Find stellar quantities from evolution tracks

Find basic stellar evolution properties (radius, luminosity, convective turnover time, moments of inertia, etc.) as a function of stellar mass and age, using the Spada et al. (2013) ¹ tracks bundled with MORS. Baraffe et al. (2015) ² tracks are also available.

Prerequisites

Install MORS and download stellar evolution data:

pip install fwl-mors
mors download all

Spada tracks

Available quantities

Option 1: Call a quantity function directly

Each quantity has a dedicated function:

import mors

Rstar = mors.Rstar(1.0, 1000.0)   # Mstar=1.0 Msun, Age=1000 Myr
print(Rstar)                        # in Rsun

Option 2: Use the generic Value accessor

Choose the quantity by name at runtime:

import mors

Rstar = mors.Value(1.0, 1000.0, 'Rstar')
print(Rstar)

Option 3: Vectorised inputs

All functions accept scalars, lists, or NumPy arrays for mass and age.

Multiple masses, one age — returns a 1D array:

import numpy as np
import mors

masses = np.array([0.8, 1.0, 1.2])
R = mors.Rstar(masses, 1000.0)
print(R.shape)  # (3,)

One mass, multiple ages — returns a 1D array:

import numpy as np
import mors

ages = np.array([10.0, 100.0, 1000.0])
L = mors.Lbol(1.0, ages)
print(L.shape)  # (3,)

Multiple masses and multiple ages — returns a 2D array:

import numpy as np
import mors

masses = np.array([0.8, 1.0, 1.2])
ages   = np.array([10.0, 100.0, 1000.0])
T = mors.Teff(masses, ages)
print(T.shape)  # (3, 3) — shape (len(masses), len(ages))

Multiple quantities via Value — adds a third dimension:

import numpy as np
import mors

masses = np.array([0.9, 1.0])
ages   = np.array([100.0, 1000.0])
vals = mors.Value(masses, ages, ['Rstar', 'Lbol', 'tauConv'])
print(vals.shape)  # (2, 2, 3) — (masses, ages, quantities)

Performance: pre-loading a mass track

On first use, MORS compiles the Spada grid and saves a cache file in the stellar evolution tracks directory. Subsequent runs load from this cache and are faster.

If you will query many ages for a specific mass, pre-load that track to avoid repeated interpolation between mass bins:

import mors

mors.LoadTrack(1.02)  # does nothing if already loaded

Baraffe tracks

MORS also provides access to Baraffe et al. (2015) ² tracks.

Step 1: Load a Baraffe track

import mors

baraffe = mors.BaraffeTrack(Mstar=0.5)

BaraffeTrack performs mass interpolation if needed.

Step 2: Query radius, luminosity, and flux

time_yr = 1e7  # years

Rstar = baraffe.BaraffeStellarRadius(time_yr)       # Rsun
Lbol  = baraffe.BaraffeLuminosity(time_yr)          # Lsun
Flux  = baraffe.BaraffeSolarConstant(time_yr, 1.0)  # W m⁻² at 1 AU

BaraffeSolarConstant(time, distance) takes distance in AU.

Common pitfalls

• Spada functions use Age in Myr; Baraffe functions use time in yr.
• The convective turnover time key is 'tauConv', not 'tau'.
• "Core" and "envelope" follow the rotation model convention, not the nuclear-burning core definition.
• The first Spada call may be slower due to cache generation.