Having trouble writing down a metric in terms of metric tensor in matrix form?

In summary: Here is the corrected summary:In summary, to write the FLRW metric in matrix form, we first assign the coordinates q0, q1, q2, and q3 to t, w, θ, and Φ respectively. Then, the matrix of coefficients will be a diagonal matrix with diagonal entries of 1, -R(t)^2, -R(t)^2*s^2, and -R(t)^2*s^2*sin^2(θ) respectively. This corresponds to the scalar coefficients in each term of the metric expression, with a factor of 1/2 for off-diagonal terms.
  • #1
zeromodz
246
0
Can someone please explain to me how exactly you write down a metric, say the FLRW metric in matrix form. Say we have the given metric here.

ds^2 = dt^2 - R(t)^2 * [dw^2 + s^2 * (dθ^2 + sin^2(θ)dΦ^2)]

Thank you.
 
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  • #2
Let the coordinates be q1,q2,q3,q4.

The line element will be a sum of terms like C12dq1dq2.

In matrix form, C12 will be in row 1 column 2 of the matrix.

Edit: See Rasalhague's post for the correct version. I forgot the 1/2 for the off-diagonal terms.
 
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  • #3
In your example, if q0 = t, q1 = w, q2 = θ, q3 = Φ (where superscripts are indices), then the matrix of coefficients will be as follows, with superscript 2 denoting an exponent:

[tex]\begin{pmatrix}
1 & 0 & 0 & 0\\
0 & R(t)^2 & 0 & 0\\
0 & 0 & (R(t) \cdot s)^2 & 0\\
0 & 0 & 0 & (R(t)\cdot s \cdot \sin(\theta))^2
\end{pmatrix}[/tex]

= diag(1,0,0,0) - R(t)2[diag(0,1,0,0) + s2(diag(0,0,1,0)+diag(0,0,0,sin(θ)2)].

Here diag(a,b,c,d) denotes a diagonal 4x4 matrix with diagonal entries as indicated, from top left to bottom right.

In general, given an expression of the form

[tex]ds^2 = ...,[/tex]

where the values of the indices are not equal, the scalar coefficients in each term of the form

[tex]A \, dx^\mu dx^\nu \enspace (\text{no summation} )[/tex]

(EDIT: Ignore the words "no summation" - a relic of previous version which I forgot to remove before posting. Sorry.) correspond to matrix entries

[tex]g_{\mu\nu} = \frac{1}{2} A.[/tex]

And where the values of the indices are equal, the scalar coefficients in each term of the form

[tex]B \, (dx^\mu)^2[/tex]

correspond to matrix entries

[tex]g_{\mu\mu} = B.[/tex]
 
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  • #4
Rasalhague accidentally missed some minus signs:

[tex]\begin{pmatrix}
1 & 0 & 0 & 0\\
0 & -R(t)^2 & 0 & 0\\
0 & 0 & -R(t)^2 \, s^2 & 0\\
0 & 0 & 0 & -R(t)^2 \, s^2 \, \sin^2\theta
\end{pmatrix}[/tex]​
 
  • #5
Oopsh... Thanks for the correction, Dr Greg!
 

FAQ: Having trouble writing down a metric in terms of metric tensor in matrix form?

What is a metric tensor?

A metric tensor is a mathematical object that describes the distance and angle relationships between points in a space. It is used in the field of differential geometry to measure distances and angles in curved spaces.

Why is it important to write a metric in terms of a metric tensor in matrix form?

Writing a metric in terms of a metric tensor in matrix form allows for a simpler and more compact representation of the metric. It also makes it easier to perform calculations and transformations in the space.

How do you write a metric in terms of a metric tensor in matrix form?

To write a metric in terms of a metric tensor in matrix form, you first need to identify the components of the metric tensor that correspond to the metric. Then, you can write the metric in terms of these components using matrix notation.

What are the benefits of using a matrix form for a metric tensor?

Using a matrix form for a metric tensor allows for easier manipulation and calculation of the metric. It also allows for a more intuitive understanding of the metric and its properties.

Are there any limitations to writing a metric in terms of a metric tensor in matrix form?

One limitation of writing a metric in terms of a metric tensor in matrix form is that it may not be possible to do so for all types of metrics, especially in non-Euclidean spaces. Additionally, the matrix form may not be suitable for certain types of calculations or transformations in the space.

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