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A Unified Theory of Non-overlapping Robin–Schwarz Methods: Continuous and Discrete, Including Cross Points

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Abstract

Non-overlapping Schwarz methods with generalized Robin transmission conditions were originally introduced by B. Després for time-harmonic wave propagation problems and have largely developed over the past thirty years. The aim of the paper is to provide both a review of the available formulations and methods as well as a consistent theory applicable to more general cases than studied until to date. An abstract variational framework is provided reformulating the original problem by the well-known form involving a scattering operator and an interface exchange operator, and the equivalence between the formulations is discussed thoroughly. The framework applies to a series of wave propagation problems throughout the de Rham complex, such as the scalar Helmholtz equation, Maxwell’s equations, a dual formulation of the Helmholtz equation in H(div), as well as any conforming finite element discretization thereof, and it applies also to coercive problems. Three convergence results are shown. The first one (using compactness) and the second one (based on absorption) generalize Després’ early findings and apply as well to the FETI-2LM formulation (a discrete method introduced by de La Bourdonnaye, Farhat, Macedo, Magoulés, and Roux). The third result, oriented on the work by Collino, Ghanemi, and Joly, establishes a convergence rate and covers cases with cross points, while not requiring any regularity of the solution. The key ingredient is a global interface exchange operator, proposed originally by X. Claeys and further developed by Claeys and Parolin, here worked out in full generality. The third type of convergence theory is applicable at the discrete level as well, where the exchange operator is allowed to be even local. The resulting scheme can be viewed as a generalization of the 2-Lagrange-multiplier method introduced by S. Loisel, and connections are drawn to another technique proposed by Gander and Santugini.

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Notes

  1. In a large part of literature, \(U(x, t) = u(x) e^{-\text {i}\omega t}\) is used (see e.g., [17, 77], opposed to [19, 48]), which would lead to a replacement of \(\text {i}\) by \(-\text {i}\) throughout this paper.

  2. In [19] this operator is called transmission operator and denoted by \(T_{ij}\).

  3. In the literature, the dual of a complex Banach space is sometimes defined as the space of bounded anti-linear forms and, correspondingly, sesquilinear forms are used. This article features linear and bilinear forms because they better correspond to the matrix-vector setting.

  4. Here real-valued means that either (a) \({\widehat{U}}\) and \(U_i\) are real Hilbert spaces, or (b) \({\widehat{U}}\) and \(U_i\) are complexified and \(R_i\) has the form \(R_i (u_\text {re}+ \text {i}u_\text {im}) = R_{i,\text {re}} u_\text {re}+ \text {i}R_{i,\text {re}} u_\text {im}\) for an operator \(R_{i,\text {re}}\) acting on the real Hilbert spaces.

  5. In the literature, this operator is often not made visible, sometimes it is denoted by B [17].

  6. In the literature, one often reads of faces, in the two-dimensional case of edges.

  7. The projection operator defined in (3.5) is denoted by K in [68].

  8. called polar set in [51, p. 58].

  9. Also called transmission operator, often denoted by T [17, 19], or B [49, 68].

  10. For the Helmholtz equation and for the choice \(\alpha = \text {i}\) and \(M = \kappa I\), we have \(\lambda _i = \text {i}\kappa u_i + \partial u_i/\partial \nu _i\) and \(S_i \lambda _i = \text {i}\kappa u_i - \partial u_i/\partial \nu _i\), cf. (2.5).

  11. \(M_i :\varLambda _i \rightarrow \varLambda _i^*\) is symmetric iff \(M_i^{\textsf{T}}= M_i\).

  12. \(A_i :U_i \rightarrow U_i^*\) is non-negative iff \(\langle A_i v, {\overline{v}} \rangle \ge 0\) for all \(v \in U_i\).

  13. Note that Ass. A4 and Ass. A7 together imply that \((M + {\mathcal {X}}^{\textsf{T}}M {\mathcal {X}}) = 2 M\) has a bounded inverse.

  14. Note that this is implied by Ass. A4 and Ass. A6. Alternatively, Ass. A6 and Ass. A7 together imply that \((M + {\mathcal {X}}^{\textsf{T}}M {\mathcal {X}})\) is bounded positively from below.

  15. Recall from Sect. 5.4 that the original method as proposed in [49, Sect. 4] uses two distinct exchange operators.

  16. In the typical applications, the existence of such an operator is shown using Poincaré-, Friedrichs-, or Korn-type inequalities.

References

  1. Alonso Rodríguez, A.M., Gerardo-Giorda, L.: New nonoverlapping domain decomposition methods for the harmonic Maxwell system. SIAM J. Sci. Comput. 28(1), 102–122 (2006)

    MathSciNet  MATH  Google Scholar 

  2. Beirão da Veiga, L., Pavarino, L.F., Scacchi, S., Widlund, O.B., Zampini, S.: Isogeometric BDDC preconditioners with deluxe scaling. SIAM J. Sci. Comput. 36(3), 1118–1139 (2014)

    MathSciNet  MATH  Google Scholar 

  3. Bendali, A., Boubendir, Y.: Non-overlapping domain decomposition method for a nodal finite element method. Numer. Math. 103, 515–537 (2005)

    MathSciNet  MATH  Google Scholar 

  4. Boubendir, Y., Antoine, X., Geuzaine, C.: A quasi-optimal non-overlapping domain decomposition algorithm for the Helmholtz equation. J. Comput. Phys. 231(2), 262–280 (2012)

    MathSciNet  MATH  Google Scholar 

  5. Brezzi, F., Marini, L.D.: A three-field domain decomposition method. In: Quateroni, A., Périaux, J., Kuznetsov, Y.A., Widlund, O. (eds) Domain Decomposition in Science and Engineering—The Sixth International Conference on Domain Decomposition, June 15–19, 1992, Como, Italy, Contemporary Mathematics, vol. 157, pp. 27–34. AMS, Providence (1993). http://www.ddm.org/DD06/Brezzi_Marini.pdf

  6. Buffa, A., Ciarlet, P., Jr.: On traces for functional spaces related to Maxwell’s equations Part I: an integration by parts formula in Lipschitz polyhedra. Math. Methods Appl. Sci. 24, 9–30 (2001)

    MathSciNet  MATH  Google Scholar 

  7. Cessenant, O., Després, B.: Application of an ultra weak variational formulation of elliptic PDEs to the two-dimensional Helmholtz problem. SIAM J. Numer. Anal. 35(1), 255–299 (1998)

    MathSciNet  MATH  Google Scholar 

  8. Chandler-Wilde, S.N., Hewett, D.P., Moiola, A.: Sobolev spaces on non-Lipschitz subsets of \(\mathbb{R} ^n\) with application to boundary integral equations on fractal screens. Integr. Equ. Oper. Theory 87(2), 179–224 (2017)

    MATH  Google Scholar 

  9. Claeys, X.: Quasi-local multi-trace boundary integral formulations. Numer. Methods Partial Differ. Equ. 31(6), 2043–2062 (2015)

    MATH  Google Scholar 

  10. Claeys, X.: Non-local variant of the optimised Schwarz method for arbitrary non-overlapping subdomain partitions. ESAIM Math. Model. Numer. Anal. 55(2), 429–448 (2021)

    MathSciNet  MATH  Google Scholar 

  11. Claeys, X.: Non-self adjoint impedance in generalized optimized Schwarz methods. Technical Report arXiv:2108.03652v1 [math.AP] (2021). To appear in IMA. J. Numer. Anal. https://doi.org/10.1093/imanum/drac062

  12. Claeys, X., Dolean, V., Gander, M.J.: An introduction to multitrace formulations and associated domain decomposition solvers. Appl. Numer. Math. 135, 69–86 (2019)

    MathSciNet  MATH  Google Scholar 

  13. Claeys, X., Hiptmair, R.: Electromagnetic scattering at composite objects: a novel multi-trace boundary integral formulation. ESAIM Math. Model. Numer. Anal. 46 (2012)

  14. Claeys, X., Hiptmair, R.: Boundary integral formulation of the first kind for acoustic scattering by composite structures. Commun. Pure Appl. Math. 66(8), 1163–1201 (2013)

    MATH  Google Scholar 

  15. Claeys, X., Hiptmair, R., Jerez-Hanckes, C.: Multi-trace boundary integral equations. In: Graham, I.G., Langer, U., Melenk, J.M., Sini, M. (eds.) Direct and Inverse Problems in Wave Propagation and Applications, Radon Series on Computational and Applied Mathematics, vol. 14, pp. 51–100. De Gruyter, Berlin (2013)

    Google Scholar 

  16. Claeys, X., Hiptmair, R., Jerez-Hanckes, C., Pintarelli, S.: Novel multi-trace boundary integral equations for transmission boundary value problems. In: Fokas, A.S., Pelloni, B. (eds) Unified Transform for Boundary Value Problems: Applications and Advances. SIAM (2015)

  17. Claeys, X., Parolin, E.: Robust treatment of cross points in optimized Schwarz methods. Numer. Math. 151(2), 405–442 (2022). ArXiv: 2003.06657 [math.NA], March 2020

