[astroseminar at Sapienza] Avviso di Seminario - Maria Giovanna Dainotti - 4 febbraio ore 16 Conversi

Alessandro Melchiorri alessandro.melchiorri at roma1.infn.it
Thu Jan 30 17:02:53 CET 2025


A New Master Supernovae Ia sample and the investigation of the H0 
tension

A cura di Maria Giovanna Dainotti (National Astronomical Observatory of 
Japan)

martedì 4 feb 2025, 16:00  → 18:00  Europe/Rome
Aula Conversi (Dip. di Fisica - Edificio G. Marconi)

Descrizione
Modern cosmological research still thoroughly debates the discrepancy 
between local probes and the Cosmic Microwave Background observations in 
the Hubble constant (
H0 ) measurements, ranging from  4σ  to 6σ. In the current study we 
examine this tension using the Supernovae Ia (SNe Ia) data from the 
Pantheon, PantheonPlus, Joint Lightcurve Analysis (JLA), and Dark Energy 
Survey (DES) catalogs together with their combination called Master 
Sample containing 3789 SNe Ia, and dividing all of them into 
redshift-ordered bins. Two main binning techniques are presented: the 
equipopulation and the equispace in the logz. We perform a Markov-Chain 
Monte Carlo analysis (MCMC) for each bin to determine the H0  value, 
estimating it within the standard flat ΛCDM and the w0waCDM models. 
These H0 values are then fitted with the following phenomenological 
function: H0(z)=H0^/(1+z)^α, where H0^ is a free parameter representing 
H0(z) fitted at z=0 and α is the evolutionary parameter. Our results 
indicate a decreasing trend characterized by α∼0.01  whose consistency 
with zero range from
1.00σ  at 3 bins in the Pantheon sample with the w0waCDM model to >6σ  
at 12 bins with the JLA and DES samples within the ΛCDM model. Such a 
trend in the SNe Ia catalogs could be due to evolution with redshift for 
the SNe Ia astrophysical variables or unveiled selection biases. 
Alternatively, intrinsic physics, possibly the f(R)  theory of gravity, 
could be responsible for this trend. I will also explore possibility 
with combining Gamma-Ray Bursts, BAO and SNe Ia with a new likelihood 
analysis and without binning the data.



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