The Misbehaving Universe

[CraigS]

Here’s an interesting one on the state-of-the-art in Spiral Galaxy formation modelling. (http://www.physorg.com/news/2011-08-glimpse-birth-milky.html)
The following words caught my eye:

Hmmm ... when it comes to theory in science, there is no ‘proof’, so we can dispense with that statement pretty quickly, but what does this exercise really then represent ?

In their simulation, the spiral galaxy shape forms on its own. In the model, they're tracking the behaviours of individual components of a galaxy comprising 790 billion solar masses and 18.6 million particles .. a huge number crunching task !

Principles Used (Inputs):
- cold dark matter paradigm;
- physical laws of gravity;
- fluid dynamics;
- radiophysics.

Model Outputs (Results):
- stars form in giant high density cold molecular gas clouds;
- star formation and distribution not uniform - clumped, clustered;
- heat build up by supernova explosions;
- visible matter accelerated to high redshifts by these explosions;
- removal of this matter from the core results in a concave disk;
- this results in the correct stellar mass as per observations;
- at the end, a thin curved disk forms corresponding to measured mass, angular momentum and rotational velocity ratios.

General Litmus/Reality Tests:
- can’t have too many stars at the centre;
- the overall stellar mass can’t be several times bigger than observed.

Predictions:
- distributions of stars and hot gases for the outer halos of the Milky Way (currently technologically, beyond detection).

There’s also a whole lot of extra ‘tweaks’ they’ve recommended going forward (of course).

Coming back to answer my original question though, to me, what it is they’ve actually shown, is that from the known individual component behaviours, a spiral shape forms which matches fairly closely to what we observe at the macro-scales .. which in itself, is amazing! That this happens, shows us that the universe is capable of forming galaxy shapes, which are not immediate directly relatable (in quantifiable terms), with the known individual component behaviours. (Ie: the whole is different from the sum of its parts).

If this is the way the universe behaves overall, then why should we ever expect the behaviours at any given level of scale, to necessarily be the same at the next level up or down ?

Cheers
PS: For anyone interested, the paper describing the model is here. (http://arxiv.org/pdf/1103.6030v2)

[renormalised]

Well, damn it, send it to its room without any supper!!!!:):P:P

[renormalised]

It's not a matter of misbehaving. You haven't seen the forest for the trees. A forest doesn't have the same morphology as the trees which make it up. What is happening, is that the patterns of morphology at the micro and meso scales, when taken as a whole, drive other patterns at the macro scale which may bear little resemblance to those smaller scale patterns. Their combined effect creates the spiral patterns of the galaxies and in turn the megascale patterns also influence the others at the smaller scales. None can be taken in isolation, except if all you're studying is those particular patterns/processes. However, in order to truly understand what is happening at any scale, you must consider the whole system. This applies to any science...let alone astronomy. Actually, it applies to anything we do.

In order to study how the spiral density wave creates and drives the spiral structures in galaxies, you must know how the stars form within them and what other processes/patterns occur within them. And, in order to understand how the stars form and the clouds of dust and gas are related to this process (and others), you must also know how the spiral structures of these galaxies work. It can't be escaped.

The problem with being overly reductionist is that you lose sight of the interrelationships between the apparently disparate pieces of the whole. That is a big problem with science...this over reliance on reductionism and pigeon holing of everything. In many cases, more knowledge can be gained by considering the whole, rather than the parts.

[CraigS]

I think we're roughly on the same page here .. its very interesting this ..

I don't think there is a need to invoke a "driving process" between the various levels of scale. If there is no evidence of one in nature and the pattern spontaneously forms in the simulation, I don't think we can say that this is happening.

I can see that there is iteration at the lower-scale level, (the outputs from one step in time feed back, as inputs to the next), that's actually the function the computer performs in the model.
Maybe there's also a natural feedback process at this same level of scale in the real thing, also.
But once again, I can't see a need for invoking feedback between this level, and say, the next one up, when the simulation forms the pattern without such a mechanism.


