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Application of Derivatives question

2023 · Shift 1 · Q22
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  5. /2023 · Shift 1 · Q22

Application of Derivatives question

2023 · Shift 1 · Q22

JEE AdvancedMathematicsApplication of DerivativesMCQ+3 / −1
Let QQQ be the cube with the set of vertices {(x1,x2,x3)∈R3:x1,x2,x3∈{0,1}}\left\{\left(x_1, x_2, x_3\right) \in \mathbb{R}^3: x_1, x_2, x_3 \in\{0,1\}\right\}{(x1​,x2​,x3​)∈R3:x1​,x2​,x3​∈{0,1}}. Let FFF be the set of all twelve lines containing the diagonals of the six faces of the cube QQQ. Let SSS be the set of all four lines containing the main diagonals of the cube QQQ; for instance, the line passing through the vertices (0,0,0)(0,0,0)(0,0,0) and (1,1,1)(1,1,1)(1,1,1) is in SSS. For lines ℓ1\ell_1ℓ1​ and ℓ2\ell_2ℓ2​, let d(ℓ1,ℓ2)d\left(\ell_1, \ell_2\right)d(ℓ1​,ℓ2​) denote the shortest distance between them. Then the maximum value of d(ℓ1,ℓ2)d\left(\ell_1, \ell_2\right)d(ℓ1​,ℓ2​), as ℓ1\ell_1ℓ1​ varies over FFF and ℓ2\ell_2ℓ2​ varies over SSS, is :
  1. A
    16\frac{1}{\sqrt{6}}6​1​
  2. B
    18\frac{1}{\sqrt{8}}8​1​
  3. C
    13\frac{1}{\sqrt{3}}3​1​
  4. D
    112\frac{1}{\sqrt{12}}12​1​
View written solutionFree

Correct answer: A

1. Understanding the Geometry

Let the cube Q have vertices at coordinates (x1,x2,x3)(x_1, x_2, x_3)(x1​,x2​,x3​) where xi∈{0,1}x_i \in \{0, 1\}xi​∈{0,1}. This is a unit cube with one vertex at the origin O(0,0,0)O(0,0,0)O(0,0,0) and edges along the coordinate axes.

  • Set S: The set of 4 lines containing the main diagonals of the cube. These connect opposite vertices. For example, the line passing through O(0,0,0)O(0,0,0)O(0,0,0) and F(1,1,1)F(1,1,1)F(1,1,1).
  • Set F: The set of 12 lines containing the diagonals of the six faces. Each face has two diagonals.

We need to find the maximum value of the shortest distance, d(ℓ1,ℓ2)d(\ell_1, \ell_2)d(ℓ1​,ℓ2​), where ℓ1∈F\ell_1 \in Fℓ1​∈F and ℓ2∈S\ell_2 \in Sℓ2​∈S.

2. Strategy: Using Symmetry

The cube is a highly symmetric object. We can simplify the problem by fixing one line and then finding its distance to all the lines in the other set. Due to symmetry, the set of distances will be the same regardless of which main diagonal we choose.

Let's choose the main diagonal ℓ2\ell_2ℓ2​ that passes through the origin O(0,0,0)O(0,0,0)O(0,0,0) and the vertex F(1,1,1)F(1,1,1)F(1,1,1).

  • A point on line ℓ2\ell_2ℓ2​ is a⃗2=(0,0,0)\vec{a}_2 = (0,0,0)a2​=(0,0,0).
  • The direction vector of ℓ2\ell_2ℓ2​ is b⃗2=(1,1,1)−(0,0,0)=(1,1,1)\vec{b}_2 = (1,1,1) - (0,0,0) = (1,1,1)b2​=(1,1,1)−(0,0,0)=(1,1,1).

3. Analyzing Distances from ℓ2\ell_2ℓ2​ to lines in F

Now, let's consider a line ℓ1∈F\ell_1 \in Fℓ1​∈F. There are two possibilities for the relationship between ℓ1\ell_1ℓ1​ and ℓ2\ell_2ℓ2​:

Case 1: ℓ1\ell_1ℓ1​ and ℓ2\ell_2ℓ2​ intersect. This occurs if the face diagonal ℓ1\ell_1ℓ1​ shares a vertex with the main diagonal ℓ2\ell_2ℓ2​. The vertices of ℓ2\ell_2ℓ2​ are O(0,0,0)O(0,0,0)O(0,0,0) and F(1,1,1)F(1,1,1)F(1,1,1).

  • There are 3 face diagonals that pass through OOO. For these, the lines intersect at the origin.
  • There are 3 face diagonals that pass through FFF. For these, the lines intersect at FFF. For these 6 out of 12 lines in FFF, the shortest distance d(ℓ1,ℓ2)d(\ell_1, \ell_2)d(ℓ1​,ℓ2​) is 0.

Case 2: ℓ1\ell_1ℓ1​ and ℓ2\ell_2ℓ2​ are skew. This occurs for the 6 face diagonals that do not pass through either O(0,0,0)O(0,0,0)O(0,0,0) or F(1,1,1)F(1,1,1)F(1,1,1). Due to the symmetry of the cube, the shortest distance from ℓ2\ell_2ℓ2​ to each of these 6 lines will be the same. Let's calculate this distance for one of them.

