Scalar (dot) product
The scalar product (or dot product ) of two vectors is a single number that captures how much they align. It is the simplest of the vector products , and arguably the most useful, because it gives you the angle between two vectors and the component of one along another.
Definition
a ⃗ ⋅ b ⃗ = ∣ a ⃗ ∣ ∣ b ⃗ ∣ cos θ , \vec{a} \cdot \vec{b} = |\vec{a}|\,|\vec{b}|\,\cos\theta, a ⋅ b = ∣ a ∣ ∣ b ∣ cos θ ,
where θ ∈ [ 0 , π ] \theta \in [0, \pi] θ ∈ [ 0 , π ] is the angle between a ⃗ \vec{a} a and b ⃗ \vec{b} b (when both are placed with the same tail).
Componentwise formula (in any orthonormal basis i ^ , j ^ , k ^ \hat{i}, \hat{j}, \hat{k} i ^ , j ^ , k ^ ):
a ⃗ ⋅ b ⃗ = a 1 b 1 + a 2 b 2 + a 3 b 3 . \vec{a} \cdot \vec{b} = a_1 b_1 + a_2 b_2 + a_3 b_3. a ⋅ b = a 1 b 1 + a 2 b 2 + a 3 b 3 .
The componentwise formula is defined this way. To show it equals ∣ a ⃗ ∣ ∣ b ⃗ ∣ cos θ |\vec a||\vec b|\cos\theta ∣ a ∣∣ b ∣ cos θ , use the law of cosines on the triangle formed by a ⃗ , b ⃗ , a ⃗ − b ⃗ \vec{a}, \vec{b}, \vec{a} - \vec{b} a , b , a − b :
∣ a ⃗ − b ⃗ ∣ 2 = ∣ a ⃗ ∣ 2 + ∣ b ⃗ ∣ 2 − 2 ∣ a ⃗ ∣ ∣ b ⃗ ∣ cos θ . |\vec{a} - \vec{b}|^2 = |\vec{a}|^2 + |\vec{b}|^2 - 2|\vec{a}||\vec{b}|\cos\theta. ∣ a − b ∣ 2 = ∣ a ∣ 2 + ∣ b ∣ 2 − 2∣ a ∣∣ b ∣ cos θ .
Expand the left side componentwise: ∣ a ⃗ − b ⃗ ∣ 2 = ( a 1 − b 1 ) 2 + ⋯ = ∣ a ⃗ ∣ 2 + ∣ b ⃗ ∣ 2 − 2 ( a 1 b 1 + a 2 b 2 + a 3 b 3 ) |\vec{a} - \vec{b}|^2 = (a_1 - b_1)^2 + \cdots = |\vec{a}|^2 + |\vec{b}|^2 - 2(a_1 b_1 + a_2 b_2 + a_3 b_3) ∣ a − b ∣ 2 = ( a 1 − b 1 ) 2 + ⋯ = ∣ a ∣ 2 + ∣ b ∣ 2 − 2 ( a 1 b 1 + a 2 b 2 + a 3 b 3 ) . Match coefficients: a 1 b 1 + a 2 b 2 + a 3 b 3 = ∣ a ⃗ ∣ ∣ b ⃗ ∣ cos θ a_1 b_1 + a_2 b_2 + a_3 b_3 = |\vec{a}||\vec{b}|\cos\theta a 1 b 1 + a 2 b 2 + a 3 b 3 = ∣ a ∣∣ b ∣ cos θ .
Key consequences
Perpendicularity test : a ⃗ ⋅ b ⃗ = 0 ⟺ a ⃗ ⊥ b ⃗ \vec{a} \cdot \vec{b} = 0 \iff \vec{a} \perp \vec{b} a ⋅ b = 0 ⟺ a ⊥ b (for non-zero vectors). The reverse is trivial; the forward is from cos 90 ∘ = 0 \cos 90^\circ = 0 cos 9 0 ∘ = 0 .
Magnitude formula : a ⃗ ⋅ a ⃗ = ∣ a ⃗ ∣ 2 \vec{a} \cdot \vec{a} = |\vec{a}|^2 a ⋅ a = ∣ a ∣ 2 .
Angle formula : cos θ = a ⃗ ⋅ b ⃗ ∣ a ⃗ ∣ ∣ b ⃗ ∣ \cos\theta = \dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}||\vec{b}|} cos θ = ∣ a ∣∣ b ∣ a ⋅ b .
Projection of a ⃗ \vec{a} a on b ⃗ \vec{b} b : the (signed) length is a ⃗ ⋅ b ⃗ ∣ b ⃗ ∣ \dfrac{\vec{a}\cdot\vec{b}}{|\vec{b}|} ∣ b ∣ a ⋅ b ; the vector projection is a ⃗ ⋅ b ⃗ ∣ b ⃗ ∣ 2 b ⃗ \dfrac{\vec{a}\cdot\vec{b}}{|\vec{b}|^2}\vec{b} ∣ b ∣ 2 a ⋅ b b .
