Vector ProjectionJEE Main

Shadow of one vector on another — interactive Mathematics simulation for IIT-JEE.

Concept

The projection of a⃗\vec a onto b⃗\vec b is the 'shadow' a⃗\vec a casts along b⃗\vec b. Its signed length is the scalar projection (a⃗⋅b⃗)/∣b⃗∣(\vec a\cdot\vec b)/|\vec b|; multiply by the unit vector b^\hat b to get the vector projection.

Key formula

compb⃗a⃗=a⃗⋅b⃗∣b⃗∣,projb⃗a⃗=a⃗⋅b⃗∣b⃗∣2 b⃗\text{comp}_{\vec b}\vec a = \frac{\vec a\cdot\vec b}{|\vec b|}, \qquad \text{proj}_{\vec b}\vec a = \frac{\vec a\cdot\vec b}{|\vec b|^2}\,\vec b

Derivation

By definition a⃗⋅b⃗=∣a⃗∣∣b⃗∣cos⁡θ\vec a\cdot\vec b = |\vec a||\vec b|\cos\theta, so ∣a⃗∣cos⁡θ=(a⃗⋅b⃗)/∣b⃗∣|\vec a|\cos\theta = (\vec a\cdot\vec b)/|\vec b| is the length of the shadow.

To turn that length into a vector along b⃗\vec b, multiply by b^=b⃗/∣b⃗∣\hat b = \vec b/|\vec b|, giving projb⃗a⃗=a⃗⋅b⃗∣b⃗∣2b⃗\text{proj}_{\vec b}\vec a = \dfrac{\vec a\cdot\vec b}{|\vec b|^2}\vec b.

The leftover a⃗−projb⃗a⃗\vec a - \text{proj}_{\vec b}\vec a is perpendicular to b⃗\vec b — the basis of orthogonal decomposition.

Scenarios to explore

Real-world applications

  • Resolving forces along and perpendicular to a surface.
  • Work done =F⃗⋅d⃗= \vec F\cdot\vec d is force projected on displacement.
  • Gram–Schmidt orthogonalisation and least-squares fitting.

JEE exam tips

  • If a⃗⋅b⃗=0\vec a\cdot\vec b = 0 the vectors are perpendicular and the projection is zero.
  • The component of a⃗\vec a perpendicular to b⃗\vec b has length ∣a⃗∣sin⁡θ|\vec a|\sin\theta.

Common mistakes

  • Dividing by ∣b⃗∣|\vec b| once when the vector projection needs ∣b⃗∣2|\vec b|^2.
  • Reporting the scalar projection as always positive — it carries the sign of cos⁡θ\cos\theta.
  • Projecting onto a⃗\vec a when the question asks for projection onto b⃗\vec b.

Exam traps to avoid

  • Scalar projection is a number (can be negative); vector projection is a vector.
  • Projection onto b⃗\vec b depends only on the direction of b⃗\vec b, not its magnitude.