Bridging the Gap between Life and Physics by Ron Cottam & Willy Ranson

Author:Ron Cottam & Willy Ranson
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

Coda

These are all general properties of a model hierarchy , which we believe characterizes natural systems and their evolution far better than the conventional ‘single entity ’ compositional representation which results from the application of reductionism in science . The implications are many and varied: most particularly, the unstated assumption of science that analysis and synthesis are symmetrically related is found to be insufficient. As we have pointed out, the most prominent property of a differentiated entity is its unification . Not only must a level of organization be viewed in the light of its context at the same scale , but the dissociation of a particular level from the rest of its neighbours must not leave its properties incomplete . A model hierarchy retains these characteristics , whereas a compositional hierarchy does not. This is very much a combination of top-down plus bottom-up approaches to natural properties, as opposed to the uniquely top-down approach of conventional science . All properties are group properties, not just individual ones.

An apparent contradiction must now be resolved. We have suggested that the inter-scale complex regions are Rosennean in nature —thus archetypically analogue —and that they would, therefore, require an infinite number of models to completely formally represent them, or an infinite number of bits for accurate digital representation . But we also conclude that our Natural hierarchy is a primarily digital facsimile of an analogue view of our surroundings. This seemingly analogue view is based on the multi-parametric digitized form of modelling we habitually and apparently necessarily adopt in the human pursuit of representational accuracy . We say apparently, because it is only our reliance on conventional techniques of computation that makes it necessary to fragment the complementary characteristics of Natural phenomena in order to represent them in a tractable form. We have indicated in a previous publication (Cottam et al. 1998) that organisms appear to resort to a more performant chaos -based scheme of information processing . Chaotic systems have the ability to explore their phase spaces and generate new information in a manner which is more related to their characteristic Lyapounov exponents than to their characteristic processing-element size (Nicolis and Prigogine 1989), and this makes it possible to increase information -processing density rather than merely quantity.

On close examination, our original formulation of a multi-scale Natural hierarchy does indeed turn out to be primarily digital in character, because its multi-parametric models are constructed through the fragmentation of phenomenological properties. The complex inter-scale regions, however, should be assessed from an entirely different but still hierarchical viewpoint , as their properties are essentially inseparable. This particular analogue viewpoint is totally inaccessible from a conventional scientific platform, as it is ‘strange’ to traditional modelling and conventional computation : it is characteristic of a holistic approach, rather than a reductive one. We cannot stress this point too strongly: the second hierarchy of complex regions is analogue in nature , as opposed to the digital character of the first one. The first scale hierarchy is reductive towards localization at the right-hand side of Fig.

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