How to multiply matrix with row vector?

  • Context: High School 
  • Thread starter Thread starter entropy1
  • Start date Start date
  • Tags Tags
    Matrix Row Vector
Click For Summary
SUMMARY

The discussion focuses on the multiplication of a 3x3 matrix with a row vector, emphasizing the requirement that the inner dimensions must match for valid multiplication. Specifically, a 3x3 matrix can be multiplied by a 1x3 row vector to yield a 1x3 result, while a 1x3 row vector multiplied by a 3x1 column vector results in a single scalar value, akin to the dot product. The importance of understanding the mathematical significance of 'row times column' is highlighted, as using tricks can lead to confusion rather than clarity.

PREREQUISITES
  • Understanding of matrix dimensions and multiplication rules
  • Familiarity with row and column vectors
  • Basic knowledge of linear algebra concepts
  • Ability to perform dot products and tensor operations
NEXT STEPS
  • Study matrix multiplication rules in linear algebra
  • Learn about the properties of row and column vectors
  • Explore the concept of tensors and their applications
  • Investigate the geometric interpretation of dot products
USEFUL FOR

Students and professionals in mathematics, physics, and engineering who require a solid understanding of matrix operations and their implications in various applications.

entropy1
Messages
1,232
Reaction score
72
How do I calculate a 3x3 matrix multiplication with a 3 column row vector, like below?

##
\begin{bmatrix}
A11 & A12 & A13\\
A21 & A22 & A23\\
A31 & A32 & A33
\end{bmatrix}\begin{bmatrix}
B1 & B2 & B3
\end{bmatrix}
##
 
Last edited:
Physics news on Phys.org
You can only multiply matrix times column or row times matrix.
$$
\begin{pmatrix}a_{11}&a_{12}&a_{13}\\a_{21}&a_{22}&a_{23}\\a_{31}&a_{32}&a_{33}\end{pmatrix}\cdot
\begin{pmatrix}b_{1}\\b_{2}\\b_{3}\end{pmatrix}=
\begin{pmatrix}a_{11}b_{1}+a_{12}b_{2}+a_{13}b_{3}\\a_{21}b_{1}+a_{22}b_{2}+a_{23}b_{3}\\a_{31}b_{1}+a_{32}b_{2}+a_{33}b_{3}\end{pmatrix}
$$
 
  • Like
Likes   Reactions: scottdave and jim mcnamara
The "inner dimensions" must match. A column vector is a 3x1 [3 rows by 1 column] while a row vector is a 1x3 matrix.

Use the outer dimensions to get dimension of the resulting matrix.

So you can multiply a (1x3) by a (3x3) and get a 1x3.

Multiply a 1x3 by a 3x1 and get a 1x1... essentially the same as dot product of two vectors
 
  • Like
Likes   Reactions: DeBangis21 and FactChecker
I guess you can use various tricks, like assuming your row vector is the first row of a 3X3 matrix with zeros in the other places, or that the matrix on the left is made up of three “independent” column vectors, etc. However, you have to ask yourself what mathematical or physical objects do I get from such tricks?
 
Last edited:
apostolosdt said:
However, you have to ask yourself what mathematical or physical objects do I get from such tricks?
That's the point! It is important to understand the rule: 'row times column'. This has a meaning in itself, so "tricks" may cause more confusion than they solve. E.g.
$$
\begin{pmatrix}a&b&c\end{pmatrix}\cdot \begin{pmatrix}x\\y\\z\end{pmatrix} =\bigl \langle \begin{pmatrix}a&b&c\end{pmatrix}\, , \,\begin{pmatrix}x&y&z\end{pmatrix} \bigr\rangle = ax+by+cz \in \mathbb{R}
$$
is a number, e.g. a real number if the vectors have real components, whereas
$$
\begin{pmatrix}a\\b\\c\end{pmatrix}\cdot \begin{pmatrix}x&y&z\end{pmatrix}=\begin{pmatrix}a\\b\\c\end{pmatrix}\otimes \begin{pmatrix}x&y&z\end{pmatrix}=\begin{pmatrix}ax&ay&az\\bx&by&bz\\cx&cy&cz\end{pmatrix} \in \operatorname{M}(2,\mathbb{R})
$$
is a rank-##1## matrix, i.e. e.g. a ##(1,1)##-tensor.
 

Similar threads

  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 6 ·
Replies
6
Views
4K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 27 ·
Replies
27
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
2
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K