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8.2 Coordinate Operations of Vectors

Key Takeaways

  • In an orthonormal coordinate system with standard basis (i⃗,j⃗)(\vec{i}, \vec{j}), any vector a⃗=xi⃗+yj⃗\vec{a} = x\vec{i} + y\vec{j} is uniquely identified by the ordered pair (x,y)(x, y).

  • Vector addition, subtraction, and scalar multiplication correspond to component-wise algebraic operations: a⃗±b⃗=(x1±x2,y1±y2)\vec{a} \pm \vec{b} = (x_1 \pm x_2, y_1 \pm y_2) and λa⃗=(λx,λy)\lambda \vec{a} = (\lambda x, \lambda y).

  • The coordinate criterion for vector parallelism (collinearity) is x1y2−x2y1=0x_1 y_2 - x_2 y_1 = 0, derived from cross-multiplying proportional components.

  • Directed line segment AB⃗\vec{AB} from A(x1,y1)A(x_1, y_1) to B(x2,y2)B(x_2, y_2) has coordinates (x2−x1,y2−y1)(x_2 - x_1, y_2 - y_1), with magnitude ∣AB⃗∣=(x2−x1)2+(y2−y1)2|\vec{AB}| = \sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2}.

  • The section formula locates point PP dividing segment ABAB in ratio λ\lambda (AP⃗=λPB⃗\vec{AP} = \lambda \vec{PB}) at P(x1+λx21+λ,y1+λy21+λ)P\left(\frac{x_1 + \lambda x_2}{1 + \lambda}, \frac{y_1 + \lambda y_2}{1 + \lambda}\right), specializing to the midpoint formula when λ=1\lambda = 1.

Last updated: July 2026

8.2 Coordinate Operations of Vectors

Coordinate operations translate geometric vector concepts into algebraic manipulations. By choosing an orthogonal coordinate system, plane vector operations reduce to arithmetic on component pairs, transforming complex geometric proofs into linear algebraic computations.


1. Cartesian Coordinate System and Vector Coordinates

1.1 Orthonormal Basis

In a Cartesian coordinate system OxyOxy, let i⃗\vec{i} and j⃗\vec{j} denote the unit vectors along the positive xx-axis and positive yy-axis, respectively:

  • ∣i⃗∣=1|\vec{i}| = 1, ∣j⃗∣=1|\vec{j}| = 1, and i⃗⊥j⃗\vec{i} \perp \vec{j}.
  • The set {i⃗,j⃗}\{\vec{i}, \vec{j}\} forms a standard orthonormal basis for the plane.

1.2 Vector Coordinate Representation

By the Fundamental Theorem of Plane Vectors, any vector a⃗\vec{a} in the plane can be uniquely expressed as:

a⃗=xi⃗+yj⃗\vec{a} = x\vec{i} + y\vec{j}

The ordered pair of real numbers (x,y)(x, y) is called the coordinate representation of vector a⃗\vec{a}, written as a⃗=(x,y)\vec{a} = (x, y).

  • xx is the xx-component (horizontal projection).
  • yy is the yy-component (vertical projection).
  • The origin position vector OP⃗\vec{OP} corresponding to point P(x,y)P(x, y) has coordinates OP⃗=(x,y)\vec{OP} = (x, y).

1.3 Segment Vector Coordinates

Given initial point A(x1,y1)A(x_1, y_1) and terminal point B(x2,y2)B(x_2, y_2), the vector AB⃗\vec{AB} is computed as terminal point coordinates minus initial point coordinates:

AB⃗=OB⃗−OA⃗=(x2,y2)−(x1,y1)=(x2−x1,y2−y1)\vec{AB} = \vec{OB} - \vec{OA} = (x_2, y_2) - (x_1, y_1) = (x_2 - x_1, y_2 - y_1)

Vector Magnitude in Coordinates

The magnitude of vector a⃗=(x,y)\vec{a} = (x, y) is given by the Pythagorean formula:

∣a⃗∣=x2+y2|\vec{a}| = \sqrt{x^2 + y^2}

For directed segment AB⃗\vec{AB} with endpoints A(x1,y1)A(x_1, y_1) and B(x2,y2)B(x_2, y_2):

∣AB⃗∣=(x2−x1)2+(y2−y1)2|\vec{AB}| = \sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2}

2. Algebraic Operations in Coordinate Form

Let a⃗=(x1,y1)\vec{a} = (x_1, y_1), b⃗=(x2,y2)\vec{b} = (x_2, y_2), and scalar λ∈R\lambda \in \mathbb{R}.

