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Basis Orientation Defined in a Vector Space 📂Geometry

Basis Orientation Defined in a Vector Space

Definition 1

U={u1,,un}V={v1,,vn} U = \left\{ \mathbf{u}_{1}, \cdots, \mathbf{u}_{n} \right\} \\ V = \left\{ \mathbf{v}_{1}, \cdots, \mathbf{v}_{n} \right\} Let U,VU,V be a basis of the vector space XX, and define the matrix (aij)Cn×n\left( a_{ij} \right) \in \mathbb{C}^{n \times n} such that the following equation is satisfied. vj=i=1naijui \mathbf{v}_{j} = \sum_{i=1}^{n} a_{ij} \mathbf{u}_{i} If det(aij)>0\det \left( a_{ij} \right) > 0 then U,VU,V is said to have the same Orientation. If det(aij)<0\det \left( a_{ij} \right) < 0 then they have different orientations.

In particular, in the Euclidean space X=RnX = \mathbb{R}^{n}, orientations have specific names.

  • For R2\mathbb{R}^{2}, the basis {e2,e1}\left\{ \mathbf{e}_{2}, \mathbf{e}_{1} \right\} is in a clockwise direction.
  • For R3\mathbb{R}^{3}, the basis {e1,e2,e3}\left\{ \mathbf{e}_{1}, \mathbf{e}_{2}, \mathbf{e}_{3} \right\} is in a right-hand direction.

  • ek\mathbf{e}_{k} is a unit vector (0,,0,1,0,,0)\left( 0, \cdots , 0, 1, 0 ,\cdots ,0 \right) whose kk-th component is 11 and the rest are 00.

Explanation

Be aware that the two bases are ordered in the definition of orientation. Since orientation is determined by the determinant, changing their order will swap the rows and columns of matrix (aij)\left( a_{ij} \right), causing the sign to accurately flip once each time.

The reason for defining orientation geometrically should not be hard to understand. It’s good to think of it as the direction in which the clock hands move on a 22-dimensional plane R2\mathbb{R}^{2}, and in a 33-dimensional space R3\mathbb{R}^{3}, it resembles the motion of wrapping the right hand inward while lifting the thumb. From 44 dimensions onwards, since these concepts do not apply, there’s no specific name, and it is only possible to evaluate whether the two bases are the same or different.

Example

u1=e1v1=(1,1,0)u2=e2v2=(1,0,1)u3=e3v3=(2,1,3) \begin{align*} \mathbf{u}_{1} =& \mathbf{e}_{1} & \mathbf{v}_{1} =& \left( 1, 1, 0 \right) \\ \mathbf{u}_{2} =& \mathbf{e}_{2} & \mathbf{v}_{2} =& \left( 1, 0, -1 \right) \\ \mathbf{u}_{3} =& \mathbf{e}_{3} & \mathbf{v}_{3} =& \left( 2, 1, 3 \right) \end{align*}

Considering such two bases in R3\mathbb{R}^{3}, v1=(1,1,0)=1e1+1e2+0e3v2=(1,0,1)=1e1+0e21e3v3=(2,1,3)=2e1+1e2+3e3 \begin{align*} \mathbf{v}_{1} = \left( 1, 1, 0 \right) =& 1 \mathbf{e}_{1} + 1 \mathbf{e}_{2} + 0 \mathbf{e}_{3} \\ \mathbf{v}_{2} = \left( 1, 0, -1 \right) =& 1 \mathbf{e}_{1} + 0 \mathbf{e}_{2} - 1 \mathbf{e}_{3} \\ \mathbf{v}_{3} = \left( 2, 1, 3 \right) =& 2 \mathbf{e}_{1} + 1 \mathbf{e}_{2} + 3 \mathbf{e}_{3} \end{align*} the matrix (aij)\left( a_{ij} \right) is defined as [112101013] \begin{bmatrix} 1 & 1 & 2 \\ 1 & 0 & 1 \\ 0 & -1 & 3 \end{bmatrix} and its determinant is det(aij)=1(03(1)1)1(13(1)2)+0(1102)=15+0=4<0 \begin{align*} \det \left( a_{ij} \right) =& 1 \cdot (0 \cdot 3 - (-1)\cdot 1) \\ && - 1 \cdot ( 1 \cdot 3 - (-1) \cdot 2 ) \\ & + 0 \cdot ( 1 \cdot 1 - 0 \cdot 2 ) \\ =& 1 - 5 + 0 \\ =& -4 \\ <& 0 \end{align*} thus, the two bases have different orientations.


  1. Millman. (1977). Elements of Differential Geometry: p6. ↩︎