Uncertainty propagation visible light spectrum

In summary, the conversation discusses an experiment to calculate the range of visible light spectrum using diffraction theory and a diffraction grating. The variables and equations involved are listed, and the conversation also explores how to estimate the uncertainty for a complex equation. It is suggested to use calculus, and a formula for calculating uncertainty in a function with multiple variables is provided. The formula is then applied to the original equation, resulting in a calculated uncertainty of 7.79 x 10^-8, which matches the result obtained from an online uncertainty calculator.
  • #1
zdenton
5
0

Homework Statement


I have conducted an experiment which attempts to calculate the range of the visible light spectrum. Basically white light was shined through a diffraction grating (300 lines/mm) and diffraction theory is applied to calculate the wavelength.

So, here are the variables:
[tex]d=\frac{1}{300000}[/tex]

[tex]l=0.20[/tex]

[tex]\Delta l=0.001[/tex]

[tex]y=0.043[/tex]

[tex]\Delta y=0.005[/tex]


Homework Equations


[tex]\sin\alpha=\frac{\lambda}{d}[/tex]

[tex]\tan\alpha=\frac{y}{l}[/tex]


The Attempt at a Solution


I combined these equations to end up with:
[tex]\lambda=d\times\sin\left(\arctan\left(\frac{y}{l}\right)\right)[/tex]
The problem is that I don't know how to estimate an uncertainty for this equation. I know that for simple equations like [tex]y=q\times r[/tex] the uncertainty is [tex]\Delta y=\left(\frac{\Delta q}{q}+\frac{\Delta r}{r}\right)\times y[/tex]. Unfortunately I don't know how to apply this to a more complex equation. If anyone could lead me in the right direction as to an equation which would give the uncertainty for [tex]\lambda=d\times\sin\left(\arctan\left(\frac{y}{l}\right)\right)[/tex], it would be greatly appreciated.
 
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  • #2
It can be done using calculus, if you've had calculus. But first I would get rid of the trig functions.

What's an equivalent expression for sin(arctan(x)) ?
 
  • #3
[tex]\frac{x}{x^{2}+1}[/tex]
Substituting [tex]\frac{y}{l}[/tex] for [tex]x[/tex] gives:
[tex]\frac{\frac{y}{\left|y\right|}\times l}{\sqrt{y^{2}+l^{2}}}[/tex]

I hadn't thought of doing this, so it seems to be a step in the right direction. I have done limited calculus, I'm just finishing the first year of IB Math HL so we're starting on integration right now. I looked briefly at the wikipedia page for error propagation and didn't really understand it.
 
  • #4
Hmm... yeah, Wikipedia is being ridiculously detailed about this.

FYI, here's the usual case: if you have a function [tex]f(x, y, z)[/tex] and the uncertainties in the arguments are [tex]\delta x[/tex], [tex]\delta y[/tex], and [tex]\delta z[/tex], then the uncertainty in [tex]f[/tex] is
[tex]\delta f = \sqrt{\left(\frac{\partial f}{\partial x}\delta x\right)^2 + \left(\frac{\partial f}{\partial y}\delta y\right)^2 + \left(\frac{\partial f}{\partial z}\delta z\right)^2}[/tex]
Of course, there are some conditions on that formula, i.e. small, independent (uncorrelated) uncertainties and Gaussian distributions, but probably 99% of the time that formula is good enough.
 
  • #5
OK, thanks for the help so far. I applied the above formula to my equation and received the following result:
[tex]\delta f = \sqrt{{\delta l}^{2}\,{\left( -\frac{d\,\left| l\right| \,y}{{l}^{2}\,\sqrt{{y}^{2}+{l}^{2}}}+\frac{d\,y}{\left| l\right| \,\sqrt{{y}^{2}+{l}^{2}}}-\frac{d\,\left| l\right| \,y}{{\left( {y}^{2}+{l}^{2}\right) }^{\frac{3}{2}}}\right) }^{2}+{\delta y}^{2}\,{\left( \frac{d\,\left| l\right| }{l\,\sqrt{{y}^{2}+{l}^{2}}}-\frac{d\,\left| l\right| \,{y}^{2}}{l\,{\left( {y}^{2}+{l}^{2}\right) }^{\frac{3}{2}}}\right) }^{2}}[/tex]

Substituting with the variables in my first post returns the result:
[tex]\delta f = 7.79\times 10^{-8}[/tex]

Which is exactly what I received when I tried using an online uncertainty calculator! Thank you so much!
 
Last edited:

1. What is uncertainty propagation in the visible light spectrum?

Uncertainty propagation in the visible light spectrum refers to the process of quantifying and accounting for the uncertainties associated with measurements or calculations of properties related to visible light, such as wavelength, frequency, and intensity.

2. Why is uncertainty propagation important in the visible light spectrum?

Uncertainty propagation is important in the visible light spectrum because it allows scientists to determine the reliability and accuracy of their measurements and calculations. It also helps to identify and minimize sources of error in experimental or theoretical data.

3. How is uncertainty propagated in the visible light spectrum?

Uncertainty is typically propagated in the visible light spectrum using statistical methods, such as error propagation equations and Monte Carlo simulations. These methods take into account the uncertainties associated with individual measurements and use them to determine the overall uncertainty of a property or parameter.

4. What factors can contribute to uncertainty in the visible light spectrum?

There are several factors that can contribute to uncertainty in the visible light spectrum, including instrumental errors, environmental conditions, and human error. Additionally, the inherent properties of light, such as its wave-particle duality, can also introduce uncertainty in measurements and calculations.

5. How can uncertainty in the visible light spectrum be minimized?

Uncertainty in the visible light spectrum can be minimized by using high-quality and properly calibrated instruments, controlling for environmental factors, and repeating measurements multiple times to account for human error. Additionally, using advanced statistical methods and conducting thorough error analysis can also help to reduce uncertainty.

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