Transforming E^2(x,t) to A_y^2 + A_z^2 in Harmonic Waves

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SUMMARY

The transformation of the equation ##E^2(x,t)## to ##A_y^2 + A_z^2## in harmonic waves is clarified through integration over one complete cycle. The established equation ##E^2 = E_y^2 + E_z^2## leads to the integral result of ##\frac{\pi A_y^2}{\omega} + \frac{\pi A_z^2}{\omega}## when evaluated from ##t = 0## to ##t = \frac{2\pi}{\omega}##. This result can be simplified to yield the intensity equation ##I = \frac{1}{2} \Big( \frac{\epsilon}{\mu} \Big)^{\frac{1}{2}} (A_y^2 + A_z^2)##. The discussion emphasizes the importance of correctly interpreting the time period ##T## in relation to the frequency ##f## for accurate integration.

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Athenian
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Homework Statement
Show that ##I = \frac{1}{2} \Big( \frac{\epsilon}{\mu} \Big)^{\frac{1}{2}} (A_y^2 + A_z^2)##
Relevant Equations
$$I = \frac{1}{T} \int_0^T \Big( \frac{\epsilon}{\mu} \Big)^{\frac{1}{2}} E^2 (x,t)dt$$
$$E_y (x,t) = A_y cos(kx-\omega t)$$
$$E_z (x,t) = A_z cos(kx-\omega t + \phi)$$
Note that ##\phi## is the phase difference
$$E^2 = E_y^2 + E_z^2$$
To begin with, I am trying to understand how does ##E^2 (x,t)## transform to ##A_y^2 + A_z^2##. And, noting that the already established equation of ##E^2 = E_y^2 + E_z^2##, I would assume that ##E^2 (x,t)## somehow ends up to being ##A_y^2 + A_z^2##. However, noting that ##E^2 = (A_y cos(kx-\omega t))^2 + (A_z cos(kx-\omega t + \phi))^2##, I can't see how this can be equal to ##A_y^2 + A_z^2## yet. In other words, I am having a hard time with the math if I am going about this in the right direction.

In short, any help toward helping me understand and ultimately solve the question would be greatly appreciated. Thank you for your help!
 
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Athenian said:
However, noting that E2=(Aycos(kx−ωt))2+(Azcos(kx−ωt+ϕ))2, I can't see how this can be equal to Ay2+Az2 yet.
It isn't. But integrate it from t = 0 to 2π/ω.
 
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Thank you for your reply. Here's what I did.

Since
$$E^2=(A_y cos(kx−\omega t))^2+(A_z cos(kx−\omega t+ \phi))^2$$

I can continue per your instructions (if I understood it correctly) by writing the following:
$$\int_0^\frac{2 \pi}{\omega} (A_y cos(kx−\omega t))^2+(A_z cos(kx−\omega t+ \phi))^2 dt = \frac{\pi A_y^2}{\omega} + \frac{\pi A_z^2}{\omega}$$

The above answer is what I got when I plugged the values into Wolfram|Alpha. However, despite integrating, my answer does not exactly equate to ##A_y + A_z##. Am I doing something wrong here or am I on the right track?

Also, I noticed you substituted ##\frac{2\pi}{\omega}## (or ##\frac{1}{f}##) for ##T##. However, isn't ##T## (time) much larger compared to the time period of oscillation (i.e. ##T >> \frac{1}{f}##)? Or, despite that, it's still fine to integrate from ##0## to ##\frac{2\pi}{\omega}##. Anyway, I just wanted to make sure I am having my understanding completely accurate and coreect.

Once again, thank you so much for your kind and prompt assistance!
 
Please ignore my confusion in the above reply. It was pretty late and I wasn't exactly thinking straight despite my efforts. Anyway, a good night's rest was all I needed to get my mind on the right track.

In short, my partial answer of ##\frac{\pi A_y^2}{\omega} + \frac{\pi A_z^2}{\omega}## was correct. However, I did not put in mind that ##\frac{1}{T}## before the integral would also become ##\frac{1}{\frac{2\pi}{\omega}}## instead.

Multiplying and simplifying everything, I got the desired solution of ##I = \frac{1}{2} \Big( \frac{\epsilon}{\mu} \Big)^{\frac{1}{2}} (A_y^2 + A_z^2)##.

However, my original question re-quoted below still stands. If somebody can help answer this conceptual or math-based question to reinforce my understanding, I would greatly appreciate it. Thank you!

Athenian said:
Also, I noticed you substituted ##\frac{2\pi}{\omega}## (or ##\frac{1}{f}##) for ##T##. However, isn't ##T## (time) much larger compared to the time period of oscillation (i.e. ##T >> \frac{1}{f}##)? Or, despite that, it's still fine to integrate from ##0## to ##\frac{2\pi}{\omega}##?
 
The answer is strictly true only for T = an integral multiple of 1/f. However, if T >> 1/f the error is small. If we write T = n/f + d, then the 1/T factor mean the error due to d is very small if n is very large.
 
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