Component of a ⃗ \vec{a} a along the direction u ^ \hat{u} u ^ (unit vector): a ⃗ ⋅ u ^ \vec{a}\cdot\hat{u} a ⋅ u ^ .
Cauchy-Schwarz : ∣ a ⃗ ⋅ b ⃗ ∣ ≤ ∣ a ⃗ ∣ ∣ b ⃗ ∣ |\vec{a}\cdot\vec{b}| \le |\vec{a}|\,|\vec{b}| ∣ a ⋅ b ∣ ≤ ∣ a ∣ ∣ b ∣ , with equality iff a ⃗ \vec{a} a and b ⃗ \vec{b} b are parallel.
Properties
Commutative : a ⃗ ⋅ b ⃗ = b ⃗ ⋅ a ⃗ \vec{a}\cdot\vec{b} = \vec{b}\cdot\vec{a} a ⋅ b = b ⋅ a .
Distributive : a ⃗ ⋅ ( b ⃗ + c ⃗ ) = a ⃗ ⋅ b ⃗ + a ⃗ ⋅ c ⃗ \vec{a}\cdot(\vec{b} + \vec{c}) = \vec{a}\cdot\vec{b} + \vec{a}\cdot\vec{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c .
Scalar factors come out : ( λ a ⃗ ) ⋅ b ⃗ = λ ( a ⃗ ⋅ b ⃗ ) (\lambda\vec{a})\cdot\vec{b} = \lambda(\vec{a}\cdot\vec{b}) ( λ a ) ⋅ b = λ ( a ⋅ b ) .
Dot products of basis vectors : i ^ ⋅ i ^ = j ^ ⋅ j ^ = k ^ ⋅ k ^ = 1 \hat{i}\cdot\hat{i} = \hat{j}\cdot\hat{j} = \hat{k}\cdot\hat{k} = 1 i ^ ⋅ i ^ = j ^ ⋅ j ^ = k ^ ⋅ k ^ = 1 ; cross-pairs = 0 = 0 = 0 .
Worked examples
Example 1. a ⃗ = 2 i ^ + 3 j ^ − k ^ \vec{a} = 2\hat{i} + 3\hat{j} - \hat{k} a = 2 i ^ + 3 j ^ − k ^ , b ⃗ = − i ^ + 4 j ^ + 2 k ^ \vec{b} = -\hat{i} + 4\hat{j} + 2\hat{k} b = − i ^ + 4 j ^ + 2 k ^ . Find a ⃗ ⋅ b ⃗ \vec{a}\cdot\vec{b} a ⋅ b .
a ⃗ ⋅ b ⃗ = ( 2 ) ( − 1 ) + ( 3 ) ( 4 ) + ( − 1 ) ( 2 ) = − 2 + 12 − 2 = 8 \vec{a}\cdot\vec{b} = (2)(-1) + (3)(4) + (-1)(2) = -2 + 12 - 2 = 8 a ⋅ b = ( 2 ) ( − 1 ) + ( 3 ) ( 4 ) + ( − 1 ) ( 2 ) = − 2 + 12 − 2 = 8 .
Example 2. Find the angle between a ⃗ = i ^ + j ^ \vec{a} = \hat{i} + \hat{j} a = i ^ + j ^ and b ⃗ = i ^ − j ^ \vec{b} = \hat{i} - \hat{j} b = i ^ − j ^ .
a ⃗ ⋅ b ⃗ = 1 − 1 = 0 \vec{a}\cdot\vec{b} = 1 - 1 = 0 a ⋅ b = 1 − 1 = 0 . So θ = π / 2 \theta = \pi/2 θ = π /2 (perpendicular).
Example 3. a ⃗ = 3 i ^ − 4 j ^ + 0 k ^ \vec{a} = 3\hat{i} - 4\hat{j} + 0\hat{k} a = 3 i ^ − 4 j ^ + 0 k ^ and b ⃗ = − 2 j ^ + k ^ \vec{b} = -2\hat{j} + \hat{k} b = − 2 j ^ + k ^ . Find the angle.
