On Fri, Feb 7, 2020 at 9:54 PM Lawrence Crowell < goldenfieldquaterni...@gmail.com> wrote:
> On Thursday, February 6, 2020 at 10:59:27 PM UTC-6, Bruce wrote: >> >> >> This argument from Kent completely destroys Everett's attempt to derive >> the Born rule from his many-worlds approach to quantum mechanics. In fact, >> it totally undermines most attempts to derive the Born rule from any >> branching theory, and undermines attempts to justify ignoring branches on >> which the Born rule weights are disconfirmed. In the many-worlds case, >> recall, all observers are aware that other observers with other data must >> exist, but each is led to construct a spurious measure of importance that >> favours their own observations against the others', and this leads to an >> obvious absurdity. In the one-world case, observers treat what actually >> happened as important, and ignore what didn't happen: this doesn't lead to >> the same difficulty. >> >> Bruce >> > > This appears to argue that observers in a branch are limited in their > ability to take the results of their branch as a Bayesian prior. This > limitation occurs for the coin flip case where some combinations have a > high degree of structure. Say all heads or a repeated sequence of heads and > tails with some structure, or apparent structure. For large N though these > are a diminishing measure. > I don't think you have fully come to terms with Kent's argument. How do you determine the measure on the observed outcomes? The argument that such 'outlier' sequences are of small measure fails at the first hurdle, because all sequences have equal measure -- all are equally likely. In fact, all occur with unit probability in MWI. Bruce > An observer might see their branch as having sufficient randomness to be a > Bayesian prior, but to derive a full theory these outlier branches with the > appearance of structure have to be eliminated. This is not a devastating > blow to MWI, but it is a limitation on its explanatory power. Of course > with statistical physics we have these logarithms and the rest and such > slop tends to be "washed out" for large enough sample space. > > No matter how hard we try it is tough to make this all epistemic, say > Bayesian etc, or ontological with frequentist statistics. > > LC > -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/everything-list/CAFxXSLRz%3D6MzUV13uBDrKrH%2BAO_RhizyyCaT1wcdpF6ctLxBUA%40mail.gmail.com.
