Abstract
A fourthorder RungeKutta in the interaction picture (RK4IP) method is presented for solving the coupled nonlinear Schrdinger equation (CNLSE) that governs the light propagation in optical fibers with randomly varying birefringence. The computational error of RK4IP is caused by the fourthorder RungeKutta algorithm, better than the splitstep approximation limited by the step size. As a result, the step size of RK4IP can have the same order of magnitude as the dispersion length and/or the nonlinear length of the fiber, provided the birefringence effect is small. For communication fibers with random birefringence, the step size of RK4IP can be orders of magnitude larger than the correlation length and the beating length of the fibers, depending on the interaction between linear and nonlinear effects. Our approach can be applied to the fibers having the general form of local birefringence and treat the Kerr nonlinearity without approximation. For the systems with realistic parameters, the RK4IP results are consistent with those using ManakovPMD approximation [1, 2, 3]. However, increased interaction between the linear and nonlinear terms in CNLSE leads to increased discrepancy between RK4IP and ManakovPMD approximation.
A fourthorder RungeKutta in the interaction picture method for coupled nonlinear Schrdinger equation
Zhongxi Zhang, Liang Chen, Xiaoyi Bao
Department of Physics, university of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5, Ontario, Canada
zzhan3@uottawa.ca
References and links
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Appendix A Introduction
In optical communication fibers, polarizationmode dispersion (PMD, i.e., group birefringence), chromatic dispersion (CD), and Kerr nonlinearity are the well known effects causing signal distortion. In linear region (i. e., without Kerr nonlinearity), the signal distortion due to PMD and CD can be predicted and compensated. On the other hand, in the limit of pure nonlinear effect (i.e., without linear effects such as PMD and CD), the signal amplitude will not be affected and the pulse shape will be unchanged along the fiber. Unfortunately both linear and nonlinear effects in real fibers are not negligible. To accurately evaluate the signal distortion, one must treat them simultaneously [1][5] by solving the coupled nonlinear Schrdinger equation (CNLSE), which was proposed in 1980’s [6] and further studied in many publications.
For a nonsoliton system, the CNLSE is solved with the step size determined by dispersion length , nonlinear length , as well as the birefringence related parameters such as fiber correlation length () (the length within which birefringence axes are randomly reoriented), beating length (the length determined by birefringence strength), and the PMD parameter (ps/) [1][3]. Ignoring the birefringence effect, the two dimensional (2D) CNLSE can be reduced to one dimensional nonlinear Schrdinger equation (1D NLSE), with its step size being only related with and . To efficiently solve the 2D CNLSE and 1D NLSE, various approaches have been proposed (cf. Refs. [1][15] and the references therein).
In optical communication fibers, the values of (10100 m) and (0.3300 m) are much smaller than and (up to hundreds of kilometers) [1, 2, 3]. Dealing with the rapidly and randomly varying birefringence in the multispan communication fibers, decreasing the computational step size to a very small percentage of and not only needs too much computation but also cannot ensure good enough accuracy because of the computational error accumulated in all steps. To efficiently solve the CNLSE, one needs an accurate approach (or algorithm) with large enough step size.
In Ref. [2], a coordinate system rotating with the principal axes in each wave plate was introduced to get the analytical solutions for the linear and nonlinear effects in CNLSE. As a result, the computational step size using the approach of Ref. [2] can be increased to a scale significantly larger than and . (Detailed value of its step size depends on the interaction between linear and nonlinear effects.) Requirements for this approach are that the circular component of the local birefringence in the fiber is negligible and that the nonlinear Kerr effect can be approximated as its statistical average over the Poincar sphere (named ManakovPMD approximation or MPMD approx in this work). Like many approaches used to solve 2D CNLSE or 1D NLSE, another essential feature of Ref. [2] is that it needs splitstep Fourier method (SSFM), which is based on the first order approximation of BakerHausdorff formula [16]
(1) 
where . Because of this, even in the case of zero birefringence, the step size using approach [2] is restricted to of and/or , assuming the computational error tolerance is less than 1 of the pulse peak (cf. the results in D.2).
The concept of interaction picture (IP) was originally used in quantum mechanics. Combined with the fourthorder RungeKutta (RK4) algorithm, the method of RK4 in IP (RK4IP) was recently proposed to study the supercontinuum generation in optical fibers (for 1D field cases) [15]. Since the IP method does not introduce the error inherent in various SSFMs, the computational error of RK4IP is determined by the accuracy of RK4.
