A channel Brownian pump powered by an unbiased external force

A Brownian pump of particles in an asymmetric finite tube is investigated in the presence of an unbiased external force. The pumping system is bounded by two particle reservoirs. It is found that the particles can be pumped through the tube from a reservoir at low concentration to one at the same or higher concentration. There exists an optimized value of temperature (or the amplitude of the external force) at which the pumping capacity takes its maximum value. The pumping capacity decreases with increasing the radius at the bottleneck of the tube.Comment: 14 pages, 9 figure

Complex quantum network model of energy transfer in photosynthetic complexes

The quantum network model with real variables is usually used to describe the excitation energy transfer (EET) in the Fenna-Matthews-Olson(FMO) complexes. In this paper we add the quantum phase factors to the hopping terms and find that the quantum phase factors play an important role in the EET. The quantum phase factors allow us to consider the space structure of the pigments. It is found that phase coherence within the complexes would allow quantum interference to affect the dynamics of the EET. There exist some optimal phase regions where the transfer efficiency takes its maxima, which indicates that when the pigments are optimally spaced, the exciton can pass through the FMO with perfect efficiency. Moreover, the optimal phase regions almost do not change with the environments. In addition, we find that the phase factors are useful in the EET just in the case of multiple-pathway. Therefore, we demonstrate that, the quantum phases may bring the other two factors, the optimal space of the pigments and multiple-pathway, together to contribute the EET in photosynthetic complexes with perfect efficiency.Comment: 8 pages, 9 figure

On Unconstrained Quasi-Submodular Function Optimization

With the extensive application of submodularity, its generalizations are constantly being proposed. However, most of them are tailored for special problems. In this paper, we focus on quasi-submodularity, a universal generalization, which satisfies weaker properties than submodularity but still enjoys favorable performance in optimization. Similar to the diminishing return property of submodularity, we first define a corresponding property called the {\em single sub-crossing}, then we propose two algorithms for unconstrained quasi-submodular function minimization and maximization, respectively. The proposed algorithms return the reduced lattices in $\mathcal{O}(n)$ iterations, and guarantee the objective function values are strictly monotonically increased or decreased after each iteration. Moreover, any local and global optima are definitely contained in the reduced lattices. Experimental results verify the effectiveness and efficiency of the proposed algorithms on lattice reduction.Comment: 11 page