I’m a cosmologist working at the interface of cosmological theory and data analysis. The main goal of my research is to find new ways to test and constrain fundamental physics with cosmological data. The initial perturbations of the universe are believed to have been created by a quantum process, and the statistical properties of the resulting density field contain information about the ultra high energy physics of the primordial universe.
Recently I have been working on different aspects of the idea of finding or constraining massive states during inflation. In principle the density perturbations created by inflation are sensitive to much higher masses than could ever be probed with a terrestrial collider and thus “cosmological collider physics” could give unique insights into ultra high energy physics. In many cases such a measurement would require futuristic experimental data and I have worked on forecasting the sensitivity of different experimental setups. For some theoretical models, even current CMB data can be used to obtain interesting and new constraints on massive states. In ongoing work I am searching for such signatures in Planck and WMAP CMB data. Cosmological collider physics (or non-gaussianities) is still a very young field and I believe there will be interesting developments in the years and decades to come. I am also interested in the challenging subject of discriminating primordial and secondary non-gaussianities, for large-scale structure surveys and other probes.
Another recent line of my research is exploring the cross-correlation of CMB and matter data induced by the kinetic and polarized SZ effects. Together with colleagues at PI we explored new estimators that provide information about the ultra large-scale structure of the universe. These estimators can be used to search for unexpected anisotropies, or provide consistency checks for our understanding of the universe.
For data analysis, the focus of my research over the last years has been to extract information about the big bang from data of the Planck satellite. This experiment measures the so called Cosmic Microwave Background (CMB), which can be understood as an afterglow of the big bang. It therefore contains invaluable information about the physics of the beginning of the universe. I am a member of the data analysis team for early universe physics of the Planck experiment. My work involves both theoretical calculation of the signals of interest, and development of statistical techniques to search for these signals.
The most successful theory of the big bang is called inflation and comes in a huge variety of models. Nobody knows which (or if any) of these models is correct. Physicists like me are therefore examining how different theories of the big bang can be tested with cosmological data, like the one from the Planck satellite. A focus of my work have been inflation models that induce oscillations in the statistical properties of the CMB data. Such oscillations are for example predicted by some string theoretical models of inflation. It would be marvellous if we were to detect such a “smoking gun” signal that would guide us to the right theory. What we can do for now is excluding those theories that disagree with the data that we already have.
Reconstruction of the remote dipole and quadrupole fields from the kinetic Sunyaev Zel’dovich and polarized Sunyaev Zel’dovich effects, arXiv: 1707.08129
Prospects for cosmological collider physics, Journal of Cosmology and Astroparticle Physics, Volume 2017, March 2017
Optimal estimator for resonance bispectra in the CMB, Phys. Rev. D 91, 043534, February 2015
The Komatsu Spergel Wandelt estimator for oscillations in the cosmic microwave background bispectrum, A&A Volume 570, October 2014
Joint resonant CMB power spectrum and bispectrum estimation, Phys. Rev. D 93, 043536 – February 2016
Planck 2015 results XVII. Constraints on primordial non-Gaussianity, Astron.Astrophys. 594 (2016) A17
Optimal CMB estimators for bispectra from excited states, Phys. Rev. D 92, 063527, September 2015
Some of my physics code is on github.