I really don't think there is any such thing as a "driving spiral density wave". I think the fact that the spiral shape appears spontaneously without any cause, suggests that it is nothing more than an illusion, which our pattern-recognition sensors pick up. There is not necessarily any "driving force" (of nature) behind it. The structure merely self-assembles in this pattern, because of the behaviours of the individual parts, at the lower scale.

Once again, I don't think there are any "workings" we can attribute as being at cause in creating the spiral structure .. there is no need for any such mechanism, as it appears purely because of interactions between the 'standard' behaviours, of the lower scale components.

I whole-heartedly agree !
:)
Cheers

[CraigS]

PS: The "Misbehaving" term in the title of this thread is intended as a tongue-in-cheek reminder, that it is not nature that's misbehaving … more likely, it is that we are expecting something to be at "cause" for the spiral pattern, which didn't actually turn up!!
How dare it !! :P
I'm gonna call that "misbehaving" !
:P :)
Cheers

[avandonk]

The only quantum computer than can mimic the Universe is the Universe!

Bert

[CraigS]

But Bert … we align our lifestyles to live in accordance with what these models are telling us.

Should I stop doing this ?

[renormalised]

Most certainly:)




If there is no connection between the scale level processes other than some randomly generated pattern at the macroscale level of structure, then any shape could be generated from the processes...any shape that obeyed all the physical laws which govern the interaction of systems. Maybe we don't "see" a connection in nature because we're too busy looking at the components and not the whole system. It's like saying here we have a human, but that human bears no relation to what their cells are doing. We may not even see the connections simply because we don't recognise any. Did that pattern spontaneously form in the simulation because it was just going to happen, or did the conditions that were programed into the individual components within that simulation, when taken as a whole, generate that spiral pattern due to the interactions between its components. Then, did the spiral become self sustaining because it was just something of consequence or did the pattern that was generated influenced the particles at the smaller scale.



Again, is it just a matter of consequence and coincidence or do they both interact with one another to produce the results given. It's very easy to just say there's no connection since we can't see one, but that is probably a case of missing the point, so to speak. Nothing happens in isolation, anywhere. It's why you have to be careful when using laws/theories of physics to describe what is happening in the Universe. They can only be approximates. They act as a set of ground rules and initial scaffolding to hang your ideas/observations on, but they never tell you the whole picture. There's always room for improvement. That's why theories come and go. Some theories hold good for a long time, others drop by the wayside rather quickly. But, no theory is immutable.



It's in part because of the spiral density wave moving through the cold, molecular clouds of the galaxies that we have any stars in the first place. A cold cloud of gas is just going to sit there and do nothing unless something prompts it to collapse and form stars.

Now, that's where you're going right out on a limb and stretching quite a few physical laws...spontaneous generation with no causative mechanism. That's tantamount to creation from nothing, which is one reason why laypeople find digesting what scientist say about the BB rather difficult and gives the looney tunes brigade their ammunition to go on with what they do. The reason why scientists say things like the BB (or in this case the spiral pattern in galaxies) has no cause is that they don't understand the mechanisms behind it very well, if at all. You can't have laws of physics saying one thing and then totally disregard one of the underlying principles behind them (cause and effect) just because you can't fathom why something happens, given your present state of understanding. There's quite a bit we do understand, make no bones about that, but we do waffle on too much and dig our own graves when it comes to making pronouncements on areas of knowledge we've barely begun to even figure out, let alone know what's happening.

There's nothing wrong with self assembly in natural systems or even spontaneous generation due to interactions at a lower level in the whole system. However, there has to be a cause and an effect which generates the final result. This could be an area where chaos theory and fractal mathematics excel in because it's pretty clear that it's the patterns created through a vast number of variables interacting with one another at all sorts of levels which eventually build to the structures that we see.

Sometimes, even illusions can have a reality all of their own. We may know they're illusions, but we still perceive their existence and reality.




