  Tensor robust principal component analysis (robust PCA) has been applied to
the lightning images. Robust PCA aims to classify the images into low-rank and
sparse components. The low rank and sparse components correspond to static
background separation and the dynamic (lightning) part of the images
correspondingly. After classification, Singular Value Decomposition (SVD)
unfold technique has been applied to sparse tensor, which transforms the tensor
to spatial-temporal spaces in the form of vector matrixes. Spectral evolution
shows the evolution of the polarization of the UV-Vis spectra. The contour maps
of 2D energy density plots reveal the zero-point energy fluctuations of the
bosons, fermions, and virtual matters from early to late stages. Detection of
such fluctuations in the early stages can help to remote sensing of the
lightning. 3D vector(ether) field representation of the sparse tensor of the
brightest lightning reveals the butterfly effect of the black holes with the
signatures of flapping. There is a correlation between the approximate entropy
and the chaos trends of the 3D vector field analyzed by the Lyapunov exponent.
In the brightest frame, the fractal dimension measures 0.8004, which is close
to the Fibonacci Hamiltonian.
