Internal
problem
ID
[13965]
Book
:
Handbook
of
exact
solutions
for
ordinary
differential
equations.
By
Polyanin
and
Zaitsev.
Second
edition
Section
:
Chapter
2,
Second-Order
Differential
Equations.
section
2.1.3-1.
Equations
with
exponential
functions
Problem
number
:
41
Date
solved
:
Friday, December 19, 2025 at 08:54:36 PM
CAS
classification
:
[[_2nd_order, _with_linear_symmetries]]
ode:=(a*exp(lambda*x)+b)*diff(diff(y(x),x),x)+(c*exp(lambda*x)+d)*diff(y(x),x)+(n*exp(lambda*x)+m)*y(x) = 0; dsolve(ode,y(x), singsol=all);
Maple trace
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 trying a quadrature 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)] checking if the LODE is missing y -> Trying a Liouvillian solution using Kovacics algorithm <- No Liouvillian solutions exists -> Trying a solution in terms of special functions: -> Bessel -> elliptic -> Legendre -> Kummer -> hyper3: Equivalence to 1F1 under a power @ Moebius -> hypergeometric -> heuristic approach <- heuristic approach successful <- hypergeometric successful <- special function solution successful Change of variables used: [x = ln(t)/lambda] Linear ODE actually solved: (n*t+m)*u(t)+(a*lambda^2*t^2+b*lambda^2*t+c*lambda*t^2+d*lambda*t)*diff(u\ (t),t)+(a*lambda^2*t^3+b*lambda^2*t^2)*diff(diff(u(t),t),t) = 0 <- change of variables successful
ode=(a*Exp[\[Lambda]*x]+b)*D[y[x],{x,2}]+(c*Exp[\[Lambda]*x]+d)*D[y[x],x]+(n*Exp[\[Lambda]*x]+m)*y[x]==0; ic={}; DSolve[{ode,ic},y[x],x,IncludeSingularSolutions->True]
from sympy import * x = symbols("x") a = symbols("a") b = symbols("b") c = symbols("c") d = symbols("d") n = symbols("n") m = symbols("m") lambda_ = symbols("lambda_") y = Function("y") ode = Eq((m + n*exp(lambda_*x))*y(x) + (a*exp(lambda_*x) + b)*Derivative(y(x), (x, 2)) + (c*exp(lambda_*x) + d)*Derivative(y(x), x),0) ics = {} dsolve(ode,func=y(x),ics=ics)
False
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)) ('factorable', '2nd_power_series_ordinary')