Finite-difference time-domain (FDTD) or Yee's method (named after the Chinese American applied mathematician Kane S. Yee, born 1934) is a numerical analysis technique used for modeling computational electrodynamics.
Finite-difference time-domain (FDTD) or Yee's method (named after the Chinese American applied mathematician Kane S. Yee, born 1934) is a numerical analysis technique used for modeling computational electrodynamics.
Finite difference schemes for time-dependent partial differential equations (PDEs) have been employed for many years in computational fluid dynamics problems, [1] including the idea of using centered finite difference operators on staggered grids in space and time to achieve second-order accuracy. [1] The novelty of Yee's FDTD scheme, presented in his seminal 1966 paper, [2] was to apply centered finite difference operators on staggered grids in space and time for each electric and magnetic vector field component in Maxwell's curl equations. The descriptor "Finite-difference time-domain" and its corresponding "FDTD" acronym were originated by Allen Taflove in 1980. [3] Since about 1990, FDTD techniques have emerged as primary means to computationally model many scientific and engineering problems dealing with electromagnetic wave interactions with material structures. Current FDTD modeling applications range from near-DC (ultralow-frequency geophysics involving the entire Earth-ionosphere waveguide) through microwaves (radar signature technology, antennas, wireless communications devices, digital interconnects, biomedical imaging/treatment) to visible light (photonic crystals, nanoplasmonics, solitons, and biophotonics). [4] In 2006, an estimated 2,000 FDTD-related publications appeared in the science and engineering literature (see Popularity). As of 2013, there are at least 25 commercial/proprietary FDTD software vendors; 13 free-software/open-source-software FDTD projects; and 2 freeware/closed-source FDTD projects, some not for commercial use (see External links).
An appreciation of the basis, technical development, and possible future of FDTD numerical techniques for Maxwell's equations can be developed by first considering their history. The following lists some of the key publications in this area.
| Partial chronology of FDTD techniques and applications for Maxwell's equations. [5] | |
|---|---|
| year | event |
| 1928 | Courant, Friedrichs, and Lewy (CFL) publish seminal paper with the discovery of conditional stability of explicit time-dependent finite difference schemes, as well as the classic FD scheme for solving second-order wave equation in 1-D and 2-D. [6] |
| 1950 | First appearance of von Neumann's method of stability analysis for implicit/explicit time-dependent finite difference methods. [7] |
| 1966 | Yee described the FDTD numerical technique for solving Maxwell's curl equations on grids staggered in space and time. [2] |
| 1969 | Lam reported the correct numerical CFL stability condition for Yee's algorithm by employing von Neumann stability analysis. [8] |
| 1975 | Taflove and Brodwin reported the first sinusoidal steady-state FDTD solutions of two- and three-dimensional electromagnetic wave interactions with material structures; [9] and the first bioelectromagnetics models. [10] |
| 1977 | Holland and Kunz & Lee applied Yee's algorithm to EMP problems. [11] [12] |
| 1980 | Taflove coined the FDTD acronym and published the first validated FDTD models of sinusoidal steady-state electromagnetic wave penetration into a three-dimensional metal cavity. [3] |
| 1981 | Mur published the first numerically stable, second-order accurate, absorbing boundary condition (ABC) for Yee's grid. [13] |
| 1982–83 | Taflove and Umashankar developed the first FDTD electromagnetic wave scattering models computing sinusoidal steady-state near-fields, far-fields, and radar cross-section for two- and three-dimensional structures. [14] [15] |
| 1984 | Liao et al reported an improved ABC based upon space-time extrapolation of the field adjacent to the outer grid boundary. [16] |
| 1985 | Gwarek introduced the lumped equivalent circuit formulation of FDTD. [17] |
| 1986 | Choi and Hoefer published the first FDTD simulation of waveguide structures. [18] |
| 1987–88 | Kriegsmann et al and Moore et al published the first articles on ABC theory in IEEE Transactions on Antennas and Propagation. [19] [20] |
| 1987–88, 1992 | Contour-path subcell techniques were introduced by Umashankar et al to permit FDTD modeling of thin wires and wire bundles, [21] by Taflove et al to model penetration through cracks in conducting screens, [22] and by Jurgens et al to conformally model the surface of a smoothly curved scatterer. [23] |
| 1988 | Sullivan et al published the first 3-D FDTD model of sinusoidal steady-state electromagnetic wave absorption by a complete human body. [24] |
| 1988 | FDTD modeling of microstrips was introduced by Zhang et al. [25] |
| 1990–91 | FDTD modeling of frequency-dependent dielectric permittivity was introduced by Kashiwa and Fukai, [26] Luebbers et al, [27] and Joseph et al. [28] |
| 1990–91 | FDTD modeling of antennas was introduced by Maloney et al, [29] Katz et al, [30] and Tirkas and Balanis. [31] |
