In this era of precision cosmology, we have managed to extract, with percent-level accuracy, the value of salient cosmological parameters using mostly linear perturbation physics such as the CMB and background geometrical observables. Following the arrival of fourth-generation galaxy surveys such as Euclid, Vera Rubin, SKA and Nancy Roman, we will enter the era of big data and nonlinearities. The ability to probe smaller scales using larger volumes is necessary for accurate statistical and theoretical models.
In this talk, I will begin with a brief overview of the primary Euclid spectroscopic and photometric probes, namely galaxy clustering and weak lensing. I will outline their uses for testing different models of gravity and dark energy. In order to do so effectively, we need to take into account observational effects, cross-correlations and the still unsolved problem of nonlinearities. Next, I will describe the challenge of nonlinear structure formation, focusing on modified gravity, in which we have many theoretical and practical unknowns in addition to a lack of computational resources. In an upcoming publication, we address this challenge by combining N-body simulations and machine learning applications to generate a predictive model optimised for both forecasts and data analysis. In spite of current uncertainties at small scales, it is precisely in this regime in which we have some hope of finding some deviations to the current LCDM paradigm.
Please join via Zoom at
https://uio.zoom.us/j/63419652784?pwd=QW9INDgrQUJZUWtGcUhSTDM1NmgzQT09
Meeting ID: 634 1965 2784
Passcode: 993852
Attendees will be muted during the colloquium, but will have the opportunity to ask questions at the end by clicking on the "raise hand” button (or send a request to me via chat).