2.2.49 Problem 48

Internal problem ID [10127]
Book : Own collection of miscellaneous problems
Section : section 2.0
Problem number : 48
Date solved : Thursday, November 27, 2025 at 10:20:41 AM
CAS classification : [[_2nd_order, _with_linear_symmetries]]

Solved as second order ode using change of variable on x method 2

Time used: 0.240 (sec)

Solve

\begin{align*} y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2}-x^{3}-\frac {1}{x}&=0 \\ \end{align*}

This is second order non-homogeneous ODE. Let the solution be

\[ y = y_h + y_p \]

Where \(y_h\) is the solution to the homogeneous ODE \( A y''(x) + B y'(x) + C y(x) = 0\), and \(y_p\) is a particular solution to the non-homogeneous ODE \(A y''(x) + B y'(x) + C y(x) = f(x)\). \(y_h\) is the solution to

\[ y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2} = 0 \]

In normal form the ode

\begin{align*} y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2}&=0 \tag {1} \end{align*}

Becomes

\begin{align*} y^{\prime \prime }+p \left (x \right ) y^{\prime }+q \left (x \right ) y&=0 \tag {2} \end{align*}

Where

\begin{align*} p \left (x \right )&=-\frac {1}{x}\\ q \left (x \right )&=-x^{2} \end{align*}

Applying change of variables \(\tau = g \left (x \right )\) to (2) gives

\begin{align*} \frac {d^{2}}{d \tau ^{2}}y \left (\tau \right )+p_{1} \left (\frac {d}{d \tau }y \left (\tau \right )\right )+q_{1} y \left (\tau \right )&=0 \tag {3} \end{align*}

Where \(\tau \) is the new independent variable, and

\begin{align*} p_{1} \left (\tau \right ) &=\frac {\tau ^{\prime \prime }\left (x \right )+p \left (x \right ) \tau ^{\prime }\left (x \right )}{{\tau ^{\prime }\left (x \right )}^{2}}\tag {4} \\ q_{1} \left (\tau \right ) &=\frac {q \left (x \right )}{{\tau ^{\prime }\left (x \right )}^{2}}\tag {5} \end{align*}

Let \(p_{1} = 0\). Eq (4) simplifies to

\begin{align*} \tau ^{\prime \prime }\left (x \right )+p \left (x \right ) \tau ^{\prime }\left (x \right )&=0 \end{align*}

This ode is solved resulting in

\begin{align*} \tau &= \int {\mathrm e}^{-\int p \left (x \right )d x}d x\\ &= \int {\mathrm e}^{-\int -\frac {1}{x}d x}d x\\ &= \int e^{\ln \left (x \right )} \,dx\\ &= \int x d x\\ &= \frac {x^{2}}{2}\tag {6} \end{align*}

Using (6) to evaluate \(q_{1}\) from (5) gives

\begin{align*} q_{1} \left (\tau \right ) &= \frac {q \left (x \right )}{{\tau ^{\prime }\left (x \right )}^{2}}\\ &= \frac {-x^{2}}{x^{2}}\\ &= -1\tag {7} \end{align*}

Substituting the above in (3) and noting that now \(p_{1} = 0\) results in

\begin{align*} \frac {d^{2}}{d \tau ^{2}}y \left (\tau \right )+q_{1} y \left (\tau \right )&=0 \\ \frac {d^{2}}{d \tau ^{2}}y \left (\tau \right )-y \left (\tau \right )&=0 \end{align*}

The above ode is now solved for \(y \left (\tau \right )\).

This is second order with constant coefficients homogeneous ODE. In standard form the ODE is

\[ A y''(\tau ) + B y'(\tau ) + C y(\tau ) = 0 \]

Where in the above \(A=1, B=0, C=-1\). Let the solution be \(y \left (\tau \right )=e^{\lambda \tau }\). Substituting this into the ODE gives

\[ \lambda ^{2} {\mathrm e}^{\tau \lambda }-{\mathrm e}^{\tau \lambda } = 0 \tag {1} \]

Since exponential function is never zero, then dividing Eq(2) throughout by \(e^{\lambda \tau }\) gives

\[ \lambda ^{2}-1 = 0 \tag {2} \]

Equation (2) is the characteristic equation of the ODE. Its roots determine the general solution form.Using the quadratic formula

\[ \lambda _{1,2} = \frac {-B}{2 A} \pm \frac {1}{2 A} \sqrt {B^2 - 4 A C} \]

Substituting \(A=1, B=0, C=-1\) into the above gives

\begin{align*} \lambda _{1,2} &= \frac {0}{(2) \left (1\right )} \pm \frac {1}{(2) \left (1\right )} \sqrt {0^2 - (4) \left (1\right )\left (-1\right )}\\ &= \pm 1 \end{align*}

