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billschnieder said:If λ can be anything, then it can also be a non-local hidden variable. I'm trying to get you to explain how your derivation will be different if λ were non-local hidden variables? It appears your answer is that it won't be different.
Yes, it won't be different. Indeed, if you asked me to characterize what λ is, in non-mathematical terms, I'd just admit openly that it's a "not-necessarily-local hidden variable". (Of course, the terminology "hidden variable" isn't ideal, since that connotes something specifically *supplementary* to the ordinary QM wf, which needn't at all be the case. Maybe "not-necessarily-local outcome-influencing variable".)
Experimenters calculate their correlations using ONLY particles actually measured. Aren't you therefore assuming that for a given particle pair, a particluar value of λ is in play?
Yes, each pair should have some particular λ.
Such that in a given run of the experiment, you could in principle think of making a list of all of the actually measured values of λ and their relative frequencies (if you knew them), to obtain a distribution of ρ(λ) that is applicable to the calculated correlation for the given run of the experiment? The actually measured distribution of λ for all 4 terms of the LHS must be identical according to your proof.
Yes, I think that's right. Of course, you can't/don't actually measure the values of λ. But apparently you meant this as a hypothetical, as in "if you could somehow magically measure them, then you could write down what the value was for each particle pair and look later at their statistical distributions in the different runs".
However as you say that the λs are hidden and the experimenters know nothing about it, you must therefore be making an additional assumption that the distributions are the same for all 4 terms calculated from 4 runs of the experiment
Yes, I've admitted this openly. We stress it in the article! Yes, yes yes. We *assume* that the distributions are the same for all 4 runs, i.e., for all 4 possible values of the setting parameters. That is, we assume that the distribution of λs is independent of the settings. We call this the "no conspiracy" assumption. Yes, this assumption is needed to derive the inequality. Yes, yes, yes.
or you could be assuming that all 4 measured distributions are identical to the the distribution of λ leaving the source?
I don't understand that. There is no consideration of the λs changing in time. If they change in time (between when they leave the source and "later" when they "do their thing", influence the outcomes somehow) then we need only ever talk about the "later" values and their distribution).
Clearly you can not make such assumptions without justification and the justification can not simply be some vague impricise statement about scientific inquiry.
Not everything can be deduced mathematically. If you find the assumption unreasonable, that's cool. Just say you accept the mathematical proof, but find the "no conspiracies" assumption unreasonable. Don't keep saying there's an "error" in the proof!
You can understand the list by saying the first row corresponds to A(a,λ1) = +1, A(b,λ1) = -1, A(a',λ1) = -1 and A(c, λ1) = +1
Sorry, I don't understand it. We are here deliberately trying to avoid the assumption that λ plus the local setting *determine* the outcome. That is, we are here deliberately trying to allow that there is some "residual indeterminism" at the measurement event. So I don't know where you got these functions A.
Note that the above is just another way of describing your factorization which you did within the proof. I'm just doing it this way because it makes it easier to see your error.
The factorization here is in terms of the E's. The idea is that λ and the local setting should determine the probabilities for the possible outcomes, hence the expected value; but they need not uniquely determine the outcome; we don't assume determinism.
Therefore you can not conclude reasonably that violation of an inequality means non-locality unless you have also ruled out the possibility that the terms from the experiment are not compatible with the mathematical requirements for deriving the inequality.
I don't know how to say it any more plainly. Yes, the conclusion of nonlocality only follows if you make the "no conspiracies" assumption.
The terms must not be assumed to be independent.
Just out of curiosity, would you say the same thing in the coin flip / drug trial analogy I described before? That is, does it violate your sense of scientific propriety to "just assume, without proof" that the coin flip outcomes are uncorrelated with the precise health status of the patients?
I take it you assume measuring a billion times does something special to the result? You said earler that the experimenters do not know anything about the nature or number of distinct λ values. So what makes you think "a billion" is enough? Let us then assume that there were 2 billion distinct values of λ. Will you still think a billion was enough?
I agree that, in principle, it might not be. But we know -- from experience/experiment -- that the statistics *converge* as you do more and more trials. That is, it takes a certain number of trials to get some accuracy, but then as you keep going things "settle in" to some values and don't change as you do more and more trials. Thus, the question of how many trials is enough is an empirical one: do enough trials such that doing more doesn't change the answer. Any experimentalist will tell you that in the case at hand the actual experiments already involve way more than enough trials.
Of course, a certain kind of mathematical rationalist will remain unsatisfied by this: "can you *prove* that things won't suddenly start changing if I take just one more billion data points?" No, I can't prove it. But you run the risk here of committing to a level of skepticism that would have you rejecting every single empirical scientific claim ever made. And that, in my book, cannot be rational.