Problem with vectors and matrices.

In summary: For example, ##(\vec a.\vec \sigma)^2## is ##\left(\sum_i a_i\sigma_i\right)^2 = \left(\sum_i a_i\sigma_i\right)\left(\sum_j a_j\sigma_j\right)##. This gives 4 terms, 2 of which are zero, the other two are ##a_ia_j\sigma_i\sigma_j##. ##\sigma_i\sigma_j## is a 2x2 matrix too, so is a scalar multiple of one of the unit matrices, ##\sigma_1, \sigma_2, \sigma_3##. So ##(\vec a.\vec \sigma)^2 =
  • #1
Dewgale
98
9

Homework Statement


Calculate ##(\vec a \cdot \vec \sigma)^2##, ##(\vec a \cdot \vec \sigma)^3##, and ##(\vec a \cdot \vec \sigma)^4##, where ##\vec a## is a 3D-vector and ##\vec \sigma## is a 3D-vector formed from the ##\sigma_i## vectors.

Homework Equations


$$\sigma_1 = \begin{bmatrix}
0 & 1\\
1 & 0
\end{bmatrix}$$
$$\sigma_2 = \begin{bmatrix}
0 & -i\\
i & 0
\end{bmatrix}$$
$$\sigma_3 = \begin{bmatrix}
1 & 0\\
0 & -1
\end{bmatrix}$$

The Attempt at a Solution


This makes very little sense to me, since there are no ##\sigma_i## vectors, just matrices. My main thought was to take the determinant of each matrix and set it as a component, such that
$$\vec \sigma_i = <-1,-1,-1>$$

Then ##\vec a \cdot \vec \sigma_i## is ##-(a_1 + a_2 + a_3)##.
##(\vec a \cdot \vec \sigma_i)^2## is ##(a_1 + a_2 + a_3)^2##,
##(\vec a \cdot \vec \sigma_i)^3## is ##-(a_1 + a_2 + a_3)^3## and
##(\vec a \cdot \vec \sigma_i)^4## is ##(a_1 + a_2 + a_3)^4##.

I have no idea, however, whether this is the right approach. Some guidance on this would be nice, thank you!
 
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  • #2
A notation like ##\mathbf{a}\cdot\mathbf{\sigma}## is just a way of saying ##a_1\sigma_1 + a_2\sigma_2 + a_3\sigma_3##. ##\mathbf{a}## is known to be a 3D vector, therefore its components are just numbers.
 
  • #3
blue_leaf77 said:
A notation like ##\mathbf{a}\cdot\mathbf{\sigma}## is just a way of saying ##a_1\sigma_1 + a_2\sigma_2 + a_3\sigma_3##. ##\mathbf{a}## is known to be a 3D vector, therefore its components are just numbers.

Yes, I know that. Thank you though. I'm confused though as to how to form a 3D vector from three 2x2 matrices. Is there a prescribed method or do I just need to do something along the lines of what I did?
 
  • #4
The sigma vector ##\mathbf{\sigma}## is just one example of vector operators, another example would be the orbital angular momentum operator ##\mathbf{L}##. Operators in quantum mechanics (as well as in linear algebra in general) need not always be represented by a matrix. The matrix representation is especially helpful when you are working in the basis formed by the eigenstates of the operator being represented as a matrix. If, on the other hand, you are given a problem in which you have to operate ##L_z## on ##Y_{lm}(\theta,\phi)## (##|l,m\rangle## in position basis), you will then resort to the position form of ##L_z##, which is equal to ##-i\hbar\frac{\partial}{\partial\phi}##, instead of its matrix form.
Dewgale said:
I'm confused though as to how to form a 3D vector from three 2x2 matrices.
Especially for spin operators, there is no position representation for them. Therefore, the most commonly used representation for these operators are the matrix form.
 
  • #5
I think what's throwing you is the last word in the problem statement. If you change it from 'vectors' to 'matrices' does it make sense for you?
##a_i\sigma_i## is just a scalar multiplied by a 2x2 matrix, giving another 2x2 matrix. The dot product ##\vec a.\vec \sigma## is a sum of these, so is another 2x2 matrix. This can be raised to integer powers.
 

1. What is a vector?

A vector is a mathematical object that represents both magnitude (size) and direction. It is typically represented as an arrow in a coordinate system, with the length of the arrow representing the magnitude and the direction of the arrow representing the direction.

2. What is a matrix?

A matrix is a rectangular array of numbers or variables arranged in rows and columns. It is used to represent and manipulate data in a structured format, and is commonly used in fields such as linear algebra, statistics, and computer science.

3. What is the difference between a vector and a matrix?

A vector is a one-dimensional object, meaning it only has one row or one column. A matrix, on the other hand, is a two-dimensional object with multiple rows and columns. While vectors can be thought of as a single entity, matrices are made up of multiple entities.

4. How are vectors and matrices used in science?

Vectors and matrices are used in a variety of scientific fields, such as physics, engineering, and computer science. They are used to model and solve problems involving multiple variables and dimensions, and are essential in analyzing and interpreting data.

5. What are some common operations performed on vectors and matrices?

Some common operations on vectors and matrices include addition, subtraction, multiplication, and division. These operations can be performed between vectors, between matrices, or between a vector and a matrix. Other operations include dot product, cross product, transpose, and inversion.

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