(Note: All previous parts in the Complexity Explained series by Dr. Vinod Wadhawan can be accessed through the ‘Related Posts’ listed below the article.)

In any evolutionary process, what evolves is complexity. Chemical complexity evolved till some of it became indistinguishable from biological complexity. Evolution of biological complexity is determined by two main factors: natural selection (made famous by Charles Darwin), and self-organization. I focus on the natural-selection aspect of biological evolution in this article.

13.1 Darwinian Evolution

The greatest single contribution to the subject of complexity was made (unwittingly, perhaps) by Charles Darwin. The year 2009 marked the second birth centenary of Darwin, as also 150 years of the publication of his celebrated book On the Origin of Species by Means of Natural Selection.

Living organisms are open systems, i.e. they are constantly exchanging matter and energy with the environment. There is a fair amount of dynamic equilibrium between a living organism and its surroundings. The organism cannot survive if this equilibrium is disturbed too much, or for too long. The fact that an organism survives implies that, in its present form, it has been able to adapt itself to the environment. If the environment changes slowly enough, living entities can evolve (over a long enough time period) a new set of capabilities or features which enable them to survive even under the changed conditions. Over long periods of such evolutionary change, creatures may even develop into new species. This was the message of Charles Darwin’s (1859) bold theory of evolution through cumulative natural selection. He demonstrated that adaptation to the environment was a necessary outcome of the exchange processes going on between organisms and their surroundings. A consequence of his theory was that all living organisms are the descendants of one or a few simple ancestral forms. Read the full story

(Note: All previous parts of Dr. Wadhawan’s series ‘Complexity Explained’ can be accessed through the Related Posts list at the bottom of this article.)

There is a distinction between replication and reproduction. Probably, the earliest living entities were able to reproduce but not to replicate. Cells can reproduce, but only molecules can replicate. Reproduction in the case of such primitive cells means to divide into two cells with the daughter cells inheriting approximately equal shares of the constituents of the cell. By contrast, replication for a molecule means the creation of an exact copy of itself by suitable chemical processes. Here I describe John von Neumann’s computer-simulation studies on self-reproduction, after introducing the notion of cellular automata. Studies on cellular automata help us understand life processes.

11.1 Introduction

Present-day life processes involve metabolic reproduction and replication. Freeman Dyson (1985) argued that metabolic reproduction and replication are logically separable propositions. He pointed out that Darwinian natural selection does not require replication, at least for simple creatures. According to Dyson, it is likely that life originated twice, with two separate kinds of organisms, one capable of metabolism without exact replication, and the other capable of replication without metabolism. At some stage the two features came together. He suggested, probably, that the earliest living creatures were able to reproduce but not to replicate. I shall discuss Dyson’s dual-origin-hypothesis for life in the next article in this series. Here I focus on some computer-simulation aspects of replication and reproduction.

An automaton has two components, which are now known by the names hardware and software. Roughly speaking, software embodies information, and hardware processes information. And the rough analogy to biology is: nucleic acid is software, and protein is hardware. Usually, protein is the essential component for metabolism, and nucleic acid is the essential component for replication. An automaton that has only hardware but no software can exist independently and maintain its metabolism so long as it finds food to eat or numbers to crunch. By contrast, an automaton that has only software but no hardware can lead only a parasitic existence (e.g. viruses). Read the full story

(Note: All previous parts of Dr. Wadhawan’s series on complexity can be accessed through the Related Posts list at the bottom of this article.)

We live only to discover beauty. All else is a form of waiting. Khalil Gibran was happy describing life like this, but scientists have a lot of trouble defining it succinctly and comprehensively. It is not easy to give a crisp definition of life, just as it is not easy to define complexity in a context-independent and unique way. Perhaps there is no clear dividing line between life and nonlife. Nevertheless, the emergence of what many of us intuitively understand to be life marked a major milestone in the evolution of complexity in our world. I survey some of the scientific attempts at defining life, as a prelude to discussing the likely mechanisms for the origin of life in a future article in this series.

10.1 What is Life?

Here are a couple of descriptions of life. Eric Chaisson (2001) first:

But what is life? Like time, life is obvious to discern yet elusive to define. Although most biologists generally skirt the issue, we suggest that our very essence can be defined as follows: Life is an open, coherent, spacetime structure maintained far from thermodynamic equilibrium by a flow of energy through it - a carbon-based system operating in a water-based medium, with higher forms metabolizing oxygen.

Margulis and Sagan (2002) next:

Life does not exist in a vacuum but dwells in the very real difference between 5800 Kelvin incoming solar radiation and 2.7 Kelvin temperature of outer space. It is the gradient upon which life’s complexity feeds.

