CN113190979B - Neural network-based optical fiber vortex mode engineering method - Google Patents
Neural network-based optical fiber vortex mode engineering method Download PDFInfo
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Abstract
The invention discloses a method for optical fiber vortex mode engineering based on a neural network, and belongs to the field of optical fiber communication. The optical fiber vortex mode performance parameters corresponding to the vortex annular optical fiber structure parameters are obtained through numerical simulation, a complex functional relation between the optical fiber vortex mode performance parameters and the vortex annular optical fiber structure parameters is constructed by utilizing a neural network, the optical fiber vortex mode performance parameters are taken as input, the vortex annular optical fiber structure parameters are taken as output, and a neural network model is trained, tested and verified. And inputting the performance parameters of the vortex mode of the target optical fiber into a neural network model to predict the required structural parameters of the vortex annular optical fiber, thereby realizing the optical fiber vortex mode engineering based on the neural network. The invention breaks through the limitation of the traditional vortex optical fiber design method and the bottleneck of vortex mode regulation, provides an optical fiber vortex mode engineering with a brand new thought similar to the optical fiber dispersion engineering, has wide application prospect in the field of vortex mode space division multiplexing systems, and fills the blank of the related technical field.
Description
Technical Field
The invention belongs to the field of optical fiber communication, in particular to an optical fiber dispersion engineering similar to an optical fiber communication technology, and relates to a method based on optical fiber vortex mode engineering of a neural network.
Background
The widespread use of emerging high-speed data communication services has created tremendous data transfer, which places higher capacity demands on future communication technologies. In recent years, wavelength division multiplexing, polarization multiplexing, time division multiplexing, and space division multiplexing techniques have been widely studied for solving the channel capacity crisis of transmission systems. Space division multiplexing, among others, increases channel capacity by increasing the number of spatially parallel channels, and still remains to be developed and utilized in depth. The optical vortex mode multiplexing technology carrying the orbital angular momentum is a very promising space division multiplexing technology, and provides a brand new solution for increasing the bandwidth and capacity of optical communication. The design and development of the optical fiber supporting the optical vortex mode transmission are one of the key problems of the optical vortex mode multiplexing technology, and the annular optical fiber is a special design optical fiber capable of supporting the multichannel optical vortex mode transmission. In the optical fiber mode multiplexing transmission process, mode group delay, mode crosstalk and mode quantity are important factors influencing the multiplexing communication performance of the optical fiber mode, and in the application scene of combining the mode division multiplexing with the wavelength division multiplexing, the wavelength bandwidth is also a key factor influencing the multiplexing communication performance. For an application scenario that a receiving end needs a multiple-input multiple-output digital signal processing (MIMO-DSP) technology to compensate for the influence of mode crosstalk, the complexity of the MIMO-DSP increases sharply along with the increase of the number of multiplexing modes and the mode group delay, so that it is important to design a vortex ring-shaped optical fiber with low vortex mode group delay to reduce the complexity of the MIMO-DSP. For the application scene of optical vortex mode multiplexing communication of which the receiving end does not need the MIMO-DSP technology, the coupling crosstalk between optical vortex modes in the transmission process is required to be reduced as much as possible, and the mode performance regulation and control such as effective refractive index separation, overlap integral reduction and the like of adjacent optical vortex modes can be realized by optimizing the structural parameters of the vortex annular optical fiber, so that the mode coupling crosstalk between the optical vortex modes is reduced, and the stable transmission of the multichannel optical vortex modes with low crosstalk is realized.
