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JesseM
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But then you use that to come to the absurd conclusion that in order to compare with empirical data, we need to make some assumptions about the distribution of values of λ on our three runs. We don't--Bell was writing for an audience of physicists, who would understand that whenever you talk about an "expectation value", the basic definition is always just a sum over each possible measurement result times the probability of that result, so to compare with empirical measurements you just take the average result on all your trials, nothing more. Bell obviously did not mean for his integrals to be the definitions of E(a,b) and E(b,c) and E(a,c), implying that you can only compare them with empirical data if you have actually confirmed that [tex]\rho(\lambda)[/tex] was the same for each run--rather he was making an argument that the "expectation values" as conventionally understood would also be equal to those integrals.billschnieder said:First of all, I said the equation is Bell's definition of HIS expectation values for the situation he is working with.
You understand that the "true probabilities" represent the frequencies of different outcomes in the limit as the number of trials goes to infinity, and not the actual frequencies in our finite series of trials? So for example, if one run with settings (a,b) included three trials where λ took the value λ3, while another run with settings (b,c) included no trials where it took the value λ3, this wouldn't imply that ρ(λi) differed in the integrals for E(a,b) and E(b,c)? Because your comment at the end of post #1224 suggests you you are still confusing the issue of what it means for the "true probabilities" ρ(λi) to differ depending on the detector settings and what it means for the actual frequencies of different values of λi to differ on runs with different detector settings:billschnieder said:Secondly, nobody said anything about the probabilities in the equation not being true probabilities, so you are complaining about an inexistent issue.
So, kinda seems like this is not actually a dead issue. You may have noticed I discussed exactly this distinction between the "true probability distribution" ρ(λi) differing from one run to another and the actual frequencies of different λi's differing from one run to another at the very start of post #1214, but since you didn't respond I don't know if you even read that or what you thought of the distinction I was making there.billschnieder said:That is why I cautioned you earlier not to prematurely blurb your claim that conspiracy must be involved for ρ(λi) to be different. Now we get an admission, however reluctantly that it is possible for ρ(λi) to be different without conspiracy. You see, the less you talk (write), the less you will have to recant later as I'm sure you are realizing.JesseM said:Even if the data was drawn from triples, and the probability of different trials didn't depend on the detector settings on each run, there's no guarantee you'd be able to exactly resort the data in the manner of my example in post #1215, where we were able to resort the data so that every row (consisting of three pairs from three runs) had the same value of a,b,c throughout
billschnieder said:Thirdly, you object to my statement but go on to say the exact same thing. This is what I said after the equation:
You really think that this is the "exact same thing" as what I was saying? Here your "practical" average requires us to know which value of λ occurred on each trial, and what the probability of each value was! Of course this is nothing like what I mean when I talk about comparing the theoretical expectation value to actual experimental data. Again, a definition of the expectation value involving "true probabilities" would be:Theoretically the above makes sense, where you measure each A(a,.), B(b,.) pair exactly once for a specific λ, and simply multiply with the probability of realizing that specific λ and then add up subsequent ones to get your expectation value E(a,b). But practically, you could obtain the same E(a,b) by calculating a simple average over a representative set of outcomes in which the frequency of realization of a specific λ, is equivalent to it's probability. ie
For example, if we had only 3 possible λ's (λ1, λ2, λ3) with probabilities (0.3, 0.5, 0.2) respectively. The expectation value will be
E(a,b) = 0.3*A(a,λ1)*B(b,λ1) + 0.5*A(a,λ2)*B(b,λ2) + 0.2*A(a,λ3)*B(b,λ3)
E(a,b) = (+1*+1)*P(detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*P(detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*P(detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*P(detector with setting a gets result -1, detector with setting b gets result -1)
So if you want to compare with empirical data on a run where the detector settings were a and b, it'd just be:
(+1*+1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result -1)
...which is equivalent to just computing the product of the two measurements on each trial, and adding them all together and dividing by the number of trials to get the empirical average for the product of the two measurements on all trials in the run.
You quote my simple equation for E(a,b) above and say:
Which mine is--I'm multiplying each possible result by the probability of that result, for example the result (+1*-1) is multiplied by P(detector with setting a gets result +1, detector with setting b gets result -1)It clearly shows that you do not understand probability or statistics. Clearly the definition of expectation value is based on probability weighted sum,
Of course. In the limit as the number of trials goes to infinity, we would expect this:billschnieder said:and law of large numbers is used as an approximation, that is why it says in the last sentence above that the expectation values is "almost surely the limit of the sample mean as the sample size grows to infinity"
(+1*+1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result -1)
to approach this:
E(a,b) = (+1*+1)*P(detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*P(detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*P(detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*P(detector with setting a gets result -1, detector with setting b gets result -1)
...where all the probabilities in the second expression represent the "true probabilities", i.e. the fraction of trials with that outcome in the limit as the number of trials goes to infinity!
So, it's not clear why you think the wikipedia definition of expectation value is somehow different from mine, or that I "do not understand probability or statistics". Perhaps you misunderstood something about my definition.