Hence

\begin{align*} \lambda _1 &= + 1 \\ \lambda _2 &= - 1 \\ \end{align*}

Which simplifies to

\begin{align*} \lambda _1 &= 1 \\ \lambda _2 &= -1 \\ \end{align*}

Since roots are distinct, then the solution is

\begin{align*} y \left (\tau \right ) &= c_1 e^{\lambda _1 \tau } + c_2 e^{\lambda _2 \tau } \\ y \left (\tau \right ) &= c_1 e^{\left (1\right )\tau } +c_2 e^{\left (-1\right )\tau } \\ \end{align*}

Or

\[ y \left (\tau \right ) =c_1 \,{\mathrm e}^{\tau }+c_2 \,{\mathrm e}^{-\tau } \]

The above solution is now transformed back to \(y\) using (6) which results in

\[ y = {\mathrm e}^{\frac {x^{2}}{2}} c_1 +{\mathrm e}^{-\frac {x^{2}}{2}} c_2 \]

Therefore the homogeneous solution \(y_h\) is

\[ y_h = {\mathrm e}^{\frac {x^{2}}{2}} c_1 +{\mathrm e}^{-\frac {x^{2}}{2}} c_2 \]

The particular solution \(y_p\) can be found using either the method of undetermined coefficients, or the method of variation of parameters. The method of variation of parameters will be used as it is more general and can be used when the coefficients of the ODE depend on \(x\) as well. Let

\begin{equation} \tag{1} y_p(x) = u_1 y_1 + u_2 y_2 \end{equation}

Where \(u_1,u_2\) to be determined, and \(y_1,y_2\) are the two basis solutions (the two linearly independent solutions of the homogeneous ODE) found earlier when solving the homogeneous ODE as

\begin{align*} y_1 &= {\mathrm e}^{-\frac {x^{2}}{2}} \\ y_2 &= {\mathrm e}^{\frac {x^{2}}{2}} \\ \end{align*}

In the Variation of parameters \(u_1,u_2\) are found using

\begin{align*} \tag{2} u_1 &= -\int \frac {y_2 f(x)}{a W(x)} \\ \tag{3} u_2 &= \int \frac {y_1 f(x)}{a W(x)} \\ \end{align*}

Where \(W(x)\) is the Wronskian and \(a\) is the coefficient in front of \(y''\) in the given ODE. The Wronskian is given by \(W= \begin {vmatrix} y_1 & y_{2} \\ y_{1}^{\prime } & y_{2}^{\prime } \end {vmatrix} \). Hence

\[ W = \begin {vmatrix} {\mathrm e}^{-\frac {x^{2}}{2}} & {\mathrm e}^{\frac {x^{2}}{2}} \\ \frac {d}{dx}\left ({\mathrm e}^{-\frac {x^{2}}{2}}\right ) & \frac {d}{dx}\left ({\mathrm e}^{\frac {x^{2}}{2}}\right ) \end {vmatrix} \]

Which gives

\[ W = \begin {vmatrix} {\mathrm e}^{-\frac {x^{2}}{2}} & {\mathrm e}^{\frac {x^{2}}{2}} \\ -x \,{\mathrm e}^{-\frac {x^{2}}{2}} & x \,{\mathrm e}^{\frac {x^{2}}{2}} \end {vmatrix} \]

Therefore

\[ W = \left ({\mathrm e}^{-\frac {x^{2}}{2}}\right )\left (x \,{\mathrm e}^{\frac {x^{2}}{2}}\right ) - \left ({\mathrm e}^{\frac {x^{2}}{2}}\right )\left (-x \,{\mathrm e}^{-\frac {x^{2}}{2}}\right ) \]

Which simplifies to

\[ W = 2 \,{\mathrm e}^{-\frac {x^{2}}{2}} x \,{\mathrm e}^{\frac {x^{2}}{2}} \]

Which simplifies to

\[ W = 2 x \]

Therefore Eq. (2) becomes

\[ u_1 = -\int \frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{3}+\frac {1}{x}\right )}{2 x}\,dx \]

Which simplifies to

\[ u_1 = - \int \frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{4}+1\right )}{2 x^{2}}d x \]

Hence

\[ u_1 = -\frac {\left (x^{2}-1\right ) {\mathrm e}^{\frac {x^{2}}{2}}}{2 x} \]

And Eq. (3) becomes

\[ u_2 = \int \frac {{\mathrm e}^{-\frac {x^{2}}{2}} \left (x^{3}+\frac {1}{x}\right )}{2 x}\,dx \]

Which simplifies to

\[ u_2 = \int \frac {{\mathrm e}^{-\frac {x^{2}}{2}} \left (x^{4}+1\right )}{2 x^{2}}d x \]

Hence

\[ u_2 = -\frac {\left (x^{2}+1\right ) {\mathrm e}^{-\frac {x^{2}}{2}}}{2 x} \]

