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Home Page > Math > Linear Algebra

Characteristic Polynomial Calculator

Calculate the characteristic polynomial det(A − λI) of a square matrix. Supports 2×2 to 6×6 matrices with step-by-step cofactor expansion, eigenvalue extraction, coefficient analysis, and interactive polynomial visualization.

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Examples:
Matrix Size
3 × 3
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CHARACTERISTIC POLYNOMIAL PREVIEW
det(A − λI) = ?

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About Characteristic Polynomial Calculator

The Characteristic Polynomial Calculator computes the characteristic polynomial \(p(\lambda) = \det(\lambda I - A)\) of any square matrix from 2×2 to 6×6. Enter your matrix values, and instantly get the polynomial in both expanded and factored form, eigenvalues with multiplicities, a coefficient analysis table, an interactive polynomial graph, and a complete step-by-step solution with MathJax-rendered formulas.

What Is the Characteristic Polynomial?

The characteristic polynomial of an \(n \times n\) matrix \(A\) is defined as:

$$p(\lambda) = \det(\lambda I - A)$$

This is a degree-\(n\) polynomial in \(\lambda\), and its roots are exactly the eigenvalues of \(A\). The characteristic polynomial encodes fundamental invariants of the matrix: its trace equals the negative of the \(\lambda^{n-1}\) coefficient, and its determinant equals the constant term (up to sign). By the Cayley–Hamilton theorem, every square matrix satisfies its own characteristic equation: \(p(A) = 0\).

Key Concepts

🔢
Eigenvalues
Roots of p(λ) = 0. These are the values λ where det(A − λI) = 0.
Trace = Σλᵢ
Sum of diagonal entries equals sum of all eigenvalues.
Det = ∏λᵢ
Determinant equals the product of all eigenvalues.
📜
Cayley–Hamilton
Every matrix satisfies its own characteristic equation: p(A) = 0.

Characteristic Polynomial Formulas by Size

SizeCharacteristic Polynomial p(λ)Key Properties
2×2\(\lambda^2 - \text{tr}(A)\lambda + \det(A)\)Always degree 2; two roots (real or complex conjugate pair)
3×3\(\lambda^3 - \text{tr}(A)\lambda^2 + (\text{sum of 2×2 minors})\lambda - \det(A)\)At least one real root guaranteed
n×n\(\det(\lambda I - A) = \lambda^n - s_1\lambda^{n-1} + s_2\lambda^{n-2} - \ldots\)\(s_k\) = sum of all k×k principal minors

Applications of the Characteristic Polynomial

FieldApplicationHow the Characteristic Polynomial Helps
Differential EquationsSolving linear ODE systemsEigenvalues from p(λ) determine solution modes (growth, decay, oscillation)
Control TheorySystem stability analysisRoots of the characteristic polynomial indicate stable vs unstable modes
Quantum MechanicsEnergy levels of systemsEigenvalues of Hamiltonian matrix are measurable energy states
Graph TheorySpectral graph analysisCharacteristic polynomial of adjacency matrix encodes graph structure
Vibration AnalysisNatural frequenciesEigenvalues give resonant frequencies of mechanical systems
Data SciencePCA / dimensionality reductionLargest eigenvalues identify principal components in covariance matrices

How to Use the Characteristic Polynomial Calculator

  1. Choose matrix size: Use the +/− buttons to select a matrix from 2×2 to 6×6. Or click a quick example to load a preset matrix.
  2. Enter matrix values: Type numbers into the matrix grid. Use Tab or arrow keys to navigate between cells. The diagonal cells are highlighted in blue to help with orientation.
  3. Click Calculate: The calculator forms the matrix (A − λI), computes the determinant symbolically to produce the characteristic polynomial, then factors it to find eigenvalues.
  4. Review the results: Examine the characteristic polynomial in expanded and factored forms. Check the eigenvalue cards for roots and multiplicities. The interactive graph shows where p(λ) crosses zero.
  5. Explore step-by-step: Use the step navigator or Auto button to walk through the complete derivation — from forming A − λI to the final verification via trace and determinant.

FAQ

What is a characteristic polynomial?
The characteristic polynomial of a square matrix A is p(λ) = det(λI − A), a degree-n polynomial whose roots are the eigenvalues of A. It encodes essential information about the matrix including its eigenvalues, trace, and determinant. The characteristic polynomial is one of the most fundamental objects in linear algebra.
How do you find the characteristic polynomial of a 2×2 matrix?
For a 2×2 matrix [[a, b], [c, d]], the characteristic polynomial is λ² − (a+d)λ + (ad − bc). This simplifies to λ² − tr(A)λ + det(A), where tr(A) = a+d is the trace and det(A) = ad − bc is the determinant. The two roots give you the eigenvalues.
What is the relationship between the characteristic polynomial and eigenvalues?
The eigenvalues of a matrix are exactly the roots of its characteristic polynomial. If λ₀ is a root of p(λ) = det(λI − A) = 0, then λ₀ is an eigenvalue. The algebraic multiplicity of an eigenvalue is its multiplicity as a root of p(λ). For example, if p(λ) = (λ − 3)²(λ − 1), then λ = 3 has algebraic multiplicity 2 and λ = 1 has algebraic multiplicity 1.
Can a characteristic polynomial have complex roots?
Yes. Even for a real matrix, the characteristic polynomial can have complex roots (eigenvalues). Complex eigenvalues of real matrices always come in conjugate pairs: if a + bi is an eigenvalue, then a − bi is also an eigenvalue. For example, the rotation matrix [[0, −1], [1, 0]] has characteristic polynomial λ² + 1, with roots ±i.
What do the coefficients of the characteristic polynomial tell us?
The coefficients encode important matrix invariants. The leading coefficient is always 1 (monic polynomial). The coefficient of λ^(n−1) equals −tr(A) (negative trace). The constant term equals (−1)ⁿ det(A). More generally, the coefficient of λ^(n−k) is (−1)^k times the sum of all k×k principal minors of A. These are called the elementary symmetric polynomials of the eigenvalues.

Reference this content, page, or tool as:

"Characteristic Polynomial Calculator" at https://MiniWebtool.com/characteristic-polynomial-calculator/ from MiniWebtool, https://MiniWebtool.com/

by miniwebtool team. Updated: 2026-04-13

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