Eric Sembrat's Test Bonanza

Relics of early life, preceding even the last universal common ancestor of all life on Earth, are present in the structure of the modern day canonical genetic code --- the map between DNA sequence and amino acids that form proteins.  The code is not random, as often assumed, but instead is now known to have certain error minimization properties.  How could such a code evolve, when it would seem that mutations to the code itself would cause the wrong proteins to be translated, thus killing the organism?  Using digital life simulations, I show how a unique and optimal genetic code can emerge over evolutionary time, but only if horizontal gene transfer --- a network effect --- was a much stronger characteristic of early life than it is now.  These results suggest a natural scenario in which evolution exhibits three distinct dynamical regimes, differentiated respectively by the way in which information flow, genetic novelty and complexity emerge. Possible observational signatures of these predictions are discussed.

The ATLAS Experiment at the Large Hadron Collider with its sister experiment CMS reported a discovery last summer of a new boson which is consistent with the Standard Model Higgs boson.  The Higgs particle has been searched for decades. It is the final jewel in the Standard Model of particle physics, a crowning achievement of 20th century science that gives a powerful understanding of fundamental particles and their interactions. In the Standard Model, the Higgs is the quantum of a field that accounts for the masses of those particles.  We will describe the apparatus, the data and other searches. 

What could possibly be new in the Ising model, arguably the most-studied model of statistical physics?  Plenty!  Consider the Ising model initially at
infinite temperature that is suddenly cooled to zero temperature and evolves by single spin-flip dynamics.  What happens?  In one dimension, the ground state is always reached and the evolution can be solved exactly.  In two dimensions, the ground state is reached only about 2/3 of the time, and the long-time evolution is characterized by two distinct time scales, the longer of which arises from topological defects.  In three dimensions, the ground state is never reached and the evolution is quite rich: (i) domains are topologically complex, with average genus growing algebraically with system size; (ii) the long-time state always contains "blinker" spins that can flip ad infinitum with no energy cost; (iii) the relaxation time grows
exponentially with system size.

Despite their everyday familiarity, thin sheets (paper, plastic, fabric, etc.) display remarkable and complex behaviors that still challenge theoretical description. The intricate coupling between the geometry of surfaces and the elasticity of a thin sheet necessarily leads to the formation of singularities, nonlinear elasticity, and geometric frustration. Nevertheless, multicellular organisms - like you - develop their three dimensional structures in part by exploiting these elastic phenomena. These considerations have led to new theoretical and experimental tools to shape elastic sheets into prescribed 3D shapes using the principles of non-Euclidean geometry. I will describe our attempts to design sheets that fold controllably into 3D structures and some related problems in the mechanics of origami, where 3D structure is developed by folding a piece of paper. These techniques open up new avenues in "experimental mathematics", allowing us to explore geometry experimentally.

The defining feature of a black hole is its event horizon through which nothing can escape outward, not even light.  And yet black holes are responsible for the brightest sources that we observe in the universe, from gamma-ray bursts to quasars. Their enormous luminosity arises from the release of gravitational binding energy outside the horizon as material falls inward.  These black hole accretion flows exhibit extraordinary behavior, including outbursts, state transitions, and quasi-periodic variability, most of which continue to defy understanding but which must be related to the magnetohydrodynamic turbulence and radioactive thermodynamics that govern the physics of these flows.  I will review recent theoretical progress in understanding this physics, much of which has been achieved through numerical simulations of the flows.

In this seminar, we will discuss how interactions between discrete electromagnetic (EM) emitters lead to a cooperative response of a metamaterial or cold atomic gas to an incident field.  We will examine a number of ways the cooperative response can be engineered and exploited. The interactions responsible arise from repeated scattering of the field between its discrete constituent elements. Our focus will be on metamaterials, which are composed of subwavelength circuit elements - or meta-atoms - whose electric and magnetic multipole interactions are governed by their design.  We also apply these ideas to atoms in an optical lattice. Understanding cooperative interactions between cold atoms may be useful, for example, in the further enhancement of quantum memories.