Mechanisms are not necessarily just one causative "force" driving a system to attain anything in particular. A mechanism can be the sum of a complex set of interactions between an infinite number of variables which ultimately create a "desired" effect within a system. The sum of all the causative behaviours generate the whole which becomes greater than the sum of its parts. The whole then affects the standard behaviours of the lower level components.



We all have to be careful in our approaches to understanding these things. There's also a downside of seeing too much forest and not enough trees, too. In looking too heavily at the big picture, you can miss the little things which are generating the problems or processes as the case may be. You need to take a balanced, holistic approach. That way, hopefully you won't miss anything important and you might come to an understanding of what you're studying...or, at least, the snotty nosed little undergrad that's going to be a future postgrad student of yours will come to that understanding. After you check into the big science lab in the sky, that is:):P:P

[renormalised]

What if it's just our interpretation which is heretical....either way and depending on your PoV. Nature might be doing something, saying, "Hey, you in the lab coat with the pocket protector, leaky pens and buck-teeth. Look at me!!!!", and because we don't have a clue at what we're looking at or doing, we're the ones who are actually misbehaving:):P

[renormalised]

Precisely, because to mimic the Universe, the quantum computer must contain the same number of qubits as the Universe itself. In order to model its processes down to the nth level, you have to have the same level complexity as the test subject itself. Otherwise, you just get an approximation.

[xelasnave]

I simulate a galaxy formation when my tea bag breaks and the milk powder clumps stir it up and ...:D.

Most interesting:thumbsup:.
Now they need a number of galaxies to see how/if they intereact during formation.

alex:):):)

[CraigS]

G'Day Alex;

Somewhere is all this, I read that it took the supercomputers 8 months to create this simulation, and it would take a PC 570 years to come up with the same result.

Can you imagine how long it would take to come up with what you're suggesting ??

Cheers

[sjastro]

About as long as the EU crowd using an abacus.;)

Steven

[renormalised]

I thought they'd be using their fingers and toes, instead:):P

[CraigS]

Yes Carl … fair enough, too. My words may have been misleading.
There is clearly a cause .. that would be the non-linear behaviours which take on a life of their own, once the smaller scales interact with eachother, within the simulation. So I guess one can point to this as the 'cause'.

What I meant to say, is that it is not caused by something external which takes on the form in our thinking of a physical "spiral density wave".
If we give such a thing the ontological status of say a primitive entity that can be demonstrated by experiment, then it should be able to be described separately from its constituents ... and I don't think we can do this for "a spiral density wave" . :question:

Also, there are systems which have feedback operating between dissimilar levels of scale … which produce a verfiable cause and effect on the components. Eg: I can kill off a few thousand brain cells by having a few drinks, eh ? This would be a different system from the ones simulated in the model we're talking about here, though.

Cheers

[xelasnave]

Yes Craig I noted their work and it would be a major task but why not... think of the time that can be wasted on developing a mere game...
alex:):):)

[avandonk]

Our minds have evolved for survival and enjoyment of life in the biosphere of Earth. Even if our brains work at the quantum level it is still remarkable we can begin to model the Universe which is far outside our needs for mere survival or earthly material enjoyment. I was just pointing out that our feeble efforts can only be at best a very poor approximation of reality. That does not mean we should stop trying. Even a negative experimental result carries meaningful information.

Consider this statement.

A brain that thinks it could fully understand it's own workings would be very feeble indeed!

If I had a full answer to your last question I would be omniscient and you know who HE/SHE is!

Bert

[CraigS]

Understood.
I know others have been around this loop a few times, and the points raised are usually very consistent, but I always find it difficult to reconcile how we can dismiss our 'best effort' complexity models, as merely very poor approximations of reality, whilst at the same time, we embrace them, in a manner which asserts the opposite (in terms of the reality of their predictive capabilities) (??).

It seems that we have invented something, which our brains are incapable of classifying, using reality as the reference. (And that is regardless of whether they actually represent a likeness to reality, or not !)

