A Generalized FDTD Method with Absorbing Boundary Condition for Solving a Time-Dependent Linear Schrodinger Equation

The Finite-Difference Time-Domain (FDTD) method is a well-known technique for the analysis of quantum devices. It solves a discretized Schrodinger equation in an iterative process. However, the method provides only a second-order accurate numerical solution and requires that the spatial grid size and time step should satisfy a very restricted condition in order to prevent the numerical solution from diverging. In this article, we present a generalized FDTD method with absorbing boundary condition for solving the one-dimensional (1D) time-dependent Schr?dinger equation and obtain a more relaxed condition for stability. The generalized FDTD scheme is tested by simulating a particle moving in free space and then hitting an energy potential. Numerical results coincide with those obtained based on the theoretical analysis.

• Schrodinger Equation; Absorbing Boundary; FDTD Method; Stability

1. Introduction

The 1D time-dependent linear Schrödinger equation, which is the basis of quantum mechanics [1,2], can be expressed as follows [3,4]:

where m is the mass of the particle (kg), J·sec is Planck’s constant, V is the potential (J), is a complex number, and The product of with its complex conjugate, indicates the probability of a particle being at spatial location x at time t.

It can be easily seen that the classic explicit two-level in time finite difference scheme, i.e.,

is unconditionally unstable, where is the approximation of. Here, and are the spatial grid size and time step, respectively, that denotes the set of all positive and negative integers, and is a second-order central difference operator such that

There are many numerical schemes developed for solving linear Schrödinger equations [1-33]. In particular, Sullivan [3] and Visscher [4] applied the finite-difference time-domain (FDTD) method, which is often employed in simulations of electromagnetic fields, to solve the above Schrödinger equation. The application of FDTD technique for the analysis of quantum devices is often called the FDTD-Q scheme, which can be described as follows [3].

The variable is first split into its real and imaginary components in order to avoid using complex numbers:

Inserting Equation (4) into Equation (1) and then separating the real and imaginary parts result in the following coupled set of equations:

,(5)

and

Thus, the second-order central finite difference approximations in space and time result in the FDTD-Q schemes as follows:

and

Here, we assume that V is dependent only on x for simplicity. The computation of the above FDTD-Q scheme is very simple and straight-forward because one may obtain from Equation (7) and then from Equation (8). Previously, the second author analyzed the stability of the FDTD-Q scheme using the discrete energy method and obtained a condition for determining the time step, , so that the scheme is stable as follows [13]:

where c is a constant. It should be pointed out that Soriano et al. [27] and Visscher [4] also used the eigenvalue method to analyze the stability of the FDTD-Q scheme and obtained a very similar condition of

However, as pointed out in [13], even if the condition is chosenthe numerical solution is still divergent. Equation (9) indicates that the condition must be less than 1 but not close to 1.

The motivation of this study is to apply the idea of the FDTD method to develop a generalized FDTD method with absorbing boundary condition for solving the linear Schrödinger equation, so that a more relaxed condition for stability may be obtained.

2. Generalized FDTD Method

To develop a generalized FDTD scheme, we assume that and are sufficiently smooth functions which vanish for sufficiently large and the potential V is dependent only on x. We first rewrite Equations (5) and (6) as

where and employ the Taylor series method to expand and at as follows:

We then evaluate those derivatives in Equation (12) by using Equations (10) and (11) repeatedly:

and so on. Substituting Equation (13) into Equation (12) gives

Similarly, we employ the Taylor series method to expand and at as follows:

Again, using Equations (10) and (11) repeatedly to evaluate those derivatives in Equation (15), we obtain

and so on. Substituting Equation (16) into Equation (15) gives

Thus, if and are approximated using some accurate finite differences, one may obtain a generalized FDTD scheme for solving the time-dependent linear Schrödinger equation as follows:

It should be pointed out that in Equation (18a) may be approximated by a higher-order accurate Lagrange polynomial or some other higher-order accurate approximations. Once is obtained from Equation (18a), one may construct a similar higherorder accurate Lagrange polynomial or some other higher-order accurate approximations for and then substitute it into Equation (18b) to obtain. Here, for simplicity, we limit ourselves to using finite difference approximations for the Laplace operator A. Furthermore, it can be seen from the above derivations that Equation (18) can be readily generalized to the multi-dimensional cases. For the case where the potential V is dependent on both temporal and spatial variables, the derivations are similar to those in Equation (16) except that the product rule of derivative with respect to t should be used.

