How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
For same-sized finite square matrices over a commutative ring,
Statement
For and over a commutative ring,
Facts & Assumptions
Given: A fixed matrix and a variable matrix .
Determinant is the unique normalized alternating column-multilinear matrix function (The determinant is the unique normalized alternating multilinear function on the columns).
Every alternating column-multilinear satisfies (Every alternating multilinear satisfies ).
Matrix multiplication is associative, distributive and unital (Matrix arithmetic over a commutative ring is associative, unital and distributive, and transpose reverses products).
Determinant is defined for every square matrix over the commutative ring (For , the determinant over a commutative ring by the Leibniz formula, and for a real matrix).
Proof
Define . Each column of is times the corresponding column of , so distributivity makes column-multilinear; equal columns of give equal columns of , so is alternating.
Since , one has .
Apply [L2] to : . Neither matrix was assumed invertible.
Depends on
- The determinant is the unique normalized alternating multilinear function on the columns
- Every alternating multilinear $F$ satisfies $F(A)=F(I)\sum_{\sigma\in S_n}\operatorname{sgn}(\sigma)\prod_i a_{\sigma(i),i}$
- Matrix arithmetic over a commutative ring is associative, unital and distributive, and transpose reverses products
- For $n\ge1$, the determinant over a commutative ring by the Leibniz formula, and $|\det A|$ for a real matrix
Used by
- An invertible square matrix over a commutative ring has unit determinant Corollary
- If A is invertible over a commutative ring, then det(A⁻¹)=det(A)⁻¹ Corollary
- Similar matrices over a commutative ring have the same determinant Corollary
- The complex Jacobian determinant of a composite of equidimensional holomorphic maps is the product Corollary
- The index of a full-rank subgroup of ℤⁿ is the absolute determinant of a generating matrix Corollary
- Orientation of a finite-dimensional real vector space Definition
- For n≥ 1, determinant is a natural transformation det:GLₙ(-)⟹(-)^× from commutative rings to groups Example
- Spectrum in a finite-dimensional matrix algebra Example
- The hyperspherical-coordinate Jacobian is the standard product of a radial power and sine powers Example
- The kernel and image of the determinant homomorphism Example
- The special linear group is a codimension-one embedded submanifold Example
- Chart and partition independence of surface measure Lemma
- For symmetric M=beginpmatrixA&BB^T&C endpmatrix with A invertible, a block-unitriangular congruence gives A⊕(C-B^TA⁻¹B) and factors det M Lemma
- Smooth orientation sign is the local integral homology multiplier Lemma
- The quaternion double cover generates the third homotopy group of SO(3) Lemma
- The real Jacobian determinant of a complex-linear automorphism is the squared modulus of its complex determinant Lemma
- A Gram determinant is nonnegative and is positive exactly when the vector list is linearly independent Theorem
- A linear map T of ℝⁿ sends Lebesgue measurable sets to Lebesgue measurable sets, with λₙ(T[E])=|det T| λₙ(E) when T is invertible and T[E] Lebesgue null when it is not Theorem
- A matrix admits a Cholesky factorisation with positive diagonal exactly when it is Hermitian positive definite, and that factor is unique Theorem
- A square matrix has an unpivoted unit-lower LU factorisation exactly when all leading principal minors are nonzero Theorem
- Change of variables for an injective C¹ map on a compact Jordan set Theorem
- For A,B∈ Mₙ(F), the products AB and BA have the same characteristic polynomial Theorem
- Norm is multiplicative, trace is F-linear, and both are transitive in towers Theorem
- Similar matrices have the same characteristic polynomial Theorem
- Sylvester's criterion: a real symmetric n× n matrix with n≥1 is positive definite if and only if all leading principal minors are positive Theorem
Dependency tree · two levels
22 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- S. New, MATH 146 Linear Algebra 1 Lecture Notes, Theorem 4.24 (standard reference, not scraped)
- P. Massot, Structures algébriques fondamentales, Lemma 6.4.2 (standard reference, not scraped)