Supernovae Data - Sum of Squared Errors

Read more about the hypothesis being tested on the home page.

\( \chi^2 = \Sigma_i (\mu_i^{d} - \mu_i^{m})^2 / \sigma^2 \)
\( \chi^2 = \Sigma_i (\mu_i^{d} - \mu_i^{m})^2 \)

Data: Pantheon+SH0ES, Distances and Covariances

Squared Sum of Errors: \[\chi^2= \Sigma_i (d_{d} - d_{m})^2 / \sigma^2 \] where dd is the distance modulus in the data, and dm is the distance predicted by the model.
Hypothesis (red): \[ d_L = (1+z)\frac{c}{H_{0}} log(1 + z) \]
ΛCDM (green): ΩM: ΩΛ:


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