Error Propagation in Transcendental Equation

In summary, the student is trying to solve an equation for k in a way that propagates errors due to a error in a.
  • #1
jst6981
2
1
Hey guys,

I'm in a class where we're learning about waveguides, and without going into too much depth, we often solve an equation

$$ \tan{(\kappa (\frac{a}{2}))} = \frac{\gamma}{\kappa} $$

for ##\kappa## numerically since there isn't an analytic solution for ##\kappa##. I'm doing a project where ##a## has an error ##\Delta a##, and I want to be able to solve this in a way so that I have a ##\kappa## written ##\kappa \pm \Delta \kappa## so that I can propagate the error in ##\kappa## due to the error in ##a## throughout the rest of my calculations for the project.

If anybody has a nice way I can do this, please let me know. I appreciate help in advance!
 
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  • #2
Vary a by Δa up and down, solve for ##\kappa## in both cases. If the resulting deviations of ##\kappa## are reasonably symmetric, use that as uncertainty. Otherwise it might need more sophisticated approaches.
 
  • #3
I had considered that, each function is roughly linear when they intersect as below.
upload_2017-11-12_23-29-52.png


I think it may work
 

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  • #4
If you write that k is a function of a and differentiate your equation wrt a, you can eliminate the trig and get a differential equation for k. Manipulate that to get k' as a function of k and a.
 
  • #5
Do you want an analytical solution or you are fine with using numerical solutions?
In the latter you can generate some toys, let's say 10,000...
In each toy, you randomly sample [itex]\alpha[/itex] from a gaussian (for example) with mean [itex]\alpha[/itex] and standard deviation [itex]\Delta \alpha[/itex], so that you get a set [itex]\{\alpha_i\} , i=1,~2,~...,~10000[/itex] measurements...
You can get the [itex]\{k_i\}[/itex] set from your equation.
See how it's distributed and try to find the 68% central coverage (aka determine [itex]\Delta k_{\pm}[/itex] where plus/minus means the up/down uncertainty - that means the range [nominal-down, nominal] contains the 34% of your toys and the range [nominal,nominal+up] contains the other 34%)...
 

1. What is error propagation in transcendental equations?

Error propagation in transcendental equations refers to the process of determining how uncertainties in the input variables affect the final result of a transcendental equation. Transcendental equations are those that involve transcendental functions such as trigonometric, exponential, or logarithmic functions. The propagated error is a measure of the uncertainty in the final result.

2. Why is error propagation important in scientific calculations?

Error propagation is important in scientific calculations because it allows us to understand the reliability and accuracy of our results. By considering the uncertainties in the input variables, we can determine the range of possible values for the final result and assess the significance of our findings.

3. How is error propagation calculated in transcendental equations?

The process of error propagation in transcendental equations involves using the partial derivative of the equation with respect to each input variable. These partial derivatives are then multiplied by the corresponding uncertainties in the input variables and added in quadrature to obtain the total propagated error.

4. Can error propagation be avoided in transcendental equations?

No, error propagation cannot be avoided in transcendental equations. Since these equations involve transcendental functions, they do not have a simple analytical solution and must be solved numerically. As a result, uncertainties in the input variables will always affect the final result.

5. How can error propagation be minimized in transcendental equations?

Error propagation can be minimized in transcendental equations by increasing the precision of the input variables. This can be achieved by using more accurate measuring instruments or increasing the number of significant figures in the data. Additionally, using numerical methods that are more accurate and stable can also help reduce error propagation.

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