Home
My Research
Talks
Publications
Teaching
Outreach
Contact
Light
Dark
Automatic
Application
Non-parametric analysis of the Hubble Diagram with Neural Networks
This study introduces a neural network-based method for nonparametric analysis of the Hubble diagram, extended to high redshifts. Validated using simulated data, the method aligns with a flat Λ (Lambda) cold dark matter model (ΩM ≈ 0.3) up to z ≈ 1-1.5, but deviates at higher redshifts. It also suggests increasing ΩM values with redshift, indicating potential dark energy evolution.
Lorenzo Giambagli
,
Duccio Fanelli
,
Guido Risaliti
,
Matilde Signorini
PDF
Cite
Project
Source Document
Cite
×