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Video Introduction: Concept of Emergence

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Emergent Phenomena in Science and Everyday Life

Калифорнийский университет в Ирвайне

4.3 (оценок: 95) | Зарегистрировано учащихся: 9.2K

Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future. However, there are some systems that defy this notion. Consider a living cell, which consists mostly of carbon, hydrogen, and oxygen along with other trace elements. We can study these components individually without ever imagining how combining them in just the right way can lead to something as complex and wonderful as a living organism! Thus, we can consider life to be an emergent property of what is essentially an accumulation of constituent parts that are somehow organized in a very precise way. This course lets you explore the concept of emergence using examples from materials science, mathematics, biology, physics, and neuroscience to illustrate how ordinary components when brought together can collectively yield unexpected, surprising behaviors. Note: The fractal image (Sierpinkski Triangle) depicted on the course home page was generated by a software application called XaoS 3.4, which is distributed by the Free Software Foundation under a GNU General Public License. Upon completing this course, you will be able to: 1. Explain the difference in assumptions between an emergent versus reductive approach to science. 2. Explain why the reductivist approach is understood by many to be inadequate as a means of describing and predicting complex systems. 3. Describe how the length scale used to examine a phenomenon can contribute to how you analyze and understand it. 4. Explain why the search for general principles that explain emergent phenomena make them an active locus of scientific investigation. 5. Discuss examples of emergent phenomena and explain why they are classified as emergent.

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4.3 (оценок: 95)

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ST

Jul 02, 2017

It's a good course to get acquainted with first hand information about studies in emergent phenomena

JH

Jan 05, 2019

Very good none technical introduction to emergent phenomena.

Из урока

Welcome - Let's Get Started

In this module we'll introduce the concept of emergence and provide an orientation to how this course will proceed.

Video Introduction: Concept of Emergence10:42

Video Introduction: Reuben H. Fleet Science Center - Part 10:47

Video Introduction: Reuben H. Fleet Science Center - Part 21:53

Преподаватели

Michael Dennin
Professor of Physics and Astronomy; Vice Provost for Teaching and Learning
Jun Allard
Assistant Professor
Donald Saari
UCI Distinguished Professor of Economics and Mathematics
Andrea Nicholas
Lecturer PSOE
Fred Y.M. Wan
Professor
Siddharth A. Parameswaran
Assistant Professor

Текст видео

[MUSIC]

My name is Michael Denton.

I'm a professor of physics and astronomy at the University of California in Irvine.

And, welcome to emergence in nature.

This is a very exciting endeavor for me.

Most of my research career has been spent studying this question of emergence,

or complex behavior.

And the fundamental feature of this, in my own research,

are systems that show interesting, surprising behavior, even though they

appear to be everyday systems because of the complex nature of the system.

And we want to just take some time in these modules in this course to explore

a number of different interesting examples of emergence in nature and

where it comes from.

In this introductory overview, we're just going to give you

some very brief ideas of what emergence is and what the units will be like.

So let's go right into that big question.

What is emergence?

The basic idea is that you have certain systems in the world.

When you look at them you can't understand them

just by understanding how the individual pieces interact.

So maybe you can imagine something as complicated as a car.

And you've tried to take your car completely apart to all

the individual pieces.

And you lay them out on the ground.

And maybe make a diagram of which piece is connected to which piece.

Just because you know each individual piece does,

you won't necessarily how a car works or how it runs or what it does?

You have to consider it as an entire whole system

all put together to understand its behavior.

Now, one feature of this is that emergence is

often our way in science of understanding behaviors in systems

that seem to appear without having any obvious explanation.

What do I mean by that?

Well, the other side of science is often what we call reductionism, or

a reductionist point of view.

Which is the idea that no matter what the behavior is, if you understand

the smallest pieces, you can predict and understand the larger behavior.

Emergence takes a slightly different point of view and

says there's some systems where the complexity leads to interesting and

surprising behavior that you can't explain just by understanding the pieces.

And a key idea that you'll see coming up over and

over in these modules is an idea of length scale.

It sounds like a fancy term, but

it's really just the idea of, are you looking at the smallest piece?

The next biggest collection of pieces, the next biggest collection of pieces?

Which length scale, which size are you looking at your system in?

Again, take our car.

If we look at it with a very, very small length scale,

we only look at small pieces, you won't maybe know that you ever have a car there.

But if you take a step back and look at it at the length scale of the car,

then you see the whole car.

And you can see what's going on.

Now we're going to focus on just a few very specific examples of emergence.

There's a wide array of emergence in natural phenomena and

an exciting thing going forward is we hope to add later modules.

So if you like this set, stay alert and watch for later editions.

We're going to start with I think the most physical, but maybe not one you'd think

about, system, which is literally shaving cream, ketchup, soap.

What we call foams and complex fluids.

Sand is even an example of this.

They're materials where at the microscopic level of molecules and

atoms you can easily classify the molecules and

atoms as liquids or solids, so the foam is gas bubbles with liquid walls.

Everything in there can flow like a fluid,

but when you look at the system as a whole, you get surprising behavior.

The shaving cream doesn't act the same as a normal, simple liquid.

So this is a nice example of emergence,

a property that happens because you put a whole bunch of bubbles together.

Another way you get interesting behavior from complex systems is something we call

chaotic behavior.

In physics, as we describe the world around us.

Most of what we do is use what we call deterministic equations.

