Chaotic Curiosity or Curios Chaos

Chaotic Curiosity or Curios Chaos Abhishek Tiwari The word science comes from â€Å" scientia †, Latin word for knowledge. Webster’s dictionary defines science as â€Å"the knowledge covering the general truths of the operations of general laws, especially as obtained and tested through the scientific method and concerned with the physical world†. In a layman’s interpretation science is a systematic way to obtain the knowledge about the mystifying secrets of Mother Nature by few known facts, observations, and few approximate estimations. New theories and laws in science are proposed by using two points- 1) repetition or reproducibility of the data, and 2) computational simulation. But what happens if these fundamental rules are not followed in a system? As they say, exceptions to rules form new rules, these infringing systems fall into the category of â€Å"Chaotic systems†. Chaotic systems are those in which the distant results are practically unknowable. The Theory of Chaos r ules this domain of science. Today chaos theory is a field of study in mathematics with several applications in the fields of biology, cosmology, economics, engineering, meteorology, and physics. It talks about deterministic dynamic systems which are not just highly but infinitely sensitive to the initial conditions. Under such circumstances even with a fraction of difference in the initial stages would yield into complete different outcomes every time the process is started hence defying the first basic rule in experimentation. Every technology is built with its own error, limitations and approximation, and therefore computer simulation of such a dynamic system to know about its fate at certain point in space-time would either require a huge amount of initially defined components or a long time calculations which would still differ with the actual outcome. In other words the deterministic nature of such dynamic systems may not help in determining their future. Meteorologist Edward Lorenz was the first person to talk about chaotic systems. He summarized this theory as, â€Å"when the present determines the future, but the approximate present does not approximately determines the future†. In 1972 Edward Lorenz wrote a paper titled as â€Å"Predictability: Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?† on the theory of Chaos. Edward Lorenz accidentally came across this topic while doing his work on weather forecast. Using a simple computer of his time, he was running a weather simulation. However due to time constraints he started his work mid way and to his astonishment he got a completely diverted results from the previous output. He concluded that the difference was generated due to the rounding-off of the numbers in the input. The consensus of the difference should practically have no effect on the immediate prediction but in a long run produced a significant difference. The word chaos is generally taken as c omplete disarray is a misnomer for this theory. The chaotic systems are not cluttered but are disciplined to an extent. Like we know for sure that the moon would not collide with earth in few weeks but the prediction remains uncertain for a longer time period. Similarly weather forecasts are known most accurately about a week before. Therefore chaotic systems are predictable for a while but later on with time it becomes random. The effectiveness of our prediction can be determined by following factors:-