# Computers and turbulence

## TL;DR

The paper reviews how rapid advances in computer power have transformed turbulence research through three stages, from simulation as experimental substitutes to systematic Monte Carlo theoretical questioning, raising questions about the nature of machine- versus human-generated theories.

## Contribution

It introduces a framework dividing turbulence research evolution into three stages based on computer capabilities and discusses implications for scientific methodology.

## Key findings

- Computers have evolved from expensive simulations to trivial, rapid Monte Carlo tools.
- This evolution allows systematic exploration of theoretical questions independent of established paradigms.
- The paper stimulates discussion on the role of machine-generated theories in scientific research.

## Abstract

This paper briefly reviews the influence that the rapid evolution of computer power in the last decades has had on turbulence research. It is argued that it can be divided into three stages. In the earliest (`heroic') one, simulations were expensive and could at most be considered as substitutes for experiments. Later, as computers grew faster and some meaningful simulations could be performed overnight, it became practical to use them as (`routine') as tools to provide answers to specific theoretical questions. More recently, some turbulence simulations have become trivial, able to run in minutes, and it is possible to think of computers as `Monte Carlo' theory machines, which can be used to systematically pose a wide range of `random' theoretical questions, only to later evaluate which of them are interesting or useful. Although apparently wasteful, it is argued that this procedure has the advantage of being reasonably independence of received wisdom, and thus more able than human researchers to scape established paradigms. The rate of growth of computer power ensures that the interval between consecutive stages is about fifteen years. Rather than offering conclusions, the purpose of the paper is to stimulate discussion on whether machine- and human-generated theories can be considered comparable concepts, and on how the challenges and opportunities created by our new computer `colleagues' can be made to fit into the traditional research process.