Continuous Wavelet Analysis of Matter Clustering Using the Gaussian-derived Wavelet

Abstract Continuous wavelet analysis has been increasingly employed in various fields of science and engineering due to its remarkable ability maintain optimal resolution both space scale. Here, we introduce wavelet-based statistics, including the power spectrum, cross correlation, bicoherence, analyze large-scale clustering matter. For this purpose, perform transforms on density distribution obtained from one-dimensional Zel’dovich approximation then measure spectra bicoherences distribution. Our results suggest that spectrum bicoherence can identify effects local environments at different scales. Moreover, apply statistics based three-dimensional isotropic IllustrisTNG simulation z = 0, investigate environmental dependence matter clustering. We find strength total increases with increasing except largest Besides, notice gas traces dark better than stars large scales all environments. On small scales, correlation between first decreases density. This is related impacts active galactic nucleus feedback distribution, which also varies environment a similar trend gas. findings are qualitatively consistent previous studies