Parameter estimation in LISA Pathfinder operational exercises

Nofrarias, M.; Ferraioli, L.; Congedo, G.; Hueller, M.; Armano, M.; Diaz‐Aguiló, Marc; Grynagier, A.; Hewitson, M.; Vitale, S.

doi:10.1088/1742-6596/363/1/012053

Cited by 7 publications

(10 citation statements)

References 8 publications

(10 reference statements)

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“…In order to calibrate the dynamics of LPF described in the previous section, the so-called system identification experiments [16][17][18] were regularly performed during the mission. Repeated experiments were necessary both to measure the long term stability of the system, and also because different working configurations of the system and/or potentially different environmental conditions could yield different calibration parameters.…”

Section: System Identification and Parameter Estimationmentioning

confidence: 99%

Calibrating the system dynamics of LISA Pathfinder

Armano¹,

Audley²,

Baird³

et al. 2018

Phys. Rev. D

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LISA Pathfinder (LPF) was a European Space Agency mission with the aim to test key technologies for future space-borne gravitational-wave observatories like LISA. The main scientific goal of LPF was to demonstrate measurements of differential acceleration between free-falling test masses at the sub-femto-g level, and to understand the residual acceleration in terms of a physical model of stray forces, and displacement readout noise. A key step towards reaching the LPF goals was the correct calibration of the dynamics of LPF, which was a three-body system composed by two testmasses enclosed in a single spacecraft, and subject to control laws for system stability. In this work, we report on the calibration procedures adopted to calculate the residual differential stray force per unit mass acting on the two test-masses in their nominal positions. The physical parameters of the adopted dynamical model are presented, together with their role on LPF performance. The analysis and results of these experiments show that the dynamics of the system was accurately modeled and the dynamical parameters were stationary throughout the mission. Finally, the impact and importance of calibrating system dynamics for future space-based gravitational wave observatories is discussed.

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Section: System Identification and Parameter Estimationmentioning

confidence: 99%

Calibrating the system dynamics of LISA Pathfinder

Armano¹,

Audley²,

Baird³

et al. 2018

Phys. Rev. D

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“…In other words, it is straightforward to apply the optimal statistic and model the equations of motion of both the eLISA link and the LPF system as coherent subtraction of measured, but asynchronous, signals. Therefore, the log-likelihood becomes (19) where the inner product is calculated based onŜ a12,n , which can either estimated from noise-only measurements or directly available as a theoretical model or even marginalised over using the full Φ-posterior. The above likelihood also implements the action of the dynamical ∆ operator, where its parameters, now θ and τ , enter into the likelihood calculation.…”

Section: Resultsmentioning

confidence: 99%

“…Firstly, the estimation of the residual acceleration noise [16], and its quantitative analysis [17], is critical for the success of the mission. Secondly, the estimation of the modelled system parameters through calibration experiments (see [18][19][20][21], and more recently [22]), ensures that disturbances and systematic errors can be effectively subtracted from the data. An alternative approach described in a recent work [23] tries subtracting all disturbances and systematic errors by relaxing the a-priori knowledge of the underlying model with a Bayesian marginalisation over noise, resulting in some marginal posterior, which in principle is found to be equivalent to a re-weighted least squares fitting.…”

Section: Introductionmentioning

confidence: 99%

Measuring test mass acceleration noise in space-based gravitational wave astronomy

Congedo

2015

Phys. Rev. D

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The basic constituent of interferometric gravitational wave detectors -the test mass to test mass interferometric link -behaves as a differential dynamometer measuring effective differential forces, comprising an integrated measure of gravity curvature, inertial effects, as well as non-gravitational spurious forces. This last contribution is going to be characterised by the LISA Pathfinder mission, a technology precursor of future space-borne detectors like eLISA. Changing the perspective from displacement to acceleration can benefit the data analysis of LISA Pathfinder and future detectors. The response in differential acceleration to gravitational waves is derived for a space-based detector's interferometric link. The acceleration formalism can also be integrated into time delay interferometry by building up the unequal-arm Michelson differential acceleration combination. The differential acceleration is nominally insensitive to the system free evolution dominating the slow displacement dynamics of low-frequency detectors. Working with acceleration also provides an effective way to subtract measured signals acting as systematics, including the actuation forces. Because of the strong similarity with the equations of motion, the optimal subtraction of systematic signals, known within some amplitude and time shift, with the focus on measuring the noise provides an effective way to solve the problem and marginalise over nuisance parameters. The F-statistic, in widespread use throughout the gravitation waves community, is included in the method and suitably generalised to marginalise over linear parameters and noise at the same time. The method is applied to LPF simulator data and, thanks to its generality, can also be applied to the data reduction and analysis of future gravitational wave detectors.

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“…To demonstrate a first application to the LTP, we can investigate a model selection case that was first encountered during a data analysis exercise [33]. These types of exercises are organized by the data analysis team with the aim of testing the developed tools in more realistic scenarios.…”

Section: B Application To a Simplified Ltp Modelmentioning

confidence: 99%

Bayesian model selection for LISA pathfinder

et al. 2014

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The main goal of the LISA Pathfinder (LPF) mission is to fully characterize the acceleration noise models and to test key technologies for future space-based gravitational-wave observatories similar to the eLISA concept. The data analysis team has developed complex three-dimensional models of the LISA Technology Package (LTP) experiment onboard the LPF. These models are used for simulations, but, more importantly, they will be used for parameter estimation purposes during flight operations. One of the tasks of the data analysis team is to identify the physical effects that contribute significantly to the properties of the instrument noise. A way of approaching this problem is to recover the essential parameters of a LTP model fitting the data. Thus, we want to define the simplest model that efficiently explains the observations. To do so, adopting a Bayesian framework, one has to estimate the so-called Bayes factor between two competing models. In our analysis, we use three main different methods to estimate it: the reversible jump Markov chain Monte Carlo method, the Schwarz criterion, and the Laplace approximation. They are applied to simulated LPF experiments in which the most probable LTP model that explains the observations is recovered. The same type of analysis presented in this paper is expected to be followed during flight operations. Moreover, the correlation of the output of the aforementioned methods with the design of the experiment is explored.

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Parameter estimation in LISA Pathfinder operational exercises

Cited by 7 publications

References 8 publications

Calibrating the system dynamics of LISA Pathfinder

Calibrating the system dynamics of LISA Pathfinder

Measuring test mass acceleration noise in space-based gravitational wave astronomy

Bayesian model selection for LISA pathfinder

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