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Grid-free weighted particle method applied to the Vlasov–Poisson equation

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We study a grid-free particle method based on following the evolution of the characteristics of the Vlasov–Poisson system, and we show that it converges for smooth enough initial data. This method is built as a combination of well-studied building blocks—mainly time integration and integral quadratures—and allows to obtain arbitrarily high orders. By making use of the Non-Uniform Fast Fourier Transform, the overall computational complexity is \( {\mathcal {O}}(P \log P + K^d \log K^d) \), where \( P \) is the total number of particles and where we only keep the Fourier modes \( k \in ({\mathbb {Z}}^d)^* \) such that \( k_1^2 + \dots + k_d^2 \le K^2 \). Some numerical results are given for the Vlasov–Poisson system in the one-dimensional case.

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References

  1. Besse, N., Mehrenberger, M.: Convergence of classes of high-order semi-Lagrangian schemes for the Vlasov-Poisson system. Math. Comput. 77(261), 93–123 (2008). https://doi.org/10.1090/S0025-5718-07-01912-6

    Article  MathSciNet  MATH  Google Scholar 

  2. Charles, F., Després, B., Mehrenberger, M.: Enhanced Convergence Estimates for Semi-Lagrangian Schemes Application to the Vlasov-Poisson Equation. SIAM J. Numer. Anal. 51(2), 840–863 (2013). https://doi.org/10.1137/110851511

    Article  MathSciNet  MATH  Google Scholar 

  3. Filbet, F.: Convergence of a Finite Volume Scheme for the Vlasov-Poisson System. SIAM J. Numer. Anal. 39(4), 1146–1169 (2001). https://doi.org/10.1137/S003614290037321X

    Article  MathSciNet  MATH  Google Scholar 

  4. Barré, J., Olivetti, A., Yamaguchi, Y.Y.: Algebraic dam** in the one-dimensional Vlasov equation. J. Phys. A: Math. Theor. 44(40), 405502 (2011). https://doi.org/10.1088/1751-8113/44/40/405502

    Article  MathSciNet  MATH  Google Scholar 

  5. Mitchell, M.S., Miecnikowski, M.T., Beylkin, G., Parker, S.E.: Efficient Fourier basis particle simulation. J. Comput. Phys. 396, 837–847 (2019). https://doi.org/10.1016/j.jcp.2019.07.023

    Article  MathSciNet  MATH  Google Scholar 

  6. Casas, F., Crouseilles, N., Faou, E., Mehrenberger, M.: High-order Hamiltonian splitting for the Vlasov-Poisson equations. Numer. Math. 135(3), 769–801 (2017). https://doi.org/10.1007/s00211-016-0816-z

    Article  MathSciNet  MATH  Google Scholar 

  7. Degond, P., Mas-Gallic, S.: The weighted particle method for convection-diffusion equations part 1: the case of an isotropie viscosity. Math. Comput. 53, 485 (1989)

    MATH  Google Scholar 

  8. Glassey, R.T.: The cauchy problem in kinetic theory. Soc. Ind. Appl. Math. (1996). https://doi.org/10.1137/1.9781611971477

    Article  MATH  Google Scholar 

  9. Hewett, D.W.: Fragmentation, merging, and internal dynamics for PIC simulation with finite size particles. J. Comput. Phys. 189(2), 390–426 (2003). https://doi.org/10.1016/S0021-9991(03)00225-0

    Article  MathSciNet  MATH  Google Scholar 

  10. Campos Pinto, M., Sonnendrücker, E., Friedman, A., Grote, D.P., Lund, S.M.: Noiseless Vlasov-Poisson simulations with linearly transformed particles. J. Comput. Phys. 275, 236–256 (2014). https://doi.org/10.1016/j.jcp.2014.06.032

    Article  MathSciNet  MATH  Google Scholar 

  11. Campos Pinto, M.: Towards smooth particle methods without smoothing. J. Sci. Comput. 65(1), 54–82 (2015). https://doi.org/10.1007/s10915-014-9953-7

    Article  MathSciNet  MATH  Google Scholar 

  12. Fu, C., Guo, Q., Gast, T., Jiang, C., Teran, J.: A polynomial particle-in-cell method. ACM Trans. Graph. 36(6), 1–12 (2017). https://doi.org/10.1145/3130800.3130878

    Article  Google Scholar 

  13. Hockney, R.W., Eastwood, J.W.: Computer Simulation Using Particles. IOP Publishing Ltd (1988). https://doi.org/10.1887/0852743920

    Book  MATH  Google Scholar 

  14. Birdsall, C.K., Langdon, A.B.: Plasma Physics Via Computer Simulation. CRC Press (1991). https://doi.org/10.1201/9781315275048

    Book  Google Scholar 

  15. Birdsall, C.K., Fuss, D.: Clouds-in-clouds, clouds-in-cells physics for many-body plasma simulation. J. Comput. Phys. 3, 494 (1968)