The traditional optical fiber design method is a calculation method based on parameter scanning, which is time-consuming and has a limited optical fiber structure. Particularly for complex fiber designs with multi-parameter optimization, very fine grids are required to achieve high-precision scanning, which makes the difficulty of the traditional design method significantly rise, and the parameter scanning needs to be carried out again each time when the fiber with different target mode performance parameters is designed, which is very time-consuming. The vortex ring-shaped optical fiber design needs to optimize structural parameters of each layer of ring in the ring core to realize target optical vortex mode performance, wherein the optimized parameters comprise the radius of the innermost layer of ring core, the width of each layer of ring, the refractive index distribution of each layer of ring and the like, the number of optimized parameters is increased along with the increase of the number of layers, and the design difficulty and complexity are also obviously increased. In view of this, how to flexibly and efficiently design a vortex ring-shaped optical fiber to obtain a specific target optical fiber vortex mode performance parameter, that is, optical fiber vortex mode engineering, is a key technology to be solved in an optical vortex mode multiplexing communication system.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an optical fiber vortex mode engineering based on a neural network, which aims to realize the optical fiber vortex mode engineering of a specific target by utilizing the neural network, flexibly adjust the structural parameters of a vortex ring-shaped optical fiber to obtain the optical fiber vortex mode performance parameters of the specific target, break through the time-consuming and limited structure realization limitations of the traditional vortex optical fiber design method and fill the blank of the related technology.
In order to achieve the above purpose, the invention provides an optical fiber vortex mode engineering based on a neural network. The method comprises the steps of obtaining optical fiber vortex mode performance parameters corresponding to a plurality of vortex ring-shaped optical fiber structural parameters by using a numerical simulation method as a sample set, adopting a BP neural network structure, taking the optical fiber vortex mode performance parameters as the input of a neural network, taking the vortex ring-shaped optical fiber structural parameters as the output of the neural network, and training, testing and verifying the neural network to obtain a corresponding neural network model. And inputting the fiber vortex mode performance parameters of the specific targets into a neural network model, and predicting the corresponding vortex ring-shaped fiber structure parameters required by the output prediction of the neural network. And obtaining corresponding optical fiber vortex mode performance parameters through numerical simulation calculation by the vortex annular optical fiber structure parameters obtained through the neural network model prediction, comparing the corresponding optical fiber vortex mode performance parameters with the target optical fiber vortex mode performance parameters, if the error is lower than a set threshold value, completing optimization, otherwise, putting the vortex annular optical fiber structure parameters and the corresponding optical fiber vortex mode performance parameters into a sample set of the neural network as newly added supplementary samples, and optimizing the neural network model. And repeating the iteration until the fiber vortex mode performance parameter obtained by numerical simulation of the vortex annular fiber structure parameter predicted by the neural network model is highly consistent with the fiber vortex mode performance parameter of the target, and the error is lower than a set threshold value, thereby realizing the fiber vortex mode engineering based on the neural network.
Preferably, the vortex ring-shaped fiber structural parameters include: the number of layers N of the annular cores, the inner diameter r 1 of the innermost annular core, the width d i of each annular core (i=1, 2, …, N), the relative refractive index difference between each annular core and the cladding, the refractive index profile N i of each annular core, which is a step index profile, or a graded index profile, having the same or different g-parameters for each annular core, or an arbitrary refractive index profile. The fiber vortex mode performance parameters include: mode effective refractive index, mode effective refractive index difference, mode group effective refractive index difference, mode effective area, inter-mode overlap integral, mode crosstalk, mode confinement loss, chromatic dispersion, nonlinearity, mode differential group delay.
Preferably, the number of layers N of the annular core in the vortex annular optical fiber structural parameter is more than or equal to 2, the relative refractive index difference between the fiber core and the cladding is less than or equal to 2 mu m, the inner diameter r 1 of the innermost annular core is more than or equal to 2 mu m, and the width d i of each annular core is more than or equal to 1 mu m (i=1, 2, …, N).
Preferably, the vortex ring-shaped optical fiber structural parameters are flexibly adjusted according to the user-defined optical fiber vortex mode engineering requirements, and finally the optical fiber vortex mode engineering with specific targets is realized. The optical fiber vortex mode engineering requirements can be mode group effective refractive index equidistant distribution, mode effective refractive index equidistant distribution, low crosstalk characteristic requirements among modes, and low differential group delay characteristic requirements among modes.
