Main Python codes used in the paper Vitral & Mamon 2020a. This concerns the deprojection of the Sérsic model (Sérsic 1963; Sersic 1968) onto volume density and mass. The main files are:
CODES:
sersic_grid_num.py : Calculates the numerical deprojection of the Sérsic model, as well as the analytical approximation by Lima Neto, Gerbal & Márquez 1999. Then it fits a polynomial to the ratio log(f_LGM/f_numerical) and saves the coefficients.
sersic_grid_comp_rms.py : Compares the new fitted model with other models in the literature
rms_per_n.py : Compares the new fitted model with other models in the literature
slope_comp.py : Compares the LGM approximation with the numerical deprojection.
test_interpolation.py : Plots the interpolation results for the parameters provided in Emsellem & van de Ven 2008
create_table_coeff.py : Creates a text file with the table corresponding to the polynomial fits.
einasto_comp.py : Compares the Einasto (1965) profile with the deprojected Sersic profile.
other_models_comp.py : Compares the deprojected Sersic profile with the models from Plummer (1911), Jaffe (1983), Hernquist (1990) and Navarro et al. (1996).
OTHER FILES:
dens_num.npy, dens_num1000.npy, mass_num.npy, mass_num1000.npy, nu_rh.npy : Numerical calculated values for different grids of volume density and mass.
coeff_1.txt, coeff_2.txt : Raw files containing the results of the polynomial fits.
coeff_dens.txt, coeff_mass.txt : Tables containing the results of the polynomial fits.
*** The results and codes here all use the Ciotti & Bertin 1999 approximation for the Sérsic parameter, b_n. For the results and codes with the numerical results from equation 2 from Vitral & Mamon 2020a, please email vitral@iap.fr.