The approach of Ref. [15] cannot be applied directly to the cases with random birefringence, because in Ref. [15] the linear dispersion operator in 1D NLSE was required to be constant along the fiber. Motivated by the analytical solution for the linear terms in CNLSE, which was proposed in Ref. [2] and is further discussed in the Appendix for our calculation, we extend the RK4IP approach from 1D NLSE to 2D CNLSE.
As there is no need to rotate the coordinate system, our approach can be applied to the fibers having the general form of local birefringence. Moreover, it treats the Kerr nonlinearity without approximation. With the help of the local error method proposed in [12], the local error of our RK4IP can be improved to , rather than of 1D RK4IP [15]. As results, for the communication fibers with random birefringence, the step size using RK4IP can be orders of magnitude larger than and . Without birefringence, the step size of RK4IP can be the same order of magnitude as and/or , or, times the step size using the approach of Ref. [2].
In the parameter regime where communication fibers operate, our results are consistent with those using MPMD approx, which was used in many publications (cf. e.g., [1, 2, 3]). Increased interaction between the linear and nonlinear terms in CNLSE will lead to increased discrepancy between RK4IP and MPMD approx.
Appendix B From CNLSE to MPMD approx
b.1 CNLSE expressed in different forms
To deal with the birefringence related problem, it is convenient to represent a 2D optical field with Dirac bra or ket notation [17]. Namely, given a field with its components being and , it can be denoted as [or ]. Thus, the CNLSE discussed in [1, 2, 3] can be written in the following form with retarded time :
(2) 
or
(3) 
where , , and () is related to () with (), respectively [2]. Here is the PMD coefficient (ps/). The average DGD of a kmlong fiber can be obtained using DGD (ps). Obviously, the second term on the lefthand side of Eq. (3) represents the phase birefringence, while the third term relates to the group birefringence (or linear PMD).
In this work, the three components of the Pauli spin matrices are denoted as
(4) 
Generally, the birefringenceinduced matrix in (2) and (3) has the form of [3]
(5) 
with () and [] being, respectively, the unit vector representing the fiber birefringence in 2D Jones (3D Stokes) space [17]. For the fiber with circular birefringence (e.g., spun optical fiber), in (5).
Parameter corresponds to the CD parameter at wavelength by =CD (ps/nmkm) with c=310m/s.
b.2 MPMD approx
Eq. (3) can also be expressed as
(7) 
which was named ManakovPMD equation in Refs. [2, 3]. The last term on the lefthand side of (7) is the Kerr nonlinearity averaged over the Poincar sphere with the 8/9 factor [1, 2, 18]. The righthand side of (7) is the nonlinear PMD due to incomplete mixing on the Poincar sphere [2, 3]. Physically it corresponds the rapidly varying fluctuations as the polarization state changes [2].
In this work, the ManakovPMD approximation (MPMD approx) means that the variation of the second term on the righthand side of (7) is approximated by its statistical average over the Poincar sphere [the first term on the righthand side of (7)]. Thus, the righthand side of (7) is approximated as zero, yielding
(8) 
Without linear birefringence, MPMD approx (8) reduces to Manakov equation [1, 2, 18].
Appendix C RK4IP: extension from 1D to 2D
c.1 RK4IP solution for 1D NLSE
Without birefringence, Eq. (3) can be reduced to 1D NLSE
(9) 
which can be formally viewed as
(10) 
Introducing transformation , NLSE in the IP has the form [15]
(11) 
or
(12) 
with
(13) 
the nonlinear operator represented in the IP. Given , the next step field () governed by Eq. (11) can be obtained using RK4, with the local error of . Choosing can reduce the required FFTs by (compared to the choice of ), yielding [15]
(14) 
c.2 RK4IP solution for 2D CNLSE with random birefringence
Eq. (3) can also be viewed as
(15) 
Introducing the transformation , with the operator given by (27), the CNLSE (15) can be expressed in IP as
(16) 
Given (the 2D field at ), the next step field can be obtained from Eq. (16) by RK4. As in 1D case of Ref. [15], one can choose to minimize the required number of FFTs, which leads to
(17) 
where ,
(18) 
and can be obtained according to (27). Introduced in (27), in (18) is the index of the last plate, whereas the unitary matrix in (18) and its Hermitian (i.e., its selfadjoint matrix) satisfy . To order all in one direction, the indexes in [given in (18)] does not follow the ordering rule introduced in the Appendix. The minus sign in () is used to denote , where is the length of the th plate discussed in the Appendix. Thus we have . Obviously, when , (17) yields , which is consistent with (27) [or (22) and (24)] given in the Appendix.
