Resetting Dyson Brownian motion

In this paper, we introduce a new stochastic process of $N$ interacting particles on the line that evolve via Dyson Brownian motion (DBM) with Dyson's index $\beta > 0$ and undergo simultaneous resetting to their initial positions at a constant rate $r$. We call this process the resetting Dyson Brownian motion (RDBM) -- in short the $\beta$-RDBM. For $\beta = 1,2,4$, the positions of the particles in the RDBM can be interpreted as the eigenvalues of a random matrix ensemble where the entries of an $N x N$ Gaussian matrix evolve as simultaneously resetting Brownian motions (with rate $r$) in the presence or absence of a harmonic trap. For $r=0$ and in the presence of a harmonic trap, this system reaches an equilibrium Gibbs-Boltzmann state of the so called Dyson log-gas. However, the stochastic resetting drives the system at long time to a nonequilibrium stationary state (NESS). We compute exactly the joint distribution of the positions of the particles in this NESS for all $\beta>0$ and calculate several observables for large $N$: the average density profile of the gas, the extreme value statistics, the spacing between two consecutive particles and the full counting statistics. We show that a nonzero resetting rate $r>0$ drastically changes the nature of the fluctuations in the stationary state: while the log-gas is rather rigid, the $\beta$-RDBM in its NESS becomes fluffy, i.e., the fluctuations of different observables are of the same order as their mean. In the absence of a harmonic trap, our results for the $\beta = 2$-RDBM can be related to nonintersecting Brownian motions in the presence of resetting. Our model demonstrates interesting effects arising from the interplay between the eigenvalue repulsion and the all-to-all attraction (generated by stochastic resetting) in an interacting particle system. Numerical simulations are in excellent agreement with our analytical results.