Monday, 29 June 2015

Quantum Darwinism



This is an edited excerpt from the book Darwin Does Physics.

Many quantum mysteries have recently been understood by including the effects of the quantum system’s environment as an integral part of explanations of its behaviour. That prior explanations, which attempted to treat quantum systems as isolated entities, led to a theory which, as Feynman famously noted, nobody understood is hardly surprising, We can only imagine how ridiculous a theory of biology would be that tried to described the multitude of adaptations displayed by organisms without references to their environments.

A 2014 review article by Maximilian Schlosshauer describes the historical unfolding of this breakthrough in quantum understanding (1):
It is a curious “historical accident" that the role of the environment in quantum mechanics was appreciated only relatively late. While one can find -for example, in Heisenberg's writings – a few early anticipatory remarks about the role of environmental interactions in the quantum-mechanical description of systems, it wasn't until the 1970s that the ubiquity and implications of environmental entanglement were realized by Zeh. It took another decade for the formalism of decoherence to be developed, chiefly by Zurek
Wojciech Zurek is widely recognized as a leader in our understanding of the nature of quantum interactions between a quantum system and its environment or of quantum decoherence. Zurek’s progress in developing his theory of quantum interactions may be broken into three steps centered on three new concepts:

1) Einselection describes the type of information which may be transferred between a quantum system and in its environment during a quantum interaction. Zurek demonstrated that only information in the form of the system’s ‘pointer states’ can survive transfer to the environment. These pointer states depend upon both the nature of the system and the component of its environment with which it will share information. Pointer states describe the few classical characteristics, such as the systems position or momentum, which is all that the environment can experience of the quantum system

2) Envariance assigns a probability to each of the possible packets of information which may be transferred. These packets correlate with measurement values and thus envariance may be use to predict the outcome of possible measurements. It is of interest that Zurek derived these probabilistic predictions from fundamental quantum axioms rather than following the tradition of including them as a separate axiom.
 
3) Quantum Darwinism describes the relative reproductive success which the different various transferred information packet achieve in their environments. Zurek has shown that it is the classical information described by einselection and envariance that achieves a high level of redundancy in the environment; other types of information have a low survival rate. Zurek considers that the high level of redundancy of classical information provides classical reality with its objective nature; numerous observers will agree on the nature of reality as they have access only to a common and highly redundant but limited pool of information.


Together these concepts describe quantum interactions in terms of a Darwinian process and I will refer to all three as the process of quantum Darwinism. In each generation of information transfer just a small subset of information is able to survive and reproduce in its environment. This is deeply analogous to natural selection where in each generation of genetic information transfer just a small subset of the possibilities are able to survive and reproduce in their environments. 

Figure 1: Wojciech Zurek

It is perhaps shocking to many physicists that the central organizing principle of biology has been used to explain one of the most fundamental physical processes. Although Zurek’s technical description has been endorsed within consensus physics, its Darwinian implications have been shunned. If you Google ‘quantum Darwinism’ and ignore entries written by him or myself, you will be left with only meager comment. Zurek however is unequivocal concerning the Darwinian nature of his theory (2):
The aim of this paper is to show that the emergence of the classical reality can be viewed as a result of the emergence of the preferred states from within the quantum substrate thorough the Darwinian paradigm, once the survival of the fittest quantum states and selective proliferation of the information about them are properly taken into account.
In my view this conjunction of fundamental physical and biological explanations provides great hope for the unification of scientific understanding within a few overarching concepts such as universal Darwinism.

Quantum Darwinism provides a detailed description of a Darwinian process in terms of a single cycle, the evolution which occurs during a single generation. While the shift in probabilities between two generations may be the unit of evolutionary change it is the long term effects due to numerous repetitions of this cycle which produce the dramatic accomplishments of evolutionary systems.

To date the development of the theory of quantum Darwinism has focused on processes involved in a single cycle and has not yet paid much attention to the long term consequences produced by continual iterations over cosmic time. We should be careful to understand that generational succession in quantum Darwinism refers to the same phenotype, such as an atom, only at a later time and possibly under slightly different circumstances. In this regards it may be analogous to generations of single-celled asexual life where succeeding generations are not truly new individuals but may rather be considered as variations on the same individual with perhaps small changes in circumstance.

