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https://www.researchgate.net/publicatio ... tanglement
http://physicsessays.org/browse-journal ... cally.html

This is by a guy called Dean L. Mamas (Greek ancestors; he's from Clearwater, Florida). What do people think?

The journal "Physics Essays" is a bit of a rip-off. The paper is two pages and you can buy it from the publisher for 25 dollar. But you can also find it on the author's ResearchGate pages.

In the one page article on http://www.researchgate.net/publication ... tanglement there is no derivation of any correlation from any local hidden variable model; in particular, the important piece of getting discrete results from continuous variables is not discussed. Instead, the author's belief is simply asserted.

gill1109 wrote:https://www.researchgate.net/publication/353523376_Bell_tests_explained_classically_without_quantum_entanglement
http://physicsessays.org/browse-journal ... cally.html

This is by a guy called Dean L. Mamas (Greek ancestors; he's from Clearwater, Florida). What do people think?

The journal "Physics Essays" is a bit of a rip-off. The paper is two pages and you can buy it from the publisher for 25 dollar. But you can also find it on the author's ResearchGate pages.

Fascinating! Take notice that Physics Essays is listed in "Emerging Sources Citation Index (ESCI)"
But I think I have an even more incredible refutation that appears in a AIP Conference Proceedings! check out this one:
https://doi.org/10.1063/1.4773147
this explanation is unbeatable.

Mikko wrote:In the one page article on http://www.researchgate.net/publication ... tanglement there is no derivation of any correlation from any local hidden variable model; in particular, the important piece of getting discrete results from continuous variables is not discussed. Instead, the author's belief is simply asserted.

Exactly. He gives two very brief intuitive arguments why one might expect a cosine curve. In fact, one of them follows from consideration of light as waves. But he proposes no mechanism which could lead to the probabilities in the discrete experiment. He refers to an earlier short paper of his own in which he says that entanglement does not exist. But if the singlet state does not exist, if only probability mixtures of product states exist, then there is also an easy local realistic model for the experiment, hence Bell's inequalities would hold.

I was writing something longer saying much the same as Mikko, but have edited that down in size. I was using the Rasch model as an analogy and no one wants to hear about the Rasch Model here.

Obviously the writer of the short paper has not applied either algebra or arithmetic to the issue.

Moving on to other papers: it seems odd to me that many people can play with algebraic formula very well (e.g. Esail, whose paper I like very much except for his insistence that the effect is local) but cannot or do not bother to follow up by using arithmetic to calculate simulated results. It seems that there may be a daunting step up in the calculations in going from pen, paper and calculator up to a computer program. Maybe that is daunting for some? IMO spreadsheets offer a less daunting intermediate step.

Anyway, reading the short paper reminded me that I had never played with the errors of measurement between exact and quantised measurements. We know Alice and Bob use +/- 1 measurements but in a simulation be can find the exact projections which are not quantised. Although the exact measurements are unreal in this physics context,using exact projections does seem to set a target correlation which agrees with the QM correlation. So I played on a spreadsheet today.

I generated 360 pairs of particles (evenly spaced around the compass) and calculated for a=0 degrees and b=45 degrees, in two dimensions, the pairs of measurements A and B and also the 'errors', that is 'exact minus quantised' measurements. Then took means, SDs and correlation of these 'errors'.

correlation = -0.206091534
means 3.08395E-18 and 1.0177E-17 (that is, both means are zero)
SDs 0.476227652 and 0.476227652
N = 360

Law of large numbers (and 360 is not that large, but the thetas are not random) means the the sums of the A values are very similar to what would have occurred with exact projections.
The two SDs are very similar and I feel that someone could maybe calculate these theoretically. These SDs will always be non-zero.
The correlation between errors is non-zero and will not reduce to zero as N increases and that is one reason that the law of large numbers will never take the quantised correlation (0.5) up to the exact correlation (0.707) between A and B.

I plotted some scatter diagrams which seem very peculiar with a number of discontinuities but I think they are OK. The scatter diagram for the two errors show that the correlation of -0.2 is very dubious as the scatter is nowhere near linear. In fact, the scatter is quite like a hyperbolic curve in four segments. I cannot show it here as they are not yet on the web and have no URL.

I have the scatterplots available now, though poor quality images.




The top plot has particle hidden variable angles going from 1 to 360 degrees along the horizontal axis.
The vertical axis shows the difference (or 'error') between the exact projection onto Alice's vector angle a , where a is zero degrees. The discontinuities arise when the exact projections are near zero and change sign as the particle angle increases. Eg from +0.1 to -0.1. But the quantised projection flips from +1 to -1 or vice versa causing a discontinuity on the graph as the errror flips from +1 to -1.

