative tools of analysis. The followings introduce a noval techniques that has been used since the early days of CMB researches. |
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Figure 01a8 Bayesian Probability |
In application of the theorem to pixelize the CMB time ordered data (TOD), "H" is identified to the TOD dt and "D" to the signal sp (see "Bayesian Monte Carol" for more details). |

(x) = f(x,
) applies the Bayesian methodology to treat p =
as running variable with x at a fixed value.
= sp then it is "believed" that the noise nt would take the role of variance
. However, since the noise is random, it has to be treated as part of the data such that
i = nt. The formulation is more complicated, in term of the likelihood function with
assuming the role of independent variable, the equation can be written in multivariate Gaussian :
/
). Figure 01a14 is an example to
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translate a musical signal into fundamental and harmonics. It demonstrates the virtue of FT to turn a mumble-jumble signal into something tangible. However, this is not exactly the process to generate a power spectrum as the FT can generate negative coefficients. A power spectrum is closely related to the optical spectrum but in unit of power instead of power/area. Its mathematical derivation is shown in the previous section on "correlation". It is actually the |
Figure 01a13 Spectrum from Prism [view large image] |
Figure 01a14 Fourier Transform of Musical Signal |
Fourier transfrom of the "variance" and also shows the presence of positively defined fundametal and harmonics (see Figure 01a7,c). |
(x) = [y(x) - y] / y, where y is the average. The CMB power spectrum is defined somewhat differently with f(x) =
(x) = [T(x) - T] as the millionth temperature difference at point x to its average. Thus, the power spectrum P(k) has the dimansion of millionth temperature squared, i.e., (
Ko)2. Even though it is positively defined and temperature is proportional to energy as E ~ kBT, such unit is only remotely related to power (= energy/sec) creating lot of confusion for perplexing novice: "where the heck is the power"? A more appropriate designation would be something like "Temperature Variance Spectrum" (or "TV Spectrum", no pun intended).![]() |
Actually, the CMB power spectrum (now denoted as C instead of P(k)) is a function of the multipole number instead of k (see "Observational Data"). Figure 01a15 shows three views of the temperature variation at different angular scales ~ 180o/ . The wavy curve is a theoretical model of the power spectrum C based on several parameters such as the total cosmic density, the baryon density (luminous matter) and the Hubble's constant as explained in more details below. There are literally millions of such models. The task is to obtain one that is best fit to the observational data. The shape of the power spectrum in Figure 01a15 can be separated into sections corresponding to different underlying physical processes (since the matter-radiation de-coupling) as summarized below: |
Figure 01a15 CMB Power Spectrum [view Large Image] |
s. Anisotropies at this scale have not evolved significantly, and hence directly reflect the "initial conditions".
s, corresponding to scales smaller than that subtended by this thickness. The damping cuts off the anisotropies at multipoles above ~ 2000.![]() |
In actual practice, the power spectrum is derived by the likelihood function as described earlier. It is also based on the assumption of Gaussian distribution, but the various terms carry different meaning as shown below. Starting from the temperature variation as the sum of Spherical Harmonics, the likelihood function for this particular case is expressed as: |
Figure 01a16 Galactic Coordinates [view large image] |
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Figure 01a17 Band Power Spectrum [view large image] |
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See Figure 01a16 for illustration of the Galactic corordinates and its relationship to various CMB temperature definitions, and Figure 01a17 for a spectrum produced by Band Power from the observations of Planck and SPT. The likelihood function in Eq.(1j) now considers the temperature variation
i as parameter and the variance ( i)2 becomes the running variable to determine the maximum . Figure 01a18 shows a series of likelihood variations as a function of ( +1)C /2 and the location of the maximum by numerical computation.
