Binomial Theorem Application in Cauchy's and Sellmeier's Equations

AI Thread Summary
The discussion focuses on applying the binomial theorem to relate Cauchy's and Sellmeier's equations in optics. The main task is to show that Cauchy's equation approximates Sellmeier's equation when the wavelength is much larger than the characteristic wavelengths. The hint suggests rewriting Sellmeier's equation and expanding it using the binomial theorem, specifically after taking the square root of n^2. A key step involves expressing the term in a suitable form for expansion, leading to a clearer understanding of the relationship between the two equations. The conversation highlights the importance of manipulating the equations correctly to facilitate the application of the binomial theorem.
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I am trying to do a question from Eugene Hecht's Optics book, which goes something like this:

Given the following equations:

Cauchy's Equation:

n = C_1 + \frac{C_2}{\lambda^2} + \frac{C_3}{\lambda^4} + ...

Sellmeier's Equation:

n^2 = 1 + \sum_{j} \frac{A_j\lambda^2}{\lambda^2-\lambda_0_j^2}<br />

where the A_j terms are constants and each \lambda_0_j is the vacuum wavelength associated with a natural frequency v_0_j, such that \lambda_0_jv_0_j = c.

Show that where \lambda &gt;&gt; \lambda_0_j, Cauchy's Equation is an approximation of Sellmeier's Equation.

Now it also gives a hint which is as follows:

Write the above expression with only the first term in the sum; expand it by the binomial theorem; take the square root of n^2 and expand again.

From the hint, I gather that it means to rewrite Sellmeier's Equation as:

n^2 = 1 + \frac{A\lambda^2}{\lambda^2 - \lambda_0^2}

From there though, I have no idea how to apply the binomial theorem to expand it. I just don't see how anything in that equation has the form (x+y)^n, except for where n = 1.

If anyone can explain to me how to apply the binomial theorem to the equation, or if I've misunderstood what the hint means, it would be much appreciated.
 
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You can use the binomial theorem to expand (1+x)^{1/2} when x<<1.
 
So you mean first take the square root of both sides, then expand it using the binomial theorem , letting x = \frac{A\lambda^2}{\lambda^2 - \lambda_0^2}, rather than first applying the binomial theorem, then taking the square root of both sides and then expanding again like the hint suggests?
 
Rewrite \frac{A_j\lambda^2}{\lambda^2-\lambda_0_j^2} as

\frac{A_j}{\lambda^2}\frac{1}{1-\frac{\lambda_0_j^2}{\lambda^2}} and expand the second part as

\frac{1}{1-x^2} \approx 1 - x^2 + x^4 - x^6 \ldots where x = \frac{\lambda}{\lambda_0_j}
 
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Aah, I didn't think to do that. Thanks, that was a great help.
 
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