Cheers

[avandonk]

Craig when you are on a modern airliner at 40,000 feet while having a meal that you would not feed to your dog just think that outside it is -50C and the air is too thin to breathe. This airliner was built by approximate models and trial and error. We do not fully understand airflow and complex structures but we get away with our approximate models as long as we stay within the parameters that we think we understand.

We cannot do better than this. We are bound by our own ignorance. It is the few that that dare to go outside this comfortable envelope that gives us more understanding. It is simply by asking better questions that progress is made in our finite knowledge.

Godel showed we can never know all without paradoxes that cannot be disproved or proved. It is this indeterminism that makes our Universe so complex. Determinism leads inexorably to simplicity. Ask any fundie.

I prefer to live in a very complex Universe even if I do not fully understand it. I also do not need to invoke a mythical entity that oversees it all. We are all surviving on our own efforts not some sky god that some idiot invented to explain the rather large bit he did not understand!

I always think that we humans are are bit like two ants crossing my infinite carpet and one ant says to the other see that everchanging glowing image I know how it works. This ant now makes himself leader and arbiter of morality and laws for his fellow ants. They were watching home and away on my TV!

Bert

[renormalised]

Turn up the volume and they'll think it's the voice of God, Bert:):):P:P

All you'll need then is a burning bush:):P

And a few slabs of rock with some scratches on them:):P

Or, maybe the TV guide:):P

[CraigS]

Elsewhere on the net, I see so often, questions being suppressed about complexity models … mostly, I see no proper explanations, even where the questions are allowed.

I can only conclude complexity models are yet to gather the evidence and even when this happens, 'predictions' are still questionable … unlike your example of a plane at altitude, which was tested many times over in variants of controlled conditions before I boarded it. It is only this which helps me to minimise my instinctive concerns.

Do we impose our need for determinism on top of that which may not be determinable in the first place ?


I'm with you in principle on that one … with the exception that my preferences don't really matter … the evidence is all around us .. if only we'd look at it ! ??

Cheers

[avandonk]

As someone that has worked in science for forty years prepare to be shocked!
Just watch this video and if you understand all the implications you understand.

http://www.youtube.com/watch?v=XVBEwn6iWOo&feature=player_embedded


Bert

[renormalised]

That was extremely interesting.

What amazes me is that much of this work had already been done decades ago and yet we've missed the boat (until now) to really come to grips with the implications of this. This will revolutionise everything from meteorology to bioengineering. The understanding of how lightning is generated to how cell membranes regulate the diffusion of substances across into cells, to power generation via photosynthesis, to new battery technologies etc etc etc. It's even conceivable that other liquids which have charge polarity of their molecules may also behave in a similar fashion and it would be wise to study these as well. This even has implications for the origin of life, as was mentioned. Given this liquid crystalline behaviour, this may also be applicable to the creation of LCD's, even information processing (liquid crystalline water CPU's???, water based "fibre optics"???).

It could even be said that the water on this planet acts like a gigantic, living cell. It has an interior that is surrounded by a "cell membrane".

This research is going to lead down paths we haven't even considered yet. It will also rewrite quite a few textbooks. In many ways, this is as revolutionary (to even more fields) as Relativity. As the adman once said "watch this space".

[multiweb]

Loved the presentation in layman terms and how he eases into it to the point everything falls back into place by the end very simply and elegantly, almost logically. Very fascinating stuff indeed.

[CraigS]

Ok … so from the perspective of this thread, complex structures can form from very simple behaviours .. in this case, charge separation in water, in the presence of hydrophyllic and hydrophobic surfaces ... all courtesy of energy delivered by incident radiation. Perhaps yet another non-linear 'system' which has influenced the evolution of the geological and atmospheric environments on this planet, for eons. I wonder how all this factors into our state-of-the-art models in these domains ?

There is clearly a very close linkage between water based life emerging on this planet, and the presence of vast quantities of water … no big news there.

