Butterfly effect
.
In chaos theory, the butterfly effect is the sensitive
dependence on initial conditions, where a small change at one place in a
deterministic nonlinear
system can result in
large differences to a later state. The name of the effect, coined by Edward Lorenz, is derived from the theoretical
example of a hurricane's formation being contingent on whether or not a distant
butterfly had flapped its wings several weeks before.
Although the
butterfly effect may appear to be an esoteric and unlikely behavior, it is
exhibited by very simple systems: for example, a ball placed at the crest of a
hill may roll into any of several valleys depending on, among other things,
slight differences in initial position.
The butterfly
effect is a common trope in fiction when presenting scenarios
involving time
travel and with
hypotheses where one storyline diverges at the moment of a seemingly minor
event resulting in two significantly different outcomes.
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Origin of the concept and the term
Chaos
theory and the
sensitive dependence on initial conditions was described in the literature in a
particular case of the three-body
problem by Henri Poincaré in 1890.[1] He later proposed that such phenomena
could be common, for example, in meteorology.[citation needed]
In 1898,[1] Jacques Hadamard noted general divergence of
trajectories in spaces of negative curvature. Pierre Duhem discussed the possible general
significance of this in 1908.[1] The idea that one butterfly could eventually have a far-reaching ripple effect on subsequent historic events first
appears in "A
Sound of Thunder", a 1952
short story by Ray
Bradbury about time
travel (see Literature and print here).
In 1961, Lorenz
was using a numerical computer model to rerun a weather prediction, when, as a
shortcut on a number in the sequence, he entered the decimal .506 instead of
entering the full .506127. The result was a completely different weather
scenario.[2] In 1963 Lorenz published a theoretical
study of this effect in a well-known paper called Deterministic Nonperiodic
Flow[3]. Elsewhere he said[citation needed]
that "One meteorologist remarked that if the theory were correct, one flap
of a seagull's wings could change the course of
weather forever." Following suggestions from colleagues, in later speeches
and papers Lorenz used the more poetic butterfly. According to Lorenz, when he failed
to provide a title for a talk he was to present at the 139th meeting of the American Association for the
Advancement of Science in 1972, Philip Merilees concocted Does the flap of a butterfly’s wings
in Brazil set off a tornado in Texas? as a title. Although a butterfly
flapping its wings has remained constant in the expression of this concept, the
location of the butterfly, the consequences, and the location of the
consequences have varied widely.[4]
The phrase
refers to the idea that a butterfly's wings might create tiny changes in the atmosphere that may ultimately alter the path of
a tornado or delay, accelerate or even prevent
the occurrence of a tornado in another location. Note that the butterfly does
not cause the tornado. The flap of the wings is a part of the initial
conditions; one set of conditions leads to a tornado while the other set of
conditions doesn't. The flapping wing represents a small change in the initial
condition of the system, which causes a chain of events leading to large-scale
alterations of events (compare: domino effect). Had the butterfly not flapped its
wings, the trajectory of the system might have been vastly different - it's
possible that the set of conditions without the butterfly flapping its wings is
the set that leads to a tornado.
Illustration
The butterfly effect in the Lorenz attractor
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time 0 ≤ t ≤ 30 (larger)
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These figures
show two segments of the three-dimensional evolution of two trajectories (one
in blue, the other in yellow) for the same period of time in the Lorenz attractor starting at two initial points that
differ by only 10−5 in the x-coordinate. Initially, the two
trajectories seem coincident, as indicated by the small difference between
the z coordinate of the blue and yellow trajectories, but for t > 23
the difference is as large as the value of the trajectory. The final position
of the cones indicates that the two trajectories are no longer coincident at t = 30.
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