Silicon-based micro-ring wavelength locking method based on symbiotic organism algorithm

Abstract

The application discloses a silicon-based micro-ring wavelength locking method based on a symbiotic organism algorithm, and the method comprises the following steps: setting upper and lower limits of heating power, randomly initializing a primary heating power species, applying the primary heating power species on a micro-heater gradually, obtaining output optical power, comparing and obtaining a primary optimal heating power species, then judging the optimal heating power, and continuously changing the heating power species through the operation of a mutual benefit stage, a symbiotic stage and a parasitic stage until the optimal heating power is obtained. Compared with the step-by-step scanning method for searching the optimal heating power, the method reduces the searching times, improves the searching speed, solves the pain points of the existing step-by-step scanning method, such as many searching times and slow speed, and provides a solution for improving the speed of micro-ring wavelength locking.

Description

Technical Field

[0001] This invention belongs to the field of micro-ring wavelength control technology, specifically relating to a silicon-based micro-ring wavelength locking method based on a symbiotic biological algorithm. Background Technology

[0002] Silicon-based microring resonators, due to their wavelength selectivity and advantages in size and power consumption, have become an ideal solution for constructing core communication devices such as optical filters, optical switches, light sources, optical modulators, and photodetectors. Because of their wavelength selectivity, silicon-based microring resonators generally need to operate at specific wavelengths; however, due to process errors, their resonant wavelength often deviates significantly from the target signal wavelength. Furthermore, the high thermo-optic coefficient of silicon makes the microring resonant wavelength highly sensitive to changes in ambient temperature. Therefore, addressing the wavelength drift problem is crucial when constructing large-scale integrated optical circuits based on silicon-based microrings.

[0003] Integrating a microheater onto a silicon-based microring resonator and applying different heating powers to the microheater to shift the resonant wavelength of the microring is a common wavelength-locking scheme. Searching for the optimal heating power to achieve wavelength locking of the silicon-based microring is essential. When the resonant wavelength of the microring is aligned with the target signal wavelength, most of the optical signal energy is coupled into the microring, resulting in a minimum output optical power. The heating power that minimizes the output optical power is the optimal heating power. Based on the above ideas, the commonly used step-scan search algorithm gradually increases the thermal power by a fixed step size, records the output optical power, and compares the minimum output optical power to obtain the minimum value. The heating power corresponding to this minimum value is the optimal heating power. However, this method has certain limitations. First, the method requires a fixed step size. If the step size is too large, each increase in heating power will cause the resonant wavelength of the microring to shift and skip the target wavelength. The minimum output optical power will not appear in the entire scanning process, and the optimal heating power cannot be found. If the step size is set too small, although the minimum output optical power will be scanned, a large number of steps are required to complete the entire scanning process, which will consume too much search time. Therefore, the step-scan search algorithm cannot simultaneously meet the requirements of wavelength locking of silicon-based microrings in terms of accuracy and speed. Summary of the Invention

[0004] The main objective of this invention is to overcome the shortcomings and deficiencies of the prior art and propose a silicon-based microring wavelength locking method based on a symbiotic biological algorithm, which reduces the number of searches and improves the search speed compared to step-scan search for the optimal heating power.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A silicon-based microring wavelength locking method based on a symbiotic biological algorithm includes:

[0007] S1. Set upper and lower limits for heating power, randomly initialize the first generation of heating power species, apply the first generation of heating power species to the micro heater one by one, obtain the output light power and compare it to obtain the first generation of optimal heating power species, determine whether it is the optimal heating power, if it is, the method ends, otherwise proceed to step S2.

[0008] S2, Mutual benefit stage: Mutual benefit update of all heating power species of the previous generation to obtain the next generation of heating power species. Apply the heating power species to the micro heater one by one to obtain the output light power. Determine whether there is an optimal heating power. If yes, the method ends; otherwise, proceed to step S3.

[0009] S3. Cohabitation stage: Randomly select half of the heating power species from the heating power species for cohabitation renewal, while the remaining heating power species remain unchanged. Apply the renewed heating power species to the micro heater one by one to obtain the output light power. Determine whether there is an optimal heating power. If yes, the method ends; otherwise, proceed to step S4.