The origin of life (as also consciousness) is the most dramatic of all emergent phenomena in nonlinear open systems. But it has not been easy to define life the way we define so many other things in science. For every characteristic believed to define life, people have come up with an example from the world of the nonliving which also possesses that characteristic. In fact, as we make further progress in the development of sophisticated ‘artificial’ smart structures, including truly smart or intelligent robots, the distinction between the living and the nonliving will get more and more blurred. I have discussed these things in my book on smart structures, and also in an article on robots of the future. Read the full story

(Note: All previous parts in the Complexity Explained series by Dr. Vinod Wadhawan can be accessed through the ‘Related Posts’ listed below the article.)

How did life originate on Earth? Chemical or molecular evolution preceded the emergence of life. Under the influx of low-entropy energy from the Sun, and aided by the presence of certain rocks, atoms and molecules underwent chemical reactions resulting in the emergence of molecules of higher and higher information content or complexity. This article explains how this occurred.

8.1 From Atoms to Molecules

The chemical symbol H is used for an atom of hydrogen, which is the first element in the periodic table of elements. It has a nucleus, which is just a proton in this case, and there is an electron orbiting around the nucleus. The electron has a negative charge, exactly equal in magnitude to the positive charge of the proton. Taking this quantity as the unit of charge, we say that an H atom has a charge number 1 (Z = 1). Taking the mass of the proton as the unit mass, we say that H has a mass number 1 (A = 1). The electron is ~2000 times lighter than the proton. Read the full story

Our universe is believed to have begun with the Big Bang, 10-15 billion years ago. Its degree of complexity at and soon after that moment was next to nil. Then why and how has the cosmic complexity gone on increasing? In fact, it is increasing exponentially fast. The explanation can be traced ultimately to the fact that the universe has been expanding all the time.

7.1 Quantum Mechanics

All phenomena are governed by the laws of quantum mechanics. Quantum theory has been remarkably successful in explaining a vast range of observations. It is also highly counterintuitive. We accept it because there is no better theory for understanding natural phenomena. In any case, there is no reason why the laws of Nature should not be counterintuitive to humans. There is nothing special about us, except that we possess intelligence and consciousness. In the history of the cosmos, we emerged on the scene very recently, whereas the laws of Nature have been there all the time. Read the full story

(For previous articles in the series check the links to ‘Related Posts’ that follow the article.)

Equilibrium is death, because equilibrium means a state of maximum entropy or disorder. Living beings are complex systems that need energy to fight entropy and stay away from a state of thermodynamic equilibrium. The immediate effect of intake of energy by a system at equilibrium is that it is driven away from equilibrium. In this article I discuss how complexity emerges in systems driven far away from equilibrium. Read the full story

(Note: This is the fifth part in the series on Complexity. Please read Part 1, Part 2, Part 3 and Part 4 first.)

As argued in Part 4 of this series of articles, the Shannon formula for information and the Boltzmann-Gibbs formula for entropy provide equivalentdescriptions of the same combinatoric problem. One can formally equate these two formulations and work out the energy required for one bit-flip of information-processing. This equivalence between negative entropy and information is very important in the context of understanding complexity. But the fact remains that the communication of information between two individuals is not independent of their prior states of knowledge and the nature of the language they use for communication of information. Thus, information has a subjective, particularly an anthropocentric, aspect also, as will become clear as we discuss here some of the ways of describing and quantifying complexity.

The Nobel Laureate Murray Gell-Mann is best known to the physics community for his seminal contributions to particle physics. He was awarded the Nobel Prize in 1969 for work which led to his discovery of quarks (the basic building blocks of all atoms, along with leptons). What is less well known is that he also wrote one of the most insightful and pioneering books on complexity. Published in 1994, the book has the interesting title: The Quark and the Jaguar: Adventures in the Simple and the Complex. Quarks have no individuality. They are governed by the laws of quantum mechanics, like everything else in the universe. And yet the same laws of quantum mechanics result in the evolution of complexity from quarks to jaguars and other creatures, which do have individuality. How this happens was the subject matter of Gell-Mann’s book. The title of the book came from a poem by the Chinese-American poet Arthur Sze: Read the full story

(Note: This is the fourth part in the series on Complexity. Please read Part 1, Part 2 and Part 3 first.)

The degree of complexity of a system may be crudely defined as the amount of information needed for describing the structure and function of the system. But what do we understand by ‘information’? In this article I introduce elementary information theory, highlight the inverse relationship between information and entropy, and discuss the computational nature of all natural phenomena. Read the full story