The availability of large datasets has boosted the application of machine learning in many
fields and is now starting to shape active-matter research as well. Machine learning …

Networks of caustics can occur in the distribution of particles suspended in a randomly
moving gas. These can facilitate coagulation of particles by bringing them into close proximity, …

We study statistical properties of the eigenvectors of non-Hermitian random matrices,
concentrating on Ginibre's complex Gaussian ensemble, in which the real and imaginary parts of …

Background While males usually benefit from as many matings as possible, females often
evolve various methods of resistance to matings. The prevalent explanation for this is that the …

We show quantitatively how the collision rate of droplets of visible moisture in turbulent air
increases very abruptly as the intensity of the turbulence passes a threshold, due to the …

This modern and self-contained book offers a clear and accessible introduction to the
important topic of machine learning with neural networks. In addition to describing the …

Adaptive divergence and speciation may happen despite opposition by gene flow. Identifying
the genomic basis underlying divergence with gene flow is a major task in evolutionary …

Statistical properties of eigenvectors in non-Hermitian random matrix ensembles are discussed,
with an emphasis on correlations between left and right eigenvectors. Two approaches …

We analyze the motion of a system of particles subjected to a random force fluctuating in both
space and time, and experiencing viscous damping. When the damping exceeds a certain …

Immigration can rescue local populations from extinction, helping to stabilize a metapopulation.
Local population dynamics is important for determining the strength of this rescue effect, …