∣ a ⃗ ∣ = 5 |\vec{a}| = 5 ∣ a ∣ = 5 , ∣ b ⃗ ∣ = 5 |\vec{b}| = \sqrt{5} ∣ b ∣ = 5 . a ⃗ ⋅ b ⃗ = 0 ⋅ 0 + ( − 4 ) ( − 2 ) + 0 ⋅ 1 = 8 \vec{a}\cdot\vec{b} = 0 \cdot 0 + (-4)(-2) + 0 \cdot 1 = 8 a ⋅ b = 0 ⋅ 0 + ( − 4 ) ( − 2 ) + 0 ⋅ 1 = 8 . So cos θ = 8 5 5 = 8 5 5 \cos\theta = \dfrac{8}{5\sqrt 5} = \dfrac{8}{5\sqrt 5} cos θ = 5 5 8 = 5 5 8 . (Approximately 0.7155 0.7155 0.7155 , θ ≈ 44.4 ∘ \theta \approx 44.4^\circ θ ≈ 44. 4 ∘ .)
Example 4. Find the projection of a ⃗ = 2 i ^ + 3 j ^ + 2 k ^ \vec{a} = 2\hat{i} + 3\hat{j} + 2\hat{k} a = 2 i ^ + 3 j ^ + 2 k ^ on b ⃗ = i ^ + 2 j ^ + k ^ \vec{b} = \hat{i} + 2\hat{j} + \hat{k} b = i ^ + 2 j ^ + k ^ .
a ⃗ ⋅ b ⃗ = 2 + 6 + 2 = 10 \vec{a}\cdot\vec{b} = 2 + 6 + 2 = 10 a ⋅ b = 2 + 6 + 2 = 10 . ∣ b ⃗ ∣ = 1 + 4 + 1 = 6 |\vec{b}| = \sqrt{1 + 4 + 1} = \sqrt{6} ∣ b ∣ = 1 + 4 + 1 = 6 . Projection length: 10 6 \dfrac{10}{\sqrt 6} 6 10 .
Example 5. Find λ \lambda λ so that a ⃗ = 2 i ^ + λ j ^ + k ^ \vec{a} = 2\hat{i} + \lambda\hat{j} + \hat{k} a = 2 i ^ + λ j ^ + k ^ is perpendicular to b ⃗ = i ^ + 2 j ^ + 3 k ^ \vec{b} = \hat{i} + 2\hat{j} + 3\hat{k} b = i ^ + 2 j ^ + 3 k ^ .
a ⃗ ⋅ b ⃗ = 2 + 2 λ + 3 = 0 \vec{a}\cdot\vec{b} = 2 + 2\lambda + 3 = 0 a ⋅ b = 2 + 2 λ + 3 = 0 , so λ = − 5 / 2 \lambda = -5/2 λ = − 5/2 .
Example 6. Show that a ⃗ + b ⃗ \vec{a} + \vec{b} a + b and a ⃗ − b ⃗ \vec{a} - \vec{b} a − b are perpendicular iff ∣ a ⃗ ∣ = ∣ b ⃗ ∣ |\vec{a}| = |\vec{b}| ∣ a ∣ = ∣ b ∣ .
( a ⃗ + b ⃗ ) ⋅ ( a ⃗ − b ⃗ ) = a ⃗ ⋅ a ⃗ − a ⃗ ⋅ b ⃗ + b ⃗ ⋅ a ⃗ − b ⃗ ⋅ b ⃗ = ∣ a ⃗ ∣ 2 − ∣ b ⃗ ∣ 2 (\vec{a} + \vec{b})\cdot(\vec{a} - \vec{b}) = \vec{a}\cdot\vec{a} - \vec{a}\cdot\vec{b} + \vec{b}\cdot\vec{a} - \vec{b}\cdot\vec{b} = |\vec{a}|^2 - |\vec{b}|^2 ( a + b ) ⋅ ( a − b ) = a ⋅ a − a ⋅ b + b ⋅ a − b ⋅ b = ∣ a ∣ 2 − ∣ b ∣ 2 . This is zero iff ∣ a ⃗ ∣ = ∣ b ⃗ ∣ |\vec{a}| = |\vec{b}| ∣ a ∣ = ∣ b ∣ . (Geometrically: the diagonals of a rhombus are perpendicular.)
Try it yourself
a ⃗ = i ^ − j ^ \vec{a} = \hat{i} - \hat{j} a = i ^ − j ^ , b ⃗ = i ^ + j ^ \vec{b} = \hat{i} + \hat{j} b = i ^ + j ^ . Find a ⃗ ⋅ b ⃗ \vec{a}\cdot\vec{b} a ⋅ b .
Find the angle between a ⃗ = 2 i ^ + 2 j ^ + k ^ \vec{a} = 2\hat{i} + 2\hat{j} + \hat{k} a = 2 i ^ + 2 j ^ + k ^ and b ⃗ = i ^ − j ^ + k ^ \vec{b} = \hat{i} - \hat{j} + \hat{k} b = i ^ − j ^ + k ^ .
If a ⃗ ⋅ b ⃗ = 0 \vec{a}\cdot\vec{b} = 0 a ⋅ b = 0 and neither vector is zero, what is the angle between them?
