Universality of efficiency at maximum power

We investigate the efficiency of power generation by thermo-chemical engines. For strong coupling between the particle and heat flows and in the presence of a left-right symmetry in the system, we demonstrate that the efficiency at maximum power displays universality up to quadratic order in the deviation from equilibrium. A maser model is presented to illustrate our argument.Comment: 4 pages, 2 figure

The Optimal Size of Stochastic Hodgkin-Huxley Neuronal Systems for Maximal Energy Efficiency in Coding of Pulse Signals

The generation and conduction of action potentials represents a fundamental means of communication in the nervous system, and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in a process of transfer pulse signals with action potentials. By computer simulation of a stochastic version of Hodgkin-Huxley model with detailed description of ion channel random gating, and analytically solve a bistable neuron model that mimic the action potential generation with a particle crossing the barrier of a double well, we find optimal number of ion channels that maximize energy efficiency for a neuron. We also investigate the energy efficiency of neuron population in which input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal combination of the number of neurons in neuron population and the number of ion channels in each neuron that maximize the energy efficiency. The energy efficiency depends on the characters of the input signals, e.g., the pulse strength and the inter-pulse intervals. We argue that trade-off between reliability of signal transmission and energy cost may influence the size of the neural systems if energy use is constrained.Comment: 22 pages, 10 figure

Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO

Exceptional Point of Degeneracy in Linear-Beam Tubes for High Power Backward-Wave Oscillators

Abstract An exceptional point of degeneracy (EPD) is induced in a system made of an electron beam interacting with an electromagnetic (EM) guided mode. This enables a degenerate synchronous regime in backward wave oscillators (BWOs) where the electron beams provides distributed gain to the EM mode with distributed power extraction. Current particle-in-cell simulation results demonstrate that BWOs operating at an EPD have a starting-oscillation current that scales quadratically to a non-vanishing value for long interaction lengths and therefore have higher power conversion efficiency at arbitrarily higher level of power generation compared to standard BWOs