Expansion in terns of Laplacian eigenfunctions

In summary, the conversation discusses the spectral decomposition in String theory, which involves expanding an arbitrary function on a Riemann surface into a complete set of orthogonal eigenfunctions. The decomposition exists under certain assumptions and the set of indices typically runs in a discrete manner. It is a powerful tool with applications in mathematics and physics.
  • #1
Bobdemaths
3
0
Hi !

I am currently studying String theory in Polchinski's book. In section 6.2, eq. 6.2.2, he takes an arbitrary function [itex]X(\sigma)[/itex] defined on a Riemann Surface [itex]M[/itex]. Then he expands it on a complete set of eigenfunctions of the laplacian,
[itex]X(\sigma)=\sum_I x_I X_I(\sigma)[/itex]
with [itex]\Delta X_I = - \omega_I^2 X_I[/itex] and [itex]\int_M d^2 \sigma \sqrt{g} X_I X_{I'} = \delta_{II'}[/itex].

My question now is : when does such a decomposition exist ? Under which assumptions (on the initial function, and the Riemann surface) ? In what kind of set does [itex]I[/itex] run in (discrete ? countable ?) ? It seems to be a very powerful tool, that's why I'm interested in those questions.

Thanks !
 
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  • #2



Hello! It's great to see that you are studying String theory in Polchinski's book. The decomposition you are referring to is known as the spectral decomposition or spectral representation. It is a powerful tool in mathematics and physics, and it can be applied to various systems, including Riemann surfaces.

To answer your question, the decomposition exists under certain assumptions on the initial function and the Riemann surface. The function X(\sigma) must be square integrable on the Riemann surface, and the Riemann surface must have a finite area. Additionally, the eigenfunctions X_I(\sigma) must be orthogonal and complete, meaning that they form a basis for the space of square integrable functions on the Riemann surface.

The set I runs in is typically discrete, meaning that it consists of a finite or countably infinite number of indices. This is because the eigenvalues \omega_I^2 are discrete and the eigenfunctions form a discrete set. However, there are cases where the set I can be continuous, such as when the Riemann surface is a circle.

I hope this helps answer your questions. The spectral decomposition is indeed a powerful tool, and it has applications in various areas of mathematics and physics. Keep studying and exploring its uses in String theory. Best of luck!
 

1. What is expansion in terms of Laplacian eigenfunctions?

Expansion in terms of Laplacian eigenfunctions is a mathematical technique used in the field of differential equations. It involves expressing a function in terms of a set of eigenfunctions of the Laplace operator, which is a differential operator commonly used in physics and engineering.

2. Why is expansion in terms of Laplacian eigenfunctions useful?

Expansion in terms of Laplacian eigenfunctions allows for the simplification of complex differential equations, making it easier to solve for the desired function. It also provides insight into the behavior of the function, as the eigenfunctions represent the different modes of oscillation or behavior of the system.

3. How is expansion in terms of Laplacian eigenfunctions performed?

The expansion is typically done using the Laplace transform, which converts the differential equation into an algebraic equation in terms of the Laplace variable. The eigenfunctions are then used to solve the algebraic equation and obtain the desired function.

4. What are some applications of expansion in terms of Laplacian eigenfunctions?

Expansion in terms of Laplacian eigenfunctions is commonly used in the study of heat transfer, acoustics, and electromagnetism. It is also used in quantum mechanics to solve the Schrödinger equation, which describes the behavior of particles at a quantum level.

5. Are there any limitations to expansion in terms of Laplacian eigenfunctions?

While expansion in terms of Laplacian eigenfunctions is a useful technique, it may not always be applicable to all types of differential equations. It also requires knowledge of the eigenfunctions of the Laplace operator, which may not always be known or easily obtainable.

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