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

Integrating Scalpels #122

Open
LucaNap opened this issue Oct 22, 2024 · 0 comments
Open

Integrating Scalpels #122

LucaNap opened this issue Oct 22, 2024 · 0 comments

Comments

@LucaNap
Copy link

LucaNap commented Oct 22, 2024

Hi everyone,

I am exploring the possibility of adding Scalpels to juliet (for who's not familiar with it, check Cameron+2020), and I am wondering how should it be done. From what I understand, juliet should first read the base Scalpels vector (U0) from a file, and then simply calculate the residuals during the fit as:

res = (RV_values - matrix_N@matrix_C) * (RV_values - matrix_N@matrix_C)

where

matrix_N = np.array([ np.ones(len(RV_times)), rv_drive(RV_times, p1), ..., U0]).T
matrix_C = np.array([offset, 1, ..., alpha]) 

rv_drive is the planetary signal model evaluated with Radvel for planet 1 (and so on, if there are others), and p1 are the parameters of the first planet. Of course, for each planet there should be a new rv_drive in matrix_N and "1" in matric_C. Finally, "offset" and "alpha" are the new priors related to the Scalpels vector (if U0 is mono-dimensional, otherwise there should be an "alpha" for each dimension of the vector). For example, if we have N radial-velocity points, one planet and a mono-dimensional U0, then:

matrix_N@matrix_C = 1*offset + K*1 + U0*alpha = offset + K + U0*alpha.

where matrix_N dimensions are Nx3 and matrix_C 3x1. So, I guess the main change should be the addition of a correction factor to K during the sampling. @nespinoza, what do you think?

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

No branches or pull requests

1 participant