title: Biology and the measurement problem.
abstract: Present-day molecular biology, despite its name, is almost entirely committed to a macroscopic, classical picture of the organism; one in which quantum aspects play no role, except as a source of noise. Particularly is this true when dealing with informational aspects; especially "genetic information". The pervading metaphor here is an identification of "genetic information" with DNA sequence, and thence with program or software. We take a quite different view herein. If we presume, to the contrary, that microphysical processes play a role in primary genetic processes, then the "information" they can convey consists of observables evaluated on states. It is then natural to analogize a complex, consisting of (observed system + observer) with the biological partition between genome (observed system) and phenotype (observer). Such a picture immediately raises the deep issues surrounding "the measurement problem" in quantum mechanics. In our brief consideration of such matters, we suggest that standard quantum mechanics is too narrow to deal with the biological pictures, because it is inexorably tied to quantifications of classical, conservative systems; there is no such for an organism. Rather, we are led to consider subsystems we call "sites", for which there is in principle no Hamiltonian. We then query the extent to which such "genetic information" is already subsumed in traditional observables a physicist would measure in vitro in a laboratory. We suggest there is no reason to believe that "genetic information", manifested in bioactivities, is reducible to these. Finally, we contrast this view of "genetic information" with more traditional ideas of program and computability. We argue that computability (algorithms) are entirely classical concepts, in a physical sense, and quite inadequate for a biology (or even a physics) in which quantum measurement processes are important.
authors.affiliation: Department of Physiology & Biophysics, Dalhousie University, Halifax, Nova Scotia, Canada B3L 3H7.
authors.forename: R
authors.initials: R
authors.lastname: Rosen
mesh_terms: D019295:Computational Biology; D016678:Genome; D010641:Phenotype; D014894:Weights and Measures