Nonlinear deterministic equations in biological evolution

We review models of biological evolution in which the population frequency changes deterministically with time. If the population is self-replicating, although the equations for simple prototypes can be linearised, nonlinear equations arise in many complex situations. For sexual populations, even in the simplest setting, the equations are necessarily nonlinear due to the mixing of the parental genetic material. The solutions of such nonlinear equations display interesting features such as multiple equilibria and phase transitions. We mainly discuss those models for which an analytical understanding of such nonlinear equations is available.Comment: Invited review for J. Nonlin. Math. Phy

Predictions and Outcomes for the Dynamics of Rotating Galaxies

A review is given of a priori predictions made for the dynamics of rotating galaxies. One theory - MOND - has had many predictions corroborated by subsequent observations. While it is sometimes possible to offer post hoc explanations for these observations in terms of dark matter, it is seldom possible to use dark matter to predict the same phenomena.Comment: 36 pages (10 are references), 9 figures. Invited review for the Galaxies special Issue "Debate on the Physics of Galactic Rotation and the Existence of Dark Matter." Provides test cases for the importance of prior predictions in the application of the scientific metho

Evolution and non-equilibrium physics. A study of the Tangled Nature Model

We argue that the stochastic dynamics of interacting agents which replicate, mutate and die constitutes a non-equilibrium physical process akin to aging in complex materials. Specifically, our study uses extensive computer simulations of the Tangled Nature Model (TNM) of biological evolution to show that punctuated equilibria successively generated by the model's dynamics have increasing entropy and are separated by increasing entropic barriers. We further show that these states are organized in a hierarchy and that limiting the values of possible interactions to a finite interval leads to stationary fluctuations within a component of the latter. A coarse-grained description based on the temporal statistics of quakes, the events leading from one component of the hierarchy to the next, accounts for the logarithmic growth of the population and the decaying rate of change of macroscopic variables. Finally, we question the role of fitness in large scale evolution models and speculate on the possible evolutionary role of rejuvenation and memory effects.Comment: 6 pages, 6 figure

Laser wakefield and direct acceleration in the plasma bubble regime

Laser wakefield acceleration (LWFA) and direct laser acceleration (DLA) are two different kinds of laser plasma electron acceleration mechanisms. LWFA relies on the laser-driven plasma wave to accelerate electrons. The interaction of ultra-short ultra-intensive laser pulses with underdense plasma leads the LWFA into a highly nonlinear regime (“plasma bubble regime”) that attracts particular interest nowadays. DLA accelerates electrons by laser electromagnetic wave in the ion channel or the plasma bubble through the Betatron resonance. This dissertation presents a hybrid laser plasma electron acceleration mechanism. We investigate its features through particle-in-cell (PIC) simulations and the single particle model. The hybrid laser plasma electron acceleration is the merging concept between the LWFA and the DLA, so called laser wakefield and direct acceleration (LWDA). The requirements of the initial conditions of the electron to undergo the LWDA are determined. The electron must have a large initial transverse energy. Two electron injection mechanisms that are suitable for the LWDA, density bump injection and ionization induced injection, are studied in detail. The features of electron beam phase space and electron dynamics are explored. Electron beam phase space appears several unique features such as spatially separated two groups, the correlation between the transverse energy and the relativistic factor and the double-peak spectrum. Electrons are synergistically accelerated by the wakefield as well as by the laser electromagnetic field in the laser-driven plasma bubble. LWDA are also investigated in the moderate power regime (10 TW) in regarding the effects of laser color and polarization. It is found that the frequency upshift laser pulse has better performance on avoiding time-jitter of electron energy spectra, electron final energy and electron charge yield. Some basic characters that related to the LWDA such as the effects of the subluminal laser wave, the effects of the longitudinal accelerating field, the electron beam emittance, the electron charge yield and potentially applications as radiation source are discussed.Physic

Fluctuations of fitness distributions and the rate of Muller's ratchet

The accumulation of deleterious mutations is driven by rare fluctuations which lead to the loss of all mutation free individuals, a process known as Muller's ratchet. Even though Muller's ratchet is a paradigmatic process in population genetics, a quantitative understanding of its rate is still lacking. The difficulty lies in the nontrivial nature of fluctuations in the fitness distribution which control the rate of extinction of the fittest genotype. We address this problem using the simple but classic model of mutation selection balance with deleterious mutations all having the same effect on fitness. We show analytically how fluctuations among the fittest individuals propagate to individuals of lower fitness and have a dramatically amplified effects on the bulk of the population at a later time. If a reduction in the size of the fittest class reduces the mean fitness only after a delay, selection opposing this reduction is also delayed. This delayed restoring force speeds up Muller's ratchet. We show how the delayed response can be accounted for using a path integral formulation of the stochastic dynamics and provide an expression for the rate of the ratchet that is accurate across a broad range of parameters.Comment: Genetics 201

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a `basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.Comment: submitted to Scientific Repor