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.
derivation-mko-real-hilbert-space-01 · ocme-new142-reader-adoption-20261021
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.
algebrainner_norm_metricfinite_dim_completeG1 — 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 metricmko_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-spacealgebra · 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.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.
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.
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.
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.
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.
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.
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.
Before
\dim_{\mathbb R}V=2<\inftyAfter
(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.
No substeps in this guide.
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.Keep V, A, inner product, norm and metric consistently bound.
Explicitly apply finite-dimensional real-inner-product completeness, not samples.
reject — Q^2 is not a real vector space, so the carrier premise fails.reject — Completeness quantifies over every Cauchy sequence.reject — No compactness certificate is supplied; R^2 itself is unbounded.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.
1 declared checks for this guide; only the listed expressions are covered.
b1b2f1dcf8c50d67a93fe52d95f8eef7b3abba9f4930257bba12534036e760dca2b4c1277cdaeb84ac961481c36f384db87a62091dfb783bf683beff32490fed97cb7f8755ddeca7526828da95db41018e1e36fdSCOPED_LEAD_AND_BILINGUAL_CONTEXT_REVIEWSame-source full JSON (formulas, ASTs, controls and revision log)