Orthonormal Bases
A basis for a vector space is a set of vectors from which every other vector in that space can be built as a linear combination. The computational basis is the default basis for a single qubit — but it carries an additional structure that makes quantum mechanics work out cleanly: it is orthonormal.
What orthonormality means
A set of vectors is orthonormal when two conditions hold simultaneously:
- Normalization — every vector has unit length. For a ket, this means .
- Orthogonality — distinct vectors in the set are perpendicular. For two different kets and , this means .
Written compactly using the Kronecker delta (which equals 1 when and 0 otherwise), the orthonormality condition for any basis is
Verifying
The column-vector representations are
For real column vectors the inner product is just the dot product, so the four cases are:
All four results match the Kronecker-delta table: the diagonal entries are 1 and the off-diagonal entries are 0. The computational basis is therefore orthonormal.
Why it matters
Orthonormality is not a cosmetic detail — it is what lets the Born rule work. Because , the two measurement outcomes are mutually exclusive: a measurement collapses the state to exactly one of them. Because , the probabilities always sum to one for any normalized . An orthonormal basis turns the abstract formalism into a consistent probability theory.
Try it
Compute all four inner products , , , and return their sum. The orthonormality conditions determine exactly what number you should get.
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