Special Operators (Unitary/Hermitian/Projection)
Special Operators: Hermitian, Unitary, Projection, Positive
Four families of operators carry all of quantum mechanics. Hermitian operators are observables (and Hamiltonians). Unitary operators are the reversible evolutions and quantum gates. Projection operators are measurements. Positive operators are density matrices and POVM elements. Each is a special case of "normal," so the spectral theorem from 0.1.5 describes them all — we just read off which eigenvalues each allows.
Learning Objectives
After this lesson you will be able to:
- Characterize Hermitian operators (real spectrum) and connect them to observables.
- Prove that unitary operators preserve inner products and have unit-modulus eigenvalues.
- Manipulate orthogonal projection operators and use them for measurement.
- Define positive (semidefinite) operators and recognize density matrices.
- Build functions of operators, especially , linking Hermitian generators to unitary gates.
Intuition
Diagonalize a normal operator (spectral theorem): it's "multiply each eigen-direction by its eigenvalue ." The type of operator is then dictated entirely by where the eigenvalues live:
| Operator | Constraint | Eigenvalues live on… | Role in QM |
|---|---|---|---|
| Hermitian | the real line | observables, Hamiltonians | |
| Unitary | the unit circle | gates, time evolution | |
| Projection | measurement onto a subspace | ||
| Positive | $A^\dagger=A,\ \langle\psi | A | \psi\rangle\ge0$ |
Everything below is making this table precise.
Theory
Hermitian operators
is Hermitian (self-adjoint) if . By the spectral theorem (Hermitian ⇒ normal) it has an orthonormal eigenbasis, and (proved in 0.1.5 E3) its eigenvalues are real. Conversely, a normal operator with real spectrum is Hermitian. So:
This is the measurement postulate's backbone (Term 1.3): an observable is a Hermitian operator, its eigenvalues are the possible measured values, and its eigenvectors are the states of definite value. The expectation value $\langle A\rangle = \langle\psi|A|\psi\rangle = \sum_k \lambda_k |\langle v_k|\psi\rangle|^2$ is a real, probability-weighted average of eigenvalues.
Unitary operators
is unitary if , i.e. .
Theorem. The following are equivalent: (i) is unitary; (ii) preserves inner products, ; (iii) maps an ONB to an ONB; (iv) is normal with all eigenvalues of modulus .
Proof of (i)⇔(ii). , which equals for all iff . (iv): normal gives an orthonormal eigenbasis with ; then $\langle v_k|U^\dagger U|v_k\rangle = |\mu_k|^2 = 1\mu_k = e^{i\theta_k}$. ∎
Preserving inner products means preserving probabilities and normalization — which is precisely why closed-system quantum evolution and every quantum gate must be unitary. Spectral form:
Projection operators
is an orthogonal projector if (idempotent) and (Hermitian). Its eigenvalues are or (0.1.5 E2); it projects onto the subspace along . For an orthonormal set spanning ,
A rank-1 projector (with ) projects onto the line through . Projectors implement projective measurement (Term 1.3): the spectral projectors of an observable give outcome with probability .
Positive (semidefinite) operators
is positive semidefinite () if it is Hermitian and for all ; equivalently, all eigenvalues are . It is positive definite () if strictly . Facts: any is positive; a positive operator has a unique positive square root (take in the spectral form). A density matrix is exactly a positive operator with (Term 1.5), and POVM elements are positive operators summing to (Term 1.3).
Functions of operators and the exponential map
For normal and any , define $f(A) = \sum_k f(\lambda_k)P_k$ (consistent with power series where they converge). The case that powers the whole field:
Hermitian generates unitary. If (Hermitian), then for real ,
is unitary, because each eigenvalue has modulus .
Proof of unitarity. (real ), and . ∎
This is the bridge from physics (Hamiltonians) to computation (gates): every gate for
some Hermitian and "time" . We use it constantly from Term 1.6 onward, and computationally it's
scipy.linalg.expm(-1j*H*t) (Appendix B). Conversely, by Stone's theorem / the matrix log, every
unitary is for some Hermitian .
Caution. only if . In general use Baker–Campbell–Hausdorff (Appendix E); the failure of this identity is exactly why Trotterization is needed for Hamiltonian simulation (Term 3.4).
Polar and singular-value decompositions (brief)
Every operator factors as with and unitary (polar decomposition), and as with diagonal (SVD). We will need the SVD for the Schmidt decomposition of entangled states (Term 1.4) and operator norms; flagged here, developed when needed.
Worked Examples
Example 1 — is Hermitian and unitary; build
has real eigenvalues (Hermitian) and (unitary) — an involution, as in 0.1.4. Using the spectral form $Z = (+1)|0\rangle\langle0| + (-1)|1\rangle\langle1|$:
the -rotation gate (Appendix E). The Hermitian generates the unitary — a concrete instance of the bridge.
