Lee Cronin
speaker
545 appearances
2 recordings
1 series
first heard Dec 2023
last heard Jun 2024
Lee Cronin’s voice in public audio — every appearance, attributed to the second.
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So with molecules, it's not trivial, but it is possible because what you can do, and because I'm a chemist, so I'm kind of like, I see the lens of the world for just chemistry. I break the molecule part, break bonds. And if you take a molecule and you break it all apart, you have a bunch of atoms.
And then you say, okay, I'm going to then take the atoms and form bonds and go up the chain of events to make the molecule. And that's what made me realize, take a toy example, literally a toy example, take a Lego object, which is broken up of Lego blocks. So you could do exactly the same thing. In this case, the Lego blocks are naturally the smallest.
They're the atoms in the actual composite structure.
lego architecture but then if you maybe take you know um a couple of blocks and put them together in a certain way maybe there have a their offset in some way that offset is on the memory you can use that offset again with only a penalty of one and you can then make a square triangle and keep going and you remember those motifs on the chain so you can then leap from the
start with all the Lego blocks or atoms just laid out in front of you and say, right, I'll take you, you, you, connect and do the least amount of work. So it's really like the smallest steps you can take on the graph to make the object. And so for molecules, it came relatively intuitively. And then we started to apply it to language. We've even started to apply it to mathematical theorems.
I'm so well out of my depth, but it looks like you can take minimum set of axioms and then start to build up kind of mathematical architectures in the same way. And then the shortest path to get there is something interesting that I don't yet understand.
It's a hard problem, but actually, if you look at it, so the best way to look at it, let's take a molecule. So if the molecule has... um, 13 bonds. First of all, take 13 copies of the molecule and just cut all the bonds. So take cut 12 bonds and then you just put them in order. Yeah. And then that's how it works. So, and you keep looking for symmetry and re or, or copies.
So you can then shorten it as you go down. And that becomes commentorily quite hard. Um, for some natural product molecules, um,
um it becomes very hard it's not impossible but we're looking at the bounds on that at the moment but as the object gets bigger it becomes really hard and but that's the bad news but the good news is there are shortcuts and we might even be able to physically measure the complexity without computationally calculating it which is kind of insane well how would you do that
Well, in the case of molecule, so if you shine light on a molecule, let's take an infrared, the molecule has each of the bonds absorbs the infrared differently in what we call the fingerprint region. And so it's a bit like, and because it's quantized as well, you have all these discrete kind of absorbences.
And my intuition after we realized we could cut molecules up in mass spec, that was the first go at this.
We did it with using infrared, and the infrared gave us an even better correlation, assembly index, and we used another technique as well in addition to infrared called NMR, nuclear magnetic resonance, which tells you about the number of different magnetic environments in a molecule, and that also worked out. So we have three techniques, which each of them independently gives us
The same or tending towards the same assembly index for a molecule that we can calculate mathematically.
Yeah.
Yeah, I'd say so. I'd agree. So I've started an assembly theory of emoticons with my lab, believe it or not. So we take emojis, pixelate them, and work out the assembly index for the emoji. And then work out how many emojis you can make on the path of emojis. So there's the Uber emoji from which all other emojis emerge. So you can then take a photograph, and by looking at the shortest path...
by reproducing the pixels to make the image you want, you can measure that. So then you start to be able to take spatial data. Now there's some problems there. What is then the definition of the object? How many pixels? How do you break it down? And so we're just learning all this right now.
So you would, first of all, determine the resolution. So then what is your X, Y, and what is the number on the X and Y plane? And then look at the surface area. And then you take all your emojis and make sure they're all looked at the same resolution. Yes. And then we would basically then... do exactly the same thing we would do for cutting the bonds.
You'd cut bits out of the emoji and look at the – you'd have a bag of pixels, and you would then add those pixels together to make the overall emoji.
So in the same way in chemistry we assume the bond is fundamental, what we do in there here is we assume the resolution at the scale at which we do it is fundamental. And we're just working that out. And you're right, that will change, right? Because as you take your lens out a bit, it will change dramatically.
But it's just a new way of looking at not just compression, what we do right now in computer science and data, one big kind of... kind of misunderstanding is assembly theory is telling you about how compressed the object is. That's not right. It's a, how much information is required on a chain of events.
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