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A^n, n=var(’n')

asked 2011-08-18 22:51:31 +0100

alreiff gravatar image

We have a matrix, for instance A = Matrix([[1,2],[3,4]]) How caculate A^n with n a variable (i.e symbolic calculus) and not n=50 or n = 100

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answered 2012-06-25 11:17:26 +0100

pang gravatar image

If the matrix is diagonalizable, the following works:

sage: def pow(D,k):
...       return diagonal_matrix([l^k for l in D.diagonal()])

sage: D,P=M.jordan_form(transformation=True)
sage: show(P*pow(D,k)*~P)

It gets more messy if the matrix admits a jordan form in Q, and it needs some patching if some eigenvalues are in QQbar\QQ, because there are no canonical coercions between QQbar and SR, the likely parent of the final result. Code like the following did the trick:

sage: D,P = M.base_extend(QQbar).jordan_form(transformation = True)
sage: matriz = (P.apply_map(lambda l:SR(l))*powJordan(D,k).apply_map(lambda l:SR(l))*(~P).apply_map(lambda l:SR(l)))

apply_map is used because base_extend does not work, for the reasons mentioned above.

powJordan could be for example like this:

sage: def powJordan(D, k):
...       '''Eleva una matriz de Jordan (no necesariamente diagonal) a una variable simbolica'''
...       
...       dim = D.ncols()
...       M = matrix(SR, dim, dim)
...   
...       i = 0
...       while i<=dim-1:
...           #Autovalores simples, o con multiplicidad algebraica == multiplicidad geometrica
...           if (i== dim-1) or D[i,i+1] == 0: 
...               M[i,i] = SR(D[i,i])^k
...               i = i + 1
...           else: #buscamos la dimension del subespacio invariante
...               counter = 1
...               for j in range(i, dim-1):
...                   if D[j,j+1] == 0:
...                       break
...                   counter += 1
...               for j in srange(i, i+counter):
...                   for t in srange(j,(i+counter)):
...                       M[j,t] = binomial(k, t-j)*SR(D[i,i])^(k-(t-j))
...               i += counter
...           
...       return M

I have to say, I'm not fully satisfied with the solution, but it might work for you as it did for me.

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answered 2011-08-18 23:10:48 +0100

kcrisman gravatar image

As you saw, this gives a NotImplementedError in Sage, so you can't do it directly.

This is possible in Maxima, though it just gives you a symbolic answer.

sage: maxima_console()
<snip>
(%i7) A: matrix([1,2],[3,4]);
                                   [ 1  2 ]
(%o7)                              [      ]
                                   [ 3  4 ]
(%i11) A.A;
                                  [ 7   10 ]
(%o11)                            [        ]
                                  [ 15  22 ]
(%i13) A^^2;
                                  [ 7   10 ]
(%o13)                            [        ]
                                  [ 15  22 ]
(%i14) A^^n;
                                          <n>
                                  [ 1  2 ]
(%o14)                            [      ]
                                  [ 3  4 ]

Unfortunately, I can't find this exponential command for matrices with letters, so we could use it by tab-completion in Sage and then use

sage: A = matrix([[1]])
sage: M = A._maxima_()
sage: M.command_name('n')

or something.

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answered 2012-06-25 12:00:57 +0100

pang gravatar image

updated 2012-06-28 09:39:45 +0100

I've found another way that might work in some situations: use the exponential of the matrix:

$$e^M=\sum_{k\geq 0} \frac{1}{k!}M^k$$

then use derivatives to recover the powers of the matrix:

$$\left(\frac{\partial}{\partial k} \right)^k e^M = M^k$$

For example:

sage:  B = matrix(SR, 2, [1,2,3,4])
...    var('t')
...    f = exp(t*B)[1,1]
sage:  print n(f.derivative(t,4)(t=0))
634.000000000000
sage:  print n((B^4)[1,1])
634.000000000000

In order words, the k-th order derivative of the function f = exp(t*B)[1,1] at zero is the [1,1] coefficient of B^k. Maybe that solves your problem.

This could be useful in combination with LazyPowerSeries, as seen in the sage book in french.

Once you've got the function $f = (e^M)_{ij}$, you could get the function k -> [k-th order derivative of $f$] = [(i,j) entry of $M^k$] by Fourier transform, product with $\psi^k$, and inverse Fourier transform. But those integrals may be non-trivial...

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Ah, pang! I will hijack this to ask what you think of the updates at #10637... they work for me...

kcrisman gravatar imagekcrisman ( 2012-06-25 12:56:38 +0100 )edit

Hi, karl: It's working now, I just need to doctest the full sage library and stuff like that. Currently my hardware is limited, so I cannot do this at any time.

pang gravatar imagepang ( 2012-06-28 09:34:55 +0100 )edit

I'll respond there.

kcrisman gravatar imagekcrisman ( 2012-06-28 11:08:59 +0100 )edit
0

answered 2017-04-28 21:02:34 +0100

mforets gravatar image

From Sage v.8.0.beta3,

sage: A = Matrix([[1,2],[3,4]])
sage: n = SR.var('n')  
sage: A^n
[ 1/22*(-1/2*sqrt(33) + 5/2)^n*(sqrt(33) + 11) - 1/22*(1/2*sqrt(33) + 5/2)^n*(sqrt(33) - 11)                                                          2/33*sqrt(33)*(1/2*sqrt(33) + 5/2)^n - 2/33*sqrt(33)*(-1/2*sqrt(33) + 5/2)^n]
[-1/88*(-1/2*sqrt(33) + 5/2)^n*(sqrt(33) + 11)*(sqrt(33) - 3) - 1/88*(1/2*sqrt(33) + 5/2)^n*(sqrt(33) + 3)*(sqrt(33) - 11)                    1/66*sqrt(33)*(1/2*sqrt(33) + 5/2)^n*(sqrt(33) + 3) + 1/66*sqrt(33)*(-1/2*sqrt(33) + 5/2)^n*(sqrt(33) - 3)]

which is

$$ \left(\begin{array}{rr} \frac{1}{22} {\left(-\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} + 11\right)} - \frac{1}{22} {\left(\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} - 11\right)} & \frac{2}{33} \sqrt{33} {\left(\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} - \frac{2}{33} \sqrt{33} {\left(-\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} \\ -\frac{1}{88} {\left(-\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} + 11\right)} {\left(\sqrt{33} - 3\right)} - \frac{1}{88} {\left(\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} + 3\right)} {\left(\sqrt{33} - 11\right)} & \frac{1}{66} \sqrt{33} {\left(\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} + 3\right)} + \frac{1}{66} \sqrt{33} {\left(-\frac{1}{2} \sqrt{33} + \frac{5}{2}\right)}^{n} {\left(\sqrt{33} - 3\right)} \end{array}\right) $$

Also in the case of 2x2 matrices there is a derivation of the closed formula for $A^n$ in this note by K. S. Williams.

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Asked: 2011-08-18 22:51:31 +0100

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Last updated: Apr 28 '17