In a number of earlier sections I have repeated Zurek’s claim that ‘classical reality emerges from the quantum substrate’ but have not provided much explanation for that astounding assertion. The claim itself may seem somewhat metaphysical, as if classical reality arises as a kind of ephemeral vapor from a more fundamental quantum reality. With a better understanding of the mechanisms of quantum Darwinism, we are now prepared to discuss this dramatic claim.  

We might view the quantum substrate as a vast sea of quantum systems which can interact with each other only by way of the four fundamental forces – make that three if gravity is considered emergent from quantum forces. As each system can only receive information concerning any other system by way of these few forces, severe constraints are placed on the information which can be received. Zurek understands these constraints as a Darwinian selection mechanism which he describes within the theory of quantum Darwinism. ‘Classical’ information best survives the transfer to other quantum systems. Thus the information that one system may acquire of another is largely classical information. 

We should understand that this information is physical, it describes the only forces known to operate in the universe. Although these are quantum forces they are well described by Newton’s classical mechanics because the classical information, even though it describes only a small subset of the quantum substrate is all that is available, all that passes through the Darwinian selection mechanism. This information obeys classical logic and the mathematics of probability theory which we consider forms of common sense. It is insufficient to fully describe the quantum reality; that really is weird and seems to operate as described by other forms of mathematics that do not jibe with common sense.

Crucially, the information which can survive the transfer entails all that one entity can feel, understand or react to concerning another entity. In other words the ability of any entity to detect the outside world is largely restricted to the classical characteristics of that world. Thus classical reality emerges from the quantum substrate. 

Both the logic we are familiar with and the physical nature of our reality are explained as due to a Darwinian selection mechanism which regulates the flow of information between entities. The universe is not static. On the reception of information entities often react with an acceleration, broadly as described by the classical theories of Newtonian mechanics, Maxwell’s electro-magnetism and the theories of special and general relativity.  These are the forces and logic which defines our classical reality. They are also the forces which powered the evolution of the universe from the Big Bang onward. 

Zurek’s theory implies that this evolution should be understood as the operation of a Darwinian process. Each generation of information exchanged by quantum systems is selected on the basis of its reproductive success and earlier physical forms are distinguished from later ones by their relative ability to survive and reproduce. In this view we can understand the evolution of the universe since the Big Bang as a form of Darwinian evolution.

From the beginning the great power of natural selection was seen not so much in changes over a single generation, but rather in the cumulative effect of these changes over evolutionary history. Already in On the Origin of Species Darwin made the case that the many biological forms found in nature have evolved from a single ancestral individual through the process of natural selection. We might say that over evolutionary time genomes have successively probed the huge number of environmental circumstance in which they have found themselves for strategies of reproductive success and that new phenotypes have been successively constructed to fit those circumstances.

Zurek has described decoherence and quantum Darwinism as responsible for the transition from quantum to classical realities. In short classical reality is composed of an extremely small subset of quantum possibilities which are selected through a Darwinian process. In this view we must see the evolution of classical reality as originating in this same Darwinian process. Thus the history of the universe may be considered as shaped through the operation of quantum Darwinism.

In Zurek’s terminology ‘pointer states’ are those quantum states which may exist in classical reality. As he explains these states are defined by their ability to achieve reproductive success within their environments (3):
According to decoherence theory, the ability to withstand scrutiny of the environment defines pointer states. As I will discuss, the proliferation of records about those states throughout the environment is the essence of quantum Darwinism.
We often assume the physical evolution of the universe since the Big Bang to be a rather straight forward case of cause and effect; the continued expansion and cooling of the universe resulted in new forms and phenomena. The Wikipedia article on the Chronology of the Universe (4) provides many examples of this way of thinking including:
In the second phase, this quark–gluon plasma universe then cooled further, the current fundamental forces we know take their present forms through further symmetry breaking – notably the breaking of electroweak symmetry – and the full range of complex and composite particles we see around us today became possible, leading to a gravitationally dominated universe, the first neutral atoms (~ 80% hydrogen), and the cosmic microwave background radiation we can detect today.
Zurek’s theory suggests that this historical process may have been more nuanced. New physical forms may have emerged as the universe changed due to their ability to discover new environmental niches in which they could survive.