As far as the commercial applicability, I'm yet to be convinced … as with all scaling-up exercises ... the devil is in the detail. The issue being what happens to the energy efficiency as the application scales ? (This being said, I also share some optimism, in that the research avenue looks interesting).

Thanks for the Youtube, Bert … very thought encouraging !

Cheers

[renormalised]

Precisely, Craig.....simplicity drives complexity, and most likely, vice versa.

I get the feeling that many of our "state of the art" models for these systems, based on a reductionist paradigm as they are, will be in need of some very heavy revision, if not total replacement in some cases.

[CraigS]

I don't think I'm so concerned by reductionism when addressing questions applicable to behaviours at different physical scales. To date, it has worked remarkably well in many areas of understanding.

I think the issue I have, is more about the imposition of predictability over systems which may be inherently … not predictable. This is at the very core of the scientific process and yet, predictability seems to be a condition imposed on the process, seemingly purely, by a human obsession to predict the future. A theory which has no predictive capability, will have no legs, by definition !

There's no question that prediction is possible where little/no randomness (or non-linearity) dominates. But in complex systems, certain macro features emerge, whose behaviours may be predictable, (due to an inherent lack of randomness), or completely unpredictable. The next scale level up in the same structure, doesn't necessarily exhibit the same degree of order (or predictability) as the lower scale .. and yet we seem to expect that it does ! (Like this guy's energy production 'cell' … will it work the same way at larger scales ???) :shrug:

Perhaps this is a by-product of (reverse) reductionism ? :shrug:

Short-term weather forecasting, as distinct from long-term weather forecasting, are two areas exhibiting completely different degrees of predictability … its not too hard to predict tomorrow's weather in a given area, but what of the weather 3 months out .. or even a year out .. or many years beyond ?
.. And yet .. these are behaviours of the same system .. ie: the Earth's atmosphere.

Other things also happen with galaxies, which even result in different structures emerging eg: spiral as distinct from open, or elliptical. Is the emergence of one of these structures over another, predictable ? … Even if they are all driven by the same fundamental forces of nature ?

I think the study of computer models, is teaching us a lot about our own self-imposed expectations about how the universe must behave .. by showing us where they actually don't behave.

But getting this word out to the masses is nigh on impossible, at present.

Cheers

[renormalised]

The problem with reductionism is that you can only reduce something to a certain extent before you start to lose sight of the connections between paths within that process. Much of the time, the behaviours of system are more holistic and synergistic in nature than nice, neat compartmentalised boxes. What's the use of knowing how each and every gear and cog in an old watch works, without having a clue about how they all work together to produce the movements of that watch. Reductionism is great for defining all the parts within a system, but it's no use to figuring out how that system works...except in a very tedious and linear way.




Another reason to be careful with reductionism. Complexity almost begs for a holistic approach to science, where both complexity and simplicity are seen as different aspects of the one overriding principle that influences the entire system. Reductionism rides very well with predictability as they both depend on a linear train of thought...A + B = C. Breaking things down into their components and then adding them altogether to get the final product. It can help with problem solving, by taking complexity and making it simpler, but doesn't necessarily show you the complete picture.



I agree, for the most part. But predicting something at one scale being applicable at another can be useful. It gives a direction in which to head with further research. It can also actually show that despite complexity and the nature of predictability/unpredictability within systems, more often than not a generalised trend in the way systems behave can be elucidated. A case of A + B ~ C.

Whether the prof's energy production cell can be scaled up is a matter of empirical experimentation, not theory. The theory will work at any scale. It's only the practicalities of scaling and whether there are restrictions to scaling up the process that exist. The only way to find out these things is to perform the experiments. The theory is only a set of guidelines with which to work with. Quite often, theory has to be revised or rewritten because of what they find through experiment.