Preferably, for a multi-channel mode group multiplexing transmission application scenario, optical fiber vortex modes are grouped, all vortex modes in each mode group are integrally used as a channel to carry information, and low-crosstalk multiplexing and demultiplexing among the mode groups are not needed by a multiple-input multiple-output digital signal processing (MIMO-DSP) technology. The fiber vortex mode performance parameters include: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Preferably, for the application scenarios of multi-channel mode multiplexing and intra-mode multi-channel mode multiplexing transmission, the optical fiber vortex mode is clustered, the number of modes in each mode group is 2 or 4, each mode in each mode group is respectively used as a channel to carry information, inter-mode low-crosstalk multiplexing and demultiplexing is performed, no MIMO-DSP technology is needed, and intra-mode multiplexing and demultiplexing adopts a small-scale (2×2 or 4×4) MIMO-DSP technology. The fiber vortex mode performance parameters include: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, the first mode group is 2 modes, the other mode groups are 4 modes, the differential group delay in the mode groups is less than or equal to 300ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Preferably, for a multi-channel mode multiplexing transmission application scenario, each mode is used as a channel to carry information, all modes do not distinguish mode groups to perform mode multiplexing and demultiplexing together, a large-scale (m×m) MIMO-DSP technology is required to be used, and M is the total channel number of the fiber vortex mode. The fiber vortex mode performance parameters include: the number of modes is more than or equal to 6, the group delay of all mode differences is less than or equal to 600ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Preferably, for a multi-channel mode multiplexing transmission application scenario including a few-order radial high-order modes, the few-order radial high-order modes are allowed to appear to further increase the number of mode channels, each mode is used as a channel to carry information, all modes do not distinguish between the mode groups to perform mode multiplexing and demultiplexing together, and a large-scale (m×m) MIMO-DSP technology is required to be used, where M is the total number of channels of the optical fiber vortex mode. The fiber vortex mode performance parameters include: the number of modes is more than or equal to 6, the group delay of all mode differentiation is less than or equal to 600ps/km, the vortex mode allows radial 2-order or 3-order modes to appear, and the wavelength range is C wave band, L wave band or C+L wave band.
Preferably, the vortex ring fiber is a multicore vortex ring fiber comprising a plurality of fiber cores, the structural parameters of each fiber core being obtained using neural network learning predictions based on fiber vortex mode performance parameters for a particular target. The multicore vortex annular optical fiber structural parameters include: the number of cores, the arrangement of the cores, the spacing between the cores, the number of layers N of the annular cores, the inner diameter r 1 of the innermost annular core, the width d i of each annular core (i=1, 2, …, N), the relative refractive index difference between each annular core and the cladding, the refractive index profile N i of each annular core, which is a step index profile, or a graded index profile, has the same or different g parameters corresponding to each annular core, or an arbitrary refractive index profile. The fiber vortex mode performance parameters include: vortex mode crosstalk between fiber cores, mode effective refractive index in each fiber core, mode effective refractive index difference, mode group effective refractive index difference, mode effective area, inter-mode overlap integral, mode crosstalk, mode limiting loss, chromatic dispersion, nonlinearity, mode differential group delay.
Compared with the prior art, the invention has the following beneficial effects:
1. The invention discloses a method for optical fiber vortex mode engineering based on a neural network, which flexibly adjusts vortex ring-shaped optical fiber structural parameters according to the optical fiber vortex mode engineering requirements of specific targets, finally realizes the optical fiber vortex mode performance parameters of the specific targets, and breaks through the limitations of time consumption and limited realization structure of the traditional optical fiber design.
2. The invention utilizes the neural network to construct the complex functional relation between the optical fiber vortex mode performance parameter and the vortex annular optical fiber structure parameter, does not need to solve the complex formula between the optical fiber vortex mode performance parameter and the vortex annular optical fiber structure parameter, only needs to complete the training of the neural network through the input and output sample set, has the characteristics of flexibility, high efficiency and universality, and provides a brand new thought for vortex annular optical fiber design and vortex mode regulation.
3. The invention has wide application range, can flexibly adjust the vortex ring-shaped optical fiber structural parameters for different requirements of various space division multiplexing communication systems on the optical fiber vortex mode performance, and finally realizes the optical fiber vortex mode engineering of a specific target.
