Chaotic Star Mist
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Clouds stream across the night sky as the world spins, a few lone jets pass by, its all a bit Chaotic.
About an hour into the shoot, I realised my camera was not triggering... opps... forgot to set camera in continuous mode. So about an hour later I had 100 images and David had over 200, so I cant wait to see how his shots turned out.
- Canon 50D.
- ISO 400, f5.6, 30 seconds, 10mm.
- Sigma 10-20mm.
- 110 single images stacked in Photoshop 6.0.
- White balance fixed. (shot in Tungsten)
Chaos (derived from the Ancient Greek Χάος, Chaos) typically means a state lacking order or predictability. In ancient Greece, it first meant the initial state of the universe, and, by extension, space, darkness, or an abys (the antithetical concept was cosmos), but later uses of the term by philosophers varied over time. In modern English, the word is used in classical studies with the original meaning; in mathematics and science to refer to a very specific kind of unpredictability; and informally to mean a state of confusion. In philosophy, and in popular culture, the word can occur with all three meanings.
Mathematically, chaos refers to a very specific kind of unpredictability: deterministic behaviour that is very sensitive to its initial conditions. In other words, infinitesimal variations in initial conditions for a chaotic dynamic system lead to large variations in behaviour.
Chaotic systems consequently appear disordered and random. However, they are actually deterministic systems governed by physical or mathematical laws, and so are completely predictable given perfect knowledge of the initial conditions. In other words, a chaotic system will always exhibit the same behaviour when seeded with the same initial conditions - there is no inherent randomness in this regard. However, such perfect knowledge is never attainable in real life; slight errors are intrinsic to any physical measurement. In a chaotic system, these slight errors will give rise to results which differ wildly from the correct result. A commonly used example is weather forecasting, which is only possible up to about a week ahead, despite theoretically being perfectly possible at any level (ignoring the effects of the uncertainty principle).