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  • We're going to talk about

  • Can we compute with art?

  • can paintings compute and it's it's a broader theme in terms of

  • What are the links between physics and chemistry and biology and computing and indeed art?

  • So I worked with somebody called Linda Jackson who's a local nottingham artist

  • She'd started to play with something called acrylic pouring where basically you take different types of paint

  • You put them down onto a canvas you let them mix and you let them dry and you end up with what I think

  • Incredibly striking an incredibly beautiful patterns like this sort of foam

  • like what we

  • Scientifically called cellular networks where you can see these cells on different lens scales and right across the board in terms of different colors

  • Etc. Those types of patterns are absolutely ubiquitous in nature right across very very large scale and scales

  • in fact

  • The large-scale structure the universe in terms of our galaxies are distributed

  • best thought of his in terms of a cellular network or this type of

  • Foam like structure all the way down to the really really really small and we're in nanoscience group

  • So we're very very keen on the really really small

  • We took a droplet of this which are nanoparticles five nanometers across

  • Tiny tiny particles of gold drop them onto a surface and let the solvent

  • evaporate

  • Left us with patterns like this. So these are not the individual particles themselves

  • This is what the particles do in terms of how they collect together and how they dry and you end up with these

  • incredible cellular type patterns which are

  • something like if you compare this with this in terms of the length scale, this is on a length scale about

  • 25,000 times smaller. This is a microscope emits an atomic force microscope image

  • So you're sitting there as a computer file if you were going

  • Okay, that's nice who's talking about science and he's talking about art. When's he gonna start talking about the computing?

  • There are strong links here in terms of the physics and the chemistry of these patterns

  • But the question is can you compute with curtains?

  • can you compute with art the question here is not can we you know generate something that does much much better than

  • Silicon technology CMOS technology in terms of the speed or the processing power, etc

  • so it's about thinking about different main sets and it's a broader and I would say more philosophical question what is information and

  • How do we process information?

  • It's a lovely piece of art what sort of computational problem can a piece of art like that solve?

  • I mean is this to do with colors?

  • Not really to do with colors much more to do with patterns in that we could just take all strip all the colors from this

  • And just make it black and white or even to a certain extent almost binary I said, but what's remarkable?

  • Is that the physical process which is underlying the art here?

  • Can be used to do a computation

  • Let's say you've got a set of schools

  • across a district or a county or indeed across the country and you

  • Want to think about the catchment area for those skills?

  • What's the best way of?

  • Dividing up the land in terms of catchment areas the fairest way and to do that we use an approach from computational geometry

  • called the Verona tessellation and

  • so to compute that which you can

  • Compute pretty straightforwardly, in fact, a lot of languages MATLAB included basically have the command built-in

  • So there's a distribution of points. It's fairly ordered

  • What we want to do is for each one of these points on here. We want to find the region that is

  • Closest to that particular point basically we want to divide this up as fairly as possible

  • So mathematically this is actually an geometrically is actually straightforward problem. So what we do is we connect up

  • One of the points to all its nearest neighbors and then what we do is we take the

  • Perpendicular bisectors, let's do that. So ones there

  • Ones here. So we're bisecting these lines and ones there

  • Ones there if you'll excuse the wobbly drawing

  • So what we have is that this area or the points within here are the closest to that point? Okay?

  • This is like numberphile stuff come on, it does feel like numberphile, but we're going to do a computation

  • I promise at the end and we're going to do a physical computation

  • I promise what you'd end up with then as you can see is just a set of hexagons

  • So that was an example of a very ordered

  • Let's take a less ordered set and a somewhat more

  • Natural set perhaps this is actually from a paper by Meredith P Richards and what she did was look at

  • distribution of schools in a district or

  • neighborhood in

  • Washington, I believe if I remember correctly

  • This is what it actually looks like the black dots are where the schools are and the question then is how would you divide up?

  • this area

  • to be the fairest in terms of the

  • Neighborhoods or the areas of the district that is served by each school

  • The algorithm is exactly as we've just done for that ordered set is you connected up

  • You connect a given point to its nearest neighbors

  • You take the perpendicular bisectors and you divide up the plane that way that's the fairest way of

  • Dividing up the land as it where I found being kind of picky here

  • I'm gonna suggest that perhaps some of those are more densely populated than others

  • Is that too complicated for this? So that's a really good point Sean

  • So yes

  • We're making a number of different assumptions here or assuming that the density of the population is the same right across the board

  • Obviously there are complications in terms of even transport links etcetera. There's a wide range of different contributions

  • we're going to do what all good physicists do even computational physicists and

  • approximate cows a large sphere PI's around three

  • Density population density is even across the board. We can set up a computer program to solve this. It's relatively straightforward