[0010] S4. Parasitism stage: Randomly select one-quarter of the heating power species from the heating power species for parasitism and update, and set them as parasitic species. The remaining heating power species remain unchanged. Apply the parasitic species to the micro heater one by one to obtain the output light power. Determine whether there is an optimal heating power. If so, the method ends. Otherwise, jump to step S2 and continue iteratively to perform subsequent steps until the optimal heating power is found.

[0011] Furthermore, setting upper and lower limits for heating power and randomly initializing the initial heating power species are as follows:

[0012] Set upper and lower limits for heating power [0, P] max Randomly initialize n heating power species in, The superscript indicates the 0th generation heating power species, and i = 1, 2...n represents the i-th heating power species.

[0013] Furthermore, step S1 also includes:

[0014] The 0th generation heating power species were applied one by one to the microheater to obtain the 0th generation microring output optical power Y. i 0 The minimum output optical power is obtained by comparison. And its corresponding heating power species, which is set as the optimal heating species of generation 0.

[0015] judge Is it less than the set output optical power threshold Th? If it is less than the threshold Th, then If the optimal heating power is reached, the method ends; otherwise, proceed to step S2.

[0016] Furthermore, the mutually beneficial phase specifically includes:

[0017] After mutually beneficial updates of all k-th generation heating power species, we obtain the (k+1)-th generation heating power species. The (k+1)th generation heating power species are successively applied to the microheater to obtain the (k+1)th generation microring output optical power Y. i k+1 Determine Y i k+1 Is it less than the output optical power threshold Th? If so, Y i k+1 The method terminates if the heating power is less than the threshold Th, and the corresponding heating power species... That is, the optimal heating power;

[0018] If Y does not exist i k+1 If Y is less than the threshold Th, compare the output optical power of the (k+1)th generation with that of the kth generation. i k+1 <Y i k This indicates that the mutual benefit update of the heating power species in generation k+1 is successful; otherwise, the mutual benefit update fails, and the heating power species remains unchanged from the previous generation. The minimum output optical power of the (k+1)th generation was obtained through comparison. The corresponding heating power species is set as the optimal heating power species of the (k+1)th generation. Proceed to step S3.

[0019] Furthermore, the method for mutually beneficial updates is as follows:

[0020] For the two heating power species of the kth generation heating power species but:

[0021]

[0022]

[0023] in, R represents the species with the optimal heating power in the kth generation. mv represent Interaction relationship r1 and r2 are random numbers in the interval [0, 1], and bf1 and bf2 are benefit factors. When r1 < 0.5, bf1 = 1 indicates partial benefit, and when r1 > 0.5, bf1 = 2 indicates full benefit. The same applies to bf2.

[0024] Furthermore, the symbiotic stage specifically includes:

[0025] From the (k+1)th generation, randomly select n / 2 species with high heating power for commensal renewal, while the remaining n / 2 species with high heating power remain unchanged.

[0026] The updated n / 2 heating powers were successively applied to the microheater to obtain the output optical power Y of the (k+2)th generation microring. i k+2 Determine Y i k+2 Is it less than the output optical power threshold Th? If so, Y i k+2 The method terminates when the heating power is less than the threshold Th, corresponding to the species. That is, the optimal heating power;

[0027] If Y does not exist i k+2 If Y is less than the threshold Th, compare the output optical power of the (k+2)th generation with that of the (k+1)th generation. i k+2 <Y i k+1 This indicates that the symbiotic relationship has successfully updated the heating power of the species in the (k+2)th generation; otherwise, the symbiotic update has failed, and the value before the update remains unchanged. The minimum output optical power of the (k+2)th generation was obtained through comparison. And its corresponding heating power species, and set it as the optimal heating species for the (k+2)th generation. Proceed to step S4.

[0028] Furthermore, the method of symbiotic renewal is as follows:

[0029]

[0030] Where r3 is a random number in the interval [-1, 1], This represents two distinct heating power species in the (k+1)th generation.

[0031] Furthermore, the parasitic stage specifically includes:

[0032] Randomly select n / 4 heating power species from the (k+2)th generation heating power population, set them as parasitic species and update them;

[0033] The updated heating power of n / 4 parasite species was successively applied to the microheater to obtain the output optical power Y of the (k+3)th generation microring. i k+3 Determine Y i k+3 Is it less than the output optical power threshold Th? If so, Y i k+3The method terminates when the heating power is less than the threshold Th, corresponding to the species. That is, the optimal heating power;

[0034] If Y does not exist i k+3 If Y is less than the threshold Th, compare the output optical power of the (k+2)th generation and the (k+3)th generation. i k+3 <Y i k+2 This indicates that the parasitic update of the heating power of the (k+3)th generation species was successful; otherwise, the parasitic update failed, and the value before parasitism remained unchanged. The minimum output optical power of the (k+3)th generation was obtained through comparison. And its corresponding heating power species, and set it as the optimal heating species for the (k+3)th generation. Finally, proceed to step S2 and continue iterating until the threshold condition is met to obtain the optimal heating power.

