Doogesh Kodi Ramanah

Born on the tropical island of Mauritius, I completed my undergraduate studies in Physics at the University of Mauritius in July 2014. Following the award of a postgraduate state scholarship, I opted for a Master's course in Theoretical Physics at Imperial College London. In October 2016, I embarked on a PhD in Cosmology at Institut d'Astrophysique de Paris under the supervision of Guilhem Lavaux and Benjamin D. Wandelt, with funding from Institut Lagrange de Paris.

The crux of my doctoral programme lies in the development of optimal and sophisticated data analysis techniques for cosmological inference. In an era of precision cosmology, the data analysis of state-of-the-art galaxy redshift surveys and cosmic microwave background (CMB) experiments with unprecedented levels of sensitivity and resolution poses complex numerical challenges. Fast and robust methods are therefore required to deal with the present and upcoming avalanches of cosmological and astrophysical data in order to maximise the scientific returns of the missions.

We are currently developing a high performance algorithm for the Wiener filtering of large and complex data sets. The Wiener filter provides the optimal solution to the signal reconstruction problem for a system described by Gaussian (normal) statistics. Since the cosmic density field can be approximated as a Gaussian random field, this is a frequently encountered and ubiquitous problem in cosmology and astrophysics. Traditional approaches of computing the Wiener filter solution have been sub-optimal or numerically intractable with modern data sets. In the first instance, the algorithm would be applied to CMB temperature and polarisation maps. In addition to CMB observations, the Wiener filter is also relevant for observations of the large-scale structures and 21-centimetre emission.

We are also working on large-scale Bayesian inference algorithms where the joint inference of density fields, power spectrum and cosmological parameters is performed within a self-consistent framework, while accounting for various systematic and statistical uncertainties. The large-scale structures have emerged as an essential probe of the dynamics and evolution of the Universe, and provides a pathway to investigate various cosmological models and inflationary scenarios.

List of publications: arxiv

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Contact: doogesh.kodi-ramanah[at]iap.fr