I don't know about that. I've seen the meteorologists stuff up even the daily weather forecasts:):P Quite regularly!!!!:)

The degree of predictability seems to depend on the degree of complexity of the system being studied and the behavioural links between that system's component parts. As I said earlier, generalised trends in predictability can be mapped out, however the more you look at the nitty gritty, the harder it becomes to figure out what's happening.




Like any other complex system, galaxy formation is not something you can just sit down and say "X and Y will become this and that galaxy". Everything has to be taken as a whole. Trying to reduce it down into a nice series of steps is all well and good, but you have to know what the causal links between the steps are, and how these interact to produce the final product. Those fundamental forces of nature do not act in isolation. Not seeing the forest for the trees means you will most certainly miss important interactions which drive the formation of the different galactic morphologies. Many of the processes within each of the different galactic morphologies are basically the same, but it's the way they interact and the timing between the processes which generates the different morphologies.




Computer models are only as good as the data they use, the level of programming being used and the complexity of algorithms generating the models. It's the old adage...GIGO. Many of our self imposed expectations are present in these models. What we see with these models where they deviate from that norm is where the algorithms produce unexpected results due to unforeseen interactions produced by those models. This is usually a function of time and increasing complexity as the models evolve. It also depends on the number of variables that the algorithms use to create the models.

I don't think that getting the word out to the masses is necessarily a good thing, considering that 98% of the masses wouldn't understand where the word was coming from. Most people have trouble just getting through an average day, let alone having to deal with chaos and non linear systems theory in their daily lives. So long as they are given a general idea of what is trying to be conveyed to them, most are quite content to leave it at that. Even there, most usually don't get what's being told to them and the reason why you get all the nonsense you see with science reporting and such, these days.

All the complicated business they leave up to those that actually can understand and use it.

[CraigS]

… and from what I've seen lately, even the experts don't necessarily agree about the 'expected' effects of things like feedback … and what mechanisms actually constitute feedback in the real complex systems.

Sensitivity to change is also hotly debated, as are the 'initial' conditions.

Its interesting to note that without the added pressure for predictions, neither would need to be 'hotly' debated at all !

Cheers

[Karls48]

From my experience, I would not trust any computer-generated models. Although the outcome of such computer generated model can match the expectations, the process how the outcome has been arrived to can not be understand and given sufficient number of iterations same outcome could be arrived to by using different internal process. Long time ago, I wrote program to predict OZ Lotto draws. My reasoning was that in infinite possibilities of random numbers generated by Lotto draws there should be random number generator that is resonant to Lotto numbers generating machine. The program looked on all past draws and by using kind of genetic algorithm try to made random numbers generator that is in synch with actual outcome. Well, by playing System 8 for two years my loss was around $140. That is way above probabilities outcome.
Why I am telling you this. Well, by changing one line in my program the process would be completely different, but outcome could be same.

Craig – question to you. You are believer in chaos theory. The butterfly flaps its wings – and so on. What will happen when tens of thousands wind generators generating GigaWatts of power will disturb airflow across the globe? What will happen when thousands of hectares of the soil are shaded by solar panels? What effect that will have on global weather? Can computer generated model answer this?

I don't think that getting the word out to the masses is necessarily a good thing, considering that 98% of the masses wouldn't understand where the word was coming from. Most people have trouble just getting through an average day, let alone having to deal with chaos and non linear systems theory in their daily lives. So long as they are given a general idea of what is trying to be conveyed to them, most are quite content to leave it at that. Even there, most usually don't get what's being told to them and the reason why you get all the nonsense you see with science reporting and such, these days.
All the complicated business they leave up to those that actually can understand and use it.

Carl – although I really admire and appreciate your knowledge and your holistic approach to the science – I think that you are bit too harsh in this comment. Not everyone is a complete idiot even if they never went to University and do not have PHD. Most of the people with some sort of technical education will ready accept applied science/technology. It is when it comes to speculative fields of science (Cosmology – Big Bang, Dark Mater, Dark Energy, Expanding Universe and number of other theories I can not thing of right now) when people start question the science. Although, those theories are best what we can come up with at this time, holistically thinking – they are most likely wrong.