[0035] Furthermore, the method for setting it as a parasitic species and updating it is as follows:

[0036]

[0037] Where r4 is a random number in the interval [-1, 1].

[0038] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0039] 1. This invention applies the symbiotic biological algorithm to the search for optimal heating power for wavelength locking in silicon-based microrings. It randomly selects an initial heating power species and iteratively changes the heating power through mutualistic, symbiotic, and parasitic operations among the heating power species until the optimal heating power is obtained. Compared with step-scan search for optimal heating power, this reduces the number of searches and greatly improves the speed of searching for optimal heating power. Attached Figure Description

[0040] Figure 1 This is a flowchart of the method of the present invention;

[0041] Figure 2 This is a graph showing the relationship between the output optical power and heating power of the micro-ring;

[0042] Figure 3a These are simulation results from the embodiments;

[0043] Figure 3b This is a simulation result diagram from the embodiment. Detailed Implementation

[0044] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0045] The symbiotic organism search algorithm, proposed in 2014, is a heuristic search algorithm based on biological symbiotic phenomena. This algorithm features few control parameters, simple operation, ease of implementation, good stability, and strong optimization capabilities, making it suitable for various target value search scenarios. The thermal response speed of silicon-based microring resonators is on the order of microseconds, allowing for rapid switching of heating power to obtain corresponding output optical power. Using heating power as the species and output optical power as the return value, the algorithm iteratively changes the heating power through mutualistic, symbiotic, and parasitic operations between heating power species until the optimal heating power that meets the conditions is obtained. This allows for rapid location of the optimal heating power, significantly reducing the number of search iterations.

[0046] Example

[0047] like Figure 1 As shown, a silicon-based microring wavelength locking method based on a symbiotic biological algorithm includes the following steps:

[0048] S1. Set the upper and lower limits of heating power [0, P]. max Randomly initialize n initial heating power species. The superscript indicates the 0th generation heating power species, and i = 1, 2...n represents the i-th heating power species;

[0049] 0th generation heating power species The output optical power Y of the 0th generation microring is obtained by applying it one by one to the microheater. i 0 The minimum output optical power is obtained by comparison. And its corresponding heating power species, which is set as the optimal heating species of generation 0.

[0050] judge Is it less than the set output optical power threshold Th? If it is less than the threshold Th, then If the optimal heating power is reached, the method ends; otherwise, proceed to step S2.

[0051] S2, Mutually Beneficial Phase: Perform mutually beneficial updates on all k-th generation heating power species, resulting in the (k+1)-th generation heating power species. The method for mutually beneficial updates is as follows:

[0052] For the two heating power species X of the k-th generation heating power species i k X j k ,but:

[0053]

[0054]

[0055] in, R represents the species with the optimal heating power in the kth generation. mv represent Interaction relationship r1 and r2 are random numbers in the interval [0, 1], and bf1 and bf2 are benefit factors. When r1 < 0.5, bf1 = 1 indicates partial benefit, and when r1 > 0.5, bf1 = 2 indicates full benefit. The same applies to bf2.

[0056] The (k+1)th generation heating power species are successively applied to the microheater to obtain the (k+1)th generation microring output optical power Y. i k +1 Determine Y i k+1 Is it less than the output optical power threshold Th? If so, Y i k+1 The method terminates if the heating power is less than the threshold Th, and the corresponding heating power species... That is, the optimal heating power;

[0057] If Y does not exist i k+1 If Y is less than the threshold Th, compare the output optical power of the (k+1)th generation with that of the kth generation. i k+1 <Y i k This indicates that the mutual benefit update of the heating power species in generation k+1 is successful; otherwise, the mutual benefit update fails, and the heating power species remains unchanged from the previous generation. The minimum output optical power of the (k+1)th generation was obtained through comparison. The corresponding heating power species is set as the optimal heating power species of the (k+1)th generation. Proceed to step S3.

