Formula for the propagation of complex errors

  • #1
accdd
96
20
If I have 2 measurements ##x = (3.0 ± 0.1), y = (-2.0 ± 0.1)## and want to calculate how the error propagates when calculating a function from those values this formula should be used: ##f(x, y) = f(x, y) ± \sqrt {(\frac{\partial f}{\partial x}*\Delta x)^2+(\frac{\partial f}{\partial y}*\Delta y)^2}##
What is the formula for calculating error propagation if x and y are complex (##x = (3 ± 0.1) + (9.5 ± 0.4)ⅈ, y = (2 ± 0.1) - (5 ± 0.4)ⅈ##)?
 
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  • #2
Change to polar coordinates.
 
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  • #3
Can you give me an example. Suppose the function is: ##f(x, y) = x + y^2##
In the non-complex case, with the data given in the previous post, I would proceed as follows:
##f(x, y) = x + y^2 = (3+(-2)^2) \pm \sqrt{0.1^2+(2*(-2) *0.1)^2}= 7\pm \sqrt{0.01+0.16}=7\pm0.41##
How can I change to polar coordinates to get the result in case of complex numbers?
The result should be: ##(-18.0 ± 4.0) - (10.5 ± 1.9)ⅈ## (Measurement jl)
 
  • #4
[itex]x+iy\equiv Re^{i\theta} [/itex]where [itex] R=\sqrt{x^{2}+y^{2}}[/itex] and [itex]\theta =\arctan(\frac{y}{x}) [/itex]. This is the easiest representation for complex multiplication (you multiply the argumets and add the angles). Complex addition is easiest in the cartesian notation.
 
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  • #5
I got stuck, not able to get the result. Can someone show me how to do it please?
 
  • #6
Svein said:
Change to polar coordinates.
After that, you'd have to know the variance of the amplitude as a function of the variances of the real and imaginary components. If they had the same variance, I think you'd have a Rayleigh distribution. I'm not sure how that generalizes to the case of unequal variances. Does that distribution have a special name?
 

1. What is the formula for the propagation of complex errors?

The formula for the propagation of complex errors is a mathematical equation used to calculate the uncertainty or error in a measurement that is affected by multiple sources of error. It takes into account the individual errors and their correlations to determine the overall uncertainty in the final result.

2. How is the formula for the propagation of complex errors derived?

The formula for the propagation of complex errors is derived from the principles of error propagation and probability theory. It is based on the concept that the uncertainty in a final measurement is influenced by the uncertainties in the individual measurements and their correlations.

3. Can the formula for the propagation of complex errors be applied to any type of measurement?

Yes, the formula for the propagation of complex errors can be applied to any type of measurement as long as the individual errors and their correlations are known. It is commonly used in fields such as physics, chemistry, and engineering to determine the uncertainty in experimental results.

4. What is the significance of the formula for the propagation of complex errors in scientific research?

The formula for the propagation of complex errors is crucial in scientific research as it allows for a more accurate and reliable determination of uncertainty in experimental results. This helps researchers to make informed decisions and draw meaningful conclusions from their data.

5. Are there any limitations to the formula for the propagation of complex errors?

While the formula for the propagation of complex errors is a useful tool in calculating uncertainty, it does have some limitations. It assumes that the errors are normally distributed and that there is a linear relationship between the measured quantities and the final result. It may not be applicable in cases where these assumptions do not hold.

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