Integral Calculation: Solving for S with A as Symmetric Matrix

In summary, the integral in question can be solved by using Cholesky decomposition to reduce it to a sequence of standard Gaussian integrals. However, it is important to note that the result depends on the dimensions of the matrix, with a minus overall sign for odd dimensions and the determinant of the matrix for even dimensions. Additionally, it is necessary to check which matrices the integral exists for.
  • #1
ChrisVer
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Homework Statement


I'm trying to calculate the integral:
[itex]S= \int (d^{N}x) exp(x_{i} A_{ij} x_{j}) = (\frac{\pi^{N}}{detA})^{\frac{1}{2}}[/itex]
where the integration is done over (-∞,+∞) , and [itex]A_{ij}=A_{ji}[/itex] (symmetric NxN matrix)


Homework Equations





The Attempt at a Solution



I am not sure how am I supposed to start calculating... Please don't give explicit answer, just a starting hint??
 
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  • #2
ChrisVer said:

Homework Statement


I'm trying to calculate the integral:
[itex]S= \int (d^{N}x) exp(x_{i} A_{ij} x_{j}) = (\frac{\pi^{N}}{detA})^{\frac{1}{2}}[/itex]
where the integration is done over (-∞,+∞) , and [itex]A_{ij}=A_{ji}[/itex] (symmetric NxN matrix)


Homework Equations





The Attempt at a Solution



I am not sure how am I supposed to start calculating... Please don't give explicit answer, just a starting hint??

I assume you meant to write ##\exp(-\sum_i \sum_j A_{ij} x_i x_j)## instead of ##\exp(x_i A_{ij} x_j)##; note the sign difference, among other things. If so, look at 'Cholesky Decomposition'; see, eg., http://en.wikipedia.org/wiki/Cholesky_decomposition. That reduces the quadratic form to a sum of squares and thus reduces your integral to a sequence of standard Gaussians. Also: there are symmetric matrices A that make your so-called result false, so you had better find out what the true question really is.
 
  • #3
In fact the question is introductory to get into calculating:
[itex] \int d^{N}\theta d^{N}\bar{\theta} exp(-\bar{\theta}_{i}A_{ij} \theta_{j})[/itex]
for [itex]\theta[/itex] being grassmann variables...
My problem with that integral, is the case of finding the normal "gaussian" integral...for which I have:
[itex]exp(-a \bar{\theta} \theta)= 1-a \bar{\theta} \theta[/itex]
which gives as a result after integrating:
[itex] \int d\theta d\bar{\theta} (1-a \bar{\theta} \theta))= -a [/itex]
(or should I first anticommute the [itex]\theta[/itex]s?)
If I use the same procedure as for the normal multidimensional gaussian integral (I'm asking about) -after diagonalizing the A etc- I will get:
[itex] \int d^{N}\theta d^{N}\bar{\theta} exp(\sum_{i}-\bar{\theta}_{i}A_{ii} \theta_{i})= ∏_{i} (-A_{ii}) ≠ detA[/itex]
which I find everywhere as a result... well it depends on the dimensions, because for N=even then indeed I get the [itex]detA[/itex] result...otherwise (if N is odd) I'm getting a minus overall sign...
 
Last edited:
  • #4
I guess that's not a Grassmann integral but a usual real integral. The trick is to realize that you can diagonalize the matrix with an SO(N) transformation. Then everything splits in a product of single Gaussians, and this product can be written in terms of the determinant. Note that there should be the sign change as indicated in posting #2. The sum symbols are not necessary, if the Einstein summation convention is used.

Of course, you should also check for which matrices the integral exists at all!
 

Related to Integral Calculation: Solving for S with A as Symmetric Matrix

1. What is integral calculation and how is it used to solve for S with A as a symmetric matrix?

Integral calculation is a mathematical process used to find the area under a curve. In this particular scenario, it is used to find the value of S when A is a symmetric matrix. This is done by setting up an integral equation and using integration techniques to solve for S.

2. What is a symmetric matrix and why is it important in integral calculation?

A symmetric matrix is a square matrix where the values above and below the main diagonal are reflections of each other. In integral calculation, it is important because it simplifies the integration process and makes it easier to solve for S.

3. Can any symmetric matrix be used to solve for S using integral calculation?

No, not all symmetric matrices can be used. The matrix must have certain properties, such as having real eigenvalues, in order for the integral calculation to be successful in solving for S.

4. What are some common techniques used in integral calculation to solve for S?

Some common techniques used include substitution, integration by parts, and partial fractions. These techniques can help simplify the integral equation and make it easier to solve for S.

5. Are there any real-world applications of integral calculation for solving for S with A as a symmetric matrix?

Yes, integral calculation is used in many fields such as physics, engineering, and economics. It can be used to solve optimization problems, calculate volumes and areas, and model natural phenomena. In these applications, solving for S with A as a symmetric matrix can help find solutions and make predictions.

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