We place ourselves in the setting of high-dimensional statistical inference where the number of variables p in a dataset of interest is of the same order of magnitude as the number of observations n.

Random Matrix Theory (RMT) has emerged as a potent framework to characterise the statistical properties of eigenvalues in large complex systems, bridging disciplines from quantum physics to number ...

Scientists analyzed each element of the neutrino mass matrix belonging to leptons and showed theoretically that the intergenerational mixing of lepton flavors is large. Furthermore, by using the ...

A well-known problem in numerical ecology is how to recombine presence-absence matrices without altering row and column totals. A few solutions have been proposed, but all of them present some issues ...

A potent theory has emerged explaining a mysterious statistical law that arises throughout physics and mathematics. Imagine an archipelago where each island hosts a single tortoise species and all the ...

We prove that given any 𝜖 > 0, random integral 𝑛 × 𝑛 matrices with independent entries that lie in any residue class modulo a prime with probability at most 1 − 𝜖 have cokernels asymptotically (as ...

Scientists are exploring a mysterious pattern, found in birds’ eyes, boxes of marbles and other surprising places, that is neither regular nor random. All complex correlated systems, from Arctic melt ...