Closed form solution for large eigenvalues

In summary, the eigenvalues of a given equation can be approximated by \(k\pi\) where \(k\) is a positive integer. For better accuracy, a larger value of \(k\) can be chosen, but the bound for \(k\) should be based on the desired level of accuracy.
  • #1
Dustinsfl
2,281
5
The eigenvalues are found by
$$
\tan\lambda_n = \frac{1}{\lambda_n}
$$
For large eigenvalues, the intersection get closer and closer to $\lambda_n = \pi k$ where $k\in\mathbb{Z}^+$ and $k > 15$.
Is this correct? Without arbitrary picking a $k$, is there a better way to determine a $k$ for when $\lambda\to\pi k$?
 
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  • #2
dwsmith said:
The eigenvalues are found by
$$
\tan\lambda_n = \frac{1}{\lambda_n}
$$
For large eigenvalues, the intersection get closer and closer to $\lambda_n = \pi k$ where $k\in\mathbb{Z}^+$ and $k > 15$.
Is this correct? Without arbitrary picking a $k$, is there a better way to determine a $k$ for when $\lambda\to\pi k$?

\[\tan\lambda_n = \frac{1}{\lambda_n}\]

\[\Rightarrow \lambda_n=k\pi+\tan^{-1}\frac{1}{\lambda_n}\mbox{ where }k\in\mathbb{Z}\]

For large positive or negative values of \(\lambda_n\), \(\tan^{-1}\frac{1}{\lambda_n}\approx 0\)

\[\therefore \lambda_n\approx k\pi\mbox{ where }k\in\mathbb{Z}\]

The larger \(k\) value you use the approximation will be better. Choosing a bound for \(k\) depends on the accuracy that you need for your approximation.
 

FAQ: Closed form solution for large eigenvalues

What is a closed form solution for large eigenvalues?

A closed form solution for large eigenvalues is a mathematical expression that can be used to directly calculate the eigenvalues of a large matrix, without the need for iterative methods. It is a more efficient and accurate way to find eigenvalues compared to other methods.

How is a closed form solution for large eigenvalues different from other methods?

A closed form solution for large eigenvalues is different from other methods because it directly calculates the eigenvalues without the need for iteration, making it faster and more accurate. Other methods, such as the power method or the Jacobi method, require multiple iterations to approximate the eigenvalues.

What are the benefits of using a closed form solution for large eigenvalues?

Using a closed form solution for large eigenvalues has several benefits. It is faster and more accurate compared to other methods, making it a more efficient way to find eigenvalues. It also allows for a better understanding of the mathematical properties of the matrix and its eigenvalues.

Are there any limitations to using a closed form solution for large eigenvalues?

While a closed form solution for large eigenvalues is a more efficient and accurate method, it may not always be possible to find a closed form solution for every matrix. In some cases, the matrix may be too complex, making it difficult or impossible to directly calculate the eigenvalues.

How is a closed form solution for large eigenvalues used in scientific research?

A closed form solution for large eigenvalues is commonly used in scientific research, particularly in fields such as physics, engineering, and statistics. It is used to analyze and understand complex systems, such as quantum mechanical systems, and to solve problems that involve large matrices with many variables.

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