  18. Collino, F., Delbue, G., Joly, P., Piacentini, A.: A new interface condition in the non-overlapping domain decomposition method for the Maxwell equations. Comput. Methods Appl. Math. Eng. 148(1–2), 195–207 (1997)

    MathSciNet  MATH  Google Scholar 

  19. Collino, F., Ghanemi, S., Joly, P.: Domain decomposition method for harmonic wave propagation: a general presentation. Comput. Methods Appl. Mech. Eng. 184(2–4), 171–211 (2000)

    MathSciNet  MATH  Google Scholar 

  20. Collino, F., Joly, P., Lecouvez, M.: Exponentially convergent non overlapping domain decomposition methods for the Helmholtz equation. ESAIM Math. Model. Numer. Anal. 54(3), 775–810 (2020)

    MathSciNet  MATH  Google Scholar 

  21. Collino, F., Joly, P., Lecouvez, M., Stupfel, B.: Quasi-local transmission conditions for non-overlapping domain decomposition methods for the Helmholtz equation. C R Phys. 15(5), 403–414 (2014)

    Google Scholar 

  22. de La Bourdonnaye, A., Farhat, C., Macedo, A., Magoulès, F., Roux, F.: A non-overlapping domain decomposition method for the exterior Helmholtz problem. In: Mandel, J. Farhat, C., Cai, X .(eds.) Domain Decomposition Methods 10, Contemporary Mathematics, vol. 218, pp. 42–66. AMS, Providence, RI (1998). (DD10 at Boulder, Colorado, August 10–14, 1997) https://doi.org/10.1090/conm/218/03001, www.ddm.org/DD10/DD10_Bourdonnaye_invited.pdf

  23. Després, B.: Décomposition de domaine et problème de Helmholtz. C. R. Acad. Sci. Paris 1(6), 313–316 (1990)

    MATH  Google Scholar 

  24. Després, B.: Domain decomposition method and the Helmholtz problem. In: Cohen, G., Halpern, L., Joly, P. (eds.) Proceedings of the First International Conference on Mathematical and Numerical Aspects of Wave Propagation, Strasbourg, pp. 44–52. SIAM, Philadelphia (1991)

  25. Després, B.: Méthodes de décomposition de domaines pour les problèmes de propagation d‘ondes en régime harmonique. Doctoral thesis, Université Paris IX Dauphine (1991)

  26. Després, B., Joly, P., Roberts, J.E.: A domain decomposition method for the harmonic Maxwell equations. In: Iterative Methods in Linear Algebra, pp. 475–484. North-Holland, Amsterdam (1992)

  27. Després, B., Nicolopoulos, A., Thierry, B.: Corners and stable optimized domain decomposition methods for the Helmholtz problem. Numer. Math. 149, 779–818 (2021)

    MathSciNet  MATH  Google Scholar 

  28. Després, B., Nicolopoulos, A., Thierry, B.: Optimized transmission conditions in domain decomposition methods with cross-points for Helmholtz equation. SIAM J. Numer. Anal. 60(5), 2482–2507 (2022)

    MathSciNet  MATH  Google Scholar 

  29. Dohrmann, C.R.: A preconditioner for substructuring based on constrained energy minimization. SIAM J. Sci. Comput. 25(1), 246–258 (2003)

    MathSciNet  MATH  Google Scholar 

  30. Dohrmann, C.R., Widlund, O.B.: A BDDC algorithm with deluxe scaling for three-dimensional H(curl) problems. Commun. Pure Appl. Math. 69(4), 745–770 (2016)

    MathSciNet  MATH  Google Scholar 

  31. Dolean, V., Gander, M.J., Gerardo-Giorda, L.: Optimized Schwarz methods for Maxwell’s equations. SIAM J. Sci. Comput. 31(3), 2193–2213 (2009)

    MathSciNet  MATH  Google Scholar 

  32. Dolean, V., Gander, M.J., Lanteri, S., Lee, J., Peng, Z.: Effective transmission conditions for domain decomposition methods applied to the time-harmonic curl-curl Maxwell’s equations. J. Comput. Phys. 280, 232–247 (2015)

    MathSciNet  MATH  Google Scholar 

  33. Dolean, V., Gander, M.J., Veneros, E., Zhang, H.: Optimized Schwarz methods for heterogeneous Helmholtz and Maxwell’s equations. In: Lee, C., Cai, X., Keyes, D.E., Kim, H.H., Klawonn, A., Park, E., Widlund, O.B. (eds.) Domain Decomposition in Science and Engineering XXIII, LNCSE, vol. 116, pp. 145–152. Springer (2017)

  34. Dolean, V., Jolivet, P., Nataf, F.: An Introduction to Domain Decomposition Methods: Algorithms, Theory, and Parallel Implementation. SIAM, Philadelphia (2015)

    MATH  Google Scholar 

  35. Dostál, Z., Horák, D., Kučera, R.: Total FETI—an easier implementable variant of the FETI method for numerical solution of elliptic PDE. Commun. Numer. Methods Eng. 22(12), 1155–1162 (2006)

    MathSciNet  MATH  Google Scholar 

  36. El Bouajaji, M., Thierry, B., Antoine, X., Geuzaine, C.: A quasi-optimal domain decomposition algorithm for the time-harmonic Maxwell’s equations. J. Comput. Phys. 294, 38 (2015)

    MathSciNet  MATH  Google Scholar 

  37. Elman, H.C.: Iterative methods for large, sparse, nonsymmetric systems of linear equations. Ph.D thesis, Yale University, Hew Haven (1982)

  38. Farhat, C., Avery, P., Tezaur, R., Li, J.: FETI-DPH: a dual-primal domain decomposition method for acoustic scattering. J. Comput. Acoust. 13(3), 499–524 (2005)

    MathSciNet  MATH  Google Scholar 

  39. Farhat, C., Macedo, A., Lesoinne, M.: A two-level domain decomposition method for the iterative solution of high frequency exterior Helmholtz problems. Numer. Math. 83(2), 283–308 (2000)

    MathSciNet  MATH  Google Scholar 

  40. Farhat, C., Macedo, A., Lesoinne, M., Roux, F., Magoulès, F., de La Bourdonnaie, A.: Two-level domain decomposition methods with Lagrange multipliers for the fast iterative solution of acoustic scattering problems. Comput. Methods Appl. Mech. Eng. 184, 213–239 (2000)

    MATH  Google Scholar 

  41. Farhat, C., Macedo, A., Magoulès, F., Roux, F.: A Lagrange multiplier based domain decomposition method for the exterior Helmholtz problem. In: Proceedings Fourth U. S. National Congress on Computational Mechanics (1997). USNCCM Conference at San Francisco, California, August 6–8 (1997)

  42. Farhat, C., Macedo, A., Tezaur, R.: FETI-H: a scalable domain decomposition method for high frequency exterior Helmholtz problems. In: Lai, C., Bjorstad, P., Cross, M., Widlund, O.B. (eds.) Eleventh International Conference on Domain Decomposition Methods. (DD11 at Greenwich, Great Britain, July 20–24, 1998) http://www.ddm.org/DD11/Farhat.pdf (1999)

  43. Farhat, C., Roux, F.: An unconventional domain decomposition method for an efficient parallel solution of large-scale finite element systems. In: Proceedings of the Fourth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado, April 1–5 (1990)

  44. Farhat, C., Roux, F.: A method of finite element tearing and interconnecting and its parallel solution algorithm. Int. J. Numer. Methods Eng. 32(6), 1205–1227 (1991)

    MathSciNet  MATH  Google Scholar 

  45. Gander, M.J.: Optimized Schwarz methods. SIAM J. Numer. Anal. 44(2), 699–731 (2006)

    MathSciNet  MATH  Google Scholar 

  46. Gander, M.J., Halpern, L., Magoulès, F.: An optimized Schwarz method with two-sided Robin transmission conditions for the Helmholtz equation. Int. J. Numer. Methods Fluids 55(2), 163–175 (2006)

    MathSciNet  MATH  Google Scholar 

  47. Gander, M.J., Kwok, F.: Best Robin parameters for optimized Schwarz methods at cross points. SIAM J. Sci. Comput. 34(4), A1849–A1879 (2012)

    MathSciNet  MATH  Google Scholar 

  48. Gander, M.J., Magoulès, F., Nataf, F.: Optimized Schwarz methods without overlap for the Helmholtz equation. SIAM J. Sci. Comput. 24(1), 38–60 (2002)

    MathSciNet  MATH  Google Scholar 

  49. Gander, M.J., Santugini-Repiquet, K.: Cross-points in domain decomposition methods with a finite element discretization. Electron. Trans. Numer. Anal. 45, 219–240 (2016)

    MathSciNet  MATH  Google Scholar 

  50. Gander, M.J., Zhang, H.: A class of iterative solvers for the Helmholtz equation: factorizations, sweeping preconditioners, source transfer, single layer potentials, polarized traces, and optimized Schwarz methods. SIAM Rev. 61(1), 3–76 (2019)

    MathSciNet  MATH  Google Scholar 

  51. Girault, V., Raviart, P.A.: Finite Element Methods for the Navier–Stokes Equations. Springer, Berlin, Heidelberg (1986)

