Metrology calibration and very high accuracy centroiding with the NEAT testbed

TL;DR

This paper discusses the development of a high-precision centroiding testbed for the NEAT astrometric mission, aiming to measure stellar positions with unprecedented accuracy to detect Earth-like exoplanets.

Contribution

It introduces a novel testbed setup combining pseudo stars and metrology fringes to achieve 5e-6 pixel centroiding precision, demonstrating progress towards NEAT's goals.

Findings

Achieved initial centroiding precision close to 2e-5 pixels.

Developed calibration procedures for pixelation error correction.

Validated the testbed design with early experimental results.

Abstract

NEAT is an astrometric mission proposed to ESA with the objectives of detecting Earth-like exoplanets in the habitable zone of nearby solar-type stars. NEAT requires the capability to measure stellar centroids at the precision of 5e-6 pixel. Current state-of-the-art methods for centroid estimation have reached a precision of about 2e-5 pixel at two times Nyquist sampling, this was shown at the JPL by the VESTA experiment. A metrology system was used to calibrate intra and inter pixel quantum efficiency variations in order to correct pixelation errors. The European part of the NEAT consortium is building a testbed in vacuum in order to achieve 5e-6 pixel precision for the centroid estimation. The goal is to provide a proof of concept for the precision requirement of the NEAT spacecraft. The testbed consists of two main sub-systems. The first one produces pseudo stars: a blackbody source is fed into a large core fiber and lights-up a pinhole mask in the object plane, which is imaged by a mirror on the CCD. The second sub-system is the metrology, it projects young fringes on the CCD. The fringes are created by two single mode fibers facing the CCD and fixed on the mirror. In this paper we present the experiments conducted and the results obtained since July 2013 when we had the first light on both the metrology and pseudo stars. We explain the data reduction procedures we used.