Method for automated modulation of KB focusing mirrors for synchrotron beamline optics

Abstract

The application discloses an automatic modulation method for a KB focusing mirror of a synchrotron radiation beamline, and belongs to the technical field of precise regulation and control of synchrotron radiation beamlines. The method comprises the following steps: obtaining a wavefront error of a light beam through a grating diffraction effect and taking the wavefront error as a core feedback signal; then, a hybrid intelligent optimization algorithm is constructed, the population of a genetic algorithm is sorted and optimized by using the path optimization advantage of an ant colony algorithm, so that the mechanical traversal path of an actuator is shortened, the convergence speed is improved, and the loss is reduced; finally, based on the wavefront error feedback, a piezoelectric actuator is driven by the hybrid algorithm, closed-loop automatic modulation of multiple degrees of freedom parameters of the KB mirror is realized, and the wavefront error reaches a nanometer level preset threshold. The application overcomes the defects of traditional methods, such as dependence on manual operation, low efficiency and insufficient precision, realizes full automation of the modulation process, and significantly improves the debugging efficiency and focusing precision of the beamline.

Description

Technical Field

[0001] This invention belongs to the field of precision control technology for synchrotron beamlines, specifically relating to an automated modulation method for synchrotron beamline optical KB focusing mirrors. Background Technology

[0002] Synchrotron radiation sources, as crucial platforms for cutting-edge scientific research, directly impact the precision and efficiency of experiments through their beam quality. The KB (Kirkpatrick-Baez) focusing system is a key optical component for achieving micron- and nanometer-scale focusing within a beamline. It uses a pair of orthogonally placed elliptical cylindrical mirrors to focus the beam horizontally and vertically, respectively. The focused spot size of the KB focusing mirror ultimately depends on the precise coordination of multiple degrees of freedom parameters, including pitch, roll, and translation (x, y, z). Any minute misalignment will introduce wavefront distortion, leading to an increase in spot size and a decrease in brightness, failing to meet the demands of advanced experiments such as nanoscale in-situ observations.

[0003] Currently, the adjustment of KB lenses mainly relies on manual experience and trial-and-error through enumeration. Operators need to repeatedly adjust the actuators of each degree of freedom based on the far-field spot morphology acquired by the CCD, gradually approaching the optimal focusing state. This method has significant bottlenecks: First, it is highly dependent on the operator's experience and judgment, and the adjustment process is time-consuming, usually requiring several hours or even longer, severely encroaching on valuable experimental time; second, using spot size or centroid position as feedback basis is essentially an indirect judgment based on light intensity distribution, and the lack of beam wavefront phase information makes it difficult to sensitively reflect deep aberrations that cause focusing degradation, and the accuracy has reached its limit.

[0004] To improve debugging efficiency and automation, some studies have attempted to introduce optimization algorithms (such as genetic algorithms) for parameter search. However, in the high-dimensional, multi-extremum parameter space of KB mirrors, single genetic algorithms suffer from insufficient global exploration capabilities, susceptibility to local optima, and slow convergence speed. Furthermore, when the algorithm drives the physical actuator to traverse parameter combinations, the resulting mechanical motion paths are lengthy, extending debugging time and exacerbating wear on precision mechanical structures. Ant colony optimization, another algorithm commonly used for path optimization, performs excellently on problems like the Traveling Salesman Problem, but its optimization efficiency and accuracy are difficult to guarantee when directly applied to such continuous high-dimensional parameter optimization problems.

[0005] Therefore, with the trend of synchrotron beamlines moving towards higher brightness and smaller focal spots, it has become an urgent technical need to break through the limitations of traditional tuning methods and develop a new method that can directly sense wavefront distortion and integrate the advantages of intelligent algorithms to achieve fast, accurate, and automated modulation. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an automated modulation method for a synchrotron beamline optical KB focusing mirror. The method obtains the beam wavefront error through grating diffraction and uses it as a key feedback signal for the algorithm. Subsequently, an ant colony algorithm is introduced to optimize the initial population of the genetic algorithm, with the core objective of shortening the path length for the motor to traverse the population. Based on this optimization, a hybrid algorithm with both global optimization capability and fast local convergence characteristics is further developed. Finally, this algorithm drives a piezoelectric actuator to complete the closed-loop modulation process of the KB mirror parameters.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] An automated modulation method for a synchrotron radiation beamline optical KB focusing mirror, comprising:

[0009] Step 1: Utilize the diffraction effect of the grating to obtain the wavefront information of the beam reflected by the KB focusing mirror, and calculate the wavefront error RMS value through wavefront reconstruction and fitting.