3. Stability

In order to prevent the numerical solution from diverging, we need to analyze the stability of the generalized FDTD method in Equation (18). Here, we consider that the Laplace operator A is only approximated by either a second-order central difference operator or a fourth-order central difference operator, where

and similar finite difference approximations for . We assume that V is a constant and use the Von Neumann analysis [34] to analyze the stability of the generalized FDTD schemes. To this end, we first let and where and are amplification factors for and, respectively, and substitute them into Equation (19a). This gives

Replacing A with in Equation (18), substituting Equation (20) into the resulting equations, and then deleting the common factor, we obtain

where. Since Equation (21a) is true for any time level n, we rewrite Equation (21a) as

substract it by Equation (21a), and then use Equation (21b) to eliminate. As such, we obtain a quadratic equation for as follows:

where, Using the fact that for a quadratic equation the solution x satisfies if and only if and we obtain from Equation (23) that if and only if By the Von Neumann analysis, we conclude that the generalized FDTD scheme is stable if i.e.,

It can be seen that

implying that, when Equation (24) is automatically satisfied, and, hence, the scheme with, is unconditionally stable. However, we cannot choose and, therefore, the generalized FDTD scheme should be imposed the condition in Equation (24). Noting that the condition in Equation (24) gives only and does not indicate whether or not there is a double root with in Equation (23) (for this case, the numerical solution may still blow up), we choose the  

maximum value of and require

where c is a constant. Using a similar argument, we may obtain the same inequality as that in Equation (26) for Hence, we obtain the following theorem.

Theorem 1. The generalized FDTD scheme

is stable if Equation (26) is satisfied.

It can be seen that when N = 0 the condition in Equation (26) reduces to that in Equation (9). Also, the accuracy of the scheme is

Similarly, for the fourth-order central difference case, we let and  

and substitute them into Equation (19b). This gives

Replacing A with substituting Equation (28)

into Equation (18), and deleting the common factor we obtain a quadratic equation for as follows:

where

Hence, we use a similar argument as before and obtain the following theorem.

Theorem 2. The generalized FDTD scheme

is stable if the following condition is satisfied

where c is a constant.

The accuracy of the scheme is It can be seen from the above both schemes that for a larger N, the evaluation for powers of or can be very expansive. Therefore, it is our suggestion to choose a smaller N for computation.

4. Absorbing Boundary Condition

When the particle travels and hits the boundary, it will reflect back to the domain under consideration. This will distort the wave packet solution. It is ideal to create an absorbing boundary condition so that the particle will not reflect back. Here, we develop a second-order absorbing boundary condition (ABC) which is obtained from analyzing the group velocity of the wavepacket at the boundaries [15]. To this end, we assume group velocities of the traveling particle to be

where is the wavenumber and is the wavelength. By incorporating the dispersion relation derived from Equation (1), one may see that the wavenumber corresponds to. Thus, the differential form of the wavenumber can be obtained as

Since a wave maintains various components with different group velocities, we impose a higher-order boundary condition as follows:

It should be pointed out that for a wave traveling towards the left, and are substituted by and. It may be seen from Equations (33) and (34) that if does not equal the two different wave components with group velocities and will be absorbed, and on the other hand, if is equal to the component of the wave with group velocity (or) will be absorbed to the second order.

