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Reconstruction of Continuous Cosmological Fields from Discrete Tracers with Graph Neural Networks
Yurii Kvasiuk, Jordan Krywonos, Matthew C. Johnson +1
We develop a hybrid GNN-CNN architecture for the reconstruction of 3-dimensional continuous cosmological matter fields from discrete point clouds, provided by observed galaxy catal…
Constraints on cosmology beyond CDM with kinetic Sunyaev Zel'dovich velocity reconstruction
Jordan Krywonos, Selim C. Hotinli, Matthew C. Johnson
Kinetic Sunyaev Zel'dovich velocity reconstruction uses the statistically anisotropic cross-correlation between cosmic microwave background (CMB) temperature anisotropies and a gal…
Improving Photometric Galaxy Clustering Constraints With Cross-Bin Correlations
Jordan Krywonos, Jessica Muir, Matthew C. Johnson
Clustering studies in current photometric galaxy surveys focus solely on auto-correlations, neglecting cross-correlations between redshift bins. We evaluate the potential advantage…
Cosmological measurements from the CMB and BAO are insensitive to the tail probability in the assumed likelihood
Jordan Krywonos, Simone Paradiso, Alex Krolewski +2
When fitting cosmological models to data, a Bayesian framework is commonly used, requiring assumptions on the form of the likelihood and model prior. In light of current tensions b…