    MATH  Google Scholar 

  52. Gong, S., Gander, M.J., Graham, I.G., Lafontaine, D., Spence, E.A.: Convergence of parallel overlapping domain decomposition methods for the Helmholtz equation. Numer. Math. 152, 259–306 (2022)

    MathSciNet  MATH  Google Scholar 

  53. Gosselet, P., Blanchard, M., Allix, O., Guguin, G.: Non-invasive global-local coupling as a Schwarz domain decomposition method: acceleration and generalization. Adv. Model. Simul. Eng. Sci. 5(4) (2018). (electronic)

  54. Grisvard, P.: Elliptic Problems in Nonsmooth Domains. Pitman, Boston (1985)

    MATH  Google Scholar 

  55. Hiptmair, R.: Operator preconditioning. Comput. Math. Appl. 52, 699–706 (2006)

    MathSciNet  MATH  Google Scholar 

  56. Hiptmair, R.: Maxwell’s equations: Continuous and discrete. In: Computational Electromagnetism. Lecture Notes in Mathematics, vol. 2148, pp. 1–58. Springer, Cham (2015)

  57. Hiptmair, R., Jerez-Hanckes, C.: Multiple traces boundary integral formulation for Helmholtz transmission problems. Adv. Appl. Math. 37, 39–91 (2012)

    MathSciNet  MATH  Google Scholar 

  58. Hiptmair, R., Jerez-Hanckes, C., Lee, J., Peng, Z.: Domain decomposition for boundary integral equations via local multi-trace formulations. In: Erhel, J., Gander, M.J., Halpern, L., Pichot, G., Sassi, T., Widlund, O. (eds.) Domain Decomposition in Science and Engineering XXI, Lecture Notes in Computational Science and Engineering, Vol. 98, pp. 43–57. Springer (2014)

  59. Hiptmair, R., Pechstein, C.: A review of regular decompositions of vector fields: continuous, discrete, and structure-preserving. In: Sherwin, S.J., Moxey, D., Periró, J., Vincent, P.E., Schwab, C. (eds.) Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018, Lecture Notes in Computational Science and Engineering, Vol. 134, pp. 45–60. Springer, Cham (2020). See also SAM-Report 2019-18, Seminar für Angewandte Mathematik, ETH Zürich, Switzerland (2019)

  60. Huber, M.: Hybrid discontinuous Galerkin methods for the wave equation. Doctoral thesis, University of Vienna, Austria (2013). http://www.asc.tuwien.ac.at/~mhuber/thesis_huber.pdf

  61. Huber, M., Pechstein, A., Schöberl, J.: Hybrid domain decomposition solvers for scalar and vectorial wave equation. In: Bank, R.E., Holst, M., Widlund, O.B., Xu, J. (eds.) Domain Decomposition Methods in Science and Engineering XX, Lecture Notes in Computational Science and Engineering, vol. 91, pp. 291–299. Springer. http://www.ddm.org/DD20/proceedings/articles/Huber.pdf (2011)

  62. Japhet, C.: Optimized Krylov–Ventcell method. Application to convection-diffusion problems. In: Bjørstad, P.E., Espedal, M.S., Keyes, D.E. (eds.) Proceedings of the 9th International Conference on Domain Decomposition Methods, pp. 382-389. http://www.ddm.org/DD9/Japhet.pdf (1998)

  63. Lee, J., Peng, Z.: Computational Electromagnetics: Domain Decomposition Methods and Practical Applications (in preparation)

  64. Lee, S., Vouvakis, M.N., Lee, J.F.: A non-overlapping domain decomposition method with non-matching grids for modeling large finite antenna arrays. J. Comput. Phys. 203(1), 1–21 (2005)

    MathSciNet  MATH  Google Scholar 

  65. Li, Y., Yin, J.: A new dual-primal domain decomposition approach for finite element simulation of 3-D large-scale electromagnetic problems. IEEE Trans. Antennas Prop. 55, 2803–2810 (2007)

    MathSciNet  MATH  Google Scholar 

  66. Liesen, J., Tichý, P.: The field of values bounds on ideal GMRES. Technical Report arXiv:1211.5969v3 [math.AP] (2020)

  67. Lions, P.L.: On the Schwarz alternating method. III: a variant for nonoverlapping subdomains. In: Chan, T.F., Glowinski, R., Périaux, J., Widlund, O. (eds.) Third International Symposium on Domain Decomposition Methods for Partial Differential Equations. SIAM, Philadelphia. Conference held in Houston, Texas, March 20-22, 1989, www.ddm.org/DD03/On_the_Schwarz_Alternating_Method_III_A_Variant_for_Nonoverlapping_Subdomains_(Lions).pdf (1990)

  68. Loisel, S.: Condition number estimates for the non-overlapping optimized Schwarz method and the 2-Lagrange multiplier method for general domains and cross points. SIAM J. Numer. Anal. 51(6), 3062–3083 (2013)

    MathSciNet  MATH  Google Scholar 

  69. Loisel, S., Nguyen, H., Scheichl, R.: Optimized Schwarz and 2-Lagrange multiplier methods for multiscale elliptic PDEs. SIAM J. Sci. Comput. 37(6), A2896–A2923 (2015)

    MathSciNet  MATH  Google Scholar 

  70. Mandel, J.: Balancing domain decomposition. Commun. Numer. Methods Eng. 9(3), 233–241 (1993)

    MathSciNet  MATH  Google Scholar 

  71. Mandel, J., Brezina, M.: Balancing domain decomposition for problems with large jumps in coefficients. Math. Comput. 65, 1387–1401 (1996)

    MathSciNet  MATH  Google Scholar 

  72. Mandel, J., Dohrmann, C.R., Tezaur, R.: An algebraic theory for primal and dual substructuring methods by constraints. Appl. Numer. Math. 54(2), 167–193 (2005)

    MathSciNet  MATH  Google Scholar 

  73. Mathew, T.P.A.: Domain Decomposition Methods for the Numerical Solution of Partial Differential Equations. Lecture Notes in Computational Science and Engineering, vol. 61. Springer, Berlin (2008)

  74. McLean, W.: Strongly Elliptic Systems and Boundary Integral Equations. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  75. Modave, A., Geuzaine, C., Antoine, X.: Corner treatments for high-order local absorbing boundary conditions in high-frequency acoustic scattering. J. Comput. Phys. 401, 109029 (2020)

    MathSciNet  MATH  Google Scholar 

  76. Modave, A., Royer, A., Geuzaine, C., Antoine, X.: A non-overlapping domain decomposition method with high-order transmission conditions and cross-point treatment for Helmholtz problems. Comput. Methods Appl. Mech. Eng. 368, 113162 (2020)

    MathSciNet  MATH  Google Scholar 

  77. Monk, P.: Finite Element Methods for Maxwell’s Equations. Oxford University Press, New York (2003)

    MATH  Google Scholar 

  78. Monk, P., Sinwel, A., Schöberl, J.: Hybridizing Raviart–Thomas elements for the Helmholtz equation. Electromagnetics 30(1), 149–176 (2010)

    Google Scholar 

  79. Nataf, F., Rogier, F., de Sturler, E.: Optimal interface conditions for domain decomposition methods. Technical Report. 301, CMAP, Ecole Polytechnique (1994)

  80. Of, G.: BETI-Gebietszerlegungsmethoden mit schnellen Randelementverfahren und Anwendungen. Doctoral thesis, Universität Stuttgart, Germany. http://dx.doi.org/10.18419/opus-4766 (2006)

  81. Of, G., Steinbach, O.: The all-floating boundary element tearing and interconnecting method. J. Numer. Math. 17(4), 277–298 (2009)

    MathSciNet  MATH  Google Scholar 

  82. Paraschos, G.N.: Robust and scalable domain decomposition methods for electromagnetic computations. Ph.D. thesis, University of Massachusetts Amherst. Doctoral dissertation, http://scholarworks.umass.edu/open_access_dissertations/619 (2012)

  83. Parolin, E.: Méthodes de décomposition de domaine sans recouvrement avec opérateurs de transmission non-locaux pour des problèmes de propagation d’ondes harmoniques. Doctoral thesis, Institut Polytechnique de Paris, France (2020). In English

  84. Pechstein, C.: Finite and Boundary Element Tearing and Interconnecting Methods for Multiscale Problems. Lecture Notes in Computational Science and Engineering, vol. 90. Springer, Berlin (2013)

  85. Pechstein, C., Dohrmann, C.R.: A unified framework for adaptive BDDC. Electron. Trans. Numer. Anal. 46, 273–336 (2017)

    MathSciNet  MATH  Google Scholar 

  86. Peng, Z., Lee, J.F.: Non-conformal domain decomposition method with second order transmission conditions for time-harmonic electromagnetics. J. Comput. Phys. 229, 5615–5629 (2010)

    MATH  Google Scholar 

  87. Piacentini, A., Rosa, N.: An improved domain decomposition method for the 3d Helmholtz equation. Comput. Methods Appl. Mech. Eng. 162(1), 113–124 (1998)

    MATH  Google Scholar 

  88. Quarteroni, A., Valli, A.: Domain Decomposition Methods for Partial Differential Equations. Calderon Press, Oxford (1999)