[0010] Step 2: Construct a genetic algorithm population with multiple motion dimension parameters of the KB focusing lens as optimization variables, and use the ant colony algorithm to optimize the traversal order of individuals in the genetic algorithm population to determine the shortest mechanical motion path.

[0011] Step 3: Using the wavefront error value as a feedback signal, drive the execution motor to sequentially modulate the attitude of the 8 motion dimensions of the KB focusing mirror according to the motion path order optimized by the ant colony algorithm, and at the same time collect the corresponding grating diffraction wavefront data. Repeat steps 1 to 3 for iterative optimization until the wavefront error value reaches the preset threshold.

[0012] In a second aspect, the present invention provides an electronic device comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned automated modulation method for a synchrotron beamline optical KB focusing mirror.

[0013] Thirdly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned automated modulation method for a synchrotron beamline optical KB focusing mirror.

[0014] The beneficial effects of this invention are as follows:

[0015] A breakthrough in control precision at the nanometer level: By using the grating diffraction wavefront error as a direct feedback quantity, the phase distortion of the beam can be sensitively captured, improving the control precision of the KB mirror to the level of wavefront error RMS≤3nm, fundamentally meeting the stringent requirements of synchrotron radiation nanofocusing experiments.

[0016] Debugging efficiency is improved by orders of magnitude: the population traversal path of the genetic algorithm is optimized by ant colony algorithm, which greatly reduces the invalid movement of the actuator. The hybrid algorithm has both global optimization capability and fast local convergence characteristics, which shortens the single modulation time from several hours in traditional manual methods to less than 60 minutes, improving efficiency by nearly 10 times and greatly saving valuable experimental time.

[0017] High degree of automation and intelligence: It realizes closed-loop automation of the entire process from wavefront detection and algorithm optimization to modulation execution, effectively reducing the dependence on operator experience and improving the standardization and repeatability of beamline debugging.

[0018] The system exhibits strong robustness and stability: the integrated environmental sensing and feedforward compensation mechanism can effectively suppress external interference such as temperature drift and mechanical vibration, ensuring the long-term stability of the modulation results (drift ≤ ±2nm / h) and guaranteeing the continuous and reliable output of high-quality beams. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the automated modulation method for a synchrotron beamline optical KB focusing mirror according to the present invention.

[0020] Figure 2 This is a flowchart of the automated modulation method for the KB focusing lens of the synchrotron radiation beamline optical system of the present invention.

[0021] Figure 3 This is a schematic diagram illustrating the principle of wavefront error calculation.

[0022] Figure 4 This is a flowchart of the hybrid algorithm. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] like Figure 1 As shown, this invention provides an automated modulation method for a synchrotron radiation beamline optical KB focusing mirror, wherein the automated modulation is a complete closed-loop control circuit. The beam emitted by the synchrotron radiation source is first incident on the KB mirror group through a pre-optical system. The KB mirror group consists of a horizontal focusing mirror (HKB) and a vertical focusing mirror (VKB), and its attitude is driven and controlled by a high-precision piezoelectric ceramic actuator.

[0025] The beam of light, reflected and focused by the KB mirror, then illuminates a high-precision grating (such as a holographic grating with a period of 100-500 line pairs / mm). The diffraction effect of the grating encodes the wavefront phase information of the beam into the resulting diffraction pattern. A wavefront detector (such as a Shack-Hartmann sensor) is responsible for acquiring this diffraction pattern array.

[0026] The wavefront sensor transmits the collected light spot information to the data processing unit (including a hybrid intelligent algorithm module). In this module, the wavefront error of the beam is first accurately calculated (quantified by the root mean square error, RMS value) through wavefront reconstruction and polynomial fitting. This wavefront error value is then used as the core feedback signal and input into the hybrid intelligent algorithm, a genetic algorithm (GA) optimized by ant colony optimization (ACO). The GA constructs an initial population using eight dimensions as genetic variables: X-direction displacement, Z-direction displacement, roll angle, and pitch angle of the HKB focusing lens, and X-direction displacement, Y-direction displacement, Z-direction displacement, and pitch angle of the VKB focusing lens. The ACO optimization treats the iterative process of the ant colony algorithm as "path optimization." The ant colony dynamically adjusts the order of each generation of the GA population through a pheromone update mechanism, minimizing the total path taken by the motor to traverse all individuals in each generation—improving the convergence speed of the GA and reducing machine wear.

[0027] The hybrid algorithm module, with the goal of minimizing wavefront error, generates control commands to adjust the various degrees of freedom (such as displacement and tilt) of the KB focusing mirror. These commands are sent to the execution and closed-loop control module, which drives the corresponding piezoelectric ceramic actuators (with a positioning accuracy ≤5nm) to drive the KB mirror.

