A finite-dimensional Hilbert certificate from one matrix

On this page
  1. Goal and scope
  2. Givens and symbols
  3. Rules and sources
  4. Main derivation
  5. Substeps and lemmas
  6. Reverse audits
  7. Error controls and negative controls
  8. Result and limitations
  9. Verification and source binding

← Guide index · Original MKO

derivation-mko-real-hilbert-space-01 · ocme-new142-reader-adoption-20261021

Goal and scope

Verify the consistent inner product, norm, metric and completeness of R^2 with A=[[2,1],[1,2]].

Only this finite-dimensional real carrier; no infinite-dimensional, compactness or separability claim.

Givens and symbols

  • algebra
  • inner_norm_metric
  • finite_dim_complete
  • G1 — V=R^2, A=[[2,1],[1,2]]; define <x,y>_A=x^T A y and derive both norm and metric from this same inner product.
  • A — fixed positive-definite matrix
  • \|\ \|_A,d_A — matching norm and metric

Rules and sources

  • mko_definition · cited — The carrier, inner product, induced norm, induced metric and completeness certificate must describe the same space. This slice uses named completeness-theorem certificates for finite-dimensional R^n with a standard or positive-definite-matrix inner product. Sampled Cauchy sequences do not establish completeness. · mko-real-hilbert-space
  • algebra · prerequisite — Use real-field identities; division requires a nonzero denominator and multiplication by a positive number preserves inequalities.
  • inner_norm_metric · prerequisite — A positive-definite symmetric bilinear form defines a real inner product; its square-root self-product is a norm, including the triangle inequality, and the difference norm is a metric.
  • finite_dim_complete · prerequisite — Named completeness certificate: every finite-dimensional real inner-product space is complete in the norm and metric induced by that inner product.

Main derivation

S01 · equivalent

Before

x=(x_1,x_2),\ y=(y_1,y_2)

After

\langle x,y\rangle_A=2x_1y_1+x_1y_2+x_2y_1+2x_2y_2

Conditions: none

Rule: algebra · Uses: G1

Leaf basis: algebra

Expand the matrix product, fixing A as the common source of every structure.

S02 · equivalent

Before

\langle ax+bz,y\rangle_A

After

a\langle x,y\rangle_A+b\langle z,y\rangle_A

Conditions: none

Rule: algebra · Uses: S01

Leaf basis: algebra

Distributivity gives real bilinearity termwise; the expanded expression also gives symmetry.

S03 · equivalent

Before

\langle x,x\rangle_A=2x_1^2+2x_1x_2+2x_2^2

After

\langle x,x\rangle_A=(x_1+x_2)^2+x_1^2+x_2^2\ge0

Conditions: none

Rule: algebra · Uses: S01

Leaf basis: algebra

The sum of squares is nonnegative, and equality forces both coordinates zero, proving positive definiteness.

S04 · implies

Before

V=\mathbb R^2,\ \langle\ ,\ \rangle_A\text{ symmetric bilinear positive definite}

After

(V,\langle\ ,\ \rangle_A)\text{ is a real inner-product space}

Conditions: none

Rule: inner_norm_metric · Uses: G1, S02, S03

Leaf basis: inner_norm_metric

All inner-product obligations are met, qualifying the space first.

S05 · theorem_application

Before

\|x\|_A=\sqrt{\langle x,x\rangle_A}

After

\|x\|_A=\sqrt{2x_1^2+2x_1x_2+2x_2^2}

Conditions: none

Rule: inner_norm_metric · Uses: S04

Leaf basis: inner_norm_metric

By the inner-product induced-norm theorem this is a norm, using the nonnegative square root.

S06 · theorem_application

Before

d_A(x,y)=\|x-y\|_A

After

d_A(x,y)=\sqrt{2(x_1-y_1)^2+2(x_1-y_1)(x_2-y_2)+2(x_2-y_2)^2}

Conditions: none

Rule: inner_norm_metric · Uses: S05

Leaf basis: inner_norm_metric

The same norm induces the metric; its norm properties give nonnegativity, separation, symmetry and triangle inequality.

S07 · implies

Before

(x_1+x_2)^2\le2(x_1^2+x_2^2)

After

\|x\|_2^2\le\|x\|_A^2\le3\|x\|_2^2

Conditions: none

Rule: algebra · Uses: S03, S05

Leaf basis: algebra

The upper bound follows from (x_1-x_2)^2≥0 and the lower from the sum of squares, additionally checking the norm binding.

S08 · theorem_application

Before

\dim_{\mathbb R}V=2<\infty

After

(V,\langle\ ,\ \rangle_A,\|\ \|_A,d_A)\text{ is a real Hilbert space}

Conditions: V=\mathbb R^2; A=A^T\text{ positive definite}

Rule: finite_dim_complete · Uses: G1, S04, S05, S06

Leaf basis: finite_dim_complete

Apply the named finite-dimensional real-inner-product completeness theorem: every d_A-Cauchy sequence has a d_A-limit in the same V, which supplies the Hilbert obligation.

Substeps and lemmas

No substeps in this guide.

Reverse audits

  • S08 · premise_audit · G1, S04, S05, S06 — The certificate binds the same carrier, product, norm and metric; sampled Cauchy sequences cannot replace it.
  • S07 · premise_audit · S03, S05 — The bounds hold for all real vectors but imply no unprovided infinite-dimensional result.
  • S06 · premise_audit · S05 — Every difference vector stays in the same V.
  • S05 · premise_audit · S04 — No different matrix or unbound norm may be substituted.
  • S04 · premise_audit · G1, S02, S03 — The carrier remains R^2, not the subset of rational vectors.
  • S03 · inverse_equivalence · S01 — No determinant shortcut or numerical sample replaces the all-x proof.
  • S02 · inverse_equivalence · S01 — a,b are arbitrary real scalars, not sampled integers.
  • S01 · inverse_equivalence · G1 — Swapping x,y preserves the expression, including both cross coefficients.

Error controls and negative controls

Five-way binding

Keep V, A, inner product, norm and metric consistently bound.

Named completeness

Explicitly apply finite-dimensional real-inner-product completeness, not samples.

  • Replacing R^2 by Q^2 permits the same real finite-dimensional theorem. → reject — Q^2 is not a real vector space, so the carrier premise fails.
  • Finitely checking Cauchy sequences proves completeness. → reject — Completeness quantifies over every Cauchy sequence.
  • Hilbert therefore makes this space compact. → reject — No compactness certificate is supplied; R^2 itself is unbounded.

Result and limitations

This R^2, with all structures induced by the same A, is a real Hilbert space; completeness is supplied by the finite-dimensional completeness theorem.

    Verification and source binding

    1 declared checks for this guide; only the listed expressions are covered.

    • source commit: b1b2f1dcf8c50d67a93fe52d95f8eef7b3abba9f
    • adopted source SHA-256: 4930257bba12534036e760dca2b4c1277cdaeb84ac961481c36f384db87a6209
    • original source SHA-256: 1dfb783bf683beff32490fed97cb7f8755ddeca7526828da95db41018e1e36fd
    • Lean: NOT_RUN · independent AI: SCOPED_LEAD_AND_BILINGUAL_CONTEXT_REVIEW

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