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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Linear combination of a finite list, and the span as the smallest linear subspace containing
Definition
Let be a vector space over a field (Vector space over a field).
Finite sums of vectors
By axiom (V1) the triple is an abelian group (Group and abelian group), hence in particular a commutative monoid (Semigroup and monoid). So the finite products of The product of a finite list in a monoid, by recursion, with the empty product () equal to the identity are available in it, and we write them additively: for and a finite list , that is a function on the von Neumann natural (The natural numbers (von Neumann), On the order is membership: ),
so that and , and the value depends only on .
Linear combinations
A linear combination in is a vector of the form
where , is a finite list of scalars and is a finite list of vectors; the sum is the finite sum just described, of the list . For , a vector is a linear combination of elements of when there are , and with .
The empty case is a real case. contains (The natural numbers (von Neumann)), and at the sum is the empty sum, which is . So is a linear combination of elements of every subset of , including . The lists are indexed from , so a linear combination of length is ; no statement here is restricted to .
The span
Let . The set of linear subspaces of containing is nonempty, since itself is one, so its intersection is a linear subspace of by The intersection of a nonempty family of linear subspaces of is a linear subspace of . That intersection is the span of ,
It contains , being an intersection of sets each of which contains , and it is contained in every linear subspace of that contains . So it is the smallest linear subspace of containing , and those two properties determine it uniquely: if and both contain and are each contained in every linear subspace containing , then each is contained in the other. This is what licenses the definite article.
A subset spans , or is a spanning set of , when .
Remarks
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The definition is the one already used for subgroups. The subgroup generated by a subset, the cyclic subgroup , and cyclic groups defines as the intersection of all subgroups containing , licensed by The intersection of a nonempty family of subgroups of is a subgroup of . Its Remarks also record a description from inside, as a set of products, proved there only for a single generator (, and every cyclic group is abelian) with the general case deferred to a later page. The span is defined here in exactly that outside shape, and the identification from inside, that is precisely the set of linear combinations of elements of , is proved in full as is exactly the set of linear combinations of finite lists of elements of , and . In particular is proved there, as a consequence of the definition, and is not stipulated here.
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Why the finite sum is The product of a finite list in a monoid, by recursion, with the empty product () equal to the identity and not Finite sums and finite products, by recursion. The latter is stated for sequences into the complete ordered field, so it cannot carry a sum of vectors in an arbitrary vector space over an arbitrary field. The monoid finite product is defined by recursion in any monoid, its empty value is the identity, and Generalised associativity: in a monoid the product of a finite list does not depend on the bracketing, and in a commutative monoid it does not depend on the order of the factors either supplies the splitting, regrouping and reordering laws for it. Reading it additively in costs nothing and is the only sum of vectors this page uses.
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A linear combination is a value, not an expression. Two different lists may produce the same vector, and nothing above asserts otherwise. Repetitions are allowed in the list , and so are coefficients equal to ; asking when a vector is a linear combination of a set in only one way is the question of linear independence, which belongs to a later page and is not raised here.
Depends on
- Vector space over a field
- Linear subspace of a vector space
- The intersection of a nonempty family of linear subspaces of $V$ is a linear subspace of $V$
- The product $g_0 g_1 \cdots g_{n-1}$ of a finite list in a monoid, by recursion, with the empty product ($n = 0$) equal to the identity
- Semigroup and monoid
- Group and abelian group
- The natural numbers $\mathbb{N}$ (von Neumann)
- On $\mathbb{N}$ the order is membership: $m < n \iff m \in n$
- Field
Used by
- Every linear subspace U of a vector space V has a complement: a linear subspace W with V = U ⊕ W Corollary
- Every spanning subset of a vector space contains a basis Corollary
- Every vector space has a basis Corollary