Avandok – Thanks for the link. For long time I have believed that, there may be an electrolyte that can store and be recharged by solar energy. I tried and nothing seems to work. It did not come to my mind that the plain water could be the answer.

[renormalised]

Problem is, Karl, that much of the general public has a hard time understanding what science is about and especially what scientists sometimes talk about. It's not that they're complete idiots (some are, but that's not the point here), it's that most people have not had an interest in science to the point that they want to know about it. What makes things worse is that journalists try to interpret what they're told and invariably get the bull by the tail or just make things up in order to "sell" a story. The science is either completely watered down and misinterpreted or it's utterly false and bears no resemblance to what they were informed about. Another thing, because someone may have a technical background doesn't necessarily mean they will understand science. They may have a handle of the applied side of things but that's far from actually understanding the theory and the practice behind the theory. Most of those areas of science you have mentioned are not for the fainthearted and even to have a good grasp of them in descriptive terms takes having a good background in the subjects. It's hard enough for those scientist doing work in these fields to come to grips with the theories as they present themselves. Can you imagine how much more difficult it would be for someone, even with a technical bent, to come to terms with them. For most of the general public, it goes right over the tops of their heads. No matter what way you think of them, reductionist or holistically, saying that they're wrong requires that you know enough to have a good enough reason to say that they are. It's very much put your money where your mouth is with science...you either know or you don't. Most don't know, so anything they say is nothing more than opinion and in most cases opinion taken from ignorance or very little background knowledge at best.

And you know what makes things worse??...even the scientists don't always agree with one another. So, you get conflicting views. Leaves poor "Joe Public" in a bit of a mess, doesn't it:):)

[renormalised]

Have you ever known two experts to actually really agree about anything??:):P

The problem with feedback mechanisms is that like anything in a complex system, they're highly sensitive to the initial conditions which support the feedback and any change which occurs will affect the outcome of the feedback. With regard to mechanisms of feedback in complex systems, this is where a reductionist approach can get you into trouble. You can break the mechanisms down into their constituent parts and follow the paths back into the system. However, taking the linear approach of following the feedback loop won't tell you how each part interacts with the whole mechanism. The actual feedback might not necessarily be linear or even predictive. Complexity within complexity, so to speak. Sometimes the direct reductionist approach works, but not all the time. That's why experimentation is crucial...the theory is only a model of what you believe to be happening and/or an explanation of what comes from experiment. It's never the answer entirely.

Throw in prediction, which is a cornerstone of theory, and that only makes things more complicated, unfortunately. If you had no need for making predictions and just accepted outcomes as they were, it would make things easier. But less satisfying and inherently more uncertain so far as understanding was concerned.

[CraigS]

Hi Karl;
I need to clarify that I'm no 'believer' in Chaos Theory (see my signature).
However, what I stand for is to acknowledge the fact that the majority of systems in nature are for the most part, non-linear. That is, the whole is not the sum of the parts, their behaviour ranges from purely chaotic to completely ordered within the same system, as do the structures formed by the processes within them. As such, most systems in nature are not predictable and yet that's exactly what we try to (inappropriately) infer from them, when we model them in computer models.

The Butterfly effect is one of the most widely mis-understood concepts I think I've ever seen. In short, it serves as a cautionary reminder about the limitations of determinism and reductionism in science ... not that butterflies play a role in determining weather. Even if we had perfect data which we could trace back from an effect to cause and discover the linear cause of events, and find that some minor event, (a butterfly flapping), originally led to a major one (a cyclone), this in no way means that if that same minor event recurs, it will go on causing the same major one again.

So, in answer to your question, the effect of solar panels and windmills on the chaotic weather system is unpredictable. So, I wouldn't have the foggiest idea what the outcome might be … and neither does anyone else !
Modelling it in a computer, will provide us with more knowledge of typical behaviours of the overall system .. but as far as being able to consistently predict the value of something detailed … like its impact on the global temperature to a fine degree of tolerance … over long periods of time??

