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Breaking Bell's Inequality with Monte Carlo Simulations in Python

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

#41
Hidden variable theory: https://en.wikipedia.org/wiki/Hidden-variable_theory

Bell test: https://en.wikipedia.org/wiki/Bell_test :

> To do away with this assumption it is necessary to detect a sufficiently large fraction of the photons. This is usually characterized in terms of the detection efficiency η [\eta], defined as the probability that a photodetector detects a photon that arrives at it. Anupam Garg and N. David Mermin showed that when using a maximally entangled state and the CHSH inequality an efficiency of η > 2*sqrt(2)/2~= 0.83 is required for a loophole-free violation.[51] Later Philippe H. Eberhard showed that when using a partially entangled state a loophole-free violation is possible for η>2/3~=0.67 which is the optimal bound for the CHSH inequality.[53] Other Bell inequalities allow for even lower bounds. For example, there exists a four-setting inequality which is violated for η>(sqrt(5)-1)/2~=0.62 [54]

CHSH inequality: https://en.wikipedia.org/wiki/CHSH_inequality

/sbin/chsh

Isn't it possible to measure the wake of a photon instead of measuring the photon itself; to measure the wake without affecting the boat that has already passed? And shouldn't a simple beam splitter be enough to demonstrate entanglement if there is an instrument with sufficient sensitivity to infer the phase of a passed photon?

This says that intensity is sufficient to read phase: https://news.ycombinator.com/item?id=40492160 :

> "Bridging coherence optics and classical mechanics: A generic light polarization-entanglement complementary relation" (2023) https://journals.aps.org/prresearch/abstract/10.1103/PhysRev... :

>> This means that hard-to-measure optical properties such as amplitudes, phases and correlations—perhaps even these of quantum wave systems—can be deduced from something a lot easier to measure: light intensity

And all it takes to win the game is to transmit classical bits with digital error correction using hidden variables?

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

#42

Earlier quoted context omitted.

> 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…

>what are we conditioning on? The local hidden state, but you don't get to set it from inside the universe when you do an experiment (this local hidden state is unobservable). From inside the universe based on this hidden state, everything behave classically, pseudo-randomly based on the local hidden state. But because you don't get to set the local hidden state during your experiment if you want to calculate the pro…

I commented awhile back on another thread that:

I think, ultimately, there are only 3 possible explanations for the paradoxes of the quantum world. 1) superdeterminism (everything including our choices in quantum experiments today were fully determined at the instant of the Big Bang), 2) something "outside" our observable reality acting as a global hidden variable (whether something like the bulk in brane cosmology or whatever is running the simulation in simulation theory) or 3) emergent spacetime (if space and time are emergent phenomena then locality and causation are not fundamental).

You seem to be suggesting something similar to option 2. Or am I misunderstanding?

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

#43

Earlier quoted context omitted.

>what are we conditioning on? The local hidden state, but you don't get to set it from inside the universe when you do an experiment (this local hidden state is unobservable). From inside the universe based on this hidden state, everything behave classically, pseudo-randomly based on the local hidden state. But because you don't get to set the local hidden state during your experiment if you want to calculate the pro…

I commented awhile back on another thread that: I think, ultimately, there are only 3 possible explanations for the paradoxes of the quantum world. 1) superdeterminism (everything including our choices in quantum experiments today were fully determined at the instant of the Big Bang), 2) something "outside" our observable reality acting as a global hidden variable (whether something like the bulk in brane cosmology o…

The solution I'm suggesting is that nature does it in the really boring way : classically. It's almost like option 2, but the state is local.

This state is local and "inside" our universe, but we can't observe it. (A good analog for thing that are unobservable from inside the universe are seed of a pseudo-random generator).

The beauty of it, is just realising that Nature's simulator can be purely local and yet not be subjected to Bell Inequalities, but still reproduce the spurious quantum correlations, if you calculate the probabilities.

Violating Bell Inequalities is totally normal when you construct your theory such that Bell Inequalities don't apply.

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

#44
post #31
post #6

This is closely related to my PhD. It was many years ago but if I remember rightly there is no need for the assumption of determinism - Bell Inequalities hold just as well for random local hidden variables. Simulating the correlations with computer programs is an interesting idea, partly because it challenges to those who still believe in a "local" reality to demonstrate Bell Inequality violations in distributed clas…

Hi, author of the article here. Regarding determinism, I think the reason the assertion is "no deterministic local hidden.." is that, you need to break both the deterministic and locality assumption. However there is a nuance, which is, do you need to break both properties to.. (a) break the Bell inequalities, or, to (b) reproduce quantum mechanics.. which is not exactly the same thing. For example, in my toy simulat…

A follow-up point: it sounds like you're also wondering whether it's possible to simulate quantum mechnics exactly with a deterministic non-local hidden variable model?

