Phase change photonic device signal processing method and device for photoelectric fusion

Abstract

The application discloses a phase change photonic device signal processing method and device for photoelectric fusion, and belongs to the technical field of photoelectric fusion. The method comprises the following steps: generating an input optical signal through a baseband equivalent module, setting an ambient temperature value and a bias voltage value of the input optical signal; inputting the ambient temperature value and the bias voltage value into a phase change dynamics core module to obtain an effective refractive index actual value, a loss coefficient actual value and a group refractive index actual value; calculating an equivalent time delay, a phase shift and a loss of the input optical signal based on the effective refractive index actual value, the loss coefficient actual value and the group refractive index actual value; wherein the phase change dynamics core module comprises a temperature calculation submodule, a phase change dynamics submodule and an optical property fitting submodule. The method can realize full-dimensional accurate simulation of a phase change photonic device from a basic component to a composite system and from an open-loop characteristic to closed-loop regulation, and provides key technical support for research and development of a nonvolatile photonic integrated system in a photoelectric fusion scene.

Description

Technical Field

[0001] This application belongs to the field of optoelectronic fusion technology, and in particular relates to a signal processing method and apparatus for phase change photonic devices oriented towards optoelectronic fusion. Background Technology

[0002] Phase-change photonic devices, with their characteristics of maintaining the state when powered off and zero static power consumption, have become the core devices for next-generation optical interconnects and programmable photonic networks. Accurate modeling of their optoelectronic characteristics is a prerequisite for device design and system integration.

[0003] Traditional photonic device modeling frameworks are only suitable for thermo-optical / electro-optical volatile tuned devices. The core logic is to first build a basic model of optical signal transmission based on baseband equivalent theory, derive the basic equations of optical signal time-domain-frequency domain correlation, wave vector change under first-order dispersion, and waveguide input-output baseband field transmission, and realize the quantitative characterization of optical signal phase shift, loss, and time delay; then introduce thermo-optical or electro-optical volatile tuning mechanisms, fit the refractive index and loss change to a correlation function of ambient temperature or applied voltage, and establish the mapping relationship between electrical / thermal excitation and optical parameters; then complete the static accumulation of optical parameters through variable fitting, and follow the volatile rule of "parameters are immediately reset after excitation removal"; finally, integrate to form a complete volatile phase shifter model, which can only meet the simulation needs of traditional volatile photonic devices. This framework suffers from three major limitations: First, it lacks the introduction of state variables and locking mechanisms for crystalline / amorphous / molten states of phase change materials, making it unable to characterize the persistence of non-volatile tuning and thus ill-suited to the core characteristic requirements of phase change photonic devices. Second, it lacks dynamic modeling capabilities for phase change dynamics, supporting only steady-state or simple transient responses and failing to accurately characterize the phase change threshold response and nonlinear hysteresis effects under pulse-driven conditions. Third, existing electronic / photonic design automation (EDA / PDA) platforms lack a suitable closed-loop optoelectronic simulation link, hindering system-level verification of the synergy between non-volatile and volatile tuning. Due to these shortcomings, existing models cannot achieve accurate optoelectronic co-simulation of phase change photonic devices, severely restricting the R&D progress of related devices in optoelectronic integration scenarios, necessitating the development of a general-purpose, dedicated modeling method.

[0004] Non-volatile phase-change photonic devices are core foundational devices in optoelectronic integration fields such as optical interconnects and programmable photonic networks. Traditional photonic device modeling frameworks only support volatile tuning processes such as thermo-optical / electro-optical processes, and have key defects such as lack of characterization of non-volatile tuning mechanisms, insufficient optoelectronic closed-loop co-simulation capabilities, and limited model scalability. As a result, mainstream EDA platforms cannot achieve accurate design and verification of such devices. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a signal processing method and device for phase-change photonic devices oriented towards optoelectronic integration. By constructing a full-link modeling system including temperature calculation, phase change ratio quantization, and optical characteristic fitting, it comprehensively covers the core physical equations relating phase change dynamics and optical parameters. It has completed the development and verification of models for various types of basic non-volatile photonic switches, composite systems, and closed-loop optoelectronic simulations. This model is compatible with mainstream EDA platforms such as Cadence Virtuoso and can achieve accurate simulation of phase-change photonic devices from basic components to composite systems, and from open-loop characteristics to closed-loop control, providing key technical support for the research and development of non-volatile photonic integrated systems in optoelectronic integration scenarios.

[0006] To address the aforementioned problems, according to a first aspect of the present invention, a signal processing method for phase-change photonic devices oriented towards optoelectronic integration is provided, the method comprising: The input optical signal is generated through the baseband equivalent module, and the ambient temperature value and bias voltage value of the input optical signal are set. The ambient temperature and bias voltage values ​​are input into the phase transition dynamics core module to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index. The equivalent time delay, phase shift, and loss of the input optical signal are calculated based on the actual values ​​of the effective refractive index, loss coefficient, and group refractive index. The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

[0007] According to one embodiment of this application, the step of inputting the ambient temperature value and bias voltage value into the phase transition dynamics core module to obtain the actual value of the effective refractive index, the actual value of the loss coefficient, and the actual value of the group refractive index includes: Input the ambient temperature and bias voltage values ​​into the temperature calculation submodule to obtain the phase change material temperature; The phase change material temperature is input into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio; Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assign values ​​to the melting ratio, crystallization ratio, and amorphization ratio parameters, and obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value. The initial values ​​of effective refractive index, loss coefficient, and group refractive index are updated based on the fitted values ​​of effective refractive index, loss coefficient, and group refractive index, as well as the free carrier absorption equation, dispersion equation, and thermo-optical effect equation of GST material, to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index.

