Sigma Percentile
JEE Advanced 1998
LEVELJEE Main

Animated Solution for Mathematics - Vector Algebra: If , and are linearly dependent vectors and , then

Select Answer:

Visualized Solution

Given Vectors and

The Unknown Vector

  • Contains two unknowns: and .

Condition for Linear Dependence

  • Vectors are linearly dependent.
  • Geometrically, they are coplanar (lie in the same plane).
  • Scalar Triple Product:

Setting up the Determinant

Expanding the Determinant

  • Expanding along the first row:

Simplifying the Equation

  • Notice that and cancel out.

Solving for

  • Combining the remaining terms:

The Magnitude Constraint

  • We still need to find .
  • Given condition:

Applying the Magnitude Formula

  • Squaring both sides:

Substituting

  • Substitute into the equation:

Solving for

  • Taking the square root:

Final Conclusion

  • The calculated values are:
  • This matches Option 4.

The Sigma Insight: Scalar Triple Product

Solution Diagram

Analyzing the Setup

Imagine standing in a three-dimensional space with two vectors, and . These vectors define a unique plane.
We introduce a third vector, . The problem states that these three vectors are linearly dependent.
Geometrically, this implies that vector lies perfectly flat within the plane defined by and .

The Power of the Scalar Triple Product

To translate this "trapped" state into mathematics, we use the scalar triple product. If three vectors are coplanar, the volume of the parallelepiped they form must be zero.
Mathematically, this volume is calculated using the determinant of the matrix formed by their components:

The Algebraic Dance

We expand this determinant along the first row:
Distributing the values, we observe that the terms involving cancel out:
Simplifying this expression, we obtain:

Closing the Loop with Magnitude

We now turn to the second constraint: the magnitude of vector is . The magnitude formula in 3D is given by:
Setting this equal to and squaring both sides, we get:
Substituting our known value into the equation:
This simplifies to , which yields .
We have successfully navigated the constraints, finding and .

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