News
Biometris invention helped analysing the gravitational waves predicted by Einstein
The detection of gravitational waves by Abbot et al (2016) as predicted by Albert Einstein in 1916 is a landmark in science. Gravitational waves arise by a merger of two black holes. To infer about the masses and position of the back holes from the gravitational waves a 13-16 parameter model is used.
The model is based on relativity theory and fitted to the data using Bayesian analysis using adaptive Monto Carlo Markov chain (MCMC) sampling (Meyer & Christensen 2016). An invention of Biometris, namely Differential Evolution Markov chain, DE-MC (ter Braak 2006; ter Braak & Vrugt 2008) was an important component of the particular methods used for this (Veitch et al. 2015). DE-MC was among the preferred adaptive MCMC samplers to use on the basis of its capability to efficiently sample multi-modal posterior densities. Here we see an unexpected contribution of Biometris to fundamental physics and astronomy.
The DE-MC project was funded for a large part by a Kennisbasis project in KBVII: Technologische Ontwikkeling (Technology Development) and had the aim to provide similar model calibration methodology to agriculture, nature and food science.
References:
Abbott BP, et al. 2016. Observation of Gravitational Waves from a Binary Black Hole Merger. Physical Review Letters 116:061102. http://link.aps.org/doi/10.1103/PhysRevLett.116.061102
Meyer R, and Christensen N. 2016. Gravitational waves: A statistical autopsy of a black hole merger. Significance 13:20-25. http://dx.doi.org/10.1111/j.1740-9713.2016.00896.x
ter Braak CJF. 2006. A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces. Statistics and Computing 16:239-249. http://dx.doi.org/10.1007/s11222-006-8769-1
ter Braak CJF, and Vrugt JA. 2008. Differential Evolution Markov Chain with snooker updater and fewer chains. Statistics and Computing 18:435-446. http://dx.doi.org/10.1007/s11222-008-9104-9
Veitch J, Raymond V, Farr B, Farr W, Graff P, Vitale S, Aylott B, Blackburn K, Christensen N, Coughlin M, Del Pozzo W, Feroz F, Gair J, Haster CJ, Kalogera V, Littenberg T, Mandel I, O’Shaughnessy R, Pitkin M, Rodriguez C, Röver C, Sidery T, Smith R, Van Der Sluys M, Vecchio A, Vousden W, and Wade L. 2015. Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library. Physical Review D 91:042003. http://link.aps.org/doi/10.1103/PhysRevD.91.042003