[0008] According to one embodiment of this application, the step of inputting the melt ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assigning values ​​to the melt ratio, crystallization ratio, and amorphization ratio parameters, and obtaining the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value includes: Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule to determine whether the current temperature is greater than or equal to the crystallization temperature threshold. When the current temperature is greater than or equal to the crystallization temperature threshold, continuous variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters. When the current temperature is less than the crystallization temperature threshold, discrete variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters to obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value.

[0009] According to one embodiment of this application, the step of inputting the phase change material temperature into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio includes: The phase change material temperature is input into the phase change kinetics submodule. The melting ratio is calculated through the melting ratio calculation equation, the crystallization ratio is calculated through the crystallization ratio calculation equation, and the amorphization ratio is calculated through the amorphization ratio calculation equation.

[0010] According to one embodiment of this application, the calculation formula for the melt ratio calculation equation is as follows:

[0011]

[0012] in, It is the melting time constant. It is the melt temperature diffusivity. It is the melting temperature. It is the temperature of PCMs. It is the melt ratio.

[0013] According to one embodiment of this application, the calculation formula for the crystallization ratio calculation equation is as follows:

[0014] Where K is the crystallization rate constant, and t is time. It refers to the crystallization ratio.

[0015] According to one embodiment of this application, the formula for calculating the effective refractive index fitting value is as follows:

[0016] in, The effective refractive index fitting value, This refers to the crystallization ratio. For a fully crystalline state, the refractive index This is the melt ratio. Adjustment factor, The amorphization ratio, The refractive index is for a completely amorphous state; The formula for calculating the group refractive index fitting value is as follows:

[0017] in, The group refractive index fitting value, For a fully crystalline state, the group refractive index, The group refractive index is for a completely amorphous state; The formula for calculating the fitted value of the loss coefficient is as follows:

[0018] in, The fitted value of the loss coefficient, The loss coefficient is for the fully crystalline state. The loss coefficient is for a completely amorphous state.

[0019] According to a second aspect of the present invention, a signal processing apparatus for phase-change photonic devices oriented towards optoelectronic integration is provided, the apparatus comprising: The generation module is used to generate the input optical signal through the baseband equivalent module and set the ambient temperature value and bias voltage value of the input optical signal. The first processing module is used to input the ambient temperature value and the bias voltage value into the phase transition dynamics core module to obtain the actual value of the effective refractive index, the actual value of the loss coefficient, and the actual value of the group refractive index. The second processing module is used to calculate the equivalent time delay, phase shift, and loss of the input optical signal based on the actual values ​​of the effective refractive index, loss coefficient, and group refractive index. The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

[0020] According to a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion as described in the first aspect above.

[0021] According to a fourth aspect of the present invention, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion as described in the first aspect above.

[0022] According to a fifth aspect of the present invention, a chip is provided, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run a program or instructions to implement the signal processing method for phase-change photonic devices oriented towards optoelectronic integration as described in the first aspect.

[0023] According to a sixth aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion as described in the first aspect above.

[0024] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application.

[0025] The present invention provides a signal processing method for phase-change photonic devices oriented towards optoelectronic integration, which has the following advantages over the prior art: (1) This invention constructs a full-link modeling system based on the baseband equivalent theory and the principle of phase transition dynamics, which includes temperature calculation, phase transition ratio quantization, and optical characteristic fitting, and fully covers the core physical equations related to phase transition dynamics and optical parameters; it has completed the model development and verification of various types of basic non-volatile photonic switches, composite systems, and closed-loop optoelectronic simulations. It is compatible with mainstream EDA platforms such as Cadence Virtuoso and can realize full-dimensional accurate simulation of phase transition photonic devices from basic components to composite systems, and from open-loop characteristics to closed-loop control, providing key technical support for the research and development of non-volatile photonic integrated systems in optoelectronic fusion scenarios.

[0026] (2) By introducing discrete state variables of the three-phase state of phase change materials and a low-temperature threshold locking strategy, this invention overcomes the core characterization problem of non-volatile tuning and makes up for the shortcomings of traditional models in terms of state preservation capability. Through the non-volatile state locking mechanism, a precise phase change dynamics modeling system is constructed. By setting a temperature threshold and combining it with a dedicated phase change dynamics equation, the accurate simulation of rapid phase change and rate-dependent behavior under pulse drive is realized, breaking through the limitation of traditional models in being unable to capture transient-steady-state transitions.

[0027] (3) This invention, by adapting to the nonlinearity and hysteresis effects of phase change materials, adopts a phased modeling and threshold separation mechanism, combined with the optical parameter calculation method of phase fraction weighted averaging, filling the modeling gap that traditional polynomial fitting cannot characterize memory effects. By constructing a full-link quantitative modeling system, it is possible to realize the open-loop characteristic simulation and closed-loop optoelectronic co-verification of non-volatile photonic devices, improving the accuracy of non-volatile photonic device simulation, thereby accelerating the fusion of photons and electrons at the loop level. Attached Figure Description

