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minkwe wrote:

Justo wrote:There are 16 different values of hidden variables , the numbers are the indices numbering them.

Hidden variables are not measured, let alone numbered in experimental data. You are assuming the availability of information that is not available in experiments.

minkwe wrote:

Justo wrote:What I have shown is that "each correlation function pertains to a different set of particle pairs." therefore they are weakly objective, and yes, of course, you can arrange them in a single 4xN (N=16) spreadsheet. The essential point is the four columns pertain to four different series of actual experiments.

You have not. You claim to but then you make an implicit assumption that the weakly objective case is the same as the strongly objective case (eq 24), and then proceed with the strongly objective case.

Justo wrote:You keep saying that but you just cannot say where, in what step, my reasoning fails or is wrong

I've mentioned several times and referenced the transition from equation (23) to (24). How can you claim that I have not shown where? You may disagree with me but to suggest that I haven't explicitly said where and how is just wrong.

minkwe wrote:Conceptually, your equation (23) is equivalent to 4 independent 2xN spreadsheets of outcomes. Your equation (24) is equivalent to a single 4xN spreadsheet of outcomes. And your equation (29) is equivalent to a single row from the single 4xN spreadsheet in equation (24). You can't derive the inequality without putting those numbers into a single 4xN spreadsheet as you did in equation (24). In fact, a spreadsheet that is not a 4xN spreadsheet can't be expected to obey the inequality. When you obtain experimental data you can't just compare it with the inequality without first converting the data to a 4xN spreadsheet. If this was not a necessary step, you would not have needed to do it before deriving the inequality.

Justo wrote:Yes, of course, that is what the derivation is all about. To prove that (23) is equivalent to 4 independent 2xN spreadsheets that reduce to one 4xN spreadsheet with actual data, i.e., "weakly objective".

So let me ask you a simple question. If I take 4 2xN spreadsheets from a weakly objective experiment, will you expect it to obey the inequality you derive without first being converted into a single 4xN spreadsheet? This is the key question.

Code: Select all

A1 [ 1  1  1 -1 -1 -1 -1 -1 -1  1]
B1 [-1  1  1 -1 -1  1 -1 -1 -1  1]

A2 [-1  1 -1 -1 -1  1 -1  1  1 -1]
B2 [ 1 -1  1  1 -1 -1  1 -1 -1 -1]

A3 [-1 -1  1  1  1 -1  1 -1 -1 -1]
B3 [-1 -1  1  1  1  1 -1 -1 -1 -1]

A4 [ 1 -1 -1 -1 -1  1 -1  1 -1  1]
B4 [-1 -1 -1 -1 -1  1  1  1 -1  1]

S = 2.4

minkwe wrote:

Code: Select all

A1 [ 1  1  1 -1 -1 -1 -1 -1 -1  1]
B1 [-1  1  1 -1 -1  1 -1 -1 -1  1]

A2 [-1  1 -1 -1 -1  1 -1  1  1 -1]
B2 [ 1 -1  1  1 -1 -1  1 -1 -1 -1]

A3 [-1 -1  1  1  1 -1  1 -1 -1 -1]
B3 [-1 -1  1  1  1  1 -1 -1 -1 -1]

A4 [ 1 -1 -1 -1 -1  1 -1  1 -1  1]
B4 [-1 -1 -1 -1 -1  1  1  1 -1  1]

S = 2.4

minkwe wrote:

Code: Select all

A1 [ 1  1  1 -1 -1 -1 -1 -1 -1  1]
B1 [-1  1  1 -1 -1  1 -1 -1 -1  1]

A2 [-1  1 -1 -1 -1  1 -1  1  1 -1]
B2 [ 1 -1  1  1 -1 -1  1 -1 -1 -1]

A3 [-1 -1  1  1  1 -1  1 -1 -1 -1]
B3 [-1 -1  1  1  1  1 -1 -1 -1 -1]

A4 [ 1 -1 -1 -1 -1  1 -1  1 -1  1]
B4 [-1 -1 -1 -1 -1  1  1  1 -1  1]

S = 2.4

gill1109 wrote:So with four sets of 10 observations each, you can violate the Bell inequality? You could violate Tsirelson’s inequality. You can even get S = 4. So what?

That is why we need a statistical independence assumption. You don’t understand probability theory, so you called it mumbo jumbo.

You don’t only need a probabilistic assumption, you also need error bars and p-values and all that. Or a prior distribution and Bayes theorem. As you like…

minkwe wrote:
This function has values but you can't derive Bell's inequality with this type of function precisely because the domain of the function which is the space of vector pairs excludes where .

Now if you take a product of two such functions
, The domain of the product is the space of vector triples which excludes the regions where

.

The first observation of the consequences of this is that any probability distribution on the domains of the individual functions won't apply to the products. I think this could be another way of stating what local has been saying about separated vs joint measurements.

Secondly, looking at your equation 29, each of the products will have a different domain and therefore the will only be a valid expression for the common part of the domains of those functions.

gill1109 wrote:PS to Michel: I think that "local" has been saying something else, I think he has been saying that entanglement will somehow break down when particles become more and more separated.

local wrote:

gill1109 wrote:PS to Michel: I think that "local" has been saying something else, I think he has been saying that entanglement will somehow break down when particles become more and more separated.

Shameless liar Gill is lying again. I have explicitly rejected this misrepresentation at least 3 or 4 times but this loser continues to misrepresent my thinking. Get it through your stupid narc head, Gill, I do not appeal to decoherence as the particles separate. Stop misrepresenting me.

One cannot sample a joint distribution with separated (marginal) measurements. That has nothing to do with decoherence. I'm happy that minkwe too acknowledges this simple reality. Gill cannot acknowledge this reality because it is devastating to his mysterian thesis. So instead he is forced to dissemble and misrepresent. Disgusting!

gill1109 wrote:"local", I said that I didn't know what you meant. I guessed and I guessed wrong.

local wrote:

gill1109 wrote:"local", I said that I didn't know what you meant. I guessed and I guessed wrong.

You are a shameless liar. I have told you several times right here on this forum what I believe in this regard, but you continue to feign ignorance and misrepresent me. Now your childish taunts expose you further.