Blind extraction of an exoplanetary spectrum through Independent Component Analysis

TL;DR

This paper demonstrates a blind, non-parametric method using Independent Component Analysis to extract exoplanet spectra from Hubble data, achieving comparable accuracy to parametric methods without prior assumptions.

Contribution

It introduces a novel blind-source separation approach for exoplanet spectrum extraction that does not rely on prior models or auxiliary data.

Findings

Spectroscopic errors are only 10-30% larger than parametric methods.

The method yields stable spectra consistent with previous analyses.

Non-parametric approach offers a more objective analysis with reasonable accuracy.

Abstract

Blind-source separation techniques are used to extract the transmission spectrum of the hot-Jupiter HD189733b recorded by the Hubble/NICMOS instrument. Such a 'blind' analysis of the data is based on the concept of independent component analysis. The de-trending of Hubble/NICMOS data using the sole assumption that nongaussian systematic noise is statistically independent from the desired light-curve signals is presented. By not assuming any prior, nor auxiliary information but the data themselves, it is shown that spectroscopic errors only about 10 - 30% larger than parametric methods can be obtained for 11 spectral bins with bin sizes of ~0.09 microns. This represents a reasonable trade-off between a higher degree of objectivity for the non-parametric methods and smaller standard errors for the parametric de-trending. Results are discussed in the light of previous analyses published in the literature. The fact that three very different analysis techniques yield comparable spectra is a strong indication of the stability of these results.