Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Breaking Bell's Inequality with Monte Carlo Simulations in Python

bytepawn.com

Post reply on HN
Print view View original

21–30 of 64 posts

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#21

Post by n4r9 »

0cf8612b2e1e wrote: post #20
eigenket wrote: post #11

Earlier quoted context omitted.

You know something has gone horrifically badly when a paper begins with > This reply paper should be read as a continuation of my previous reply paper [1], which is a reply published in this journal to a previous critique of one of my papers We're way too deep in replies now, and anyone who values their time should get out now.

On the other hand, academics slap fights are magnificently petty to behold. In any dispute the intensity of feeling is inversely proportional to the value of the issues at stake. That is why academic politics are so bitter.

The conclusion reads like someone who can't admit they're wrong on Reddit:

> The common defect in the critiques [2], [6], and [14] is that, instead of engaging with the original quaternionic 3-sphere model presented in my papers [1], [7]– [11] using Geometric Algebra, they insist on criticizing entirely unrelated flat space models based on matrices and vector “algebra.” This logical fallacy by itself renders the critiques invalid. Nevertheless, in this paper I have addressed every claim made in the critique [6] and the critiques it relies on, and demonstrated, point by point, that none of the claims made in the critiques are correct. I have demonstrated that the claims made in the critique [6] are neither proven nor justified. In particular, I have demonstrated that, contrary to its claims, critique [6] has not found any mistakes in my paper [7], or in my other related papers, either in the analytical model for the singlet correlations or in its event-by-event numerical simulations. Moreover, I have brought out a large number of mistakes and incorrect statements from the critique [6] and the critiques it relies on. Some of these mistakes are surprisingly elementary.

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#22

Post by n4r9 »

jahnu wrote: post #13
n4r9 wrote: post #7

Earlier quoted context omitted.

It requires a chunk of linear algebra to understand, but the Wikipedia page has a slightly more detailed explanation: https://en.wikipedia.org/wiki/Bell%27s_theorem#Theorem It's related to the fact that the expected value of A_1 tensor B_1 is negative 1/sqrt(2), whilst the expected value of all other tensor products are positive 1/sqrt(2).

The explanation and table in the Simple English page for this helped me grasp it better. (Although the diagram using green dots only confuses :) ) Greene's book is a fantastic read too! https://simple.wikipedia.org/wiki/Bell%27s_theorem

This looks like some kind of variant of Bell's Theorem. I've not seen it before, but it reminds me of the GHZ inequality [0]

[[EDIT - actually I take that back. The GHZ inequality refers to three systems whereas your link refers to three measurement choices]].

I don't think your link gives a derivation of the quantum correlations beyond "Quantum physics says that half the time they should get a match".

[0] https://en.wikipedia.org/wiki/Bell%27s_theorem#GHZ%E2%80%93M...

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#23

Post by Maro »

danwills wrote: post #5

"a talented college physics student can do it" I'm afraid I don't qualify for being able to do that, but I feel like I'm tantalizingly close to understanding this overall - but I'm finding it hard to understand why the lower-right "TT" quadrant is transposed in the S=2.828 example (the red box in the diagram). Maybe it's obvious if one understands it better?

Hi, I'm the guy who wrote the article.

In the article, I first show how to "break" the Bell inequality without making a reference to any complicated math or Physics, this is the section "Breaking the Bell inequality with non-local information", which uses the dice roll example. This is on purpose, for pedagogical reasons, and this is why the Python approach imo is so useful to demonstrate this whole thing: the key idea is, to break the inequality, you need to "peek" at the other side.

Then, the next mental step is simply the statement that, in "real life", you can prepare a composite system (eg. 2 photons modeled as 2 qubits) that you can seperate (modeled as the split() function in Python), you can send the 2 parts to two different observers, they use a certain measurement setup, and the whole game is played, statistic computed, etc. and then you get this value 2.82 (which breaks the Bell inequality)! So somehow, the 2 qubits are doing that we can only model [in Python] as peeking!

The actual derivation of how to get that 2.82 is, in some sense, almost like a a detail. I think with this approach, even a non-physicist can understand what this whole argument is (=Bell's genius).

"a talented college physics student can do it" - I'm a Physicist, but I'm not working as a Physicist, and I was able to derive all the numbers in that table by hand with pen & paper directly. I figured if I can do it 15 years out of school, so can a talented college physics student!

The next article will be that derivation [of the raw probabilities], I just need to transcribe it from my notebook to Latex and clean it up. If you want to see the original notes:

https://photos.app.goo.gl/sqxLnEhyeZTDD7oA6

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#24

Post by eigenket »

GistNoesis wrote: post #19
eigenket wrote: post #16

Earlier quoted context omitted.

> Hint : Listing the assumptions doesn't work Why not? I could see that it might not if you are not clear about your assumptions

It's circular reasoning, hidden in the definition of your assumptions. By defining not clearly what a measurement is and observations are. You must let the cat step out of the box your definitions put you in. You have infinite freedom in your choices of definitions, listing assumptions is creating a false dichotomy. Especially when doing so conclude to exclude the most probable assumption : Locality. Preserve localit…

Will you grant me that it is at least possible to derive Bell's inequality by listing out a complete set of assumptions (including assumptions that define what a measurement is and what observations are)?

Of course you personally may disagree with some of these axioms (indeed, if you take Bell's theorem seriously you must), but certainly it is possible to list them, and thereby derive Bell's inequality?

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#25

Post by wallfacer120 »

GistNoesis wrote: post #19
eigenket wrote: post #16

Earlier quoted context omitted.