4. The scope of the structural parameters of the vortex ring-shaped optical fiber is limited, and the vortex ring-shaped optical fiber has good compatibility with the existing optical fiber manufacturing process, and is very beneficial to the actual drawing of the optical fiber.
Drawings
FIG. 1 is a schematic diagram of a method for fiber vortex mode engineering based on a neural network;
FIG. 2 is a schematic diagram of a neural network according to the present invention;
FIG. 3 is a schematic cross-sectional view of a vortex ring-shaped optical fiber provided by the present invention;
Fig. 4 is a schematic cross-sectional view of a multicore vortex ring-shaped optical fiber provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not interfere with each other.
The invention provides a method for optical fiber vortex mode engineering based on a neural network, which is used for obtaining optical fiber vortex mode performance parameters of specific targets by adjusting vortex ring-shaped optical fiber structural parameters. The method comprises the steps of obtaining optical fiber vortex mode performance parameters corresponding to a plurality of vortex ring-shaped optical fiber structural parameters by using a numerical simulation method as a sample set, adopting a BP neural network structure, taking the optical fiber vortex mode performance parameters as the input of a neural network, taking the vortex ring-shaped optical fiber structural parameters as the output of the neural network, and training, testing and verifying the neural network to obtain a corresponding neural network model. And inputting the fiber vortex mode performance parameters of the specific targets into a neural network model, and predicting the corresponding vortex ring-shaped fiber structure parameters required by the output prediction of the neural network. And obtaining corresponding optical fiber vortex mode performance parameters through numerical simulation calculation by the vortex annular optical fiber structure parameters obtained through the neural network model prediction, comparing the corresponding optical fiber vortex mode performance parameters with the target optical fiber vortex mode performance parameters, if the error is lower than a set threshold value, completing optimization, otherwise, putting the vortex annular optical fiber structure parameters and the corresponding optical fiber vortex mode performance parameters into a sample set of the neural network as newly added supplementary samples, and optimizing the neural network model. And repeating the iteration until the fiber vortex mode performance parameter obtained by numerical simulation of the vortex annular fiber structure parameter predicted by the neural network model is highly consistent with the fiber vortex mode performance parameter of the target, and the error is lower than a set threshold value, thereby realizing the fiber vortex mode engineering based on the neural network.
Specifically, the vortex ring-shaped optical fiber structural parameters include: the number of layers N of the annular cores, the inner diameter r 1 of the innermost annular core, the width d i of each annular core (i=1, 2, …, N), the relative refractive index difference between each annular core and the cladding, the refractive index profile N i of each annular core, which is a step index profile, or a graded index profile, having the same or different g-parameters for each annular core, or an arbitrary refractive index profile. The fiber vortex mode performance parameters include: mode effective refractive index, mode effective refractive index difference, mode group effective refractive index difference, mode effective area, inter-mode overlap integral, mode crosstalk, mode confinement loss, chromatic dispersion, nonlinearity, mode differential group delay.
Specifically, the number of layers N of the annular core in the vortex annular optical fiber structural parameter is more than or equal to 2, the relative refractive index difference between the fiber core and the cladding is less than or equal to 2 mu m, the inner diameter r 1 of the innermost annular core is more than or equal to 2 mu m, and the width d i of each annular core is more than or equal to 1 mu m (i=1, 2, …, N).
Specifically, according to the fiber vortex mode engineering requirements defined by users, vortex ring-shaped fiber structure parameters are flexibly adjusted, and finally fiber vortex mode engineering with specific targets is realized. The optical fiber vortex mode engineering requirements can be mode group effective refractive index equidistant distribution, mode effective refractive index equidistant distribution, low crosstalk characteristic requirements among modes, and low differential group delay characteristic requirements among modes.
