$\operatorname{LMOpTruncation}(L, x, M, b)$
libname := libname, FileTools:-JoinPath(["maple","lib","dcfun.mla"],base=homedir):
with(dcfun):
We consider an order $2$ linear Mahler operator for the radix $b = 2$, and we 'truncate' it.
b := 2;
$$2$$
L := (2*x^6+2*x^4-x^2-1)*M^2+(-2*x^4-2*x^3-x^2+x+1)*M+2*x^2-x;
$$\left(2 x^{6}+2 x^{4}-x^{2}-1\right) M^{2}+\left(-2 x^{4}-2 x^{3}-x^{2}+x +1\right) M +2 x^{2}-x$$
L1 := LMOpTruncation(L, x, M, b);
$$2 x^{2}-x +\left(-x^{2}+x +1\right) M +\left(-x^{2}-1\right) M^{2}$$
Let us look at the Newton polygon diagram for each operator.
pix := LMOpNewtonPolygon(L, 0, x, M, b):
$$$$
pix1 := LMOpNewtonPolygon(L1, 0, x, M, b, linestyle = dot):
$$$$
plots:-display({pix, pix1});
$$$$
The lower Newton polygon (in blue) is the same for both operators. Its leftmost segment has a slope with value $-1$ and the number $\nu$ is the opposite value, that is $1$.
The leftmost segment can be extended on the left to intersect the ordinate axis at ordinate $2$; this is the number $\mu$. The horizontal line at this ordinate defines the 'truncation'. We keep only the points below or on this line, which determines the 'truncated' operator $L_1$.
Let us calculate a solution basis for each operator in the space of formal series.
B := LMOpSolve(L, x, M, b, 'ouput' = series, 'output_format' = 'basis');
$$\mathrm{table}\left(\left[1=\left[1, \left[1-2 x^{2}-6 x^{3}-14 x^{4}-30 x^{5}-62 x^{6}+\mathrm{O}\! \left(x^{7}\right), x +3 x^{2}+7 x^{3}+15 x^{4}+31 x^{5}+63 x^{6}+\mathrm{O}\! \left(x^{7}\right)\right], 1\right], \mathit{roots} =\left\{1\right\}\right]\right)$$
B1 := LMOpSolve(L1, x, M, b, 'ouput' = series, 'output_format' = 'basis');
$$\mathrm{table}\left(\left[1=\left[1, \left[1+\mathrm{O}\! \left(x^{7}\right), x +3 x^{2}+7 x^{3}+17 x^{4}+37 x^{5}+81 x^{6}+\mathrm{O}\! \left(x^{7}\right)\right], 1\right], \mathit{roots} =\left\{1\right\}\right]\right)$$
We can see that the two solution spaces have the same dimension $2$. This is what makes truncation interesting. It allows us to construct an operator that defines a solution space of a given dimension, however with solutions that are not too simple (not rational for example).
evalb(nops(B[1][2]) = nops(B1[1][2]));
$$\mathit{true}$$