In the last several posts I have introduced many of the basic concepts and jargon from the field of complexity science:
Inapplicability of reductionism and constructionism (Laplacian certainty) to complex systems.
I shall introduce more concepts as we go along, but let us now start our journey of tracing the evolution of complexity from the Big Bang onwards.
Immediately after the Big Bang the information content of our universe was nil. There was just a single force field or radiation field, with no alternative states, so the missing information was nil (recall the Shannon-information equation I = c log (1/P) in Part 21; when P = 1, we get I = 0.).
Very soon, structure appeared and the information content, or the degree of complexity, started increasing.
Chaisson (2001) identified three eras in the cosmic evolution of complexity.
1. In the beginning there was only radiation, with such a high energy density that there was hardly any structure or information content in the universe; it was just pure energy.
2. As the universe expanded and cooled, a veritable phase transition, or bifurcation in the phase-space trajectory, occurred, resulting in the emergence of matter coexisting with radiation. This marked the start of the second era, in which a high proportion of energy resided in matter, rather than in radiation.
3. The third era was heralded by the onset of 'technologically manipulative beings', namely humans.
An important way of defining the degree of complexity was introduced by Chaisson (2001), and it is different from the information based definition I have given so far in terms of either the algorithmic information content (AIC) or the effective complexity. He emphasized the importance of a central physical quantity for understanding cosmic evolution, namely FREE-ENERGY RATE DENSITY, or specific free energy rate, denoted by Φ. Chaisson emphasized the fact that 'energy flow is the principal means whereby all of Nature’s diverse systems naturally generate complexity, some of them evolving to impressive degrees of order characteristic of life and society'.
The flow refers to rates of input and output of free energy. If the input rate is zero, a system would sooner or later come to a state of equilibrium, marking an end to the evolution of complexity. If the output rate is zero, there would be disastrous consequences. Both input and output flow rates have to be nonzero and mutually compatible.
The energy per unit time per unit mass (quantifying the CHAISSON COMPLEXITY Φ) has the units of power. Other similar quantities in science are: luminosity-to-mass ratio in astronomy; power density in physics; specific radiation flux in geology; specific metabolic rate in biology; and power-to-mass ratio in engineering.
Chaisson estimated the values of this parameter for a variety of systems. The results are amazing, and important. Here are some typical estimated values:
Galaxies (Milky Way) : 0.5 ergs per second per gram
Stars (Sun) : 2
Planets (Earth) : 75
Plants (biosphere) : 900
Animals (human body) : 20,000
Brains (human cranium) : 150,000
Society (modern culture) : 500,000
Thus the degree of complexity of our universe can be seen to be increasing rapidly. And we humans are responsible for much of this increase. When we emerged on the scene (through Darwinian evolution), we brought with us a relatively large brain and the ability to develop spoken and written language. Development of powerful computers followed in due course, as also immense telecommunication networks. Information build-up and flow is the stuff we thrive on.
There are no indications of life anywhere else in our universe. Leave aside creatures with intelligence comparable to or surpassing that of humans, even the most primitive extra-terrestrial life has not been found. Therefore, from the vantage point of increase of complexity, emergence of humans has turned out to be something of cosmic importance.
The concept of the free-energy-rate-density measure of complexity and its evolution is very useful. An alternative description can be given in terms of our original definition of degree of complexity in terms of the algorithmic information content (AIC). I shall do that in the next post.