M. Diaz-Aguilo

LISA Pathfinder: mission and status

LISA Pathfinder, the second of the European Space Agencys Small Missions for Advanced Research in Technology (SMART), is a dedicated technology demonstrator for the joint ESA/NASA Laser Interferometer Space Antenna (LISA) mission. The technologies required for LISA are many and extremely challenging. This coupled with the fact that some flight hardware cannot be fully tested on ground due to Earth-induced noise led to the implementation of the LISA Pathfinder mission to test the critical LISA technologies in a flight environment. LISA Pathfinder essentially mimics one arm of the LISA constellation by shrinking the 5 million kilometre armlength down to a few tens of centimetres, giving up the sensitivity to gravitational waves, but keeping the measurement technology: the distance between the two test masses is measured using a laser interferometric technique similar to one aspect of the LISA interferometry system. The scientific objective of the LISA Pathfinder mission consists then of the first in-flight test of low frequency gravitational wave detection metrology. LISA Pathfinder is due to be launched in 2013 on-board a dedicated small launch vehicle (VEGA). After a series of apogee raising manoeuvres using an expendable propulsion module, LISA Pathfinder will enter a transfer orbit towards the first Sun?Earth Lagrange point (L1). After separation from the propulsion module, the LPF spacecraft will be stabilized using the micro-Newton thrusters, entering a 500?000 km by 800?000 km Lissajous orbit around L1. Science results will be available approximately 2 months after launch.

The LISA Pathfinder Mission

In this paper, we describe the current status of the LISA Pathfinder mission, a precursor mission aimed at demonstrating key technologies for future space-based gravitational wave detectors, like LISA. Since much of the flight hardware has already been constructed and tested, we will show that performance measurements and analysis of these flight components lead to an expected performance of the LISA Pathfinder which is a significant improvement over the mission requirements, and which actually reaches the LISA requirements over the entire LISA Pathfinder measurement band.

LISA Pathfinder data analysis

As the launch of LISA Pathfinder (LPF) draws near, more and more effort is being put in to the preparation of the data analysis activities that will be carried out during the mission operations. The operations phase of the mission will be composed of a series of experiments that will be carried out on the satellite. These experiments will be directed and analysed by the data analysis team, which is part of the operations team. The operations phase will last about 90 days, during which time the data analysis team aims to fully characterize the LPF, and in particular, its core instrument the LISA Technology Package. By analysing the various couplings present in the system, the different noise sources that will disturb the system, and through the identification of the key physical parameters of the system, a detailed noise budget of the instrument will be constructed that will allow the performance of the different subsystems to be assessed and projected towards LISA. This paper describes the various aspects of the full data analysis chain that are needed to successfully characterize the LPF and build up the noise budget during mission operations.

Theory and modelling of the magnetic field measurement in LISA PathFinder

The magnetic diagnostics subsystem of the LISA Technology Package (LTP) on board the LISA PathFinder (LPF) spacecraft includes a set of four tri-axial fluxgate magnetometers, intended to measure with high precision the magnetic field at their respective positions. However, their readouts do not provide a direct measurement of the magnetic field at the positions of the test masses, and hence an interpolation method must be designed and implemented to obtain the values of the magnetic field at these positions. However, such an interpolation process faces serious difficulties. Indeed, the size of the interpolation region is excessive for a linear interpolation to be reliable while, on the other hand, the number of magnetometer channels do not provide sufficient data to go beyond the linear approximation. We describe an alternative method to address this issue, by means of neural network algorithms. The key point in this approach is the ability of neural networks to learn from suitable training data representing the behaviour of the magnetic field. Despite the relatively large distance between the test masses and the magnetometers, and the insufficient number of data channels, we find that our artificial neural network algorithm is able to reduce the estimation errors of the field and gradient down to levels below 10%, a quite satisfactory result. Learning efficiency can be best improved by making use of data obtained in on-ground measurements prior to mission launch in all relevant satellite locations and in real operation conditions. Reliable information on that appears to be essential for a meaningful assessment of magnetic noise in the LTP.The magnetic diagnostics subsystem of the LISA Technology Package (LTP) on board the LISA PathFinder (LPF) spacecraft includes a set of four tri-axial fluxgate magnetometers, intended to measure with high precision the magnetic field at their respective positions. However, their readouts do not provide a direct measurement of the magnetic field at the positions of the test masses, and hence an interpolation method must be designed and implemented to obtain the values of the magnetic field at these positions. However, such an interpolation process faces serious difficulties. Indeed, the size of the interpolation region is excessive for a linear interpolation to be reliable while, on the other hand, the number of magnetometer channels do not provide sufficient data to go beyond the linear approximation. We describe an alternative method to address this issue, by means of neural network algorithms. The key point in this approach is the ability of neural networks to learn from suitable training data representing the behaviour of the magnetic field. Despite the relatively large distance between the test masses and the magnetometers, and the insufficient number of data channels, we find that our artificial neural network algorithm is able to reduce the estimation errors of the field and gradient down to levels below 10%, a quite satisfactory result. Learning efficiency can be best improved by making use of data obtained in on-ground measurements prior to mission launch in all relevant satellite locations and in real operation conditions. Reliable information on that appears to be essential for a meaningful assessment of magnetic noise in the LTP.