    MATH  Google Scholar 

  89. Rawat, V., Lee, J.: Non-overlapping domain decomposition method with second order transmission condition for the time-harmonic Maxwell’s equations. SIAM J. Sci. Comput. 32, 3584–3603 (2010)

    MathSciNet  MATH  Google Scholar 

  90. Roux, F.: FETI-2LM for non-matching grids. In: Bercovier, M., Gander, M.J., Kornhuber, R., Widlund, O. (eds.) Domain Decomposition Methods in Science and Engineering XVIII, Lecture Notes in Computational Science and Engineering, vol. 70, pp. 121–128. Springer, Berlin. https://doi.org/10.1007/978-3-642-02677-5_11, www.ddm.org/DD18/proceedings/numerik.mi.fu-berlin.de/DDM/DD18/Roux.pdf (2009)

  91. Roux, F., Magoulès, F., Salmon, S., Series, L.: Optimization of interface operator based on algebraic approach. In: Herrera, I., Keyes, D.E., Widlund, O.B., Yates, R. (eds.) Fourteenth International Conference on Domain Decomposition Methods, pp. 297–304. National Autonomous University of Mexico (UNAM), Mexico City, Mexico. (DD14 at Cocoyoc, Mexico, January 6–11, 2002) www.ddm.org/DD14/roux.pdf (2003)

  92. Schneider, H.: Near field sources and field coupling techniques in transient high frequency simulations. Doctoral thesis, Institut für Theorie Elektromagnetischer Felder, Technische Universität Darmstadt, Germany (2016)

  93. Smith, B.F., Bjørstad, B.E., Gropp, W.: Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations. Cambridge University Press, Cambridge (1996)

    MATH  Google Scholar 

  94. Steinbach, O.: Numerical Approximation Methods for Elliptic Boundary Value Problems. Finite and Boundary Elements, Springer, New York (2008)

    MATH  Google Scholar 

  95. Stupfel, B., Chanaud, M.: High-order transmission conditions in a domain decomposition method for the time-harmonic Maxwell’s equations in inhomogeneous media. J. Comput. Phys. 372, 385–405 (2018)

    MathSciNet  MATH  Google Scholar 

  96. Toselli, A., Widlund, O.B.: Domain Decomposition Methods—Algorithms and Theory, Springer Series in Computational Mathematics, vol. 34. Springer, Berlin (2005)

    MATH  Google Scholar 

  97. Vouvakis, M.N.: A non-conformal domain decomposition method for solving large electromagnetic wave problems. Ph.D. thesis, The Ohio State University, Columbus (2005)

  98. Vouvakis, M.N.: Recent advances on domain decomposition finite element methods. In: 2015 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE. https://doi.org/10.1109/ICEAA.2015.7297318 (2015)

  99. Vouvakis, M.N., Cendes, Z., Lee, J.F.: A FEM domain decomposition method for photonic and electromagnetic band gap structures. IEEE Trans. Antennas Propag. 54(2), 721–733 (2006)

    MathSciNet  MATH  Google Scholar 

  100. Vouvakis, M.N., Lee, J.: A fast DP-FETI like domain decomposition algorithm for the solution of large electromagnetic problems. In: Proceedings of the 8th Copper Mountain Conference on iterative methods. Copper Mountain, Colorado, March 28–April 2. https://grandmaster.colorado.edu/copper/2004/abs/vouvakis.pdf (2014)

  101. Windisch, M.: Boundary element tearing and interconnecting methods for acoustic and electromagnetic scattering. Doctoral thesis, Graz University of Technology, Austria. http://lamp.tugraz.at/~karl/verlagspdf/buch_windisch_10062011.pdf (2011)

  102. Yosida, K.: Functional Analysis, 6th edn. Springer, Berlin (1980)

    MATH  Google Scholar 

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Acknowledgements

The author would like to express his sincere thanks to Ortwin Farle (Dassault Systèmes) for very detailed discussions on the topic and the manuscript as well as biographical hints. Further thanks go to Timo Euler, Sabine Zaglmayr, and Hermann Schneider (Dassault Systèmes) as well as to Xavier Claeys (UPMC Paris) and Martin Gander (Université de Genève) for their motivation and a series of fruitful discussions. Some helpful hints were also provided by Patrick Joly (ENSTA Paris), Ivan Graham (University of Bath), Sebastian Schöps (TU Darmstadt), Clemens Hofreither (RICAM Linz), and Herbert Egger (that time TU Darmstadt, now JKU Linz).

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Appendices

Proof of Theorem 4.5

Beforehand, observe that since none of the operators T, \({\mathcal {X}}\) couples subdomain dofs or trace dofs that correspond to two different global dofs, we can treat one global interface dof at a time. So without loss of generality, we may assume that \({\mathcal {D}}_\varGamma \) consists of a single global interface dof k, such that our goal is a proof for \(\dim ({\mathcal {Z}}) = \ell _k\).

Let \({\mathcal {E}}_k'\) be the edges of a fixed minimal spanning tree of the connectivity graph \({\mathcal {C}}_k\) (see Fig. 18, left) and let us collect the remaining edges \({\mathcal {E}}_k \setminus {\mathcal {E}}_k'\) in a sequence \((e_1\,,\ldots ,e_m)\). By classical graph theory, \(\#{{\mathcal {E}}_k'} = \#{{\mathcal {N}}_k} - 1\) and for each remaining edge \(e_i\), \(i=1,\ldots ,m\), there exists an associated cycle \({\mathcal {L}}_i\) consisting of edges from \({\mathcal {E}}_k' \cup \{ e_1,\ldots ,e_i \}\), such that the number of independent cycles in \({\mathcal {C}}_k\) is given by \(\ell _k = m\) (see Fig. 18, middle).

As one observes, \(\mu \in \varLambda ^*\) has two values per facet (one for each subdomain), so accordingly, two values per edge of the connectivity graph. Since each subdomain corresponds to a node of the graph, we can think of these values as being associated with the endpoints of the edges. Under that perspective, the operator \(T^{\textsf{T}}\) sums up the all values per node, while the operator \((I + {\mathcal {X}}^{\textsf{T}})\) sums up the two values per edge.

For each edge \(e_i\), we define an element \({{\widehat{\mu }}}_i \in {\mathcal {Z}}\) by putting values \(\pm 1\) along the associated cycle \({\mathcal {L}}_i\) as illustrated in Fig. 18 (right) and zero elsewhere. Apparently, \(T^{\textsf{T}}{{\widehat{\mu }}}_i = 0\) because the two non-zero values associated with each node within the cycle have opposite sign. At the same time, the two values associated with each edge within the cycle sum up to zero as well, so \((I + {\mathcal {X}}^{\textsf{T}}) {{\widehat{\mu }}}_i = 0\). Altogether, \({{\widehat{\mu }}}_i \in {\mathcal {Z}}\). Moreover, the element \({{\widehat{\mu }}}_i\) is linearly independent from \(\{ {{\widehat{\mu }}}_j \}_{j=1}^{i-1}\) because the latter are not supported on the edge \(e_i\). Therefore \(\dim ({\mathcal {Z}}) \ge m\).

In order to see that \(\dim ({\mathcal {Z}}) \le m\), we let \(\mu \in {\mathcal {Z}}\) be arbitrary but fixed. Recall the sequence \((e_1,\ldots ,e_m)\) of remaining edges and let us start with the edge \(e_m\). Since \((I - {\mathcal {X}}^{\textsf{T}})\mu = 0\), the two values of \(\mu \) on edge \(e_m\) must have opposite sign. Therefore, we can find a coefficient \(\alpha _m\) such that \(\mu _m := \mu - \alpha _m {{\widehat{\mu }}}_m\) has vanishing values on edge \(e_m\). We proceed inductively. For \(i > 1\), suppose that \(\mu _i \in {\mathcal {Z}}\) has vanishing values on all edges \(e_i,\ldots ,e_m\). Then, since \((I - {\mathcal {X}}^{\textsf{T}})\mu _i = 0\), the two values of \(\mu _i\) on edge \(e_{i-1}\) must have opposite sign. So there exists a coefficient \(\alpha _{i-1}\) such that \(\mu _{i-1} := \mu _i - \alpha _{i-1} {{\widehat{\mu }}}_{i-1}\) has vanishing values on edge \(e_{i-1}\). Since \({{\widehat{\mu }}}_{i-1}\) has vanishing values on all the edges \(e_i,\ldots ,e_m\), the function \(\mu _{i-1}\) vanishes on all the edges \(e_{i-1},\ldots ,e_m\) and \(\mu _{i-1} \in {\mathcal {Z}}\). The inductive process stops with \(\mu _1 \in {\mathcal {Z}}\) vanishing entirely on all remaining edges \(e_1,\ldots ,e_m\), and so the only possible non-zero values of \(\mu _1\) are located at the edges of the minimal spanning tree. This spanning tree, however, must have nodes with just one edge attached. The condition \(T^{\textsf{T}}\mu _1 = 0\) implies that the values of \(\mu _1\) at these node and the attached edges is zero. Using the condition \((I + {\mathcal {X}}^{\textsf{T}}) \mu _1 = 0\) along the edges allows to show, eventually, that \(\mu _1 = 0\). Therefore, \(\dim ({\mathcal {Z}}) = m\) and \({\mathcal {Z}} = \text {span}\{ {{\widehat{\mu }}}_1, \ldots , {{\widehat{\mu }}}_m \}\).

