Towards a Quantum Model of Life:

Big Data, Topology and Field Theory

Mario Rasetti

Fondazione ISI, Via Alassio 11C, Torino Italy


No microscopic interaction or reaction exists in living matter that does not follow the laws of ordinary quantum physics and chemistry. Also, living matter is complex: biological functions appear on stage only associated with structurally complex forms. Finally, what is special about living matter is the evolution of those constraints that harness the execution of collective functions, evolving hierarchies of collective order while inert matter evolves disorder. To give rise to life, molecules must be able to function symbolically, i.e. to operate as records, codes, signals. Here we deal with the question as how a molecule becomes a message; how large and complex a system must be to support life; how communication between molecules can be distinguished from the interactions between molecules which account for their states of motion.

We argue that a molecule does not become a message only because of its shape or structure, but in the wider context of the system of physical constraints (a "symmetry") whereby information plays a dynamical role. Living molecules extract information from large sets of data and manipulate it. The goal is thus to understand a higher level: not molecular structures, but the structure of the language molecules mutually communicate with. The aim is to construct a virtual Turing-like machine accounting for life. This goal is approached in five steps: i) characterize living vs. inert matter in terms of structural features; ii) prove that quantum mechanics, capable as it is to account for states able to encode, evolve and transfer information, can account for life; iii) try and understand whence living matter derives its ability to handle data: topological methods appear to be the (only) answer; iv) build – inspired by the spin network quantum automaton scheme for information manipulation, and based on the topology of data space – a quantum topological field theory associated with living matter, able to treat large data sets; v) represent, essentially through its symmetries, the characterizing features of such field theory.