  • Let's take an example

  • Here's Nottingham. That's probably - higher density of points for schools. But I don't know. Let's say it's coffee shops

  • Well, what wanted to do is to try and work out was your closest coffee shop, which is the closest coffee shop to you

  • so the way to solve that is

  • Actually to do a Verona tessellation and so here's our points

  • Just taking away the map and we can calculate the Verona tessellation and it looks like that so again

  • It's not an ordered distribution of points. Therefore. We see a range of different polygons ranging from adult

  • See if we can see a triangle in there. I don't think so

  • I think the smallest is four-sided maybe up to seven or eight sided cells

  • Okay, so where is the physical computation well we can do it on a computer

  • or what we can do is we can

  • Take this as our computer

  • This is now a computer. This is a physical computer. And what we're going to do is going to take a droplet of these particles

  • Put it on a surface let the solvent evaporate

  • And what's going to happen? Is that those?

  • Particles are going to be carried by the tide of the solvent and get pushed together and they're going to create our own

  • Verona tessellation, let me show you exactly what I mean with a simulation

  • So the yellow dots here are the nanoparticles one question you might ask is. Well, I can't if I hold it up

  • oh, they're definitely nanoparticles and there are most definitely

  • Nanoparticles in it. In fact, we did a sixty simplest video on this some time ago. You might ask

  • Why does it look red isn't gold gold? Why does this look right?

  • There's a lot of very interesting physics as to why this is right. The yellow dots are the nanoparticles

  • The white is actually the solvent. So that's the liquid in which the particles are dissolved. What's going to happen?

  • Is that the dark bits meet you're about to see you can already see some?

  • Black patches that's where the solvent is evaporating. And so what's going to happen is when we run this

  • These holes are going to open up as the solvent evaporates the nanoparticles love to be wet by the solvent

  • They looked at to be dissolved in the solvent so they will track back as a solvent dee wets as a solvent

  • Evaporates the remaining solvent left on the surface will spread back like this carrying the nanoparticles with it

  • What we'll end up with in the end is a Voronoi tessellation. So let me run this

  • So you see these opening up?

  • Carrying the nanoparticles with them and you can already see the density and they collide

  • And so what's happening here is that you can see as these holes spread out

  • they force the nanoparticles together and ultimately you end up with something that looks like that those tessellations are absolutely everywhere just

  • Earlier this year. There was a scientific American article

  • On this is not a beautiful image

  • This is a dragonfly's wings and you see this same type of tessellation everywhere near to the large-scale structure

  • the universe giant's causway announced from this is the

  • cross-section through a cork from a wine bottle and

  • The point I want to try and make for computerphile audience is in each case. These are effectively physical computers you might argue about the

  • the universe what the large-scale structure universe, but in terms of the

  • Physical and chemical processes that have been weakened exploited to do a computation

  • Which gets me back to this? This was a distribution of coffee shops. Here's our points for our coffee shops. Here's a Verona tessellation

  • lots of calculated by the computer

  • However, this is what happens when we take a droplet of our particles put them on a surface and we look at the final stage

  • And if we overlay this on this the physics has done the computation force. It's not cared about

  • How do I join up the nearest neighbors and how to get the perpendicular bisectors?

  • It's fallen out of the physics and you might think hang on there seems to be a bit of a trick there

  • maybe there is but it's all about thinking about computation and

  • Information processing in different ways. This is almost

  • This is computation not by algorithm but computation by analogy

  • By trying to look at what's happening in a physical system and say well actually can we exploit that?

  • To do a computation for us. There must have been some kind of control in this there

  • You must have decided where those have operational right? So that's in this case

  • I've cheated a little bit shown reason the points were distributed like this is that I work backwards from the image

  • So cheated a little bit, but could we actually program this system? How would we program the system?

  • Well, what we'd have to do is control where the evaporation happens

  • Can we do that?

  • Yes

  • We can take our surface and what we can do is we can oxidize it using the tip of something called a scanning probe

  • Microscope in this case. Those lines were about a hundred

  • Nanometers wide something like are very very small lines

  • Obviously you can some some will recognize the logo at least

  • And what we can do is we can control how the the particles this is the real experiment

  • This is the simulation

  • we can control how the solvent evaporates from the surface by patterning the surface and so that's a couple examples and we can

  • put a lot of different patterns down there the next step in this is can we actually

  • Program the Verona tessellation. Can we put little points two four the evaporation of those points and

  • calculate the

  • tessellation that's something were

  • Actually is going to be stimulated by this video

  • can we part on a surface and drive the formation of the Verona tessellation and can we do a computation that way and

  • Then the values of those array elements can be whatever you want, but they might be for example

  • How much you spent on beer and pizza and coffee and so you could write a very simple program that would let simply say

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