This project uses data from two experiments, the Dark Energy Spectroscopic Instrument (DESI) and the Euclid space satellite. Both of these experiments measure the distance of millions of galaxies and with that, they map out the density distribution in the Universe. The distribution of galaxies does depend on many properties of the Universe itself. For example, if there is more Dark Energy in the Universe, the Universe expands faster at late times, which will reduce the density of galaxies we measure with these experiments. On the other hand, if there is more dark matter in the Universe, it will lead to a stronger clustering of galaxies and the Universe will look more clumpy. In this project, we calculate summary statistics like the power spectrum or bispectrum from the distribution of galaxies. These summary statistics can be compared to theoretical models of the Universe. Such tests allow us to determine what the Universe is made of (Dark Matter, Dark Energy, Neutrinos, baryons), but they can also help to determine the initial conditions. Currently, we believe that a rapid expansion phase in the early Universe called inflation set the initial conditions for later galaxy formation. This rapid expansion has theoretical motivation but has not been verified convincingly with data. The aim of this project is to (1) expand the summary statistics used for such tests, to optimally exploit the data provided by the two experiments mentioned above, (2) investigate new observables, to test the dynamics of the early Universe, (3) test General Relativity on cosmological scales.
This project addresses age-old questions like "How did the Universe begin?" and "How will the Universe end?". As such, this project has the potential to revolutionize how we see our role in the Universe. Additionally, the analysis we perform on these datasets uses cutting-edge statistical techniques which we generally make publically available. This project already published four statistical analysis tools as Python packages, which now have been downloaded >70000 times significantly impacting/improving statistical analysis far beyond astronomy.