Wednesday, August 6, 2014

Super fluid starlings and other physical analogies.

Last week a new article on starling flocks was published by the  COBBS group in Rome. This research group, led by physicist couple Irene Giardina and Andrea Cavagna, are a great example of the varied background of researchers working in collective behavior. They started as theoretical physicists, but wondered how their skills could be applied elsewhere. Such interdisciplinary thinking by physicists isn't uncommon. Physicists often think that their models and tools will be useful for a whole range of things, from voting and elections, to the structure of the brain and, of course, animal groups.

Droplet of super fluid helium.
Taken from talk by Adam Hokkanen.
The idea in the current study is that mathematical models are used to draw an analogy between starling flocks and liquid fluid helium. Waves of turning propagate through the whole group very quickly. So quickly that it can appear they change direction in unison. What the Rome physicists found out was that there is a clear ordering in the turning, with individuals successively copying the direction of their neighbours. The analogy between super fluidity and starlings can be found in a relation between alignment and speed of turning. The higher the alignment of the group, the faster turning propagates through it.
physics and biology.

How are we meant to interpret analogies like this? Should we take them seriously and think that helium and starlings are just the same types of particles? Or should we see the similarity as just a loose rhetoric device? A way of getting the readers attention? These are the sorts of questions that are important if our aim is to apply mathematical models to make analogies. But the answer you get if you ask a theoretical physicists and mathematicians can vary greatly. They can also vary if you ask the same person on different days of the week.

Some physicists take these analogies very seriously indeed. I have been told on quite a few occasions that an experiment on ants or fish is unnecessary because it is "already proved by trivial symmetries in the system". Other times the analogies are made too loosely. No-one could be expected to believe that what is true for magnets is equally true for opinions about upcoming elections, yet this pretty much the assumption in many 'voter' models. The argument is sometimes made that the two systems have "deep parallels" and that the differences between iron filings and people are surface properties!
Other times, the argument is made that these analogies "capture the public's imagination" and are useful for communication.

I wouldn't argue that there is more than one correct way to make an analogy.  However, there is a rule which I think should be followed and it is this:

Modelling analogies between a physical and biological systems should be based on empirical observations from both of the systems.

Flow of starlings in a murmuration.
From Cavagna & Giardina (2014)
This is where Andrea, Irene and the Rome team have excelled. Their starling and midge data has set new standards in 3D reconstruction of movement of animal groups. They aren't satisfied with just speculating on similarities, but check the details. And they have made big steps in collective animal behaviour along the way. They are very clear about the importance of statistical mechanics tools in the way they work, and use analogies like the superfluity and phase transitions, but always couple back to the biology.

This is when physical analogies are at there best. When we use mathematical tools, careful experiment and lateral thinking all mixed together.

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