<i>In information theory terms, a simulation can not contain more information that the sum total of the input data and the content of the simulation algorithm.</i><p>This is false outside of the most trivial definition, when you simulate evolutionary systems you can create systems far more complex than the algorithm used to generate them, the problem domain, or any other factor prior to running the simulation.  That information is crated from your random input stream which does not contain information in the classical definition.<p>PS: As to the larger context of the discussion.  From a simulation standpoint sending other scientist the code and having them run it is a bad idea. Reproducibility does not involve the lab that made the discovery sending the devices used to make the discovery to another lab.   The goal is for someone to be able to see the same effect with the most independent setup possible.  If scientist A says "building this a model with these assumptions &#62; this result."  Then another lab creates their own software which runs and finds either the same or a different result.  Or, they can look at the assumptions or inputs and say this is bad data try again.  Or, they can look at the code and say, here is a bug fix it and try again.  But, those are three independent steps best carried out by diffrent groups.