Stellar spectra

Stellar spectra#

pytransit.stars gives access to two grids of theoretical stellar spectra that PyTransit ships with. They are what the Contamination models integrate over passbands, and what the gravity-darkened model uses to convert local surface temperature into observed flux.

The grids#

Both grids are precomputed and binned. The original spectra are averaged over surface gravity and metallicity for each effective temperature and binned to a uniform 1 nm wavelength grid. This keeps them small enough to distribute inside the package – together about 18 MB – while remaining accurate enough for the broadband flux ratios they are used for.

Grid	Wavelengths	Temperatures	Reference
BT-Settl	10-30000 nm	1200-7000 K, 68 steps	Allard et al. (2012)
Husser2013	300-2500 nm	2300-12000 K, 73 steps	Husser et al. (A&A 553, A6, 2013)

BT-Settl covers a much wider wavelength range and reaches down to brown dwarf temperatures, which makes it the grid of choice for cool hosts, M dwarfs, and low-mass contaminants. It is the default in SMContamination.

Husser2013 extends to hotter stars, up to early A types, but over a narrower wavelength range.

Neither grid resolves individual lines after binning. They are meant for integrating over passbands, not for spectroscopy.

Reading a grid#

Each grid has a read_*_table function returning a pandas.DataFrame with the effective temperatures as the index and the wavelengths as the columns.

from pytransit.stars import read_bt_settl_table

df = read_bt_settl_table()
df.shape
# (68, 29991)

df.index.values[:5]        # effective temperatures in K
df.columns.values[:5]      # wavelengths in nm

Interpolating#

For a spectrum at an arbitrary temperature, create_*_interpolator returns a scipy.interpolate.RegularGridInterpolator over (temperature, wavelength).

from numpy import linspace, full, transpose
from pytransit.stars import create_bt_settl_interpolator

ip = create_bt_settl_interpolator()

wl = linspace(400.0, 900.0, 500)
spectrum = ip(transpose([full(wl.size, 5500.0), wl]))

The interpolator is built from the full table each time it is created, so create it once and reuse it.

Note

The interpolators do not extrapolate. Requesting a temperature or wavelength outside the grid raises a ValueError.

Rebuilding the tables#

compute_averaged_bt_settl_table and compute_averaged_husser2013_table regenerate the shipped tables from a locally downloaded spectrum grid. These are package maintenance functions – PyTransit comes with the tables precomputed, so they only need to be run to rebuild them.

API#

BT-Settl#

pytransit.stars.read_bt_settl_table()[source]#

Read the wavelength-binned BT-Settl stellar spectrum table shipped with PyTransit.

Reads the precomputed spectrum table from bt_settl_file. The table holds spectra averaged over surface gravity and metallicity and binned to a uniform 1 nm wavelength grid covering 10-30000 nm at 68 effective temperatures from 1200 K to 7000 K. The binning keeps the table small enough to distribute with the package while remaining accurate enough for broadband flux ratios. The temperature coverage makes this the grid of choice for cool stars, M dwarfs, and brown dwarfs.

Returns:: pandas.DataFrame – Spectra with the effective temperatures in K as the index and the wavelengths in nm as the columns.

Husser et al. (2013)#

pytransit.stars.read_husser2013_table()[source]#

Read the wavelength-binned Husser et al. (2013) PHOENIX stellar spectrum table shipped with PyTransit.

Reads the precomputed spectrum table from husser2013_file. The table holds spectra averaged over surface gravity and metallicity and binned to a uniform 1 nm wavelength grid covering 300-2500 nm at 73 effective temperatures from 2300 K to 12000 K. The binning keeps the table small enough to distribute with the package while remaining accurate enough for broadband flux ratios. The temperature coverage extends to hotter stars than the BT-Settl grid, but the wavelength coverage is narrower.

Returns:: pandas.DataFrame – Spectra with the effective temperatures in K as the index and the wavelengths in nm as the columns.