Okay dudes, no more talk about my abandonment of atheism. Here’s some science and engineering talk.
I know something about computer simulations. In fact, I know a lot about them, and their limitations.
Search algorithms (and especially AI-related search algorithms) are a specialty of mine, as is combinatorial mathematics.
The branching factor (the average number of moves per side) in chess yields approximately 10^120 possible outcomes, but the number of legally achievable positions is approximately 10^80 — the estimated number of elementary particles (protons and neutrons) in the entire known universe. Compare this to the branching factor of nucleotide sequences in the DNA molecule. Do the math.
Finite element analysis (FEA) of nonlinear, transient, dynamic systems, with the use of the most sophisticated, powerful computer program ever devised for such purposes (LS-DYNA, originally conceived at Lawrence Livermore National Laboratory in the mid-1970s for the development of variable-yield nuclear weapons) is another of my computer-simulation specialties.
Dyna has been used heavily in the automotive industry for simulating car crashes, so that cars can be designed to produce the least damage to occupants.
In these simulations everything is precisely known and empirically quantified (the material properties of the components — modulus of elasticity, mass density, shear modulus, precisely calibrated failure modes, etc.).
In addition, the explicit FEA time step (the minimal integration time step determined by the software based on the speed on sound in the smallest finite element and its mass density, which is required to avoid numerical instability) is critical. In my simulations the time step is approximately a ten-millionth of second, during which partial differential equations, based on the laws of physics (F=ma in particular) are solved to compute the physical distortion of the system and the propagation of the forces throughout the system in question.
One learns very quickly with FEA simulations that even with all of this knowledge and sophistication one must empirically justify the results of the simulation incrementally by comparing the results with the reality it attempts to simulate.
One false assumption about a material property or any of the other aspects of a simulation can completely invalidate it. Worse yet, it can produce results that seem reasonable, but are completely wrong.
So, the next time someone tries to convince you that a computer simulation has validated the creative power of the Darwinian mechanism of random errors filtered by natural selection in biology, you should tell them to go back to school and learn something about legitimate computer simulations, and how difficult it is to produce reliable results, even when the details are well known.