1. Introduction
During the last few decades, semiconductor devices have triggered a significant level of interest, due to the wide variety of applications in which they are used, such as systems associated with communications, remote sensing, and optical computing [
1–3
H. P. Sardesai and A. P. Weiner, “Nonlinear fiber-optic receiver for ultra short pulse code division multiple access communications,” IEEE Electron. Lett.
33, 610–611 (1997). [CrossRef]
]. Most current simulation models for such devices lack the ability to accurately simulate the physics within a gain or absorbing region since they are based on the known macroscopic and phenomenological models. Recently, Amit and Robert
4 and Ziolkowski
5 have accurately simulated the electromagnetic interactions in a dispersive and nonlinear medium by incorporating macroscopic polarization into Maxwell’s equations, where the quantum mechanical effects and time-domain dynamics of the atomic populations are governed by rate equations. In fact, their two-level or four-level atom models can be considered as Lorentz models. However, for most semiconductor materials, the spectral broadening of transition of the photons has to be taken into account. In this case the single Lorentz model is no longer valid and an alternative model must be used.
In this paper we present such a method and begin with the semi-classical density matrix theory [
6
M. Sargent, M. O. Scully, and W. E. lamb, Laser Physics (Addison-Wesley, Reading, MA, 1974).
,
7
A. Yariv, Quantum Electronics , 3rd ed. (Wiley, New York, 1989).
] to derive the quantum mechanical descriptions of the semiconductor medium. Such physical models incorporate all propagation effects so that an associated macroscopic susceptibility can be derived. We then couple Maxwell’s equations with the induced polarization to numerically solve the quantum well medium. Usually, the susceptibility of quantum well is very complex due to the complicated conduction and valence band structures, which bring about the invalidity of the single Lorentz model in such materials. In addition, when the injection current increases, the response of the susceptibility and change are no longer linear. So, the key point is to accurately describe the susceptibility. In our model, we use the Fourier transformation to derive the time response of the susceptibility. Then the Prony’s method [
8
F. B. Hildebrand, Introduction to Numerical Analysis (Dover, New York, 1974).
] is applied to approximate it with a superposition of exponential series so that the susceptibility of a quantum well can be expressed as a superposition of multiple Lorentz-like models. Using the inverse Fourier transform one can derive the time-domain response. In this way, each term of multiple Lorentz-like models can be solved using FDTD technique, as we show.
Accordingly, the remainder of the paper is organized as follows: In Sec. II, based on the semi-classical density-matrix theory, the microscopic susceptibility in semiconductor structure is obtained. Then, multiple Lorentz-like models are derived using the Prony’s method. In Sec. III, the FDTD method is applied to numerically solve the quantum well structure, and the numerical results are provided in Sec. IV. Finally, a conclusion and summary are presented in Sec. V.
2. Macroscopic susceptibility
Based on the semi-classical density matrix theory, we consider a two-level system of semiconductor medium with a rigorous
k selection rule applied to the recombining electron-hole pairs, the band structure of which is shown in
Fig. 1. In this case, the density-matrix equations can be written in terms of the distribution (occupation) functions for electrons
fe
and holes
fh
, in the presence of an optical field
E(
t), as
where “*” stands for the complex conjugate, and
and
Fig. 1. Band structure of the semiconductor.
are the quasi-Fermi distributions that the electrons and the holes tend to relax to in the presence of the optical field perturbation,
ħ is Plank’s constant /2
π ,
τe
and
τh
are the intraband relaxation time of the electrons in conduction band and holes in valence band, respectively.
Ee
(
k) and
Eh
(
k) are the energies of the electron and hole with wave vector
k, respectively.
Fe
and
Fh
are quasi-Fermi energy levels for electrons and holes, respectively, and
ρeh
(
k) is off-diagonal (electron-hole) density matrix element,
Ek
is possible transition energy of a electron-hole pair with wave vector
k,
T
2 is the intraband dephasing time and
γ is the dipole moment matrix element.
(
k) and
(
k) are implicitly dependent on the optical and injection current in the semiconductor region. The steady-state solution of Eqs. (
1) and (
2) can be written as
where
L(
ħω-
Ek
) =
E
2
T
2
/[
E
2
T
2
+ (
ħω -
Ek
)
2] is the Lorentz (broadening) function,
E
T
2
=
ħ/
T
2 is the space average photon density inside the active region,
Is
= ħ
2
ε
0
n
2/
γ
2
E(
τe
+
τh
)
T
2 is the saturation photon density, and
n is the model refractive index.
fe
(
k) and
fh
(
k) are the nonlinear function of the presence field or average photon density. Under the small signal approximation, in which the photon density is very small compared with saturation density, the second terms in Eq. (
6) and Eq. (
7) can be omitted, thus
fe
(
k) and
fh
(
k) can be simplified to
(
k) and
(
k), respectively. In this case, by performing the Fourier transform, the solution of Eq. (
3) is
where “⊗” stands for convolution. As is well known, the induced polarization can be written quantum mechanically as
or classically as
where
χ is the macroscopic susceptibility. From Eq. (
9) and Eq. (
10), we obtain the expression in frequency domain as
Combine Eq. (
11) with Eq. (
6)–Eq. (
8), the susceptibility can be derived as
In this case, V stands for the volume of the active medium region. Please be advised that this is valid for small signal intensities and slowly varying pulses.