Therefore the particular solution, from equation (1) is

\[ y_p(x) = -\frac {\left (x^{2}-1\right ) {\mathrm e}^{\frac {x^{2}}{2}} {\mathrm e}^{-\frac {x^{2}}{2}}}{2 x}-\frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{2}+1\right ) {\mathrm e}^{-\frac {x^{2}}{2}}}{2 x} \]

Which simplifies to

\[ y_p(x) = -x \]

Therefore the general solution is

\begin{align*} y &= y_h + y_p \\ &= \left ({\mathrm e}^{\frac {x^{2}}{2}} c_1 +{\mathrm e}^{-\frac {x^{2}}{2}} c_2\right ) + \left (-x\right ) \\ \end{align*}

Summary of solutions found

\begin{align*} y &= {\mathrm e}^{\frac {x^{2}}{2}} c_1 +{\mathrm e}^{-\frac {x^{2}}{2}} c_2 -x \\ \end{align*}

Solved as second order Bessel ode

Time used: 0.315 (sec)

Solve

\begin{align*} y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2}-x^{3}-\frac {1}{x}&=0 \\ \end{align*}

Writing the ode as

\begin{align*} x^{2} y^{\prime \prime }-y^{\prime } x -x^{4} y = x \left (x^{4}+1\right )\tag {1} \end{align*}

Let the solution be

\begin{align*} y &= y_h + y_p \end{align*}

Where \(y_h\) is the solution to the homogeneous ODE and \(y_p\) is a particular solution to the non-homogeneous ODE. Bessel ode has the form

\begin{align*} x^{2} y^{\prime \prime }+y^{\prime } x +\left (-n^{2}+x^{2}\right ) y = 0\tag {2} \end{align*}

The generalized form of Bessel ode is given by Bowman (1958) as the following

\begin{align*} x^{2} y^{\prime \prime }+\left (1-2 \alpha \right ) x y^{\prime }+\left (\beta ^{2} \gamma ^{2} x^{2 \gamma }-n^{2} \gamma ^{2}+\alpha ^{2}\right ) y = 0\tag {3} \end{align*}

With the standard solution

\begin{align*} y&=x^{\alpha } \left (c_3 \operatorname {BesselJ}\left (n , \beta \,x^{\gamma }\right )+c_4 \operatorname {BesselY}\left (n , \beta \,x^{\gamma }\right )\right )\tag {4} \end{align*}

Comparing (3) to (1) and solving for \(\alpha ,\beta ,n,\gamma \) gives

\begin{align*} \alpha &= 1\\ \beta &= \frac {i}{2}\\ n &= {\frac {1}{2}}\\ \gamma &= 2 \end{align*}

Substituting all the above into (4) gives the solution as

\begin{align*} y = \frac {2 i c_3 x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}-\frac {2 c_4 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \end{align*}

Therefore the homogeneous solution \(y_h\) is

\[ y_h = \frac {2 i c_3 x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}-\frac {2 c_4 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \]

The particular solution \(y_p\) can be found using either the method of undetermined coefficients, or the method of variation of parameters. The method of variation of parameters will be used as it is more general and can be used when the coefficients of the ODE depend on \(x\) as well. Let

\begin{equation} \tag{1} y_p(x) = u_1 y_1 + u_2 y_2 \end{equation}

Where \(u_1,u_2\) to be determined, and \(y_1,y_2\) are the two basis solutions (the two linearly independent solutions of the homogeneous ODE) found earlier when solving the homogeneous ODE as

\begin{align*} y_1 &= \frac {2 i x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \\ y_2 &= -\frac {2 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \\ \end{align*}

In the Variation of parameters \(u_1,u_2\) are found using

\begin{align*} \tag{2} u_1 &= -\int \frac {y_2 f(x)}{a W(x)} \\ \tag{3} u_2 &= \int \frac {y_1 f(x)}{a W(x)} \\ \end{align*}

Where \(W(x)\) is the Wronskian and \(a\) is the coefficient in front of \(y''\) in the given ODE. The Wronskian is given by \(W= \begin {vmatrix} y_1 & y_{2} \\ y_{1}^{\prime } & y_{2}^{\prime } \end {vmatrix} \). Hence

\[ W = \begin {vmatrix} \frac {2 i x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} & -\frac {2 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \\ \frac {d}{dx}\left (\frac {2 i x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right ) & \frac {d}{dx}\left (-\frac {2 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right ) \end {vmatrix} \]

Which gives

\[ W = \begin {vmatrix} \frac {2 i x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} & -\frac {2 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \\ \frac {2 i \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}+\frac {2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \left (i x^{2}\right )^{{3}/{2}}}+\frac {2 i x^{2} \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} & -\frac {2 \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}+\frac {2 i x^{2} \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \left (i x^{2}\right )^{{3}/{2}}}-\frac {2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}} \end {vmatrix} \]

