Related Formula
Cauchy-Schwarz Inequality for vectors:
( c · d)² ≤ | cyz|² | d|²$$(\vec{c} \cdot \vec{d})^2 \le |\vec{c}_{yz}|^2 |\vec{d}|^2$$
Core Logic
Calculate cross product c = a × b$\vec{c} = \vec{a} \times \vec{b}$:
c = vmatrix i & j & k 2 & -1 & 1 0 & λ & 2 vmatrix = (-2-λ) i - 4 j + 2λ k$$\vec{c} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ 2 & -1 & 1 \\ 0 & \lambda & 2 \end{vmatrix} = (-2-\lambda)\hat{i} - 4\hat{j} + 2\lambda\hat{k}$$
Given | c| = √(53)$|\vec{c}| = \sqrt{53}$:
(-2-λ)² + 16 + 4λ² = 53 5λ² + 4λ - 33 = 0$$(-2-\lambda)^2 + 16 + 4\lambda^2 = 53 \implies 5\lambda^2 + 4\lambda - 33 = 0$$
(5λ - 11)(λ + 3) = 0$$(5\lambda - 11)(\lambda + 3) = 0$$
Since λ in Z$\lambda \in \mathbb{Z}$, we get λ = -3$\lambda = -3$.
Thus, c = i - 4 j - 6 k$\vec{c} = \hat{i} - 4\hat{j} - 6\hat{k}$.
Step 1: Maximum Value of Dot Product Squared
Vector d$\vec{d}$ lies in yz-plane: d = y j + z k$\vec{d} = y\hat{j} + z\hat{k}$ with y² + z² = 4$y^2 + z^2 = 4$.
( c · d)² = (-4y - 6z)²$$(\vec{c} \cdot \vec{d})^2 = (-4y - 6z)^2$$
By Cauchy-Schwarz inequality:
(-4y - 6z)² ≤ ((-4)² + (-6)²)(y² + z²) = (16 + 36)(4) = 52 × 4 = 208$$(-4y - 6z)^2 \le ((-4)^2 + (-6)^2)(y^2 + z^2) = (16 + 36)(4) = 52 \times 4 = 208$$
Pattern Recognition
Project c$\vec{c}$ onto yz-plane components and apply Cauchy-Schwarz inequality to maximize dot product.
Chapter Mix
Class 12 Maths: Vector Algebra