Wu Degang, Szeto Kwok Yip
Department of Phyiscs, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, HKSAR, China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Feb;89(2):022142. doi: 10.1103/PhysRevE.89.022142. Epub 2014 Feb 27.
Inspired by the flashing ratchet, Parrondo's game presents an apparently paradoxical situation. Parrondo's game consists of two individual games, game A and game B. Game A is a slightly losing coin-tossing game. Game B has two coins, with an integer parameter M. If the current cumulative capital (in discrete unit) is a multiple of M, an unfavorable coin p(b) is used, otherwise a favorable p(g) coin is used. Paradoxically, a combination of game A and game B could lead to a winning game, which is the Parrondo effect. We extend the original Parrondo's game to include the possibility of M being either M(1) or M(2). Also, we distinguish between strong Parrondo effect, i.e., two losing games combine to form a winning game, and weak Parrondo effect, i.e., two games combine to form a better-performing game. We find that when M(2) is not a multiple of M(1), the combination of B(M(1)) and B(M(2)) has strong and weak Parrondo effect for some subsets in the parameter space (p(b),p(g)), while there is neither strong nor weak effect when M(2) is a multiple of M(1). Furthermore, when M(2) is not a multiple of M(1), a stochastic mixture of game A may cancel the strong and weak Parrondo effect. Following a discretization scheme in the literature of Parrondo's game, we establish a link between our extended Parrondo's game with the analysis of discrete Brownian ratchet. We find a relation between the Parrondo effect of our extended model to the macroscopic bias in a discrete ratchet. The slope of a ratchet potential can be mapped to the fair game condition in the extended model, so that under some conditions, the macroscopic bias in a discrete ratchet can provide a good predictor for the game performance of the extended model. On the other hand, our extended model suggests a design of a ratchet in which the potential is a mixture of two periodic potentials.
受闪烁棘轮的启发,帕隆多博弈呈现出一种看似矛盾的情形。帕隆多博弈由两个独立的博弈组成,博弈A和博弈B。博弈A是一个略输的抛硬币游戏。博弈B有两枚硬币,有一个整数参数M。如果当前累计资金(以离散单位计)是M的倍数,则使用不利硬币p(b),否则使用有利硬币p(g)。矛盾的是,博弈A和博弈B的组合可能导致一个赢的博弈,即帕隆多效应。我们扩展了原始的帕隆多博弈,使其包含M为M(1)或M(2)的可能性。此外,我们区分了强帕隆多效应,即两个输的博弈组合形成一个赢的博弈,以及弱帕隆多效应,即两个博弈组合形成一个表现更好的博弈。我们发现,当M(2)不是M(1)的倍数时,B(M(1))和B(M(2))的组合在参数空间(p(b),p(g))的某些子集中具有强和弱帕隆多效应,而当M(2)是M(1)的倍数时,则既没有强效应也没有弱效应。此外,当M(2)不是M(1)的倍数时,博弈A的随机混合可能会消除强和弱帕隆多效应。遵循帕隆多博弈文献中的离散化方案,我们在扩展的帕隆多博弈与离散布朗棘轮的分析之间建立了联系。我们发现扩展模型的帕隆多效应与离散棘轮中的宏观偏差之间的关系。棘轮势的斜率可以映射到扩展模型中的公平博弈条件,因此在某些条件下,离散棘轮中的宏观偏差可以为扩展模型的博弈性能提供一个良好的预测指标。另一方面,我们的扩展模型提出了一种棘轮的设计,其中势是两个周期势的混合。