Appendix D Applications and discussions
In the following numerical calculations, the input optical field is assumed to be a periodic repetition of bit (N=16) de Bruijn sequence, i.e., , where and is the time interval of each bit. Here determines the elementary input pulse shape and is the logic value of the th bit. Within the time interval [0, ], the elementary forms of RZ and NRZ pulses (or Marks) are assumed to be and , respectively, with the optical energy per transmitted bit [19, 20]. Outside this time interval, is zero. Obviously, is the mark power. To give the NRZ optical pulses slightly rounded edges, the input pulses are generated by passing through an input optical filter [2]. In this work, it is assumed to be fifthorder Bessel type with bandwidth .
In all simulations, the fiber loss has been neglected, implying that there are no optical amplifiers in the system and, consequently, no amplifier (ASE) noise.
Only OOK format is considered in this section. Before photodetection, the optical signal is assumed to be filtered by a FabryProt type channel filter with bandwidth [20, 21]. The squarelawdetected signal is then electrically filtered by a fifthorder Bessel filter with bandwidth [3, 21, 22]. In the following figures, the electrically filtered photoelectric pulses are represented in units of W, since detected current corresponds to optical power [2].
In our computation, the approach of adaptive step size is used. Namely, given step size , one can use RK4IP (17) to obtain (the fine solution at ) and (the coarse solution at ) from (the obtained solution at ). Similarly, based on , the second fine solution can be obtained. Then the next step size can be adjusted, depending on the difference between and . According to Ref.[12], the local error of RK4IP can be improved from [15] to by using .
d.1 RK4IP and SSFM comparison: zero birefringence

Without birefringence, 2D CNLSE (3) can be reduced to 1D NLSE (9) with its splitstep solution being ()
(19) 
where is the Fourier transformation of , while denotes inverse Fourier transformation. Note that, in the case of zero birefringence, the SSFM result of Ref. [2] can be reduced to (19).
Obviously, (19) should yield the same result as the RK4IP solution (17) (without birefringence). This is numerically confirmed by considering a NRZOOK pulse train launched into the fiber with CD=17 ps/(nmkm) and =80m [=1.26 (Wkm)]. The bandwidths of the electrical filter and the input optical filter are G and . The input mark power is 20 mW for L=100 km (a) and 2 mW for L=500 km (b). As shown in Fig. 1, the results of RK4IP without birefringence agrees very well with those using SSFM (19).
d.2 Step size of RK4IP
Here, the step size means that, within given computational error tolerance ( of the pulse peak), the maximum allowable step size at the end of the fiber.
Table 1. Step size using RK4IP and SSFM of Ref. [2] obtained with given L and fiber length L. The dispersion length L km and the computational accuracy of the pulse peak.
random birefringence  no  birefringence  

RK4IP  RK4IP  SSFM of [2]  
(Lkm, L=100 km)  7 km  30 km  3 km 
(Lkm, L=500 km)  45 km  250km  40 km 
Table 1 shows the step sizes using RK4IP for the fibers of Fig. 1 (a) and (b) with random birefringence [ =50m, =10m, and =1.0ps/(km), yielding average DGD22ps], compared with the step size using RK4IP (without birefringence) and the step size using (19), which is the SSFM of Ref. [2] in the case of zero birefringence. Notice that the fiber dispersion length ( is the signal bandwidth) for the two cases of Fig. 1 is km, while the nonlinear length is 40 km for the case of Fig. 1 (a) and 400 km for (b).
In each case of zero birefringence, the RK4IP step size is around the smaller one of L and L, or, about 610 times of the step size of SSFM of Ref. [2], which is around of L and/or L.
