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.
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- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Linear subspace of a vector space
Definition
Let be a vector space over a field (Vector space over a field). A subset is a linear subspace of when
- (W1) ;
- (W2) is closed under the vector addition: implies ;
- (W3) is closed under scalar multiplication: and imply .
Every vector space has the two trivial linear subspaces and itself; a linear subspace with is called proper.
The restricted operations are the required data, and is a vector space. By (W2) the vector addition of restricts to a binary operation , and by (W3) the scalar multiplication restricts to a map . With these and the element , the set is a vector space over :
- axioms (V2)–(V5) are equations required of elements of , which are in particular elements of , so they are inherited from ; likewise associativity and commutativity of the restricted addition;
- lies in by (W1) and is a two-sided identity for the restricted addition, since it is one in ;
- for the vector lies in by (W3), and (In any vector space , , , , and forces or ), so and holds in .
So is an abelian group, which is axiom (V1), and is a vector space over whose zero vector and whose additive inverses are those of . In the language of Subgroup, the three displayed conditions (S1) , (S2) closure under addition and (S3) closure under additive inverses all hold, so is a subgroup of the abelian group (Group and abelian group); that reading, and its converse, are recorded as The additive group of a vector space is an abelian group and every linear subspace is a subgroup of it; conversely a subgroup closed under scalar multiplication is a linear subspace and are cited from there rather than re-argued below.
Remarks
-
"Linear subspace", never bare "subspace", in this library. The word subspace is already in use here for the topological notion, a subset of a topological space carrying the induced topology, which is an unrelated idea. The names on this page therefore all say linear:
def-linear-subspace,lem-linear-subspace-criterion,lem-intersection-of-linear-subspaces,lem-linear-subspace-is-a-subgroup,def-sum-of-linear-subspaces. Where the ambient vector space is fixed and no confusion is possible, the surrounding prose still writes the full phrase. -
Closure under negatives is not a fourth condition. It follows from (W3), because the additive inverse of a vector is the scalar multiple . This is why the definition asks for three conditions where the definition of a subgroup asks for three of its own, and why the one-step test (One-step subspace test: a nonempty is a linear subspace if and only if for all and ) can compress them into one.
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(W1) cannot be replaced by "" while dropping the others. It can be replaced by nonemptiness given (W3), since a nonempty closed under scalar multiplication contains (In any vector space , , , , and forces or ) for any of its elements . Stated with (W1) the definition is checkable one condition at a time, and the economical single test is One-step subspace test: a nonempty is a linear subspace if and only if for all and .
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The field matters. A subset of may be closed under the scalars of a subfield without being closed under all of , so "linear subspace" always means "linear subspace over the field named". Restriction of scalars (A field is a vector space over itself, and over any subfield every -vector space is a -vector space by restricting the scalars) is what makes that distinction possible.
Depends on
Used by
- A separable infinite-dimensional Hilbert space is ℓ² Corollary
- Every linear subspace U of a vector space V has a complement: a linear subspace W with V = U ⊕ W Corollary
- Every vector space has a basis Corollary
- If V = ⨁_i<n Uᵢ with every Uᵢ finite-dimensional, then V is finite-dimensional and dim_F V = ∑_i<n dim_F Uᵢ; in particular dim_F(U ⊕ W) = dim_F U + dim_F W Corollary
- Orthonormal eigenbasis for a compact self adjoint operator Corollary
- A compact operator can have nondense range Counterexample
- Compactness is not preserved by strong operator limits Counterexample
- Inside the space of eventually zero families, the linear subspace spanned by { eᵢ : i ≥ 1 } is proper and has a basis equinumerous with a basis of the whole space, so "equal dimension forces equality" fails without finite dimension Counterexample
- The first quadrant of ℝ² contains 0 and is closed under addition and is not a linear subspace, since it is not closed under multiplication by -1 Counterexample
- The standard unit families { eᵢ : i ∈ ℕ } are linearly independent in F^ℕ but do not span it: the constant family 1_F is not a finite linear combination of them Counterexample
- The union of the two coordinate axes of F² is closed under scalar multiplication and is not closed under addition, so neither closure condition implies the other Counterexample
- Three distinct lines U₀, U₁, U₂ in F² have dim_F(U₀+U₁+U₂) = 2 while the inclusion-exclusion analogue of the dimension formula predicts 3, so the two-subspace formula does not extend Counterexample
- Three lines in F² that meet pairwise only in 0 and whose sum is F² with decompositions that are not unique, so pairwise trivial intersection does not give a direct sum Counterexample
- A complemented closed subspace of a normed space Definition
- Affine subspaces as translates x+U of linear subspaces Definition
- Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis Definition
- Continuous annihilator of a linear subspace Definition
- Fredholm operator cokernel and index Definition
- Infinitesimal generator of a unitary group Definition
- Internal direct sum V = ⨁_i<n Uᵢ: the sum is everything and each summand meets the sum of the others only in 0_V Definition
- Lie subalgebras and ideals Definition
- Lie subalgebras, ideals, and center Definition
- Linear combination of a finite list, and the span span(S) as the smallest linear subspace containing S Definition
- Linear hyperplane Definition
- Normed subspace Definition
- Ordered partitions and coordinate parabolics Definition
- Orthogonality and the orthogonal complement Definition
- Orthonormal families, complete orthonormal systems and Hilbert bases Definition
- Spectrum and resolvent of a bounded operator Definition
- Split Banach submanifold Definition
- Subrepresentations, direct sums of representations, and irreducibility Definition
- The annihilator U^∘≤ V^* of U≤ V and the preannihilator ^∘ S≤ V of S≤ V^* Definition
- The fixed subspace V^G of a representation Definition
- The graph of a linear operator with a linear domain Definition
- The Grassmannian of r-dimensional subspaces of a finite-dimensional vector space Definition
- The Hilbert orthogonal projection onto a closed subspace Definition
- The orthogonal complement W^⊥={v:⟨ v,w⟩=0 for all w∈ W} Definition
- The quotient vector space V/W and its canonical projection Definition
- The real dominated-extension principle as an additional hypothesis over ZF Definition
- The subspace Γ of directions along which a series converges absolutely, and its orthogonal complement Γ^⊥ Definition
…and 63 more results.
Dependency tree · two levels
13 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
- Linear subspace (Wikipedia) (standard reference, not scraped)
- S. Axler, Linear Algebra Done Right, 4th ed., Ch. 1 (standard reference, not scraped)