Computing with Polynomial Ordinary Differential Equations

TL;DR

This paper investigates the computational power of polynomial ordinary differential equations (ODEs), establishing their equivalence to Turing machines and proposing a robust notion of time complexity for continuous systems.

Contribution

It demonstrates that polynomial ODEs can serve as a programming model with a well-defined complexity measure, extending the classical GPAC model and confirming its computational equivalence to Turing machines.

Findings

Polynomial ODEs are equivalent to Turing machines in computational power.

A robust, equivalent notion of time complexity for polynomial ODE computations is established.

Polynomial ODEs can be used as a programming framework with consistent complexity measures.

Abstract

In 1941, Claude Shannon introduced the General Purpose Analog Computer(GPAC) as a mathematical model of Differential Analysers, that is to say as a model of continuous-time analog (mechanical, and later one electronic) machines of that time. Following Shannon's arguments, functions generated by GPACs must be differentially algebraic. As it is known that some computable functions like Euler's $\Gamma(x)=\int_{0}^{\infty}t^{x-1}e^{-t}dt$ or Riemann's Zeta function $\zeta(x)=\sum_{k=0}^\infty \frac1{k^x}$ are not differentially algebraic, this argument has been often used to demonstrate in the past that the GPAC is less powerful than digital computation. It was proved in JOC2007, that if a more modern notion of computation is considered, i.e. in particular if computability is not restricted to real-time generation of functions, the GPAC is actually equivalent to Turing machines. Our purpose is first to discuss the robustness of the notion of computation involved in JOC2007, by establishing that natural variants of the notion of computation from this paper leads to the same computability result. Second, to go considerations about (time) complexity, we explore several natural variants for measuring time/space complexity of a computation. Rather surprisingly, whereas defining a robust time complexity for general continuous time systems is a well known open problem, we prove that all variants are actually equivalent even at the complexity level. As a consequence, it seems that a robust and well defined notion of time complexity exists for the GPAC, or equivalently for computations by polynomial ordinary differential equations. Another side effect of our proof is also that we show in some way that polynomial ordinary differential equations can be used as a kind of programming model, and that there is a rather nice and robust notion of ODE programming.