Tomography/Power Spectrum Techniques for Removal of Fixed Pattern Noise from Hubble Space Telescope Spectra

Abstract

We have developed tomography/power spectrum algorithms to differentiate the intrinsic stellar spectrum from the pronounced fluctuations in the spectrum counts due to photocathode granularity and diode-to-diode gain variations. We have presented the results of four typical high signal-to-noise (S/N) and high-resolution data sets, obtained from the Goddard High Resolution Spectrograph (GHRS) aboard the Hubble Space Telescope (HST), for the bright star α Gru to demonstrate various utilities of these techniques. Our algorithms allow the final merged HST spectrum to achieve a higher signal-to-noise ratio, and could be applied to resolve the fixed pattern noise (FPN) problems that would be found in the distorted/degraded detectors in `both current and future planned instrumentations, e.g., the GHRS and the second generation Space Telescope Imaging Spectrograph (STIS) for the HST.