Analyzing modal noise in non-circular core fibers using a python script to visualize the standard deviation of light intensity across multiple images to reduce modal noise in spectrograph instrumentation

Abstract

In astronomy, spectrographs may be used to generate radial velocities (RVs) which can then detect the existence of an exoplanet. This radial velocity method, or doppler method, is among the most popular and successful methods of exoplanet detection (along with the transit method), however, most are taken in the visible spectrum. By shifting the focus towards the near-infrared, smaller terrestrial planets could be discovered orbiting cooler M Dwarf stars. In 2012, Dr. Peter Plavchan and his colleagues constructed a non-circular core fiber scrambler designed to couple starlight through fibers of varying diameter, length, and shape, minimizing modal noise in the process, with the purpose of precisely measuring radial velocities in the near-infrared H band. This scrambler, which is capable of imaging both fiber cross-sections as well as the final resulting spectra of stars, was used to take numerous exposures with targets including SV Peg, Vega, and Arcturus. We wrote a python program that creates several different plots that aid in visualizing the FITS file data of the fiber cross-sections as a normalized plot of the light spread function of the CDC pixel counts over their pixel position. The script also calculates the standard deviation of the modal noise across images. We try to improve upon the ranges used to create the plots and from which we calculate the standard deviation with the goal of increasing the accuracy of the standard deviation of the modal noise across images. It was discovered that the 200 micron octagonal agitated fiber reduced the most modal noise. In general, it was found that fibers longer in length, octagonal in core shape, and continuously and randomly agitated are the most efficient for successful spectroscopy.