Inflight magnetic characterization of the test masses onboard LISA Pathfinder

LISA Pathfinder is a science and technology demonstrator of the European Space Agency within the framework of its LISA mission, the latter aiming to be the first space-borne gravitational wave observatory. The payload of LISA Pathfinder is the so-called LISA Technology Package, which is designed to measure relative accelerations between two test masses in nominal free fall. The diagnostics subsystem consists of several modules, one of which is the magnetic diagnostics unit. Its main function is the assessment of the differential acceleration noise between the test masses due to magnetic effects. This subsystem is composed of two onboard coils intended to produce controlled magnetic fields at the location of the test masses. These magnetic fields couple with the remanent magnetic moment and susceptibility and produce forces and torques on the test masses. These, in turn, produce kinematic excursions of the test masses which are sensed by the onboard interferometer. We prove that adequately processing these excursions, the magnetic properties of the test masses can be estimated using classical multi-parameter estimation techniques. Moreover, we show that special processing procedures to minimize the effect of the multi channel cross-talks are needed. Finally, we demonstrate that the quality of our estimates is frequency dependent. We also suggest that using a multiple frequency experiment the global estimate can be obtained in such a way that the results of the magnetic experiment are more reliable. Finally, using our procedure we compute the the contribution of the magnetic noise to the total proof-mass acceleration noise.

Parameter estimation in LISA Pathfinder operational exercises

The LISA Pathfinder data analysis team has been developing in the last years the infrastructure and methods required to run the mission during flight operations. These are gathered in the LTPDA toolbox, an object oriented MATLAB toolbox that allows all the data analysis functionalities for the mission, while storing the history of all operations performed to the data, thus easing traceability and reproducibility of the analysis. The parameter estimation methods in the toolbox have been applied recently to data sets generated with the OSE (Off-line Simulations Environment), a detailed LISA Pathfinder non-linear simulator that will serve as a reference simulator during mission operations. These simulations, so called operational exercises, are the last verification step before translating these experiments into tele-command sequences for the spacecraft, producing therefore very relevant datasets to test our data analysis methods. In this contribution we report the results obtained with three different parameter estimation methods during one of these operational exercises.

State-space modelling for heater induced thermal effects on LISA Pathfinder's Test Masses

The OSE (Offline Simulations Environment) simulator of the LPF (LISA Pathfinder) mission is intended to simulate the different experiments to be carried out in flight. Amongst these, the thermal diagnostics experiments are intended to relate thermal disturbances and interferometer readouts, thereby allowing the subtraction of thermally induced interferences from the interferometer channels. In this paper we report on the modelling of these simulated experiments, including the parametrisation of different thermal effects (radiation pressure effect, radiometer effect) that will appear in the Inertial Sensor environment of the LTP (LISA Technology Package). We report as well how these experiments are going to be implemented in the LTPDA toolbox, which is a dedicated tool for LPF data analysis that will allow full traceability and reproducibility of the analysis thanks to complete recording of the processes.

LISA PathFinder radiation monitor proton irradiation test results

The design of the Radiation Monitor in the LISA Technology Package on board LISA Pathnder is based on two silicon PIN diodes, placed parallel to each other in a telescopic configuration. One of them is able to record spectral information of the particle hitting the diode. A test campaign for the flight model Radiation Monitor was done in the Paul Scherrer Institute Proton Irradiation Facility in September 2010. Its purpose was to check correct functionality of the Radiation Monitor under real high energy proton fluxes. Here we present the results of the experiments done and their assessment by means of a simulated flight model geometry using GEANT4 toolkit. No deviation from nominal RM performance was detected, which means the instrument is fully ready for flight.

Milli-Hertz Gravitational Waves: LISA and LISA PathFinder

Ground based GW detectors are limited at their lower frequency band (1-10 Hz) by settlement gravity gradients and seismic noise, and their sensitivity peaks at around 100 Hz. Sources in this band are mostly short duration signals, and their rates uncertain. Going down to milli-Hertz frequencies significantly increases the number and types of available sources. LISA was planned with the idea to explore a likely richer region of the GW spectrum, beyond that accessible to ground detectors; the latter are however expected to produce the first GW observations. In this paper I will present the main LISA concepts; in particular, emphasis will be placed on LISAPathFinder, the ESA precursor of LISA, in which our research group in Barcelona is heavily involved.

Neural network interpolation of the magnetic field for the LISA Pathfinder Diagnostics Subsystem

LISA Pathfinder is a science and technology demonstrator of the European Space Agency within the framework of its LISA mission, which aims to be the first space-borne gravitational wave observatory. The payload of LISA Pathfinder is the so-called LISA Technology Package, which is designed to measure relative accelerations between two test masses in nominal free fall. Its disturbances are monitored and dealt by the diagnostics subsystem. This subsystem consists of several modules, and one of these is the magnetic diagnostics system, which includes a set of four tri-axial fluxgate magnetometers, intended to measure with high precision the magnetic field at the positions of the test masses. However, since the magnetometers are located far from the positions of the test masses, the magnetic field at their positions must be interpolated. It has been recently shown that because there are not enough magnetic channels, classical interpolation methods fail to derive reliable measurements at the positions of the test masses, while neural network interpolation can provide the required measurements at the desired accuracy. In this paper we expand these studies and we assess the reliability and robustness of the neural network interpolation scheme for variations of the locations and possible offsets of the magnetometers, as well as for changes in environmental conditions. We find that neural networks are robust enough to derive accurate measurements of the magnetic field at the positions of the test masses in most circumstances.