Fig. 18
figure 18

Illustration of the proof Theorem 4.5Left: minimal spanning tree, \(\circ \) nodes with just one edge attached Middle: black edges: minimal spanning tree, colored: sequence of remaining edges with associated cycles Right: Values of \({{\widehat{\mu }}}_5\) associated with the cycle of \(e_5\)

Invertibility of Generalized Robin Problems

In this section, we investigate the invertibility of the augmented operator \(A + \alpha T^{\textsf{T}}M T\), cf. Assumption A5. As for classical wave propagation, the two building blocks are the Fredholm property and the injectivity, which altogether ensure a bounded inverse, see e.g. [56, 77]. In the discrete case, invertibility is usually proved either via injectivity alone or via an inf-sup condition derived from the continuous counterpart, cf. e.g. [56].

We begin with the injectivity (Sect. B.1), visit some general tools on the Fredholm property (Sect. B.2) and apply these for standard as well as generalized Robin problems (Sect. B.3 and Sect. B.4). As will be noted, for some constellations in the case of Maxwell’s equations, the Fredholm property remains an open problem.

1.1 Injectivity

We start with the assumption that the operator M is block-diagonal, which allows to treat one subdomain at a time.

Assumption C1

The operator M from Ass. A3 has the block-diagonal form \(M = \textrm{diag}(M_i)_{i=1}^N\), where each operator \(M_i :\varLambda _i \rightarrow \varLambda _i^*\) is real-valued, symmetric, non-negative, and definite, i.e., \(\langle M_i \lambda _i, {\overline{\lambda }}_i \rangle = 0 \implies \lambda _i = 0\) for all \(\lambda _i \in \varLambda _i\).

Note that Assumption A6 implies Ass. C1 but not vice versa.

Assumption C2

In accordance with Assumption A8, the following holds:

  1. (i)

    In the coercive case (with \(\alpha = 1\)):

    $$\begin{aligned} \big [ A_i v_i = 0 \text { and } T_i v_i = 0 \big ] \implies v_i = 0 \qquad \forall v_i \in U_i\,. \end{aligned}$$
  2. (ii)

    In the wave propagation case (with \(\alpha = \text {i}\)):

    $$\begin{aligned} \big [ (A_{i,0} - A_{i,2})v_i = 0 \text { and } A_{i,1} v_i = 0 \text { and } T_i v_i = 0 \big ] \implies v_i = 0 \qquad \forall v_i \in U_i\,. \end{aligned}$$

Assumption C2 can be seen as an abstract version of Holmgreen’s theorem: \(A_i v = 0\) (in case (i)) implies that the Neumann trace on the interface is zero, \(T_i v = 0\) means that the Dirichlet trace on the interface is zero. Inside the subdomain, v fulfills the homogeneous PDE, so v must vanish entirely; see also [39, Thm. 1] or [40, Thm. A.1]. In the typical coercive cases, \(A_i\) has a finite-dimensional kernel (constant functions, rigid body modes), which is fixed by the Dirichlet condition. For Maxwell’s equations, Part (ii) of Ass. C2 is widely known as the continuation principle, cf. e.g. [77, Sect. 4.6].

In the discrete case, the following proposition, which is essentially [11, Lemma 5.1], allows to derive Ass. C2 from the assumptions on the original operator \({\widehat{A}}\).

Proposition B.1

Let Assumption A8 hold, assume that \(\ker ({\widehat{A}}) = \{ 0 \}\) (cf. Sect. 2.2), and let, in addition, Assumption B1 be fulfilled. Then Assumption C2 holds as well.

Proof

Assume without loss of generality, that we are in Case (ii) of Assumption A8 (the proof of Case (i) is analogous) and that \((A_{i,0} - A_{i,2}) v_i = 0\) and \(A_{i,1} v_i = 0\) and \(T_i v_i = 0\). Assumption B1 guarantees that \(\ker (T_i) \subseteq U_{i,B}\), and so for \(T_i v_i = 0\) there exists a function \({\widehat{v}} \in {\widehat{U}}\) such that \(v_i = R_i {\widehat{v}}\) and \(R_j {\widehat{v}} = 0\) for all \(j \ne i\). From this and our initial assumptions, we can conclude that \({\widehat{A}} {\widehat{v}} = 0\), which implies \({\widehat{v}} = 0\) and therefore \(v_i = 0\). \(\square \)

Proposition B.2

(injectivity) Let Assumptions A8, C1, and C2 hold. Then the operator \({{\widetilde{A}}}_i\) is injective.

Proof

For arbitrary but fixed \(v \in U_i\) with \({{\widetilde{A}}}_i v = 0\), we show that \(v = 0\).

Coercive case (\(\alpha = 1\)): \({{\widetilde{A}}}_i = A_i + T_i^{\textsf{T}}M_i T_i\) with \(A_i\) real-valued, symmetric, and non-negative. Due to our assumptions,

$$\begin{aligned} \langle A_i v, {\overline{v}} \rangle + \langle M_i T_i v, T_i {\overline{v}} \rangle = 0, \end{aligned}$$

and since both terms are non-negative, both must vanish. From the assumptions on \(A_i\) and \(M_i\), this implies \(A_i v = 0\) and \(T_i v = 0\). Assumption C2(i) guarantees that \(v = 0\).

Wave propagation case (\(\alpha = \text {i}\)):

$$\begin{aligned} {{\widetilde{A}}}_i = A_{i,0} + \text {i}{{\widetilde{A}}}_{i,1} - A_{i,2}\,, \qquad \text {where } {{\widetilde{A}}}_{i,1} = A_{i,1} + T_i^{\textsf{T}}M_i T_i\,. \end{aligned}$$

Due to our assumptions,

$$\begin{aligned} \langle (A_{i,0} - A_{i,2}) v, {\overline{v}} \rangle + \text {i}\Big ( \underbrace{ \langle A_{i,1} v, {\overline{v}} \rangle }_{ \ge 0 } + \underbrace{ \langle M_i T_i v, T_i {\overline{v}} \rangle }_{ \ge 0 } \Big ) = 0. \end{aligned}$$

Both the real and imaginary part must vanish. Since all the summands in the imaginary part are non-negative,

$$\begin{aligned} \langle A_{i,1} v, {\overline{v}} \rangle = 0 \qquad \text {and} \qquad \langle M_i T_i v, T_i v \rangle = 0. \end{aligned}$$

From the assumptions on \(A_{i,1}\) and on \(M_i\), it follows that \(A_{i,1} v = 0\) and \(T_i v = 0\). Recalling that \({{\widetilde{A}}}_i v = 0\), this implies also that \((A_{i,0} - A_{i,2})v = 0\). Assumption C2(ii) guarantees that \(v = 0\). \(\square \)

1.2 Technical Tools for Fredholm Operators

Lemma B.3

Let V be a real or complexified Hilbert space and \(A :V \rightarrow V^*\) a bounded linear operator that fulfills a generalized Gårding inequality with respect to an isomorphism \({\textsf{F}} :V \rightarrow V\) and a compact bounded linear operator \(C :V \rightarrow V^*\), i.e., there exists a constant \(\gamma > 0\) such that

$$\begin{aligned} \big | \langle A v, {\textsf{F}} {\overline{v}} \rangle + \langle C v, {\overline{v}} \rangle \big | \ge \gamma \Vert v \Vert _V^2 \qquad \forall v \in V, \end{aligned}$$
(B.1)

Then A is Fredholm with index zero.

Proof

We find that the (possibly complex-valued) operator \({\textsf{F}}^{\textsf{T}}A + C\) is positive bounded from below in the sense that

$$\begin{aligned} \big | \langle ({\textsf{F}}^{\textsf{T}}A + C) v, {\overline{v}} \rangle \big | \ge \gamma \Vert v \Vert _V^2 \qquad \forall v \in V. \end{aligned}$$

Since \({\textsf{F}}^{\textsf{T}}A + C\) is obviously bounded, a suitable version of the Lax-Milgram lemma (see e.g. [77, Lemma 2.21]) implies that \({\textsf{F}}^{\textsf{T}}A + C\) is an isomorphism. In particular, \({\textsf{F}}^{\textsf{T}}A + C\) is Fredholm with index zero. Since C is compact, a standard result (see e.g. [74, Thm 2.26]) implies that \({\textsf{F}}^{\textsf{T}}A\) is Fredholm with index zero. Since \({\textsf{F}}^{\textsf{T}}\) is an isomorphism, another standard argument (see e.g. [74, Thm. 2.21]) yields that A itself is Fredholm with index zero. \(\square \)

Lemma B.4

Let V be a complexified Hilbert space and \(A :V \rightarrow V^*\) a bounded linear operator of the form

$$\begin{aligned} A = A_0 + \text {i}\sigma A_1 - A_2\,, \end{aligned}$$

with \(\sigma \in \{ +1, -1 \}\) and with linear, bounded, real-valued, symmetric, and non-negative operators \(A_i :V \rightarrow V^*\). Moreover, assume real-valued projection operators \({\textsf{N}}\) and \({\textsf{R}} :V \rightarrow V\) with \({\textsf{N}} + {\textsf{R}} = I\) such that

  1. (i)

    \(A_0 {\textsf{N}} = 0\),

  2. (ii)

    \(A_2 {\textsf{R}}\) is compact,

  3. (iii)

    either (a) \(A_1 {\textsf{N}}\) is compact or (b) \(A_1 {\textsf{R}}\) is compact, and

  4. (iv)

    there exists a constant \(c > 0\) such that \(\langle (A_0 + A_1 + A_2) v, {\overline{v}} \rangle \ge c\, \Vert v \Vert _V^2\) for all \(v \in V\).