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Figure 01a18 Likelihood Power Spectrum [view large image] |
Note that (2 +1)C /4 ~ ( +1)C /2 per for > > 1. The (2 +1) is related to the number of m states for each and it is also part of the normalization constant for Y m; while - ( +1) is the eigenvalue for r2 2Y m = - ( +1)Y m. See "Spherical Harmonics". |
, p
) is the methematical tool to derive the theoretical power spectrum of CMB. The following provides a very brief summery of the formation.![]() |
![]() The temperature T was about 3000 K at the time of the CMB formation (Figure 01a19). |
Figure 01a19 Black Body Spectrum [view large image] |
A full-fledged General Relativity treatment would involve the space-time metric g![]() determined by the GR field equation, and the geodesic equation (the GR version of the equation of motion, i.e., F = ma). The collision term C[f] is evaluated from the Compton scattering process (p) + e-(q) (p') + e-(q'). See "Boltzmann Equation" for details. |
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Figure 01a20 Optical Depth Effect |
Essentially, the l-h-s of Eq.(1k) is related to gravitational interaction, while those terms on the r-h-s modify its appearance through -e- Compton scattering in the intervening space. |
is the dominant factor for the collison effect on the r-h-s of Eq.(1k). It is defined by :
= 0 for no scattering; otherwise Rt < Ri, the power spectrum is distorted or flattened as shown in Figure 01a20. In the absence of gravitational variations and other effects, Eq.(1k) shows that
=
0 e-
.
+
= constant is conserved or
. This is known as SW (Sachs-Wolfe) Plateau, which reflects the initial condition when the power spectrum is flat, i.e., P(k) = Askns-1, with ns ~ 1. In such circumstance, both temperature and gravitational variations are proportional to 
(the density fluctuation). The origin of CMB sound wave can be derived by applying the equation of continuity and Euler's equation for compressible fluid (see "Navier-Stokes Equations"):![]() |
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Figure 01a21 CMB Formation |
The acoustic oscillations (or Doppler peaks) determine 6 cosmic parameters : k, ![]() , cd, b, f , and the Hubble constant H0. See a list of the 10 parameters, also "Baryon Acoustic Oscillations (BAO)" and "Generation of CMBR". |
=
0R(t)[1+
(t)] which is non-zero even in the absence of gravitational fluctuation.![]() |
![]() The likelihood function is computed numerically for different values of a given parameter. A particular value corresponding to the likelihood maximum is chosen (see Figure 01a7,d). |
Figure 01a22 Cosmic Parameters [view large image] |
Figure 01a22 illustrates the variation of the power spectrum model with the increasing value of the parameter. |
(click image to access video); also check out "Max's Cosmic Cinema"
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Figure 02 Acoustic Oscillations |
(x) can be expressed by the Fourier series:
(x) =
k{Gk cos(kx)} ---------- (1)
/
,
is the wavelength. The coefficient Gk can be calculated from the inverse relation:
{
(x) cos(kx)}, where the sum is over all x. For a given value of k, its harmonics are 2k, 3k, ...; k is called the fundamental mode. Thus, the CMBR power spectrum depends on the phase of the k-waves, i.e., cos(kx) as well.
(as shown in the WMAP map) or its Fourier Transform counterpart (angular frequency or multipole
as shown in Figure 01a15). Mathematically, the trigonometric function cos(kx) (the phase shift) in Eq.(1) is repalced by the Spherical Harmonics Y
m(
,
), where
= 0 denotes the monopole,
= 1 the dipole,
= 2 the quadrupole, ..., and m can be any integer between -
and
. The coefficient Gk is replaced by alm . Each alm constitutes a multipole mode. In effect, the x in Eq.(1) is replaced by the angular coordinates
and its Fourier transform k is related to the multi-pole moment
. Thus in terms of spherical harmonics, the temperature variation can be expressed as:
). After integrating over
:![]() |
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Figure 03c Legendre Polynomials [view large image] |
Thus, in layman's language, the Power Spectrum can be defined as : "The amount of fluctuation (in term of variance) per small interval of n( )". |
terms as it is most affected by the difference in the transformation from a discrete sum to continuous integration (see Eq.(2b) above and an animated graph to illustrate the Hubble constant dependence on the lower multipole of the CMB spectrum); and as illustrated in Figure 06 for
= 0,
(
+ 1)C
/2
= 0, but the original form is (2
+ 1)C
/4
= C
/4
.
