We are located at the University Observatory Munich (USM). We work on the interface between theoretical and observational cosmology. Our main research interest is in confronting modern cosmological theories with observations. Here we have in particular a strong research program in exploiting galaxy clusters and cosmic voids, but also in more general probes of the large-scale structure and the cosmic microwave background. One of our main motivations is to understand the nature of the cosmic acceleration in the Universe. Here we try to constrain theoretical models from standard dark energy, coupled scalar fields to theories which extend Einstein's gravity at large distances. In order to achieve this goal, we use analytical and numerical methods, such as N-body simulations of the structure formation process, state of the art statistical analysis tools and modern Bayesian techniques. Furthermore, we have a strong research program in machine learning applications in astrophysics, but also apply these methods in medical physics and string theory.
We are involved in the following national and international collaborations: The Dark Energy Survey DES, The Euclid satellite mission of ESA, the Dark Energy Science Collaboration DESC at the Rubin Observatory Legacy Survey of Space and Time, the Hobby-Eberly Telescope Dark Energy Experiment HETDEX, the eRosita X-ray satellite mission, the Square Kilometer Array SKA and the LiteBird satellite mission.
We work together with other groups at the Max Planck institutes. Among others: OPINAS and High Energy Astrophysics groups at MPE, the Cosmology research group at MPA, as well as with members of other groups at the Excellence Cluster and groups at MPP.
Recent Papers by Group Members
Dark Energy Survey Year 3 results: Imprints of cosmic voids and superclusters in the Planck CMB lensing map, Kovács, A. et al.,Monthly Notices of the Royal Astronomical Society, 515, 4417, (2022)
Dark energy survey year 3 results: cosmological constraints from the analysis of cosmic shear in harmonic space, Doux, C. et al.,Monthly Notices of the Royal Astronomical Society, 515, 1942, (2022)
The GIGANTES Data Set: Precision Cosmology from Voids in the Machine-learning Era, Kreisch, Christina D. et al.,The Astrophysical Journal, 935, 100, (2022)
On the relative bias of void tracers in the Dark Energy Survey, Pollina, G. et al.,Monthly Notices of the Royal Astronomical Society, 487, 2836, (2019)
The Dark Energy Survey Image Processing Pipeline, Morganson, E. et al.,Publications of the Astronomical Society of the Pacific, 130, 074501, (2018)
Lattice simulations of Abelian gauge fields coupled to axions during inflation, Caravano, Angelo et al.,Physical Review D, 105, 123530, (2022)
Lattice Simulations of Axion-U(1) Inflation, Caravano, Angelo et al.,2022arXiv220412874C
Improving the accuracy of estimators for the two-point correlation function, Kerscher, Martin et al.,arXiv:2203.13288
Updated neutrino mass constraints from galaxy clustering and CMB lensing-galaxy cross-correlation measurements, Tanseri, Isabelle et al.,Journal of High Energy Astrophysics, 36, 1, (2022)
Consistent equivalence principle tests with fast radio bursts, Reischke, Robert et al.,Monthly Notices of the Royal Astronomical Society, 512, 285, (2022)
Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations, Naidoo, K. et al.,arXiv:2208.10503
Euclid preparation. XXIV. Calibration of the halo mass function in $\Lambda(\nu)$CDM cosmologies, Euclid Collaboration et al.,arXiv:2208.02174
A duality connecting neural network and cosmological dynamics, Krippendorf, Sven et al.,Machine Learning: Science and Technology, 3, 035011, (2022)
Updated bounds on axion-like particles from X-ray observations, Schallmoser, Simon et al.,Monthly Notices of the Royal Astronomical Society, 514, 329, (2022)
The bias of cosmic voids in the presence of massive neutrinos, Schuster, Nico et al.,Journal of Cosmology and Astroparticle Physics, 2019, 055, (2019)