Within the scope of this theory we find a close analogy to natural selection. We might say that over evolutionary time quantum systems have successively probed the huge number of environmental circumstance in which they have found themselves for strategies of reproductive success and that new phenotypes have been successively constructed to fit those circumstances. If we understand ‘phenotype’, in this context, as the succession of physical forms, the physical evolution of the universe since the Big Bang may be understood in terms of a Darwinian process: Quantum Darwinism.

Bibliography

1. Schlosshauer, Maximilian. The quantum-to-classical transition and decoherence. [book auth.] M. Aspelmeyer, et al. Handbook of Quantum Information. 2014.
2. Zurek, Wojciech H. Quantum Darwinism and envariance. [book auth.] P. C. W. Davies, and C. H. Harper, eds. J. D. Barrow. Science and Ultimate Reality: From the Quantum to the Cosmos. s.l. : Cambridge University Press, 2004.
3. Quantum Darwinism, Classical Reality, and the randomness of quantum jumps. Zurek, Wojciech H. 2014, Physics Today, Vols. vol. 67, pp. 44-50 (2014).
4. Wikipedia. Chronology of the Universe. Wikipedia. [Online] [Cited: June 28, 2015.] https://en.wikipedia.org/wiki/Chronology_of_the_universe.


Monday, 8 June 2015

Science as a Darwinian process





Over the past forty years my intellectual life has focused almost exclusively on a single idea: Universal Darwinism. Fortunately due to its ‘universal’ nature this one idea has not been overly constraining. In fact I consider it capable of a huge unification of scientific understanding. As I have attempted to communicate in my writings, much of scientific understanding may be summarized as instances of Darwinian processes and as I am attempting to demonstrate in my next book, this understanding may be further summarized in a few potent spiritual-like principles, one of which is:

Knowledge is the creator and essence of all things

Such statements may seem a little too new-age but I believe this one is backed by overwhelming scientific evidence and is actually little more controversial than John Wheeler’s claim that ‘everything is information’.

Perhaps the foremost form of cultural knowledge is science and it is important for the development of my paradigm to be able to include science itself within the framework of Universal Darwinism. Most aspects of the process of science are easily accommodated but one aspect has presented a substantial puzzle.


Philosophers of science have long considered science as a Darwinian process (1; 2; 3). Scientific hypotheses are largely learned (a type of inheritance) by the generation of science students from the parent generation of scientists but there is inevitably some variation amongst their understandings. Scientific ideas are also often re-thought or re-copied by researchers, with possibly some variations, and to complete the Darwinian process there is selection amongst the hypotheses largely due to their simplicity, elegance and the support they receive from experimental evidence.

Although this process has been largely accepted for decades there remains one troubling problem: where do new hypotheses come from? In the Darwinian process of natural selection the parallel question is ‘where do new genes come from’ and this is usually explained as random genetic mutation or copying errors. In science, however the formation of new hypotheses may not appear to be a random process. Scientist spend much of their time in the purposeful pursuit of trying to formulate suitable hypotheses and their success is often experienced as a ‘eureka’ moment. 

Researchers are constantly introducing new hypotheses to the scientific literature for evaluation by their peers and judgement by the evidence but the process by which they formulate these new hypotheses is poorly understood. It is usually characterized as a purposeful ‘creative’ process having little in common with the random processes which introduce new genetic sequences into the repertoire of biology.

In recent times our understanding of human cognitive processes has often been illuminated by the construction of computerized models. When a machine model can be constructed which duplicates some puzzling human cognitive ability it adds plausibility to the hypothesis that the human brain performs this ability in a manner analogous to the computer algorithm. For instance the Bayesian Brain School of neuroscience argues that the human brain operates largely as a Bayesian computer; selecting from amongst the many competing hypotheses that it generates according to the sensory data it receives. These hypotheses are made more plausible when the researchers can demonstrate Bayesian computer models which duplicate some aspects of human cognitive abilities.

