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:
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.
They are the same thing. Eigenvalues are the roots of the characteristic polynomial.
Yes, it can compute and display both real and complex eigenvalues.
Our calculator can efficiently process matrices up to 10x10 in size.
Yes, you can create an account to save and revisit your previous calculations.
The characteristic polynomial is defined only for square matrices. For non-square matrices, consider using our SVD (Singular Value Decomposition) calculator.
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