That's a fancy language for

saying, if I know what you're doing now, I can predict what you're doing later.

So we take the simple case of throwing a baseball.

So one of the simplest systems we look at in physics, if I know the velocity,

the speed I let the ball go and the direction I throw it.

And I can take into account air resistance.

I can predict exactly where that baseball will land every time.

That's deterministic behavior.

If I take a bunch of baseballs connected in an interesting way,

all of the individual interactions, what we call the pairs of interactions.

Maybe I have four baseballs and

they're interacting with certain rules between the baseballs.

I can predict each of those individually.

But when I put the system together, a new behavior emerges called chaotic behavior.

Many of you have heard of chaos.

It's a fun, interesting area of study.

And suddenly we get a system that is fundamentally unpredictable.

So we start with deterministic behavior, predictable behavior.

And chaotic behavior emerges which is unpredictable.

So this will be a fun little segment.

Another segment we have is related to what we call pattern formation.

We'll say a little bit more about it later, but this is a lot of fun.

This is where you get the stripes,

spots, and all the rich patterns you have around you in nature.

And it really is a biology question.

It wouldn't be a fun physics thing if we didn't do a little bit of

quantum mechanics.

Quantum mechanics is kind of a little bit weird,

hard to understand because we don't have a good intuition for it.

But even in quantum mechanics,

we have this issue of systems interacting together.

When they become large systems, you get new and surprising behavior.

One of the things we'll look at is what happens to electronic charge

in quantum mechanics systems that have a lot of pieces.

And the other big one, of course we have to talk about consciousness.

One of the greatest challenges in science the whole mind, body problem.

Where does your consciousness really come from?

Is it really something you can understand by looking at individual neurons?

Or is there something more that emerges out of the complex behavior from all

the interactions of the neurons.

They have a lot of things in common.

If you go back and

think about these, there is different length scales, levels of complexity.

All right think about consciousness.

I have the molecules in my neurons.

I have the neurons themselves.

I have the interconnections between the neurons.

This is what we mean by different length scales.

And if you look at each of my examples.

You can track and think about where are those length scales.

We have what we call a new scientific principle

that applies to this system as a whole.

A simple way to think about this is imagine molecules in a gas.

We talk about the second law of thermodynamics.

This will come up in a lot of modules.

But very loosely speaking, the second law of thermodynamics tells us

if I have large collection of gas molecules,

they're going to want to be in the most random state they can be.

That means they want to fill the room not sit in a corner of the room.

That's a statement I can only make because I have a large system of molecules.

If I have a single molecule, it's not meaningful to say.

It will exist in its most complicated state possible or

with the most number of states.

It's just not a meaningful statement, that's a statement about systems.

It's a physics principle that emerges and applies to the system as a whole.

The final thing we'll look at and I don't want to say anything more now because it

is the surprises is all of these have surprising behaviors.

The last point I want to make before we go on and

tackle these questions is emergence really tackles this question of design in nature.

If you only look at science from a reductionist point of view,

then sometimes complexity can be hard to explain.

A simple example of this people often give is a watch.

A watch is a clear example that it must have been designed and

put together on purpose because if I take the individual pieces out,

then I can look at what individual pieces do but none of that information

really tells me what the watch will do or how it will work unless

I put the whole thing together on purpose to make it work in a design fashion.

In nature what we actually get is this idea of emergent properties and

complex behavior can lead to things that look like design,

look like they're like the clock and requires somebody to build it,

when actually it just arises spontaneously because of the laws of physics.

So a great example to look at this is pattern formation.

Now we're going to have a whole segment on it, so I'm not going to go into a lot of

detail, but I want to leave you with one nice example.

Imagine you have fluid usually a thin layer in a dish and

I heat it from below, and I cool it from above, and my heating's uniform.

There's no reason for this system to show any structure or have any patterns.

I'm not imposing it.

I'm not designing for it.

But if I heat it to a critical point, I will actually get convection rolls.

Hot fluid rises, cold fluid sinks, and you get these rolls.

And when you look at them from above, you get a really nice,

interesting pattern, stripes, hexagons, sometimes things that look like squares.

You can do this in a thin layer of oil on your kitchen stove and

you'll probably get hexagons.

Now, randomly moving these molecules will never organize themselves like this and

from a reductionist point of view, it's very hard to explain how this occurs.

But this is one of the fundamental principles that governs these complex,

what we call non-linear systems, driven systems and it emerges naturally.

And it's just part of the laws of physics.

It's not really something that has to be designed in.

In this course, as you go through these modules,

a few tips I think would be useful to give you.

One of the things is pictures really help.

And there's some places where some of the people do a little mini hands-on

demonstration.

Some of those you can even try at home to get a feel for it.

You want to really think in terms of images and ideas, because these

are behaviors that are happening kind of at this complex, emergent level.

So, playing with stuff at home really helps.

And sometimes, what's fascinating about these complex behavior, even though we

use the word complex behavior, they're occurring sometimes in rather simple ways.

And the words we use as scientists actually mean what we're saying they mean.

So when I say I study patterns and I study stripes and

hexagons, people used to look at me, like what is that?

That must be something really hard and crazy and I'm like, no, no.

It's stripes and hexagons.

So sometimes just relax and realize you actually do understand what we say so

hopefully you really enjoy these modules and

then you'll look forward to when we add ones in the future.

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