Quantum Computing - Meteorology

[Overheal]

Okay - this is the place to post this. Right?

I understand a smidge about Quantum Computing. It was mentioned a few times while I was in college. And I've had a good read here:

http://gizmodo.com/5335901/giz-expla...-a-distant-one

And I was thinking from this, it implies that many of our computer models, especially meteorology, are always going to be grossly inaccurate until Quantum Computing comes around, because Meteorology deals with thousands of "What If"'s whereas binary is limited by Is and Is Not.

Of course reading about QC and then reading about Hurricane Bill brought this train of thought about

Are we basically all fecked until QC becomes conventional? Meteorology is always getting better, but at the same time, its still also terribly inaccurate as far as predictions go. Especially the farther out you get.

DOC: First you're gonna have to get out and change clothes.
MARTY: Doc, it's pouring rain.
DOC: Oh, right... (Checks his watch) Wait 3 more seconds.
(Rain stops, sun comes out)
DOC: Right on the tick. Too bad the Post Office isn't as efficient as the weather service.

Spielberg, that prophetic bastard.

[-JammyDodger-]

I'd say you'd probably get a better response to this in phys/chem. Also, just so you know, something like this is welcome in EYH.

[Fremen]

My understanding of Quantum computing is that it doesn't allow a user to do any fundamentally new computations (computations in the "turing computable" sense of the word), it just speeds up existing ones. Factoring a number and searching a list become much easier with quantum computers.

The problem with weather prediction is related to "chaos theory" or dynamical systems to use the more modern name. The physics behind weather patterns is pretty well understood, but the data we input to the model is inexact. It can never be exact, since in that case we would need to know the position and momentum of every molecule in the atmosphere.

Since the weather is a dynamical system, small changes in input lead to large changes in output (this is known as the "butterfly effect"). The models work well up to a couple of days, but beyond that the errors grow too large.

"Chaos" by James Gleick is a great book on the subject, it's definitely worth a look.

[Overheal]

Originally Posted by Fremen

My understanding of Quantum computing is that it doesn't allow a user to do any fundamentally new computations (computations in the "turing computable" sense of the word), it just speeds up existing ones. Factoring a number and searching a list become much easier with quantum computers.

The problem with weather prediction is related to "chaos theory" or dynamical systems to use the more modern name. The physics behind weather patterns is pretty well understood, but the data we input to the model is inexact. It can never be exact, since in that case we would need to know the position and momentum of every molecule in the atmosphere.

Since the weather is a dynamical system, small changes in input lead to large changes in output (this is known as the "butterfly effect"). The models work well up to a couple of days, but beyond that the errors grow too large.

"Chaos" by James Gleick is a great book on the subject, it's definitely worth a look.

I would have agreed with you yesterday. If not for the show I watched this morning on PBS about Factorial Geometry, and how it can be used to accurately model nature. Theyve already used it to express the Human heartbeat as a factorial equation; mountain ranges; etc. and in the end of the segment they cut down a tree in the rainforrest, took readings from it, generated an FG model from it, and from that they pretty accurately mapped out the surrounding environment, expressed as a factorial geometric equation.

But then you have that factoring problem, and you still need the power of QuBits.

[Fremen]

Hm, do you mean fractal geometry?
Dynamical systems is inherently linked to fractals. In fact, you can't really study one without studying the other.