Bell's Theorem: Griffiths' Probability Density & Indeterministic QM

AI Thread Summary
Griffiths' use of the probability density \rho(\lambda) for hidden variables in Bell's Theorem raises questions about the determinism of quantum mechanics. The hidden variable theory aims to demonstrate that quantum mechanics is incomplete by suggesting that unknown properties (\lambda) influence outcomes, leading to statistical distributions rather than deterministic predictions. This implies that even "identically prepared" systems may differ due to their unique histories. The discussion highlights a potential contradiction in using probability to describe a theory intended to be deterministic. Understanding these concepts may be clarified through additional resources, such as Blumel's explanations.
touqra
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I am referring to Introduction to Quantum Mechanics (2nd Edition) by David J. Griffiths, page 425 on Bell's Theorem.

Griffiths used a parameter, called \rho(\lambda) as the probability density for the hidden variable.

What I don't understand is that the hidden variable was suppose to make the theory deterministic, or specifically to show that quantum mechanics as an indeterministic theory is incomplete.
What is the reason that he can use probability to describe the hidden variable? Isn't this a contradiction?
 
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This test of QM involves making many measurements on systems that have been "identically prepared". The idea of HV theory is that there might be some unknown property of the system (labeled by \lambda) that determines exactly what will happen in that particular system, and that \lambda varies from system to system. Thus the supposedly "identical preparation" of different systems is actually not identical, but depends in some way on the precise details and prior history of each system. This gives a statistical distribution for \lambda which is called \rho(\lambda).

EDIT: just noticed that the OP is from 2005!
 
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