- galois.FieldArray.characteristic_poly() Poly
Computes the characteristic polynomial of a finite field element \(a\) or a square matrix \(\mathbf{A}\).
- Returns:¶
For scalar inputs, the degree-\(m\) characteristic polynomial \(c_a(x)\) of \(a\) over \(\mathrm{GF}(p)\). For square \(n \times n\) matrix inputs, the degree-\(n\) characteristic polynomial \(c_A(x)\) of \(\mathbf{A}\) over \(\mathrm{GF}(p^m)\).
- Raises:¶
ValueError – If the array is not a single finite field element (scalar 0-D array) or a square \(n \times n\) matrix (2-D array).
Notes¶
An element \(a\) of \(\mathrm{GF}(p^m)\) has characteristic polynomial \(c_a(x)\) over \(\mathrm{GF}(p)\). The characteristic polynomial when evaluated in \(\mathrm{GF}(p^m)\) annihilates \(a\), that is \(c_a(a) = 0\). In prime fields \(\mathrm{GF}(p)\), the characteristic polynomial of \(a\) is simply \(c_a(x) = x - a\).
An \(n \times n\) matrix \(\mathbf{A}\) has characteristic polynomial \(c_A(x) = \textrm{det}(x\mathbf{I} - \mathbf{A})\) over \(\mathrm{GF}(p^m)\). The constant coefficient of the characteristic polynomial is \(\textrm{det}(-\mathbf{A})\). The \(x^{n-1}\) coefficient of the characteristic polynomial is \(-\textrm{Tr}(\mathbf{A})\). The characteristic polynomial annihilates \(\mathbf{A}\), that is \(c_A(\mathbf{A}) = \mathbf{0}\).
References¶
Examples¶
The characteristic polynomial of the element \(a\).
In [1]: GF = galois.GF(3**5) In [2]: a = GF.Random(); a Out[2]: GF(125, order=3^5) In [3]: poly = a.characteristic_poly(); poly Out[3]: Poly(x^5 + x^4 + 2x^3 + 2x^2 + 1, GF(3)) # The characteristic polynomial annihilates a In [4]: poly(a, field=GF) Out[4]: GF(0, order=3^5)
In [5]: GF = galois.GF(3**5, repr="poly") In [6]: a = GF.Random(); a Out[6]: GF(2α^4 + 2α^2 + 2α + 2, order=3^5) In [7]: poly = a.characteristic_poly(); poly Out[7]: Poly(x^5 + 2x^3 + x^2 + 1, GF(3)) # The characteristic polynomial annihilates a In [8]: poly(a, field=GF) Out[8]: GF(0, order=3^5)
In [9]: GF = galois.GF(3**5, repr="power") In [10]: a = GF.Random(); a Out[10]: GF(α^177, order=3^5) In [11]: poly = a.characteristic_poly(); poly Out[11]: Poly(x^5 + 2x^3 + 2x^2 + x + 1, GF(3)) # The characteristic polynomial annihilates a In [12]: poly(a, field=GF) Out[12]: GF(0, order=3^5)
The characteristic polynomial of the square matrix \(\mathbf{A}\).
In [13]: GF = galois.GF(3**5) In [14]: A = GF.Random((3,3)); A Out[14]: GF([[ 38, 39, 214], [171, 114, 33], [ 52, 144, 145]], order=3^5) In [15]: poly = A.characteristic_poly(); poly Out[15]: Poly(x^3 + 147x^2 + 116x + 12, GF(3^5)) # The x^0 coefficient is det(-A) In [16]: poly.coeffs[-1] == np.linalg.det(-A) Out[16]: np.True_ # The x^n-1 coefficient is -Tr(A) In [17]: poly.coeffs[1] == -np.trace(A) Out[17]: np.True_ # The characteristic polynomial annihilates the matrix A In [18]: poly(A, elementwise=False) Out[18]: GF([[0, 0, 0], [0, 0, 0], [0, 0, 0]], order=3^5)
In [19]: GF = galois.GF(3**5, repr="poly") In [20]: A = GF.Random((3,3)); A Out[20]: GF([[2α^4 + α^3 + 2α^2 + 2α + 2, 2α^2 + 1, 0], [ 2α^4 + α + 1, α^3 + 2α^2 + 2α, 2α^4 + 2α^3 + α^2 + 2], [ 2α^4 + α^3 + α^2 + 1, α^4 + α^3 + α^2 + 2α, 2α^4 + 2α^2 + 2]], order=3^5) In [21]: poly = A.characteristic_poly(); poly Out[21]: Poly(x^3 + (2α^4 + α^3 + 2α + 2)x^2 + (2α^4 + α^3 + α^2 + 2)x + (α^4 + 2α^3 + 2α^2), GF(3^5)) # The x^0 coefficient is det(-A) In [22]: poly.coeffs[-1] == np.linalg.det(-A) Out[22]: np.True_ # The x^n-1 coefficient is -Tr(A) In [23]: poly.coeffs[1] == -np.trace(A) Out[23]: np.True_ # The characteristic polynomial annihilates the matrix A In [24]: poly(A, elementwise=False) Out[24]: GF([[0, 0, 0], [0, 0, 0], [0, 0, 0]], order=3^5)
In [25]: GF = galois.GF(3**5, repr="power") In [26]: A = GF.Random((3,3)); A Out[26]: GF([[ α^8, α^155, α^103], [α^172, α^2, α^31], [α^161, α^114, α^196]], order=3^5) In [27]: poly = A.characteristic_poly(); poly Out[27]: Poly(x^3 + (α^237)x^2 + (α^77)x + α^60, GF(3^5)) # The x^0 coefficient is det(-A) In [28]: poly.coeffs[-1] == np.linalg.det(-A) Out[28]: np.True_ # The x^n-1 coefficient is -Tr(A) In [29]: poly.coeffs[1] == -np.trace(A) Out[29]: np.True_ # The characteristic polynomial annihilates the matrix A In [30]: poly(A, elementwise=False) Out[30]: GF([[0, 0, 0], [0, 0, 0], [0, 0, 0]], order=3^5)