MHB Integrating a diagonal 2x2 matrix

Click For Summary
The discussion focuses on deriving the expression for \(\mathbf{V}_{-1}^{(D)}\) in the context of integrating a diagonal 2x2 matrix. The equation \(\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x} = \frac{i}{2}\begin{bmatrix} -(qr)_t & 0 \\ 0 & (qr)_t \end{bmatrix}\) is rewritten using \(\sigma_3\) to show that it can be expressed in terms of \(\alpha \sigma_3 + c\mathbb{I}\). The relationship \(\alpha_x + \frac{1}{2}i(qr)_t = 0\) indicates how \(\alpha\) is derived from the differential equation. The author concludes that the integration process essentially substitutes one differential equation for another. The thread was later marked as solved by the original poster.
Dustinsfl
Messages
2,217
Reaction score
5
\(r = r(x, t)\), \(q = q(x, t)\), \(\sigma_3 =
\begin{bmatrix}
1 & 0\\
0 & -1
\end{bmatrix}
\)
I have the equation
\begin{align}
\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x} &= \frac{i}{2}\begin{bmatrix}
-(qr)_t & 0\\
0 & (qr)_t
\end{bmatrix}\\
\mathbf{V}_{-1}^{(D)} &= \alpha\sigma_3 + c\mathbb{I}\qquad (*)
\end{align}
where \(\alpha\) is a function of \(x\) and \(t\) related to \(q\) and \(r\) and
\[
\alpha_x + \frac{1}{2}i(qr)_t = 0
\]

How is \((*)\) obtained? I don't see it. I know that \(c\mathbb{I}\) is the matrix constant of integration so I am only focused on how \(\alpha\sigma_3\) comes from integrating the diagonal matrix.

I am trying to figure out the last page of
http://math.arizona.edu/~mcl/Miller/MillerLecture06.pdf
 
Last edited:
Mathematics news on Phys.org
dwsmith said:
\(r = r(x, t)\), \(q = q(x, t)\), \(\sigma_3 =
\begin{bmatrix}
1 & 0\\
0 & -1
\end{bmatrix}
\)
I have the equation
\begin{align}
\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x} &= \frac{i}{2}\begin{bmatrix}
-(qr)_t & 0\\
0 & (qr)_t
\end{bmatrix}\\
\mathbf{V}_{-1}^{(D)} &= \alpha\sigma_3 + c\mathbb{I}\qquad (*)
\end{align}
where \(\alpha\) is a function of \(x\) and \(t\) related to \(q\) and \(r\) and
\[
\alpha_x + \frac{1}{2}i(qr)_t = 0
\]

How is \((*)\) obtained? I don't see it. I know that \(c\mathbb{I}\) is the matrix constant of integration so I am only focused on how \(\alpha\sigma_3\) comes from integrating the diagonal matrix.

I am trying to figure out the last page of
http://math.arizona.edu/~mcl/Miller/MillerLecture06.pdf

Hmm. Interesting. Well, we can write
$$\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x}=\frac{i}{2}\begin{bmatrix}
-(qr)_t & 0 \\ 0 & (qr)_t \end{bmatrix}=- \frac{i(qr)_{t}}{2} \begin{bmatrix} 1 &0 \\ 0 &-1 \end{bmatrix}= - \frac{i(qr)_{t}}{2} \sigma_{3}.$$
At the very least, if we take
$$\mathbf{V}_{-1}^{(D)} = \alpha \sigma_3 + c\mathbb{I} \qquad (*),$$
where
$$\alpha_x + \frac{1}{2}i(qr)_t = 0,$$
then if we differentiate $(*)$ w.r.t. $x$, we get that
$$\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x}= \alpha_{x} \sigma_{3}=
- \frac{i(qr)_{t}}{2} \sigma_{3},$$
which is what we had before. Given that the author has not specified $\alpha$ explicitly, but only given a DE that it satisfies, it looks to me as though he's merely substituted one DE for another.
 
Ackbach said:
Hmm. Interesting. Well, we can write
$$\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x}=\frac{i}{2}\begin{bmatrix}
-(qr)_t & 0 \\ 0 & (qr)_t \end{bmatrix}=- \frac{i(qr)_{t}}{2} \begin{bmatrix} 1 &0 \\ 0 &-1 \end{bmatrix}= - \frac{i(qr)_{t}}{2} \sigma_{3}.$$
At the very least, if we take
$$\mathbf{V}_{-1}^{(D)} = \alpha \sigma_3 + c\mathbb{I} \qquad (*),$$
where
$$\alpha_x + \frac{1}{2}i(qr)_t = 0,$$
then if we differentiate $(*)$ w.r.t. $x$, we get that
$$\frac{\partial\mathbf{V}_{-1}^{(D)}}{\partial x}= \alpha_{x} \sigma_{3}=
- \frac{i(qr)_{t}}{2} \sigma_{3},$$
which is what we had before. Given that the author has not specified $\alpha$ explicitly, but only given a DE that it satisfies, it looks to me as though he's merely substituted one DE for another.

Thanks, I actually figured everything out but forgot to mark the thread as solved.
 
Thread 'Erroneously  finding discrepancy in transpose rule'
Obviously, there is something elementary I am missing here. To form the transpose of a matrix, one exchanges rows and columns, so the transpose of a scalar, considered as (or isomorphic to) a one-entry matrix, should stay the same, including if the scalar is a complex number. On the other hand, in the isomorphism between the complex plane and the real plane, a complex number a+bi corresponds to a matrix in the real plane; taking the transpose we get which then corresponds to a-bi...

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
4K
Replies
33
Views
1K
  • · Replies 16 ·
Replies
16
Views
4K
  • · Replies 4 ·
Replies
4
Views
1K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 2 ·
Replies
2
Views
1K