Numerical method to Lippman-Schwinger equation

In summary, this sums up to saying that you can re-order terms in a finite sum without changing the result.
  • #1
HadronPhysics
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There is a question that puzzle me when I apply numerical method to principal value integral. Let me descibe it. We make use of the fact that the integral ##\int_0^\infty \frac{dk}{k^2-k_0^2}## vanishes, namely,
$$
\int_0^\infty \frac{dk}{k^2-k_0^2} = 0 .
$$
We use this formula to express a principal value intergral as
$$ \mathcal{P}\int_0^\infty \frac{f(x)}{k^2-k_0^2}dk = \int_0^\infty \frac{f(k)-f(k_0)}{k^2-k_0^2}dk .$$
Now, the right hand side is no longer singular at ##k=k_0## because it is proportional to the derivative ##df/dx##. We can approximate this integral numerically, i.e.,
$$ \int_0^\infty \frac{f(k)-f(k_0)}{k^2-k_0^2}dk \approx \sum_i^N w_i \frac{f(k_i)-f(k_0)}{k_i^2-k_0^2} ,$$
where we adopt the Gaussian quadrature method.
Next, we change to Lippman-Schwinger equation where the principal integral occurs. That is
$$ R(k', k) = V(k', k) + \frac{2}{\pi} \mathcal{P}\int_0^\infty dp \frac{p^2V(k', p)R(p, k)}{(k_0^2-p^2)/2\mu} .$$
Then, we can evaluate this equation by the method that we have mentioned. we get
$$ R(k, k_0) = V(k, k_0) + \frac{2}{\pi} \sum_i^N \frac{p_i^2V(k', p_i)R(p_i, k_0)-k_0^2V(k', k_0)R(k_0, k_0)}{(k_0^2-p_i^2)/2\mu} w_i ,$$
where we let $k$ be $k_0$.
At present, everything is ok. the question that puzzles me will occur at the next step. In some computational physics books, for example, you can refer to [[1]](#id1), page: 118, it said that we can split term in summation to two part, namely,
$$ R(k, k_0) = V(k, k_0) \frac{2}{\pi} \left[ \sum_i^N \frac{k_i^2V(k, k_i)R(k_i, k_0)w_i}{(k_0^2-k_i^2)/2\mu} - k_0^2V(k, k_0)R(k_0, k_0)\sum_j^N\frac{w_j}{(k_0^2-k_j^2)/2\mu} \right] .$$
In the previous discussion, we constructed the term $\frac{f(k)-f(k_0)}{k^2-k_0^2}$ to avoid the singular at $k=k_0$. But here, we split the summation into two part. If $k_j\to k_0$, or $k_i\to k_0$, we can not see the term that is proportional to $df/dk$. I can not understand this step, because I think it contradicts the eqaution: ##\mathcal{P}\int_0^\infty \frac{f(x)}{k^2-k_0^2}dk = \int_0^\infty \frac{f(k)-f(k_0)}{k^2-k_0^2}dk. ##<div id="id1"></div>
- [1] [COMPUTATIONAL PHYSICS](https://courses.physics.ucsd.edu/2017/Spring/physics142/Lectures/Lecture18/Hjorth-JensenLectures2010.pdf)
 
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  • #2
You have approximated the integral by a finite sum of bounded quantities. Terms of finite sums can always be re-ordered as you find convenient without affecting the result, and doing so in a context where you are using floating-point arithmetic might actually increase the accuracy of the result.

You are not then taking the limit [itex]N \to \infty[/itex] and trying to sum an infinite series, where I agree that any re-ordering of the terms would require rigorous jusitification that the limit is not thereby affected. (It is more complicated here, since the values of the summands are themselves dependent on [itex]N[/itex].)
 
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1. What is the Lippman-Schwinger equation?

The Lippman-Schwinger equation is a mathematical equation used in quantum mechanics to describe the scattering of particles by a potential. It is used to calculate the scattering amplitude, which is a measure of how likely it is for particles to scatter off each other.

2. How is the Lippman-Schwinger equation solved numerically?

The Lippman-Schwinger equation can be solved numerically using various methods such as the finite difference method, the finite element method, and the boundary element method. These methods involve discretizing the equation and solving it iteratively to obtain a numerical solution.

3. What are the advantages of using a numerical method to solve the Lippman-Schwinger equation?

Numerical methods offer a more efficient and accurate way to solve the Lippman-Schwinger equation compared to analytical methods. They also allow for the inclusion of complex potentials and boundary conditions, making them more versatile for practical applications.

4. Are there any limitations to using a numerical method for the Lippman-Schwinger equation?

One limitation of using a numerical method is that it requires a significant amount of computational resources, especially for higher dimensional problems. Additionally, the accuracy of the solution may be affected by the choice of discretization and numerical parameters.

5. How can the accuracy of a numerical solution to the Lippman-Schwinger equation be improved?

The accuracy of a numerical solution can be improved by using more advanced numerical techniques, such as adaptive mesh refinement, to better capture the behavior of the solution. It is also important to carefully choose the numerical parameters and ensure that the discretization is fine enough to accurately represent the problem.

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