Specifically, for a multi-channel mode group multiplexing transmission application scenario, optical fiber vortex modes are grouped, all vortex modes in each mode group are integrally used as a channel to carry information, and low-crosstalk multiplexing and demultiplexing among the mode groups are not needed, so that a multiple-input multiple-output digital signal processing (MIMO-DSP) technology is not needed. The fiber vortex mode performance parameters include: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Specifically, for the application scenarios of multi-channel mode multiplexing and intra-mode multi-channel mode multiplexing transmission, the optical fiber vortex mode is clustered, the number of modes in each mode group is 2 or 4, each mode in each mode group is respectively used as a channel to carry information, inter-mode low-crosstalk multiplexing and demultiplexing is performed, no MIMO-DSP technology is needed, and intra-mode multiplexing and demultiplexing adopts a small-scale (2×2 or 4×4) MIMO-DSP technology. The fiber vortex mode performance parameters include: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, the first mode group is 2 modes, the other mode groups are 4 modes, the differential group delay in the mode groups is less than or equal to 300ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Specifically, for a multi-channel mode multiplexing transmission application scenario, each mode is used as a channel to carry information, all modes do not distinguish mode groups to perform mode multiplexing and demultiplexing together, a large-scale (m×m) MIMO-DSP technology is required to be used, and M is the total channel number of the fiber vortex mode. The fiber vortex mode performance parameters include: the number of modes is more than or equal to 6, the group delay of all mode differences is less than or equal to 600ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
Specifically, for a multi-channel mode multiplexing transmission application scenario including a few-order radial high-order modes, the few-order radial high-order modes are allowed to appear to further increase the number of mode channels, each mode is used as a channel to carry information, all modes do not distinguish between the mode groups to perform mode multiplexing and demultiplexing together, and a large-scale (m×m) MIMO-DSP technology is required to be used, where M is the total number of channels of the optical fiber vortex mode. The fiber vortex mode performance parameters include: the number of modes is more than or equal to 6, the group delay of all mode differentiation is less than or equal to 600ps/km, the vortex mode allows radial 2-order or 3-order modes to appear, and the wavelength range is C wave band, L wave band or C+L wave band.
Specifically, the vortex ring-shaped optical fiber is a multicore vortex ring-shaped optical fiber, which comprises a plurality of fiber cores, and the structural parameter of each fiber core is obtained by utilizing neural network learning prediction according to the fiber vortex mode performance parameter of a specific target. The multicore vortex annular optical fiber structural parameters include: the number of cores, the arrangement of the cores, the spacing between the cores, the number of layers N of the annular cores, the inner diameter r 1 of the innermost annular core, the width d i of each annular core (i=1, 2, …, N), the relative refractive index difference between each annular core and the cladding, the refractive index profile N i of each annular core, which is a step index profile, or a graded index profile, has the same or different g parameters corresponding to each annular core, or an arbitrary refractive index profile. The fiber vortex mode performance parameters include: vortex mode crosstalk between fiber cores, mode effective refractive index in each fiber core, mode effective refractive index difference, mode group effective refractive index difference, mode effective area, inter-mode overlap integral, mode crosstalk, mode limiting loss, chromatic dispersion, nonlinearity, mode differential group delay.
The following description is made with reference to specific embodiments and drawings.
Fig. 1 is a schematic diagram of a method for optical fiber vortex mode engineering based on a neural network. The method comprises the steps of obtaining fiber vortex mode performance parameters corresponding to a plurality of vortex ring-shaped fiber structure parameters by using a numerical simulation method as a sample set, taking the fiber vortex mode performance parameters as input of a neural network, taking the vortex ring-shaped fiber structure parameters as output of the neural network, and training, testing and verifying the neural network to obtain a corresponding neural network model. And inputting the fiber vortex mode performance parameters of the specific targets into a neural network model, and predicting the corresponding vortex ring-shaped fiber structure parameters required by the output prediction of the neural network. And obtaining corresponding optical fiber vortex mode performance parameters by a numerical simulation method through vortex ring-shaped optical fiber structure parameters obtained by the neural network model prediction, comparing the optical fiber vortex mode performance parameters with the optical fiber vortex mode performance parameters of a specific target, if the error is lower than a set threshold value, completing optimization, otherwise, putting the vortex ring-shaped optical fiber structure parameters and the corresponding optical fiber vortex mode performance parameters into a sample set of the neural network as newly added supplementary samples, and optimizing the neural network model. And repeating the iteration until the fiber vortex mode performance parameter obtained by numerical simulation of the vortex annular fiber structure parameter predicted by the neural network model is in high coincidence with the fiber vortex mode performance parameter of the specific target, and the error is lower than a set threshold.
