Cosmological Data Analysis of the Power-Law Gravity Model Using Recent Datasets

The accelerated expansion of the Universe has motivated extensive studies of modified theories of gravity as alternatives to dark energy. In this work, we investigate the power-law  gravity model in the framework of symmetric teleparallel gravity using recent cosmological observations. The model parameters are constrained through a Bayesian Markov Chain Monte Carlo analysis employing two combinations of datasets: Pantheon+SHOES + Hubble measurements and Pantheon+SHOES + Hubble measurements + DESI baryon acoustic oscillation data. The modified Friedmann equation corresponding to the power-law  model is solved numerically to reconstruct the cosmic expansion history. The resulting constraints are compared with those obtained for the standard CDM cosmology. Model performance is assessed using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). This analysis provides updated observational constraints on power-law  gravity and examines its consistency with current cosmological observations.