1. Robin boundary conditions are used in heat conductance theory to interpolate between a perfectly insulating boundary, described by Neumann boundary conditions, and a temperature fixing boundary, described by Dirichlet boundary conditions. To date, most studies concentrated on the first few Robin eigenvalues, with applications in shape optimization and related isoperimetric inequalities and asymptotics of the first eigenvalues.
Our goal is very different, aiming to study the difference between high-lying Robin and Neumann eigenvalues. I expect the questions that arose in this study to significantly advance spectral theory.
2. The theory of uniform distribution of sequences modulo one has a long history, with many developments since its creation over a century ago. Much more recent is the study of ``local'' statistics of sequences, motivated by problems in quantum chaos and the theory of the Riemann zeta function. Key examples of such local statistics are the nearest neighbour spacing distribution, which is defined as the limit distribution (assuming it exists) of the gaps between neighbouring elements in the sequence, rescaled so as to have mean value unity; and the pair correlation function, which measures repulsion between pairs of levels, and is analytically the most accessible example of a ``local'' statistic.
For many sequences arising in number theory, one believes that these local statistics coincide with those of random numbers, but establishing this rigorously is notoriously difficult. One of the few examples where the level spacing distribution was understood is that of the fractional parts of square roots of integers, which was discovered to be non-random in 2004. However, if one perturbs the sequence by dilating it, then it is believed that the generic dilates will revert to having random behavior. One of the main goals for the second part of the project is to establish it for the pair correlation function, and the work I am currently doing with my former postdoc Niclas Technau holds great promise for this.