Then A is Fredholm with index zero. The same holds if (iii) and (iv) are replaced by the alternative conditions

  1. (iii’)

    \({\textsf{N}}^{\textsf{T}}A_1 {\textsf{R}}\) is compact, and

  2. (iv’)

    there exists a constant \(c > 0\) such that \(\langle (A_0 + A_2) v, {\overline{v}} \rangle \ge c\, \Vert v \Vert _V^2\) for all \(v \in V\).

Remark B.5

The case \({\textsf{N}} = 0\) is admitted. In that case, only (ii) and (iv) are required.

Proof of Lemma B.4

We define \({\textsf{F}} := {\textsf{R}} - {\textsf{N}}\), which is an isomorphism:

$$\begin{aligned} {\textsf{F}}^2 = (2{\textsf{R}} - I)^2 = 4{\textsf{R}}^2 - 4{\textsf{R}} + I = I. \end{aligned}$$

Using property (i) and the relations \({\textsf{F}} = 2 {\textsf{R}} - I = I - 2 {\textsf{N}}\), we find that

$$\begin{aligned} \langle A v, {\textsf{F}} w \rangle&= \langle A_0 v, ({\textsf{R}} - {\textsf{N}}) w \rangle - \langle A_2 v, ({\textsf{R}} - {\textsf{N}}) w \rangle + \text {i}\sigma \langle A_1 v, ({\textsf{R}} - {\textsf{N}}) w \rangle \\&= \langle A_0 v, ({\textsf{R}} + {\textsf{N}}) w \rangle + \langle A_2 v, (I - 2 {\textsf{R}}) w \rangle + \text {i}\sigma \langle A_1 v, (2 {\textsf{R}} - I) w \rangle \\&= \langle (A_0 + A_2) v, w \rangle - \text {i}\sigma \langle A_1 v, w \rangle - 2 \langle A_2 v, {\textsf{R}} w \rangle + 2 \text {i}\sigma \langle A_1 v, {\textsf{R}} w \rangle , \end{aligned}$$

which will be used for Case (b). Alternatively, we have

$$\begin{aligned} \langle A v, {\textsf{F}} w \rangle&= \langle A_0 v, ({\textsf{R}} + {\textsf{N}}) w \rangle + \langle A_2 v, (I - 2 {\textsf{R}}) w \rangle + \text {i}\sigma \langle A_1 v, (I - 2 {\textsf{N}}) w \rangle \\&= \langle (A_0 + A_2) v, w \rangle + \text {i}\sigma \langle A_1 v, w \rangle - 2 \langle A_2 v, {\textsf{R}} w \rangle - 2 \text {i}\sigma \langle A_1 v, {\textsf{N}} w \rangle , \end{aligned}$$

which will be used for Case (a). We define \(C :V \rightarrow V^*\) by

$$\begin{aligned} \langle C v, w \rangle := {\left\{ \begin{array}{ll} 2 \langle A_2 v, {\textsf{R}} w \rangle + 2 \text {i}\sigma \langle A_1 v, {\textsf{N}} w \rangle &{} \text {in Case~(a),}\\ 2 \langle A_2 v, {\textsf{R}} w \rangle - 2 \text {i}\sigma \langle A_1 v, {\textsf{R}} w \rangle &{} \text {in Case~(b),} \end{array}\right. } \end{aligned}$$

which is a compact operator by property (ii) and (iii). Then,

$$\begin{aligned} \big | \langle (A + C) v, {\textsf{F}} {\overline{v}} \rangle \big | = \big | \underbrace{\langle (A_0 + A_2) v, {\overline{v}} \rangle }_{\in {\mathbb {R}}_0^+} {} + \text {i}\underbrace{\delta \sigma }_{= \pm 1} \underbrace{\langle A_1 v, {\overline{v}} \rangle }_{\in {\mathbb {R}}_0^+} \big | = \langle (A_0 + A_1 + A_2) v, {\overline{v}} \rangle \ge c\, \Vert v \Vert _V^2\,, \end{aligned}$$

with \(\delta = 1\) in Case (a) and \(\delta = -1\) is Case (b). An application of Lemma B.3 shows that \({{\widetilde{A}}}\) is Fredholm. Under the conditions (iii’) and (iv’), we can use

$$\begin{aligned} \langle A v, {\textsf{F}} w \rangle&= \langle A_0 v, ({\textsf{R}} + {\textsf{N}}) w \rangle + \langle A_2 v, (I - 2{\textsf{R}}) w \rangle + \text {i}\sigma \langle A_1 ({\textsf{R}} + {\textsf{N}}) v, ({\textsf{R}} - {\textsf{N}}) w \rangle \\&= \langle (A_0 + A_2) v , w \rangle - 2 \langle A_2 v, {\textsf{R}} w \rangle + \text {i}\sigma \big ( \langle A_1 {\textsf{R}} v, {\textsf{R}} w \rangle - \langle A_1 {\textsf{N}} v, {\textsf{N}} w \rangle \\&\qquad - \langle A_1 {\textsf{R}} v, {\textsf{N}} w \rangle + \langle A_1 {\textsf{N}} v, {\textsf{R}} w \rangle \big ). \end{aligned}$$

We define \(C :V \rightarrow V^*\) by \(\langle C v, w \rangle := 2 \langle A_2 v, {\textsf{R}} w \rangle + \text {i}\sigma \langle A_1 {\textsf{R}} v, {\textsf{N}} w \rangle - \text {i}\sigma \langle A_1 {\textsf{N}} v, {\textsf{R}} w \rangle \), which is a compact operator by properties (ii) and (iii’). Due to (iv’)

$$\begin{aligned} \big | \langle (A + C) v, {\textsf{F}} {\overline{v}} \rangle \big |&= \big | \underbrace{ \langle (A_0 + A_2) v, {\overline{v}} \rangle }_{\in {\mathbb {R}}_0^+} + \text {i}\sigma \! \underbrace{ \big ( \langle A_1 {\textsf{R}} v, {\textsf{R}} {\overline{v}} \rangle \! - \! \langle A_1 {\textsf{N}} v, {\textsf{N}} {\overline{v}} \rangle \big )}_{ \in {\mathbb {R}} } \big | \\&\ge \langle (A_0 + A_2) v, {\overline{v}} \rangle \ge c \Vert v \Vert _V^2\,, \end{aligned}$$

and so again Lemma B.3 implies that \({{\widetilde{A}}}\) is Fredholm. \(\square \)

1.3 Standard Robin Problems

For the following, let us assume that \(\varOmega \subset {\mathbb {R}}^3\) is a bounded Lipschitz domain and \(\varGamma _D\), \(\varGamma _N\), \(\varGamma _R \subset \partial \varOmega \) disjoint surfaces such that \(\partial \varOmega = \overline{\varGamma _D \cup \varGamma _N \cup \varGamma _R}\) and such that \(\varGamma _R\) has non-vanishing surface measure. Note, however, that \(\varGamma _D\) and/or \(\varGamma _N\) are allowed to be empty. Moreover, any of the sets \(\partial \varGamma _D\), \(\partial \varGamma _N\), \(\partial \varGamma _R\) (unless empty) should fulfill the requirements stated in [59, Sect. 2], in particular being the union of closed curves that are piecewise \(C^1\). Later on, it is further assumed that \(\varOmega \) is a curvilinear Lipschitz polyhedron.

1.3.1 The Primal Helmholtz Equation

Let \({\widehat{U}} := H^1_D(\varOmega ) = \{ v \in H^1(\varOmega ) :v = 0 \text { on } \varGamma _D \}\) and let the operator \({\widehat{A}} :{\widehat{U}} \rightarrow {\widehat{U}}^*\) be given by \({\widehat{A}} = {\widehat{A}}_0 + \text {i}{\widehat{A}}_1 - {\widehat{A}}_2\) with

$$\begin{aligned} \langle {\widehat{A}}_0 {\widehat{u}}, {\widehat{v}} \rangle = \int _\varOmega \nabla {\widehat{u}} \cdot \nabla {\widehat{v}} \, dx, \qquad \langle {\widehat{A}}_1 {\widehat{u}}, {\widehat{v}} \rangle = \int _{\varGamma _R} \eta \, {\widehat{u}}\, {\widehat{v}} \, ds, \qquad \langle {\widehat{A}}_2 {\widehat{u}}, {\widehat{v}} \rangle = \int _\varOmega \kappa ^2 {\widehat{u}}\, {\widehat{v}} \, dx. \end{aligned}$$

We set \(\widehat{{\textsf{N}}} = 0\) and \(\widehat{{\textsf{R}}} = I\). Since \({\widehat{A}}_2\) is compact and since

$$\begin{aligned} \langle ({\widehat{A}}_0 + {\widehat{A}}_1 + {\widehat{A}}_2) {\widehat{v}}, \overline{{\widehat{v}}} \rangle \ge \min (1, \kappa _{\min }^2) \Vert {\widehat{v}} \Vert _{H^1(\varOmega )}^2\,, \end{aligned}$$

where \(\kappa _{\min }\) is a positive lower bound for the coefficient \(\kappa \) in \(\varOmega \), Lemma B.4 guarantees that \({\widehat{A}}\) is Fredholm.

