BANZAI-NRES

BANZAI-NRES is the data reduction pipeline for NRES high-resolution spectrographs on the Las Cumbres Observatory network.

• Install
• Data Products
• Wavelength Solution
• Stellar Classification and Radial Velocity Measurement
• Development
• Example Data Reduction
• Differences from the Commissioning Pipeline

BANZAI-NRES is designed to process all of the data from the Network of Robotic Echelle Spectrographs (NRES) on the Las Cumbres Observatory network. These instruments have a resolving power of R=50,000 and cover the optical 380-860 nm range. This pipeline provides extracted, wavelength calibrated spectra. If the target is a star, we provide stellar classification parameters (e.g. effective temperature and surface gravity) and a radial velocity measurement. The automated radial velocity measurements from this pipeline have a precision of ~ 10 m/s for high signal-to-noise observations.

The data flow and infrastructure of this pipeline relies heavily on BANZAI, enabling this repo to focus on analysis that is specific to spectrographs. Spectral orders are detected and extracted entirely using Python and numpy routines. The wavelength calibration is primarily done using xwavecal as described in Brandt et al. 2020 DOI: 10.3847/1538-3881/ab929c. Radial velocities and classifications are computed by cross-correlating with the PHOENIX stellar atmosphere models from Husser et al. 2013, DOI: 10.1051/0004-6361/201219058. BANZAI-NRES propagates an estimate of the formal uncertainties from all of the data processing stages and includes these in the output data products. These are used as weights in the cross correlation function to measure the radial velocity. We adopt an optimal weighting scheme for the cross correlation based on Zackay & Ofek 2017 DOI: 10.3847/1538-4357/836/2/187.

License

This code is licensed under GPLv3. See LICENSE.rst for more details.