Pierre Boccard

Cosmology from the Rubin Void Size Function

The void size function (VSF), the abundance of voids as a function of their size, is sensitive to the matter density, to the amplitude of the matter fluctuations and to dark energy, but it has mostly been used with spectroscopic surveys. In this project I present the first forecast of the cosmological constraints from voids in the photometric data of the Rubin Observatory LSST, using a realistic mock catalogue of luminous red galaxies built from the SkySim5000 simulation and the model of Verza et al. extended to photometric redshifts. I also study the combination of voids with galaxy clusters.

With G. Degni, N. Schuster, G. McFarland, K. Ghaemi Ardakani, P. Vielzeuf and A. Pisani · CPPM, LSST DESC · 2024–present

• paper Boccard et al., Cosmology from the Rubin Void Size Function, soon to be submitted to A&A

Toward modelling redshift uncertainties in the photometric void size function

Photometric redshift errors spread galaxies along the line of sight over distances comparable to the size of voids. We extend the theoretical model of the void size function to include this effect, as a damping of the variance of the density field, and we test it on AbacusSummit halo lightcones with mock photometric redshifts. This is a first step towards modelling voids in LSST and Euclid.

With G. Verza, G. Degni, N. Schuster, G. McFarland, K. Ghaemi Ardakani, P. Vielzeuf and A. Pisani · CPPM, CCA (Flatiron Institute) · 2024–present

• paper Boccard et al., Toward modelling redshift uncertainties in the photometric void size function, soon to be submitted to ApJL

VoidX-Voronoi: finding voids with a graph neural network

Classical void finders depend on hand-tuned choices: smoothing scales, density thresholds and merging criteria. In this project I treat void finding as a node-classification problem on the graph given by the Voronoi tessellation of the tracers, and train a deep graph-attention network to reproduce a void catalogue directly from it, in an N-body simulation. It is a side project, in which I also build my skills in machine learning.

Side project · CPPM · ongoing

Searching for decaying dark matter in cosmic voids

The gamma-ray signal of decaying dark matter scales with the dark matter density, while voids contain very few of the astrophysical sources that dominate the gamma-ray sky elsewhere. With Elena Pinetti, we are preparing a search for decaying dark matter that combines DESI void catalogues, Fermi-LAT gamma-ray data and Euclid weak-lensing shear, which measures the dark matter profile of the voids. The project is at the planning stage.

DESI · in preparation