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Any map drawn on the surface of a sphere, whether it be the CMBR's temperature or the topography of the earth, can be broken down into multipoles. The lowest multipoles are the largest-area, continent- and ocean-size undulations on the temperature map. Higher multipoles are like successively smaller-area plateaus, mountains and hills (and trenches and valleys) inserted on top of the larger features. The entire complicated topography is the sum of the individual multipoles. The lowest mode ( = 0) is the monopole - the entire sphere pulses as one. This is the average temperature (2.726oK) of the CMBR. The next lowest mode ( = 1) is the dipole, in which the temperature goes up in one hemisphere and down in the other. In the CMBR mapping, the dipole is dominated by the Doppler shift of the solar system's motion relative to the CMBR; the sky appears slightly hotter in the direction the sun is traveling (see Figure 02-05 in Topic 02, Observable Universe). The CMBR power spectrum begins at C =2 because the real information about cosmic fluctuations begins with the quadrupole ( = 2). Note that the peak variation occurs at about = 200 corresponding to an angular size of about 1 degree (Figures 06, and 01a15). Figure 04 shows the multipoles with = 0, 1, 2. The red color represents variation above the average (green); while the blue color denots less.
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Figure 04 Multipoles |
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In the photon fluid approximation, the medium for sound propagation is a fluid of pure photons without taking into account the matter and expansion effects. It should occur in the era of recombination. Figure 05 is a plot of the displacement (red) and its square (blue) of the sound wave at the moment of recombination as a function of k, i.e., it is a much simplified version of the power spectrum. It shows many differences when compares to the observed power spectrum in Figure 06. See a different derivation of this primordial power spectrum in "Quantum Fluctuations and Cosmic Structures". |
Figure 05 Simplified Power Spectrum |
Figure 06 Observed Power Spectrum [view large image] |
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The relationship between the sound wave and the Hubble horizon is crucial to understand the differences between the simplified and observed power spectrum. Figure 07 plots the inverse of the Hubble horizon (in a comoving frame) against the conformal time in the inflationary era (blue), the radiation era (orange), and the matter era (red). For those values of k under the colored curves, the corresponding wavelength is greater than the Hubble horizon. These kinds of sound wave are frozen and cannot oscillate. As time progresses beyond the inflationary era, sound wave with longer and longer wave-length can re-appear first into the radiation era then to the matter era. |
Figure 07 Hubble Horizon and Sound Wave |
T/T ~ -
, where
is gravitational potential. Then there is the ISW (Integrated Sachs-Wolfe) effect, which modifies the energy of the photons as they climb in and out of the potential well associated with large scale structures. The ISW effect is seen mainly in the lowest multipoles in the power spectrum. The last one is the Doppler peaks. It is caused by electron movements in the plasma, because some of the electrons are moving towards the observer and some move away when they last scatter radiation. The temperature fluctuation is given by the formula:
T/T ~ v/c with an angular size around 1o - 2o.![]() |
There are altogether 10 parameters in these equations, including the densities of CDM, baryons, neutrinos, vacuum energy and curvature, the reionization optical depth, and the normalization and tilt for both scalar (unpolarized) and tensor (polarized) fluctuations, etc. Usually, numerical computation is used to construct models with various values of the parameters. NASA has provided an online computer program "Build A Universe" to crank out power spectrum with various input parameters. Figure 09 is another one called "Max's Cosmic Cinema" by Max Tegmark of MIT. It shows the effects of varying the parameters on the theoretical curves. The graph on the top is the CMBR power spectrum, while the one below shows the power spectrum of the large scale structures. Click the STOP or esc button to view a stationary graph. |
Figure 09 Power Spectrum Animation |
- This is the optical depth. It is used to measure the average distance a photon travelled before its original path is altered by hitting something, e.g., an electron. The CMBR would experiences a certain optical depth, if the Universe was reioninized long ago by quasars or early stars. This effect smears out small-scale features in the CMBR power spectrum, suppressing all accoustic peaks by a constant factor exp(-
), while leaving the power spectrum on the large scale structures unaffected.
k - The space curvature is measured by this parameter from a negative number (open universe) to zero (flat universe), and a positive number (closed universe).
- This is the cosmological constant contribution to the cosmic acceleration discovered lately. It is sometimes referred to as vacuum energy density.
cd or
cd - This is the undetected cold matter density in term of the critical density
c, i.e.,
cd =
cd/
c
b or
b - This is the observable luminous matter (baryons) density in term of the critical density
c, i.e.,
b =
b/
c
- This is the undetected hot matter density such as neutrinos.
