Fourier transform and Cosmic variance - a few precisions

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Discussion Overview

The discussion revolves around the statistical analysis of the power spectrum in the context of Fourier transforms and cosmic variance. Participants explore the implications of measuring variance at different modes of the Fourier decomposition, particularly at the zero mode, and the associated statistical errors.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Conceptual clarification

Main Points Raised

  • One participant discusses the challenge of measuring variance at the zero mode of the Fourier transform, noting that it results in an infinite statistical error due to having only one pixel.
  • The same participant questions the formulation of the statistical error as a relative error and seeks clarification on the conditions for assimilating standard deviation to relative error.
  • Another participant requests a reference for the original report cited, emphasizing the need for verifiable sources.
  • A subsequent post provides a link to a related discussion in French but acknowledges that it may not be easily understood by all participants.
  • Another participant expresses frustration over the lack of clarity in the discussion and requests a peer-reviewed source to support the claims made.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are ongoing requests for clarification and references, indicating uncertainty and differing levels of understanding regarding the statistical concepts discussed.

Contextual Notes

The discussion includes references to specific mathematical formulations and concepts that may depend on definitions not fully provided in the thread. There are also unresolved issues regarding the validity of the links shared and the clarity of the original sources.

fab13
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TL;DR
I would like to understand the reasoning which is done on a report about the cosmic variance. I nedd precisions to know how the expression linking the error relative of Power spectrum and the number of pixels in Fourier space. I would like also to understand under which conditions relative error and standard deviation are equal.
I cite an original report of a colleague :
If we are interested in power spectrum, we want to estimate the
variance of the amplitude of the modes ##k## of our Fourier
decomposition. If one observes the whole observable Universe and we
do the Fourier transformation we get a cube whose center is the mode
## |\vec{k}| = 0## which corresponds to the mean value of the observed
field.

This mode has only one pixel. How do we measure the variance of the
process at ## |\vec{k}| = 0 ## ? We can not.

In fact we can but the value of doesn't mean anything because the
error is infinite. In other words, we have an intrinsic (statistical)
error which depends on the number of achievements to which we have
access.

one will be able to consider spheres of sizes ## dk ## between ## [k: k +
dk] ## which will contain a number of pixels ## N_ {k} = V_ {k}/(dk)^{3}## where ## V_{k} = 4 \pi k^{2} dk ## is the volume of the sphere
and ## (dk)^{3} ## is the volume of a pixel in our Fourier transform
cube.

So one can estimate how many values one can use to calculate our
power spectrum for each value of ## k ##. The greater the ## k ##, the
greater the number of accessible values and therefore the statistical
error decreases. The power spectrum is a variance estimator so the
statistical error is basically a relative error:

## \dfrac{\sigma (P(k))}{P(k)} = \sqrt{\dfrac{2}{N_{k}
-1}}_{\text{with}} N_{k} \approx 4\pi \left (\dfrac{k}{dk}\right)^{2} ##

So we can see that for the case ##|\vec{k}| = 0## we have an infinite error because ##N_{k} = 1##.
1) I can't manage to proove that the statistical error is formulated like :

##\dfrac{\sigma (P (k))}{P(k)} = \sqrt{\dfrac {2}{N_{k} -1}}_{\text{with}} N_{k} \approx 4\pi \left(\dfrac{k}{dk}\right)^{2}##

and why it is considered like a relative error ?

2) Which are the conditions to assimilate a statistical error (standard deviation) to a relative error (##\dfrac{\Delta x}{x}##) ?

3) How to prove that ##N_{k} = 1## in the case ##|\vec{k}| = 0## ?

Any help is welcome.
 
Last edited:
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fab13 said:
I cite an original report of a colleague
Please give a reference. You can't cite a source that nobody else but you can see.
 
Isn't really no one who could help me about this problem of understanding ?
 
fab13 said:
Hoping this will help you
Aside from the text being in French, this is still just a discussion forum and does not give enough information to figure out what the discussion is supposed to be about. There is one link to what looks like it should be a presentation, but the link is not valid (404 error).

Is there a peer-reviewed paper or something similar that the discussion you linked to is based on? Can you provide a link to such a paper?
 

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