[0028] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic flowchart of a signal processing method for phase-change photonic devices oriented towards optoelectronic integration provided in an embodiment of this application; Figure 2 This is a conventional phase shifter model framework diagram provided in the embodiments of this application; Figure 3 This is a schematic diagram of the phase shifter model provided in the embodiments of this application; Figure 4 This is a schematic diagram and modeling principle diagram of the non-volatile waveguide switch provided in the embodiments of this application; Figure 5 This is a schematic diagram and modeling principle diagram of a non-volatile directional coupler type switch provided in the embodiments of this application; Figure 6 This is a schematic diagram and modeling principle diagram of the non-volatile MZI type switch provided in the embodiments of this application; Figure 7 This is a schematic diagram and modeling principle diagram of the non-volatile MRR type switch provided in the embodiments of this application; Figure 8 The embodiments of this application provide voltage pulses, temperature waveforms, phase ratios, and transmission spectra of the crystallization / amorphization process of the 4.9μm phase change unit. Figure 9 These are the spectrum diagrams of the four basic non-volatile switching units provided in the embodiments of this application; Figure 10 This is a schematic diagram of the non-volatile photonic logic gate structure provided in the embodiments of this application; Figure 11 This is a schematic diagram of the modeling architecture and principle of non-volatile photonic logic gates provided in the embodiments of this application; Figure 12 This is the transmission spectrum of the non-volatile photonic logic gate pass-through bus provided in the embodiments of this application; Figure 13 This is the transmission spectrum of the non-volatile photonic logic gate download bus provided in the embodiments of this application; Figure 14 This is a schematic diagram of the non-volatile weighted photonic digital-to-analog converter structure provided in the embodiments of this application; Figure 15 This application provides a modeling architecture and principle for a non-volatile weighted photonic digital-to-analog converter. Figure 16 This is the transmission spectrum of the download bus under the modulation signals "0000" and "1111" provided in the embodiments of this application; Figure 17The random modulation signal input and PDAC output provided in the embodiments of this application; Figure 18 This is the waveform (after filtering) generated by configuring the input signal, as provided in the embodiments of this application. Figure 19 This application provides a microring resonator wavelength locking architecture that combines non-volatile coarse tuning and volatile fine tuning. Figure 20 This is a schematic diagram of the ADMRR wavelength-locked loop in Cadence software provided in the embodiments of this application; Figure 21 This application provides a micro-ring modulator wavelength-locking architecture that combines non-volatile coarse tuning and volatile fine tuning. Figure 22 This is a schematic diagram of the ADMRM wavelength-locked loop in Cadence software provided in the embodiments of this application; Figure 23 This application provides a non-volatile wavelength locking architecture for APMRM in low-temperature environments. Figure 24 This is a schematic diagram of the APMRM non-volatile wavelength-locked loop in Cadence software provided in the embodiments of this application; Figure 25 This is a schematic diagram of the structure of the phase-change photonic device signal processing apparatus for optoelectronic fusion provided in the embodiments of this application; Figure 26 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0030] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate to allow embodiments of this application to be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0031] The following description, in conjunction with the accompanying drawings, details the signal processing method, device, electronic equipment, and readable storage medium for phase-change photonic devices oriented towards optoelectronic integration, provided by the embodiments of this application, through specific implementations and application scenarios.

[0032] Among them, the signal processing method for phase-change photonic devices oriented towards optoelectronic integration can be applied to the terminal, specifically executed by the hardware or software in the terminal.

[0033] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).

[0034] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.

[0035] The phase-change photonic device signal processing method for optoelectronic fusion provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the phase-change photonic device signal processing method for optoelectronic fusion. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The following uses an electronic device as the execution subject to illustrate the phase-change photonic device signal processing method for optoelectronic fusion provided in this application embodiment.

[0036] Figure 1 This is a schematic flowchart of a signal processing method for phase-change photonic devices oriented towards optoelectronic fusion provided in an embodiment of this application, as shown below. Figure 1 As shown, the signal processing method for phase-change photonic devices oriented towards optoelectronic integration includes steps 110, 120, and 130.

[0037] Step 110: Generate the input optical signal through the baseband equivalent module, and set the ambient temperature value and bias voltage value of the input optical signal; It is easy to understand that, in order to achieve an analytical description of the optical signal transmission process in the waveguide, the time-domain-frequency domain correlation expression of the optical signal is first established based on the baseband equivalent theory. To convert the optical carrier frequency into the baseband frequency to simplify the optical transmission calculation, the baseband equivalent expression of the optical signal is as follows:

[0038]

[0039] in, It is an analytical electric field. Its baseband equivalent field is represented by a complex number. It is the speed of light. This is the reference frequency; the actual frequency is... It can be represented as .

[0040] To describe the wave vector changes of optical signals at different frequencies under first-order dispersion conditions, the frequency is derived. The wave vector equation at that point, if only first-order dispersion is considered, then the frequency... wave vector at the location The calculation formula is as follows:

[0041] in, At frequency The effective refractive index at that point, for , Group refractive index.

[0042] To establish a length of The correspondence between the waveguide input and output baseband fields, for a length of... Waveguide, output field It can be used as an input field The function representation is shown below:

[0043] in, It is transmission loss. It is relative to Phase shift, time delay Then it is used to indicate relative to The phase shift.

[0044] Step 120: Input the ambient temperature value and bias voltage value into the phase transition dynamics core module to obtain the actual value of effective refractive index, actual value of loss coefficient and actual value of group refractive index; In some embodiments, inputting the ambient temperature value and bias voltage value into the phase transition dynamics core module to obtain the actual value of the effective refractive index, the actual value of the loss coefficient, and the actual value of the group refractive index includes: Input the ambient temperature and bias voltage values ​​into the temperature calculation submodule to obtain the phase change material temperature; To quantify the dynamic temperature change of the phase change material under the action of a PIN micro heater, the equation for temperature change over time and the corresponding heating power equation are derived. The real-time temperature of the phase change material is determined by the initial temperature, heating power, and heat loss. The calculation formula for its time-domain variation equation is shown below:

[0045] The relationship between the electric power of the PIN heater and physical quantities such as electric field and charge carriers leads to the following equation for calculating the heating power:

[0046] in, It is thermal resistance. It is electrical power. It is the initial temperature. It is the heat transfer coefficient. It is thermal efficiency. It is the current flowing through the PN junction. It is the applied voltage. It is the amount of electron charge. Electron current density, The hole current density n and p are the electron and hole concentrations, respectively. and It is the mobility of electrons and holes. It is the electric field strength.

