Proof of the Pythagorean theorem in an inner product space
Builds on Inner productNorm induced by an inner productOrthogonal vectors
Proof
We expand the square of the norm with the rules of the inner product.
- Let be an inner product space over or , with inner product . Let with , which means that and are orthogonal.
- For all , conjugate symmetry and linearity in the first argument give .
- By the definition of the induced norm, .
- Linearity in the first argument and step 2 give .
- By conjugate symmetry, . Also by step 1.
- So .
Idea
The square of the norm of a sum expands like the square of a sum of numbers. There are two cross terms, and . Orthogonality makes both cross terms zero, and only the two squares remain.
Reading path
To understand this page from the ground up, read these 7 pages in order. The foundations come first.
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- Vector space definition
- Inner product definition
- Norm definition
- Inner product space definition
- Orthogonal vectors definition
- Norm induced by an inner product definition
- Proof of the Pythagorean theorem in an inner product space proof
Where this leads
55 pages build on this one.
- Distance from a point to a line
- Directrix
- Pythagorean theorem in an inner product space
- Least squares
- Parabola
- Distance from a point to a plane
- Orthogonal projection is the closest point
- Bessel's inequality
- Incentre
- Altitude of a triangle
- Earthquake location problem
- Non-negative least squares
- Hellinger–Reissner principle
- Conjugate residual method
- Full waveform inversion
- Local regression
- Geophysical inversion
- Hilbert–Schmidt expansion theorem
- Minimal residual method
- Moving horizon estimation
- Céa's lemma
- Ordinary least squares
- Proof that the orthogonal projection is the closest point
- Smoothing spline
- Finite element method in structural mechanics
- Lax–Milgram theorem
- Response surface methodology
- Nonlinear regression
- Generalized minimal residual method
- Minimum total potential energy principle
- Data assimilation
- Gauss–Newton algorithm
- Hilbert space adjoint
- Proof of Bessel's inequality
- Proof of the formula for the distance from a point to a line
- Hilbert projection theorem
- Korn's inequality
- Ridge regression
- L-curve
- Proof of the formula for the distance from a point to a plane
- Biconjugate gradient stabilized method
- Galerkin method
- GNSS positioning
- System identification
- Empirical risk minimization
- Isotonic regression
- Bra–ket notation
- Hu–Washizu principle
- Ladyzhenskaya–Babuška–Brezzi condition
- Levenberg–Marquardt algorithm
- Riesz representation theorem
- Box–Jenkins method
- Lasso
- Numerical methods for linear least squares
- Lomb–Scargle periodogram
Further reading
- Web https://linear.axler.net/LADR4e.pdf, Theorem 6.12
About this page
| Tag | 794QRK467A |
|---|---|
| URI | m2://794QRK467A |
| Kind | proof |
| Writing | W0 stub |
| MSC | 46C05 |
| Proves | Pythagorean theorem in an inner product space |
| Uses | Inner product, Norm induced by an inner product, Orthogonal vectors |
| Changed | 4 November 2026 |
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