1.3.2 The Dual Helmholtz Equation

Let \({\widehat{U}} := \{ \textbf{v}\in \textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}, \varOmega ) :\textbf{v}_{n|\varGamma _R} \in L^2(\varGamma _R) \}\), where \(\textbf{v}_n\) denotes the normal trace of \(\textbf{v}\) in \(H^{-1/2}(\partial \varOmega )\). The restriction \(\textbf{v}_{n|\varGamma _R}\) is well-defined in \(H^{-1/2}_{00}(\varGamma _R)\). We use the norm \(\Vert \textbf{v}\Vert _{{\widehat{U}}}^2 = \Vert \textbf{v}\Vert _{\textbf{L}^2(\varOmega )}^2 + \Vert \mathop {{\text {div}}}\textbf{v}\Vert _{L^2(\varOmega )}^2 + \Vert \textbf{v}_{n|\varGamma _R} \Vert _{L^2(\varGamma _R)}^2\). The operator \({\widehat{A}} :{\widehat{U}} \rightarrow {\widehat{U}}^*\) is given by \({\widehat{A}} = {\widehat{A}}_0 + \text {i}{\widehat{A}}_1 - {\widehat{A}}_2\) with

$$\begin{aligned} \langle {\widehat{A}}_0 {{\widehat{\textbf{u}}}}, {{\widehat{\textbf{v}}}} \rangle = \int _\varOmega \kappa ^{-2} \mathop {{\text {div}}}{{\widehat{\textbf{u}}}}\, \mathop {{\text {div}}}{{\widehat{\textbf{v}}}} \, dx, \quad \langle {\widehat{A}}_1 {{\widehat{\textbf{u}}}}, {{\widehat{\textbf{v}}}} \rangle = \int _{\varGamma _R} \eta ^{-1}\, {{\widehat{\textbf{u}}}}_n {{\widehat{\textbf{v}}}}_n \, ds, \quad \langle {\widehat{A}}_2 {{\widehat{\textbf{u}}}}, {{\widehat{\textbf{v}}}} \rangle = \int _\varOmega {{\widehat{\textbf{u}}}} \cdot {{\widehat{\textbf{v}}}} \, dx. \end{aligned}$$

Due to the regular decomposition result in [59], there exist bounded, linear, and real-valued projections \(\underline{{\textsf{N}}} :\textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}, \varOmega ) \rightarrow \textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}0, \varOmega )\) and \(\underline{{\textsf{R}}} :\textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}, \varOmega ) \rightarrow \textbf{H}^1_{\varGamma _N}(\varOmega )\) with \(\underline{{\textsf{N}}} + \underline{{\textsf{R}}} = I\) in \(\textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}, \varOmega )\). For \({{\widehat{\textbf{v}}}} \in {\widehat{U}}\),

$$\begin{aligned} {{\widehat{\textbf{v}}}}_{n|\varGamma _R} = (\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}} )_{n|\varGamma _R} + (\underline{{\textsf{N}}} {{\widehat{\textbf{v}}}})_{n|\varGamma _R} \in L^2(\varGamma _R). \end{aligned}$$

Assuming that \(\varOmega \) is a curvilinear polyhedron (cf. [6]), the outer normal \(\textbf{n}\) is piecewise smooth. Therefore, since \(\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}} \in \textbf{H}^1_{\varGamma _N}(\varOmega )\), we find that \((\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}})_{n|\varGamma _R} = (\underline{{\textsf{R}}}{{\widehat{\textbf{v}}}})_{|\varGamma _R} \cdot \textbf{n}\in H^{1/2}_{\text {pw}}(\varGamma _R) \subset L^2(\varGamma _R)\). This shows that \((\underline{{\textsf{N}}} {{\widehat{\textbf{v}}}})_{n|\varGamma _R} \in L^2(\varGamma _R)\) as well. Hence, we can restrict \(\underline{{\textsf{R}}}\), \(\underline{{\textsf{N}}}\) to operators \(\widehat{{\textsf{R}}}\), \(\widehat{{\textsf{N}}} :{\widehat{U}} \rightarrow {\widehat{U}}\), and we meet the prerequisites of Lemma B.4:

  • \(\widehat{{\textsf{R}}}\), \(\widehat{{\textsf{N}}}\) are projectors and \(\widehat{{\textsf{R}}} + \widehat{{\textsf{N}}} = I\) in \({\widehat{U}}\),

  • \({\widehat{A}}_0 \widehat{{\textsf{N}}} = 0\) since \(\underline{{\textsf{N}}}\) maps to \(\textbf{H}_{\varGamma _N}(\mathop {{\text {div}}}0, \varOmega )\),

  • \({\widehat{A}}_2 \widehat{{\textsf{R}}}\) is compact since \(\underline{{\textsf{R}}}\) maps to \(\textbf{H}^1_{\varGamma _N}(\varOmega )\) which is compactly embedded in \(\textbf{L}^2(\varOmega )\),

  • \({\widehat{A}}_1 \widehat{{\textsf{R}}}\) is compact since \((\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}})_{n|\varGamma _R} \in H^{1/2}_{\text {pw}}(\varGamma _R)\) which is compactly embedded in \(L^2(\varGamma _R)\),

  • \(\langle ({\widehat{A}}_0 + {\widehat{A}}_1 + {\widehat{A}}_2) {{\widehat{\textbf{v}}}}, \overline{{{\widehat{\textbf{v}}}}} \rangle \ge \min (1, \kappa _{\max }^{-2}, \eta _{\max }^{-1}) \big ( \Vert \mathop {{\text {div}}}{{\widehat{\textbf{v}}}} \Vert _{L^2(\varOmega )}^2 + \Vert {{\widehat{\textbf{v}}}} \Vert _{\textbf{L}^2(\varOmega )}^2 + \Vert {{\widehat{\textbf{v}}}}_{n|\varGamma _R} \Vert _{L^2(\varGamma _R)}^2 \big )\),

where \(\kappa _{\max }\), \(\eta _{\max }\) are finite upper bounds for the coefficients \(\kappa \), \(\eta \) in \(\varOmega \).

1.3.3 Maxwell’s Equations

To avoid complications, it is again assumed that \(\varOmega \) is a curvilinear Lipschitz polyhedron (cf. [6]). Let \({\widehat{U}} := \{ \textbf{v}\in \textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}, \varOmega ) :\textbf{v}_{\tau |\varGamma _R} \in L^2(\varGamma _R) \}\), where \(\textbf{v}_\tau = \textbf{v}\times \textbf{n}\) denotes the tangential trace of \(\textbf{v}\) in \(\textbf{H}^{-1/2}(\partial \varOmega )\) and the restriction \(\textbf{v}_{\tau |\varGamma _R}\) is well-defined, for details see [6, 77]. We use the norm \(\Vert \textbf{v}\Vert _{{\widehat{U}}}^2 = \Vert \textbf{v}\Vert _{\textbf{L}^2(\varOmega )}^2 + \Vert \mathop {{\text {\textbf{curl}}}}\textbf{v}\Vert _{\textbf{L}^2(\varOmega )}^2 + \Vert \textbf{v}_{\tau |\varGamma _R} \Vert _{\textbf{L}^2(\varGamma _R)}^2\). The operator \({\widehat{A}} :{\widehat{U}} \rightarrow {\widehat{U}}^*\) is given by \({\widehat{A}} = {\widehat{A}}_0 + \text {i}{\widehat{A}}_1 - {\widehat{A}}_2\) with

$$\begin{aligned}&\langle {\widehat{A}}_0 {{\widehat{\textbf{u}}}}, {{\widehat{\textbf{v}}}} \rangle = \! \int _\varOmega \!\! \mu ^{-1} \mathop {{\text {\textbf{curl}}}}{{\widehat{\textbf{u}}}} \cdot \mathop {{\text {\textbf{curl}}}}{{\widehat{\textbf{v}}}} \, dx, \quad \langle {\widehat{A}}_1 {{\widehat{\textbf{u}}}}, {{\widehat{\textbf{v}}}} \rangle = \! \int _{\varGamma _R} \!\!\! \omega \eta ^{-1}\, {{\widehat{\textbf{u}}}}_\tau \cdot {{\widehat{\textbf{v}}}}_\tau \, ds, \quad \\&\langle {\widehat{A}}_2 {{\widehat{\textbf{u}}}},{{\widehat{\textbf{v}}}} \rangle = \! \int _\varOmega \!\! \omega ^2 \varepsilon {{\widehat{\textbf{u}}}} \cdot {{\widehat{\textbf{v}}}} \, dx. \end{aligned}$$

