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In this section, we describe what the Scenario Machine is and how it works. Monte-Carlo simulations of binary star evolution allows one to study the evolution of a large ensemble of binaries and to estimate numbers of binaries at different evolutionary stages simultaneously . Originally, this method for statistical study of binary evolution was proposed by Kornilov and Lipunov (1983a,b)[85, 86] to investigate the spin evolution of magnetized NS in massive binary systems. Lipunov and Postnov (1987a,b,c, 1988)[114, 112, 113, 116] simulated low-mass binary evolution focusing on spin evolution of magnetized WD. Dewey and Cordes (1987)[45] and Bailes (1989)[7] applied a similar method for analysis of radio pulsar statistics; de Kool (1992)[42] and de Kool and Ritter (1993)[43] performed a detailed investigation using the Monte-Carlo method of the formation and diverse properties of galactic cataclysmic variables. Using a similar approach, Tutukov and Yungelson (1993b)[197] studied the formation of NS in binary systems (see also Yungelson et al., 1994[216]). A more detailed Monte-Carlo simulation of binary stellar evolution in young open clusters until both stars have become compact objects was recently reported by Pols and Marinus (1994)[163].
Of course, inevitable simplifications of analytical description of the binary evolution used to avoid extensive numerical calculations, mean that the numbers of different types of binaries are uncertain to within a factor of 2-3; ratios between various binary stellar populations are more precise.
Another method which is widely used for binary evolution studies is the calculation of distribution functions (see, e.g. Iben and Tutukov, 1984a,b;[72, 73] Meurs and van den Heuvel, 1989;[141] van den Heuvel, 1994,[205] for general discussion). However, within the framework of this method it is very difficult to take into account numerous factors influencing stellar evolution; it is especially hard to include even at a qualitative level the spin evolution of magnetized compact stars.