Unified model for the LISA measurements and instrument simulations

TL;DR

This paper introduces a comprehensive simulation model for LISA, incorporating relativistic reference frames, clock synchronization, laser frequency modeling, and onboard processing, to improve preflight data analysis and instrument development.

Contribution

It presents a novel unified model for LISA measurements and simulations, including relativistic effects and realistic instrument features, with two implementations widely used in the community.

Findings

TDI processing recovers gravitational-wave signals from complex simulated data.

The models are integrated into LISANode and LISA Instrument, supporting LISA data challenges.

The simulation enhances preflight analysis and instrument design for LISA.

Abstract

LISA is a space-based mHz gravitational-wave observatory, with a planned launch in 2034. It is expected to be the first detector of its kind, and will present unique challenges in instrumentation and data analysis. An accurate preflight simulation of LISA data is a vital part of the development of both the instrument and the analysis methods. The simulation must include a detailed model of the full measurement and analysis chain, capturing the main features that affect the instrument performance and processing algorithms. Here, we propose a new model that includes, for the first time, proper relativistic treatment of reference frames with realistic orbits; a model for onboard clocks and clock synchronization measurements; proper modeling of total laser frequencies, including laser locking, frequency planning and Doppler shifts; better treatment of onboard processing and updated noise models. We then introduce two implementations of this model, LISANode and LISA Instrument. We demonstrate that TDI processing successfully recovers gravitational-wave signals from the significantly more realistic and complex simulated data. LISANode and LISA Instrument are already widely used by the LISA community and, for example, currently provide the mock data for the LISA Data Challenges.