On symbolic computation of C.P. Okeke functional equations using Python programming language

Abstract

AbstractThis present paper is inspired by one of the questions posed by Okeke (Results Math 78(96):1-30, 2023, see Remark 2.10b). In particular, we aim to develop a robust computer code based on the theoretical results obtained in Okeke (2023), which determines the polynomial solutions of the following functional equation,$$\begin{aligned} \textstyle \sum \limits _{i=1}^n \gamma _i F(a_i x + b_i y)=\textstyle \sum \limits _{j=1}^m(\alpha _j x + \beta _j y) f(c_j x + d_j y), \end{aligned}$$∑i=1nγiF(aix+biy)=∑j=1m(αjx+βjy)f(cjx+djy),for all$$x,y\in \mathbb {R}$$x,y∈R,$$\gamma _i,\alpha _j,\beta _j \in \mathbb {R},$$γi,αj,βj∈R,and$$a_i,b_i,c_j,d_j \in \mathbb {Q},$$ai,bi,cj,dj∈Q,and their special forms. The primary motivation for writing such a computer code is that solving even simple equations belonging to class (0.1) needs long and tiresome calculations. Therefore, one of the advantages of such a computer code is that it allows us to solve complicated problems quickly, easily, and efficiently. Additionally, the computer code will significantly improve the level of accuracy in calculations. Along with that, there is also the factor of speed. We point out that the computer code will operate with symbolic calculations provided by the programming language Python, which means that it does not contain any numerical or approximate methods, and it yields the exact solutions of the equations considered.