Characteristic/Minimal polynomials - Linear Algebra question

In summary, the conversation discusses finding polynomials a(λ) and b(λ) using the Euclidean algorithm to find the greatest common divisor of (λ+2)^2 and (λ-3) and using them to calculate the kernel of a given matrix.
  • #1
Locoism
81
0

Homework Statement


Given the matrix:

0 1 0
0 0 1
12 8 -1

(sorry I don't know how to put proper matrix format)

a) find polynomials a(λ)(λ+2)2+b(λ)(λ-3) = 1 (where a(λ) and b(λ) are the polynomials)


The Attempt at a Solution



Well the characteristic polynomial is already given, but can easily be found, as
(λ+2)2(λ-3)
but how do I find such polynomials? Is this what is meant by the minimal polynomial?
 
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  • #2
Locoism said:

Homework Statement


Given the matrix:

0 1 0
0 0 1
12 8 -1

(sorry I don't know how to put proper matrix format)

a) find polynomials a(λ)(λ+2)2+b(λ)(λ-3) = 1 (where a(λ) and b(λ) are the polynomials)


The Attempt at a Solution



Well the characteristic polynomial is already given, but can easily be found, as
(λ+2)2(λ-3)
but how do I find such polynomials? Is this what is meant by the minimal polynomial?

I don't understand. First you say that the characteristic polynomial "can easily be found, as (x+2)^2 *(x-3)" [using 'x' instead of 'lambda'], but then you say "but how do I find such polynomials?". So, do you, or do you not know how to find the characteristic polynomial?

As to minimal polynomial: well, it is a theorem that a matrix satisfies its own characteristic polynomial. For you matrix A the characteristic polynomial is C(x) = x^3 + x^2 - 8x - 12, so A satisfies A^3 + A^2 - 8A - 12I (where I = 3x3 identity matrix). In other words, the polynomial C "annihilates" A: C(A) = 0. The minimal polynomial of A is the polynomial of least degree that annihilates A (and has leading coefficient = 1). Sometimes the characteristic polynomial is the minimal polynomial, and sometimes not. For example, the 3x3 identity matrix I = [[1 0 0],[0 1 0], [0 0 1]] has characteristic polynomial C(x) = x^3 - 1, but has minimal polynomial x-1 (because A - 1*I = 0 when A = I).

One algorithm to find the minimal polynomial is that used by Maple: regard I, A, A^2 and A^3 as 9-dimensional vectors, obtained by writing the rows side-by side (so A <--> [0 1 0 0 0 1 12 8 -1], etc.). The fact that A satisfies the characteristic polynomial means that A^3 is a linear combination of I, A and A^2 with known coefficients. By doing linear algebra row operations, we can find the smallest number of rows among I, A, A^2 and A^3 such that A^k is a linear combination of I, A,..., A^(k-1), and that linear combination gives the minimal polynomial.

RGV
 
  • #3
Ray Vickson said:
I don't understand. First you say that the characteristic polynomial "can easily be found, as (x+2)^2 *(x-3)" [using 'x' instead of 'lambda'], but then you say "but how do I find such polynomials?". So, do you, or do you not know how to find the characteristic polynomial?

I think Locoism was referring to part a):
a) find polynomials a(λ)(λ+2)2+b(λ)(λ-3) = 1 (where a(λ) and b(λ) are the polynomials)

These can be found using the Euclidean algorithm: http://en.wikipedia.org/wiki/Euclidean_algorithm#Polynomials.
 
  • #4
Yes, sorry that was a little ambiguous.
Thank you very much spamiam, if I understand correctly, I just need to apply the algorithm to find the gcd of (x+2)^2 and (x-3)?
 
  • #5
Well, you're actually using the Euclidean algorithm followed by reverse substitution. I probably should have given you http://en.wikipedia.org/wiki/Extended_Euclidean_algorithm" link instead. For simplicity, I'll give you an example using integers instead of polynomials.

Consider 7 and 19. They are relatively prime, so gcd(7,19)=1. By http://en.wikipedia.org/wiki/B%C3%A9zout%27s_identity" there are integers a and b such that 7a + 19b = 1. Using the Euclidean algorithm, we get

19=2(7) +5
7=1(5) +2
5=2(2)+1

Solving these equations for the remainders, we have

1=5-2(2)
2=7-5
5=19-2(7)

giving us
[tex]
1=5-2 \cdot 2 = 5-2(7-5)=3 \cdot 5 - 2 \cdot 7 = 3(19-2 \cdot 7) -2 \cdot 7 = 3\cdot 19 -8 \cdot 7 \, .
[/tex]
The process is analogous for polynomials, I believe.
 
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  • #6
Thank you so much!
Ok so I end up with a(λ) = 1/25 and b(λ) = -1/25(λ-7) (it works out)
So if I use these with the matrix A as in
E1 = 1/25(A+2)2
E2 = -1/25(A-7)(A-3)
and I want to calculate the Kernel, would that just be (A-3) and (A+2)2 respectively seeing as E1*E2 = 0? And then ImageE1 would just be KernelE2 and vice-versa?
 
  • #7
I'm not quite sure I follow... Typically you just need to set up [itex] E_1 x = 0[/itex] and solve for x to compute the kernel. What is the question you're trying to answer?
 

1. What is a characteristic polynomial?

A characteristic polynomial is a polynomial that is associated with a square matrix. It is used to find the eigenvalues of the matrix, which are the values that, when multiplied by the identity matrix, give back the original matrix.

2. How is a characteristic polynomial calculated?

The characteristic polynomial is calculated by taking the determinant of the matrix minus lambda times the identity matrix. Lambda is a variable used in polynomial equations.

3. What is the significance of the characteristic polynomial?

The characteristic polynomial is significant because it helps us find the eigenvalues of a matrix, which are important in many areas of mathematics, such as solving differential equations and analyzing the behavior of systems.

4. What is a minimal polynomial?

A minimal polynomial is the smallest polynomial that, when applied to a square matrix, equals zero. It is used to find the eigenvalues of a matrix and can also be used to determine if a matrix is diagonalizable.

5. How is a minimal polynomial different from a characteristic polynomial?

A minimal polynomial and a characteristic polynomial are different in that a minimal polynomial is used to find the eigenvalues of a matrix, while the characteristic polynomial is used to find the determinant of a matrix. Additionally, a minimal polynomial is the smallest polynomial that equals zero when applied to a matrix, while the characteristic polynomial can have a higher degree.

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