Therefore

\[ W = \left (\frac {2 i x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right )\left (-\frac {2 \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}+\frac {2 i x^{2} \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \left (i x^{2}\right )^{{3}/{2}}}-\frac {2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right ) - \left (-\frac {2 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right )\left (\frac {2 i \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}+\frac {2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \left (i x^{2}\right )^{{3}/{2}}}+\frac {2 i x^{2} \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right ) \]

Which simplifies to

\[ W = -\frac {4 x \left (\sinh \left (\frac {x^{2}}{2}\right )^{2}-\cosh \left (\frac {x^{2}}{2}\right )^{2}\right )}{\pi } \]

Which simplifies to

\[ W = \frac {4 x}{\pi } \]

Therefore Eq. (2) becomes

\[ u_1 = -\int \frac {-\frac {2 x^{2} \cosh \left (\frac {x^{2}}{2}\right ) \left (x^{4}+1\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}}{\frac {4 x^{3}}{\pi }}\,dx \]

Which simplifies to

\[ u_1 = - \int -\frac {\sqrt {\pi }\, \cosh \left (\frac {x^{2}}{2}\right ) \left (x^{4}+1\right )}{2 x \sqrt {i x^{2}}}d x \]

Hence

\[ u_1 = -\frac {\sqrt {\pi }\, \left (2 \cosh \left (\frac {x^{2}}{2}\right )-2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )\right )}{4 \sqrt {i x^{2}}} \]

And Eq. (3) becomes

\[ u_2 = \int \frac {\frac {2 i x^{2} \sinh \left (\frac {x^{2}}{2}\right ) \left (x^{4}+1\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}}{\frac {4 x^{3}}{\pi }}\,dx \]

Which simplifies to

\[ u_2 = \int \frac {i \sqrt {\pi }\, \sinh \left (\frac {x^{2}}{2}\right ) \left (x^{4}+1\right )}{2 x \sqrt {i x^{2}}}d x \]

Hence

\[ u_2 = \frac {i \sqrt {\pi }\, \left (2 x^{2} \cosh \left (\frac {x^{2}}{2}\right )-2 \sinh \left (\frac {x^{2}}{2}\right )\right )}{4 \sqrt {i x^{2}}} \]

Therefore the particular solution, from equation (1) is

\[ y_p(x) = -\frac {\left (2 \cosh \left (\frac {x^{2}}{2}\right )-2 x^{2} \sinh \left (\frac {x^{2}}{2}\right )\right ) \sinh \left (\frac {x^{2}}{2}\right )}{2 x}-\frac {\cosh \left (\frac {x^{2}}{2}\right ) \left (2 x^{2} \cosh \left (\frac {x^{2}}{2}\right )-2 \sinh \left (\frac {x^{2}}{2}\right )\right )}{2 x} \]

Which simplifies to

\[ y_p(x) = -x \]

Therefore the general solution is

\begin{align*} y &= y_h + y_p \\ &= \left (\frac {2 i c_3 x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}-\frac {2 c_4 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}\right ) + \left (-x\right ) \\ \end{align*}

Summary of solutions found

\begin{align*} y &= \frac {2 i c_3 x \sinh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}-\frac {2 c_4 x \cosh \left (\frac {x^{2}}{2}\right )}{\sqrt {\pi }\, \sqrt {i x^{2}}}-x \\ \end{align*}

Solved as second order ode using Kovacic algorithm

Time used: 0.356 (sec)

Solve

\begin{align*} y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2}-x^{3}-\frac {1}{x}&=0 \\ \end{align*}

Writing the ode as

\begin{align*} y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2} &= 0 \tag {1} \\ A y^{\prime \prime } + B y^{\prime } + C y &= 0 \tag {2} \end{align*}

Comparing (1) and (2) shows that

\begin{align*} A &= 1 \\ B &= -\frac {1}{x}\tag {3} \\ C &= -x^{2} \end{align*}

Applying the Liouville transformation on the dependent variable gives

\begin{align*} z(x) &= y e^{\int \frac {B}{2 A} \,dx} \end{align*}

Then (2) becomes

\begin{align*} z''(x) = r z(x)\tag {4} \end{align*}

Where \(r\) is given by

\begin{align*} r &= \frac {s}{t}\tag {5} \\ &= \frac {2 A B' - 2 B A' + B^2 - 4 A C}{4 A^2} \end{align*}

Substituting the values of \(A,B,C\) from (3) in the above and simplifying gives

\begin{align*} r &= \frac {4 x^{4}+3}{4 x^{2}}\tag {6} \end{align*}

Comparing the above to (5) shows that

\begin{align*} s &= 4 x^{4}+3\\ t &= 4 x^{2} \end{align*}

Therefore eq. (4) becomes

\begin{align*} z''(x) &= \left ( \frac {4 x^{4}+3}{4 x^{2}}\right ) z(x)\tag {7} \end{align*}

Equation (7) is now solved. After finding \(z(x)\) then \(y\) is found using the inverse transformation

\begin{align*} y &= z \left (x \right ) e^{-\int \frac {B}{2 A} \,dx} \end{align*}

The first step is to determine the case of Kovacic algorithm this ode belongs to. There are 3 cases depending on the order of poles of \(r\) and the order of \(r\) at \(\infty \). The following table summarizes these cases.

