Eigenvalues and Phases
Before we can understand quantum phase estimation (QPE), we need a precise answer to a simpler question: what does a unitary operator do to its eigenvectors?
Eigenvalues of unitary operators
Recall that a vector is an eigenvector of an operator with eigenvalue if
For a general matrix the eigenvalue can be any complex number. But unitary operators obey , which places a tight constraint on .
Claim: every eigenvalue of a unitary operator lies on the unit circle of the complex plane, i.e., .
Proof: take the norm of both sides of :
Because is unitary it preserves norms, so . Dividing both sides by gives , hence .
Any complex number with unit modulus can be written as for some real angle . This angle is called the phase of the eigenvalue.
Writing the eigenvalue as a phase
Since every unitary eigenvalue satisfies , we write
The factor of is conventional: it makes a fraction of a full turn, so corresponds to and corresponds to .
The eigenvector equation becomes
The number encodes everything about how acts on its eigenvector: it is a pure rotation of the global phase.
A concrete example: the gate
The gate (also called gate) is defined by
Its eigenvalues are the diagonal entries: (eigenvector ) and (eigenvector ).
For we identify
So the gate imparts a phase of (one-eighth of a full turn) to its eigenvector. QPE can recover this fraction as an ordinary binary number.
Why this matters for algorithms
Many quantum algorithms reduce to estimating the phase of a known unitary applied to one of its eigenvectors. Examples include:
- Shor's algorithm — period-finding is recast as phase estimation of a modular-exponentiation unitary.
- Quantum simulation — simulating a Hamiltonian by running and reading off energy eigenvalues as phases.
- HHL algorithm — solving linear systems via eigenvalue inversion, where eigenvalues are first estimated as phases.
In each case the core question is the same: given and , find such that . The next lessons build the circuit that answers it.
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