On 2/7/2020 9:54 PM, Bruce Kellett wrote:
On Sat, Feb 8, 2020 at 4:41 PM 'Brent Meeker' via Everything List
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On 2/7/2020 8:14 PM, Bruce Kellett wrote:
On Sat, Feb 8, 2020 at 1:26 PM 'Brent Meeker' via Everything List
<[email protected]
<mailto:[email protected]>> wrote:
On 2/7/2020 5:57 PM, Bruce Kellett wrote:
There is nothing that picks out one particular set of paths
as preferred in the many-worlds situation.
Sure you can. For example you can pick out the set of paths
whose statistics are within some bounds of the mean.
Assuming you know what the 'mean' is absent any experiment.
The mean is estimated by the average of the experimental values.
In other words, you use the data to infer probabilities. But the same
data occur whatever the probabilities, so your backward inference to
the probabilities is meaningless.
Otherwise you are just cherry picking data to support your
arbitrary theory.
One can only get that in a stochastic one-world model.
All paths occur in a stochastic one-world model too.
No they don't. They are possible, perhaps, but they do not
necessarily occur.
They don't /necessarily/ occur. But they probabilistic occur.
It means they occur with high probability given enough instances of the
experiment. So I don't see why you attach great significance to all
possibilities occurring in MWI.
What on earth does that mean?
If the probability is very low, then the improbable sequences of
results need not occur even if you repeat the experiment 'till the
heat death of the universe. In MWI the low weight sequences
necessarily occur in every run of the experiments. Do you not see the
difference?
But the improbable sequences will occur in the same proportion in both
scenarios.
Otherwise it wouldn't be a stochastic model. So it seems that
all you objections to MWI apply equally.
Get a grip, Brent.
The only difference is that some probability measure is
assumed as part of the model.
And this gives one a principled reason for ignoring the paths
that are not observed.
Why not ignore them because they are not observed? That's a
principled reason.
That is a one-world theory. And I agree that that is the way to go.
Low probability has an independent meaning in the one-world case,
so one is unlikely to observe a low probability set of results.
One is unlikely to observe a result that is realized in only a
small fraction of the MW branches.
Why? One does not choose one's results at random from the set of all
possible results.
The theory is that which experience "you" have is determined by making a
copy of you for each result and one of them, at random, is the "you" who
has the experience. So it is effectively a random sample from the
possible results.
In MWI there is always an observer who gets every possible set of
results. Why ignore those unfortunates who get rest inconsistent with
your pet theory?
Because they are relatively few in number and hence unlikely to be the
"you" who gets the result.
I agree that MWI fails to derive the Born rule. But I don't
agree that it is inconsistent with it, given the version of MWI
that postulates many branches...not just one per possible outcome.
The point is that MWI is inconsistent with experience. There will
always be observers who get results inconsistent with the Born rule.
Why do you think you can't get a result inconsistent with the Born rule
in one world. What do you mean by "inconsistent". The results are
probabilistic so they will have degrees of consistency and inconsistency
with the Born rule...just as there is a spread of results in MWI.
And we cannot ensure that we are not such observers. So how can we
claim that our theory is confirmed by the data? The data are
consistent with all possible theories -- or none at all.
But it's not all or nothing. It's statistics.
Brent
Bruce
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