2.15.1 Problem 10

Internal problem ID [13427]
Book : Handbook of exact solutions for ordinary differential equations. By Polyanin and Zaitsev. Second edition
Section : Chapter 1, section 1.2. Riccati Equation. subsection 1.2.7-2. Equations containing arccosine.
Problem number : 10
Date solved : Sunday, January 18, 2026 at 08:07:57 PM
CAS classification : [_Riccati]

2.15.1.1 Solved using first_order_ode_riccati_by_guessing_particular_solution

1.640 (sec)

Entering first order ode riccati guess solver

\begin{align*} y^{\prime }&=y^{2}+\lambda \arccos \left (x \right )^{n} y-a^{2}+a \lambda \arccos \left (x \right )^{n} \\ \end{align*}

This is a Riccati ODE. Comparing the above ODE to solve with the Riccati standard form

\[ y' = f_0(x)+ f_1(x)y+f_2(x)y^{2} \]

Shows that

\begin{align*} f_0(x) & =a \lambda \arccos \left (x \right )^{n}-a^{2}\\ f_1(x) & =\arccos \left (x \right )^{n} \lambda \\ f_2(x) &=1 \end{align*}

Using trial and error, the following particular solution was found

\[ y_p = -a \]

Since a particular solution is known, then the general solution is given by

\begin{align*} y &= y_p + \frac { \phi (x) }{ c_1 - \int { \phi (x) f_2 \,dx} } \end{align*}

Where

\begin{align*} \phi (x) &= e^{ \int 2 f_2 y_p + f_1 \,dx } \end{align*}

Evaluating the above gives the general solution as

\[ y = -a +\frac {{\mathrm e}^{\int \left (\arccos \left (x \right )^{n} \lambda -2 a \right )d x}}{c_1 -\int {\mathrm e}^{\int \left (\arccos \left (x \right )^{n} \lambda -2 a \right )d x}d x} \]

Summary of solutions found

\begin{align*} y &= -a +\frac {{\mathrm e}^{\int \left (\arccos \left (x \right )^{n} \lambda -2 a \right )d x}}{c_1 -\int {\mathrm e}^{\int \left (\arccos \left (x \right )^{n} \lambda -2 a \right )d x}d x} \\ \end{align*}

2.15.1.2 ✓ Maple. Time used: 0.006 (sec). Leaf size: 386

ode:=diff(y(x),x) = y(x)^2+lambda*arccos(x)^n*y(x)-a^2+a*lambda*arccos(x)^n; 
dsolve(ode,y(x), singsol=all);
 

\[ \text {Expression too large to display} \]

Maple trace

Methods for first order ODEs: 
--- Trying classification methods --- 
trying a quadrature 
trying 1st order linear 
trying Bernoulli 
trying separable 
trying inverse linear 
trying homogeneous types: 
trying Chini 
differential order: 1; looking for linear symmetries 
trying exact 
Looking for potential symmetries 
trying Riccati 
trying Riccati sub-methods: 
   trying Riccati_symmetries 
   trying Riccati to 2nd Order 
   -> Calling odsolve with the ODE, diff(diff(y(x),x),x) = lambda*arccos(x)^n* 
diff(y(x),x)+(a^2-a*lambda*arccos(x)^n)*y(x), y(x) 
      *** Sublevel 2 *** 
      Methods for second order ODEs: 
      --- Trying classification methods --- 
      trying a symmetry of the form [xi=0, eta=F(x)] 
      checking if the LODE is missing y 
      -> Heun: Equivalence to the GHE or one of its 4 confluent cases under a \ 
power @ Moebius 
      -> trying a solution of the form r0(x) * Y + r1(x) * Y where Y = exp(int\ 
(r(x), dx)) * 2F1([a1, a2], [b1], f) 
      -> Trying changes of variables to rationalize or make the ODE simpler 
      <- unable to find a useful change of variables 
         trying a symmetry of the form [xi=0, eta=F(x)] 
         trying 2nd order exact linear 
         trying symmetries linear in x and y(x) 
         trying to convert to a linear ODE with constant coefficients 
         trying 2nd order, integrating factor of the form mu(x,y) 
         trying a symmetry of the form [xi=0, eta=F(x)] 
         checking if the LODE is missing y 
         -> Heun: Equivalence to the GHE or one of its 4 confluent cases under \ 
a power @ Moebius 
         -> trying a solution of the form r0(x) * Y + r1(x) * Y where Y = exp(\ 
int(r(x), dx)) * 2F1([a1, a2], [b1], f) 
         -> Trying changes of variables to rationalize or make the ODE simpler 
         <- unable to find a useful change of variables 
            trying a symmetry of the form [xi=0, eta=F(x)] 
         trying to convert to an ODE of Bessel type 
   -> Trying a change of variables to reduce to Bernoulli 
   -> Calling odsolve with the ODE, diff(y(x),x)-(y(x)^2+y(x)+lambda*arccos(x)^ 
n*y(x)*x+x^2*(-a^2+a*lambda*arccos(x)^n))/x, y(x), explicit 
      *** Sublevel 2 *** 
      Methods for first order ODEs: 
      --- Trying classification methods --- 
      trying a quadrature 
      trying 1st order linear 
      trying Bernoulli 
      trying separable 
      trying inverse linear 
      trying homogeneous types: 
      trying Chini 
      differential order: 1; looking for linear symmetries 
      trying exact 
      Looking for potential symmetries 
      trying Riccati 
      trying Riccati sub-methods: 
         trying Riccati_symmetries 
      trying inverse_Riccati 
      trying 1st order ODE linearizable_by_differentiation 
   -> trying a symmetry pattern of the form [F(x)*G(y), 0] 
   -> trying a symmetry pattern of the form [0, F(x)*G(y)] 
   <- symmetry pattern of the form [0, F(x)*G(y)] successful 
   <- Riccati with symmetry pattern of the form [0,F(x)*G(y)] successful
 