OperationGeometric ConceptCoordinate Formula
Additiona⃗+b⃗\vec{a} + \vec{b}(x1+x2,y1+y2)(x_1 + x_2, y_1 + y_2)
Subtractiona⃗−b⃗\vec{a} - \vec{b}(x1−x2,y1−y2)(x_1 - x_2, y_1 - y_2)
Scalar Multiplicationλa⃗\lambda \vec{a}(λx1,λy1)(\lambda x_1, \lambda y_1)
Linear Combinationαa⃗+βb⃗\alpha \vec{a} + \beta \vec{b}(αx1+βx2,αy1+βy2)(\alpha x_1 + \beta x_2, \alpha y_1 + \beta y_2)

3. Coordinate Criterion for Parallel (Collinear) Vectors

Theorem (Coordinate Parallelism Criterion): Let a⃗=(x1,y1)\vec{a} = (x_1, y_1) and b⃗=(x2,y2)\vec{b} = (x_2, y_2). The vectors a⃗\vec{a} and b⃗\vec{b} are parallel (a⃗∥b⃗\vec{a} \parallel \vec{b}) if and only if:

x1y2−x2y1=0x_1 y_2 - x_2 y_1 = 0

Derivation:

  1. If a⃗=0⃗=(0,0)\vec{a} = \vec{0} = (0,0), then 0⋅y2−x2⋅0=00 \cdot y_2 - x_2 \cdot 0 = 0 holds trivially, and 0⃗∥b⃗\vec{0} \parallel \vec{b} is true.
  2. If a⃗≠0⃗\vec{a} \neq \vec{0}, then a⃗∥b⃗  ⟺  ∃λ∈R\vec{a} \parallel \vec{b} \iff \exists \lambda \in \mathbb{R} such that b⃗=λa⃗\vec{b} = \lambda \vec{a}.
  3. In coordinates: (x2,y2)=(λx1,λy1)  ⟹  x2=λx1(x_2, y_2) = (\lambda x_1, \lambda y_1) \implies x_2 = \lambda x_1 and y2=λy1y_2 = \lambda y_1.
  4. Eliminating λ\lambda: x1y2=x1(λy1)=λx1y1=(λx1)y1=x2y1  ⟹  x1y2−x2y1=0x_1 y_2 = x_1 (\lambda y_1) = \lambda x_1 y_1 = (\lambda x_1) y_1 = x_2 y_1 \implies x_1 y_2 - x_2 y_1 = 0

Memory Trick (Cross Multiplication): Multiply the outer components and inner components: Outer−Inner=x1y2−x2y1=0\text{Outer} - \text{Inner} = x_1 y_2 - x_2 y_1 = 0.


4. Division of Line Segments and Centroid Formulas

4.1 Section Formula (Internal/External Division)

Let points A(x1,y1)A(x_1, y_1) and B(x2,y2)B(x_2, y_2) define a segment. If point P(x,y)P(x, y) divides the directed segment ABAB such that AP⃗=λPB⃗\vec{AP} = \lambda \vec{PB} ( λ≠−1 \,\lambda \neq -1\,):

x=x1+λx21+λ,y=y1+λy21+λx = \frac{x_1 + \lambda x_2}{1 + \lambda}, \quad y = \frac{y_1 + \lambda y_2}{1 + \lambda}
  • If λ>0\lambda > 0, PP is an internal division point.
  • If −1<λ<0-1 < \lambda < 0 or λ<−1\lambda < -1, PP is an external division point.

4.2 Midpoint Formula

When λ=1\lambda = 1, PP is the midpoint M(xM,yM)M(x_M, y_M) of ABAB:

xM=x1+x22,yM=y1+y22x_M = \frac{x_1 + x_2}{2}, \quad y_M = \frac{y_1 + y_2}{2}

In vector form: OM⃗=12(OA⃗+OB⃗)\vec{OM} = \frac{1}{2}(\vec{OA} + \vec{OB}).

