Math Problem Statement

If the determinant of X^2-5I2 is 0, prove that X^2=5I2

Solution

We are given the equation:

det(X25I2)=0\det(X^2 - 5I_2) = 0

where XX is a 2×22 \times 2 matrix and I2I_2 is the 2×22 \times 2 identity matrix. We need to prove that this implies X2=5I2X^2 = 5I_2.

Step-by-step Proof:

  1. Use of the Determinant Property:
    The determinant of a matrix being 0 implies that the matrix itself is singular, i.e., it has no inverse. In this case, it means that: det(X25I2)=0\det(X^2 - 5I_2) = 0 implies that X25I2X^2 - 5I_2 is a singular matrix.

  2. Eigenvalues and Determinants:
    Let’s assume λ\lambda is an eigenvalue of the matrix XX. For any matrix XX, its eigenvalues satisfy the equation det(XλI)=0\det(X - \lambda I) = 0.

    Now, since X25I2X^2 - 5I_2 is singular, the eigenvalues of X25I2X^2 - 5I_2 must include 0. That is, for eigenvalues λ\lambda of XX, we have: λ25=0\lambda^2 - 5 = 0 or λ2=5\lambda^2 = 5 which means the eigenvalues of XX are λ=±5\lambda = \pm \sqrt{5}.

  3. Diagonalization:
    Since XX is a 2×22 \times 2 matrix and has two distinct eigenvalues (±5\pm \sqrt{5}), it can be diagonalized. That is, there exists an invertible matrix PP and a diagonal matrix DD such that: X=PDP1X = P D P^{-1} where D=diag(5,5)D = \text{diag}(\sqrt{5}, -\sqrt{5}).

  4. Square of XX:
    Squaring both sides of X=PDP1X = P D P^{-1}: X2=PD2P1X^2 = P D^2 P^{-1} Since D2=diag(5,5)=5I2D^2 = \text{diag}(5, 5) = 5I_2, we have: X2=P(5I2)P1=5PI2P1=5I2X^2 = P (5I_2) P^{-1} = 5P I_2 P^{-1} = 5I_2

Thus, we have shown that X2=5I2X^2 = 5I_2.

Conclusion:

The fact that det(X25I2)=0\det(X^2 - 5I_2) = 0 implies that the eigenvalues of XX are ±5\pm \sqrt{5}, and hence X2=5I2X^2 = 5I_2, as required.


Do you want further details on any of the steps, or would you like more examples?

Here are five related questions you might consider:

  1. How do eigenvalues affect the determinant of a matrix?
  2. Can you prove a similar result for a 3×33 \times 3 matrix?
  3. How does diagonalization help in simplifying matrix problems?
  4. Can the proof work without assuming diagonalizability of XX?
  5. What would happen if XX had repeated eigenvalues?

Tip: Always check if a matrix is diagonalizable when solving matrix equations. Diagonalization simplifies the process significantly!

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Math Problem Analysis

Mathematical Concepts

Linear Algebra
Matrix Determinants
Eigenvalues
Diagonalization

Formulas

det(X^2 - 5I_2) = 0
Eigenvalue equation: det(X - λI) = 0
λ^2 = 5
X = PDP^{-1}
X^2 = P D^2 P^{-1} = 5I_2

Theorems

Determinant Theorem
Eigenvalue Theorem
Diagonalization Theorem

Suitable Grade Level

Undergraduate Level (Linear Algebra)