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ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28
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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

Let R be the real numbers (The real numbers), a field (The reals form a field), and let R2 be the function space on the von Neumann natural 2={0,1} with the pointwise operations (The vector space FX of all functions X→F with pointwise operations, and Fn as the case X=n={0,1,…,n−1}, The natural numbers N (von Neumann), On N the order is membership: m<n  ⟺  m∈n). We write (y0,y1) for the element y of R2 with y(0)=y0 and y(1)=y1, so that e0=(1,0) and e1=(0,1) are the standard unit vectors (The standard list e:n→Fn with ei(i)=1F and ei(j)=0F for j≠i is an ordered basis of Fn; hence dim⁡FFn=n, and F0 is the zero space with basis ∅ and dimension 0).

Put x:=(1,2) and consider three ordered bases of R2 (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis):

  • e=(e0,e1), the standard ordered basis;
  • e′=(e1,e0), its reversal, which has the same image {e0,e1};
  • v=(v0,v1) with v0:=(1,1) and v1:=(1,0).

Then the coordinate list of x (A finite list v:n→V is an ordered basis if and only if every x∈V equals ∑i<nλivi for exactly one λ:n→F; those scalars are the coordinates of x in that ordered basis) is

(1,2)  in e,(2,1)  in e′,(2,−1)  in v.

Three different lists for one vector, and the first two differ although the two ordered bases have the same image. Coordinates are attached to an ordered basis, not to a basis.

Facts & Assumptions

Given: The field R, the vector space R2 with pointwise operations, the vector x=(1,2), and the three lists e, e′ and v above.

[L1]

FX is a vector space over F with pointwise operations, and two elements are equal exactly when they agree at every point (The vector space FX of all functions X→F with pointwise operations, and Fn as the case X=n={0,1,…,n−1}, Vector space over a field).

[L2]

e:2→R2 is an ordered basis, and (∑i<2λiei)(j)=λj for every λ:2→R and j<2 (The standard list e:n→Fn with ei(i)=1F and ei(j)=0F for j≠i is an ordered basis of Fn; hence dim⁡FFn=n, and F0 is the zero space with basis ∅ and dimension 0, claims 2 and 3).

[L5]

The vector space axioms and the field axioms of R: (V2) λ(y+z)=λy+λz, (V3) (λ+μ)y=λy+μy, (V5) 1y=y; (V,+,0V) is abelian; 0y=0V; and R is a field (Vector space over a field, In any vector space 0Fv=0V, λ0V=0V, (−λ)v=−(λv), (−1F)v=−v, and λv=0V forces λ=0F or v=0V, Field, The reals form a field).

[L6]

Injectivity and images are as in Injection, surjection, bijection.

Verification

technique · direct
1.1

Coordinates in e. By the standard basis lemma, e is an ordered basis of R2 and the coordinate list of y∈R2 is i↦y(i); for x=(1,2) that list is (1,2).

L2L3
1.2

e′ is an ordered basis. The list e′=(e1,e0) is injective, since e0≠e1 (e0 takes the value 1 at 0 and e1 takes the value 0 there), and its image is {e0,e1}=e[2], which is a basis of R2; so e′ is an injective list whose image is a basis.

L1L2L6
1.3

Coordinates in e′. For λ:2→R, ∑i<2λiei′=λ0e1+λ1e0=λ1e0+λ0e1=∑i<2μiei with μ0=λ1 and μ1=λ0; evaluating with the standard basis, this vector is (λ1,λ0). It equals x=(1,2) exactly when λ1=1 and λ0=2, so the coordinate list of x in e′ is (2,1).

L2L4L5
1.4

v is an ordered basis and the coordinates of a general vector in it. Note v0=(1,1)=e0+e1 and v1=(1,0)=e0. For λ:2→R, ∑i<2λivi=λ0(e0+e1)+λ1e0=(λ0e0+λ0e1)+λ1e0=(λ0+λ1)e0+λ0e1, using (V2), (V3) and the abelian group laws; by the standard basis this vector is (λ0+λ1, λ0). Given y=(y0,y1), the equations λ0+λ1=y0 and λ0=y1 have the unique solution λ0=y1, λ1=y0−y1, so every y is ∑i<2λivi for exactly one λ and v is an ordered basis.

L2L3L4L5
2.1

Coordinates of x in v. Taking y=x=(1,2) in step 1.4 gives λ0=2 and λ1=1−2=−1, so the coordinate list of x in v is (2,−1); and 2(1,1)+(−1)(1,0)=(2,2)+(−1,0)=(1,2)=x confirms it.

step 1.4L1L5
3.1

The three coordinate lists of the single vector x are therefore (1,2), (2,1) and (2,−1), computed in steps 1.1, 1.3 and 2.1; the first two are different although e and e′ have the same image, so the coordinate list depends on the ordered basis and not merely on the underlying set.

step 1.1step 1.3step 2.1∎

Remarks

  • What is and is not being said. Uniqueness of the coordinate list (A finite list v:n→V is an ordered basis if and only if every x∈V equals ∑i<nλivi for exactly one λ:n→F; those scalars are the coordinates of x in that ordered basis) is uniqueness for a fixed ordered basis. Nothing there says that different ordered bases give the same list, and this example shows they do not, even when they differ only in the order. Reordering the list permutes the coordinates of every vector at once.

  • The third basis is not a reordering of the first. Its image {(1,1),(1,0)} is a different set from {(1,0),(0,1)}, and its coordinates differ for a further reason: the vectors themselves are different. The passage between coordinate lists of two ordered bases is a change of basis, taken up on a later page once linear maps are available; the point here is only that the two lists differ.

  • The arithmetic was recomputed, not copied. With v0=(1,1) and v1=(1,0), matching (1,2) forces the second coordinate first: λ0 is the second entry, so λ0=2, and then λ1=1−2=−1. Reading the pair off in the other order would give (−1,2), which is wrong.

Depends on

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