4.3 Centroid Formula of a Triangle

For △ABC\triangle ABC with vertices A(xA,yA)A(x_A, y_A), B(xB,yB)B(x_B, y_B), C(xC,yC)C(x_C, y_C), the centroid G(xG,yG)G(x_G, y_G) satisfies:

xG=xA+xB+xC3,yG=yA+yB+yC3x_G = \frac{x_A + x_B + x_C}{3}, \quad y_G = \frac{y_A + y_B + y_C}{3}

Vector characteristic equation of centroid GG:

GA⃗+GB⃗+GC⃗=0⃗  ⟺  OG⃗=13(OA⃗+OB⃗+OC⃗)\vec{GA} + \vec{GB} + \vec{GC} = \vec{0} \quad \iff \quad \vec{OG} = \frac{1}{3}(\vec{OA} + \vec{OB} + \vec{OC})

5. Worked Gaokao Exam Examples

Worked Example 1: Parallel Vectors and Parameters

Problem: Given vectors a⃗=(1,m)\vec{a} = (1, m) and b⃗=(m−2,3)\vec{b} = (m - 2, 3) where m∈Rm \in \mathbb{R}.

  1. Find the value(s) of mm such that a⃗∥b⃗\vec{a} \parallel \vec{b}.
  2. For each such mm, determine whether a⃗\vec{a} and b⃗\vec{b} have the same or opposite direction.

Solution:

  1. Apply the coordinate parallelism criterion x1y2−x2y1=0x_1 y_2 - x_2 y_1 = 0: 1⋅3−m(m−2)=0  ⟹  3−m2+2m=0  ⟹  m2−2m−3=01 \cdot 3 - m(m - 2) = 0 \implies 3 - m^2 + 2m = 0 \implies m^2 - 2m - 3 = 0
  2. Factor the quadratic equation: (m−3)(m+1)=0  ⟹  m=3orm=−1(m - 3)(m + 1) = 0 \implies m = 3 \quad \text{or} \quad m = -1
  3. Case 1: m=3m = 3
    • a⃗=(1,3)\vec{a} = (1, 3) and b⃗=(3−2,3)=(1,3)\vec{b} = (3 - 2, 3) = (1, 3).
    • Here b⃗=1⋅a⃗\vec{b} = 1 \cdot \vec{a}, so λ=1>0\lambda = 1 > 0. Vectors a⃗\vec{a} and b⃗\vec{b} are codirectional (same direction).
  4. Case 2: m=−1m = -1
    • a⃗=(1,−1)\vec{a} = (1, -1) and b⃗=(−1−2,3)=(−3,3)\vec{b} = (-1 - 2, 3) = (-3, 3).
    • Here b⃗=−3⋅a⃗\vec{b} = -3 \cdot \vec{a}, so λ=−3<0\lambda = -3 < 0. Vectors a⃗\vec{a} and b⃗\vec{b} are antidirectional (opposite direction).

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Cartesian Vector Coordinates and Parallel Condition
Test Your Knowledge

Given vectors a⃗=(2,−1)\vec{a} = (2, -1) and b⃗=(−4,k)\vec{b} = (-4, k). If a⃗∥b⃗\vec{a} \parallel \vec{b}, what is the value of scalar kk?

A

k=−2k = -2

B

k=−1k = -1

C

k=0k = 0

D

k=2k = 2

Test Your Knowledge

Points A(1,3)A(1, 3) and B(5,−1)B(5, -1) are given in a Cartesian plane. Point PP lies on segment ABAB such that AP⃗=3PB⃗\vec{AP} = 3 \vec{PB}. What are the coordinates of point PP?

A

(3,1)(3, 1)

B

(4,0)(4, 0)

C

(2,2)(2, 2)

D

(72,12)\left(\frac{7}{2}, \frac{1}{2}\right)

Test Your Knowledge

Given vectors a⃗=(1,2)\vec{a} = (1, 2) and b⃗=(−3,1)\vec{b} = (-3, 1), compute the coordinate representation of vector c⃗=2a⃗−3b⃗\vec{c} = 2\vec{a} - 3\vec{b}.

A

(−7,1)(-7, 1)

B

(11,−1)(11, -1)

C

(11,1)(11, 1)

D

(−1,7)(-1, 7)

Sections you finish are checked off in the contents.