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Hello again Rod,
I’m sorry I didn’t respond to your reply at the time, but better late than never. First I want to thank you for it, but then I want to clarify what I meant.
I wanted to find out in what sense you claim that your model explains the phenomena Bell’s theorem identifies as perplexing. In my mind, the first thing a model must do to achieve that is to give formulae which generate the correct probabilities for the outcomes. Standard QM does that, and Bohmian mechanics does that in a different way, provided you assume the “equilibrium” distribution for the initial positions. I mentioned the possibility of other distributions only as a reminder to this – if you choose a “wrong” distribution, you can even get wrong results! You say that your model can also accommodate “wrong” distributions, but if the final boundary conditions are supplied in the “usual” manner, i.e., with the same probabilities, a “wrong” distribution won’t lead to “wrong” results, will it?
In my work, I provided a retrocausal toy model which gives the “correct” results in a different way, and I wanted to compare this with other publications discussing zig-zag causation, but I couldn’t make a meaningful comparison with your work. I think that’s not a surprise, because as you say your work is an “add-on,” and uses the standard QM formulae to get the outcome probabilities.
In this sense, I think it’s quite different from Bohmian Mechanics (BM). True, you have the particle path going down the corresponding “finger” in your measurement device, as in BM, but you’ve supplied the corresponding final boundary condition, so the probability for this or that outcome is predetermined, unlike BM. And if I want to compare and ask how the probabilities are determined, I’m back to comparing with standard QM.
Am I right?