Case	Allowed pole order for \(r\)	Allowed value for \(\mathcal {O}(\infty )\)
1	\(\left \{ 0,1,2,4,6,8,\cdots \right \} \)	\(\left \{ \cdots ,-6,-4,-2,0,2,3,4,5,6,\cdots \right \} \)
2	Need to have at least one pole that is either order \(2\) or odd order greater than \(2\). Any other pole order is allowed as long as the above condition is satisfied. Hence the following set of pole orders are all allowed. \(\{1,2\}\),\(\{1,3\}\),\(\{2\}\),\(\{3\}\),\(\{3,4\}\),\(\{1,2,5\}\).	no condition
3	\(\left \{ 1,2\right \} \)	\(\left \{ 2,3,4,5,6,7,\cdots \right \} \)

Table 2.41: Necessary conditions for each Kovacic case

The order of \(r\) at \(\infty \) is the degree of \(t\) minus the degree of \(s\). Therefore

\begin{align*} O\left (\infty \right ) &= \text {deg}(t) - \text {deg}(s) \\ &= 2 - 4 \\ &= -2 \end{align*}

The poles of \(r\) in eq. (7) and the order of each pole are determined by solving for the roots of \(t=4 x^{2}\). There is a pole at \(x=0\) of order \(2\). Since there is no odd order pole larger than \(2\) and the order at \(\infty \) is \(-2\) then the necessary conditions for case one are met. Since there is a pole of order \(2\) then necessary conditions for case two are met. Therefore

\begin{align*} L &= [1, 2] \end{align*}

Attempting to find a solution using case \(n=1\).

Looking at poles of order 2. The partial fractions decomposition of \(r\) is

\[ r = \frac {3}{4 x^{2}}+x^{2} \]

For the pole at \(x=0\) let \(b\) be the coefficient of \(\frac {1}{ x^{2}}\) in the partial fractions decomposition of \(r\) given above. Therefore \(b={\frac {3}{4}}\). Hence

\begin{alignat*}{2} [\sqrt r]_c &= 0 \\ \alpha _c^{+} &= \frac {1}{2} + \sqrt {1+4 b} &&= {\frac {3}{2}}\\ \alpha _c^{-} &= \frac {1}{2} - \sqrt {1+4 b} &&= -{\frac {1}{2}} \end{alignat*}

Since the order of \(r\) at \(\infty \) is \(O_r(\infty ) = -2\) then

\begin{alignat*}{3} v &= \frac {-O_r(\infty )}{2} &&= \frac {2}{2} &&= 1 \end{alignat*}

\([\sqrt r]_\infty \) is the sum of terms involving \(x^i\) for \(0\leq i \leq v\) in the Laurent series for \(\sqrt r\) at \(\infty \). Therefore

\begin{align*} [\sqrt r]_\infty &= \sum _{i=0}^{v} a_i x^i \\ &= \sum _{i=0}^{1} a_i x^i \tag {8} \end{align*}

Let \(a\) be the coefficient of \(x^v=x^1\) in the above sum. The Laurent series of \(\sqrt r\) at \(\infty \) is

\begin{equation} \tag{9} \sqrt r \approx x +\frac {3}{8 x^{3}}-\frac {9}{128 x^{7}}+\frac {27}{1024 x^{11}}-\frac {405}{32768 x^{15}}+\frac {1701}{262144 x^{19}}-\frac {15309}{4194304 x^{23}}+\frac {72171}{33554432 x^{27}} + \dots \end{equation}

Comparing Eq. (9) with Eq. (8) shows that

\[ a = 1 \]

From Eq. (9) the sum up to \(v=1\) gives

\begin{align*} [\sqrt r]_\infty &= \sum _{i=0}^{1} a_i x^i \\ &= x \tag {10} \end{align*}

Now we need to find \(b\), where \(b\) be the coefficient of \(x^{v-1} = x^{0}=1\) in \(r\) minus the coefficient of same term but in \(\left ( [\sqrt r]_\infty \right )^2 \) where \([\sqrt r]_\infty \) was found above in Eq (10). Hence

\[ \left ( [\sqrt r]_\infty \right )^2 = x^{2} \]

This shows that the coefficient of \(1\) in the above is \(0\). Now we need to find the coefficient of \(1\) in \(r\). How this is done depends on if \(v=0\) or not. Since \(v=1\) which is not zero, then starting \(r=\frac {s}{t}\), we do long division and write this in the form

\[ r = Q + \frac {R}{t} \]

