A new highly convergent Monte Carlo method for matrix computations Original Research Article

In this paper a second degree iterative Monte Carlo method for solving systems of linear algebraic equations and matrix inversion is presented. Comparisons are made with iterative Monte Carlo methods with degree one. It is shown that the mean value of the number of chains N, and the chain length T, required to reach given precision can be reduced. The following estimate on N is obtained: N=Nc/(cN+bN1/2c)2, where Nc is the number of chains in the usual degree one method. In addition it is shown that b>0 and that N