Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

OH full range - 730 lines #5

Open
erwanp opened this issue Jan 10, 2021 · 1 comment
Open

OH full range - 730 lines #5

erwanp opened this issue Jan 10, 2021 · 1 comment
Labels
new benchmark Suggested conditions for new RADIS benchmark

Comments

@erwanp
Copy link
Member

erwanp commented Jan 10, 2021

@dcmvdbekerom I set up a quite extreme example where we see the weaknesses of the LDM method / FFT when there are very little lines and a large spectral range.

  • LDM : 27s
  • historical : 0.43s

https://github.com/radis/radis-benchmark/blob/master/manual_benchmarks/OH%20benchmark.ipynb

I do not think the LDM can be improved much for these conditions. Instead, we should make use of the fact that RADIS has the historical method already implemented, and switch to it automatically.

I discussed this previously, but in a first approximation :

  • DLM scales as spectral range / wstep * log(spectral range / wstep) (FFT)
  • historical method (line-centered lineshape with cutoff) scales as broadening_cutoff * spectral range / wstep^2 (convolution) * N_lines

Therefore the ratio R should be a good indicator of when to use LDM (R >> Rcrit) and when to use the historical method (R << Rcrit)

R = broadening_cutoff  / wstep * N_lines / log(spectral range / wstep)

In the benchmark example, I calculated R=50e6 and we're definitly in a historical method computation, so we can already say that Rcrit >> 50e6.

This in itself could be a GSOC project, actually !

  • Build a big map of benchmark cases
  • Run the methods and manually optimize
  • Derive a better R expression.
  • Implement the automatic switch using a high-level "optimization='auto'" mode in calc_spectrum

Related

@erwanp erwanp added the new benchmark Suggested conditions for new RADIS benchmark label Jan 10, 2021
@erwanp
Copy link
Member Author

erwanp commented Mar 29, 2021

Featured in OpenAstronomy GSOC 2021 project Automatic Lineshape Engine 🚀 with @pkj-m

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
new benchmark Suggested conditions for new RADIS benchmark
Projects
None yet
Development

No branches or pull requests

1 participant