Gaussian Integrals in Two Dimensions

In summary, a Gaussian integral in two dimensions is a mathematical concept used to calculate the area under a two-dimensional Gaussian function, commonly used in probability theory and statistics. There are various methods for solving these integrals, and they have many practical applications in physics, engineering, and statistics. However, they may not accurately model all real-world situations that do not follow a normal distribution. An example of a Gaussian integral in two dimensions is calculating the probability of a particle's position in a two-dimensional box using the wave function of the particle.
  • #1
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Let ##a, b##, and ##c## be real numbers such that ##a## and ##c## are positive and ##ac > b^2##. Evaluate the double integral $$\int_{-\infty}^\infty \int_{-\infty}^\infty e^{-ax^2 - 2bxy - cy^2}\, dx\, dy$$
 
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  • #2
Diagonalizing [itex]\begin{pmatrix} a & b \\ b & c \end{pmatrix}[/itex] seems like a good start.
 
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  • #3
The matrix in post 2 is symmetric so it is diagonalized by multiplications of orthonormal matrix and its inversed so transversed matrix from the both ends. The orthonormal matrix change bases from x,y to another orthonormal bases, say u,v with ##dxdy=dudv##.
[tex]
ax^2+2bxy+cy^2=\begin{pmatrix}
x & y \\
\end{pmatrix}
\begin{pmatrix}
a & b \\
b & c \\
\end{pmatrix}
\begin{pmatrix}
x \\
y \\
\end{pmatrix}
=
\begin{pmatrix}
u & v \\
\end{pmatrix}
\begin{pmatrix}
\lambda_1& 0 \\
0 & \lambda_2 \\
\end{pmatrix}
\begin{pmatrix}
u \\
v \\
\end{pmatrix}
=\lambda_1 u^2+ \lambda_2 v^2
[/tex]

In this new bases the double integral is carried out independently so the integral is
[tex]\frac{\pi}{\sqrt{\lambda_1\lambda_2}}[/tex]
where eigenvalues ##\lambda_1,\lambda_2## are solutions of quadratic secular equation
[tex](a-\lambda)(c-\lambda)-b^2=0[/tex]
[tex]\lambda^2 -(a+c)\lambda+ac-b^2=0[/tex]
Thus the integral is
[tex]\frac{\pi}{\sqrt{ac-b^2}}[/tex]
 
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  • #4
\begin{align*}
\int_{-\infty}^\infty \int_{-\infty}^\infty e^{-ax^2 - 2bxy - cy^2} dxdy & = \int_{-\infty}^\infty \int_{-\infty}^\infty e^{-a \left( x + \frac{b}{a} y \right)^2 + \frac{b^2}{a} y^2 - cy^2} dxdy
\nonumber \\
& = \int_{-\infty}^\infty \left( \int_{-\infty}^\infty e^{-a \left( x + \frac{b}{a} y \right)^2} dx \right) e^{- \frac{1}{a} (ac - b^2) y^2} dy
\nonumber \\
& = \sqrt{\frac{\pi}{a}} \int_{-\infty}^\infty e^{- \frac{1}{a} (ac - b^2) y^2} dy \qquad (\text{note: } ac-b^2 > 0)
\nonumber \\
& = \sqrt{\frac{\pi}{a}} \cdot \sqrt{\frac{a \pi}{ac-b^2}}
\nonumber \\
& = \frac{\pi}{\sqrt{ac-b^2}}
\end{align*}
 
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FAQ: Gaussian Integrals in Two Dimensions

1. What is a Gaussian integral in two dimensions?

A Gaussian integral in two dimensions is a type of integral that involves a two-dimensional Gaussian function. This function is defined as f(x,y) = Ae-(x2+y2)/2σ2, where A is a constant and σ is the standard deviation. The integral is typically written as ∫∫f(x,y)dxdy and can be used to calculate the area under the curve of the Gaussian function over a two-dimensional space.

2. What is the purpose of calculating Gaussian integrals in two dimensions?

Gaussian integrals in two dimensions are often used in statistics and physics to model and analyze various phenomena. They can also be used to calculate probabilities and determine the expected value of a random variable. In physics, they are commonly used to solve problems related to heat transfer, diffusion, and wave propagation.

3. How do you solve a Gaussian integral in two dimensions?

Solving a Gaussian integral in two dimensions involves using various techniques such as substitution, integration by parts, and completing the square. It is also helpful to use tables or software programs to look up the values of common integrals. In some cases, the integral may not have an exact solution and numerical methods may be used to approximate the value.

4. What are some applications of Gaussian integrals in two dimensions?

Gaussian integrals in two dimensions have various applications in science and engineering. In statistics, they are used to calculate probabilities and determine confidence intervals. In physics, they are used to solve problems related to heat transfer, diffusion, and wave propagation. They are also used in signal processing, image processing, and pattern recognition.

5. Are there any limitations to using Gaussian integrals in two dimensions?

While Gaussian integrals in two dimensions have many applications, they also have some limitations. For example, the integral may not have an exact solution in some cases and numerical methods must be used. Additionally, the Gaussian function assumes a symmetric distribution, which may not accurately model all real-world phenomena. It is important to carefully consider the assumptions and limitations when using Gaussian integrals in two dimensions.

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