[0047] The phase change material temperature is input into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio; In some embodiments, inputting the phase change material temperature into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio includes: The phase change material temperature is input into the phase change kinetics submodule. The melting ratio is calculated through the melting ratio calculation equation, the crystallization ratio is calculated through the crystallization ratio calculation equation, and the amorphization ratio is calculated through the amorphization ratio calculation equation.

[0048] To characterize the dynamic change in the proportion of the molten region after the phase change material reaches the melting threshold, a differential governing equation for the melting ratio and its solution results are established. The rate of change of the melting ratio is constrained by both temperature and melting time constant. In some embodiments, the calculation formulas for the differential governing equation are shown below:

[0049] By solving the above differential equation, the time-domain analytical expression for the melting ratio is obtained as follows:

[0050] in, It is the melting time constant. It is the melt temperature diffusivity. It is the melting temperature. It is the temperature of PCMs. It is the melt ratio, and t corresponds to a temperature greater than 100°C. The time period, not the entire time domain.

[0051] To quantify the degree of crystallization of phase change materials within the crystallization temperature range, a calculation model for the crystallization ratio is established based on the JMAK equation. The increase in the crystallization ratio over time follows an exponential correlation law. In some embodiments, the calculation formula for the crystallization ratio calculation equation is as follows:

[0052] Where K is the crystallization rate constant, and t is time. It refers to the crystallization ratio.

[0053] Crystallization rate constant It exhibits an exponential relationship with temperature, and its calculation equation is as follows:

[0054] in, For frequency factors, For activation energy, Boltzmann's constant, For the temperature of PCMs, Crystallization fraction, crystallization temperature It is 473K.

[0055] To achieve a normalized constraint on the proportions of the three phases (crystalline, molten, and amorphous) in phase change materials, in some embodiments, the calculation formula for the amorphization ratio is as follows:

[0056] in, , , These represent the amorphization ratio, melting ratio, and crystallization ratio, respectively.

[0057] Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assign values ​​to the melting ratio, crystallization ratio, and amorphization ratio parameters, and obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value. In some embodiments, the step of inputting the melt ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assigning values ​​to the melt ratio, crystallization ratio, and amorphization ratio parameters, and obtaining the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value includes: Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule to determine whether the current temperature is greater than or equal to the crystallization temperature threshold. When the current temperature is greater than or equal to the crystallization temperature threshold, continuous variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters. When the current temperature is less than the crystallization temperature threshold, discrete variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters to obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value.

[0058] The initial values ​​of effective refractive index, loss coefficient, and group refractive index are updated based on the fitted values ​​of effective refractive index, loss coefficient, and group refractive index, as well as the free carrier absorption equation, dispersion equation, and thermo-optical effect equation of GST material, to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index.

[0059] To achieve a precise correlation between the optical parameters and phase ratios of phase change materials, and to realize non-volatility by leveraging latch-like properties, the phase ratios are first assigned as discrete variables. Then, a weighted fitting of the optical parameters is performed based on these discrete variables. To achieve non-volatility, when the temperature is below the crystallization threshold... At that time, , , The value is assigned to a discrete variable and locked until the temperature exceeds the limit in the next heating phase. This mechanism is similar to a latch, ensuring that the optical parameters are kept stable after the excitation is removed; Based on the locked discrete phase ratios, a weighted fitting of the effective refractive index is completed, and the equation is:

[0060] Based on the discrete phase ratio, a weighted fitting of the group refractive index is achieved, and the equation is as follows:

[0061] Based on the discrete phase ratio, a weighted fitting of the loss coefficient is completed, and the equation is:

[0062] in, and It refers to the refractive index of the perfectly crystalline and perfectly amorphous states. and It is the group refractive index of the perfectly crystalline and perfectly amorphous states. and This refers to the loss coefficients for fully crystalline and fully amorphous states. Adjustment factor. Typically less than 1 (set to 0.7 in this paper), because it is assumed that the optical parameters of the molten phase change material are between those of the crystalline and amorphous states. This is attributed to the increased disorder of the atomic structure within the molten state compared to the crystalline state. The precise value can be calibrated based on experimental measurements for accurate adjustment.

[0063] To quantify the impact of changes in free carrier concentration within the 1550nm band on optical parameters, the corresponding equations for refractive index and loss variation are established: The equation for the refractive index shift caused by the change in free carrier concentration is:

[0064] The equation for the loss coefficient shift caused by changes in free carrier concentration is:

[0065] in, and These are the changes in refractive index caused by variations in the concentrations of free electrons and free holes, respectively.

[0066] The equation for the refractive index change caused by free carriers in the 1.3μm band is:

[0067] The equation for the loss variation caused by free carriers in the 1.3μm band is:

[0068] in, and These are the changes in refractive index caused by variations in the concentrations of free electrons and free holes, respectively.

[0069] Step 130: Calculate the equivalent time delay, phase shift, and loss of the input optical signal based on the actual values ​​of the effective refractive index, loss coefficient, and group refractive index; The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

[0070] To quantify the thermo-optical response characteristics of GST materials in different phase states, the thermo-optical coefficient equations for the real and imaginary parts of its refractive index are given: The real part thermo-optic coefficient of the refractive index of the amorphous phase GST is:

[0071] The imaginary part of the thermo-optical coefficient of the refractive index of the amorphous phase GST is:

[0072] The real part thermo-optic coefficient of the refractive index of the GST crystalline phase is:

[0073] The imaginary part of the thermo-optical coefficient of the refractive index of the GST crystalline phase is: in, and These are the thermo-optic coefficients of the real part of the refractive index in the amorphous and crystalline phases of GST, respectively, representing the change of refractive index with temperature; and It is the corresponding coefficient of the imaginary part of the refractive index, representing the change of absorption with temperature.

