HAZMAT

The HAbitable Zones and M dwarf Activity across Time (HAZMAT) program assesses the lifetime exposure of planets to stellar ultraviolet (UV) radiation using GALEX data, HST COS and STIS spectra, and semi-empirical, full-wavelength models. The program quantifies the evolution of far- and near-UV (FUV; NUV) emission for early- and mid-M (HAZMAT I), late-M (HAZMAT III), and K (HAZMAT V) type stars, as well as extreme-UV (EUV) emission from early-M stars (HAZMAT VI).

The data products below are high-resolution synthetic spectra (EUV – IR; 100 Angstroms to 5.5 microns) of early-M stars at five distinct ages between 10 Myr and 5 Gyr. The spectra are computed with the PHOENIX atmosphere code from one-dimensional upper atmosphere models of 0.35 and 0.45 solar mass stars (stellar parameters given in Table 1 of the HAZMAT VI paper). The wavelengths (given in Angstroms) are in vacuum and the wavelength grid has a resolution of <0.1 Angstroms. The flux densities (given in ergs/cm^2/s/Angstrom) are that at the stellar surface and are scalable to a distance D via (R_star/D)^2 where R_star is dependent on the age and mass of the star from Table 1.

Downloadable data products include five spectra per 0.35 and 0.45 solar mass stars at ages of 10, 45, 120, 650, and 5000 Myr. The spectra reproduce either the minimum ("MIN"), lower quartile ("LQ"), median ("MED"), upper quartile ("UQ"), or maximum ("MAX") FUV and NUV flux density per age as calculated from the GALEX stellar sample in HAZMAT I.  The complete set of HAZMAT series papers are available in the Reference section at the bottom of the page.

Also available for download are high-resolution full-wavelength (100 Angstrom – 950 micron) PHOENIX spectra of specific M dwarf planet host stars from Peacock et al. 2019a,b. The data products are synthetic spectra in wavelength (Angstrom) and flux density at the surface of the star (ergs/s/cm^2/ Angstrom). In the publications, the flux densities are scaled by (R_star/D)^2.  The Peacock et al. 2019a,b references are available in the Reference section at the bottom of the page.

TRAPPIST-1 is a moderately active ultracool M8 dwarf star that hosts seven transiting planets orbiting within 0.063 au. In the absence of broadband UV spectral observations, we constrained three different models using HST Lyman α observations from TRAPPIST-1 (Model “1A”) and Galaxy Evolution Explorer UV photometric detections from a set of old (>1 Gyr) M8 stars (Models “2A” and “2B”).  The star's radius is taken to be 0.12 solar radii and distance is taken to be 12.1 pc.  GJ 832 is an M1.5V star that hosts two planets: a 0.64 M_J planet at a semimajor axis of 3.56 au and a 5.4 M_E super-Earth located in the canonical habitable zone (0.16 au).  The star's radis is taken to be 0.50 solar radii and distance is taken to be 0.96 pc.  GJ 176 is an M 2.5V star that hosts an 8.3 M_E planet orbiting at 0.66 au.  The star's radius is taken to be 0.45 solar radii and distance is taken to be 9.47 pc.  GJ 436 is an M3.5 V star that hosts a 23 M_E planet orbiting at 0.287 au. Lyα transit observations of this Neptune-sized planet show a 56% transit depth that is most likely caused by a large cloud of escaping hydrogen (Kulow et al. 2014; Ehrenreich et al. 2015).  The star's radius is taken to be 0.46 solar radii and distance is taken to be 9.76 pc.

Acknowledgements

If you make use of the synthetic HAZMAT spectral data products, please cite Peacock et al. (2020).  If you make use of the synthetic TRAPPIST-1 spectral data products, please cite Peacock et al. (2019a).  If you make use of the synthetic GJ 832, GJ 176, or GJ 436 spectral data products, please cite Peacock et al. (2019b).

Sample Scripts

To get started, here are some Python and IDL lines to read in the model spectra, provided by the HLSP team.  MAST provides these for convenience, but does not take responsibility for long-term maintenance of these commands.

Python

from astropy.io import fits
import matplotlib.pyplot as plt
spec = fits.getdata(‘hlsp_hazmat_phoenix_synthspec_10myr_med-m0.45-t3550-g4.24_v1_fullres.fits’,1)
plt.plot(spec['WAVELENGTH'],spec['FLUX'])
plt.suptitle('10 Myr, M=0.45 Msun Median Model’)
plt.xlabel('Wavelength (Angstroms)')
plt.ylabel('Flux Density (erg/cm2/s/Ang)')
plt.show()

from astropy.io import ascii
import matplotlib.pyplot as plt
spec = ascii.read(“hlsp_hazmat_phoenix_synthspec_10myr_med-m0.45-t3550-g4.24_v1_fullres.txt”)
plt.plot(spec[0],spec[1])
plt.suptitle('10 Myr, M=0.45 Msun Median Model’)
plt.xlabel('Wavelength (Angstroms)')
plt.ylabel('Flux Density (erg/cm2/s/Ang)')
plt.show()

IDL

spec = MRDFITS(‘hlsp_hazmat_phoenix_synthspec_10myr_med-m0.45-t3550-g4.24_v1_fullres.fits’,1,head)
plot,spec.wavelength,spec.flux,xrange=[100,3000],/xlog,/ylog,$
       charsize=2,charthick=2,title=’10 Myr, M=0.45 Msun Median Model’,$
       xtitle='Wavelength (Angstroms)’, ytitle='Flux Density (erg/cm2/s/Ang)',$
       
readcol,‘hlsp_hazmat_phoenix_synthspec_10myr_med-m0.45-t3550-g4.24_v1_fullres.txt’,wavelength, flux
plot,wavelength,flux,xrange=[100,3000],/xlog,/ylog,$
       charsize=2,charthick=2, title=’10 Myr, M=0.45 Msun Median Model’,$
       xtitle='Wavelength (Angstroms)’, ytitle='Flux Density (erg/cm2/s/Ang)',$

Data Tables