des-y5-sn
Compute the likelihood of DES Y5 Supernova data
File |
likelihood/des-sn/des_y5_sn_likelihood.py |
Attribution |
DES Collaboration |
URL |
|
Citations |
DES Collaboration: T. M. C. Abbott et al 2024 ApJL 973 L14 |
This module gives a likelihood of the distance modulus of the DES Y5 supernovae. It marginalizes over the supernova absolute magnitude so there is no need to vary that parameter.
The module starts from the angular diameter distance so it can apply the heliocentric correction, rather than reading the computed mu(z) values.
Assumptions
Supernova modelling
FLRW metric and D_A, D_L relation
Setup Parameters
Name |
Type |
Default |
Description |
|---|---|---|---|
data_file |
str |
module_dir/DES-SN5YR_HD.csv |
Optional. File containing supernova measurements |
covmat_file |
str |
module_dir/STAT+SYS.txt.gz |
Optional. File containing supernova measurements |
x_section |
str |
distances |
Datablock section for input theory redshift |
x_name |
str |
z |
Datablock name for input theory redshift |
y_section |
str |
distances |
Datablock section for input theory angular diameter distance |
y_name |
str |
D_A |
Datablock name for input theory angular diameter distance |
like_name |
str |
desy5sn |
Named for the saved output likelihood |
likelihood_only |
bool |
False |
Skip saving everything except the likelihood. This prevents you from using e.g. the Fisher matrix sampler but can be faster for quick likelihoods |
include_norm |
bool |
False |
Include the normalizing constant at the start of the likelihood. May be needed when comparing models. |
Input values
Section |
Name |
Type |
Default |
Description |
|---|---|---|---|---|
distances |
z |
real 1d |
Redshifts of calculated theory D_A(z) |
|
D_A |
real 1d |
Angular diameter distance D_A(z) at given redshifts |
Output values
Section |
Name |
Type |
Description |
|---|---|---|---|
likelihoods |
desy5sn_like |
real |
Gaussian likelihood value of supplied theory D_A(z) |
data_vector |
desy5sn_covariance |
real 2d |
Fixed covariance matrix, only if likelihood_only=F |
desy5sn_data |
real 1d |
Fixed data vector mu_obs, only if likelihood_only=F |
|
desy5sn_simulation |
real 1d |
Simulated data vector including simulated noise for e.g. ABC, only if likelihood_only=F |
|
desy5sn_theory |
real 1d |
Predicted theory values mu_theory(z_obs) only if likelihood_only=F |
|
desy5sn_chi2 |
real |
chi^2 value, only if likelihood_only=F |