Statistical Spectral Fitting of Brown Dwarf Binary Systems
Leanne Lunsford and Faculty Mentors: Denise Stephens, Eric Hintz – Physics & Astronomy
Brown dwarfs are an intermediary classification between stars and planets. They are too small to sustain hydrogen fusion because core temperature directly proportional to gravitational pressure, of which they have not enough, yet too massive to be a gas giant like Jupiter. L dwarfs have alkali metals in their atmospheres and are the warmest category of brown dwarf, reaching temperatures as high as 2000 Kelvin. T dwarfs as temperatures as low as 700K are cool enough for methane and other molecules such as water and ammonia to build up in their atmosphere. The way that molecules interact in both types of brown dwarfs and the regions they occupy are both results of many factors that are difficult to determine such as age, mass, and chemical makeup. Brown dwarf binary systems are our best resources for understanding and accurately modeling brown dwarfs, as the orbital mechanics of the two objects allow us to calculate the masses. Binary systems are also made up of objects of the same relative age and composition. With this information, combined with spectral observations, we have statistically modeled the relationship between temperature, surface gravity, cloud particle density, and atmospheric mixing for five brown dwarf binary systems.
The spectral observations used in this analysis came from the Spitzer Telescope archives, taken with the Infrared Spectrograph (IRS) on staring mode. The exposure-level data frames, or bcd files, contain the spectra in two diffraction orders. Order one records wavelengths between 7.57 and 14.28μm, while order two contains values between 5.21 and 7.56μm. These files require a lengthy cleaning process to remove imperfections, as each image contains bad pixel values recorded by the camera. Dead pixels are easy to account for as they can be found in the same position on every frame. Hot pixels are different in that they can vary in frame and location, as they appear when the camera sensor becomes hot during long exposures and record false values.
Once the bad pixel values were corrected, we used the program SMART, the Spectroscopic Modeling Analysis and Reduction Tool specifically designed for IRS data, for final cleaning and extraction. The background emission and low-level rogue pixels were removed, leaving behind a clearly identifiable spectral line. The SMART program performs a flux calibration to account for the fact that every pixel on the CCD reacts differently over time to the flux received. Finally, the spectra were extracted and both orders merged together to create a spectrum that spans from 5 to 14μm. Near-infrared data from 1 to 2.5μm was obtained for each object, in units of Jansky (Jy), which was combined with the extracted data to create a final spectrum ready for analysis.
Thousands of single and binary brown dwarf models were created by Saumon and Marley1, by using permutations of the temperature, gravity, cloud, and vertical mixing parameters. Temperatures for the models span from 500K to 2400K in increments of usually 100K. Surface gravity is measured in cgs units, and ranges from 4 to 5.5 Galileo. The cloud parameter indicates the particle density of the clouds, and a value of 1 indicates a high density while 4 indicates a low density. In a high vertical mixing system, NH3 and CH4 absorption bands are weaker than expected, as these molecules are pulled low into the atmosphere, where they are converted into N2 and CO due to higher temperatures. We have determined which models best fit the given spectra by using the function below2.
IRS spectral data from the Spitzer Space Telescope Archive, in collaboration with IRAF and SMART,
can provide a plethora of information previously unknown to us about the binary nature of particular
brown dwarfs. Now that the fitting process has been performed, and potential single and binary systems
have been recorded along with their unique parameter values, the next step is to download photometric
data from the Hubble Space Telescope Archive and apply a psf-fitting technique to confirm the results.
I give my thanks to Dr. Denise Stephens for her instruction and support throughout my internship with
the BYU Research Experience for Undergraduates (REU). My gratitude also goes to Riley Finnegan and
Baylee Danz for their work on PSF-fitting the HST data that provided me with the potential binaries.
Finally, I would like to thank the BYU Office of Research and Creative Activities (ORCA) and the
National Science Foundation for their funding (NSF-1461219).