With Equations (5), (6) and (34), the wavefunctions at the left and right boundaries can be determined as

where

Here, the upper signs in Equation (35) apply to the left boundary, whereas the lower signs apply to the right. We then use the second-order finite difference schemes to approximate and at the left and right boundaries as follows, respectively,

and

Upon substituting Equations (37) and (38) into Equation (35), we obtain discrete absorbing boundary conditions as follows:

and

5. Numerical Examples

To test the stability of the generalized FDTD schemes in Equation (27) and Equation (30) with discrete absorbing boundary conditions, Equation (39), we employed the present schemes and the original FDTD scheme to simulate a particle moving in free space and then hitting an energy potential as tested in [3]. To this end, we initiated a particle at a wavelength of in a Gaussian envelop of width with the following two equations:

and

where is the center of the pulse. We chose a mesh of 1600 spatial grid points and the following values for parameters [3]: J×sec, kg, m, and m. Furthermore, V was chosen to be 0 in the first 800 grid points and 100 eV in the next 800 grid points.

Two quantities of importance in quantum mechanics are the expected values of the kinetic energy and the potential energy. They are calculated from and in the simulation as follows,

and

where and are evaluated using the fourth-order finite difference approximations:

and

Based on the above formula, the electron moves in free space and then hits an energy potential with a total energy of about 150 eV. The energy is purely kinetic due to the fact that there is no potential energy available before the energy barrier is reached. With an increase in time, the electron will propagate in the positive spatial direction. The waveform begins to spread, but the total kinetic energy remains constant. After the electron strikes the potential barrier, part of the energy will be converted to potential energy. The waveform indicates that there is some probability that the electron is reflected and some probability that it penetrates the potential barrier. However, the total energy should remain constant.  

In our computations, we chose N = 2 in Equation (27) and Equation (30), and let

where is a parameter used in [3]. Using Equation (43), we rewrite the conditions in Equation (26) and Equation (31) for N = 2 as

Figures 1 and 2 show the simulation of an electron moving in free space and then hitting a potential of 100 eV, which was obtained by using the original FDTD-Q scheme (N = 0) with μ = 0.46875. It can be seen that  

when μ = 0.46875 (in which

, the FDTD-Q scheme is stable and indeed the numerical solution does not diverge. Figure 1 shows that when the absorbing boundary condition is not imposed, the wavepacket is distorted at On the other hand, Figure 2 shows that the wavepacket disappears at when an absorbing boundary condition is imposed. Similar results

are obtained when we used the generalized FDTD scheme (N = 2) with μ = 0.46875.

It is noted that when μ = 0.5 the original FDTD-Q scheme produces a divergent solution, because

which violates the stability condition. Thus, we employed the generalized FDTD scheme, Equation (27) with N = 2 and Equation (30) with N = 2 for this case. It is noted that when μ = 0.5,

implying the stability condition Equation (26) is satisfied, and

implying the stability condition Equation (31) is satisfied.

Figures 3 and 4 show the simulation of an electron moving in free space and then hitting a potential of 100 eV, which was obtained using the generalized FDTD scheme,  

Equation (27) with N = 2 and μ = 0.5. It can be seen from Figure 3 that when the absorbing boundary condition is not imposed, the wavepacket is distorted at On the other hand, when an absorbing boundary condition is imposed, the wavepacket disappears at as shown in Figure 4.

Figures 5 and 6 show the simulation of an electron moving in free space and then hitting a potential of 100 eV, which was obtained using the generalized FDTD scheme, Equation (30) with N = 2 and μ = 0.5. Again, it can be seen from Figure 5 that when the absorbing boundary condition is not imposed, the wavepacket is distorted at On the other hand, when an absorbing boundary condition is imposed, the wavepacket disappears at as shown in Figure 6.

The above numerical example indicates that both generalized FDTD schemes break through the limitation (μ < 0.5) of the original FDTD-Q scheme. It should be pointed out that one may obtain a larger value of μ if N is chosen to be larger in the generalized FDTD scheme.

6. Conclusion

We have developed a generalized FDTD method with absorbing boundary condition for solving the 1D timedependent Schrödinger equation and obtain a more relaxed condition for stability when central difference

approximations are employed for spatial derivatives. Numerical results coincide with those obtained based on the theoretical analysis.  