Example 2 — A rank-1 projector and an expectation value
For , the projector onto is . Probability of outcome "0" measuring in the computational basis:
And : the outcomes are equally likely, averaging to . Consistent with the Bloch picture of lying on the equator (Term 1.2).
Hands-on (Python)
import numpy as np
from scipy.linalg import expm
def dag(A): return A.conj().T
Z = np.array([[1, 0], [0, -1]], dtype=complex)
def is_hermitian(A): return np.allclose(A, dag(A))
def is_unitary(A): return np.allclose(dag(A) @ A, np.eye(A.shape[0]))
def is_projector(A): return is_hermitian(A) and np.allclose(A @ A, A)
def is_positive(A, tol=1e-12):
w = np.linalg.eigvalsh((A + dag(A)) / 2) # symmetrize for numerical safety
return np.all(w >= -tol)
print(is_hermitian(Z), is_unitary(Z)) # True True (involution)
# Hermitian generates unitary: R_z(θ) = exp(-i θ Z / 2)
theta = 0.9
Rz = expm(-1j * theta * Z / 2)
print(is_unitary(Rz)) # True
print(np.round(Rz, 3)) # diag(e^{-iθ/2}, e^{+iθ/2})# Projector onto |0> and a Born probability for |+>:
ket0 = np.array([1, 0], dtype=complex)
plus = np.array([1, 1], dtype=complex) / np.sqrt(2)
P0 = np.outer(ket0, ket0.conj())
print(is_projector(P0)) # True
print(np.real(plus.conj() @ P0 @ plus)) # 0.5 = Born prob of outcome "0"
# A density matrix is positive with trace 1:
rho = 0.5 * np.eye(2) # maximally mixed qubit
print(is_positive(rho), np.isclose(np.trace(rho), 1)) # True True
# Square root of a positive operator:
A = np.array([[2, 0], [0, 9]], dtype=complex)
sqrtA = expm(0.5 * np.log(2) * np.array([[1,0],[0,0]]) # illustrative; in practice:
) # prefer scipy.linalg.sqrtm
from scipy.linalg import sqrtm
print(np.round(sqrtm(A).real, 3)) # diag(√2, 3)Exercises
E1 (easy). Show that Y = \begin{psmallmatrix}0&-i\\ i&0\end{psmallmatrix} is Hermitian and unitary, and find its eigenvalues.
Solution
Y^\dagger = \overline{Y}^T = \begin{psmallmatrix}0&-i\\ i&0\end{psmallmatrix} = Y (Hermitian). so (unitary). .
E2 (easy). Prove that the product of two unitaries is unitary.
Solution
. ∎ (Hence circuits, which compose gates, are unitary.)
E3 (medium). Let be Hermitian. Prove is unitary directly from $U^\dagger = e^{-iH^\dagger} = e^{-iH}$, and explain where Hermiticity is used.
Solution
Since , . Because and commute, . Hermiticity is what makes the exponent of the negative of that of (so they cancel); for non-Hermitian this fails. ∎
E4 (medium). Show that if is a projector then is a projector, and . Interpret for measurement.
Solution
and , a projector. $P(I-P) = P - P^2 = P - P = 0{P, I-P}$ are complementary outcomes of a yes/no measurement; their probabilities , and a definite outcome lands entirely in one subspace.
E5 (hard). Prove that any positive operator has a unique positive square root, and that for some .
Solution
Spectrally with . Define $\sqrt A = \sum_k\sqrt{\lambda_k}|v_k\rangle\langle v_k|\succeq0(\sqrt A)^2 = A$. Uniqueness among positive roots: any positive with commutes with (since ), hence shares 's eigenbasis, and on each eigenvector must multiply by the nonnegative root — so . Finally with . ∎
Checkpoint
- Where do the eigenvalues of Hermitian, unitary, projection, and positive operators live?
- Prove unitaries preserve inner products and state why that matters physically.
- Give the spectral form of an orthogonal projector and its eigenvalues.
- State the Hermitian-generates-unitary theorem and why it bridges physics and computation.
- When does , and what's the consequence when it fails?
Answers
- Hermitian → ; unitary → unit circle ; projector → ; positive → .
- iff ; preserving overlaps preserves probabilities/normalization, required of valid evolutions and gates.
- over an ONB of the target subspace; eigenvalues and .
- For Hermitian , is unitary; thus every observable/energy generates a valid gate, and every gate is for some Hermitian .
- Only when ; otherwise BCH adds commutator corrections, and Hamiltonian simulation must Trotterize (Term 3.4).
Further Reading
- [NC] Nielsen & Chuang, §2.1.6–2.1.8 — Hermitian/unitary/positive operators, functions of operators, polar/singular decompositions.
- [Axl] Axler, Linear Algebra Done Right, Ch. 7 — self-adjoint, normal, positive operators, isometries.
- [Pre] Preskill, Ph219, Ch. 2–3 — operators and their physical roles.
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