Where \(Q\) is the quotient and \(R\) is the remainder. Then the coefficient of \(1\) in \(r\) will be the coefficient this term in the quotient. Doing long division gives

\begin{align*} r &= \frac {s}{t} \\ &= \frac {4 x^{4}+3}{4 x^{2}} \\ &= Q + \frac {R}{4 x^{2}} \\ &= \left (x^{2}\right ) + \left ( \frac {3}{4 x^{2}}\right ) \\ &= \frac {3}{4 x^{2}}+x^{2} \end{align*}

We see that the coefficient of the term \(x\) in the quotient is \(0\). Now \(b\) can be found.

\begin{align*} b &= \left (0\right )-\left (0\right )\\ &= 0 \end{align*}

Hence

\begin{alignat*}{3} [\sqrt r]_\infty &= x\\ \alpha _{\infty }^{+} &= \frac {1}{2} \left ( \frac {b}{a} - v \right ) &&= \frac {1}{2} \left ( \frac {0}{1} - 1 \right ) &&= -{\frac {1}{2}}\\ \alpha _{\infty }^{-} &= \frac {1}{2} \left ( -\frac {b}{a} - v \right ) &&= \frac {1}{2} \left ( -\frac {0}{1} - 1 \right ) &&= -{\frac {1}{2}} \end{alignat*}

The following table summarizes the findings so far for poles and for the order of \(r\) at \(\infty \) where \(r\) is

\[ r=\frac {4 x^{4}+3}{4 x^{2}} \]

pole \(c\) location	pole order	\([\sqrt r]_c\)	\(\alpha _c^{+}\)	\(\alpha _c^{-}\)
\(0\)	\(2\)	\(0\)	\(\frac {3}{2}\)	\(-{\frac {1}{2}}\)

Order of \(r\) at \(\infty \)	\([\sqrt r]_\infty \)	\(\alpha _\infty ^{+}\)	\(\alpha _\infty ^{-}\)
\(-2\)	\(x\)	\(-{\frac {1}{2}}\)	\(-{\frac {1}{2}}\)

Now that the all \([\sqrt r]_c\) and its associated \(\alpha _c^{\pm }\) have been determined for all the poles in the set \(\Gamma \) and \([\sqrt r]_\infty \) and its associated \(\alpha _\infty ^{\pm }\) have also been found, the next step is to determine possible non negative integer \(d\) from these using

\begin{align*} d &= \alpha _\infty ^{s(\infty )} - \sum _{c \in \Gamma } \alpha _c^{s(c)} \end{align*}

Where \(s(c)\) is either \(+\) or \(-\) and \(s(\infty )\) is the sign of \(\alpha _\infty ^{\pm }\). This is done by trial over all set of families \(s=(s(c))_{c \in \Gamma \cup {\infty }}\) until such \(d\) is found to work in finding candidate \(\omega \). Trying \(\alpha _\infty ^{-} = -{\frac {1}{2}}\) then

\begin{align*} d &= \alpha _\infty ^{-} - \left ( \alpha _{c_1}^{-} \right ) \\ &= -{\frac {1}{2}} - \left ( -{\frac {1}{2}} \right ) \\ &= 0 \end{align*}

Since \(d\) an integer and \(d \geq 0\) then it can be used to find \(\omega \) using

\begin{align*} \omega &= \sum _{c \in \Gamma } \left ( s(c) [\sqrt r]_c + \frac {\alpha _c^{s(c)}}{x-c} \right ) + s(\infty ) [\sqrt r]_\infty \end{align*}

The above gives

\begin{align*} \omega &= \left ( (-)[\sqrt r]_{c_1} + \frac { \alpha _{c_1}^{-} }{x- c_1}\right ) + (-) [\sqrt r]_\infty \\ &= -\frac {1}{2 x} + (-) \left ( x \right ) \\ &= -\frac {1}{2 x}-x\\ &= -\frac {1}{2 x}-x \end{align*}

Now that \(\omega \) is determined, the next step is find a corresponding minimal polynomial \(p(x)\) of degree \(d=0\) to solve the ode. The polynomial \(p(x)\) needs to satisfy the equation

\begin{align*} p'' + 2 \omega p' + \left ( \omega ' +\omega ^2 -r\right ) p = 0 \tag {1A} \end{align*}

Let

\begin{align*} p(x) &= 1\tag {2A} \end{align*}

Substituting the above in eq. (1A) gives

\begin{align*} \left (0\right ) + 2 \left (-\frac {1}{2 x}-x\right ) \left (0\right ) + \left ( \left (\frac {1}{2 x^{2}}-1\right ) + \left (-\frac {1}{2 x}-x\right )^2 - \left (\frac {4 x^{4}+3}{4 x^{2}}\right ) \right ) &= 0\\ 0 = 0 \end{align*}

The equation is satisfied since both sides are zero. Therefore the first solution to the ode \(z'' = r z\) is

\begin{align*} z_1(x) &= p e^{ \int \omega \,dx} \\ &= {\mathrm e}^{\int \left (-\frac {1}{2 x}-x \right )d x}\\ &= \frac {{\mathrm e}^{-\frac {x^{2}}{2}}}{\sqrt {x}} \end{align*}

