The story revolves around something similar to "Jordan normal form":
$$P^{-1}AP=J.$$
First, to generate two 4×4 lower triangular matrices — $A,\ J$ (5×5 in the end):
n = 4;
rules = {{i_, i_} -> i - 1, {i_, j_} /; i >= j -> j};
lowT[n_, range__: All] := SparseArray[rules[[range]], {n, n}]
{A, J} = lowT[n, #] & /@ {All, 1} // Normal;
MatrixForm /@ {A, J}
$\{ {\left( {\matrix{0 & 0 & 0 & 0 \cr 1 & 1 & 0 & 0 \cr 1 & 2 & 2 & 0 \cr 1 & 2 & 3 & 3 \cr } } \right), \left( {\matrix{0 & 0 & 0 & 0 \cr 0 & 1 & 0 & 0 \cr 0 & 0 & 2 & 0 \cr 0 & 0 & 0 & 3 \cr } } \right)} \}$
Then, set the variable $P$, solve the equation on the top.
P = x~Array~{n, n};
sol = Solve[(P~MatrixPower~-1).A.P == J, Flatten@P];
The original result is rather long as algebraic form. For simplicity, arbitrarily substituting some numerical value, here, the elements on the diagonal are all set to 1:
(P = P /. Flatten@sol /. Table[x[i, i] -> 1, {i, n}]) // MatrixForm
$\left(\begin{array}{cccc}1 & 0 & 0 & 0 \\-1 & 1 & 0 & 0 \\\frac{1}{2} & -2 & 1 & 0 \\-\frac{1}{6} & 2 & -3 & 1 \\\end{array}\right)$
Finally, show the numerical equation and verify the correctness.
Inactivate[MatrixPower[P, -1].A.P == J, Dot] // TraditionalForm
% // Activate
$\left(\begin{array}{cccc}1 & 0 & 0 & 0 \\1 & 1 & 0 & 0 \\\frac{3}{2} & 2 & 1 & 0 \\\frac{8}{3} & 4 & 3 & 1 \\\end{array}\right).\left(\begin{array}{cccc}0 & 0 & 0 & 0 \\1 & 1 & 0 & 0 \\1 & 2 & 2 & 0 \\1 & 2 & 3 & 3 \\\end{array}\right).\left(\begin{array}{cccc}1 & 0 & 0 & 0 \\-1 & 1 & 0 & 0 \\ \frac{1}{2} & -2 & 1 & 0 \\-\frac{1}{6} & 2 & -3 & 1 \\\end{array}\right)=\left(\begin{array}{cccc}0 & 0 & 0 & 0 \\0 & 1 & 0 & 0 \\0 & 0 & 2 & 0 \\0 & 0 & 0 & 3 \\\end{array}\right)$
True
All code runs completed in about 2.5 seconds, but when it comes to 5×5(n=5), the equation will take too long that there is no hope for waiting it finish out.
So where is the problem?
Thanks for helping!
P.S. All code is merged as follows:
n = 4;
rules = {{i_, i_} -> i - 1, {i_, j_} /; i >= j -> j};
lowT[n_, range__: All] := SparseArray[rules[[range]], {n, n}]
{A, J} = lowT[n, #] & /@ {All, 1} // Normal;
MatrixForm /@ {A, J}
P = x~Array~{n, n};
sol = Solve[(P~MatrixPower~-1).A.P == J, Flatten@P];
(P = P /. Flatten@sol /. Table[x[i, i] -> 1, {i, n}]) // MatrixForm
Inactivate[MatrixPower[P, -1].A.P == J, Dot] // TraditionalForm
% // Activate
Solve[]
is not really necessary here. Since you mention already knowing about Jordan form, you can useJordanDecomposition[]
to show thatlowT[n, All]
is diagonalizable, and the first matrix returned byJordanDecomposition[lowT[n, All]]
is the similarity transformation you are looking for. $\endgroup$