TY - JOUR AB - We consider large non-Hermitian random matrices X with complex, independent, identically distributed centred entries and show that the linear statistics of their eigenvalues are asymptotically Gaussian for test functions having 2+ϵ derivatives. Previously this result was known only for a few special cases; either the test functions were required to be analytic [72], or the distribution of the matrix elements needed to be Gaussian [73], or at least match the Gaussian up to the first four moments [82, 56]. We find the exact dependence of the limiting variance on the fourth cumulant that was not known before. The proof relies on two novel ingredients: (i) a local law for a product of two resolvents of the Hermitisation of X with different spectral parameters and (ii) a coupling of several weakly dependent Dyson Brownian motions. These methods are also the key inputs for our analogous results on the linear eigenvalue statistics of real matrices X that are presented in the companion paper [32]. AU - Cipolloni, Giorgio AU - Erdös, László AU - Schröder, Dominik J ID - 10405 IS - 5 JF - Communications on Pure and Applied Mathematics SN - 0010-3640 TI - Central limit theorem for linear eigenvalue statistics of non-Hermitian random matrices VL - 76 ER -