Given the complexity of the dynamics of a plasma, reductions are needed. The Hamiltonian framework offers various ways to carry out such reductions. I will introduce some of these methods by considering in particular the example of gyrokinetics, which is a kinetic model for plasmas in a strong magnetic field.

I will describe several models for running insects, from an energy-conserving biped, through a muscle-actuated hexapod driven by a neural central pattern generator, to a reduced phase-oscillator model that captures the dynamics of unperturbed gaits and of impulsive perturbations. I will argue that both simple models and large simulations are necessary to understand biological systems.  The models show that piecewise-holonomic constraints due to intermittent foot contacts confer asymptotic stability on the feedforward system, while leg force sensors modulate motor outputs to mitigate large perturbations. Phase response curves and coupling functions help explain reflexive feedback mechanisms.  The talk will draw on joint work with Einat Fuchs, Robert Full, Raffaele Ghigliazza, Raghu Kukillaya, Josh Proctor, John Schmitt, and Justin Seipel. Research supported by NSF and the J. Insley Blair Pyne Fund of Princeton University.

Bio: 

Philip Holmes was born in England in 1945 and educated at the Universities of Oxford and Southampton. He taught at Cornell from 1977 to 1994, when he moved to Princeton, where he is a Professor of Mechanical and Aerospace Engineering and of Applied and Computational Mathematics and a member of Princeton's Neuroscience Institute. Much of his research has been in dynamical systems and their applications in engineering and the physical sciences, but in the past 15 years he has increasingly  turned to biology. He currently works on animal locomotion and the neuro-dynamics of decision making. He has also published four collections of poems (Anvil Press, London).

The motor protein kinesin uses adenosine triphosphate (ATP) as a fuel and walks along the microtubule filaments in the cell. They are vital for many
cellular processes including intracellular transport and cell division.  Although recent progress in experiments yielded much information regarding
their motility, a structure-based, physical mechanism by which the motor amplifies the ATP-driven small conformational change in the motor head into
a large, 8-nm stepping motion remains largely a mystery. I will discuss molecular dynamics simulations elucidating its force-generation mechanism
and tests by single-molecule optical trap measurements. We find that the motion consists of autonomous force-generation and guided diffusion, where
the partitioning of the two depends on functional needs of different kinesin families.

Multicellular behavior in bacterial biofilms is intimately tied to the production of an extracellular polysaccharide (EPS) matrix that encases the cells and provides physical integrity to the colony as a whole.  As a colony grows from a few cells into a biofilm, a sudden increase in EPS production generates osmotic stresses that cause the biofilm to expand. Moreover, EPS production is triggered by a nutrient depletion gradient that develops in the biofilm due to diffusive mass transport limitations. These polymer physics based biofilm behaviors suggest that EPS production may have evolved in biofilms to beat the diffusion limit of nutrient transport into the colony, though no direct observation of nutrient transport has been observed previously. In this talk I will discuss measurements of nutrient transport into b. subtilis biofilms and show that when EPS production is up-regulated, the polymer sucks fluid into the colony with a characteristic time dependence like that of pressure driven flow.

In contrast to bacteria in biofilms, eukaryotic cell behavior in tissues is intimately tied to forces generated by molecular motor-driven contractions.  Contraction generated tensions are balanced by deformations in the cell's microenvironment, by internal cytoskeletal structures, and by the incompressible cytosolic fluid contained within the cell membrane.  However, contraction generated pressures cannot be supported by the cytosol if the cell membrane is adequately permeable.  Small, non-selective pores called gap junctions connect cells in a layer, allowing small molecules to pass between cells.  In the second half of this talk I will discuss measurements of contraction driven fluid movement across gap junctions connecting neighboring cells.  We observe contracting cells pushing fluid into their neighbors.  To study the mechanics of intercellular fluid flow, we apply biologically relevant pressures to large regions of cells in a monolayer with a micro-indentation system.  We directly measure indentation force and volume as a function of time to determine fluid flow rates and associated stresses between cells.  We find that gap-junction permeability does not limit fluid transport between cells, and that fluid flow is controlled by a balance of cytoskeletal tension throughout the cell monolayer.