[0074] Figure 2 This is a conventional phase shifter model framework diagram provided in the embodiments of this application. Figure 3 This is the phase shifter model framework proposed in the embodiments of this application, such as... Figure 3 As shown, the processing flow of the phase shifter model includes the following steps: (1) Based on the baseband equivalent theory, a basic framework for optical signal propagation is constructed, and the basic equations for optical signal time-frequency domain correlation, wave vector change under first-order dispersion and waveguide input-output baseband field transmission are derived. The quantitative characterization of optical signal phase shift, loss and time delay is completed, laying the foundation for the underlying transmission theory. (2) Based on the electrothermal conversion principle of PIN micro heater, establish the time-domain variation equation of the real-time temperature of phase change material and the correlation equation of heating power, quantify the correspondence between physical quantities such as electric field and charge carrier and heating power, and clarify the temperature prerequisite for phase change triggering. (3) Based on the melting (900K) and crystallization (473K) temperature thresholds, the proportions of molten state and crystalline state are calculated by the melting ratio differential equation and analytical solution and JMAK crystallization equation, respectively. Then, the proportion of amorphous state is obtained by normalization constraint, so as to realize the dynamic tracking of the three-phase ratio of phase change material. (4) When the temperature of the phase change material is below the crystallization threshold, the proportion of each phase is assigned as a discrete variable and locked. The latch-like characteristics are used to ensure the long-term stability of the phase after the external excitation is removed, thus realizing the non-volatile core function. (5) Based on the locked discrete phase ratio, the core optical parameters such as effective refractive index, group refractive index and loss coefficient are weighted and fitted. At the same time, the free carrier absorption / dispersion equations and the thermo-optic effect equations of GST materials in the 1550nm and 1300nm bands are supplemented to form an optical parameter characterization system covering the entire physical process.

[0075] In some embodiments, the basic nonvolatile photonic switch model is verified. Figure 4 This is a schematic diagram and modeling principle diagram of the non-volatile waveguide switch provided in the embodiments of this application. Figure 5 This is a schematic diagram and modeling principle diagram of the non-volatile directional coupler type switch provided in the embodiments of this application. Figure 6 This is a schematic diagram and modeling principle diagram of the non-volatile MZI type switch provided in the embodiments of this application. Figure 7This document presents a schematic diagram and modeling principle diagram of a non-volatile MRR switch provided in this application embodiment. To verify the accuracy of the proposed model in characterizing the basic non-volatile photonic device characteristics, the model was built using Verilog-A language on the Cadence Virtuoso platform. Specific basic examples include: verification of a non-volatile waveguide switch, a non-volatile directional coupler switch, a non-volatile MZI switch, and a non-volatile MRR switch.

[0076] Figure 8 This application provides embodiments of the voltage pulse, temperature waveform, phase ratio, and transmission spectrum of the crystallization / amorphization process of a 4.9 μm phase transition unit, as shown in the examples. Figure 8 As shown, to verify the non-volatile waveguide switch, the core parameters used in the simulation are: the complex refractive index of crystalline GST is 6.63+1.55i, the complex refractive index of amorphous GST is 4.6+0.34i, the PCM length is available in two specifications of 4.9μm and 10μm, and the doping concentration is... Simulations of the crystallization / amorphization process were conducted on a 4.9 μm phase transition unit. During the crystallization process, a 50 μs, 3.5 V electrical pulse was applied to raise the temperature to 700 K and maintain it within the crystallization temperature range. The crystallization ratio steadily increased over time, and the transmittance at a wavelength of 1550 nm monotonically decreased with increasing crystallization ratio. During the amorphization process, a 100 ns, 6.5 V electrical pulse was applied to raise the temperature to 1200 K to achieve melting. After rapid quenching, the amorphization ratio increased, and the corresponding transmittance increased by 100%. The simulated linear data and the experimental point data showed a high degree of agreement, verifying the reliability of the model.

[0077] Figure 9 These are the spectrum diagrams of four basic non-volatile switching units provided in the embodiments of this application, such as... Figure 9 As shown in Figure (a), multi-level phase state control simulation was carried out on the 10μm phase transition unit. By controlling the crystallinity, multi-level phase states of 33.3% and 66.6% were achieved, with corresponding transmission contrast ratios of 3.3dB and 6.6dB, respectively. A transmission contrast ratio of 10dB was achieved in the whole state. The simulation results are consistent with the experimental data, which verifies the multi-level control characterization capability of the model.

[0078] Verification of non-volatile directional coupler type switches. For example... Figure 9As shown in Figure (b), the core simulation parameters are: PCM length of 35 μm, coupling gap of 150 nm, complex refractive index of crystalline GST of 6.63 + 1.55i, and complex refractive index of amorphous GST of 4.6 + 0.34i. The transmission spectrum in the wavelength range of 1510-1540 nm was obtained by DC parameter scanning. Under amorphous GST, the device insertion loss was 1 dB and the crosstalk at the bar / cross port was less than -15 dB; under crystalline GST, the insertion loss was 2.5 dB and the crosstalk was less than -10 dB. The simulation data agrees well with the experimental data, verifying the model's ability to characterize coupling properties.

