ABSTRACT
It is pointed out that the mystery of how biological systems measure their lengths vanishes away if one premises that they have discovered a way to generate linear waves analogous to compressional sound. These can be used to detect length at either large or small scales using echo timing and fringe counting. It is shown that suitable linear chemical potential waves can, in fact, be manufactured by tuning to criticality conventional reaction-diffusion with a small number substance. Min oscillations in Escherichia coli are cited as precedent resonant length measurement using chemical potential waves analogous to laser detection. Mitotic structures in eukaryotes are identified as candidates for such an effect at higher frequency. The engineering principle is shown to be very general and functionally the same as that used by hearing organs.
Subject(s)
Escherichia coli/cytology , Adenosine Triphosphatases/metabolism , Animals , Bacterial Proteins/metabolism , Biomedical Engineering , Biophysical Phenomena , Cell Cycle Proteins/metabolism , Cytoskeletal Proteins/metabolism , Diffusion , Escherichia coli Proteins/metabolism , Giant Cells/cytology , Lasers , Models, Biological , Motion , Neurons/cytology , Oscillometry , Spectrometry, Fluorescence , Spindle ApparatusABSTRACT
Despite their cultural differences, physics and biology are destined to interact with each other more in the future. The reason is that modern physics is fundamentally about codification of emergent law, and life is the greatest of all emergent phenomena.
Subject(s)
Biophysics , Biophysics/methods , Biophysics/organization & administrationABSTRACT
Experience with complex systems more primitive than the brain teaches important lessons about big data in biology. Chief among them is that physical laws, relationships among measured things that are always true, emerge out of chaos, not the other way around. Correct prediction (as opposed to incorrect prediction) from large data sets requires understanding of these laws. The reason is that the same processes that make them also make the system wildly error-intolerant if the errors are too large. This instability routinely causes computer simulations of even primitive systems to fail by enabling mistakes to cascade into ever worsening falsehoods. The more complex and sophisticated the system is, the more intolerant to errors it becomes.
Subject(s)
Brain/physiology , Connectome/methods , Physical Phenomena , Animals , Computer Simulation , HumansABSTRACT
Recently, a new phenomenological Hamiltonian has been proposed to describe the superconducting cuprates. This so-called Gossamer Hamiltonian is an apt model for a superconductor with strong on-site Coulomb repulsion between the electrons. It is shown that at half-filling the Gossamer superconductor with strong repulsion is unstable toward an antiferromagnetic insulator. The superconducting state undergoes a quantum phase transition to an antiferromagnetic insulator as one increases the on-site Coulomb repulsion. Near the transition the Gossamer superconductor becomes spectroscopically indistinguishable from the insulator.
