Firstly, I obtained a 1024^3 mesh from TNG100-1 data by CIC assignment scheme. And then I chose 10000 lines along the z-axis orthogonal to the x-y plane, so each line contains 1024 (\delta + 1).

Next, I perform FFT for every line. Finally, I compute the 1D power spectrum by averaging over 10000 lines.

Here is my result of dark matter

However, the standard deviation of this power spectrum is so large, the maximum of std is a prop to 10^8. Why is it happen?

Dylan Nelson

6 Nov '20

Hello Yun,

Have you compared your results to the power spectra computed and presented in Springel+18 (e.g. Fig 4)?

Yun Wang

7 Nov '20

Thank you for your reply. I don't know why I failed to upload my figures.

The shape of my power spectrum is similar to Springel's.

Hi guys,

Firstly, I obtained a 1024^3 mesh from TNG100-1 data by CIC assignment scheme. And then I chose 10000 lines along the z-axis orthogonal to the x-y plane, so each line contains 1024 (\delta + 1).

Next, I perform FFT for every line. Finally, I compute the 1D power spectrum by averaging over 10000 lines.

Here is my result of dark matter

However, the standard deviation of this power spectrum is so large, the maximum of std is a prop to 10^8. Why is it happen?

Hello Yun,

Have you compared your results to the power spectra computed and presented in Springel+18 (e.g. Fig 4)?

Thank you for your reply. I don't know why I failed to upload my figures.

The shape of my power spectrum is similar to Springel's.