Characteristic Polynomial:
Eigenvalues:
Note: This calculator provides approximate results. For precise calculations and professional applications, please consult with a mathematician or use specialized software.
Understanding the characteristic polynomial of a matrix is crucial in linear algebra and many scientific applications. Our characteristic polynomial calculator simplifies this process, helping students, engineers, and researchers analyze matrices effortlessly.
Note: This calculator provides approximate results. For precise calculations and professional applications, please consult with a mathematician or use specialized software.
The characteristic polynomial of a square matrix A is defined as:
p(λ) = det(λI - A)
Where:
This polynomial is essential for finding eigenvalues and understanding the properties of linear transformations.
The characteristic polynomial is presented in standard form:
p(λ) = an λ^n + a(n-1) λ^(n-1) + … + a_1 λ + a_0
The roots of this polynomial are the eigenvalues of the matrix. These values provide crucial information about the matrix’s behavior in linear transformations.
Let’s consider a 2x2 matrix:
A = [1 2] [3 4]
Using our calculator, you’ll get:
Characteristic Polynomial: p(λ) = λ^2 - 5λ - 2 Eigenvalues: λ_1 ≈ 5.37, λ_2 ≈ -0.37
Our calculator also provides:
A: They are the same thing. Eigenvalues are the roots of the characteristic polynomial.
A: Yes, it can compute and display both real and complex eigenvalues.
A: Our calculator can efficiently process matrices up to 10x10 in size.
A: Yes, you can create an account to save and revisit your previous calculations.
A: The characteristic polynomial is defined only for square matrices. For non-square matrices, consider using our SVD (Singular Value Decomposition) calculator.
Start analyzing your matrices now with our powerful characteristic polynomial calculator. Whether you’re a student tackling linear algebra or a professional working on complex systems, our tool will simplify your calculations and enhance your understanding of matrix properties.
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