[0079] Verification of non-volatile MZI type switches. For example... Figure 9 As shown in Figure (c), the core simulation parameters are: PCM length of 10 μm, length difference between the two arms of 100 μm, complex refractive index of crystalline GST of 6.63 + 1.55i, and complex refractive index of amorphous GST of 4.6 + 0.34i. Simulations were conducted in the wavelength range of 1536-1550 nm. The extinction ratio of the device reached -20 dB in the completely amorphous state and decreased to -9 dB with a blue shift in the spectrum in the completely crystalline state. The transmission characteristics under multiple phase states were consistent with the experimental data, verifying the interference characteristic characterization capability of the model.

[0080] Verification of non-volatile MRR type switches. For example... Figure 9 As shown in Figure (d), the core simulation parameters are: PCM length of 15 μm, microring circumference of 90.63 μm, tuning range of 1 nm, coupling coefficient of 0.15, complex refractive index of crystalline GST of 6.63 + 1.55i, and complex refractive index of amorphous GST of 4.6 + 0.34i. Simulations were conducted in the wavelength range of 1552.5–1557.5 nm. With increasing crystallinity, the resonance spectrum redshifted by 1 nm, the quality factor decreased from 5200 to 1300, and the extinction ratio decreased from 14 dB to 2 dB. The simulation data matched the experimental data, verifying the model's ability to characterize resonance properties.

[0081] Hierarchical modeling and verification of composite devices. In some embodiments, to verify the system-level scalability of the model, a composite system is constructed based on the basic device model and simulation verification is performed.

[0082] Verification of non-volatile optical logic gates. Figure 10 This is a schematic diagram of a non-volatile photonic logic gate structure provided in an embodiment of this application. Figure 11 This application provides a schematic diagram of the non-volatile photonic logic gate modeling architecture and principle. The schematic diagram is as follows: Figure 11As shown, the core simulation parameters are: the complex refractive index of the crystalline GSST is 5.14 + 0.42i, the complex refractive index of the amorphous GSST is 3.39 + 0.00018i, the PCM length of the MRR switch is 0.855 μm, the microring circumference is 22 μm, the ring spacing is 10 μm, and the coupling coefficient is 0.125. A two-stage microring array is constructed with a non-volatile MRR as the core. Four logic inputs (00 / 10 / 01 / 11) are achieved by controlling the phase transition state. Scanning is carried out in the wavelength range of 1552-1556 nm, OR logic is implemented in the wavelength range of 1553.13-1553.45 nm, and AND logic is implemented in the wavelength range of 1553.49-1553.84 nm. Figure 12 This is the transmission spectrum of the non-volatile photonic logic gate pass-through bus provided in the embodiments of this application, and NOR / NAND logic can be synchronously implemented at the download end. Figure 13 This is the transmission spectrum of the non-volatile photonic logic gate download bus provided in the embodiments of this application, such as... Figure 13 As shown, the logic output extinction ratio reaches a maximum of 18.97 dB. The simulation results are in high agreement with the experimental data, verifying the model's ability to represent system-level logic functions.

[0083] Figure 14 This is a schematic diagram of the non-volatile weighted photonic digital-to-analog converter structure provided in the embodiments of this application, with 4-bit non-volatile weighted PDAC verification. Figure 15 This application provides a non-volatile weighted photonic digital-to-analog converter modeling architecture and principle, along with a schematic diagram of the modeling architecture and principle. Figure 15 As shown, the core simulation parameters are: the complex refractive index of crystalline GST is 6.63 + 1.55i, the complex refractive index of amorphous GST is 4.6 + 0.34i, and the doping concentration is... The PCM length is 1.1 μm; the perimeters of MRR1, MRR2, MRR3, and MRR4 are 62.33 μm, 62.52 μm, 62.71 μm, and 62.90 μm, respectively. The ring spacing is 20 μm, and the coupling coefficient is 0.05. Power weighting from 1 / 2 to 1 / 16 is achieved through four non-volatile waveguide switches, and multi-wavelength modulation is accomplished using four micro-ring modulators with different resonant wavelengths. Figure 16 This is the transmission spectrum of the download bus under modulation signals of "0000" and "1111" provided in the embodiments of this application, such as... Figure 16 As shown, when “0000” is entered, there is no effective optical power output at the download end; when “1111” is entered, the optical power of the four wavelengths is output according to the weighted ratio. Figure 17 The random modulation signal input and PDAC output provided in the embodiments of this application are, for example... Figure 17 As shown, the error between the PDAC output and the ideal value under random modulation signal input is within 3%. Figure 18This is the waveform (after filtering) generated by configuring the input signal, as provided in the embodiments of this application. Figure 18 As shown, different combinations of digital inputs can generate waveforms such as square waves, sawtooth waves, triangular waves, and sine waves. The effective number of bits (ENOB) of the sine wave output is calculated to be 3.74 bits, which meets the requirements of high-precision digital-to-analog conversion. The simulation results are consistent with the LumericalInterconnect data, verifying the system-level digital-to-analog conversion representation capability of the model.

[0084] Closed-loop optoelectronic co-simulation verification. To verify the optoelectronic co-simulation capability of the model, a multi-scenario closed-loop system was built and verified. All simulations were performed on the E5-2687W / 128GB computing platform using Cadence Virtuoso (IC618).

[0085] Wavelength locking of a non-volatile coarse-tuning-volatile fine-tuning co-loop microring resonator. Figure 19 This application provides a schematic diagram of a microring resonator wavelength-locking architecture that combines non-volatile coarse tuning and volatile fine tuning, as illustrated in the embodiments below. Figure 19 As shown, a closed-loop system including a non-volatile MRR, a thermo-optical tuning module, a PD, a TIA, and an LTM control algorithm is constructed. The simulation parameters are the same as those of the non-volatile MRR type switch, except that the coverage area of ​​the PCM unit is modified to 5μm. Figure 20 This application provides a schematic diagram of the ADMRR wavelength-locked loop in Cadence software, along with a closed-loop simulation graph, as shown in the embodiments of this application. Figure 20 As shown, the initial ambient temperature is 300K, the input wavelength is 1556nm, and the phase change material is initially completely amorphous. Phase change crystallization is achieved through a 3.5V, 50μs pulse to complete coarse wavelength alignment, followed by dynamic compensation through thermo-optical tuning. Compared to a pure thermo-optical tuning scheme, the hybrid tuning architecture reduces the initial lock-in time by 30% and effectively compensates for ambient temperature disturbances of 10K / 100Hz, verifying the model's closed-loop co-simulation capability.

