How is the Bessel function approximated by a ln function

In summary, the approximation for the Bessel function of the second kind is found by adding a constant to theln(x) when x is approaching zero.
  • #1
sinbaski
7
0

Homework Statement


It is stated in "Mathematical methods of Physics" by J. Mathews, 2nd ed, p274, that the Bessel function of the second kind and of order zero, i.e. [itex]Y_0(x)[/itex] can be approximated by [itex]\frac{2}{\pi}\ln(x)[/itex]+constant as [itex]x \to 0[/itex], but no more details are given in the same text.

Homework Equations


Could you show me how that approximation comes about?

The Attempt at a Solution


Visually I see the resemblance between the functions, but I cannot derive the approximation myself.
 
Last edited:
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  • #2
sinbaski said:

Homework Statement


It is stated in "Mathematical methods of Physics" by J. Mathews, 2nd ed, p274, that the Bessel function of the first kind and of order zero, i.e. [itex]Y_0(x)[/itex] can be approximated by [itex]\frac{2}{\pi}\ln(x)[/itex]+constant as [itex]x \to 0[/itex], but no more details are given in the same text.


Homework Equations


Could you show me how that approximation comes about?


The Attempt at a Solution


Visually I see the resemblance between the functions, but I cannot derive the approximation myself.

Hi sinbaski, welcome to PF!:smile:

Do you mean the Bessel function of the second kind? (Bessel functions of the first kind are finite at the origin. and [itex]\frac{2}{\pi}\ln(x)[/itex] is not)
 
  • #3
Yes, gabbagabbahey, I meant the second kind. Sorry, that was a careless typo! :|
 
  • #4
Okay, well there are a few different ways of defining the Bessel functions, so what definition are you using in your course?
 
  • #5
In the same book [itex]Y_m[/itex] is defined as

[itex]
Y_m(x) = \frac{J_m(x) \cos m\pi - J_{-m}(x)}{\sin m\pi}
[/itex]

while [itex]J_m(x)[/itex] is defined as
[itex]
J_m(x) = \sum_{r=0}^{\infty} \frac{(-1)^r}{r! \Gamma(r+m+1)}\left(\frac{x}{2}\right)^{2r+m}
[/itex]
 
  • #6
I think the answer will pop out if you go back to solving the Bessel differential equation for m=0. The method of Frobenius will yield one solution J0(x), and now you need to construct a second, independent one.
 
  • #7
I have to admit I can't solve by hand the Bessel equation
[itex]
x^2 y'' + x y' + x^2 y = 0
[/itex]

Matlab gives the solution to the equation as
[itex]
A J_0(x) + B Y_0(x)
[/itex]

Still I don't see how [itex]\frac{2}{\pi}\ln(x)[/itex] emerges from the equations :(
 
  • #8
You want to learn about the Frobenius method. Depending on the roots so the indicial equation, sometimes it'll yield two independent solutions, but in this case, it doesn't. Wikipedia just tells you the form of the second solution.

http://en.wikipedia.org/wiki/Frobenius_method#Double_roots

If you look on page 16 of Mathews and Walker, there's a discussion of how to solve Bessel's equation using Frobenius, including how to find the second solution.
 
  • #9
I did a bit more reading, and it looks like to get the constant factor of ##2/\pi##, you're going to have to look at the definition of Ym(x). It's an indeterminate form when m is an integer, so you want to evaluate it using L'Hopital's rule.
 
  • #10
sinbaski said:
In the same book [itex]Y_m[/itex] is defined as

[itex]
Y_m(x) = \frac{J_m(x) \cos m\pi - J_{-m}(x)}{\sin m\pi}
[/itex]

For integer [itex]m[/itex], this should really be

[tex]Y_m(x) = \lim_{\alpha \to m} \frac{J_{\alpha}(x) \cos \alpha \pi - J_{-\alpha}(x)}{\sin \alpha \pi}[/tex]

while [itex]J_m(x)[/itex] is defined as
[itex]
J_m(x) = \sum_{r=0}^{\infty} \frac{(-1)^r}{r! \Gamma(r+m+1)}\left(\frac{x}{2}\right)^{2r+m}
[/itex]

Okay, so use this definition, with the (corrected) one above to find an expression for [itex]Y_0(x)[/itex].

