A noisy Monte Carlo algorithm - art. no. 074505

We propose a Monte Carlo algorithm to promote the Kennedy-Kuti linear accep t-reject algorithm which accommodates unbiased stochastic estimates of the probability to an exact one. This is achieved by adopting the Metropolis ac cept-reject steps for both the dynamical and noise configurations. We test it on the five state model and obtain desirable results even for the case w ith large noise. We also discuss its application to lattice QCD with stocha stically estimated fermion determinants.