Taking into account random birefringence, the RK4IP step size is decreased from 30km to 7 km for the case of L km (L=100km) and from 250 km to 45km for L km (L=500km). In general, the stronger the interaction between the linear and nonlinear parts in CNLSE, the more impact of and on the step size, assuming that and are much larger than the former. (For the same reason, the step size of approach [2] also needs to be decreased correspondingly.)
d.3 RK4IP solutions and MPMD approximations with random birefringence

Fig. 2 shows good agreement between RK4IP result and MPMD approx for a NRZOOK system with 5 100km spans of transmission fiber and 5 13km spans of dispersion compensation fiber. To get the received photoelectric pulses shown in Fig. 2, a precompensation fiber (6 km) is inserted before the first 100km fiber, whereas the last compensation fiber is 5 km long. The birefringence related parameters are m, =10 m, and =2.0 ps/(km), which means average DGD is around 2.047 ps with the birefringence direction being randomly changed every 10 m. As in D.1, the input optical filter with bandwidth of is used to generate rounded edges for NRZ signal. Other paratemeters given in the caption of Fig. 2 are based on the discussion of Ref. [3]. As plotted in Fig. 2, there is no significant difference between the RK4IP solution (17) and the MPMD approx (8). To confirm that such agreement is not because of the weak enough nonlinearity, one can increase the nonlinear coefficient in (8) from /(Wkm) to /(Wkm) for the transmission fibers and from /(Wkm) to /(Wkm) for the compensation fibers. Our result shows that the discrepancy between the two approximations can be more than 20 (not plotted in Fig. 2).


Fig. 3 shows the RK4IP solution and MPMD approx for a RZOOK system using 50 100km spans of eLEAF fiber [21], with effective mode area being =72 m and CD in the range of ps/(kmnm). To get the received photoelectric pulse shown in Fig. 3, each 100km fiber with CD=4.5ps/(kmnm) is followed by 429 ps/nm compensation. Also, precompensation of 117 ps/nm before the first 100km fiber and last compensation of 234 ps/nm after the 50th 100km fiber are used. The birefringence related parameters are m and m. As shown in Fig. 3, the agreement between the RK4IP solution and MPMD approx is not as good as that of Fig. 2. Considering that, due to the linearnonlinear interaction accumulated in such 50 100km fibers, any small change in the related parameters will lead to significant change in received pulse shape, the MPMD approx (dotdashed) in Fig. 3 can be viewed as a reasonably good approximation of the CNLSE solution obtained using RK4IP (dashed).
Appendix E Summary
Based on the RK4IP method for 1D NLSE [15] as well as the analytical solution for the linear terms in CNLSE [2], RK4IP method for 2D CNLSE is presented in this work. Without rotating the coordinate system for each step, our approach can be applied to a fiber with general form of birefringence. Besides, the Kerr nonlinearity in the CNLSE is treated without approximation. Since there is no splitstep approximation for each step and the local error method of Ref. [12] is used, for normal fibers with random birefringence, the step size using RK4IP can be orders of magnitude larger than and , depending on the intensity of the linearnonlinear interaction. Without birefringence effect, the RK4IP step size can be increased to the same order of magnitude as and/or , or, around times the step size using the approach of Ref. [2].
In the parameter regime where communication fibers normally operate, our results are consistent well with the results using MPMD approx (8) [1, 2, 3]. Increased interaction between the linear and nonlinear terms in the CNLSE will lead to increased discrepancy between RK4IP solution and MPMD approx.
Acknowledgment
The authors acknowledge the financial support from Canadian funding agencies: NSERC.
Appendix: Optical field in the fiber without nonlinearity
For a system with , Eq. (3) can be reduced to
(20) 
In frequency domain, Eq. (20) can be simplified as
(21) 
where . (Note that in Ref. [2], the Fourier transformation was defined to be .)
Assuming
(22) 
Eq. (21) is equivalent to the following differential equation for the matrix [2]:
(23) 
The correct solution of (23) should be in the form of [2]
(24)  
(25) 
where . When , is the length of the th plate with its birefringence direction being represented by . In (24), is the number of the plates between and and the index denotes the th plate. The expression of given by (24) can also be extended to the case of , provided to notice that 1) for each plate, ; 2) () are ordered from to , i.e., is the first left plate of . [ In (25) is determined by the strengths of the phase birefringence () and the group birefringence (), which is assumed to be independent of in this work.]
Using a fixed coordinate system in our approach, the result of (24) can be simply obtained by algebra operations such as [17]
(26) 
Obviously, in time domain, the transform matrices in (22) have the form of ()
(27) 