Uncovering Uncertainty: The Experimental Covariance Curve for Entangled Photons

In summary, the conversation discusses experimental covariance curves for entangled photons, specifically with a focus on abs(Cov(0)) being less than 1. The example of the violation of Bell inequalities by photons more than 10km apart is mentioned, and there is a discussion about the ability to predict with certainty in this case. A quantum calculation is also mentioned, with the result being -7/8*cos(theta), which is different from the standard qm prediction of -cos(theta). There is a question about whether the theory needs to be changed to better match the experimental result, or if the experiment itself is not accurate enough. It is noted that no experiment is perfect and there is always some degree of uncorrelated background that can reduce
  • #1
jk22
729
24
Some experimental covariance curve for entangled photons gives abs(Cov(0)) less than 1.
For example : Violation of Bell inequalities by photons more than 10km apart by Gisin's group in Geneva.

Does this mean that experimentally we can't predict with certainty in this case ?

In order to explain that curve I made a quantum calculation that leads to Cov(theta) equals -7/8*cos(theta) but i find it a bit weird and don't know if i can put it in this forum.
 
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  • #2
Does this mean that experimentally we can't predict with certainty in this case ?
Knowing one value, we cannot predict the other with 100% certainty in this case, right.
 
  • #3
However standard qm gives -cos(theta) and hence predict with certainty at theta equals 0.

So is the theory with something to be changed in order to get nearer to the experimental result or is it the experiment which is not accurate enough ?
 
  • #4
I don't know which specific experiment you mean, but no experiment is perfect. You always have uncorrelated background (or even background correlated in the wrong way), which reduces correlation.
 

Related to Uncovering Uncertainty: The Experimental Covariance Curve for Entangled Photons

What is an experimental covariance curve?

An experimental covariance curve is a graphical representation of the relationship between two variables in an experiment. It shows the change in one variable in response to changes in the other variable.

Why is the experimental covariance curve important?

The experimental covariance curve is important because it allows scientists to visually identify and understand the relationship between two variables in an experiment. This can help them make conclusions about the cause and effect relationship between the variables.

How is an experimental covariance curve calculated?

The experimental covariance curve is calculated by taking the product of the deviations of each data point from the mean for both variables and then dividing by the total number of data points.

What does a positive covariance value on the curve indicate?

A positive covariance value on the curve indicates that the two variables are positively correlated, meaning that as one variable increases, the other also increases.

Can the experimental covariance curve show causation between two variables?

No, the experimental covariance curve alone cannot show causation between two variables. It only shows the relationship between the variables and further experiments or analysis is needed to establish causation.

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