Cramer's Rule and Dyadics(Menzel)

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Discussion Overview

The discussion revolves around the application of Cramer's Rule in the context of dyadics as presented in Donald H. Menzel's Mathematical Physics. Participants explore the mathematical formulation and potential issues regarding the transposition of rows in determinants related to the rule, as well as the nature of the dyadic and the algebra involved.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions whether the first and second rows should be transposed in the last equation, suggesting that the current expression may yield a negative result.
  • Another participant points out that the problem involves multi-linear/tensor algebra and seeks clarification on the nature of the basis vectors used.
  • A participant explains that the symbols used represent traditional vector calculus notation and expresses discomfort with the concept of dyadics.
  • Several participants discuss the implications of treating rows as a coefficient matrix and suggest that transposing them could lead to different outcomes in applying Cramer's Rule.
  • One participant emphasizes the need to replace rows in the determinant of the numerator appropriately, based on the coefficients of the transposed matrix.

Areas of Agreement / Disagreement

Participants express differing views on the correct application of Cramer's Rule and the appropriate handling of row transpositions in the context of the problem. The discussion remains unresolved, with multiple competing perspectives on the mathematical formulation.

Contextual Notes

There are limitations regarding the assumptions made about the algebra of the basis vectors and the specific conditions under which Cramer's Rule is applied. The discussion highlights potential misunderstandings related to the ordering of rows in determinants.

Odious Suspect
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The following is from Donald H. Menzel's Mathematical Physics:

##\Phi =\left(
\begin{array}{c}
a_{11}\hat{\mathfrak{i}} \hat{\mathfrak{j}}
+a_{12}\hat{\mathfrak{i}} \hat{\mathfrak{j}}
+a_{13}\hat{\mathfrak{i}} \hat{\mathfrak{k}} \\
+a_{21}\hat{\mathfrak{j}} \hat{\mathfrak{i}}
+a_{22}\hat{\mathfrak{j}} \hat{\mathfrak{j}}
+a_{23}\hat{\mathfrak{j}} \hat{\mathfrak{k}} \\
+a_{31}\hat{\mathfrak{k}} \hat{\mathfrak{i}}
+a_{32}\hat{\mathfrak{k}} \hat{\mathfrak{j}}
+a_{33}\hat{\mathfrak{k}} \hat{\mathfrak{k}} \\
\end{array}
\right)=\hat{\mathfrak{i}} \mathfrak{B}_1+\hat{\mathfrak{j}} \mathfrak{B}_2+\hat{\mathfrak{k}} \mathfrak{B}_3##

##\mathfrak{B}_1=\hat{\mathfrak{i}} a_{11}+\hat{\mathfrak{j}} a_{21}+\hat{\mathfrak{k}} a_{31}=\Phi \cdot \hat{\mathfrak{i}}##

##\mathfrak{B}_2=\hat{\mathfrak{i}} a_{12}+\hat{\mathfrak{j}} a_{22}+\hat{\mathfrak{k}} a_{32}=\Phi \cdot \hat{\mathfrak{j}}##

##\mathfrak{B}_3=\hat{\mathfrak{i}} a_{13}+\hat{\mathfrak{j}} a_{23}+\hat{\mathfrak{k}} a_{33}=\Phi \cdot \hat{\mathfrak{k}}##

##\mathfrak{i}=\frac{\left| \begin{array}{ccc}
\mathfrak{B}_1 & \mathfrak{B}_2 & \mathfrak{B}_3 \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33} \\
\end{array}\right|
}{
\left|
\begin{array}{ccc}
a_{11} & a_{12} & a_{13} \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33} \\
\end{array}
\right|} ##

##\mathfrak{j}=\frac{\left| \begin{array}{ccc}
\mathfrak{B}_1 & \mathfrak{B}_2 & \mathfrak{B}_3 \\
a_{11} & a_{12} & a_{13} \\
a_{31} & a_{32} & a_{33} \\
\end{array} \right|
}{
\left|
\begin{array}{ccc}
a_{11} & a_{12} & a_{13} \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33} \\
\end{array}
\right|} ##

Should the first and second rows be transposed in the numerator of the last equation? It appears that the expression, as given, will result in the negative of the advertised value.
 