There exist bounded, linear, and real-valued projectors \(\underline{{\textsf{N}}} :\textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}, \varOmega ) \rightarrow \textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}0, \varOmega )\) and \(\underline{{\textsf{R}}} :\textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}, \varOmega ) \rightarrow \textbf{H}^1_{\varGamma _D}(\varOmega )\) with \(\underline{{\textsf{R}}} + \underline{{\textsf{N}}} = I\) in \(\textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}, \varOmega )\), see [59]. For \({{\widehat{\textbf{v}}}} \in {\widehat{U}}\),

$$\begin{aligned} {{\widehat{\textbf{v}}}}_{\tau |\varGamma _R} = (\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}} )_{\tau |\varGamma _R} + (\underline{{\textsf{N}}} {{\widehat{\textbf{v}}}})_{\tau |\varGamma _R} \in \textbf{L}^2(\varGamma _R). \end{aligned}$$

Due to the assumptions on \(\varOmega \), the normal \(\textbf{n}\) is piecewise smooth. Therefore, since \(\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}} \in \textbf{H}^1_{\varGamma _D}(\varOmega )\), we find that \((\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}})_{\tau |\varGamma _R} = (\underline{{\textsf{R}}}{{\widehat{\textbf{v}}}})_{|\varGamma _R} \times \textbf{n}\in \textbf{H}^{1/2}_{\text {pw}}(\varGamma _R) \subset \textbf{L}^2(\varGamma _R)\). This shows that \((\underline{{\textsf{N}}} {{\widehat{\textbf{v}}}})_{\tau |\varGamma _R} \in \textbf{L}^2(\varGamma _R)\) as well. Hence, we can restrict \(\underline{{\textsf{N}}}\), \(\underline{{\textsf{R}}}\) to operators \(\widehat{{\textsf{N}}}\), \(\widehat{{\textsf{R}}} :{\widehat{U}} \rightarrow {\widehat{U}}\), and we meet the prerequisites of Lemma B.4:

  • \(\widehat{{\textsf{N}}}\), \(\widehat{{\textsf{R}}}\) are projectors and \(\widehat{{\textsf{N}}} + \widehat{{\textsf{R}}} = I\) in \({\widehat{U}}\),

  • \({\widehat{A}}_0 \widehat{{\textsf{N}}} = 0\) since \(\underline{{\textsf{N}}}\) maps to \(\textbf{H}_{\varGamma _D}(\mathop {{\text {\textbf{curl}}}}0, \varOmega )\),

  • \({\widehat{A}}_2 \widehat{{\textsf{R}}}\) is compact since \(\underline{{\textsf{R}}}\) maps to \(\textbf{H}^1_{\varGamma _D}(\varOmega )\) which is compactly embedded in \(\textbf{L}^2(\varOmega )\),

  • \({\widehat{A}}_1 \widehat{{\textsf{R}}}\) is compact since \((\underline{{\textsf{R}}} {{\widehat{\textbf{v}}}})_{\tau |\varGamma _R} \in \textbf{H}^{1/2}_{\text {pw}}(\varGamma _R)\) which is compactly embedded in \(\textbf{L}^2(\varGamma _R)\),

  • \(\langle ({\widehat{A}}_0 + {\widehat{A}}_1 + {\widehat{A}}_2) {{\widehat{\textbf{v}}}}, \overline{{{\widehat{\textbf{v}}}}} \rangle \ge \min (\mu _{\max }^{-1}, \omega ^2 \varepsilon _{\min }^2, \omega \eta _{\min }) \big ( \Vert \mathop {{\text {\textbf{curl}}}}{{\widehat{\textbf{v}}}} \Vert _{L^2(\varOmega )}^2 + \Vert {{\widehat{\textbf{v}}}} \Vert _{\textbf{L}^2(\varOmega )}^2 + \Vert {{\widehat{\textbf{v}}}}_{\tau |\varGamma _R} \Vert _{\textbf{L}^2(\varGamma _R)}^2 \big )\),

where \(\mu _{\max }\), \(\varepsilon _{\min }\), \(\eta _{\min }\) are finite upper/positive lower bounds for the coefficients \(\mu \), \(\varepsilon \), \(\eta \) in \(\varOmega \).

1.4 Generalized Robin Problems

In this section, we investigate whether the subdomain operator

$$\begin{aligned} {{\widetilde{A}}}_i := A_i + \alpha T_i^{\textsf{T}}M_i T_i \end{aligned}$$

is Fredholm with index zero.

1.4.1 Wave Propagation Case

In accordance with Assumption A8 (with \(\alpha = \text {i}\)), we assume that there exist projectors \({\textsf{N}}_i\), \({\textsf{R}}_i\) such that

  1. (i)

    \(A_{i,0} {\textsf{N}}_i = 0\),

  2. (ii)

    \(A_{i,2} {\textsf{R}}_i\) is compact,

  3. (iii)

    either (a) \(A_{i,1} {\textsf{N}}_i\) is compact or (b) \(A_{i,1} {\textsf{R}}_i\) is compact, and

  4. (iv)

    there exists a constant \(c_i > 0\) such that \(\langle (A_{i,0} + A_{i,1} + A_{i,2}) v, {\overline{v}} \rangle \ge c \Vert v \Vert _{U_i}^2\) for all \(v \in U_i\).

such that Lemma B.4 implies that \(A_i\) is Fredholm with index zero. With the definitions

$$\begin{aligned} {{\widetilde{A}}}_i = A_{i,0} + \text {i}{{\widetilde{A}}}_{i,1} - A_{i,2}\,, \qquad \text {where } {{\widetilde{A}}}_{i,1} = A_{i,1} + T_i^{\textsf{T}}M_i T_i\,, \end{aligned}$$

Lemma B.4 would imply that \({{\widetilde{A}}}_i\) is Fredholm with index zero as well if, in addition to the above:

  1. (v)

    either (a) \({{\widetilde{A}}}_{i,1} {\textsf{N}}_i\) is compact or (b) \({{\widetilde{A}}}_{i,1} {\textsf{R}}_i\) is compact, and

  2. (vi)

    there exists a constant \(c_i > 0\) such that \(\langle (A_{i,0} + {{\widetilde{A}}}_{i,1} + A_{i,2}) v, {\overline{v}} \rangle \ge c \Vert v \Vert _{U_i}^2\) for all \(v \in U_i\).

The inequality (vi) follows from (iv) because \(M_i\) is non-negative. We are left with the question whether the operator \(T_i^{\textsf{T}}M_i T_i {\textsf{N}}_i\) (in case (a)) or \(T_i^{\textsf{T}}M_i T_i {\textsf{R}}_i\) (in case (b)) is compact:

  • For the primal Helmholtz formulation, we can use \({\textsf{N}}_i = 0\).

  • If the trace operator \(T_i\) itself is compact (cf. Theorem 6.4), we are also done.

  • For the dual Helmholtz formulation, (iii) holds with case (b), \(\textrm{range}(T_i {\textsf{R}}_i) \subset H^{1/2}_{\text {pw}}(\varGamma _i)\), where \(\varGamma _i\) is the chosen interface, possibly split into facets. The latter space is compactly embedded in \(L^2(\varGamma _i)\), and thus also compactly embedded in any chosen trace space \(\varLambda _i\) (which requires at most \(H^{-1/2}\)-regularity). Therefore, \(T_i {\textsf{R}}_i :U_i \rightarrow \varLambda _i\) is compact, and so (v) holds with case (b).

The Maxwell case is to a large extent open, at least if \(T_i\) is not compact. However, one exceptional situation shall be mentioned: If \(A_{i,1} = 0\) and \(M_i\) is orthogonal with respect to the regular decomposition, i.e., \({\textsf{N}}_i^{\textsf{T}}T_i^{\textsf{T}}M_i T_i {\textsf{R}}_i = 0\), then using the alternative conditions (iii’), (iv’) in Lemma B.4, one can show that \({{\widetilde{A}}}_i\) is Fredholm with index zero. For more results see [83, Sect. 3.4.2].

1.4.2 Coercive Case

In accordance with Assuption A8 (with \(\alpha = 1\)), we assume that there exists a compact operatorFootnote 16\(C_i\) such that \(A_i + C_i\) is bounded positively from below, such that \(A_i\) is Fredholm with index zero. Since, by assumption \(M_i\) is non-negative,

$$\begin{aligned} \langle ({{\widetilde{A}}}_i + C_i) v, {\overline{v}} \rangle = \langle (A_i + C_i) v, {\overline{v}} \rangle + \langle M_i T_i v, T_i {\overline{v}} \rangle \ge \gamma _i \Vert v \Vert _{U_i}^2, \end{aligned}$$

for some constant \(\gamma _i > 0\) such that \({{\widetilde{A}}}_i\) is Fredholm.

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Pechstein, C. A Unified Theory of Non-overlapping Robin–Schwarz Methods: Continuous and Discrete, Including Cross Points. J Sci Comput 96, 60 (2023). https://doi.org/10.1007/s10915-023-02248-9

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