Find λ \lambda λ if i ^ + j ^ − k ^ \hat{i} + \hat{j} - \hat{k} i ^ + j ^ − k ^ is perpendicular to 2 i ^ + λ j ^ + k ^ 2\hat{i} + \lambda\hat{j} + \hat{k} 2 i ^ + λ j ^ + k ^ .
Find the projection of a ⃗ = 7 i ^ + j ^ − 4 k ^ \vec{a} = 7\hat{i} + \hat{j} - 4\hat{k} a = 7 i ^ + j ^ − 4 k ^ on b ⃗ = 2 i ^ + 6 j ^ + 3 k ^ \vec{b} = 2\hat{i} + 6\hat{j} + 3\hat{k} b = 2 i ^ + 6 j ^ + 3 k ^ .
If ∣ a ⃗ ∣ = 3 |\vec{a}| = 3 ∣ a ∣ = 3 , ∣ b ⃗ ∣ = 4 |\vec{b}| = 4 ∣ b ∣ = 4 , and the angle between them is 60 ∘ 60^\circ 6 0 ∘ , find a ⃗ ⋅ b ⃗ \vec{a}\cdot\vec{b} a ⋅ b .
If ∣ a ⃗ + b ⃗ ∣ 2 = ∣ a ⃗ ∣ 2 + ∣ b ⃗ ∣ 2 |\vec{a} + \vec{b}|^2 = |\vec{a}|^2 + |\vec{b}|^2 ∣ a + b ∣ 2 = ∣ a ∣ 2 + ∣ b ∣ 2 , what is the angle between a ⃗ \vec{a} a and b ⃗ \vec{b} b ?
Show that the diagonals of a square are perpendicular.
Show that for any vectors a ⃗ , b ⃗ , c ⃗ \vec{a}, \vec{b}, \vec{c} a , b , c : a ⃗ ⋅ ( b ⃗ + c ⃗ ) = a ⃗ ⋅ b ⃗ + a ⃗ ⋅ c ⃗ \vec{a}\cdot(\vec{b}+\vec{c}) = \vec{a}\cdot\vec{b} + \vec{a}\cdot\vec{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c .
Find ∣ a ⃗ − b ⃗ ∣ |\vec{a} - \vec{b}| ∣ a − b ∣ if ∣ a ⃗ ∣ = 5 |\vec{a}| = 5 ∣ a ∣ = 5 , ∣ b ⃗ ∣ = 6 |\vec{b}| = 6 ∣ b ∣ = 6 , angle between them θ \theta θ with cos θ = 1 / 3 \cos\theta = 1/3 cos θ = 1/3 .
Find a unit vector perpendicular to both i ^ + j ^ \hat{i} + \hat{j} i ^ + j ^ and j ^ + k ^ \hat{j} + \hat{k} j ^ + k ^ . (Try: a vector r ⃗ = a i ^ + b j ^ + c k ^ \vec{r} = a\hat{i} + b\hat{j} + c\hat{k} r = a i ^ + b j ^ + c k ^ with r ⃗ ⋅ \vec{r}\cdot r ⋅ each = 0 = 0 = 0 .)
Show ( a ⃗ ⋅ b ⃗ ) 2 ≤ ∣ a ⃗ ∣ 2 ∣ b ⃗ ∣ 2 (\vec{a} \cdot \vec{b})^2 \le |\vec{a}|^2 |\vec{b}|^2 ( a ⋅ b ) 2 ≤ ∣ a ∣ 2 ∣ b ∣ 2 (Cauchy-Schwarz).
The work done by a force F ⃗ = 3 i ^ − j ^ + 2 k ^ \vec{F} = 3\hat{i} - \hat{j} + 2\hat{k} F = 3 i ^ − j ^ + 2 k ^ moving a particle by d ⃗ = i ^ + 2 j ^ − 3 k ^ \vec{d} = \hat{i} + 2\hat{j} - 3\hat{k} d = i ^ + 2 j ^ − 3 k ^ .
The cosine of the angle between the diagonals of the cube 0 ≤ x , y , z ≤ 1 0 \le x, y, z \le 1 0 ≤ x , y , z ≤ 1 .
Pitfalls and tricks
Dot product is a scalar. Don't write a ⃗ ⋅ b ⃗ \vec{a}\cdot\vec{b} a ⋅ b as a vector.
Use the angle formula in geometric problems where the angle matters.
Use the componentwise formula when you have coordinates , it's the fastest path.
Projection has a sign. Negative projection means a ⃗ \vec{a} a points opposite to b ⃗ \vec{b} b .
Test perpendicularity via a ⃗ ⋅ b ⃗ = 0 \vec{a}\cdot\vec{b} = 0 a ⋅ b = 0 , far cleaner than computing angles.