Equations for Lagrange-Laguerre mesh

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In summary, the author is looking for the expressions for the Kinetic energy matrix elements for the Laguerre mesh to be used in solving the 1-D Schrodinger equation. They are looking for $T_{ij} =\frac{{\alpha + 1}^{2}}{(4x_i)^2} + S_{ij}, i=j$ where $S_{ij}=\left(x_ix_j\right)^{\frac{1}{2}} \sum_{k \ne i,j} {x^{-1}_k }(x_k - x_i)^{-1}(x_k-x_j)^{-1
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ognik
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Hi - I have been through quite a few articles on the Lagrange Mesh method and mostly follow it, but still find it confusing to understand which are the practical equations I should be using.

I want to find the expression(s) for the Kinetic energy matrix elements for the Laguerre mesh to be used in solving the 1-D Schrodinger eqtn. - so that I can write a fortran program to calculate the elements.

I will assume the potential V everywhere = 0, then the Schrodinger eqtn I want to solve is (from a couple of the articles, mostly with Baye an author) $ \hat{T}\phi = E\phi $, where $ \hat{T} = - \d{^2{}}{{x}^2} + \frac{\alpha(\alpha -2)}{4x^2} $

Not stated in the article, but I will assume that the usual $\frac{{\hbar}^{2}}{2m}$ term has been set to 1 for convenience.

The articles actually recommend the Hermite mesh for 1-D, but my task is to use the Laguerre mesh. What I couldn't be certain of from the articles therefore, is that the $\frac{\alpha(\alpha -2)}{4x^2}$ term seems to be for the Laguerre mesh in a radial situation, therefore for the 1-D case I think I should use $\hat{T} = - \d{^2{}}{{x}^2}$ but would appreciate confirmation?Either way, the articles state the following eqtns for the matrix elements:

$ T_{ij} =\frac{{\alpha + 1}^{2}}{(4x_i)^2} + S_{ij}, i=j $
$ T_{ij} = {(-1)}^{(i-j)} \left[ \frac{1}{2}\left(\alpha+1{\left(x_i x_j\right)}^{-\frac{1}{2}}\right)
\left( {x_i}^{-1}+{x_j}^{-1} \right) + S_{ij} \right] , i \ne j$

where $ S_{ij}=\left(x_ix_j\right)^{\frac{1}{2}} \sum_{k \ne i,j} {x^{-1}_k }(x_k - x_i)^{-1}(x_k-x_j)^{-1} $

But how big do I make the matrix? I think that I should sum i,j from 1 to N and look at the accuracy with different values of N
The Laguerre mesh is over $[0, \infty)$ and some of the error in the method are the mesh points between N and $\infty$ that we ignore. An example in an article used N=4, but with no justification.

However the column vectors of T will be an orthonormal basis for the space, which should be 1-D so I can't see how T can be an NxN matrix, with N large?

The N I choose also determines the Laguerre eqtn from which the mesh points $x_i$ can be determined, the roots from $L^{\alpha}_N(x_i) = 0 $ This all makes me think there is more than 1 N in play?

I have read through these articles until the letters dribbled off the page in protest, the answer to N eludes me.

Even if you don't have all the answers, I'd appreciate all assistance, thanks.
 
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I noticed that N determines the number of solutions (eigenvalues, leading to eigenvectors). I think that by choosing N, I effectively ignore the terms between N and $\infty$ - so those represent some error in the method.
I am still not sure what N represents, I could see it representing the radial distance from the original but am sure it is more than that?
 

FAQ: Equations for Lagrange-Laguerre mesh

What is the purpose of Lagrange-Laguerre mesh equations?

The purpose of Lagrange-Laguerre mesh equations is to provide a mathematical framework for solving complex problems in fields such as physics, engineering, and economics. These equations involve a combination of Lagrange polynomials and Laguerre polynomials, which are used to approximate solutions to differential equations or optimization problems.

How are Lagrange-Laguerre mesh equations different from other types of mesh equations?

Lagrange-Laguerre mesh equations are unique because they use a specific combination of polynomials to accurately represent a wide range of functions. This allows for more efficient and accurate solutions compared to other types of mesh equations.

Can Lagrange-Laguerre mesh equations be used for any type of problem?

While Lagrange-Laguerre mesh equations are versatile and can be applied to many different types of problems, they are most commonly used for solving differential equations and optimization problems.

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Like any mathematical tool, Lagrange-Laguerre mesh equations have their limitations. They may not be suitable for highly nonlinear problems or problems with complex boundary conditions. Additionally, the accuracy of the solutions may be affected by the number of mesh points used.

How are Lagrange-Laguerre mesh equations applied in real-world situations?

Lagrange-Laguerre mesh equations have a wide range of applications in various fields, such as fluid dynamics, heat transfer, and structural engineering. They are used to model and solve problems in these areas, providing valuable insights and predictions for real-world situations.

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