The first solution to the original ode in \(y\) is found from

\begin{align*} y_1 &= z_1 e^{ \int -\frac {1}{2} \frac {B}{A} \,dx} \\ &= z_1 e^{ -\int \frac {1}{2} \frac {-\frac {1}{x}}{1} \,dx} \\ &= z_1 e^{\frac {\ln \left (x \right )}{2}} \\ &= z_1 \left (\sqrt {x}\right ) \\ \end{align*}

Which simplifies to

\[ y_1 = {\mathrm e}^{-\frac {x^{2}}{2}} \]

The second solution \(y_2\) to the original ode is found using reduction of order

\[ y_2 = y_1 \int \frac { e^{\int -\frac {B}{A} \,dx}}{y_1^2} \,dx \]

Substituting gives

\begin{align*} y_2 &= y_1 \int \frac { e^{\int -\frac {-\frac {1}{x}}{1} \,dx}}{\left (y_1\right )^2} \,dx \\ &= y_1 \int \frac { e^{\ln \left (x \right )}}{\left (y_1\right )^2} \,dx \\ &= y_1 \left (\frac {{\mathrm e}^{x^{2}}}{2}\right ) \\ \end{align*}

Therefore the solution is

\begin{align*} y &= c_1 y_1 + c_2 y_2 \\ &= c_1 \left ({\mathrm e}^{-\frac {x^{2}}{2}}\right ) + c_2 \left ({\mathrm e}^{-\frac {x^{2}}{2}}\left (\frac {{\mathrm e}^{x^{2}}}{2}\right )\right ) \\ \end{align*}

This is second order nonhomogeneous ODE. Let the solution be

\[ y = y_h + y_p \]

Where \(y_h\) is the solution to the homogeneous ODE \( A y''(x) + B y'(x) + C y(x) = 0\), and \(y_p\) is a particular solution to the nonhomogeneous ODE \(A y''(x) + B y'(x) + C y(x) = f(x)\). \(y_h\) is the solution to

\[ y^{\prime \prime }-\frac {y^{\prime }}{x}-y x^{2} = 0 \]

The homogeneous solution is found using the Kovacic algorithm which results in

\[ y_h = c_1 \,{\mathrm e}^{-\frac {x^{2}}{2}}+\frac {c_2 \,{\mathrm e}^{\frac {x^{2}}{2}}}{2} \]

The particular solution \(y_p\) can be found using either the method of undetermined coefficients, or the method of variation of parameters. The method of variation of parameters will be used as it is more general and can be used when the coefficients of the ODE depend on \(x\) as well. Let

\begin{equation} \tag{1} y_p(x) = u_1 y_1 + u_2 y_2 \end{equation}

Where \(u_1,u_2\) to be determined, and \(y_1,y_2\) are the two basis solutions (the two linearly independent solutions of the homogeneous ODE) found earlier when solving the homogeneous ODE as

\begin{align*} y_1 &= {\mathrm e}^{-\frac {x^{2}}{2}} \\ y_2 &= \frac {{\mathrm e}^{\frac {x^{2}}{2}}}{2} \\ \end{align*}

In the Variation of parameters \(u_1,u_2\) are found using

\begin{align*} \tag{2} u_1 &= -\int \frac {y_2 f(x)}{a W(x)} \\ \tag{3} u_2 &= \int \frac {y_1 f(x)}{a W(x)} \\ \end{align*}

Where \(W(x)\) is the Wronskian and \(a\) is the coefficient in front of \(y''\) in the given ODE. The Wronskian is given by \(W= \begin {vmatrix} y_1 & y_{2} \\ y_{1}^{\prime } & y_{2}^{\prime } \end {vmatrix} \). Hence

\[ W = \begin {vmatrix} {\mathrm e}^{-\frac {x^{2}}{2}} & \frac {{\mathrm e}^{\frac {x^{2}}{2}}}{2} \\ \frac {d}{dx}\left ({\mathrm e}^{-\frac {x^{2}}{2}}\right ) & \frac {d}{dx}\left (\frac {{\mathrm e}^{\frac {x^{2}}{2}}}{2}\right ) \end {vmatrix} \]

Which gives

\[ W = \begin {vmatrix} {\mathrm e}^{-\frac {x^{2}}{2}} & \frac {{\mathrm e}^{\frac {x^{2}}{2}}}{2} \\ -x \,{\mathrm e}^{-\frac {x^{2}}{2}} & \frac {x \,{\mathrm e}^{\frac {x^{2}}{2}}}{2} \end {vmatrix} \]

Therefore

\[ W = \left ({\mathrm e}^{-\frac {x^{2}}{2}}\right )\left (\frac {x \,{\mathrm e}^{\frac {x^{2}}{2}}}{2}\right ) - \left (\frac {{\mathrm e}^{\frac {x^{2}}{2}}}{2}\right )\left (-x \,{\mathrm e}^{-\frac {x^{2}}{2}}\right ) \]

