Q
MCQ
Vectors
Let $\mathbf{a} = 2\hat{i} – \hat{j} + \hat{k}$, $\mathbf{b} = \lambda\hat{j} + 2\hat{k}$. If $\mathbf{c} = \mathbf{a} \times \mathbf{b}$ and $|\mathbf{c}| = \sqrt{53}$, where $\lambda$ is an integer, and $\mathbf{d}$ is a vector in the $yz$-plane with $|\mathbf{d}| = 2$, then the maximum value of $(\mathbf{c} \cdot \mathbf{d})^2$ is
A) 148
B) 196
C) 172
D) 208 ✓
1. Cross Product Formula
For vectors $\mathbf{a} = (a_1,a_2,a_3)$ and $\mathbf{b} = (b_1,b_2,b_3)$, the cross product $\mathbf{c} = \mathbf{a} \times \mathbf{b}$ is computed using the determinant: $c_x = a_2b_3 – a_3b_2$, $c_y = a_3b_1 – a_1b_3$, $c_z = a_1b_2 – a_2b_1$. The result is perpendicular to both $\mathbf{a}$ and $\mathbf{b}$. The magnitude $|\mathbf{a} \times \mathbf{b}| = |\mathbf{a}||\mathbf{b}|\sin\theta$ where $\theta$ is the angle between them.
2. Dot Product and Projection
The dot product $\mathbf{c} \cdot \mathbf{d} = c_1d_1 + c_2d_2 + c_3d_3 = |\mathbf{c}||\mathbf{d}|\cos\theta$. When $\mathbf{d}$ is restricted to the yz-plane ($d_x = 0$), only the $y$ and $z$ components of $\mathbf{c}$ contribute. The maximum dot product is $|\mathbf{c}||\mathbf{d}|$ when vectors are parallel, but here d is constrained to yz-plane so only the yz-projection of c is used.
3. Cauchy-Schwarz Inequality
The Cauchy-Schwarz inequality states $(a_1b_1 + a_2b_2)^2 \leq (a_1^2 + a_2^2)(b_1^2 + b_2^2)$. For our problem: $(-4y-6z)^2 \leq (16+36)(y^2+z^2)$. Equality holds when $\frac{y}{-4} = \frac{z}{-6}$, i.e., $y:z = 4:6 = 2:3$. This gives the configuration that maximizes the dot product.
4. Integer Constraints in Quadratics
When solving $5\lambda^2 + 4\lambda – 33 = 0$, the discriminant is $\Delta = 16 + 660 = 676 = 26^2$. Roots: $\lambda = \frac{-4 \pm 26}{10}$. One root is $\lambda = 2.2$ (not integer) and other is $\lambda = -3$ (integer). Always verify by substituting back: $5(9) + 4(-3) – 33 = 45 – 12 – 33 = 0$ ✓.
5. Vectors in Coordinate Planes
A vector in the yz-plane has the form $\mathbf{d} = (0, y, z)$. Its magnitude is $\sqrt{y^2+z^2}$. When computing $\mathbf{c} \cdot \mathbf{d}$, the x-component of $\mathbf{c}$ makes no contribution. This effectively reduces a 3D problem to 2D, simplifying the optimization. The constraint $|\mathbf{d}|=2$ means we are optimizing on a circle of radius 2 in the yz-plane.
Q
How do you compute a cross product?
⌄
Use the determinant: c = a×b gives cx = a2b3-a3b2, cy = a3b1-a1b3, cz = a1b2-a2b1. Result is perpendicular to both a and b.
Q
How to find magnitude of cross product?
⌄
|a×b|² = sum of squares of all three components. Here: |c|² = (λ+2)² + 16 + 4λ². Set equal to 53 and solve for λ.
Q
What is the Cauchy-Schwarz inequality?
⌄
(a·b)² ≤ |a|²|b|². For yz-plane: (-4y-6z)² ≤ (16+36)(y²+z²) = 52×4 = 208. Equality when y/4 = z/6.
Q
Why does d in yz-plane matter?
⌄
d = (0,y,z) so c·d = -4y-6z (x-component cancels). The bound uses only yz-components of c, giving 4²+6²=52, not |c|²=53.
Q
Why is λ = -3 chosen?
⌄
Solving 5λ²+4λ-33=0 gives λ=2.2 (not integer) or λ=-3 (integer). Since the problem specifies integer λ, we take λ=-3.
Q
How to verify |c|²=53 with λ=-3?
⌄
c = (1,-4,-6): |c|² = 1+16+36 = 53 ✓. All three components confirmed correct.
Q
What d vector achieves the maximum?
⌄
d proportional to (0,4,6) normalized to |d|=2. So d = (0, 4/√13 × 2/√4, …) — the direction (0,2,3)/√13 × 2.
Q
Why is the answer 208 not 212?
⌄
If d were unrestricted in 3D: max (c·d)² = |c|²|d|² = 53×4=212. But d is in yz-plane, so only yz-part of c (4²+6²=52) counts: 52×4=208.
Q
What does |d|=2 constraint mean?
⌄
y²+z²=4 confines d to a circle of radius 2 in the yz-plane. We maximize (c·d)² = (-4y-6z)² over this circle.
Q
When does equality hold in Cauchy-Schwarz?
⌄
When vectors are proportional: (y,z) ∝ (4,6). Normalize: y=4/√13, z=6/√13, but scale so y²+z²=4, giving y=8/√13, z=12/√13.