Arguably, this is exactly what the Bohmian "Pilot-wave" interpretation of quantum mechanics is - see e.g. https://plato.stanford.edu/entries/qm-bohm/

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

#45
> Victor can prepare a pair of quantum particles in a special state known as an entangled state. In this state, the outcomes of Alice's and Bob's measurements are not just random but are correlated in a way that defies any classical explanation based on local hidden variables.

What if there are no hidden properties per particle, but the combination of specific property values of particles allow for breaking Bell's Inequality?

I.e. what we call 'entanglement', it might not be 'action-at-a-distance', but the simple effect of the interaction of the properties of the two particles as they are generated.

For example, if we have two billiard balls, which are really close together, and we hit them with a third ball simultaneously, their spin will be correlated when we measure it for both balls (without taking into account other factors, i.e. friction, tilting of the table etc). Wouldn't that break Bell's inequality as well? the spins of the two balls will be correlated.

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

#46
post #45

> Victor can prepare a pair of quantum particles in a special state known as an entangled state. In this state, the outcomes of Alice's and Bob's measurements are not just random but are correlated in a way that defies any classical explanation based on local hidden variables. What if there are no hidden properties per particle, but the combination of specific property values of particles allow for breaking Bell's In…

"their spin will be correlated" - in this case the billiard's spin is a per-ball property that is set before they are sent to Alice and Bob, and happens to be correlated. You can simulate this in the Python code, but you will not be able to break the Bell inequality like that. This is similar to the dice example I give, where the objects sent to Alice and Bob are random from their perspective (since the dice roll happens with Victor), and correlated.

In general, classical correlation cannot break the Bell inequalities [assuming no peeking, ie. no action-at-a-distance in the measurement devices]. To be clear, I didn't prove this in the article, the approach the article takes is "here is some code, play around with it to get a feeling for why".

Hope this helps.

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

#47

Earlier quoted context omitted.

> 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…

>what are we conditioning on? The local hidden state, but you don't get to set it from inside the universe when you do an experiment (this local hidden state is unobservable). From inside the universe based on this hidden state, everything behave classically, pseudo-randomly based on the local hidden state. But because you don't get to set the local hidden state during your experiment if you want to calculate the pro…

I agree with the sibling comment by eigenket:

> Everything up to the [spoiler ahead] in this comment is (as far as I can tell) exactly how things work in standard formulations of Bell's inequality. There's nothing weird or crackpot there.

Moreover, to clarify, it's not necessary that the hidden variables can be measurable or that you can set them. So if a system like the one you described must follow the Bell's Inequality if all the other hypothesis are true.

I read the code and it looks like an accurate implementation of the model proposed in the paper.

From the paper you liked:

> However, the expectation values E(X1X2), displayed in (13) contain a factor 1/2, meaning that they do not violate CHSH inequality.

I agree with that part. The model should not violate the Bell's inequality or the equivalent version.

> The agreement with quantum predictions is obtained only after the “photon identification procedure”, which selects, from the raw data, final data samples.

The selection rule is the weird part. It's described in equations 7 and 8.

  x := sign(1 + cos[2(a − φ)] − 2 · r1)
where r1 is a uniform random value between 0 and 1.

a is the angle of the polarizer

φ is the secret variable that is the angle of the photon. (QM says that this type of entangled photons have no a secret angle, this model assumes that each photon has a hidden variable that is the secret value φ.)

So far so good, this calculation gives the expected result if you assume that φ is chosen from a uniform distribution between 0° and 360°.

  v := r2 |sin[2(a − φ)]|^d (Vmax − Vmin) − Vmax
  selected := (v ≤ V)
where r2 is a uniform random value between 0 and 1.

With the numbers in your program

  v := r2 |sin[2(a − φ)]|^2 (10 − 0) − 10
  selected := (v ≤ -9.99)
that is equivalent to

  selected := r2 |sin[2(a − φ)]|^2 ≤ -0.001
I've don't remember anything similar, and I can't imagine what it means experimentally.

