Scale invariance in the power spectrum

In summary, the conversation discusses the predictions of inflation and the Harrison-Zeldovich spectrum for the scalar spectral index (n_s). While inflation does not predict a specific value for n_s, it is expected to be less than one due to the end of inflation. The Harrison-Zeldovich spectrum, which assumes scale invariance, was not a proper physical model and predicted n_s to be exactly one. However, with the launch of WMAP, the prevailing view was that n_s would be slightly different from one.
  • #1
windy miller
303
25
I understand the inflation predicts a nearly scale invariant power spectrum but some have claimed this was predicted before inflation (by Harrison and Zeldovitch?)
My understanding is that perfectly scale invariance would predict ns=1 but inflation predicts ns =.96. So did the prior prediction ( if this claim is true) predict ns=1 or ns=.96 ?
 
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  • #2
Inflation doesn't predict a specific value of the scalar spectral index (##n_s##). Instead, there are a wide variety of models of inflation and they can all have rather different values for ##n_s##. Inflation predicts a spectral index different from one (usually less) because inflation has to come to an end. The different inflation models end in slightly different ways, leading to different predictions.

From what I recall, the Harrison-Zeldovitch spectrum, which simply assumes scale invariance, wasn't ever a proper physical model of the universe. It more or less just assumes that there are these perturbations, and that they are scale invariant, but doesn't actually have a workable model that would cause that.

So when we got to the point of measuring this spectrum in the early 2000's with the launch of WMAP, the prevailing view was that the most likely result would have been a spectral index somewhat different from one, with ##n_s = 1## considered to be a null hypothesis.
 
  • #3
Thanks you for that's its very interesting. Would I be correct to assume then the Harrison Zeldovich spectrum would have assume to be exactly one if they were just assuming scale invariance without a model to produce it?
 
  • #4
windy miller said:
Thanks you for that's its very interesting. Would I be correct to assume then the Harrison Zeldovich spectrum would have assume to be exactly one if they were just assuming scale invariance without a model to produce it?
Yes. The HZ spectrum has n=1.
 

Related to Scale invariance in the power spectrum

1. What is scale invariance in the power spectrum?

Scale invariance in the power spectrum refers to the property of a system or phenomenon to exhibit the same statistical properties at different scales. This means that the power spectrum, which describes the distribution of energy or power over different frequencies, remains unchanged when the scale of observation is changed.

2. Why is scale invariance important in science?

Scale invariance is important in science because it allows us to understand and analyze complex systems and phenomena at different levels of observation. It also helps us to identify and study patterns and relationships that may not be easily observable at a single scale.

3. How is scale invariance measured in the power spectrum?

Scale invariance in the power spectrum is measured using a mathematical concept called fractal dimension. This dimension quantifies the degree of self-similarity in a system at different scales. A higher fractal dimension indicates a higher degree of scale invariance.

4. What are some examples of scale invariance in the power spectrum?

Scale invariance in the power spectrum is observed in many natural and man-made systems, such as the distribution of galaxy clusters, the size distribution of earthquakes, the branching patterns of trees, and the fluctuations in financial markets. It is also seen in physical phenomena like turbulence and diffusion.

5. Can scale invariance be broken or disrupted?

Yes, scale invariance can be broken or disrupted in certain systems. This can happen when there are external forces or disturbances that affect the system at a particular scale, causing a deviation from the expected statistical properties. However, the overall concept of scale invariance remains a useful tool for understanding complex systems in many fields of science.

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