    Article  MATH  Google Scholar 

  16. Verboncoeur, J.P.: Particle simulation of plasmas: review and advances. Plasma Phys. Controlled Fusion 47(5A), 231–260 (2005). https://doi.org/10.1088/0741-3335/47/5A/017

    Article  Google Scholar 

  17. Okuda, H.: Nonphysical noises and instabilities in plasma simulation due to a spatial grid. J. Comput. Phys. 10(3), 475–486 (1972). https://doi.org/10.1016/0021-9991(72)90048-4

    Article  Google Scholar 

  18. Langdon, A.B.: Effects of the spatial grid in simulation plasmas. J. Comput. Phys. 6(2), 247–267 (1970). https://doi.org/10.1016/0021-9991(70)90024-0

    Article  Google Scholar 

  19. Brackbill, J.U., Kothe, D.B., Ruppel, H.M.: Flip: a low-dissipation, particle-in-cell method for fluid flow. Comput. Phys. Commun. 48(1), 25–38 (1988). https://doi.org/10.1016/0010-4655(88)90020-3

    Article  Google Scholar 

  20. Brackbill, J.U.: On energy and momentum conservation in particle-in-cell plasma simulation. J. Comput. Phys. 317, 405–427 (2016). https://doi.org/10.1016/j.jcp.2016.04.050

    Article  MathSciNet  MATH  Google Scholar 

  21. Wollman, S., Ozizmir, E.: Numerical approximation of the one-dimensional Vlasov-Poisson system with periodic boundary conditions. SIAM J. Numer. Anal. 33(4), 1377–1409 (1996). https://doi.org/10.1137/S0036142993233585

    Article  MathSciNet  MATH  Google Scholar 

  22. Besse, N.: Convergence of a Semi-Lagrangian scheme for the one-dimensional Vlasov-Poisson system. SIAM J. Numer. Anal. 42(1), 350–382 (2004). https://doi.org/10.1137/S0036142902410775

    Article  MathSciNet  MATH  Google Scholar 

  23. Respaud, T., Sonnendrücker, E.: Analysis of a new class of forward semi-Lagrangian schemes for the 1D Vlasov Poisson equations. Numer. Math. 118(2), 329–366 (2011). https://doi.org/10.1007/s00211-010-0351-2

    Article  MathSciNet  MATH  Google Scholar 

  24. Wollman, S.: On the approximation of the Vlasov-Poisson system by particle methods. SIAM J. Numer. Anal. 37(4), 1369–1398 (2000). https://doi.org/10.1137/S0036142999298528

    Article  MathSciNet  MATH  Google Scholar 

  25. Anderson, C., Greengard, C.: On vortex methods. SIAM J. Numer. Anal. 22(3), 413–440 (1985). https://doi.org/10.1137/0722025

    Article  MathSciNet  MATH  Google Scholar 

  26. Perlman, M.: On the accuracy of vortex methods. J. Comput. Phys. 59(2), 200–223 (1985). https://doi.org/10.1016/0021-9991(85)90142-1

    Article  MathSciNet  MATH  Google Scholar 

  27. Arsénio, D., Dormy, E., Lacave, C.: The vortex method for two-dimensional ideal flows in exterior domains. SIAM J. Math. Anal. 52(4), 3881–3961 (2020). https://doi.org/10.1137/19M1291947

    Article  MathSciNet  MATH  Google Scholar 

  28. Hald, O.H.: Convergence of vortex methods for Euler’s equations. II. SIAM J. Numer. Anal. 16(5), 726–755 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  29. Beale, J.T., Majda, A.: Vortex methods: I: convergence in three dimensions. Math. Comput. 39(159), 1 (1982)

  30. Beale, J.T.: A convergent 3-D vortex method with grid-free stretching. Math. Comput. 46(174), 401 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  31. Cottet, G.H.: Convergence of a Vortex in cell method for the two-dimensional Euler equations. Math. Comput. 49, 407 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  32. Goodman, J., Hou, T.Y., Lowengrub, J.: Convergence of the point vortex method for the 2-D euler equations. Commun. Pure Appl. Math. 43(3), 415–430 (1990). https://doi.org/10.1002/cpa.3160430305

    Article  MathSciNet  MATH  Google Scholar 

  33. Cottet, G.-H., Goodman, J., Hou, T.Y.: Convergence of the grid-free point vortex method for the three-dimensional Euler equations. SIAM J. Numer. Anal. 28(2), 291–307 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  34. Hejlesen, M.M., Rasmussen, J.T., Chatelain, P., Walther, J.H.: A high order solver for the unbounded Poisson equation. J. Comput. Phys. 252, 458–467 (2013). https://doi.org/10.1016/j.jcp.2013.05.050

    Article  MathSciNet  MATH  Google Scholar 

  35. Qin, M.: Symplectic schemes for nonautonomous Hamiltonian system. Acta Math. Appl. Sin. 12(3), 284–288 (1996). https://doi.org/10.1007/BF02011893

    Article  MathSciNet  MATH  Google Scholar 

  36. Hairer, E., Wanner, G.: A theory for Nyström methods. Numer. Math. 25(4), 383–400 (1975). https://doi.org/10.1007/BF01396335