Let's pick the face diagonal ℓ1\ell_1ℓ1​ on the face z=0z=0z=0 (the xy-plane) which connects the vertices A(1,0,0)A(1,0,0)A(1,0,0) and C(0,1,0)C(0,1,0)C(0,1,0).

  • A point on line ℓ1\ell_1ℓ1​ is a⃗1=(1,0,0)\vec{a}_1 = (1,0,0)a1​=(1,0,0).
  • The direction vector of ℓ1\ell_1ℓ1​ is b⃗1=C−A=(0,1,0)−(1,0,0)=(−1,1,0)\vec{b}_1 = C - A = (0,1,0) - (1,0,0) = (-1,1,0)b1​=C−A=(0,1,0)−(1,0,0)=(−1,1,0).

4. Calculating the Shortest Distance

The formula for the shortest distance between two skew lines with vector equations r⃗=a⃗1+sb⃗1\vec{r} = \vec{a}_1 + s\vec{b}_1r=a1​+sb1​ and r⃗=a⃗2+tb⃗2\vec{r} = \vec{a}_2 + t\vec{b}_2r=a2​+tb2​ is: d=∣(a⃗1−a⃗2)⋅(b⃗1×b⃗2)∣∣b⃗1×b⃗2∣d = \frac{|(\vec{a}_1 - \vec{a}_2) \cdot (\vec{b}_1 \times \vec{b}_2)|}{|\vec{b}_1 \times \vec{b}_2|}d=∣b1​×b2​∣∣(a1​−a2​)⋅(b1​×b2​)∣​ Let's compute the necessary components:

  • a⃗1−a⃗2=(1,0,0)−(0,0,0)=(1,0,0)\vec{a}_1 - \vec{a}_2 = (1,0,0) - (0,0,0) = (1,0,0)a1​−a2​=(1,0,0)−(0,0,0)=(1,0,0).

  • b⃗1×b⃗2=(−1,1,0)×(1,1,1)\vec{b}_1 \times \vec{b}_2 = (-1,1,0) \times (1,1,1)b1​×b2​=(−1,1,0)×(1,1,1). We can compute this using the determinant: b⃗1×b⃗2=∣i^j^k^−110111∣=i^(1−0)−j^(−1−0)+k^(−1−1)=(1,1,−2)\vec{b}_1 \times \vec{b}_2 = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ -1 & 1 & 0 \\ 1 & 1 & 1 \end{vmatrix} = \hat{i}(1-0) - \hat{j}(-1-0) + \hat{k}(-1-1) = (1, 1, -2)b1​×b2​=​i^−11​j^​11​k^01​​=i^(1−0)−j^​(−1−0)+k^(−1−1)=(1,1,−2) Now, we calculate the numerator and denominator for the distance formula.

  • Numerator: ∣(a⃗1−a⃗2)⋅(b⃗1×b⃗2)∣=∣(1,0,0)⋅(1,1,−2)∣=∣1(1)+0(1)+0(−2)∣=∣1∣=1|(\vec{a}_1 - \vec{a}_2) \cdot (\vec{b}_1 \times \vec{b}_2)| = |(1,0,0) \cdot (1,1,-2)| = |1(1) + 0(1) + 0(-2)| = |1| = 1∣(a1​−a2​)⋅(b1​×b2​)∣=∣(1,0,0)⋅(1,1,−2)∣=∣1(1)+0(1)+0(−2)∣=∣1∣=1

  • Denominator: ∣b⃗1×b⃗2∣=∣(1,1,−2)∣=12+12+(−2)2=1+1+4=6|\vec{b}_1 \times \vec{b}_2| = |(1,1,-2)| = \sqrt{1^2 + 1^2 + (-2)^2} = \sqrt{1+1+4} = \sqrt{6}∣b1​×b2​∣=∣(1,1,−2)∣=12+12+(−2)2​=1+1+4​=6​

  • Shortest Distance: d(ℓ1,ℓ2)=16d(\ell_1, \ell_2) = \frac{1}{\sqrt{6}}d(ℓ1​,ℓ2​)=6​1​

5. Conclusion

For any pair of lines (ℓ1,ℓ2)(\ell_1, \ell_2)(ℓ1​,ℓ2​) with ℓ1∈F\ell_1 \in Fℓ1​∈F and ℓ2∈S\ell_2 \in Sℓ2​∈S, the shortest distance is either 0 (if they intersect) or 16\frac{1}{\sqrt{6}}6​1​ (if they are skew).

The problem asks for the maximum value of d(ℓ1,ℓ2)d(\ell_1, \ell_2)d(ℓ1​,ℓ2​).

Maximum value = max⁡{0,16}=16\max \left\{0, \frac{1}{\sqrt{6}}\right\} = \frac{1}{\sqrt{6}}max{0,6​1​}=6​1​.

This matches option A.

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