[0028] The above process is iterated in cycles, forming a closed-loop feedback system of "measurement-calculation-decision-execution" until the calculated wavefront error value converges within the preset nanometer threshold range (such as RMS≤5nm), ultimately achieving automated and high-precision optimization of the KB mirror focusing performance.

[0029] like Figure 2 As shown, before proceeding with the steps of this invention, system initialization is performed: initializing the genetic algorithm, ant colony algorithm parameters, and the motion dimension range of the KB focusing lens.

[0030] First, set the adjustment range for each motion dimension parameter of the KB focusing lens (including but not limited to the displacement and tilt angle of the horizontal and vertical mirrors), such as tilt angle ±1mrad and translation ±10μm.

[0031] Subsequently, the hybrid intelligent algorithm is initialized: the genetic algorithm (GA) generates an initial population according to the parameter range and sets its operation parameters such as crossover probability (Pc) and mutation probability (Pm);

[0032] Meanwhile, the Ant Colony Algorithm (ACO) initializes its pheromone matrix and sets parameters such as the number of ants (num_ant), the pheromone importance factor (alpha), and the heuristic importance factor (beta).

[0033] The method specifically includes:

[0034] Step 1: Utilize the diffraction effect of the grating to obtain the wavefront information of the beam reflected by the KB focusing mirror, and calculate the wavefront error value through wavefront reconstruction and fitting.

[0035] like Figure 3 As shown, the detector acquires a diffraction image modulated by a grating. After wavefront reconstruction, the wavefront height distribution in each dimension is obtained along the vertical and horizontal directions. Based on this, a quadratic polynomial is used for fitting, and the quadratic term of the fitting is removed to obtain the wavefront height residual. Finally, the residual value RMS is calculated. This RMS value is fed back into the ant colony-genetic algorithm as an evaluation index for individuals. Using this method, the ant colony algorithm traverses all individuals in the genetic algorithm population (each individual is a specific combination of KB mirror motion parameters) to find the order with the shortest total path. Then, the piezoelectric actuator is driven to modulate the motion dimensions of the KB focusing mirror sequentially according to the optimized shortest path order.

[0036] Subsequently, the light spot generated after grating diffraction is collected, data is acquired using a wavefront sensor, and the wavefront error value (RMS value as an example) under this attitude is calculated by wavefront reconstruction and polynomial fitting. This wavefront error value is the fitness value for evaluating the quality of this parameter combination.

[0037] Step 2: Construct a genetic algorithm population with multiple motion dimension parameters of the KB focusing lens as optimization variables, and use the ant colony algorithm to optimize the traversal order of individuals in the genetic algorithm population to determine the shortest mechanical motion path. This step is the core optimization loop:

[0038] like Figure 4 As shown, the genetic algorithm, based on the fitness values ​​(wavefront error) of all individuals in the obtained population, performs selection, crossover, and mutation operations to generate a new next-generation population. The ant colony algorithm, after each generation of new population is generated, abstracts the process of traversing all individuals in the population (i.e., testing all parameter combinations) into a path optimization problem. The ant colony uses a pheromone update mechanism to find and determine the traversal order of individuals that minimizes the total movement path of the actuator. This step specifically includes:

[0039] Population initialization: Using multiple motion dimension parameters of the KB focusing lens as genetic variables, an initial population of the genetic algorithm is generated within a preset parameter range, where each individual represents a specific combination of KB lens motion parameters;

[0040] Path optimization modeling: The process of traversing all individuals in the genetic algorithm population is abstracted into a path optimization problem, where the path length is defined by the total mechanical motion generated by the actuator switching between the KB mirror poses corresponding to different individuals;

[0041] Ant colony optimization: The ant colony algorithm is applied to solve the path optimization problem. By simulating the pheromone update and path selection mechanism of the ant colony, the shortest mechanical movement path sequence for traversing all individuals in the population is dynamically planned.

[0042] Order output: The shortest path order obtained by the ant colony algorithm optimization is used as the individual traversal order of the actuator to actually modulate the KB focusing lens.

[0043] This invention optimizes the population order of the motion parameters of the genetic algorithm by using the ant colony algorithm, making full use of the advantages of the two algorithms. The ant colony algorithm is good at finding the optimal path, while the genetic algorithm has a unique role in population evolution. The combination of the two improves the overall optimization effect.

[0044] Step 3: Using the wavefront error value as a feedback signal, drive the execution motor to sequentially modulate the attitude of the 8 motion dimensions of the KB focusing mirror according to the motion path order optimized by the ant colony algorithm, and at the same time collect the corresponding grating diffraction wavefront data. Repeat steps 1 to 3 for iterative optimization until the wavefront error value reaches the preset threshold.