Most of the times r2 is not tiny, so most of the times this means that the sine is tiny that means that the secret angle of the photon is almost aligned or almost orthogonal to the polarizer.

So this is a device that can measure the secret angle of the photon. This is not a real device, so it can't be proposed as an alternative explanation of the violation of the Bell's inequality.

You may be wondering why I claim it's not a real device.

If you have a detector of polarization, once you fix the angle 'a', you can't distinguish:

1) Unpolarized light, that is in particular the type of light used in a Bell's inequality test where the state is (|00> + |11>)/sqrt(2) or in other versions (|01> + |10>)/sqrt(2), where 0 is horizontal and v is vertical, or a uniform random values of φ in the model of the paper

2) Light polarized in 45° to the detector's angle, that is like a constant φ in both models.

In both cases, you detect 50% of the photons.

If you use the selection device of this paper,

1) with unpolarized light you will get selections when r2 is very small or when φ is almost paraller or orthogonal to the angle a.

2) with polarized light at 45° you will get selections when r2 is very small

So with polarized light at 45° the number of events will be much smaller than with not polarized light.

In particular if you have the source of not polarized light and the detector, adding a polarizer at 45° in the middle will reduce the number of events in the firs case to 1/4 and in the other to almost 0.

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

#48
post #44
post #31

Earlier quoted context omitted.

Hi, author of the article here. Regarding determinism, I think the reason the assertion is "no deterministic local hidden.." is that, you need to break both the deterministic and locality assumption. However there is a nuance, which is, do you need to break both properties to.. (a) break the Bell inequalities, or, to (b) reproduce quantum mechanics.. which is not exactly the same thing. For example, in my toy simulat…

A follow-up point: it sounds like you're also wondering whether it's possible to simulate quantum mechnics exactly with a deterministic non-local hidden variable model? Arguably, this is exactly what the Bohmian "Pilot-wave" interpretation of quantum mechanics is - see e.g. https://plato.stanford.edu/entries/qm-bohm/

Thanks for the pointer.

To be honest, I wasn't wondering that :)

From what I understand, historically nothing ever came of these different interpretations of QM. I subscribe to the Feynman motto of "shut up and calculate", with the modern modification of ".. or simulate".

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

#49
post #46
post #45

> Victor can prepare a pair of quantum particles in a special state known as an entangled state. In this state, the outcomes of Alice's and Bob's measurements are not just random but are correlated in a way that defies any classical explanation based on local hidden variables. What if there are no hidden properties per particle, but the combination of specific property values of particles allow for breaking Bell's In…

"their spin will be correlated" - in this case the billiard's spin is a per-ball property that is set before they are sent to Alice and Bob, and happens to be correlated. You can simulate this in the Python code, but you will not be able to break the Bell inequality like that. This is similar to the dice example I give, where the objects sent to Alice and Bob are random from their perspective (since the dice roll hap…

> In general, classical correlation cannot break the Bell inequalities [assuming no peeking, ie. no action-at-a-distance in the measurement devices].

What if the particles have properties that mutate their state after they are sent to Alice and Bob?

Suppose, in the billiards example, that I put a small device into the balls that changes the spin of the ball to some predefined value.

Wouldn't that break the Bell inequalities without action at a distance?

The reason for the breaking would be that the state of the balls would be modified after they are sent to Alice and Bob. It would look like action at a distance without being 'action at a distance'.

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

#50
post #49
post #46

Earlier quoted context omitted.

"their spin will be correlated" - in this case the billiard's spin is a per-ball property that is set before they are sent to Alice and Bob, and happens to be correlated. You can simulate this in the Python code, but you will not be able to break the Bell inequality like that. This is similar to the dice example I give, where the objects sent to Alice and Bob are random from their perspective (since the dice roll hap…

> In general, classical correlation cannot break the Bell inequalities [assuming no peeking, ie. no action-at-a-distance in the measurement devices]. What if the particles have properties that mutate their state after they are sent to Alice and Bob? Suppose, in the billiards example, that I put a small device into the balls that changes the spin of the ball to some predefined value. Wouldn't that break the Bell inequ…

It doesn't matter when the state of the ball changes (when Victor sends them, on the way, when it's measured). You can play around with this in the Python code, there is shows up like "it doesn't matter which function you put that line of code, the functions are called one after the other". The functions in question are generate_composite(), split(), and the 4 measure_X_Y(), called from bell_experiment().
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