Pantheon+SH0ES
This page documents the supernova half of the data: the Pantheon+SH0ES distance-modulus catalogue, of which 1,590 of 1,701 entries survive the redshift cut and enter the likelihood.
At a glance
| Quantity | Value |
|---|---|
| Entries in the file | 1,701 |
| Kept (z > 0.01) | 1,590 |
| Redshift range kept | 0.01016 → 2.26137 |
| Distance modulus | MU_SH0ES (or MU_SHOES) |
| Covariance | Pantheon+SH0ES_STAT+SYS.cov, rows/columns of the kept SNe |
Columns read
| Column | Meaning | Fallback name |
|---|---|---|
zHD | Hubble-diagram redshift | — |
MU_SH0ES | observed distance modulus | MU_SHOES |
MU_SH0ES_ERR_DIAG | diagonal error on μ | MU_SHOES_ERR_DIAG |
The loader (load_pantheon_data) raises an explicit error listing the available columns if one of the three is missing. The diagonal errors are only used for reporting: the likelihood uses the full covariance matrix (Covariance Handling).
The redshift cut
Supernovae with z ≤ 0.01 are removed to limit the influence of local peculiar velocities. The cut is applied to zHD, and the row indices of the kept supernovae are carried over to the covariance matrix so that the two stay aligned.
The distance moduli are SH0ES-calibrated
MU_SH0ES is the Pantheon+ distance modulus on the SH0ES calibration scale. The fit has no free absolute-magnitude nuisance parameter: it compares MU_SH0ES directly with the model μ(z) = 5 log₁₀(DL/Mpc) + 25. The H₀ values obtained (Parameter Constraints) therefore sit on that calibration scale and should not be read as an independent H₀ measurement.
How to load
# src/xi_protocol1b_bao_run.py
from pathlib import Path
from xi_protocol1b_bao_run import load_pantheon_data, load_pantheon_covariance
z, mu, mu_err, kept_idx, n_total = load_pantheon_data(Path("data/raw/Pantheon+SH0ES.dat"), zcut=0.01)
cov, cov_inv = load_pantheon_covariance(Path("data/raw/Pantheon+SH0ES_STAT+SYS.cov"), kept_idx)
The catalogue is an external survey product and is not redistributed with the repository; place it in data/raw/ by hand (Quick Run).