[0045] The population optimized and sorted using the ant colony algorithm is used as the starting point for the next iteration. Steps 1-3 are repeated until the wavefront error converges to a preset threshold or the maximum number of iterations is reached. When the wavefront error approaches the target threshold (RMS ≤ 5nm), a local search strategy (such as reducing the parameter adjustment step size) can be used for final fine-tuning. Finally, the optimal KB mirror parameter combination that minimizes the wavefront error is output, and the actuator position is locked, completing the entire automated modulation process. This step specifically includes:

[0046] Closed-loop drive and measurement: Using the wavefront error value as a real-time feedback signal, the actuator is driven to strictly follow the motion path order optimized by the ant colony algorithm, and sequentially adjust the KB focusing lens to the posture corresponding to each individual in the population; under each posture, the wavefront data of the beam after diffraction by the grating is collected synchronously.

[0047] Fitness assessment and algorithm evolution: The wavefront data collected at each step is reconstructed and fitted to calculate the wavefront error value under the current posture, and this value is used as the fitness value of the corresponding individual; the genetic algorithm performs selection, crossover and mutation operations based on the fitness values ​​of all individuals to generate a new generation of optimized population;

[0048] Iterative convergence judgment: Repeat steps 1 to 3 to perform iterative optimization until one of the following convergence conditions is met: the calculated wavefront error value reaches or exceeds the preset nanometer threshold, or the number of algorithm iterations reaches the preset maximum limit.

[0049] Example:

[0050] The application scenario is based on the hard X-ray beamline (energy range 10-30 keV) of a high-energy synchrotron radiation facility.

[0051] The system's hardware configuration is as follows: The KB mirror is made of silicon-based platinum-plated material, with curvature radii of 50 meters for the horizontal mirror and 80 meters for the vertical mirror. The grating used for wavefront detection is a holographic grating with 1000 line pairs / mm and a size of 50×50 mm. The wavefront sensor is a Shack-Hartmann type with a 128×128 sub-aperture array to ensure a sufficient spatial sampling rate. The actuator is a nanometer-precision piezoelectric ceramic actuator with a stroke range of at least ±100 micrometers and a positioning resolution of up to 0.1 nanometers.

[0052] The automated modulation process is performed according to the following steps:

[0053] The first step is parameter initialization. Set the allowable adjustment range for each degree of freedom of the KB mirror (including the X-axis displacement, Z-axis displacement, roll angle, and pitch angle of the horizontal mirror, and the X-axis displacement, Y-axis displacement, Z-axis displacement, and pitch angle of the vertical mirror). Initialize the hybrid algorithm parameters: set the population size of the Genetic Algorithm (GA) to 20-80, the crossover probability (Pc) to 0.5, and the mutation probability (Pm) to 0.1; set the pheromone evaporation coefficient (ρ) of the Ant Colony Algorithm (ACO) to 0.5, and the heuristic factor (β) to 2.0. Set the convergence target for the root mean square (RMS) value of the wavefront error to ≤3 nanometers.

[0054] The second step is to initiate the closed-loop modulation process. After the system starts, it automatically acquires the beam wavefront information of the KB focusing lens in its initial state and calculates and saves the initial wavefront error value RMS.

[0055] The third step involves iterative optimization using a hybrid algorithm. The system then enters the core optimization loop:

[0056] Drive and Measurement: After the genetic algorithm generates a population containing multiple individuals (combinations of motion parameters for the KB focusing mirror), the ant colony algorithm first plans the shortest mechanical path to traverse these individuals. Subsequently, the system drives the piezoelectric actuator according to this path, sequentially adjusting the KB mirror to the posture corresponding to each individual, and simultaneously acquiring the grating diffraction spot.

[0057] Calculation and evaluation: Wavefront reconstruction and polynomial fitting are performed on each acquired diffraction spot to accurately calculate the wavefront error RMS value corresponding to the attitude of each KB mirror, which is used as the fitness value for evaluating the set of motion parameters.

[0058] Evolution and Optimization: Genetic algorithms perform selection, crossover, and mutation operations based on the fitness values ​​of all individuals to generate a new generation of the population. Ant colony algorithms, on the other hand, update pheromones based on the actual test results of the current round of traversal, providing an optimization basis for path planning of the next generation of the population.

[0059] Looping and Judgment: Repeat the above process until the wavefront error meets the convergence condition. In this embodiment, the wavefront error converged after about 30 iterations, reaching the experimental level.

