arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1701.04040cond-mat.stat-mech
收藏

多粒子群平均场模型的低温反问题

Inverse problem for multi-species mean field models in the low temperature phase

Micaela Fedele, Cecilia Vernia

摘要:

在本文中,我们解决了一类平均场模型(Curie-Weiss模型及其多物种版本)的逆问题时,存在多个热力学状态,如在低温相的相空间是集群。逆问题在于从根据模型的分布生成的配置数据开始重构模型参数。我们表明,不考虑许多国家的存在下的反演过程的应用程序产生非常差的推理结果。利用聚类算法解决了这一问题。当系统具有正、负磁化两种对称状态时,只需将磁化强度的符号从正翻转到负(反之亦然),就能以较小的计算量得到参数重构。当系统处于临界状态时,参数重建失败:在这种情况下,我们给出了居里-外斯模型的正确反演公式,并证明了它们可以用来测量系统接近临界状态的程度。

英文摘要:

In this paper we solve the inverse problem for a class of mean field models (Curie-Weiss model and its multi-species version) when multiple thermodynamic states are present, as in the low temperature phase where the phase space is clustered. The inverse problem consists in reconstructing the model parameters starting from configuration data generated according to the distribution of the model. We show that the application of the inversion procedure without taking into account the presence of many states produces very poor inference results. This problem is overcomed using the clustering algorithm. When the system has two symmetric states of positive and negative magnetization, the parameter reconstruction can be also obtained with smaller computational effort simply by flipping the sign of the magnetizations from positive to negative (or viceversa). The parameter reconstruction fails when the system is critical: in this case we give the correct inversion formulas for the Curie-Weiss model and we show that they can be used to measuring how much the system is close to criticality.

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。

↑