7. Acknowledgements

The research was supported by a grant from the LaSPACE, Louisiana.

References

1. S. Brandt and H. D. Dahmen, “The Picture Book of Quantum Mechanics,” Springer Verlag, Berlin, 1995. doi:10.1007/978-1-4684-0233-9

2. D. J. Griffiths, “Introduction to Quantum Mechanics. Englewood Cliffs,” Prentice-Hall, NJ, 1995.

3. D. M. Sullivan, “Electromagnetic Simulation Using The FDTD Method,” IEEE Press. New York, 2000. doi:10.1109/9780470544518

4. P. B. Visscher, “A Fast Explicit Algorithm for the Time Dependent Schrodinger Equation,” Comput. Phys., Vol. 5, 1991, pp. 596-598. doi:10.1063/1.168415

5. A. Arnold, M. Ehrhardt and I. Sofronov, “Discrete Transparent Boundary Conditions for the Schr?dinger Equation: Fast Calculation, Approximation and Stability,” Communications in Mathematical Science, Vol. 1, 2003, pp. 501-556.

6. A. Askar and A. S. Cakmak, “Explicit Integration Method for the Time-Dependent Schr?dinger Equation,” J Chem Phys, Vol. 68, 1978, pp. 2794-2798. doi:10.1063/1.436072

7. W. Bao, S. Jin and P. Markowich, “On Time-Splitting Spectral Approximations for the Schr?dinger Equation in the Semiclassical Regime,” J Comput Phys, Vol. 26, 2005, pp. 487-524.

8. N. Carjan, M. Rizea and S. Strottman, “Efficient Numerical Solution of the Time-Dependent Schr?dinger Equation for Deep Tunneling,” Romanian Reports in Physics, Vol. 55, 2003, pp. 555-579.

9. T. F. Chan, D. Lee and L. Shen, “Stable Explicit Schemes for Equations of the Schr?dinger Type,” SIAM J Numer Anal, Vol. 23, 1986, pp. 274-281. doi:10.1137/0723019

10. H. Chen and B. D. Shizgal, “The Quadrature Discretization Method in the Solution of the Schr?dinger Equation,” J Chem, Vol. 24, 1998, pp. 321-343.

11. Z. Chen, J. Zhang and Z. Yu, “Solution of the Time-Dependent Schr?dinger Equation with Absorbing Boundary Conditions,” Journal of Semiconductors, Vol. 30, 2009, pp. 012001. doi:10.1088/1674-4926/30/1/012001

12. W. Dai, “An Unconditionally Stable Three-Level Explicit Difference Scheme for the Schr?dinger Equation with A Variable Coefficient,” SIAM J Numer Anal, Vol. 29, 1992, pp. 174-181. doi:10.1137/0729011

13. W. Dai, G. Li, R. Nassar and S. Su, “On the Stability of the FDTD Method for Solving A Time-Dependent Schr?dinger Equation,” Numer Methods Partial Differential Eq. Vol. 21, 2005, pp. 1140-1154. doi:10.1002/num.20082

14. S. Descomb and M. Thalhammer, “An Exact Local Error Representation of Exponential Operator Splitting Methods for Evolutionary Problems and Applications to Linear Schr?dinger Equations in the Semi-Classical Regime,” BIT Numer Math, Vol. 50, 2010, pp. 729-749.

15. T. Fevens and H. Jiang, “Absorbing boundary conditions for the Schr?dinger equation,” SIAM J Sci Comput, Vol. 21, 1999, pp. 255-282. doi:10.1137/S1064827594277053

16. F. Fujiwara, “FDTD-Q Analysis of a Mott Insulator Quantum Phase,” Ph.D. diss., University of Tokyo, Japan 2007.

17. H. Han, J. Jin and X. Wu, “A Finite-Difference Method for the One Dimensional Time Dependent Schr?dinger Equation on Unbounded Domain,” Computers and Mathematics with Applications, Vol. 50, 2005, pp. 1345-1362. doi:10.1016/j.camwa.2005.05.006

18. M. Hochbruuck and C. Lubich, “On Magnus Integrators for Time-Dependent Schr?dinger Equations,” SIAM J Numer Anal, Vol. 41, 2003, pp. 945-963.

