Skip to content

Mathematics · Ch 6 — Line and Plane

Coplanarity of Two Lines

6.6

Coplanarity of Two Lines

Two lines in space may or may not lie in a common plane. Parallel lines always do — any two parallel lines determine a plane between them. The interesting case is a pair of non-parallel lines: such lines are coplanar precisely when the shortest distance between them is zero (if it were positive, the lines would be skew, passing each other in different planes without ever meeting). This gives a clean test: two non-parallel lines r⃗=a⃗1+λ1b⃗1\vec r=\vec a_1+\lambda_1\vec b_1 and r⃗=a⃗2+λ2b⃗2\vec r=\vec a_2+\lambda_2\vec b_2 are coplanar if and only if

(a⃗2−a⃗1)⋅(b⃗1×b⃗2)=0.(\vec a_2-\vec a_1)\cdot(\vec b_1\times\vec b_2)=0.

When this holds, the common plane can be pinned down immediately: it passes through the point A(a⃗1)A(\vec a_1), and since both b⃗1\vec b_1 and b⃗2\vec b_2 lie in the plane, their cross product b⃗1×b⃗2\vec b_1\times\vec b_2 must be normal to it. So the plane's equation is

(r⃗−a⃗1)⋅(b⃗1×b⃗2)=0.(\vec r-\vec a_1)\cdot(\vec b_1\times\vec b_2)=0.

In Cartesian form, for lines x−x1a1=y−y1b1=z−z1c1\dfrac{x-x_1}{a_1}=\dfrac{y-y_1}{b_1}=\dfrac{z-z_1}{c_1} and x−x2a2=y−y2b2=z−z2c2\dfrac{x-x_2}{a_2}=\dfrac{y-y_2}{b_2}=\dfrac{z-z_2}{c_2}, the same idea becomes a 3×33\times3 determinant test:

∣x2−x1y2−y1z2−z1a1b1c1a2b2c2∣=0,\begin{vmatrix}x_2-x_1 & y_2-y_1 & z_2-z_1\\ a_1 & b_1 & c_1\\ a_2 & b_2 & c_2\end{vmatrix}=0,

and the plane determined by the two lines is

∣x−x1y−y1z−z1a1b1c1a2b2c2∣=0.\begin{vmatrix}x-x_1 & y-y_1 & z-z_1\\ a_1 & b_1 & c_1\\ a_2 & b_2 & c_2\end{vmatrix}=0.

Worked example. Show that the lines r⃗=(i^+j^−k^)+λ(2i^−2j^+k^)\vec r=(\hat i+\hat j-\hat k)+\lambda(2\hat i-2\hat j+\hat k) and r⃗=(4i^−3j^+2k^)+μ(i^−2j^+2k^)\vec r=(4\hat i-3\hat j+2\hat k)+\mu(\hat i-2\hat j+2\hat k) are coplanar, and find the plane they determine.

Here a⃗1=i^+j^−k^\vec a_1=\hat i+\hat j-\hat k, a⃗2=4i^−3j^+2k^\vec a_2=4\hat i-3\hat j+2\hat k, b⃗1=2i^−2j^+k^\vec b_1=2\hat i-2\hat j+\hat k, b⃗2=i^−2j^+2k^\vec b_2=\hat i-2\hat j+2\hat k, so a⃗2−a⃗1=3i^−4j^+3k^\vec a_2-\vec a_1=3\hat i-4\hat j+3\hat k.

(a⃗2−a⃗1)⋅(b⃗1×b⃗2)=∣3−432−211−22∣=3(−4+2)−(−4)(4−1)+3(−4+2)=−6+12−6=0,(\vec a_2-\vec a_1)\cdot(\vec b_1\times\vec b_2)=\begin{vmatrix}3&-4&3\\2&-2&1\\1&-2&2\end{vmatrix}=3(-4+2)-(-4)(4-1)+3(-4+2)=-6+12-6=0, …