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Hey Odious Suspect.

This looks like a multi-linear/tensor problem and I think it needs to be pointed out what sort of algebra the i_hat, j_hat and l_hat (looks like a weird l) have.

Are they just the normal cross product relations or are they something else?
 
chiro said:
Hey Odious Suspect.

This looks like a multi-linear/tensor problem and I think it needs to be pointed out what sort of algebra the i_hat, j_hat and l_hat (looks like a weird l) have.

Are they just the normal cross product relations or are they something else?

##\hat{\mathfrak{i}}, \hat{\mathfrak{j}}, \hat{\mathfrak{k}}## are the traditional ##\hat{i}, \hat{j}, \hat{k}## of vector calculus. I use German (Fraktur) letters for vector-ish and tensor-ish things. The ##\Phi## beast is a dyadic. I am not comfortable enough with dyadics to provide a "crash course" to get you up to speed. You know what the Uppanishads say about the blind leading the blind.

##\mathfrak{B}_i## are vectors (n-tuples).
 
Hi there. so i usually get problems where you transpose a whole matrix. but we can treat the two rows as a coefficient matrix

if you treat the two rows as a coefficient matrix and transpose them you get [ B1 A11 A12 ]
[ B2 B3 A13 ]

cramer's rule if you want to solve for just one of the variables instead of all is that x1 = det ( A1 ) / det (A) x2 = det (A2) / det (A). You could make B the column 1 variable and solve for B. Transpose the matrix. [ B1 a11 a31 ] det (B) / det ( of the original matrix) = B.
[ B2 a12 a32 ]
[ B3 a13 a33 ]

so what a marvel of a comely matrix problem. hope you have a great day.
 
akeleti8 said:
Hi there. so i usually get problems where you transpose a whole matrix. but we can treat the two rows as a coefficient matrix

if you treat the two rows as a coefficient matrix and transpose them you get [ B1 A11 A12 ]
[ B2 B3 A13 ]

cramer's rule if you want to solve for just one of the variables instead of all is that x1 = det ( A1 ) / det (A) x2 = det (A2) / det (A). You could make B the column 1 variable and solve for B. Transpose the matrix. [ B1 a11 a31 ] det (B) / det ( of the original matrix) = B.
[ B2 a12 a32 ]
[ B3 a13 a33 ]

so what a marvel of a comely matrix problem. hope you have a great day.

Thank you for taking the time to read and reply. My question has to do with the ordering of rows in the last application of Cramer's rule in the original post.

##\mathfrak{j}=\frac{\left| \begin{array}{ccc}
\mathfrak{B}_1 & \mathfrak{B}_2 & \mathfrak{B}_3 \\
a_{11} & a_{12} & a_{13} \\
a_{31} & a_{32} & a_{33} \\
\end{array} \right|
}{
\left|
\begin{array}{ccc}
a_{11} & a_{12} & a_{13} \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33} \\
\end{array}
\right|} ##

The replacement of rows in the determinant of the numerator is appropriate due to the fact (which I didn't emphasize) that the coefficients in the system of simultaneous linear equations are those of the transposed matrix. The problem is to solve (invert) the following equation:

##\left[\begin{array}{ccc} \hat{\mathfrak{i}} & \hat{\mathfrak{j}} & \hat{\mathfrak{k}}\end{array}\right]\left[\begin{array}{ccc} a_{11} & a_{12} & a_{13}\\ a_{21} & a_{22} & a_{23}\\ a_{31} & a_{32} & a_{33} \end{array}\right]=\left[\begin{array}{ccc} \mathfrak{B}_{1} & \mathfrak{B}_{2} & \mathfrak{B}_{2}\end{array}\right]##

It appears to me that Menzel should have written

##\mathfrak{j}=\frac{\left| \begin{array}{ccc}
a_{11} & a_{12} & a_{13} \\
\mathfrak{B}_1 & \mathfrak{B}_2 & \mathfrak{B}_3 \\
a_{31} & a_{32} & a_{33} \\
\end{array} \right|
}{
\left|
\begin{array}{ccc}
a_{11} & a_{12} & a_{13} \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33} \\
\end{array}
\right|} ##
 

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