Tilt-to-length coupling in LISA Pathfinder: a data analysis

TL;DR

This paper analyzes the tilt-to-length coupling noise in LISA Pathfinder, demonstrating its dependence on system alignment, validating an analytical model with mission data, and discussing implications for future space-based gravitational wave detectors.

Contribution

It introduces and validates an analytical model for tilt-to-length coupling noise dependence on alignment, using LISA Pathfinder data and a new physical coupling model.

Findings

Analytical model accurately describes tilt-to-length coupling dependence on alignment.

Realignments during the mission were only partially successful.

A physical coupling model was developed using long cross-talk experiment data.

Abstract

We present a study of the tilt-to-length coupling noise during the LISA Pathfinder mission and how it depended on the system's alignment. Tilt-to-length coupling noise is the unwanted coupling of angular and lateral spacecraft or test mass motion into the primary interferometric displacement readout. It was one of the major noise sources in the LISA Pathfinder mission and is likewise expected to be a primary noise source in LISA. We demonstrate here that a recently derived and published analytical model describes the dependency of the LISA Pathfinder tilt-to-length coupling noise on the alignment of the two freely falling test masses. This was verified with the data taken before and after the realignments performed in March (engineering days) and June 2016, and during a two-day experiment in February 2017 (long cross-talk experiment). The latter was performed with the explicit goal of testing the tilt-to-length coupling noise dependency on the test mass alignment. Using the analytical model, we show that all realignments performed during the mission were only partially successful and explain the reasons why. In addition to the analytical model, we computed another physical tilt-to-length coupling model via a minimising routine making use of the long cross-talk experiment data. A similar approach could prove useful for the LISA mission.