Understanding the Notation of Matrices in Quantum Mechanics

In summary, the conversation discusses the notation of matrices and its relationship with linear operators. The use of the identity operator and the definition of the matrix of a linear operator with respect to an ordered basis are explained. The conversation also mentions the convenience of choosing the same ordered basis for both U and V. Lastly, the importance of understanding this relationship is highlighted, as it is a key factor in matrix multiplication.
  • #1
rsaad
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Homework Statement



The problem is I am unable to understand the proof. I understand how it is done but I do not know how it is related to the theorem. It is probably because I am unable to understand the notation of matrices, the one involving k.
It is given that
I=δ_ij
= 1 0 0...0
0 1 0...0
...0
...1
So now how do I relate k with it?

So before you explain to me what's going on, please elaborate on the notation.
Thank you.
 

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  • #2
If you mean that you don't understand how to go from the first line to the second, all they've done is to insert the identity operator in the form ##1=\sum_k|k\rangle\langle k|##. If you mean that you don't understand how to go from the second row to the third, then you need to learn about the relationship between linear operators and matrices.

Let U and V be vector spaces. Let ##T:U\to V## be linear. Let ##A=(u_1,\dots,u_n)## and ##B=(v_1,\dots,v_m)## be ordered bases for U and V respectively. The matrix [T] of the linear operator T with respect to the pair (A,B) of ordered bases is defined by
$$[T]_{ij}=(Tu_j)_i.$$ The right-hand side is interpreted as "the ith component of the vector ##Tu_j## in the ordered basis B".

You should find it very easy to verify that if B is an orthonormal ordered basis, we have ##[T]_{ij}=\langle v_i,Tu_j\rangle##.

The reason for the definition of [T] can be seen by doing a simple calculation. Suppose that Tx=y. I won't write any summation sigmas, since we can remember to do a sum over each index that appears twice.
$$\begin{align}y &=y_i v_i\\
Tx &= T(x_j u_j)=x_jT(u_j)=x_j(Tu_j)_i v_i.\end{align}$$ Since the v_i are linearly independent, this implies that ##y_i=(Tu_j)_i x_j##. This can be interpreted as a matrix equation [y]=[T][x], if we define [y] and [x] in the obvious ways, and [T] as above. (Recall that the definition of matrix multiplication is ##(AB)_{ij}=A_{ik}B_{kj}##).

When U=V, it's convenient to choose A=B, and we can talk about the matrix of a linear operator with respect to an ordered basis, instead of with respect to a pair of ordered bases.

Notations like [T] are typically only used in explanations like this. I think most books would use T both for the linear operator and the corresponding matrix with respect to a pair of ordered bases.

Edit: It would be a good exercise for you to prove that if ##T:U\to V## and ##S:V\to W## are linear, then ##[S\circ T]=[T]##. This result is the main reason why matrix multiplication is defined the way it is.
 
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1. What are matrices in quantum mechanics?

In quantum mechanics, matrices are mathematical objects used to represent physical observables such as position, momentum, and spin. They are used in the formulation of quantum mechanics to describe the behavior and interactions of particles at a quantum level.

2. How are matrices used in quantum mechanics?

Matrices are used in quantum mechanics to calculate the probabilities of different outcomes of a measurement. They are also used to describe the evolution of a quantum system over time, as well as the relationships between different observables.

3. What is the significance of matrix operations in quantum mechanics?

Matrix operations, such as addition, multiplication, and inversion, play a crucial role in quantum mechanics. They are used to manipulate matrices and obtain new matrices that represent different physical quantities or states of a quantum system.

4. Are there any limitations to using matrices in quantum mechanics?

While matrices are a powerful tool in quantum mechanics, there are some limitations to their use. For example, they can only represent discrete values, which may not accurately reflect the continuous nature of some physical quantities. Additionally, certain quantum systems may require the use of higher-dimensional matrices, which can be computationally challenging.

5. How do matrices in quantum mechanics relate to the concept of superposition?

In quantum mechanics, superposition refers to the ability of a quantum system to exist in multiple states simultaneously. Matrices are used to represent these different states, and the superposition of these states is described by matrix operations. This allows us to calculate the probabilities of different outcomes in a measurement, which can help us understand the behavior of quantum systems.

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