Which simplifies to

\[ W = {\mathrm e}^{-\frac {x^{2}}{2}} x \,{\mathrm e}^{\frac {x^{2}}{2}} \]

Which simplifies to

\[ W = x \]

Therefore Eq. (2) becomes

\[ u_1 = -\int \frac {\frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{3}+\frac {1}{x}\right )}{2}}{x}\,dx \]

Which simplifies to

\[ u_1 = - \int \frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{4}+1\right )}{2 x^{2}}d x \]

Hence

\[ u_1 = -\frac {\left (x^{2}-1\right ) {\mathrm e}^{\frac {x^{2}}{2}}}{2 x} \]

And Eq. (3) becomes

\[ u_2 = \int \frac {{\mathrm e}^{-\frac {x^{2}}{2}} \left (x^{3}+\frac {1}{x}\right )}{x}\,dx \]

Which simplifies to

\[ u_2 = \int \frac {{\mathrm e}^{-\frac {x^{2}}{2}} \left (x^{4}+1\right )}{x^{2}}d x \]

Hence

\[ u_2 = -\frac {\left (x^{2}+1\right ) {\mathrm e}^{-\frac {x^{2}}{2}}}{x} \]

Therefore the particular solution, from equation (1) is

\[ y_p(x) = -\frac {\left (x^{2}-1\right ) {\mathrm e}^{\frac {x^{2}}{2}} {\mathrm e}^{-\frac {x^{2}}{2}}}{2 x}-\frac {{\mathrm e}^{\frac {x^{2}}{2}} \left (x^{2}+1\right ) {\mathrm e}^{-\frac {x^{2}}{2}}}{2 x} \]

Which simplifies to

\[ y_p(x) = -x \]

Therefore the general solution is

\begin{align*} y &= y_h + y_p \\ &= \left (c_1 \,{\mathrm e}^{-\frac {x^{2}}{2}}+\frac {c_2 \,{\mathrm e}^{\frac {x^{2}}{2}}}{2}\right ) + \left (-x\right ) \\ \end{align*}

Summary of solutions found

\begin{align*} y &= -x +c_1 \,{\mathrm e}^{-\frac {x^{2}}{2}}+\frac {c_2 \,{\mathrm e}^{\frac {x^{2}}{2}}}{2} \\ \end{align*}

✓ Maple. Time used: 0.002 (sec). Leaf size: 24

ode:=diff(diff(y(x),x),x)-1/x*diff(y(x),x)-x^2*y(x)-x^3-1/x = 0; 
dsolve(ode,y(x), singsol=all);
 

\[ y = \sinh \left (\frac {x^{2}}{2}\right ) c_2 +\cosh \left (\frac {x^{2}}{2}\right ) c_1 -x \]

Maple trace

Methods for second order ODEs: 
--- Trying classification methods --- 
trying a quadrature 
trying high order exact linear fully integrable 
trying differential order: 2; linear nonhomogeneous with symmetry [0,1] 
trying a double symmetry of the form [xi=0, eta=F(x)] 
-> Try solving first the homogeneous part of the ODE 
   checking if the LODE has constant coefficients 
   checking if the LODE is of Euler type 
   trying a symmetry of the form [xi=0, eta=F(x)] 
   <- linear_1 successful 
<- solving first the homogeneous part of the ODE successful
 

✓ Mathematica. Time used: 0.083 (sec). Leaf size: 110

ode=D[y[x],{x,2}]-1/x*D[y[x],x]-x^2*y[x]-x^3-1/x==0; 
ic={}; 
DSolve[{ode,ic},y[x],x,IncludeSingularSolutions->True]
 

\begin{align*} y(x)&\to \cosh \left (\frac {x^2}{2}\right ) \int _1^x-\frac {\left (K[1]^4+1\right ) \sinh \left (\frac {K[1]^2}{2}\right )}{K[1]^2}dK[1]+i \sinh \left (\frac {x^2}{2}\right ) \int _1^x-\frac {i \cosh \left (\frac {K[2]^2}{2}\right ) \left (K[2]^4+1\right )}{K[2]^2}dK[2]+c_1 \cosh \left (\frac {x^2}{2}\right )+i c_2 \sinh \left (\frac {x^2}{2}\right ) \end{align*}

✗ Sympy

from sympy import * 
x = symbols("x") 
y = Function("y") 
ode = Eq(-x**3 - x**2*y(x) + Derivative(y(x), (x, 2)) - Derivative(y(x), x)/x - 1/x,0) 
ics = {} 
dsolve(ode,func=y(x),ics=ics)
 

NotImplementedError : The given ODE x**4 + x**3*y(x) - x*Derivative(y(x), (x, 2)) + Derivative(y(x), x) + 1 cannot be solved by the factorable group method