Fig. 2 is a schematic diagram of a neural network according to the present invention. The number of hidden layer layers of the neural network is determined, the number of hidden layer neurons, a nonlinear activation function, an error function and the like are determined, and the number of neurons of an input layer and an output layer is respectively determined by the number of input and output variables. The vortex ring-shaped optical fiber structure parameters are used for obtaining corresponding optical fiber vortex mode performance parameters through a numerical simulation method, the optical fiber vortex mode performance parameters are used as input of a neural network, the vortex ring-shaped optical fiber structure parameters are used as output of the neural network, an input and output sample set of the neural network is obtained, a neural network model is optimized, and finally the neural network model capable of predicting the vortex ring-shaped optical fiber structure parameters through the optical fiber vortex mode performance parameters is built.
As shown in fig. 3, a schematic cross-sectional view of a vortex ring-shaped optical fiber provided by the present invention, the number of ring cores is 5, and the number of layers of the vortex ring-shaped optical fiber includes, but is not limited to, 5 layers. The inner cladding 1 and the outer cladding 2 are made of pure silicon dioxide materials, and the refractive indexes of the inner cladding 1 and the outer cladding 2 are the same. The innermost annular core 3 has an inner diameter r 1, a width d 1, the second annular core 4 has a width d 2, the third annular core 5 has a width d 3, the fourth annular core 6 has a width d 4, the fifth annular core 7 has a width d 5, and the refractive index profile of each annular core is N i (i=1, 2, …, N). Wherein the inner diameter r 1 of the innermost annular core is more than or equal to 2 mu m, the width d i of each annular core is more than or equal to 1 mu m (i=1, 2, …, N), and the relative refractive index difference between the fiber core and the cladding is less than or equal to 2%.
As shown in fig. 4, a schematic cross-sectional view of a multicore vortex ring-shaped optical fiber provided by the present invention, where the number of ring-shaped cores is 2, and the number of vortex ring-shaped cores includes but is not limited to 2. The number of layers of the toroidal core 1 is 3, including but not limited to 3 layers; the number of layers of the toroidal core 2 is 3, including but not limited to 3 layers. The inner cladding 3 of the annular core 1 and the inner cladding 4 of the annular core 2 are both made of pure silica material. Wherein the distance L between the annular cores 1 and 2 is more than or equal to 30 mu m, the inner diameter r 1 of the innermost annular core of each fiber core is more than or equal to 2 mu m, the width d i of each annular core is more than or equal to 1 mu m (i=1, 2, …, N), and the relative refractive index difference between the fiber cores and the cladding is less than or equal to 2%.
The present invention is not limited to the above embodiments, and those skilled in the art can implement the present invention in various other embodiments according to the present disclosure, so that any simple changes or modifications of the design structure and concept of the present invention are possible, and they fall within the scope of the present invention.
