2x2 Eigenvalues
Implement a solution to compute the eigenvalues of a 2×2 matrix using the characteristic equation. This task involves finding the scalar values, λ, that represent how much change occurs in a linear transformation.
The concept of eigenvalues and eigenvectors is crucial in linear algebra, as it helps describe the properties of linear transformations. For a 2×2 matrix A=(acbd), the eigenvalues satisfy the equation det(A−λI)=0, where I is the identity matrix.
- Start with the matrix A and the identity matrix I.
- Construct the matrix A−λI.
- Compute the determinant of A−λI and set it equal to zero.
This technique is widely used in computer vision for image processing and analysis.
Example:
A = [[4, 1], [2, 3]]
eigenvalues = [5.0, 2.0]
Finding eigenvalues of a 2×2 matrix using the characteristic equation:
For matrix A = [[a, b], [c, d]], eigenvalues satisfy: det(A−λI)=0
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Set up the characteristic equation: For A = [[4, 1], [2, 3]]: det(4−λ213−λ)=0
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Expand the determinant: (4−λ)(3−λ)−(1)(2)=0 12−4λ−3λ+λ2−2=0 λ2−7λ+10=0
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Apply the quadratic formula: λ=27±49−40=27±3
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Solve for both eigenvalues: λ1=27+3=5 λ2=27−3=2
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Result: eigenvalues = [5.0, 2.0]
The trace (sum of diagonal) equals 4+3=7=5+2, and determinant equals 12−2=10=5×2. ✓
Constraints:
- A is a 2×2 real matrix
- Return eigenvalues sorted in descending order
- Round to 4 decimal places
- Assume real eigenvalues (discriminant ≥ 0)