> Hint : Listing the assumptions doesn't work Why not? I could see that it might not if you are not clear about your assumptions

It's circular reasoning, hidden in the definition of your assumptions. By defining not clearly what a measurement is and observations are. You must let the cat step out of the box your definitions put you in. You have infinite freedom in your choices of definitions, listing assumptions is creating a false dichotomy. Especially when doing so conclude to exclude the most probable assumption : Locality. Preserve localit…

[dead]

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#26

Post by meroes »

eigenket wrote: post #12
GistNoesis wrote: post #9

The Bell's Inequalities are a test for the capacity for inductive reasoning of the pupil. If the pupil succeed he is not to be admitted to join the ranks of quantum physicist. You usually show a pupil the problem with classical probabilities, and show that you can't violate Bell's Inequalities, then you show that Quantum Mechanics managed to replicated the observed probabilities using a non-local way, and therefore y…

> You usually show a pupil the problem with classical probabilities, and show that you can't violate Bell's Inequalities, then you show that Quantum Mechanics managed to replicated the observed probabilities using a non-local way, and therefore you conclude that the world is non-local. If you do this you're doing a bad job at being a teacher. The way the argument should go is you start with a list of assumptions (of…

MWI is not local according to all the big names I read; Lev Vaidman, Tim Maudlin, and Im pretty sure David Wallace too.

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#27

Post by wallfacer120 »

GistNoesis wrote: post #9

The Bell's Inequalities are a test for the capacity for inductive reasoning of the pupil. If the pupil succeed he is not to be admitted to join the ranks of quantum physicist. You usually show a pupil the problem with classical probabilities, and show that you can't violate Bell's Inequalities, then you show that Quantum Mechanics managed to replicated the observed probabilities using a non-local way, and therefore y…

[dead]

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#28

Post by GistNoesis »

eigenket wrote: post #24
GistNoesis wrote: post #19

Earlier quoted context omitted.

It's circular reasoning, hidden in the definition of your assumptions. By defining not clearly what a measurement is and observations are. You must let the cat step out of the box your definitions put you in. You have infinite freedom in your choices of definitions, listing assumptions is creating a false dichotomy. Especially when doing so conclude to exclude the most probable assumption : Locality. Preserve localit…

Will you grant me that it is at least possible to derive Bell's inequality by listing out a complete set of assumptions (including assumptions that define what a measurement is and what observations are)? Of course you personally may disagree with some of these axioms (indeed, if you take Bell's theorem seriously you must), but certainly it is possible to list them, and thereby derive Bell's inequality?

Bell's theorem is a theorem. If hypothesis applies conclusion must follow. That's math. Everything is fine with it (They are a reformulation of "Bonferroni inequalities" or "Boole's_inequality" by the way).

You've got to reframe the problem so that Bell's theorem doesn't apply. When you build your theory, if you manage to define what a measurement is, so that you don't satisfy the hypothesis of the Bell's theorem, you get to avoid having to have its conclusions.

One of Bell's theorem implied hypothesis is that measurements/observations are probabilities, so by defining measurement instead as a conditional probability, you get to avoid being subjected to Bell's inequalities.

It's inductive reasoning, you don't get truth you only get self consistency, and a model that looks much nicer than QM.

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#29

Post by eigenket »

meroes wrote: post #26
eigenket wrote: post #12

Earlier quoted context omitted.

> You usually show a pupil the problem with classical probabilities, and show that you can't violate Bell's Inequalities, then you show that Quantum Mechanics managed to replicated the observed probabilities using a non-local way, and therefore you conclude that the world is non-local. If you do this you're doing a bad job at being a teacher. The way the argument should go is you start with a list of assumptions (of…

MWI is not local according to all the big names I read; Lev Vaidman, Tim Maudlin, and Im pretty sure David Wallace too.

You can probably define locality in a way that MWI is nonlocal, but you can also definitely define it in a way such that MWI is local.

For me the most important thing about nonlocality is the lack of any "action at a distance", MWI satisfies this, but if you make more stringent demands it might not satisfy those.

Re: Breaking Bell's Inequality with Monte Carlo Simulations in Python

#30

Post by eigenket »

GistNoesis wrote: post #28
eigenket wrote: post #24

Earlier quoted context omitted.

Will you grant me that it is at least possible to derive Bell's inequality by listing out a complete set of assumptions (including assumptions that define what a measurement is and what observations are)? Of course you personally may disagree with some of these axioms (indeed, if you take Bell's theorem seriously you must), but certainly it is possible to list them, and thereby derive Bell's inequality?

Bell's theorem is a theorem. If hypothesis applies conclusion must follow. That's math. Everything is fine with it (They are a reformulation of "Bonferroni inequalities" or "Boole's_inequality" by the way). You've got to reframe the problem so that Bell's theorem doesn't apply. When you build your theory, if you manage to define what a measurement is, so that you don't satisfy the hypothesis of the Bell's theorem, yo…

> You've got to reframe the problem so that Bell's theorem doesn't apply. When you build your theory, if you manage to define what a measurement is, so that you don't satisfy the hypothesis of the Bell's theorem, you get to avoid having to have its conclusions.

This (in my opinion) a bad way of explaining how the standard reasoning goes. We start with a list of assumptions, we prove this inequality which it turns out is not satisfied, we reject (at least) one of our assumptions. These is no crackpottery here, this is the norm.

> by defining measurement instead as a conditional probability

This sounds like it probably doesn't get you anywhere, but I'll bite - what are we conditioning on? In the standard formulation of Bell's theorem they are conditional on the "hidden variable" we are assuming exists, as well as any relevant measurement settings but it sounds like you're imagining something wilder than that.

Post reply on HN