[0060] The fourth step is to complete the modulation. Once the wavefront error reaches the preset threshold, the system outputs the optimal combination of KB mirror parameters, the piezoelectric actuator locks its position, and the modulation process ends. The entire automated process takes approximately 60 minutes, which is more than 10 times more efficient and significantly improves accuracy compared to traditional manual debugging methods (which typically take more than 10 hours).

[0061] In a second aspect, the present invention provides an electronic device comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned automated modulation method for a synchrotron beamline optical KB focusing mirror.

[0062] Thirdly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned automated modulation method for a synchrotron beamline optical KB focusing mirror.

[0063] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automated modulation method for a synchrotron beamline optical KB focusing mirror, characterized in that, include: Step 1: Utilize the diffraction effect of the grating to obtain the wavefront information of the beam reflected by the KB focusing mirror, and calculate the wavefront error value through wavefront reconstruction and fitting. Step 2: Construct a genetic algorithm population with multiple motion dimension parameters of the KB focusing lens as optimization variables, and use the ant colony algorithm to optimize the traversal order of individuals in the genetic algorithm population to determine the shortest mechanical motion path. Step 3: Using the wavefront error value as a feedback signal, drive the execution motor to sequentially modulate the attitude of the 8 motion dimensions of the KB focusing mirror according to the motion path order optimized by the ant colony algorithm, and at the same time collect the corresponding grating diffraction wavefront data. Repeat steps 1 to 3 for iterative optimization until the wavefront error value reaches the preset threshold.

2. The automated modulation method for a synchrotron beamline optical KB focusing mirror according to claim 1, characterized in that, In step 1, the wavefront error value is the root mean square error value of the wavefront phase distribution.

3. The automated modulation method for a synchrotron radiation beamline optical KB focusing mirror according to claim 1, characterized in that, In step 2, the motion dimension parameters of the KB focusing lens include at least the X-direction displacement, Z-direction displacement, ROLL angle, and Pitch angle of the horizontal focusing lens, and the X-direction displacement, Y-direction displacement, Z-direction displacement, and Pitch angle of the vertical focusing lens.

4. The automated modulation method for a synchrotron radiation beamline optical KB focusing mirror according to claim 1, characterized in that, Step 2 includes: Population initialization: Using multiple motion dimension parameters of the KB focusing lens as genetic variables, an initial population of the genetic algorithm is generated within a preset parameter range, where each individual represents a specific combination of KB focusing lens motion parameters; Path optimization modeling: The process of traversing all individuals in the genetic algorithm population is abstracted into a path optimization problem, where the path length is defined by the total mechanical motion generated by the actuator switching between the KB focusing lens postures corresponding to different individuals; Ant colony optimization: The ant colony algorithm is applied to solve the path optimization problem. By simulating the pheromone update and path selection mechanism of the ant colony, the shortest mechanical movement path sequence for traversing all individuals in the population is dynamically planned. Order output: The order of the shortest mechanical motion paths obtained by the ant colony algorithm optimization is used as the individual traversal order of the actuator to actually modulate the KB focusing lens.

5. An automated modulation method for a synchrotron radiation beamline optical KB focusing mirror according to claim 1, characterized in that, Step 3 includes: Closed-loop drive and measurement: Using the wavefront error value as a real-time feedback signal, the actuator motor is driven to adjust the KB focusing lens to the posture corresponding to each individual in the population in sequence according to the motion path order optimized by the ant colony algorithm; under each posture, the wavefront data of the beam after diffraction by the grating are collected synchronously. Fitness assessment and algorithm evolution: The wavefront data collected at each step is reconstructed and fitted to calculate the wavefront error value under the current posture, and the wavefront error value is used as the fitness value of the corresponding individual; the genetic algorithm performs selection, crossover and mutation operations based on the fitness values ​​of all individuals to generate a new generation of optimized population; Iterative convergence judgment: Repeat steps 1 to 3 to perform iterative optimization until the convergence condition is met.

6. An automated modulation method for a synchrotron beamline optical KB focusing mirror according to claim 5, characterized in that, The convergence condition is: the calculated wavefront error value reaches or is better than a preset threshold.

7. An automated modulation method for a synchrotron radiation beamline optical KB focusing mirror according to claim 6, characterized in that, When the wavefront error approaches the preset threshold, a local search strategy is activated to reduce the parameter adjustment step size for final fine-tuning.

8. An automated modulation method for a synchrotron radiation beamline optical KB focusing mirror according to claim 6, characterized in that, The preset threshold is root mean square error (RMS) ≤ 5nm.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement an automated modulation method for a synchrotron beamline optical KB focusing mirror as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement an automated modulation method for a synchrotron beamline optical KB focusing mirror as described in any one of claims 1-8.

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