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FOUNDATIONS OF QUANTUM MECHANICS

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VII. 5. STOCHASTIC HIDDEN VARIABLES 155<br />

Using (VII. 64), another Bell inequality can be derived for E(⃗a, ⃗ b) by means of the relation<br />

∫<br />

E(⃗a, ⃗ (<br />

b) = p⃗a, ⃗ b<br />

(1, 1, λ) − p ⃗a, ⃗ b<br />

(1, −1, λ) (VII. 66)<br />

Defining<br />

Λ<br />

− p ⃗a, ⃗ b<br />

(−1, 1, λ) + p ⃗a, ⃗ b<br />

(−1, −1, λ) dλ )<br />

∫<br />

(<br />

= p⃗a (1 | λ) − p ⃗a (−1 | λ) ) ( p ⃗b (1 | λ) − p ⃗b (−1 | λ) ) ρ(λ) dλ.<br />

Λ<br />

f (⃗a, λ) := p ⃗a (1 | λ) − p ⃗a (−1 | λ) (VII. 67)<br />

and<br />

g( ⃗ b, λ) := p ⃗b (1 | λ) − p ⃗b (−1 | λ), (VII. 68)<br />

we see that<br />

|f (⃗a, λ)| 1 and |g( ⃗ b, λ)| 1, (VII. 69)<br />

which brings us back to (VII. 25) and the subsequent equations so that again we obtain the Bell<br />

inequality (VII. 13). Violation of this Bell inequality means that (VII. 64) can not apply and<br />

therefore no HVT can guarantee both outcome independence (VII. 61) and parameter independence<br />

(VII. 62). □<br />

VII. 5. 1<br />

OUTCOME, PARAMETER AND SOURCE INDEPENDENCE<br />

The importance of the distinction between outcome and parameter independence was first brought<br />

to attention by J. Jarrett (1984).<br />

1. Outcome independence, (VII. 61), means that the probability of outcome b, for given λ, does<br />

not depend on the outcome a. This is motivated by the idea that λ gives a complete description of<br />

the state of the pair of particles; the variable λ contains an exhaustive specification of all factors<br />

which are relevant for the outcomes of measurement. Therefore, specifying the extra information that<br />

outcome a has occurred can, if λ is already known, not lead to new information on b.<br />

The purpose of the requirement can be illustrated by giving the next example, in which it is not<br />

satisfied. Suppose that two people, without looking, each draw a little ball out of a box containing two<br />

little balls, one black and one white. Hereafter they separate, one travels to New York, the other to<br />

Tokyo. Now consider a ‘stochastic hidden variable’ with probability 1 2<br />

for the little balls to be black<br />

or white. On arrival at Tokyo the traveler opens his hand and sees that his little ball is black, which<br />

instantaneously enables him to predict the color of the little ball in New York, it has to be white. Here<br />

the outcome of measurement of the one little ball does provide relevant information on the outcome<br />

of a measurement of the other little ball.

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