- If V has a spanning set with n elements, then every linearly independent subset of V is finite with at most n elements; in particular V has no linearly independent subset equinumerous with ℕ Corollary
- {(1,0), (0,1), (1,1)} spans F² and is linearly dependent, so a spanning set need not be a basis; each of its three two-element subsets is a basis 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 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
- Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis Definition
- Finite-dimensional vector space, and its dimension dim_F V; infinite-dimensional means having no finite basis Definition
- Linear independence: a finite list v : n → V is independent when ∑_i<n λᵢ vᵢ = 0_V forces every λᵢ = 0_F, and a subset S ⊆ V is independent when every injective finite list into S is independent Definition
- Row space, column space, nullspace, row rank, column rank and matrix rank Definition
- Series of vectors in ℝⁿ, absolute convergence, rearrangement, and the set of rearrangement sums Definition
- The sum U + W of two linear subspaces and the sum ∑_i<n Uᵢ of a finite family Definition
- An additive f : ℝ → ℝ that is not x ↦ cx: the coefficient of one fixed Hamel basis vector. It is unbounded above and below on every nondegenerate interval, its graph is dense in ℝ², and every nonempty level set is dense in ℝ Example
- F^ℕ is a vector space and the eventually zero families form a linear subspace of it that is the span of the standard unit families Example
- In F³ the three coordinate lines are linear subspaces whose internal direct sum is F³, and F⁰ is the zero space Example
- ℝ as a vector space over ℚ has a basis, and every such basis is infinite; the existence proof exhibits none Example
- Steinitz's confinement bound realised on an explicit list of six unit vectors in ℝ² summing to zero Example
- The standard unit families eₖ ∈ F^ℕ form a basis of the linear subspace of eventually zero families: an explicit infinite basis, built with no choice principle Example
- The vector (1,2) ∈ ℝ² has coordinate list (1,2) in the standard ordered basis, (2,1) in its reversal, and (2,-1) in the ordered basis ((1,1),(1,0)) Example
- Two planes in F³ whose sum is F³ and whose intersection is a line, computed explicitly Example
- FALSE: all norms on a real vector space are equivalent False statement
- FALSE: every additive f : ℝ → ℝ is of the form x ↦ cx for a single real c False statement
- FALSE: The union of two linear subspaces is a linear subspace False statement
- FALSE: the union of two linearly independent subsets of a vector space is linearly independent False statement
- ∑_i<n Uᵢ = span(⋃_i<n Uᵢ), so the sum is the smallest linear subspace containing every Uᵢ Lemma
- A subset S ⊆ V is linearly dependent if and only if some s ∈ S lies in span(S ∖ {s}); and span(S) is already the set of linear combinations of INJECTIVE finite lists into S Lemma
- Assuming the Axiom of Choice, ℝ has a Hamel basis over ℚ: there is B ⊆ ℝ such that every real is a finite ℚ-linear combination of elements of B in exactly one way, and each basis vector carries a well-defined ℚ-linear coefficient map Lemma
- Finite sums re-indexed along an injection, with a zero term deleted, and concatenated; and the closure properties of linear independence: an independent list is injective and never 0_V, its sublists are independent, a list is independent exactly when it is injective with linearly independent image, and every subset of a linearly independent set is linearly independent Lemma
- For B ⊆ V the following are equivalent: B is a basis; B is a maximal linearly independent subset of V; B is a minimal spanning subset of V — maximality and minimality being in the inclusion order Lemma
- For n≥2, the punctured space ℝⁿ∖{0} is polygonally connected Lemma
- If S ⊆ V is linearly independent and w ∉ span(S) then S ∪ {w} is linearly independent and span(S) ⊊ span(S ∪ {w}); and if w ∈ span(S) then span(S ∪ {w}) = span(S) Lemma
- S ⊆ V is linearly independent if and only if every finite subset of S is; consequently the union of a nonempty chain of linearly independent subsets of V, ordered by inclusion, is linearly independent Lemma
- span(S) is exactly the set of linear combinations of finite lists of elements of S, and span(∅) = {0_V} Lemma
- span{v} = { λ v : λ ∈ F }, which is {0_V} when v = 0_V, and when v ≠ 0_V contains 0_V only as the multiple 0_F v Lemma
- The finite and reverse triangle inequalities for a norm; and for n ≥ 1 every norm N on ℝⁿ satisfies N(x) ≤ C‖ x‖₁ and is Lipschitz, hence continuous, for d₂ Lemma
- The span is monotone and idempotent, span(S) = S exactly when S is a linear subspace, and span(S ∪ {0_V}) = span(S) Lemma
…and 8 more results.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 49 results over 17 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Linear span (Wikipedia) (standard reference, not scraped)
- Linear combination (Wikipedia) (standard reference, not scraped)
- S. Axler, Linear Algebra Done Right, 4th ed. (free PDF, CC BY-NC) (standard reference, not scraped)