[0086] Wavelength locking of a non-volatile coarse-tuning-volatile fine-tuning co-loop modulator. Figure 21 This application provides a schematic diagram of a micro-ring modulator wavelength-locking architecture that combines non-volatile coarse tuning and volatile fine tuning, as illustrated in the embodiments of this application. Figure 21 As shown, an electro-optic modulation module and an LTR control algorithm are introduced on the basis of the above system to construct an ADMRM wavelength locking system. The simulation parameters are consistent with those of the micro-ring resonator wavelength locking system. Figure 22 This application provides a schematic diagram of the ADMRM wavelength-locked loop in Cadence software, along with a closed-loop simulation graph, as shown in the embodiments of this application. Figure 22As shown, the initial ambient temperature is 300K, the input wavelength is 1310nm, and the phase change material is initially completely amorphous. Non-volatile wavelength alignment is achieved through a 3.5V, 50μs pulse. Then, a 1Gbps, 2V swing NRZ modulation signal is loaded into the model. The system can stably compensate for ambient temperature disturbances of 10K / 100Hz. The eye diagram of the device output is at its maximum opening in the locked state, which verifies the model's adaptability to closed-loop simulation of modulation devices.

[0087] Non-volatile wavelength locking of micro-ring modulators in low-temperature (4K) environments. Figure 23 This is a schematic diagram of the modeling framework for the APMRM non-volatile wavelength locking architecture in a low-temperature environment provided in this application embodiment, as shown below. Figure 23 As shown, a non-volatile wavelength-locked system was constructed at a low temperature of 4K. The simulation parameters were: micro-ring perimeter of 94.54 μm, coupling coefficient of 0.1375, PCM coverage length of 8 μm, and PN junction doping concentration of [missing information]. The complex refractive index of GST material is 6.63+1.55i in the crystalline state and 4.6+0.34i in the amorphous state. Figure 24 This is a schematic diagram of the APMRM non-volatile wavelength-locked loop in Cadence software provided in the embodiments of this application. The closed-loop simulation diagram is shown below. Figure 24 As shown, the initial ambient temperature is 4K, the input wavelength is 1325.511nm, and the phase change material is initially in a fully crystalline state. By applying multiple sets of amorphization pulses (12V / 1us, 12V / 1.15us, 12V / 1.35us, 12V / 1.55us), multi-level phase transitions are achieved. The TIA output gradually decreases, the transmission spectrum gradually blue-shifts, and the eye diagram gradually opens. The changes in each parameter correspond to each other, and the simulation results are in high agreement with the experimental data, verifying the model's closed-loop simulation capability in low-temperature scenarios.

[0088] It should be noted that the core components of the Verilog-A general model for phase-change photonic devices oriented towards optoelectronic integration include PIN microheaters, non-volatile waveguides, directional couplers, MZI, and MRR. Simulations of four types of basic non-volatile photonic switches, non-volatile optical logic gates and 4-bit photonic digital-to-analog converter composite systems, non-volatile coarse-tuning-volatile fine-tuning coordination, and closed-loop optoelectronic simulations under low-temperature conditions are all used only to verify the accuracy, scalability, and effectiveness of optoelectronic co-simulation of this model.

[0089] The signal processing method for phase-change photonic devices oriented towards optoelectronic fusion provided in this application embodiment can be executed by a signal processing device for phase-change photonic devices oriented towards optoelectronic fusion. This application embodiment uses the execution of the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion by a signal processing device for phase-change photonic devices oriented towards optoelectronic fusion as an example to illustrate the signal processing device for phase-change photonic devices oriented towards optoelectronic fusion provided in this application embodiment.

[0090] This application also provides a signal processing device for phase-change photonic devices oriented towards optoelectronic integration, such as... Figure 25 As shown, the phase-change photonic device signal processing apparatus for optoelectronic integration includes: a generation module 2510, a first processing module 2520, and a second processing module 2530.

[0091] The generation module 2510 is used to generate an input optical signal through a baseband equivalent module and to set the ambient temperature value and bias voltage value of the input optical signal. The first processing module 2520 is used to input the ambient temperature value and the bias voltage value into the phase transition dynamics core module to obtain the actual value of the effective refractive index, the actual value of the loss coefficient and the actual value of the group refractive index. The second processing module 2530 is used to calculate the equivalent time delay, phase shift and loss of the input optical signal based on the actual value of the effective refractive index, the actual value of the loss coefficient and the actual value of the group refractive index; The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

[0092] The signal processing method for phase-change photonic devices oriented towards optoelectronic integration provided in this application constructs a full-link modeling system that includes temperature calculation, phase change ratio quantization, and optical characteristic fitting, comprehensively covering the core physical equations relating phase change dynamics and optical parameters. It also completes the development and verification of models for various types of basic non-volatile photonic switches, composite systems, and closed-loop optoelectronic simulations. This model is compatible with mainstream EDA platforms such as Cadence Virtuoso and can achieve accurate simulation of phase-change photonic devices across all dimensions, from basic components to composite systems, and from open-loop characteristics to closed-loop control, providing key technical support for the development of non-volatile photonic integrated systems in optoelectronic integration scenarios.

