Automatic classification of magnetic field line topology by persistent homology

被引:0
作者
Bohlsen, N. [1 ,3 ]
Robins, V. [2 ]
Hole, M. [1 ]
机构
[1] Australian Natl Univ, Math Sci Inst, Canberra, ACT 2601, Australia
[2] Australian Natl Univ, Res Sch Phys, Canberra, ACT 2601, Australia
[3] Princeton Univ, Princeton, NJ 08540 USA
关键词
Topological data analysis; Persistent homology; Hamiltonian orbits; Magnetic geometry; TRANSPORT; TOKAMAK;
D O I
10.1016/j.physd.2025.134595
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A method for the automatic classification of the orbits of magnetic field lines into topologically distinct classes using the Vietoris-Rips persistent homology is presented. The input to the method is the Poincare map orbits of field lines and the output is a separation into three classes: islands, chaotic layers, and invariant tori. The classification is tested numerically for the case of a toy model of a perturbed tokamak represented initially in its geometric coordinates. The persistent H-1 data is demonstrated to be sufficient to distinguish magnetic islands from the other orbits. When combined with persistent H-0 information, describing the average spacing between points on the Poincare section, the larger chaotic orbits can then be separated from very thin chaotic layers and invariant tori. It is then shown that if straight field line coordinates exist for a nearby integrable field configuration, the performance of the classification can be improved by transforming into this natural coordinate system. The focus is the application to toroidal magnetic confinement but the method is sufficiently general to apply to generic 1 1/2 d Hamiltonian systems.
引用
收藏
页码:1 / 22
页数:22
相关论文
共 42 条
  • [1] THE VIETORIS-RIPS COMPLEXES OF A CIRCLE
    Adamaszek, Michal
    Adams, Henry
    [J]. PACIFIC JOURNAL OF MATHEMATICS, 2017, 290 (01) : 1 - 40
  • [2] Topological Analysis of Magnetic Reconnection in Kinetic Plasma Simulations
    Banesh, Divya
    Lo, Li-Ta
    Kilian, Patrick
    Guo, Fan
    Hamann, Bernd
    [J]. 2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020), 2020, : 6 - 10
  • [4] Berry M.V., 2020, Hamiltonian Dynamical Systems, P27
  • [5] A universal null-distribution for topological data analysis
    Bobrowski, Omer
    Skraba, Primoz
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [6] Boissonnat J.-D., 2022, Novel Mathematics Inspired By Industrial Challenges, P247, DOI DOI 10.1007/978-3-030-96173-2_9
  • [7] Burby J. W., 2023, Nonlinearity, P5884, DOI 10.1088/1361-6544/acf26a
  • [8] General formulas for adiabatic invariants in nearly periodic Hamiltonian systems
    Burby, J. W.
    Squire, J.
    [J]. JOURNAL OF PLASMA PHYSICS, 2020, 86 (06)
  • [9] An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
    Chazal, Frederic
    Michel, Bertrand
    [J]. FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2021, 4
  • [10] UNIVERSAL INSTABILITY OF MANY-DIMENSIONAL OSCILLATOR SYSTEMS
    CHIRIKOV, BV
    [J]. PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 1979, 52 (05): : 263 - 379