… No way !

Cheers

[CraigS]

The problem with feedback mechanisms in say, Climate Models, is that no-one has been able to figure out a way to actually measure these from existing observational data. The issue appears to be a lack of accurate long-term measurements of global cloud cover changes.

From thereon, the 'debate' becomes 'my opinion' vs 'your opinion'.

With no empirical data, the relationships between incident radiation and temperature, (and vice-versa), is unverifiable.

Mind you, there's plenty of temperature data … and yet there are still big arguments about whether or not these show an increasing or decreasing trend. ;)

Even if we did have accurate cloud cover data, there'd probably still be disagreement .. as it seems to me, that this is a blatantly obvious chaotic phenomenon where prediction is not possible … all as you point out .. even the feedback mechanisms are likely to be chaotic.

Cheers

[avandonk]

It has been said before that all life is water dancing to the molecules.

I have seen ordered water in high resolution xray crystallographic electron density maps around protein molecules. The paradigm was that it only extended for a few layers. It was wrong.

My real urge is to get back into the lab to explore this. Unfortunately all I can do is pass on the information and my version of the implications.

All of science is models of reality. It is only by experiment we refine these models. Eventually the model is found wanting to really describe what is going on. The tools we have are only limited by our ingenuity and insight.

I am sure my view of the Universe will be considered 'quaint' in the future. Until this happens it is the best we can do. It is up to our young to further explore and find what we have been overlooking.

Bert

[bojan]

This is extremely interesting!

Now , a bit OT question:
Anybody knows how to save this (and other) video stream to hard disk, for viewing later, without internet connection?
I investigated a bit, it seems the video (in flv format) essentially comes form various sources, and, while it does exist in computer memory, it is not in cache, (or at least doesn't appear to be there) and therefore can't be saved?

[CraigS]

Yep … its interesting that Complexity Models created to replicate natural phenomena, cannot be (easily) directly tested. Parts of them may be able to be tested, but it is unlikely that the whole, can.
This therefore also applies for models where spiral galaxies are created .. and climate forecast models … all for the same reasons. As everyone says, these models will only ever be approximations for the real thing.
However, in complex systems, small errors in the models, originating from untested assumptions, can lead to dramatically different predictions.
More complexity sub-systems added to the models, is also likely to drive the models further away from reality .. the same as too few.
As astrophotographers are aware, in the presence of 'noise', more data improves visibility of 'trends', but 'noise' is fundamentally different from chaotic behaviour .. so more data also doesn't 'smooth out chaotic behaviour. Extrapolating a chaotic model, only results in more chaos.

In this case, predictions will always be in error and the further out you go in time, the bigger the errors will be (away from reality).

Cheers

[renormalised]

You know, with all this talking we've yet to come up with a suitable punishment for this misbehaving universe:):P

I reckon 20 lashes with the feather duster and then transportation for life to a suitable penal colony, say Cairns or Canberra, will be sufficient:):P:P:P

[avandonk]

It is the first sign of maturity when the young first question and then defy their parents. Punishment is the last phase! Choosing their retirement home comes to mind!

Bert

[multiweb]

Unless it is streamed it is always in the cache and Youtube always caches its output. It's not always in FLV format but you can rename the file extension to FLV and play it in a standalone player if you wish. Usually do a search for videoplayback[n], where n auto increments to 1,2 etc... and sort by date/filesize. The file shouldn't have any extension. Just copy it somewhere else and rename it <myvideo>.flv and play it back at your own leisure.

[bojan]

Thanks mate.. I knew about no extension (was saving as flv from Cacheviewer before), but sometimes the file (like in this particular case with Bert's link) can't be found in cache.
Actually, I found small segments, but not the whole contiguous file. Will try again :thumbsup:
Of course, in this particular case there were also some other methods available (torrentz) to get to the file, but..

[TrevorW]

Chaos rules (so does the man from UNCLE)