Dataset of PCA Applied to Fermi-Pasta-Ulam-Tsingou Trajectories

The dataset contains the correlation matrix's eigenvalues and the reconstruction errors from PCA performed using singular value decomposition, applied to the trajectories of Fermi–Pasta–Ulam–Tsingou (FPUT) $\beta$ model with $N = 32$ coupled harmonic oscillators. Each Numpy array is obtained from PCA applied to an entire model's trajectory comprising $n_s = 4{,}000{,}000$ data points, initialized by exciting the first mode ($k=1$). The parameter $\beta$ varies over the interval $[0.1, 3]$, in increments of $0.1$.