Matrix Notation: ℝm x n Meaning & Vectors

In summary, When referring to matrices, ℝm x n usually means a set of m by n matrices with real coefficients. This notation can also apply to vectors, as they can be regarded as matrices as well. However, for referring to vectors in an m*n-dimensional real space, the notation would be written as ℝmn. Another example of notation for matrices is ℂ2, which can mean either complex 2-dimensional vectors or complex 2 by 2 matrices. The Pauli spin matrices in Quantum mechanics are examples of complex 2 by 2 matrices, which act on the vector space ℂ2.
  • #1
dyn
773
61
Hi. When referring to matrices what does ℝm x n mean ? Does this notation also apply to vectors ?
Thanks
 
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  • #2
dyn said:
Hi. When referring to matrices what does ℝm x n mean ? Does this notation also apply to vectors ?
Thanks
It usually means ##m \times n## real matrices, i.e. matrices with ##m## rows and ##n## columns and real numbers as entries.
You may regard every single matrix as a vector as well, if you like. So, yes.
However, if one only wants to speak about vectors in an ##m \cdot n##-dimensional real space, one would probably write ##\mathbb{R}^{mn}##.
 
  • #3
dyn said:
Hi. When referring to matrices what does ℝm x n mean ? Does this notation also apply to vectors ?
Thanks
I would assume it means the space of m by n matrices with real coefficients. Not sure that I have seen it before, though. The x could be to distinguish it from ℝmn, which would mean vectors with mn coefficients. Same dimensionality and, regarded purely as vector spaces, isomorphic, but capable of different additional structure.
 
  • #4
haruspex said:
I would assume it means the space of m by n matrices with real coefficients. Not sure that I have seen it before, though. The x could be to distinguish it from ℝmn, which would mean vectors with mn coefficients. Same dimensionality and, regarded purely as vector spaces, isomorphic, but capable of different additional structure.

Yes, it's the set of all matrices with real coefficients. It's the same as ##M_{n,m}(\mathbb{R})##
 
  • #5
Thanks. I have seen 2x2 complex matrices described by ℂ2. Does this mean ℂ2 x 2 ? Are people using this notation interchangeably or sloppily ?
 
  • #6
dyn said:
Thanks. I have seen 2x2 complex matrices described by ℂ2. Does this mean ℂ2 x 2 ? Are people using this notation interchangeably or sloppily ?
No. It means it is ... uh, wrong.

One might write ##\mathbb{C}^2## as real ##2 \times 2##-matrices, i.e. elements of ##\mathbb{R}^{2 \times 2}##.

Complex
##2 \times 2##-matrices are elements of ##\mathbb{C}^{2 \times 2}##.
They apply to / operate on / map vectors of ##\mathbb{C}^2##.
 
  • #7
fresh_42 said:
No. It means it is ... uh, wrong.

One might write ##\mathbb{C}^2## as real ##2 \times 2##-matrices, i.e. elements of ##\mathbb{R}^{2 \times 2}##.
Surely that would be wrong too. It should mean complex vectors of two dimensions.
 
  • #8
haruspex said:
Surely that would be wrong too. It should mean complex vectors of two dimensions.
I can write every ##\begin{bmatrix}x_1+iy_1 \\ x_2+iy_2\end{bmatrix}\in \mathbb{C}^2## as ##\begin{bmatrix}x_1 & x_2 \\ y_1 & y_2 \end{bmatrix} \in \mathbb{R^{2 \times 2}}##, can't I?
How would you start to explain that ##SU(2)## is a cover of ##SO(3)##?
 
  • #9
fresh_42 said:
I can write every ##\begin{bmatrix}x_1+iy_1 \\ x_2+iy_2\end{bmatrix}\in \mathbb{C}^2## as ##\begin{bmatrix}x_1 & x_2 \\ y_1 & y_2 \end{bmatrix} \in \mathbb{R^{2 \times 2}}##, can't I?
You can set up a mapping between the two, but it is not an isomorphism. There is a multiplication defined for ##\mathbb{C}^2 \times \mathbb{C}^2\rightarrow\mathbb{C}##, and one defined for ##\mathbb{R}^{2 \times 2}\times\mathbb{R}^{2 \times 2}\rightarrow\mathbb{R}^{2 \times 2}##, but no mapping for either.
 
  • #10
haruspex said:
You can set up a mapping between the two, but it is not an isomorphism. There is a multiplication defined for ##\mathbb{C}^2 \times \mathbb{C}^2\rightarrow\mathbb{C}##, and one defined for of ##\mathbb{R}^{2 \times 2}\times\mathbb{R}^{2 \times 2}\rightarrow\mathbb{R}^{2 \times 2}##, but no mapping for either.
None of which I claimed. I only said it can be written as such (implying it can serve for some applications).
I have not claimed that it is an algebra isomorpism. However, it is an isomorphism of real vector spaces! To disqualify this as wrong, is misleading, to say the least.
 
  • #11
fresh_42 said:
I only said it can be written as such (implying it can serve for some applications
I guess that's where we differ. Writing it "as such" implies isomorphism to me. Qualified with suitable wording to explain the sense in which they are being equated (i.e. describing the mapping) is fine, but that is different.
 
  • #12
Thanks. So as a specific example if I have the Pauli spin matrices from Quantum mechanics. Are they examples of ℂ2 or ℂ2 x 2 matrices ?
 
  • #13
dyn said:
Thanks. So as a specific example if I have the Pauli spin matrices from Quantum mechanics. Are they examples of ℂ2 or ℂ2 x 2 matrices ?
They are complex ##2 \times 2 - ##matrices, i.e. elements of ##\mathbb{M}(2,\mathbb{C}) \cong \mathbb{C}^{2 \times 2}## which naturally act on the vector space ##\mathbb{C}^2##.
(There are four complex matrix entries, so they have to "live" in a vector space of four complex dimensions. ##\mathbb{C^2}## has only two.)
 

1. What is the meaning of "ℝm x n" in matrix notation?

In matrix notation, "ℝm x n" refers to a matrix with m rows and n columns, where m and n are both positive integers. This notation is used to indicate the size or dimensions of a matrix.

2. How is matrix notation used to represent vectors?

In matrix notation, a vector is represented as a matrix with either one row or one column. For example, a column vector with three elements would be written as a 3x1 matrix, and a row vector with four elements would be written as a 1x4 matrix.

3. What is the purpose of using matrix notation in mathematics?

Matrix notation is used in mathematics to simplify and generalize the representation of mathematical operations involving multiple variables. It allows for concise and organized notation, making it easier to perform calculations and solve equations.

4. How are vectors and matrices related in matrix notation?

Vectors can be thought of as a special case of matrices, where one dimension is equal to 1. In fact, a 1xN matrix is equivalent to a row vector, and an Nx1 matrix is equivalent to a column vector. Matrices can also be used to perform operations on vectors, such as addition, subtraction, and multiplication.

5. What does the "ℝ" symbol stand for in matrix notation?

The "ℝ" symbol in matrix notation stands for the set of real numbers. This indicates that the elements within the matrix or vector are real numbers, as opposed to complex numbers, which are represented by the symbol "ℂ".

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