| 1990 | FDTD modeling of picosecond optoelectronic switches was introduced by Sano and Shibata, [32] and El-Ghazaly et al. [33] |
| 1992–94 | FDTD modeling of the propagation of optical pulses in nonlinear dispersive media was introduced, including the first temporal solitons in one dimension by Goorjian and Taflove; [34] beam self-focusing by Ziolkowski and Judkins; [35] the first temporal solitons in two dimensions by Joseph et al; [36] and the first spatial solitons in two dimensions by Joseph and Taflove. [37] |
| 1992 | FDTD modeling of lumped electronic circuit elements was introduced by Sui et al. [38] |
| 1993 | Toland et al published the first FDTD models of gain devices (tunnel diodes and Gunn diodes) exciting cavities and antennas. [39] |
| 1993 | Aoyagi et al present a hybrid Yee algorithm/scalar-wave equation and demonstrate equivalence of Yee scheme to finite difference scheme for electromagnetic wave equation. [40] |
| 1994 | Thomas et al introduced a Norton's equivalent circuit for the FDTD space lattice, which permits the SPICE circuit analysis tool to implement accurate subgrid models of nonlinear electronic components or complete circuits embedded within the lattice. [41] |
| 1994 | Berenger introduced the highly effective, perfectly matched layer (PML) ABC for two-dimensional FDTD grids, [42] which was extended to non-orthogonal meshes by Navarro et al, [43] and three dimensions by Katz et al, [44] and to dispersive waveguide terminations by Reuter et al. [45] |
| 1994 | Chew and Weedon introduced the coordinate stretching PML that is easily extended to three dimensions, other coordinate systems and other physical equations. [46] |
| 1995–96 | Sacks et al and Gedney introduced a physically realizable, uniaxial perfectly matched layer (UPML) ABC. [47] [48] |
| 1997 | Liu introduced the pseudospectral time-domain (PSTD) method, which permits extremely coarse spatial sampling of the electromagnetic field at the Nyquist limit. [49] |
| 1997 | Ramahi introduced the complementary operators method (COM) to implement highly effective analytical ABCs. [50] |
| 1998 | Maloney and Kesler introduced several novel means to analyze periodic structures in the FDTD space lattice. [51] |
| 1998 | Nagra and York introduced a hybrid FDTD-quantum mechanics model of electromagnetic wave interactions with materials having electrons transitioning between multiple energy levels. [52] |
| 1998 | Hagness et al introduced FDTD modeling of the detection of breast cancer using ultrawideband radar techniques. [53] |
| 1999 | Schneider and Wagner introduced a comprehensive analysis of FDTD grid dispersion based upon complex wavenumbers. [54] |
| 2000–01 | Zheng, Chen, and Zhang introduced the first three-dimensional alternating-direction implicit (ADI) FDTD algorithm with provable unconditional numerical stability. [55] [56] |
| 2000 | Roden and Gedney introduced the advanced convolutional PML (CPML) ABC. [57] |
| 2000 | Rylander and Bondeson introduced a provably stable FDTD - finite-element time-domain hybrid technique. [58] |
| 2002 | Hayakawa et al and Simpson and Taflove independently introduced FDTD modeling of the global Earth-ionosphere waveguide for extremely low-frequency geophysical phenomena. [59] [60] |
| 2003 | DeRaedt introduced the unconditionally stable, “one-step” FDTD technique. [61] |
| 2004 | Soriano and Navarro derived the stability condition for Quantum FDTD technique. [62] |
| 2008 | Ahmed, Chua, Li and Chen introduced the three-dimensional locally one-dimensional (LOD)FDTD method and proved unconditional numerical stability. [63] |
| 2008 | Taniguchi, Baba, Nagaoka and Ametani introduced a Thin Wire Representation for FDTD Computations for conductive media [64] |
| 2009 | Oliveira and Sobrinho applied the FDTD method for simulating lightning strokes in a power substation [65] |
| 2012 | Moxley et al developed a generalized finite-difference time-domain quantum method for the N-body interacting Hamiltonian. [66] |
| 2013 | Moxley et al developed a generalized finite-difference time-domain scheme for solving nonlinear Schrödinger equations. [67] |
| 2014 | Moxley et al developed an implicit generalized finite-difference time-domain scheme for solving nonlinear Schrödinger equations. [68] |
| 2021 | Oliveira and Paiva developed the Least Squares Finite-Difference Time-Domain method (LS-FDTD) for using time steps beyond FDTD CFL limit. [69] |
When Maxwell's differential equations are examined, it can be seen that the change in the E-field in time (the time derivative) is dependent on the change in the H-field across space (the curl). This results in the basic FDTD time-stepping relation that, at any point in space, the updated value of the E-field in time is dependent on the stored value of the E-field and the numerical curl of the local distribution of the H-field in space. [2]
The H-field is time-stepped in a similar manner. At any point in space, the updated value of the H-field in time is dependent on the stored value of the H-field and the numerical curl of the local distribution of the E-field in space. Iterating the E-field and H-field updates results in a marching-in-time process wherein sampled-data analogs of the continuous electromagnetic waves under consideration propagate in a numerical grid stored in the computer memory.
