  In this talk we show how the sign problem, occurring in dynamical simulations
of random matrices at nonzero chemical potential, can be avoided by judiciously
combining matrices into subsets. One can prove that these subsets have real and
positive weights such that importance sampling can be used in Monte Carlo
simulations. The number of matrices per subset is proportional to the matrix
dimension. We measure the chiral condensate and observe that the statistical
error is independent of the chemical potential and grows linearly with the
matrix dimension, which contrasts strongly with its exponential growth in
reweighting methods.
