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The optimizations of the track fittings require complex simulations ofsilicon strip detectors to be compliant with the fundamental properties of thehit heteroscedasticity. Many different generations of random numbers must beavailable with distributions as similar as possible to the test-beam data. Afast way to solve this problem is an extension of an algorithm of frequent usefor the center of gravity positioning corrections. Such extension gives asingle method to generate the required types of random numbers. Actually, thestarting algorithm is a random number generator, useful in a reverse mode: fromnon uniform sets of data to uniform ones. The inversion of this operationproduces random numbers of given distributions. Many methods have beendeveloped to generate random numbers, but none of those methods is directlyconnected with this positioning corrections. Hence, the adaptation of thecorrection algorithm to operate in both mode is illustrated. A sampledistribution is generated and its consistency is verified with theKolmogorov-Smirnov test. As final step, the elimination of the noise isexplored, in fact, simulations require noiseless distributions to be modifiedby given noise models.

Unifying positioning corrections and random number generations in silicon micro-strip trackers