Full Index

AtmosphereCPU(atm_korg)

Build a CPU-backed atmosphere from a Korg atmosphere object.

AtmosphereCPU(atm_korg)

Construct an AtmosphereCPU with thermodynamic and velocity fields on the CPU.

AtmosphereGPU(atm_korg)

Build a GPU-backed atmosphere from a Korg atmosphere object.

AtmosphereGPU(atm_korg)

Construct an AtmosphereGPU with thermodynamic fields from Korg and velocity fields allocated on the GPU.

StellarProps(; Teff=NaN, logg=NaN, Fe_H=NaN, vsini=0.0, v_macro=NaN, v_micro=NaN,
              ρstar=1.0, istar=90.0)

Container for stellar parameters and broadening properties used by FormationTemps.

Keyword arguments:

• Teff: effective temperature (K).
• logg: log10 surface gravity (cgs).
• Fe_H: metallicity [Fe/H] (dex), used to build A_X.
• vsini: projected rotation velocity (m/s).
• v_macro: macroturbulent velocity (m/s); if NaN, uses vmac_fit(Teff, logg).
• v_micro: microturbulent velocity (m/s); if NaN, uses vmic_fit(Teff).
• ρstar: stellar radius scale factor for disk integration (dimensionless).
• istar: inclination angle in degrees (90 = equator-on).

calc_formation_temp(star, linelist; use_gpu=GPU_DEFAULT, Δλ=0.01, convolve=false,
                    minλ=NaN, maxλ=NaN, u1=NaN, u2=NaN, Nϕ=128, kwargs...)

Compute flux formation temperatures, normalized flux, and flux contribution function for a given star and linelist.

The wavelength grid is built from the line list (wl * 1e8) with padding and step Δλ. Use minλ/maxλ (Angstrom) to override the default bounds (first/last line ± 2 A).

Returns a FormTempResult with fields:

• wavs: wavelength grid (Angstrom).
• flux: normalized flux (sum(cfunc_dt_flux) / sum(cfunc_dt_flux_cont)).
• form_temps: formation temperature defined at 50% of the cumulative flux contribution.
• cont_func: contribution function, shape (Natm - 1, Nλ).
• atmosphere: atmosphere structure used for the calculation.

If convolve=true, applies Hirano rotation + macroturbulent convolution using limb-darkening coefficients u1 and u2. Otherwise, performs numerical disk integration using Nϕ latitude bins. Set use_gpu=true to use the GPU implementation when available.

Examples

star = StellarProps(Teff=5777.0, logg=4.44, Fe_H=0.0, vsini=2100.0)
linelist = Korg.read_linelist(joinpath(FT.datdir, "Sun_VALD.lin"))[1:500]
result = calc_formation_temp(star, linelist; Δλ=0.01, convolve=true, u1=0.43, u2=0.31)

Adapted from Korg.jl -> line_absorption!()

convolve_gray_rotation(xs, ys, vsini, u1)

Convolve a spectrum with the Gray (2008) rotation kernel using linear limb darkening.

TODO: finish docs.

convolve_hirano_rotmacro(xs, ys, vsini, ζ_rt, u1, u2; intres=intres_glob)

Convolve a spectrum with the Hirano et al. (2011) rotation+macroturbulence kernel.

TODO: finish docs.

convolve_instrument_gauss(xs, ys; new_res=1.17e5, oversampling=2.0)

Convolve a spectrum with a Gaussian LSF at resolving power new_res.

TODO: finish docs.

convolve_iso_rt_macro(xs, ys, ζ_rt)

Convolve a spectrum with the isotropic radial-tangential macroturbulence kernel.

TODO: finish docs.

convolve_rt_macro(xs, ys, ζ_rt, μ)
convolve_rt_macro(xs, ys, ζ_r, ζ_t, μ)

Convolve a spectrum with a radial-tangential macroturbulence kernel.

TODO: finish docs.

elav(a::AbstractVector)
elav(a; dims)

Compute midpoints between adjacent elements along dims.

TODO: finish docs.

get_Ts(atm)

Return the temperature grid as a standard Array.

get_marcs_atm(Teff, logg, A_X; n_layers=56)

Interpolate a MARCS atmosphere from Korg and return it with n_layers layers.

get_zs(atm)

Return the height grid as a standard Array.

get_τs(atm)

Return the optical depth grid as a standard Array.

Equation 17.8 from Gray (2008), assuming AR = AT and ζR = ζT

Equation 18.14 from The Observation and Analysis of Stellar Photospheres (Gray 2008)

Equation B12 from Hirano et al. (2011). NOTE: This is returns the Fourier Transform of the rotmacro convolution kernel, not the kernel itself!!

rebin_spectrum(xs_old, ys_old, xs_new)
rebin_spectrum(xs_old, ys_old, σs_old, xs_new)

Rebin a spectrum (and optional uncertainties) from xs_old to xs_new.

Based on the SpectRes spectral resampling implementation: https://github.com/ACCarnall/SpectRes/blob/master/spectres/spectral_resampling.py

Note: the algorithm may introduce small shifts if the wavelength grids are misaligned.

round_to_power(x::Real)

Round x to one significant digit based on its order of magnitude.

TODO: finish docs.

Equation 17.6 from Gray (2008), assuming AR = AT

Equation 17.6 from Gray (2008), assuming AR = AT and ξR = ξT

searchsortednearest(a, x)
searchsortednearest(x, a)

Return the index of the element in sorted vector a that is closest to x.

TODO: finish docs.

vmac_fit(teff, logg)
vmac_fit(teff)

Empirical macroturbulent velocity fits.

vmac_fit(teff, logg) uses the Doyle et al. (2014) relation with teff in K and logg in cgs. vmac_fit(teff) uses the Bruntt et al. (2010) relation with teff in K. Both return the macroturbulent velocity in m/s.

vmic_fit(teff)

Empirical microturbulent velocity fit from Bruntt et al. (2010).

Input teff is in K; returns microturbulent velocity in m/s.