计算竞赛中的马太效应：高难度可能导致51%的优势
The Matthew Effect in Computation Contests: High Difficulty May Lead to 51% Dominance
摘要：
我们研究的计算比赛中，玩家竞争寻找一个解决方案，以一个赢家通吃的奖励给定的问题。搜索过程在参与者之间是独立的，参与者的搜索速度与他们的计算能力成正比。这种抽象模型的一个具体应用是工作量证明类型的区块链系统（如比特币）的挖掘过程。虽然一个人的获胜概率被认为是成比例的，他的计算能力在以前的研究比特币，我们表明，它不是在严格意义上的情况。由于获胜概率和计算能力比例之间的差距，系统中将出现马太效应，富人更富，穷人更穷。此外，我们发现，允许球员池彼此或减少解决方案的数量的问题可能会加剧马太效应，反之亦然。
英文摘要：
We study the computation contests where players compete for searching a solution to a given problem with a winner-take-all reward. The search processes are independent across the players and the search speeds of players are proportional to their computational powers. One concrete application of this abstract model is the mining process of proof-of-work type blockchain systems, such as Bitcoin. Although one's winning probability is believed to be proportional to his computational power in previous studies on Bitcoin, we show that it is not the case in the strict sense. Because of the gaps between the winning probabilities and the proportions of computational powers, the Matthew effect will emerge in the system, where the rich get richer and the poor get poorer. In addition, we show that allowing the players to pool with each other or reducing the number of solutions to the problem may aggravate the Matthew effect and vice versa.
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