This description holds true for 1-D, 2-D, and 3-D FDTD techniques. When multiple dimensions are considered, calculating the numerical curl can become complicated. Kane Yee's seminal 1966 paper proposed spatially staggering the vector components of the E-field and H-field about rectangular unit cells of a Cartesian computational grid so that each E-field vector component is located midway between a pair of H-field vector components, and conversely. [2] This scheme, now known as a Yee lattice, has proven to be very robust, and remains at the core of many current FDTD software constructs.
Furthermore, Yee proposed a leapfrog scheme for marching in time wherein the E-field and H-field updates are staggered so that E-field updates are conducted midway during each time-step between successive H-field updates, and conversely. [2] On the plus side, this explicit time-stepping scheme avoids the need to solve simultaneous equations, and furthermore yields dissipation-free numerical wave propagation. On the minus side, this scheme mandates an upper bound on the time-step to ensure numerical stability. [9] As a result, certain classes of simulations can require many thousands of time-steps for completion.
To implement an FDTD solution of Maxwell's equations, a computational domain must first be established. The computational domain is simply the physical region over which the simulation will be performed. The E and H fields are determined at every point in space within that computational domain. The material of each cell within the computational domain must be specified. Typically, the material is either free-space (air), metal, or dielectric. Any material can be used as long as the permeability, permittivity, and conductivity are specified.
The permittivity of dispersive materials in tabular form cannot be directly substituted into the FDTD scheme. Instead, it can be approximated using multiple Debye, Drude, Lorentz or critical point terms. This approximation can be obtained using open fitting programs [70] and does not necessarily have physical meaning.
Once the computational domain and the grid materials are established, a source is specified. The source can be current on a wire, applied electric field or impinging plane wave. In the last case FDTD can be used to simulate light scattering from arbitrary shaped objects, planar periodic structures at various incident angles, [71] [72] and photonic band structure of infinite periodic structures. [73] [74]
Since the E and H fields are determined directly, the output of the simulation is usually the E or H field at a point or a series of points within the computational domain. The simulation evolves the E and H fields forward in time.
Processing may be done on the E and H fields returned by the simulation. Data processing may also occur while the simulation is ongoing.
While the FDTD technique computes electromagnetic fields within a compact spatial region, scattered and/or radiated far fields can be obtained via near-to-far-field transformations. [14]
Every modeling technique has strengths and weaknesses, and the FDTD method is no different.
The most commonly used grid truncation techniques for open-region FDTD modeling problems are the Mur absorbing boundary condition (ABC), [13] the Liao ABC, [16] and various perfectly matched layer (PML) formulations. [4] [43] [42] [47] The Mur and Liao techniques are simpler than PML. However, PML (which is technically an absorbing region rather than a boundary condition per se) can provide orders-of-magnitude lower reflections. The PML concept was introduced by J.-P. Berenger in a seminal 1994 paper in the Journal of Computational Physics. [42] Since 1994, Berenger's original split-field implementation has been modified and extended to the uniaxial PML (UPML), the convolutional PML (CPML), and the higher-order PML. The latter two PML formulations have increased ability to absorb evanescent waves, and therefore can in principle be placed closer to a simulated scattering or radiating structure than Berenger's original formulation.
To reduce undesired numerical reflection from the PML additional back absorbing layers technique can be used. [76]
 | This section possibly contains original research .(August 2013) |
Notwithstanding both the general increase in academic publication throughput during the same period and the overall expansion of interest in all Computational electromagnetics (CEM) techniques, there are seven primary reasons for the tremendous expansion of interest in FDTD computational solution approaches for Maxwell's equations:
Taflove has argued that these factors combine to suggest that FDTD will remain one of the dominant computational electrodynamics techniques (as well as potentially other multiphysics problems). [4]
The following article in Nature Milestones: Photons illustrates the historical significance of the FDTD method as related to Maxwell's equations:
Allen Taflove's interview, "Numerical Solution," in the January 2015 focus issue of Nature Photonics honoring the 150th anniversary of the publication of Maxwell's equations. This interview touches on how the development of FDTD ties into the century and one-half history of Maxwell's theory of electrodynamics:
The following university-level textbooks provide a good general introduction to the FDTD method:
Free software/Open-source software FDTD projects:
Freeware/Closed source FDTD projects (some not for commercial use):