Maple step by step

\[ \begin {array}{lll} & {} & \textrm {Let's solve}\hspace {3pt} \\ {} & {} & \frac {d}{d x}y \left (x \right )=y \left (x \right )^{2}+\lambda \arccos \left (x \right )^{13427} y \left (x \right )-a^{2}+a \lambda \arccos \left (x \right )^{13427} \\ \bullet & {} & \textrm {Highest derivative means the order of the ODE is}\hspace {3pt} 1 \\ {} & {} & \frac {d}{d x}y \left (x \right ) \\ \bullet & {} & \textrm {Solve for the highest derivative}\hspace {3pt} \\ {} & {} & \frac {d}{d x}y \left (x \right )=y \left (x \right )^{2}+\lambda \arccos \left (x \right )^{13427} y \left (x \right )-a^{2}+a \lambda \arccos \left (x \right )^{13427} \end {array} \]

2.15.1.3 ✓ Mathematica. Time used: 0.703 (sec). Leaf size: 220

ode=D[y[x],x]==y[x]^2+\[Lambda]*ArcCos[x]^n*y[x]-a^2+a*\[Lambda]*ArcCos[x]^n; 
ic={}; 
DSolve[{ode,ic},y[x],x,IncludeSingularSolutions->True]
 

\[ \text {Solve}\left [\int _1^x-\frac {i \exp \left (-\int _1^{K[2]}\left (2 a-\lambda \arccos (K[1])^n\right )dK[1]\right ) \left (-\lambda \arccos (K[2])^n+a-y(x)\right )}{n \lambda (a+y(x))}dK[2]+\int _1^{y(x)}\left (-\int _1^x\left (\frac {i \exp \left (-\int _1^{K[2]}\left (2 a-\lambda \arccos (K[1])^n\right )dK[1]\right ) \left (-\lambda \arccos (K[2])^n+a-K[3]\right )}{n \lambda (a+K[3])^2}+\frac {i \exp \left (-\int _1^{K[2]}\left (2 a-\lambda \arccos (K[1])^n\right )dK[1]\right )}{n \lambda (a+K[3])}\right )dK[2]-\frac {i \exp \left (-\int _1^x\left (2 a-\lambda \arccos (K[1])^n\right )dK[1]\right )}{n \lambda (a+K[3])^2}\right )dK[3]=c_1,y(x)\right ] \]

2.15.1.4 ✓ Sympy. Time used: 5.313 (sec). Leaf size: 76

from sympy import * 
x = symbols("x") 
a = symbols("a") 
lambda_ = symbols("lambda_") 
n = symbols("n") 
y = Function("y") 
ode = Eq(a**2 - a*lambda_*acos(x)**n - lambda_*y(x)*acos(x)**n - y(x)**2 + Derivative(y(x), x),0) 
ics = {} 
dsolve(ode,func=y(x),ics=ics)
 

\[ y{\left (x \right )} = \frac {\left (- C_{1} a e^{2 a x} + a e^{2 a x} \int e^{- 2 a x} e^{\lambda _{} \int \operatorname {acos}^{n}{\left (x \right )}\, dx}\, dx + e^{\lambda _{} \int \operatorname {acos}^{n}{\left (x \right )}\, dx}\right ) e^{- 2 a x}}{C_{1} - \int e^{- 2 a x} e^{\lambda _{} \int \operatorname {acos}^{n}{\left (x \right )}\, dx}\, dx} \]

Python version: 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] 
Sympy version 1.14.0
 

classify_ode(ode,func=y(x)) 
 
('1st_power_series', 'lie_group')