Next, we consider a quasi-two-dimensional (2D) system for the movement of the charge carriers in the quantum well (QW) semiconductor. [
9
D. Kasemset, C. S. Hong, N. B. Patel, and P. D. Dapkus, “Graded barrier single quantum well lasers-theory and experiment,” IEEE J. Quantum Electron.
19, 1025–1030 (1983). [CrossRef]
] In the horizontal plane (
x, y plane) of the QW, the movement remains unrestricted; in the vertical dimension
z, it is confined. The density of states in such a system is obtained from the energy levels
En
(
n = 1,2,⋯) of the quantized dimension
z, each forming a subband
n with respect to the free
x, y movement. The 2D density of states
D(
E'} , i.e., the available states per unit area and unit energy, can be written as the sum over the step-like density of states functions of each individual subband. [
10
R. Dingle and I. Festkorperprobleme, Advances in solid state physics (Braunschweig, Pergamon-Vieweg).
]
where H is the Heaviside unit step function, mn
is the effective mass in the n
th 2D sub-band
with respect to the x, y movement, dz
is the thickness of quantum well structure. The energy E' is measured from the band edge of the bulk semiconductor into the band. The quasi-Fermi levels of the electrons and holes can represent the injection level, and, the quasi-Fermi levels for electrons and holes are related through the charge neutrality condition. In the valence band, there are usually two branch holes, namely, the heavy (h) and light (l) holes. As a result of the conservation of in-plane momentum kx,y
and confinement quantum number n during a dipole transition of injected electrons from conduction to the valence bands, the 2D density of states functions of the two sub-bands with same n can be combined to form a reduced 2D density of states describing the dipoles of energy E' = ħω between the electron and the respective hole; i.e.,
where the effective mass
mn
in Eq. (
20) is replaced by reduced effective mass,
and
is the gap between the subband pair en
~ ihn
. The linear susceptibility χ can be rewritten as
The square of transition matrix elements in the QW structures generally can be written as [
11
P. S. Zory, “Quantum Well Lasers,” (Academic Press INC, CA, 1993).
]
where δi is defined as the polarization modification factor, and is the square of the transition matrix element given by :
in which
ξ is the Matrix element prefactor [
12
N. K. Dutta, “Calculated threshold current of GaAs quantum well lasers.,” J. Appl. Phy.
53, 7211–7214 (1983). [CrossRef]
], for GaAs
ξ is 2.66. The polarization modification factor in the QW provides an enhancement of the oscillator strength for TE polarization at photon energies near the gain peak as opposed to TM polarization, where the oscillator strength is diminished. Thus, for a QW structure, stability of lasing in the TE mode is improved further, and TM polarization need not be considered. The TE polarization modification factors for the e-hh and e-lh transitions, respectively, are:
With the modified matrix element, the susceptibility eventually becomes
The energy levels in the quantum well structures in the
z direction can be obtained by solving the Schrodinger equation for a one-dimensional potential well, the following eigenvalue equations are obtained [
11
P. S. Zory, “Quantum Well Lasers,” (Academic Press INC, CA, 1993).
],
where V
0 is the depth of the potential well and m is the effective mass. The eigenvalue equation can be numerically solved to yield the energy levels En
in a potential well.
3. Auxiliary differential equation Finite-Difference Time-Domain (ADE-FDTD) method
In the last section, we obtain the macroscopic susceptibility of semiconductor material based on the semi-classical density matrix theory, thus, the induced polarization can be incorporated into the Maxwell’s equations. In general, the material is dispersive and nonlinear due to the transitions and combinations of electrons and holes. Under the small signal approximation the material becomes linear, as a result we only need consider it as a dispersive material. Once the induced polarization of such a material is determined, we can then apply numerical techniques to simulate the wave propagation in the corresponding gain or absorbing medium. To further simplify the algorithm, we instead use induced polarization, where we derive an equivalent conductivity for the quantum well medium to incorporate into the Maxwell’s equations.
