The paper by Dinda and Maartens explores the evidence for dynamical dark energy using baryon acoustic oscillation (BAO) measurements from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). They use a model-agnostic approach to reconstruct the equation of state of dark energy, independent of any specific dark energy model, by applying Gaussian Process (GP) regression. The study combines DESI DR1 BAO data with other datasets, including CMB distance priors and supernova data from the Pantheon+ sample. Key findings include: - The evidence for dynamical dark energy is less significant compared to the evidence when using the \(w_0 w_a\)CDM model, which is the primary model used in the DESI paper. - The reconstructed equation of state \(w(z)\) from CMB+DESI DR1 BAO data shows a preference for phantom behavior, but this evidence is not strong enough to conclude significant deviations from the standard \(\Lambda\)CDM model. - When combining DESI DR1 BAO data with supernova data, the reconstructed \(w(z)\) is consistent with the \(\Lambda\)CDM model within 1σ to 2σ confidence levels. - The model-agnostic approach provides constraints on cosmological parameters such as the Hubble constant and the matter-energy density parameter, which are not consistent with the results reported in the DESI paper using the \(w_0 w_a\)CDM model but are somewhat consistent with the \(w\)CDM model. - The normalized energy density parameter of dark energy, \(f_{\text{DE}}\), is also reconstructed, showing that deviations from the \(\Lambda\)CDM value are not significant. In conclusion, the model-agnostic approach suggests significantly lower evidence for dynamical dark energy compared to the \(w_0 w_a\)CDM model, indicating that the evidence for dynamical dark energy is not strong enough to firmly conclude its existence.The paper by Dinda and Maartens explores the evidence for dynamical dark energy using baryon acoustic oscillation (BAO) measurements from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). They use a model-agnostic approach to reconstruct the equation of state of dark energy, independent of any specific dark energy model, by applying Gaussian Process (GP) regression. The study combines DESI DR1 BAO data with other datasets, including CMB distance priors and supernova data from the Pantheon+ sample. Key findings include: - The evidence for dynamical dark energy is less significant compared to the evidence when using the \(w_0 w_a\)CDM model, which is the primary model used in the DESI paper. - The reconstructed equation of state \(w(z)\) from CMB+DESI DR1 BAO data shows a preference for phantom behavior, but this evidence is not strong enough to conclude significant deviations from the standard \(\Lambda\)CDM model. - When combining DESI DR1 BAO data with supernova data, the reconstructed \(w(z)\) is consistent with the \(\Lambda\)CDM model within 1σ to 2σ confidence levels. - The model-agnostic approach provides constraints on cosmological parameters such as the Hubble constant and the matter-energy density parameter, which are not consistent with the results reported in the DESI paper using the \(w_0 w_a\)CDM model but are somewhat consistent with the \(w\)CDM model. - The normalized energy density parameter of dark energy, \(f_{\text{DE}}\), is also reconstructed, showing that deviations from the \(\Lambda\)CDM value are not significant. In conclusion, the model-agnostic approach suggests significantly lower evidence for dynamical dark energy compared to the \(w_0 w_a\)CDM model, indicating that the evidence for dynamical dark energy is not strong enough to firmly conclude its existence.