No, all expectation values are just defines as a sum over all possible results times the probability of each possible result. And in this experiment the value of λ is not a "result", the "result" on each trial is just +1 or -1.billschnieder said:You are trying to restrict the definition by suggesting that expection value is defined ONLY over the possible paired outcomes (++, --, +-, -+) and not possible λ's, but that is naive, and short-sighted but also ridiculous as we will see shortly.
No, ρ(λ) is a probability measure over values of λ, and it happens to be true (according to Bell's physical assumptions) that the value of λ along with the detector angles completely determines the results on each trial. But you can also define a probability measure on the results themselves, that would just be a measure that assigns probabilities between 0 and 1 to each of the four possible results:billschnieder said:Now let us go back to the first sentence of the wikipedia definition above and notice the last two words "probability measure". In case you do not know what that means, a probability meaure is simply any real valued function which assigns 1 to the entire probablity space and maps events into the range from 0 to 1. An expectation value can be defined over any such probabiliy measure, not just the one you pick and choose for argumentation purposes. In Bell's equation (2),
[tex] \int d\lambda \rho (\lambda ) = 1 [/tex]
Therefore ρ(λ) is a probability measure over the paired products A(a,λ)A(b,λ)
1. (detector with setting a gets result +1, detector with setting b gets result +1)
2. (detector with setting a gets result +1, detector with setting b gets result -1)
3. (detector with setting a gets result -1, detector with setting b gets result +1
4. (detector with setting a gets result -1, detector with setting b gets result -1)
With the sum of the four probabilities equalling one. That's exactly the sort of probability measure I was assuming when I wrote down my equation:
E(a,b) = (+1*+1)*P(detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*P(detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*P(detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*P(detector with setting a gets result -1, detector with setting b gets result -1)
And when trying to compare an equation involving expectation values to actual empirical results, every physicist would understand that you don't need to even consider the question of what values λ may have taken on your experimental runs, instead you'd just compute something like this:
(+1*+1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result +1) + (+1*-1)*(fraction of trials where detector with setting a gets result +1, detector with setting b gets result -1) + (-1*+1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result +1) + (-1*-1)*(fraction of trials where detector with setting a gets result -1, detector with setting b gets result -1)
...which, by the law of large numbers, is terrifically unlikely to differ significantly from the "true" expectation value if you have done a large number of trials. If you think a physicists comparing experimental data to Bell's inequality would actually have to draw any conclusions about the values of λ on the experimental trials, I guarantee you that your understanding is totally idiosyncratic and contrary to the understanding of all mainstream physicists who talk about testing Bell's inequality empirically.
billshand Bell's equation (2) IS defining an expectation value for paired products irrespective of any physical assumptions. There is no escape for you here.[/QUOTE said:If equation (2) was supposed to be the definition of the expectation value, rather than just an expression that he would expect the expectation value (under its 'normal' meaning, the one I've given above involving only actual measurable results and the probabilities of each result) to be equal to, then why do you think he would need to make physical arguments as to why equation (2) should be the correct form? Do you deny that he did make physical arguments for the form of equation (2), like in the first paper where he wrote:
Do you disagree that here the first paragraph is providing physical justification for why A is a function only of a and λ but not b, and why B is a function of b and λ but not a, along with a justification for why we should believe the result A can be completely determined by a and the hidden parameters λ in the first place? Likewise, in the paper http://cdsweb.cern.ch/record/142461/files/198009299.pdfpapers , would you deny that this section from p. 16 of the pdf (p. 15 of the paper) is trying to provide physical justification for why the same function ρ(λ) appears in different integrals for different expectation values like E(a,b) and E(b,c)?Now we make the hypothesis, and it seems one at least worth considering, that if the two measurements are made at places remote from one another the orientation of one magnet does not influence the result obtained with the other. Since we can predict in advance the result of measuring any chosen component of [tex]\sigma_2[/tex], by previously measuring the same component of [tex]\sigma_1[/tex], it follows that the result of an such measurement must actually be predetermined. Since the initial quantum mechanical wave function does not determine the result of an individual measurement, this predetermination implies the possibility of a more complete specification of the state.
Let this more complete specification be effected by means of parameters λ ... the result A of measuring [tex]\sigma_1 \cdot a[/tex] is then determined by a and λ, and the result B of measuring [tex]\sigma_2 \cdot b[/tex] in the same instance is determined by b and λ
If you don't disagree that these sections are attempts to provide physical justification for the form of the integrals he writes, why do you think he would feel the need to provide physical justification if he didn't have some independent meaning of "expectation values" in mind, like the meaning I talked about above involving just the different results and the probabilities of each one?Secondly, it may be that it is not permissible to regard the experimental settings a and b in the analyzers as independent variables, as we did. We supposed them in particular to be independent of the supplementary variable λ, in that a and b could be changed without changing the probability distribution ρ(λ). Now even if we have arranged that a and b are generated by apparently random radioactive devices, housed in separate boxes and thickly shielded, or by Swiss national lottery machines, or by elaborate computer programmes, or by apparently free willed experimental physicists, or by some combination of all of these, we cannot be sure that a and b are not significantly influenced by the same factors λ that influence A and B. But this way of arranging quantum mechanical correlations would be even more mind boggling than one in which causal chains go faster than light. Apparently separate parts of the world would be deeply and conspiratorially entangled, and our apparent free will would be entangled with them.
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