Still the question remains: how does the brain produce innovative new hypotheses? Just now light has been shed on solving this problem by a Darwinian computer algorithm which has discovered a new scientific model or hypothesis describing how Planarian worms manage to regenerate damaged tissue (4).

Planarian worms are small, some as small as 1/8 of an inch. They have been of great interest to biology for over a hundred years due to their remarkable ability to re-grow removed tissue. For instance if one is cut in two, two new complete separate individuals will be regenerated (5).

Using the techniques of molecular biology, 240 genes have been identified that are involved in this worm’s regenerative abilities.  However the mechanism by which these genes operate to produce regeneration remained elusive. Some of the genes produce proteins but some regulate the activity of other genes. Further, the mechanism by which the resulting proteins actually produce regeneration remained unclear. The result is that up to now there has been no comprehensive model or hypothesis describing the process.

A team of biologists at Tufts University has just discovered a model which can explain all of the experimental evidence. Perhaps the most remarkable aspect of this discovery is that it was indirect; scientists did not discover it directly but rather developed a computer program which made the actual discovery. The team of scientists programmed a computer to evolve models with random variations through a Darwinian process. At each generation those model which most closely predicted the experimental evidence were selected, with small variations, to form the next generation of model exploration. In the end this process discovered for the first time a model in complete conformance with the data.


Figure 1: A high level schematic of the computer generated model for Planarian regeneration.
 
Amazingly this discovered model, although it has eluded human researchers, is readily understandable and straightforward to those familiar with the problem. Further, it posits the involvement of proteins that had not been identified in previous experiments. Attempting to experimentally identify these predicted proteins provides for a straightforward means of further experimental testing of the model.  

It is plausible that complete models of complex phenomena, such as that of an entire cell, may remain forever beyond the scope of the human intellect to conceive, but perhaps not beyond the scope of what computers, properly programmed, may discover. Perhaps of even greater importance this research suggests that human hypothesis formation or model creation may not be an impenetrable intuitive ability but may arise from an unconscious Darwinian process taking place within the human brain. 

My conception of science as a Darwinian process has focused on the concept of a model or a family of competing hypotheses being selected according the assignment of updated probabilities when new evidence is received. This portion of the scientific method is straightforward and well described by the algorithms of Bayesian inference. Mathematical theorems tell us how the probabilities must be updated on the reception of new information.
However, new and unexpected evidence may be found that seems to make all of the hypotheses within the model more unlikely. In other words we may find that our evidence has outgrown the model. In this case how does science find a new model that will more fully embrace all the evidence? 

The received wisdom within the scientific community is that the process of model formation is akin to an art form, that it is the creative portion of science and not amenable to algorithmic description. However a model of Planarian regeneration which conforms to the experimental evidence and has eluded human investigators for many years has now been discovered by a computer algorithm. This must cause us to re-evaluate the idea that hypothesis formation is an ill-defined and opaque creative process. The fact that the algorithmic process which discovered this model is a Darwinian algorithm is just icing on the cake.

Bibliography

1. Campbell, Donald. Evolutionary Epistemology. [book auth.] P. A. Schilpp. In The philosophy of Karl R. Popper. s.l. : Open Court. , 1974, pp. 412-463.
2. Popper, Karl. Objective Knowledge. s.l. : Claredon Press, 1972.
3. Hull, David L. Science as a Process: An Evolutionary Account of the Social and Conceptual Development of Science. Chicago and London : The University of Chicago Press, 1988.
4. Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration. Lobo, Daniel and Levin , Michael . s.l. : PLOS, 2015. DOI: 10.1371/journal.pcbi.1004295.
5. Wikipedia. Planarian. Wikipedia. [Online] [Cited: June 6, 2015.] http://en.wikipedia.org/wiki/Planarian.