    Article  MathSciNet  MATH  Google Scholar 

  37. Feng, K., Qin, M.: Symplectic Geometric Algorithms for Hamiltonian Systems. Springer, Berlin (2010). https://doi.org/10.1007/978-3-642-01777-3

    Book  MATH  Google Scholar 

  38. Yoshida, H.: Construction of higher order symplectic integrators. Phys. Lett. A 150(5–7), 262–268 (1990). https://doi.org/10.1016/0375-9601(90)90092-3

    Article  MathSciNet  Google Scholar 

  39. Barnett, A.H.: Aliasing error of the Exp\$( beta sqrt 1-Z \(\hat{2}\) ) \$ Kernel in the Nonuniform Fast Fourier Transform. ar**v (2020)

  40. Buyl, P.: Numerical resolution of the Vlasov equation for the Hamiltonian Mean-Field model. Commun. Nonlinear Sci. Numer. Simul. 15(8), 2133–2139 (2010). https://doi.org/10.1016/j.cnsns.2009.08.020

    Article  MathSciNet  MATH  Google Scholar 

  41. Antoni, M., Ruffo, S.: Clustering and relaxation in Hamiltonian long-range dynamics. Phys. Rev. E 52(3), 2361–2374 (1995). https://doi.org/10.1103/PhysRevE.52.2361

    Article  Google Scholar 

  42. Pareschi, L., Rey, T.: Moment preserving Fourier-Galerkin spectral methods and application to the Boltzmann equation. SIAM J. Numer. Anal. 60, 3216 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  43. Barnett, A.H., Magland, J.F., Klinteberg, L.: A Parallel Non-Uniform Fast Fourier Transform Library Based on an “Exponential of Semicircle” Kernel. ar**v (2019)

  44. Atkinson, K.E.: An Introduction to Numerical Analysis, ed Wiley, New York (1989)

    MATH  Google Scholar 

  45. Sonnendrucker, E.: Numerical methods for the Vlasov-Maxwell equations. Springer, Berlin (2016)

    Google Scholar 

  46. Einkemmer, L., Ostermann, A.: A strategy to suppress recurrence in grid-based Vlasov solvers. Eur. Phys. J. D 68(7), 197 (2014). https://doi.org/10.1140/epjd/e2014-50058-x. arxiv:1401.4809

    Article  Google Scholar 

  47. Abbasi, H., Jenab, M.H., Pajouh, H.H.: Preventing the recurrence effect in the Vlasov simulation by randomizing phase-point velocities in phase space. Phys. Rev. E 84(3), 036702 (2011). https://doi.org/10.1103/PhysRevE.84.036702

    Article  Google Scholar 

  48. Mehrenberger, M.: Recurrence phenomenon for Vlasov-Poisson simulations on regular finite element mesh. Commun. Comput. Phys. 28(3), 877–901 (2020). https://doi.org/10.4208/cicp.OA-2019-0022

    Article  MathSciNet  MATH  Google Scholar 

  49. Pinto, M.C., Ameres, J., Kormann, K., Sonnendrücker, E.: On Geometric Fourier particle in cell methods. ar**v (2021)

  50. Kraus, M., Kormann, K., Morrison, P.J., Sonnendrücker, E.: GEMPIC: geometric electromagnetic particle-in-cell methods. J. Plasma Phys. 83(4), 905830401 (2017). https://doi.org/10.1017/S002237781700040X

    Article  Google Scholar 

  51. Crouseilles, N., Respaud, T., Sonnendrücker, E.: A forward semi-Lagrangian method for the numerical solution of the Vlasov equation. Comput. Phys. Commun. 180(10), 1730–1745 (2009). https://doi.org/10.1016/j.cpc.2009.04.024

    Article  MathSciNet  MATH  Google Scholar 

  52. Nguyen-van-yen, R., Sonnendrücker, É., Schneider, K., Farge, M.: Particle-in-wavelets scheme for the 1D Vlasov-Poisson equations. ESAIM Proc. 32, 134–148 (2011). https://doi.org/10.1051/proc/2011017

    Article  MathSciNet  MATH  Google Scholar 

  53. Abramowitz, M., Stegun, I.A.: Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables vol. 55. US Government printing office (1964)

  54. Berend, D., Tassa, T.: Improved bounds on bell numbers and on moments of sums of random variables. Probab. Math. Stat. 30(2), 185–205 (2010)

    MathSciNet  MATH  Google Scholar 

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Acknowledgements

The author would like to thank his PhD advisors, Nicolas Crouseilles and Erwan Faou, for fruitful discussions and their valuable insights. The author would also like to thank the Centre Henri Lebesgue, program ANR-11- LABX-0020-0. This work has been carried out within the framework of the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No 101052200—EUROfusion). Views and opinions expressed are however those of the author only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.

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Le Henaff, Y. Grid-free weighted particle method applied to the Vlasov–Poisson equation. Numer. Math. 155, 289–344 (2023). https://doi.org/10.1007/s00211-023-01378-4

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