arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2003.01154cs.DScs.DMmath.CO

小集扩张图上 Potts 模型的高效算法

Efficient algorithms for the Potts model on small-set expanders

Charles Carlson, Ewan Davies, Alexandra Kolla

AI总结:

本文针对小集扩张图上的铁磁 Potts 模型,提出一种近似算法,通过高效寻找伪基态并围绕其探索状态空间,解决低温问题在典型实例上的计算可行性。

摘要:

近似计数的一个新兴趋势是表明某些“低温”问题在典型实例上是容易的,尽管存在最坏情况下的困难性结果。对于正则图类,人们通常表明扩张性可以在算法上被利用,并且由于随机正则图以高概率是良好的扩张图,该问题通常是易处理的。受用于唯一博弈的亚指数时间算法中所采用方法的启发,我们为具有小集扩张条件的图上的铁磁 Potts 模型的配分函数开发了一种近似算法。在此类图中,仅探索模型接近基态的状态空间可能是不够的,而我们方法的一个新颖特征是高效地找到一组更大的“伪基态”,使得在每个伪基态周围探索模型就足够了。

英文摘要:

An emerging trend in approximate counting is to show that certain `low-temperature' problems are easy on typical instances, despite worst-case hardness results. For the class of regular graphs one usually shows that expansion can be exploited algorithmically, and since random regular graphs are good expanders with high probability the problem is typically tractable. Inspired by approaches used in subexponential-time algorithms for Unique Games, we develop an approximation algorithm for the partition function of the ferromagnetic Potts model on graphs with a small-set expansion condition. In such graphs it may not suffice to explore the state space of the model close to ground states, and a novel feature of our method is to efficiently find a larger set of `pseudo-ground states' such that it is enough to explore the model around each pseudo-ground state.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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