3.6 corresponds to an age of the universe T = 1/H0 = 13.5x109 years.
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The density fluctuationn of the cosmic structure is different from the CMBR temperature fluctuation since there is insufficient repulsive force to counteract the gravitational attraction. The plot (see Figure 10) does not show the "up and down" variation as in Figure 02-08. It displays a smooth curve for the variation of galaxy counts on different scale. The measurements have been taken by both the 2dF and SDSS (Sloan Digital Sky Survey) teams with consistent results. Essentially, the measurements were performed with a series of spheres of a given radius at random in the universe and counting the number of galaxies in each one and compute the average difference. The procedure was repeated with spheres of various radii to produce the plot in Figure 10, which is in broad agreement with CDM theory. |
Figure 10 Density Fluctuation in Size Scale [view large image] |
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Thus, the galaxy is the basic unit in determining the density of certain spherical volume with radius r by counting the number of such unit within. Density fluctuation is defined by the averaged density variation from one volume (of fixed radius r) to another. Figure 10a illustrates the relationship with the two-point correlation function, where is a reference-density. For example, the observable universe with radius r ~ 13.8 Glys and total number of galaxies ~ 2x1012 within is used to define ~ 0.1 galaxy/Mly3.
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Figure 10a |

=2
/k. The magnitude of these k-space components is described by the density power spectrum P(k). See "Quantum Fluctuations and Cosmic Structures" for more detail.
> dH) is frozen outside the horizon. Some of the k-waves would re-enter into the observable universe later as it expands (see lower right illustration in Figure 01a21). This is the era of sound wave generation via the alternative gravity attraction and repulsion by radiation pressure. ![]() |
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Figure 11 Cosmic Era |
Figure 12 Density Power Spectrum, Measured |
Figure 13 Density Power Spectrum, Components |
CMB data, giving a value . |

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In effect, the spectral index n in Eq.(3b) varies with a range of 2 1 0 from ancient to modern. The normalization constant A also depends on time as shown in Figure 14. It also shows that in early universe, the P(k) curve is almost a straight line extended to high k value (short wave length) enabling the portion of power spectrum in the form of Ak and then evolves by shifting the maximum toward lower value of k (longer wave length).Just a casual inspection at the power spectrum suggests that it could be simulated by projectile formula of the form : |
Figure 14 Power Spectrum Evolution [view large image] |
Figure 15 Power Spectrum Model [view large image] |
(k) = P(k)/k = -ak2 + bk + c where a, b, c are constants to be determined by observational data. |

(k) in Figure 12 :
(k) up to the maximum, but fails to portray the long tail toward the higher value of "k". Nevertheless, it is instructive to examine the constants in Eq.(4) by comparing it to the Newtonian equation of motion for projectile in constant gravitational acceleration g :
(k) as d2
(k)/dk2 = -2a, the solution of which is given by Eq.(4), where ![]() |
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(k) = P(k)/k = -ak2 + bk + c + e(k) ----- (6).Further investigation reveals that it is possible to fit the entire power spectrum by adding one term to the power spectrum (k) after the maximum as shown in Figure 16 (in red). It means that the effect is turned on only at the moment of recombination. The damping produced by the origin projectile formula is too much, it has to be reduced by an extra term as shown. In Figure 16, the scale is compressed while the k scale is expanded in plotting the graph.
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Figure 16 Power Spectrum, Simulated [view large image] |
Figure 17 Simulated Density Fluctuation |
The correctional term e(k) = 0.95x108x(k - 0.02)2 has to be very precise. It would not work for just a little deviation from the value of 0.95x108. It has to be turned on only after the era of recombination. |
(k) provides only half of the information to determine the strength of density fluctuation (see Eq.(3)). The other half is from the Spherical Bessel Function sin(kr)/kr (see Figure 01a2). The amplitude of this function decreases gradually with increasing value of kr leading to the fluctuation weakening in large scales as portrayed by the simulation in Figure 17 (in log-log plot). It is in good agreement with the measurement in Figure 10.
(see
for further details)
) in the early universe seeded density fluctuations (??), leading to temperature fluctuations (?T).

