Sum of the probabilities equals 3 in bipartite covariance ?

In summary, if we consider a bipartite system as in an EPRB experiment, we get the probabilities p(++), p(--), p(+,-) and p(-+), p(+A), p(+B), p(-A), and p(-B), respectively. The sum of all the probabilities equals 3. How does that come? Is it because in fact there are only double events out of which we consider the averages of A and B sides too, thus making 3 sample set out of one experiment? Can you be a bit more specific? What is p(+A) for example? p(+A) is the probability of measuring + for the A operator. A and B are just spin
  • #1
jk22
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If we consider a bipartite system as in EPRB experiment we get the probabilities :

p(++)=p(--)=1/4*(1-cos(theta))
p(+-)=p(-+)=1/4*(1+cos(theta))

p(+A)=p(+B)=p(-A)=p(-B)=1/2

Thus the sum of all the probabilities equals 3...

How does that come ? Is it because in fact there are only double events out of which we consider the averages of A and B sides too, thus making 3 sample set out of one experiment ?
 
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  • #2
Can you be a bit more specific? What is p(+A) for example?
 
  • #3
p(+A) is the probability of measuring + for the A operator. A and B are just spin 1/2 operators and we measure a singlet state Psi=1/Sqrt(2)(0,1,-1,0)

measuring A in this bipartite system means of course measuring [tex]A1=A\otimes\mathbb{1}[/tex].

If I take A=diag(1,-1) [tex]B=\left(\begin{array}{cc}cos(\theta)&sin(\theta)\\sin(\theta)&-cos(\theta)\end{array}\right)[/tex] then A1 just has two eigenvalues 1 and -1. p(+A) is the probability of measurement for the eigenvalue 1 of A1.

All this was to compute the covariance [tex]\langle A\otimes B\rangle - \langle A\rangle\langle B\rangle[/tex]

Of course the average of A is p(+A)-p(-A)=0= average of B.
 
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  • #4
If 3 events A B and C are certain to occur we have
p(A) = p(B) = p(C) = 1 and we have p(A) + p(B) + p(C) = 3.
No problem.
What do you want to do with that?
 
  • #5
I am not sure about specific probability of these operators but if I remember the theory of probability correctly,
P(A)+P(B)+P(C) = 1 means the probability of occurring event A or event B or event C is 1. If probability of these events are interconnected it is always 1. If A, B and C are independent, dividing by total events will give 1 anyway.
 
  • #6
if 3 events are sure this means they happen as a whole and nothing else so we normally write p(abc) is 1 ?
 
  • #7
I would say P(A)*P(B)*P(C) = 1. It means the probability of occurring event A and event B and event C is 1 which means all three events will surely happen and as you can see each of these events need to have probability 1 individually in this case.

The P(A) + P(B) + P(C) = 1 means either of these events will surely happen.
 
  • #8
but the axioms of probability say p(omega) is 1 where omega is the set of all events.
I got it :
In our case event A is +-,++,--,-+
B is +a,-a
C is +b,-b

but B and C are not real events we deduce them from A, for example +a is the reunion of ++ and +-
aso.
Thanks, i have often dumb analyses.
 
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1. What is the sum of probabilities equals 3 in bipartite covariance?

The sum of probabilities equals 3 in bipartite covariance refers to the probability of two events occurring simultaneously in a bipartite system. This is calculated by taking the covariance of the two events and multiplying it by the sum of the probabilities of each event.

2. How is the sum of probabilities equals 3 calculated in bipartite covariance?

The sum of probabilities equals 3 in bipartite covariance is calculated by taking the covariance of the two events and multiplying it by the sum of the probabilities of each event. This formula can be written as P(A and B) = Cov(A,B) * (P(A) + P(B)).

3. Why is the sum of probabilities equals 3 important in bipartite covariance?

The sum of probabilities equals 3 is important in bipartite covariance because it allows us to understand the relationship between two events in a system. It helps us determine if the events are positively or negatively correlated, and how strong the correlation is.

4. Can the sum of probabilities equals 3 be greater or less than 3 in bipartite covariance?

No, the sum of probabilities equals 3 cannot be greater or less than 3 in bipartite covariance. This is because the probabilities of the two events must always add up to 1, and the covariance can range from -1 to 1. Therefore, the maximum possible value for the sum of probabilities is 3, and the minimum possible value is -3.

5. How is the sum of probabilities equals 3 related to correlation in bipartite systems?

The sum of probabilities equals 3 is directly related to correlation in bipartite systems. If the sum of probabilities is positive, it indicates a positive correlation between the two events, meaning that when one event occurs, the other is more likely to occur. If the sum of probabilities is negative, it indicates a negative correlation, meaning that when one event occurs, the other is less likely to occur. A sum of probabilities of 3 indicates a perfect positive correlation, while a sum of probabilities of -3 indicates a perfect negative correlation.

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