Note: There's no need for you to actually solve Bessel's differential equation for this problem (the above equations are the two independent solutions), but it is a good exercise and one you may want to do after this problem (or before)
 
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  • #11
Thank you for your kind reply! The wikipage is very comprehensive compared with the book. Now I think I have got something, following your advice:
[itex]
\lim_{m\to 0} \frac{\cos m\pi J_m(x) - J_{-m}(x)}{\sin m\pi}
[/itex]
[itex]
= \lim_{m\to 0}\frac{
-\pi\sin m\pi J_m(x) + \cos m\pi \frac{\partial}{\partial m}J_m(x) + \frac{\partial}{\partial (-m)}J_{-m}(x)
}{\pi \cos m\pi}
[/itex]
[itex]
= \frac{2}{\pi} \lim_{m\to 0} \frac{\partial}{\partial m}J_m(x)
[/itex]

Then
[itex]
\frac{\partial}{\partial m}J_m(x) = \frac{\partial}{\partial m}\sum_{r=0}^{\infty} \frac{(-1)^r}{r!\Gamma(m+r+1)}\left(\frac{x}{2}\right)^{m+2r}
[/itex]
[itex]
= \ln(x/2)\sum_{r=0}^{\infty} \frac{(-1)^r}{r!\Gamma(m+r+1)}\left(\frac{x}{2}\right)^{m+2r} +
\sum_{r=0}^{\infty} \left(\frac{x}{2}\right)^{m+2r} \frac{\partial}{\partial m}\frac{(-1)^r}{r!\Gamma(m+r+1)}
[/itex]

Taking the limit [itex]x \to 0, m\to 0[/itex], the first sum reduces to [itex]\ln(x/2)[/itex] while the second becomes a constant. Thus we get the desired result of [itex]\frac{2}{\pi}\ln(x)+C[/itex]

Do you think this argument is correct?
 
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  • #12
sinbaski said:
[itex]
= \ln(x/2)\sum_{r=0}^{\infty} \frac{(-1)^r}{r!\Gamma(m+r+1)}\left(\frac{x}{2}\right)^{m+2r} +
\sum_{r=0}^{\infty} \left(\frac{x}{2}\right)^{m+2r} \frac{\partial}{\partial m}\frac{(-1)^r}{r!\Gamma(m+r+1)}
[/itex]

Taking the limit [itex]x \to 0, m\to 0[/itex], the first sum reduces to [itex]\ln(x/2)[/itex] while the second becomes a constant. Thus we get the desired result of [itex]\frac{2}{\pi}\ln(x)+C[/itex]

Do you think this argument is correct?

I'm not sure it makes any sense to say that taking the limit [itex]x \to 0[/itex] and [itex]m \to 0[/itex] of [itex]\ln(x/2)\sum_{r=0}^{\infty} \frac{(-1)^r}{r!\Gamma(m+r+1)}\left(\frac{x}{2}\right)^{m+2r}[/itex] results in [itex]\ln(x/2)[/itex]. I think you should take the limit [itex]m \to 0[/itex] of the whole expression (obviously you will need to first calculate [itex]\frac{\partial}{\partial m}\frac{(-1)^r}{r!\Gamma(m+r+1)}[/itex] ), simplify it as much as possible, and then do a Taylor Series approximation for small [itex]x[/itex].
 

1. What is a Bessel function?

A Bessel function is a mathematical function that is commonly used in physics and engineering to describe phenomena such as wave propagation, heat conduction, and quantum mechanics. It is named after the mathematician Friedrich Bessel and is characterized by its oscillatory behavior.

2. How is the Bessel function approximated by a ln function?

The Bessel function can be approximated by a ln function using the asymptotic expansion method. This involves finding a series of terms that become increasingly accurate as the variable in the function approaches a certain value. In the case of Bessel functions, the variable is usually the size of the argument, and the ln function is used to approximate the behavior of the function for large arguments.

3. What is the purpose of approximating the Bessel function by a ln function?

The Bessel function is a complex function that can be difficult to work with, especially for large arguments. By approximating it with a simpler function like ln, calculations become easier and more manageable. This approximation is also useful for analyzing the behavior of the Bessel function at its asymptotes, which can provide valuable insights for solving practical problems.

4. Are there any limitations to approximating the Bessel function by a ln function?

Yes, there are limitations to this approximation. The ln function is only accurate for large arguments and may not accurately represent the behavior of the Bessel function for smaller arguments. Therefore, this method should only be used when working with large arguments. Additionally, the accuracy of the approximation can vary depending on the specific Bessel function being approximated.

5. How do scientists use the Bessel function approximation in their research?

Scientists use the Bessel function approximation in a variety of fields, including physics, engineering, and mathematics. It is often used to model physical phenomena such as heat transfer, wave propagation, and quantum mechanics. In practical applications, the Bessel function approximation can also be used to simplify complex calculations and provide insights into the behavior of the system being studied.

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