Interactively fit Brown Dwarf Spectra with the gollum dashboard

In this tutorial we will see how the spectra of brown dwarfs vary as a function of their intrinsic properties. We will fit observed spectra of a particular brown dwarf with the gollum dashboard, a dashboard which fits models based on properties including effective temperature, surface gravity, metallicity, rotational broadening, and radial velocity. The fitting for this tutorial will be based on the Sonora-Bobcat 2021 models, which takes into account effective temperature, surface gravity, and metallicity as intrinsic values.

from gollum.sonora import SonoraGrid
from specutils import Spectrum1D
import pandas as pd
import astropy.units as u

from IPython.display import HTML
from IPython.display import Image

First, we will read in an example spectrum of this ultracool dwarf:

2MASS J05591914-1404488

We got its data from the Keck Telescope’s NIRSPEC spectrograph. A specific section of this data is displayed below.

df = pd.read_csv('../../data/2mass0559_59.dat',
                 delim_whitespace=True,
                 comment='#',
                 names=['wave', 'flux'])

df.head()

The unit for wavelength here is microns and the unit for flux is “counts”.

bdss_spectrum = Spectrum1D(spectral_axis=df.wave.values*u.micron,
                           flux=df.flux.values*u.ct)

wl_lo, wl_hi = (bdss_spectrum.wavelength.value.min(),
                bdss_spectrum.wavelength.value.max())

Next, we can read in the Sonora-Bobcat grid and show an interactive dashboard.

grid = SonoraGrid(wl_lo=wl_lo, wl_hi=wl_hi)

Awesome! Now you can hand-in a data spectrum to overlay it onto the grid and begin fitting using the interactive sliders.

grid.show_dashboard(data=bdss_spectrum, show_telluric=False)

The dashboard looks great!