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The span is monotone and idempotent, exactly when is a linear subspace, and
Statement
Let be a vector space over a field (Vector space over a field) and let . Then:
- Extensive. .
- Monotone. If then .
- Idempotent. .
- if and only if is a linear subspace of (Linear subspace of a vector space).
- .
Facts & Assumptions
Given: A field , a vector space over , and subsets .
is a linear subspace of , it contains , and it is contained in every linear subspace of that contains ; the same holds with or any other subset in place of (Linear combination of a finite list, and the span as the smallest linear subspace containing ).
Every linear subspace of contains , by condition (W1) (Linear subspace of a vector space).
Proof
Claim 1 is part of the defining description of the span: it contains .
Claim 2. Suppose . Then is a linear subspace of containing , hence containing ; since is contained in every linear subspace containing , we get .
If is a linear subspace of , then is itself a linear subspace containing , so ; together with this gives .
Conversely, if then is a linear subspace of , because is one.
, since is a linear subspace of .
Steps 1.3 and 1.4 together are claim 4.
Claim 5. From and step 1.2 we get . Conversely by step 1.1 and by step 1.5, so , and since is a linear subspace containing , minimality gives .
Claim 3. The set is a linear subspace of , so applying claim 4 to it gives .
Claims 1, 2, 3, 4 and 5 are steps 1.1, 1.2, 3.1, 2.1 and 2.2 respectively.
Remarks
-
These three properties are exactly what makes the span a closure operator on the subsets of : extensive, monotone and idempotent. The closed sets of that operator are the linear subspaces, which is the content of claim 4. The subgroup generated by a subset (The subgroup generated by a subset, the cyclic subgroup , and cyclic groups) is the closure operator of the same shape on the subsets of a group.
-
Claim 5 says is invisible to the span. Adding or deleting the zero vector changes nothing, since every linear subspace contains it. It does not follow, and is not claimed here, that deleting any other single vector changes nothing: that question is about linear independence and belongs to a later page.
-
Claim 2 is used constantly in the form "a bigger set spans more". It is what lets a spanning set be enlarged freely, and, with claim 3, what lets the span be computed in stages: spanning a set, then spanning the result, gains nothing.
Depends on
Used by
- 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
- {(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
- 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
- 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
- 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
- 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
- If dim_F V = n and U is a linear subspace of V, then U is finite-dimensional, dim_F U ≤ n, and dim_F U = n if and only if U = V Theorem
- The dimension formula: for finite-dimensional linear subspaces U and W of V, the subspaces U + W and U ∩ W are finite-dimensional and dim_F(U+W) + dim_F(U ∩ W) = dim_F U + dim_F W Theorem
- The Steinitz exchange lemma: if L ⊆ V is linearly independent and S ⊆ V spans V with S finite of size n, then L is finite with |L| = m ≤ n, and there is T ⊆ S of size n - m such that L ∪ T spans V Theorem
- Zorn's lemma gives a basis between any linearly independent set and any spanning set containing it: if L ⊆ S ⊆ V with L independent and span(S) = V, there is a basis B of V with L ⊆ B ⊆ S Theorem
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 37 results over 16 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)
- Closure operator (Wikipedia) (standard reference, not scraped)