2026/07/22 by Suman Pramanick, Anoop Krishna, Rajesh Mondal +1
#astro-ph.CO #gr-qc
The light-cone (LC) effect introduces line-of-sight (LoS) statistical inhomogeneity into the 21-cm signal. Consequently, the traditional power spectrum (PS) fails to capture the full two-point statistical information. The evolving power spectrum (ePS), Pe(k, z), offers an alternative that accounts for this LoS evolution. We compare the statistical power of three different summary statistics: the standard cylindrical PS P(k_⊥,k_∥), slice-wise PS Ps(k, z) (3D PS for small bandwidth LC slices), and ePS Pe(k, z). We first demonstrate that Pe(k,z) successfully recovers the benchmark 3D PS of coeval simulations across most k and z, whereas the slice-wise PS recovers only at large k. To efficiently perform parameter inference, we train artificial neural network (ANN) emulators on 500 LC 21-cm signals. Our forecasts incorporate cosmic variance, estimated using 50 statistically independent realizations of the signal, alongside SKA-Low system noise for integration times of 1000 and 104 hrs. We find that ePS outperforms its peers, yielding 3 and 1.4 times tighter constraints than P(k_⊥,k_∥) and Ps(k,z), respectively. Our results establish the ePS as an optimal summary statistic for interpreting forthcoming data.