[0058] S3, Cohabitation Stage: From the (k+1)th generation of heating power species, randomly select n / 2 heating power species for cohabitation renewal, while the remaining n / 2 heating power species remain unchanged. The method of symbiotic renewal is as follows:

[0059]

[0060] Where r3 is a random number in the interval [-1, 1], This represents two distinct heating power species in the (k+1)th generation.

[0061] The updated n / 2 heating powers were successively applied to the microheater to obtain the output optical power Y of the (k+2)th generation microring.i k+2 Determine Y i k+2 Is it less than the output optical power threshold Th? If so, Y i k+2 The method terminates when the heating power is less than the threshold Th, corresponding to the species. That is, the optimal heating power;

[0062] If Y does not exist i k+2 If Y is less than the threshold Th, compare the output optical power of the (k+2)th generation with that of the (k+1)th generation. i k+2 <Y i k+1 This indicates that the symbiotic relationship has successfully updated the heating power of the species in the (k+2)th generation; otherwise, the symbiotic update has failed, and the value before the update remains unchanged. The minimum output optical power of the (k+2)th generation was obtained through comparison. And its corresponding heating power species, and set it as the optimal heating species for the (k+2)th generation. Proceed to step S4.

[0063] S4. Parasitism Stage: Randomly select n / 4 heating power species from the (k+2)th generation heating power population, set them as parasitic species, and update them. The update method is as follows:

[0064]

[0065] Where r4 is a random number in the interval [-1, 1].

[0066] The updated heating power of n / 4 parasite species was successively applied to the microheater to obtain the output optical power Y of the (k+3)th generation microring. i k+3 Determine Y i k+3 Is it less than the output optical power threshold Th? If so, Y i k+3 The method terminates when the heating power is less than the threshold Th, corresponding to the species. That is, the optimal heating power;

[0067] If Y does not exist i k+3 If Y is less than the threshold Th, compare the output optical power of the (k+2)th generation and the (k+3)th generation. i k+3 <Y i k+2 This indicates that the parasitic update of the heating power of the (k+3)th generation species was successful; otherwise, the parasitic update failed, and the value before parasitism remained unchanged. The minimum output optical power of the (k+3)th generation was obtained through comparison. And its corresponding heating power species, and set it as the optimal heating species for the (k+3)th generation. Finally, proceed to step S2 and continue iterating through subsequent steps until the threshold condition is met, thus obtaining the optimal heating power.

[0068] In this embodiment, simulation was performed in MATLAB, where the maximum heating power Pmax was set to 130mW, the number of species was set to 20, and the maximum number of iterations was set to 50. The relationship between the heating power and the output optical power of the microring is as follows: Figure 2 As shown, the threshold is set to -6.3 dBm, and the optimal heating power is 58.5 mW.

[0069] Simulation results are as follows Figure 3a and Figure 3b As shown in the histogram of search counts in 1000 simulation experiments, the highest number of searches was around 40, and the average number of searches was 70. The optimal heating power obtained in the 1000 experiments converged within the range of [57.6mW, 59.4mW], which is near the set optimal heating power of 58.5mW, indicating that the method in this embodiment can find the optimal heating power. However, if a step-scan search is used to find the optimal heating power, a step interval of 0.1mW is required, theoretically requiring a maximum of 1300 searches. Therefore, compared to a step-scan search for the optimal heating power, the method of this invention reduces the number of searches by approximately 15 times, significantly improving the speed of finding the optimal heating power.

[0070] It should also be noted that, in this specification, terms such as "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0071] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A silicon-based micro-ring wavelength locking method based on a symbiotic organism algorithm, characterized in that, Comprise: S1, set the upper and lower limits of heating power, randomly initialize the initial heating power species, apply the initial heating power species to the micro-heater one by one, get the output optical power and compare to get the initial optimal heating power species, judge whether it is the optimal heating power, if yes, the method ends, otherwise enter step S2; S2, mutual benefit stage, update all heating power species of the last generation to get the next generation of heating power species, apply the heating power species to the micro-heater one by one, get the output optical power, judge whether there is the best heating power, if yes, the method ends, otherwise enter step S3; S3, symbiotic stage, randomly select half of the heating power species from the heating power species for symbiotic update, the remaining heating power species remain unchanged, apply the updated heating power species to the micro-heater one by one, get the output optical power, judge whether there is the best heating power, if yes, the method ends, otherwise enter step S4; S4, parasitic stage, randomly select one fourth of the heating power species from the heating power species for parasitic update, set as the parasite species, the remaining heating power species remain unchanged, apply the parasite species to the micro-heater one by one, get the output optical power, judge whether there is the best heating power, if yes, the method ends, otherwise jump to step S2, continue the iteration cycle to perform the subsequent steps until the best heating power is found.

2. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 1, characterized in that, The specific method of setting the upper and lower limits of heating power and randomly initializing the initial heating power species is: Set the upper and lower limits of heating power [0, P max ], randomly initialize n heating power species wherein, The superscript of i = 1, 2…n represents the i th heating power species.

3. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 2, characterized in that, Step S1 further comprises: The 0th generation heating power species is applied on the micro-heater one by one to obtain the 0th generation micro-ring output light power Y i 0 The minimum output light power is obtained by comparison and the corresponding heating power species, which is set as the 0th generation optimal heating species determining whether it is less than a set output light power threshold Th, if less than the threshold Tg, then the optimal heating power, the method ends, otherwise step S2 is entered.

4. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 3, characterized in that, The specific method of mutual benefit stage is: The k+1 generation of heating power species is applied on the micro-heater to obtain the k+1 generation of micro-ring output optical power Y The k+1 generation of heating power species is applied on the micro-heater to obtain the k+1 generation of micro-ring output optical power Y i k+1 , judge whether Y i k+1 is less than the output optical power threshold Th, if there is Y i k+1 less than the threshold Th, the method ends, and the corresponding heating power species is the optimal heating power If Y i k+1 If Y i k+1 If Y i k If Y If Y If Y Go to step S3.

5. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 4, characterized in that, The method of mutual benefit update is: for the 2 heating power species of the kth generation heating power species then: wherein, represents the optimal heating power species of the kth generation, R mv represents the interaction relationship r1, r2 are random numbers in the interval [0, 1], and bf1, bf2 are benefit factors, wherein when r1 < 0.5, bf1 = 1 indicates partial benefit, when r1 > 0.5, bf1 = 2 indicates complete benefit, and bf2 is the same.

6. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 4, characterized in that, The specific method of symbiotic stage is: n / 2 randomly selected heating power species from the k+1 generation are allowed to coexist with the remaining n / 2 heating power species from the k+1 generation, i.e. The n / 2 heating powers after the symbiotic update are applied on the micro-heater in turn to obtain the output light power Y of the k+2th generation of the micro-ring i k+2 , and it is determined whether Y i k+2 is less than the output light power threshold Th. If there is Y i k+2 less than the threshold Th, the method ends, and the corresponding heating power species is the optimal heating power. If Y i k+2 If Y i k+2 If Y i k+1 , indicating that the symbiosis is successful, update the heating power species of the k+2 generation; otherwise, the symbiotic update fails, and the value before the symbiotic update is maintained Compare the output optical power of the k+2 generation And its corresponding heating power species, and set it as the optimal heating species of the k+2 generation Enter step S4.

7. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 6, characterized in that, The method of symbiotic update is: where r3 is a random number in the interval [-1, 1], representing two different heating power species in the k+1 generation.

8. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 6, characterized in that, The specific method of parasitic stage is: Randomly select n / 4 heating power species from the k+2 generation of heating power species, set them as parasite species and update them; The updated n / 4 parasitic species of heating power is applied on the micro-heater to obtain the k+3th generation of micro-ring output light power Y i k+3 , judge Y i k+3 whether it is less than the output light power threshold Th, if there is Y i k+3 less than the threshold Th, the method ends, and the corresponding heating power species is the optimal heating power; If Y i k+3 If Y i k+3 If Y i k+2 , it means that the parasitic species is successfully updated to the k+3th generation, otherwise, the parasitic update fails, and the value before parasitism is maintained, that is, The minimum value of the output optical power of the k+3th generation and its corresponding heating power species are compared, and it is set as the optimal heating species of the k+3th generation Finally, jump to step S2 to continue iteration until the threshold condition is met to obtain the optimal heating power.

9. The silicon-based micro-ring wavelength locking method based on symbiotic algorithm according to claim 8, characterized in that, The method of setting as parasite species and updating is: Wherein, r4 is a random number in the interval [-1, 1].

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