Abstract p-Adic mathematical physics is a branch of modern mathematical physics based on
the application of p-adic mathematical methods in modeling physical and related …

A review of theoretical concepts and diverse applications of sparse representations and
compressive sampling (CS) approaches in engineering mechanics problems is provided …

Sparse approximate solutions to linear equations are classically obtained via L1 norm
regularized least squares, but this method often underestimates the true solution. As an …

We present reconstructed convergence maps, mass maps, from the Dark Energy Survey
(DES) third year (Y3) weak gravitational lensing data set. The mass maps are weighted …

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of
increasing difficulty. The high-resolution and depth of imaging data now available render …

We present the first reconstruction of dark matter maps from weak lensing observational data
using deep learning. We train a convolution neural network with a U-Net-based architecture …

X-ray computed tomography (X-ray CT) has been widely used in the earth sciences, as it is
non-destructive method for providing us the three-dimensional structures of rocks and …

The superb image quality, stability, and sensitivity of JWST permit deconvolution techniques
to be pursued with a fidelity unavailable to ground-based observations. We present an …

The calculation of a sparse approximate solution to a linear system of equations is often
performed using either L1-norm regularization and convex optimization or nonconvex …

Context. Due to the limited number of antennas and the limited observation time, an array of
antennas in very long baseline interfer-ometry (VLBI) often samples the Fourier domain only …