An integral over three Legendre polynomials

In summary, the conversation discusses an integral involving Legendre polynomials and the attempt to find an analytic solution for it. The conversation also mentions the diagonal and off-diagonal terms and the potential form of the solution. Additional help or hints are requested to find the exact form of the solution.
  • #1
alfredska
31
0

Homework Statement


I encountered the following integral in my research, and I've yet to find an analytic solution:
[tex]I(n_1,n_2,n_3) = \int_{-1}^{1} d(\cos\theta_1) \int_{-1}^{1} d(\cos\theta_2) P_{n_1}(\cos\theta_1) P_{n_2}[\cos(\theta_1-\theta_2)] P_{n_3}(\cos\theta_2)[/tex]
where [itex]P_n(x)[/itex] is the nth Legendre polynomial.

Homework Equations


Orthogonal polynomial relation:
[tex]\int_{-1}^{1} d(\cos\theta) P_{n_1}(\cos\theta) P_{n_2}(\cos\theta) = \int_{0}^{\pi} d\theta (\sin\theta) P_{n_1}(\cos\theta) P_{n_2}(\cos\theta) = \frac{2}{2n_1+1}\delta_{n_1,n_2}[/tex]

The Attempt at a Solution


Mathematica does not have much trouble in evaluating the integral exactly (Integrate, not NIntegrate) for a given set of [itex]\{n_1, n_2, n_3\}[/itex].
Code:
k[n1_,n2_,n3_]:=Integrate[Sin[x]Sin[y]LegendreP[n1,Cos[x]]LegendreP[n2,Cos[x-y]]LegendreP[n3,Cos[y]],{x,0,Pi},{y,0,Pi}]

I can see already that [itex]I(n_1, n_2, n_3)[/itex] is not diagonal.

The diagonal terms contain the factor [tex]\frac{2^n}{(2n+1)^2}[/tex]
but that is not all. They also contain something that looks like a truncated double factorial: [itex](2n-1)![/itex], where the truncation point is not clear yet. And still there's more to the series that I haven't figured out:
[tex]I(n,n,n) = 2^n \left[\frac{2}{2n+1}\right]^2 \times \left\{1,\frac{1}{2},\frac{1}{3},\frac{1}{5},\frac{4}{35},\frac{4}{63},\frac{8}{231},\frac{8}{429}, \frac{64}{6435}, ... \right\}[/tex]
for [itex]n=0,1,2,...[/itex]

The off-diagonal terms appear to all contain a [itex]\pi^2[/itex] term, and some power of 2.

I suspect that the solution will need to be written in the form
[tex]I(n_1,n_2,n_3) = \delta_{n_1,n_2}\delta_{n_2,n_3}f(n_1) + (1-\delta_{n_1,n_2}\delta_{n_2,n_3})\pi^2 g(n_1,n_2,n_3)[/tex]
 
Last edited:
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  • #2
but I haven't been able to find the exact form of f and g. Any help or hints would be greatly appreciated.
 

FAQ: An integral over three Legendre polynomials

1. What is an integral over three Legendre polynomials?

An integral over three Legendre polynomials is a mathematical expression that involves the integration of three separate Legendre polynomials, which are special types of mathematical functions. The integral is typically written as ∫P(x)Q(x)R(x)dx, where P(x), Q(x), and R(x) are Legendre polynomials.

2. How is an integral over three Legendre polynomials different from a regular integral?

An integral over three Legendre polynomials differs from a regular integral because it involves the integration of three separate Legendre polynomials, rather than just one. This makes the calculation more complex and requires a different approach than a regular integral.

3. What is the purpose of an integral over three Legendre polynomials?

The purpose of an integral over three Legendre polynomials is to find the area under the curve formed by the three polynomials. It is commonly used in mathematical and scientific applications, such as in calculating moments of inertia in physics and in solving differential equations.

4. What are some techniques for solving an integral over three Legendre polynomials?

There are several techniques for solving an integral over three Legendre polynomials, including using special integration formulas for Legendre polynomials, applying the product rule and substitution, and using numerical integration methods such as Simpson's rule.

5. How can an integral over three Legendre polynomials be applied in real-world situations?

An integral over three Legendre polynomials has many practical applications in fields such as physics, engineering, and statistics. It can be used to calculate moments of inertia for rotating objects, solve differential equations in quantum mechanics, and estimate probabilities in statistical analysis.

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