Claims (7)
1. The method for optical fiber vortex mode engineering based on the neural network is characterized by comprising the following steps of:
Taking fiber vortex mode performance parameters corresponding to a plurality of vortex ring-shaped fiber structure parameters obtained by a numerical simulation method as a sample set, taking the fiber vortex mode performance parameters as input of a neural network, taking the vortex ring-shaped fiber structure parameters as output of the neural network, training, testing and verifying the neural network to obtain a corresponding neural network model; according to the fiber vortex mode engineering requirements defined by users, adjusting vortex ring-shaped fiber structure parameters, and finally realizing fiber vortex mode engineering of vortex mode performance targets; the optical fiber vortex mode engineering requirements are mode group effective refractive index equidistant distribution, mode effective refractive index equidistant distribution, low crosstalk characteristic requirements among modes, or low differential group delay characteristic requirements among modes;
inputting the performance parameters of the vortex mode of the target optical fiber into a neural network model, and predicting the required corresponding vortex annular optical fiber structure parameters;
The predicted vortex ring-shaped optical fiber structure parameters are calculated through numerical simulation to obtain corresponding optical fiber vortex mode performance parameters, the corresponding optical fiber vortex mode performance parameters are compared with target optical fiber vortex mode performance parameters, if the error is lower than a set threshold value, optimization is completed, otherwise, the vortex ring-shaped optical fiber structure parameters and the corresponding optical fiber vortex mode performance parameters are put into a sample set of a neural network to serve as newly added supplementary samples, a neural network model is optimized, iteration is repeated until the error between the optical fiber vortex mode performance parameters obtained through numerical simulation of the vortex ring-shaped optical fiber structure parameters predicted by the neural network model and the optical fiber vortex mode performance parameters of a specific target is lower than the set threshold value, and therefore optical fiber vortex mode engineering based on the neural network is achieved;
The vortex ring-shaped optical fiber comprises a multilayer ring-shaped core, an inner cladding and an outer cladding, and the vortex ring-shaped optical fiber structure parameters comprise: the number of layers N of the annular core, the inner diameter r 1 of the innermost annular core, the width d i of each annular core, the relative refractive index difference between each annular core and the cladding, the refractive index profile N i of each annular core, where i = 1,2, …, N; the optical fiber vortex mode performance parameters include: mode effective refractive index, mode effective refractive index difference, mode group effective refractive index difference, mode effective area, inter-mode overlap integral, mode crosstalk, mode limiting loss, chromatic dispersion, nonlinearity, mode differential group delay;
The number of layers N of the annular core in the vortex annular optical fiber structural parameter is more than or equal to 2, the relative refractive index difference between the fiber core and the cladding is less than or equal to 2 mu m, the inner diameter r 1 of the innermost annular core is more than or equal to 2 mu m, and the width d i of each annular core is more than or equal to 1 mu m, wherein i=1, 2, … and N.
2. The method of neural network-based fiber-optic vortex mode engineering according to claim 1, wherein the fiber-optic vortex mode performance parameters comprise: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
3. The method of neural network-based fiber-optic vortex mode engineering according to claim 1, wherein the fiber-optic vortex mode performance parameters comprise: the number of the mode groups is more than or equal to 2, the effective refractive index difference between the mode groups is more than or equal to 10 -3, the crosstalk between the mode groups is less than or equal to-20 dB/km, the first mode group is 2 modes, the other mode groups are 4 modes, the differential group delay in the mode groups is less than or equal to 300ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
4. The method of neural network-based fiber-optic vortex mode engineering according to claim 1, wherein the fiber-optic vortex mode performance parameters comprise: the number of modes is more than or equal to 6, the group delay of all mode differences is less than or equal to 600ps/km, all vortex modes inhibit radial high-order modes, only radial 1-order modes are supported, and the wavelength range is C wave band, L wave band or C+L wave band.
5. The method of neural network-based fiber-optic vortex mode engineering according to claim 1, wherein the fiber-optic vortex mode performance parameters comprise: the number of modes is more than or equal to 6, the group delay of all mode differentiation is less than or equal to 600ps/km, the vortex mode allows radial 2-order or 3-order modes to appear, and the wavelength range is C wave band, L wave band or C+L wave band.
6. The method of claim 1, wherein the vortex ring fiber is a multicore vortex ring fiber comprising a plurality of fiber cores, and wherein the structural parameters of each fiber core are obtained by neural network learning prediction based on the fiber vortex mode performance parameters of the target.
7. The method of neural network fiber optic vortex mode engineering according to claim 6, wherein the multicore vortex ring-shaped fiber structure parameters comprise: the number of fiber cores, the arrangement of the fiber cores, the interval between the fiber cores and each fiber core is an annular core, the number of layers N of the annular cores, the inner diameter r 1 of the innermost annular core, the width d i of each annular core, the relative refractive index difference between each annular core and the cladding layer and the refractive index distribution N i of each annular core, wherein i=1, 2, … and N; the optical fiber vortex mode performance parameters include: vortex mode crosstalk between fiber cores, mode effective refractive index in each fiber core, mode effective refractive index difference, mode effective area, mode group effective refractive index difference, mode overlap integral, mode crosstalk, mode limiting loss, chromatic dispersion, nonlinearity, mode differential group delay.
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