|q⟩ Bad Qubits

intermediate · Physics · Operators, Eigenvalues & Spectral Theorem

Matrix Elements

A linear operator becomes concrete the moment you pick a basis: it turns into a grid of numbers, a matrix. The individual numbers in that grid are called matrix elements, and computing them is the everyday arithmetic of quantum mechanics.

Definition

Let {∣e1⟩,…,∣en⟩}\{|e_1\rangle, \dots, |e_n\rangle\} be an orthonormal basis, so ⟨ei∣ej⟩=δij\langle e_i | e_j\rangle = \delta_{ij}. For a linear operator AA, the matrix element between basis vectors ∣ei⟩|e_i\rangle and ∣ej⟩|e_j\rangle is the complex number

Aij=⟨ei∣A∣ej⟩.A_{ij} = \langle e_i | A | e_j \rangle.

Read it inside out: first AA acts on ∣ej⟩|e_j\rangle to produce a vector A∣ej⟩A|e_j\rangle, then you take the inner product of that vector with ∣ei⟩|e_i\rangle. The result is a single scalar — the entry in row ii, column jj of the matrix of AA.

Why this recovers the whole matrix

Recall from the previous lesson that A∣ej⟩=∑iAij∣ei⟩A|e_j\rangle = \sum_i A_{ij}|e_i\rangle. Take the inner product of both sides with ⟨ei∣\langle e_i| and use orthonormality:

⟨ei∣A∣ej⟩=∑kAkj ⟨ei∣ek⟩=∑kAkj δik=Aij.\langle e_i | A | e_j \rangle = \sum_k A_{kj}\,\langle e_i | e_k\rangle = \sum_k A_{kj}\,\delta_{ik} = A_{ij}.

So the bracket ⟨ei∣A∣ej⟩\langle e_i | A | e_j \rangle is exactly the coefficient AijA_{ij}. Sweeping ii and jj over the basis fills in the entire matrix. The matrix and the operator carry the same information once a basis is fixed.

Reading off the matrix from gate actions

For a qubit with the computational basis {∣0⟩,∣1⟩}\{|0\rangle, |1\rangle\} (with ∣0⟩|0\rangle labeling row/ column 00 and ∣1⟩|1\rangle labeling row/column 11), the three Pauli operators are

X=(0110),Y=(0−ii0),Z=(100−1).X = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}, \quad Y = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix}, \quad Z = \begin{pmatrix} 1 & 0 \\ 0 & -1 \end{pmatrix}.

Take YY. Its defining action is Y∣0⟩=i∣1⟩Y|0\rangle = i|1\rangle and Y∣1⟩=−i∣0⟩Y|1\rangle = -i|0\rangle. To find ⟨0∣Y∣1⟩\langle 0 | Y | 1 \rangle, compute Y∣1⟩=−i∣0⟩Y|1\rangle = -i|0\rangle and then project onto ⟨0∣\langle 0|:

⟨0∣Y∣1⟩=⟨0∣(−i∣0⟩)=−i ⟨0∣0⟩=−i.\langle 0 | Y | 1 \rangle = \langle 0 | (-i|0\rangle) = -i\,\langle 0 | 0\rangle = -i.

That −i-i sits in row 00, column 11 — exactly the top-right entry of the matrix above. Likewise

⟨1∣Y∣0⟩=⟨1∣(i∣1⟩)=i,\langle 1 | Y | 0 \rangle = \langle 1 | (i|1\rangle) = i,

the bottom-left entry. Notice ⟨0∣Y∣1⟩=⟨1∣Y∣0⟩‾\langle 0|Y|1\rangle = \overline{\langle 1|Y|0\rangle}: the off-diagonal elements are complex conjugates of each other. That is the Hermitian symmetry Aij=Aji‾A_{ij} = \overline{A_{ji}}, a property we will study in detail two lessons from now.

A useful sanity check: the trace

The diagonal matrix elements Aii=⟨ei∣A∣ei⟩A_{ii} = \langle e_i | A | e_i\rangle add up to the trace,

Tr⁡(A)=∑i⟨ei∣A∣ei⟩.\operatorname{Tr}(A) = \sum_i \langle e_i | A | e_i \rangle.

Remarkably, the trace does not depend on the chosen orthonormal basis, even though the individual AiiA_{ii} do. For each Pauli matrix above, the two diagonal entries cancel, so Tr⁡(X)=Tr⁡(Y)=Tr⁡(Z)=0\operatorname{Tr}(X) = \operatorname{Tr}(Y) = \operatorname{Tr}(Z) = 0.

Try it

Compute the matrix element ⟨1∣Y∣0⟩\langle 1 | Y | 0 \rangle of the Pauli-YY operator. It is purely imaginary — return its imaginary part as a plain number.

Run your code to see the quantum state.

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