Introduction¶
This Python package offers a suite of tools designed for simulating various random surface growth models. The foundational concepts and methodologies are significantly influenced by the work presented in the book by Barabási and Stanley [BarabasiS95] (1995) on fractal concepts in surface growth.
It is known that the fluctuations in the surface growth models fall into a few universality classes. The most famous one is the Kardar-Parisi-Zhang (KPZ) equation Kardar et al. [KPZ86]
where \(\eta\) is a centered Gaussian noise, which is white in both space and time. The KPZ equation (1) is a stochastic partial differential equation (SPDE) [Wal86].
KPZ equation (1) was solved by Hairer [Hai13] in 2013. The fluctuations of the KPZ equation (1) are in the KPZ universality class; see Amir et al. [ACQ11]. Numerous discrete models report the same universality class as the KPZ universality class, including
the ballistic documentation model: [FV85], [MRSB86], [FV85].
the Eden model: [BKR+88], [PRacz85], [JB85] [MJB86], [ZS86].
solid-on-Solid model: …
Theoretical results include the fluctuations of:
History of the Package¶
The foundational elements of this package, which include the random deposition, random deposition with surface relaxation, the ballistic deposition models, and a visualization component, were initially crafted by the first author. These components, forming the basis of the package, were part of a graduate student seminar in October 2023, as documented in Chen [Che23a]. The seminar’s slides provide an excellent introduction to these foundational aspects of the package.
Building upon this foundation, the package has been enriched with simulations for growth models with Tetris pieces. This feature is to test the belief of the universality of the growth models. This feature was developed as a final course project for the course “Math 7820: Applied Stochastic Processes I,” undertaken by the second and third authors in Fall 2023. This is still an ongoing project. More feature and functionalities will be added in the future. Some simulation experiments will be carried out to test the universality of the growth models.
Acknowledgments¶
The references throughout this document have been meticulously compiled and are available in a comprehensive bibliography bank [Che23b].
This work is partially supported by the National Science Foundation (NSF) under Grant No. No. 2246850 (2023–2026) and the collaboration/travel award from the Simons foundation under Award No. 959981 (2022–2027).
Bibliography¶
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