As is well known, the FDTD method has become one of the more widely used numerical techniques for solving electromagnetic boundary value problems due to its reduced memory requirements and its simplicity of implementation. In short, the FDTD method directly discretize Maxwell’s equations in both time and space by using central difference technique, and iteratively updates the electrical and magnetic field components at all points in the computational space using the leapfrog fashion. The material parameters of the medium are also incorporated in the computation. To this end, the method is able to easily deal with the interactions between electromagnetic fields and objects having complex shape and/or inhomogeneous media.
Over the past several years, a number of different methods have been proposed to account for material dispersion with absorption and gain using the FDTD method. These include recursive convolution (RC) methods [
13
R. J. Luebbers and F. Hunsberger, “FDTD for Nth-order dispersive media,” IEEE Trans. Antennas Propag.
40, 1279–1301 (1992). [CrossRef]
,
14
D. F. Kelley and R. J. Luebbers, “Piecewise linear recursive convolution for dispersive media using FDTD,” IEEE Trans. Antennas Propag.
44, 792–797 (1996). [CrossRef]
] that implement a discretized convolution of the dispersion relation, ADE methods that discretize a differential equation obtained from the relevant constitutive relations, and
Z-transform methods [
15
D. M. Sullivan, “Frequency-dependent FDTD methods using Z transforms,” IEEE Trans. Antennas Propag.
40, 1223–1230 (1992). [CrossRef]
] based on digital processing techniques. Although the RC method can be easily implemented, it needs the entire field history to implement the convolution, and the convolution involves a very demanding computer burden. As a result, we choose an alternative method, namely the ADE method to solve the problem.
In general, Maxwell’s equations within the quantum well medium can be written in the
form
where P is the induced polarization. For simplicity, we considered here only a one-dimensional problem with field components Ex
and Hy
propagating along z direction through a nonmagnetic, isotropic medium. In this case, the above equations reduced to:
where the polarization
P(
t) is defined in Eq. (
10). Also, the susceptibility
χ(
t)in the time domain can be obtained by performing the Fourier transform on Eq. (
17), which is given by:
where
ωT
= 2
π/
T
2 and
U(
t) is the unit step function. From Eq. (
25), since
χ(
t) is implicit function of
t, the derivative of
P(
t) with respect to
t can be performed analytically. To this end, we introduce the polarization current density
J(
t) to replace the
P(
t),
The corresponding frequency field form is J(ω) = σ(ω)E(ω). The equivalent conductivity σ(t) can be derived from as,
Obviously, the response of conductivity σ(t) is very complex due to the presence of the quantum well. One reason for this is that, at the higher excitation of the quantum well medium, the transitions involving the second subband can be very important, so that a spectrum with two peaks may appear. Another reason is that the semiconductor medium is constructed by collecting two-level atoms with a range of transition frequencies, which is similar to an inhomogeneous broadened two-level system. As a result, it involves multiple oscillators.
Once we have known the time domain response of σ(t), the ADE method is applied. To
do so, we reformulate the frequency dependent conductivity function. It is well known that if the time domain σ(t) can be approximated by a sum of complex exponential functions, one can use the highly efficient auxiliary differential equation. Thus, by using Prony’s method it is possible to set up the complex exponentials:
in which αi
is damping factor of the i-th mode, ωi
is the resonant frequency of the i-th mode, and P is the order of the model. Usually there are polarization pole pairs, therefore, in frequency domain,
where Ai
+ jBi
= Ci
. Using Prony’s method, we record N equally spaced time samples of σ(N) in the time domain and set up the following N-p equations:
Solving this set of equations for El
permits the Dl
to be found as the roots of the polynomial
The next step is to find the
Cl
in Eq. (
28). This is accomplished by writing out Eq. (
28) for each of the time samples, thereby obtaining a set of
N equations:
Once Cl
and Dl
are solved, the αi
, ωi
, Ai
and Bi
can be found. Then the polarization electric current density can be expressed as the superposition of multiple polarization current components
By performing an inverse Fourier transform of each term in the above equation, we have
The above equations are required ADEs for the equivalent induced current
J (
t). This can be easily and accurately implemented using the FDTD method. The electromagnetic field components and induced electric currents are shown in the grid as indicated in
Fig. 2.
Fig. 2. FDTD grid sketch map
Using the central difference expression, we can discretize Eq. (
24) and Eq. (
35), in which the electric field is centered at time-step
n+1/2, and magnetic field and polarization current are centered at time-step
n. They are given by
Thus, ADE-FDTD algorithm can be used to model a dispersive medium with P pairs Lorentz pole. The reformulated ADE method eliminates the requirement to solve for the field history, and, it needs a smaller number of unknowns to store than the RC method. In the following section, we present a few of examples to illustrate the utility of the proposed algorithm.