Intepretable and higher-order statistics for late-time cosmology

Contribution List

1. Introduction to the Workshop

Alex Cole (University of Amsterdam), Matteo Biagetti (SISSA)

6/27/22, 10:00 AM

2. Large Scale Structures in an hour or so

Emiliano Sefusatti (OATs)

6/27/22, 10:30 AM

The goal of this lecture is to provide a pedagogical introduction to the standard cosmological model, with a particular focus on large-scale structure formation at late times.

3. Introduction to the Data Challenge

Juan Manuel Calles Hansen (Pontificia Universidad Católica de Valparaíso), Matteo Biagetti (SISSA)

6/27/22, 12:00 PM

4. Practical, Informative, Spatial Statistics with Applications to Cosmological Large Scale Structure

Tom Abel

6/27/22, 2:00 PM

23. Towards optimal likelihood-free inference for cosmology with deep learning

Dr Francisco Villaescusa-Navarro (CCA, Flatiron)

6/27/22, 3:30 PM

In this talk I will first show with toy examples how deep learning can find optimal summary statistics to extract the maximum information from cosmological data. I will then show how it can also perform really complex tasks like extracting information from very small, highly non-linear, scales while marginalizing over baryonic effects at the field level. I will also present the major...

11. An introduction to persistent homology

Magnus Botnan

6/28/22, 9:30 AM

In this talk, I will first give a gentle introduction to persistent homology with an emphasis on certain theorems that will be referenced in Mathieu’s talk later in the day. After this, I will discuss some recent advances in multiparameter persistent homology.

8. Constraining Cosmology with Persistent Homology

Jacky Yip (University of Wisconsin-Madison)

6/28/22, 11:00 AM

Persistent homology naturally addresses the multi-scale characteristics of the large scale structure. I will discuss the specifics of its application to mock galaxy catalogues to construct a simple and interpretable summary statistic. With the Fisher matrix formalism, I will show that our approach outperforms the momentum-space statistics in constraining cosmological parameters and offers...

10. Higher-order statistics in cosmic shear

Sven Heydenreich

6/28/22, 2:00 PM

The weak gravitational lensing effect is a powerful tool to study the structure and evolution of our Universe and, according to the Dark Energy Task Force, one of the most promising methods to constrain the equation of state of dark energy. In this talk, I will present two higher-order shear statistics: the third-order aperture masses and persistent homology. I will discuss their potential...

13. Introduction to Topological Machine Learning

Mathieu Carriere

6/29/22, 9:30 AM

In this talk, I will show through several examples and applications how persistence theory can be used to build relevant topological descriptors/signatures from data sets, that encode useful topological information that is often complementary to other usual descriptors. Then, we will show how these signatures can be converted into features for further data analysis and machine learning tasks,...

12. Antifragile Persistent Homology using Fisher Information

Karthik Viswanathan

6/29/22, 11:00 AM

Antifragility is a property of systems in which they increase their capability to thrive in the presence of volatility and noise. I will present how persistent homology can be made adaptive by learning the optimal filtration that is resilient to noise in data. This is done by maximizing the Fisher Information among a variational family of filtration parameters using gradient descent. By doing...

9. Scattering transforms, recent applications in astrophysics and cosmology

Erwan Allys

6/29/22, 2:00 PM

New statistical descriptions related to the so-called Scattering Transform recently obtained attractive results for several astrophysical applications. These statistics share ideas with convolutional neural networks, but do not require to be learned, allowing for a direct characterization of interactions between scales in non-linear processes. In this talk, I will present these statistical...

16. Cosmology beyond the average with one-point statistics

Cora Uhlemann

6/30/22, 9:30 AM

One-point statistics such as counts-in-cells capture essential non-Gaussian properties of the cosmic web, including peculiar regions of high and low density. I will show that those statistics not only provide information complementary to common two-point statistics, but also allow for accurate theoretical predictions. I will explain how matter counts-in-cells statistics and their dependence on...

15. Joint power spectrum-bispectrum covariance and the squeezed configurations

Lina Castiblanco

6/30/22, 11:00 AM

Predictions from single-field inflation are consistent with CMB observations. Large-scale structure observations will improve our knowledge of the early universe. In particular, we can learn much about the inflationary era by testing for primordial non-Gaussianity (PNG). The upcoming galaxy surveys promise to improve such constraints by mapping the 3-dimensional distribution of matter and...

14. Analysing the PDF of density fluctuations - can it work in real data?

Oliver Friedrich

6/30/22, 2:00 PM

Key analyses of the cosmic large-scale structure only capture the "scale-dimension" of the cosmic web: they measure the variance of fluctuations as a function of scale. A powerful way to complement this vast compression of data is to add the "density-dimension": at a fix smoothing scale one can analyse the entire shape of the probability density function (PDF) of density fluctuations (cf. Cora...

17. Amplitudes meet the Swampland

Gary Shiu

6/30/22, 4:00 PM

This talk is hosted by ICTP

18. The Quijote PNG simulations - A test bed for higher order statistics and primordial non-Gaussianity

William Coulton

7/1/22, 9:00 AM

Constraints on primordial non-Gaussianity (PNG) provide powerful insights into the early universe. To date, the CMB has been the leading source of information and I will briefly overview what more we expect to gain from upcoming experiments. Large scale structure measurements potentially have a wealth of information that could surpass the CMB. However, due to the non-linear nature of...

19. Dark Matter Dynamics

Tom Abel

7/1/22, 11:00 AM

IFPU Colloquium

20. Cosmology with Cosmic Voids

Nico Hamaus (LMU Munich)

7/1/22, 2:00 PM

Voids in the large-scale structure of the Universe are currently entering the realm of precision cosmology. Most ongoing and planned surveys are considering them as a cosmological probe in various ways. The aim is to extract information that is complementary to what is already accessible via the traditional probes. I will present some recent highlights from the analysis of cosmic voids in both...

21. The Initial Shape of the Universe

Juan Manuel Calles Hansen (Pontificia Universidad Católica de Valparaíso)

7/1/22, 3:00 PM

We want to explore the potential of topological data analysis in detecting primordial non-Gaussianity through observations of the large scale structures of the universe. As a proof of concept, we estimate the Fisher information content on primordial non-Gaussianity using halo catalogs generated from N-body simulations run with both Gaussian and non-Gaussian initial conditions. We perform...

22. Closing Remarks

Alex Cole (University of Amsterdam), Matteo Biagetti (SISSA)

24. Introduction to the Data Challenge

Juan Manuel Calles Hansen (Pontificia Universidad Católica de Valparaíso), Matteo Biagetti (SISSA)

6. TBA

Alex Cole (University of Amsterdam)