[0093] The phase-change photonic device signal processing apparatus for optoelectronic integration provided in this application embodiment can achieve… Figures 1 to 3 The various processes implemented in the embodiment of the signal processing method for phase-change photonic devices oriented towards optoelectronic integration will not be described in detail here to avoid repetition.

[0094] In some embodiments, such as Figure 26As shown, this application embodiment also provides an electronic device 2600, including a processor 2601, a memory 2602, and a computer program stored in the memory 2602 and executable on the processor 2601. When the program is executed by the processor 2601, it implements the various processes of the above-described embodiment of the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0095] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0096] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described embodiment of the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0097] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0098] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described signal processing method for phase-change photonic devices oriented towards optoelectronic fusion.

[0099] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0100] This application also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described embodiment of the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0101] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a device-level chip, device chip, chip device, or on-chip device chip, etc.

[0102] It should be noted that, in this document, the terms "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 limitations, 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 that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the signal processing method for phase-change photonic devices oriented towards optoelectronic fusion of the various embodiments of this application.

[0104] In the description of this application, "first feature" and "second feature" may include one or more of the features.

[0105] In the description of this application, "multiple" means two or more.

[0106] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0107] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0108] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A signal processing method for phase-change photonic devices oriented towards optoelectronic integration, characterized in that, The method includes: The input optical signal is generated through the baseband equivalent module, and the ambient temperature value and bias voltage value of the input optical signal are set. The ambient temperature and bias voltage values ​​are input into the phase transition dynamics core module to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index. The equivalent time delay, phase shift, and loss of the input optical signal are calculated based on the actual values ​​of the effective refractive index, loss coefficient, and group refractive index. The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

2. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 1, characterized in that, The process of inputting ambient temperature and bias voltage values ​​into the phase transition dynamics core module to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index includes: Input the ambient temperature and bias voltage values ​​into the temperature calculation submodule to obtain the phase change material temperature; The phase change material temperature is input into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio; Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assign values ​​to the melting ratio, crystallization ratio, and amorphization ratio parameters, and obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value. The initial values ​​of effective refractive index, loss coefficient, and group refractive index are updated based on the fitted values ​​of effective refractive index, loss coefficient, and group refractive index, as well as the free carrier absorption equation, dispersion equation, and thermo-optical effect equation of GST material, to obtain the actual values ​​of effective refractive index, loss coefficient, and group refractive index.

3. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 2, characterized in that, The step of inputting the melt ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule, assigning values ​​to the melt ratio, crystallization ratio, and amorphization ratio parameters, and obtaining the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value includes: Input the melting ratio, crystallization ratio, and amorphization ratio into the optical property fitting submodule to determine whether the current temperature is greater than or equal to the crystallization temperature threshold. When the current temperature is greater than or equal to the crystallization temperature threshold, continuous variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters. When the current temperature is less than the crystallization temperature threshold, discrete variables are assigned to the melting ratio, crystallization ratio, and amorphization ratio parameters to obtain the effective refractive index fitting value, loss coefficient fitting value, and group refractive index fitting value.

4. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 3, characterized in that, The step of inputting the phase change material temperature into the phase change kinetics submodule to obtain the melting ratio, crystallization ratio, and amorphization ratio includes: The phase change material temperature is input into the phase change kinetics submodule. The melting ratio is calculated through the melting ratio calculation equation, the crystallization ratio is calculated through the crystallization ratio calculation equation, and the amorphization ratio is calculated through the amorphization ratio calculation equation.

5. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 4, characterized in that, The calculation formula for the melt ratio calculation equation is as follows: in, It is the melting time constant. It is the melt temperature diffusivity. It is the melting temperature. It is the temperature of PCMs. It is the melt ratio.

6. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 5, characterized in that, The calculation formula for the crystallization ratio calculation equation is as follows: in, , It refers to the crystallization ratio.

7. The signal processing method for phase-change photonic devices oriented towards optoelectronic integration according to claim 6, characterized in that, The formula for calculating the effective refractive index fitting value is as follows: in, The effective refractive index fitting value, This refers to the crystallization ratio. For a fully crystalline state, the refractive index This is the melt ratio. Adjustment factor, The amorphization ratio, The refractive index is for a completely amorphous state; The formula for calculating the group refractive index fitting value is as follows: in, The group refractive index fitting value, For a fully crystalline state, the group refractive index, The group refractive index is for a completely amorphous state; The formula for calculating the fitted value of the loss coefficient is as follows: in, The fitted value of the loss coefficient, The loss coefficient is for the fully crystalline state. The loss coefficient is for a completely amorphous state.

8. A signal processing apparatus for phase-change photonic devices oriented towards optoelectronic integration, implemented using the signal processing method for phase-change photonic devices oriented towards optoelectronic integration as described in any one of claims 1 to 7, characterized in that, The device includes: The generation module is used to generate the input optical signal through the baseband equivalent module and set the ambient temperature value and bias voltage value of the input optical signal. The first processing module is used to input the ambient temperature value and the bias voltage value into the phase transition dynamics core module to obtain the actual value of the effective refractive index, the actual value of the loss coefficient, and the actual value of the group refractive index. The second processing module is used to calculate the equivalent time delay, phase shift, and loss of the input optical signal based on the actual values ​​of the effective refractive index, loss coefficient, and group refractive index. The core module of phase transition dynamics includes a temperature calculation submodule, a phase transition dynamics submodule, and an optical property fitting submodule.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the signal processing method for phase-change photonic devices oriented towards optoelectronic integration as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the signal processing method for phase-change photonic devices oriented towards optoelectronic integration as described in any one of claims 1 to 7.

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