19. B. Jazbi and M. Moini, “On the Numerical Solution of One Dimensional Schr?dinger Equation with Boundary Conditions Involving Fractional Differential Operators,” IUST International Journal of Engineering Science, Vol. 19, 2008, pp. 21-26.

20. Z. Kalogiratou, Th. Monovasilis and T. E. Simos, “Asymptotically Symplectic Integrators of 3rd and 4th Order for the Numerical Solution of the Schr?dinger Equation,” Computational Fluid and Solid Mechanics 2003, pp. 2012-2015.

21. K. S. Kunz and R. J. Luebbers, “The Finite Difference Time Domain Method for Electromagnetics,” CRC Press, Roca Raton, FL, 1993.

22. J. P. Kuska, “Absorbing Boundary Conditions for the Schr?dinger Equation On Finite Intervals,” Physical Review B, Vol. 46, 1992, pp. 5000-5003. doi:10.1103/PhysRevB.46.5000

23. J. Lo and B. D. Shizgal, “Spectral Convergence of the Quadrature Discretization Method in the Solution of the Schr?dinger and Fokker-Planck Equations: Comparison with Sinc Methods,” J Chem Phys, Vol. 125, 2006, pp. 194108. doi:10.1063/1.2378622

24. P. L. Nash and L.Y. Chen, “Efficient Finite Difference Solutions to the Time-Dependent Schr?dinger Equation,” J Comput Phys, Vol. 130, 1997, pp. 266-268. doi:10.1006/jcph.1996.5589

25. J. M. Sanz-Serna, “Methods for the Numerical Solution of the Schr?dinger Equation,” Math Comp, Vol. 43, 1984, pp. 21-27. doi:10.1090/S0025-5718-1984-0744922-X

26. T. Shibata, “Absorbing Boundary Conditions for Finite-Difference Time-Domain Calculation of the One-Dimensional Schr?dinger Equation,” Physical Review B, Vol. 42, 1991, pp. 6760-6763. doi:10.1103/PhysRevB.43.6760

27. A. Soriano, E. A. Navarro, J. A. Porti and V. Such, “Analysis of the Finite Difference Time Domain Technique to Solve the Schr?dinger Equation for Quantum Devices,” Journal of Applied Physics, Vol. 95, 2004, pp. 8011-8018. doi:10.1063/1.1753661

28. M. Stricklans and D. Yager-Elorriaga, “A Parallel Algorithm for Solving the 3D Schr?dinger Equation,” arXiv.0904.0939v4 4 June 2010.

29. D. M. Sullivan and D. S. Citrin, “Time-domain Simulation of Two Electrons in A Quantum Dot,” Journal of Applied Physics, Vol. 89, 2001, pp. 3841-3846. doi:10.1063/1.1352559

30. D. M. Sullivan and D. S. Citrin, “Time-domain Simulation of A Universal Quantum Gate,” Journal of Applied Physics Vol. 96, 2002, pp. 3219-3226. doi:10.1063/1.1445277

31. J. Szeftel, “Design of Absorbing Boundary Condition for Schr?dinger Equations in Rd,” SIAM J Numer Anal Vol. 42, 2004, pp. 1527-1551. doi:10.1137/S0036142902418345

32. A. Taflove, Computational Electrodynamics: The Finite-Difference Time-Domain,” Artech House, Boston, 1995.

33. L. Wu, “Dufort-Frankel-Type Methods for Linear and Nonlinear Schr?dinger Equations,” SIAM J Numer Anal, Vol. 33, 1996, pp. 1526-1533. doi:10.1137/S0036142994270636

34. K. W. Morton and D. F. Mayers, “Numerical Solution of Partial Differential Equations,” Cambridge University Press, London, 1994.