The middle plot is for Bob where angle b for Bob is 45 degrees. So the plot is similar to the Alice plot but moved 45 degrees to the right.

The bottom plot shows the scatter of Alice's error (vertical axis) against Bob's error (horizontal axis). A product moment correlation of -0.2 doesn't do it justice. The correlation IMO is locally for a smooth, though segmented, line/curve but globally the segments are unusual :)

You wrote “ it seems odd to me that many people can play with algebraic formula very well (e.g. Esail, whose paper I like very much except for his insistence that the effect is local) but cannot or do not bother to follow up by using arithmetic to calculate simulated results. It seems that there may be a daunting step up in the calculations in going from pen, paper and calculator up to a computer program. Maybe that is daunting for some? IMO spreadsheets offer a less daunting intermediate step”.

I agree. School kids learn Excel. Most people never learn programming. But an Excel spreadsheet is a Turing machine! https://www.techrepublic.com/article/mi ... -language/

We just have to wait for a couple of human generations to move on.

It will be useful if simple scripting programs can supply data to a spreadsheet, let the spreadsheet do its stuff, and then get data back. Then we can do experiments with the spreadsheet models.

Well, it is probably not what you mean by simple scripted programs but I use Visual Basic within the Excel package. I take data from the spreadsheets, do calculations in VB, then return the results to the spreadsheet. However I usually play with the calculations first in the spreadsheet before moving to VB for the program design. And mostly I only use the VB when dealing with thousands/millions of data points. So I have increasingly cut out the VB stage, which I find pain in the neck in comparison to the spreadsheet. Using systematic distributions of angles also gives maybe surprisingly good results with small numbers of data points compared to completely random angles.

I started learning Fortran66 in the late 1960s/ early 1970s. There were no spreadsheets then. I used Fortran in my work and some programs ran annually for a couple of decades and were distributed to dozens of committees. So that was efficient use of computer programs. None of the programs I have written for Bell are continually used in such a way, so it makes sense to use a spreadsheet with small numbers of data points, if possible, for one-off trials. Later I learned Lotus123 which soon gave way to the use of Excel.

Justo wrote:But I think I have an even more incredible refutation that appears in a AIP Conference Proceedings! check out this one:
https://doi.org/10.1063/1.4773147
this explanation is unbeatable.

I couldnt acces that specific pdf, but on his 2014 arvix it seems he contradicts himself when saying the terms of the inequality dont have to be equal or inequal at the same time, and then 2 sentences later he says the terms have to be equal and inequal at the same time.

Dirkman wrote:

Justo wrote:But I think I have an even more incredible refutation that appears in a AIP Conference Proceedings! check out this one:
https://doi.org/10.1063/1.4773147
this explanation is unbeatable.

I couldnt acces that specific pdf, but on his 2014 arvix it seems he contradicts himself when saying the terms of the inequality dont have to be equal or inequal at the same time, and then 2 sentences later he says the terms have to be equal and inequal at the same time.

I could not find the arxiv article. But in the AIP Conference Proceedings paper he presents two derivations of Bell inequality incorrectness. One says the following: According to Bell, the results are +1 and -1, however, according to logical rules the results must be 1 and 0. Then he presents his counterexample by listing four measurements that give <AB>=0 according to Bell. Next he lists four results that give 1 according to the rules of logic. The conclusion is that if Bell is correct we must have 1=0, contradiction! It is good that he at least finds that 1=0 is an arithmetic contradiction.

Barukcic writes a lot of strange things which tells me that he does not know what he is talking about. Look at his formulas (3) and (4). He says that Bell defines an expectation value as a summation of values times probabilities of those values. The sum of the probabilities of possible values of the hidden variable is equal to 1. This is the definition of the theoretical expectation value of a function of a discrete random variable. E(f(X)) = sum_x f(x) P(X = x). Then Barukcic says that when you compute the expectation for real data, all P(X = x) = 1. I'm not surprised that if you know so little maths, that you can quickly derive that 0 = 1.

Barukcic is a dentist from former Yugoslavia who has written an interesting book on causality in which he completely redefines all of mathematics and statistics. I've met him once or twice in Vaxjo. He is a fascinating character, great fun to talk to. I'm not saying that it's impossible for a dentist to rewrite the foundations of modern science. It's great. I am saying that I find his work full of self-contradictions. It is very, very idiosyncratic, so hard to read. It made no sense to me, at all.