Focus depth controllable Gaussian-Bessel beam generation method and device and storage medium

Abstract

The invention relates to a focus depth controllable Gaussian-Bessel beam generation method, a focus depth controllable Gaussian-Bessel beam generation device and a storage medium, and belongs to the technical field of laser processing. In the optimization process, a standard axicon phase corresponding to a target non-diffraction propagation length is introduced as a fixed initial value, the problems of slow convergence and uncontrollable focal depth caused by a random or zero initial value in a traditional method are avoided, rapid, flexible and controllable focal depth is realized, and by obtaining the actually measured light intensity along the optical axis direction, the target non-diffraction propagation length is optimized. Compared with numerical simulation light intensity point by point, a difference field matrix is constructed and fed back to an optimization process to iteratively update a phase function, so that not only is the uniformity of axial intensity improved, but also attenuation caused by tail energy collapse and environmental noise under a long focal depth condition is effectively inhibited, and the method has high robustness and practicability. The technology is suitable for scenes with extremely high requirements on uniformity and focal depth, such as laser precision processing, long focal depth microscopic imaging, optical communication and the like.

Description

Technical Field

[0001] This invention relates to the field of laser processing technology, and in particular to a method, apparatus and storage medium for generating Gaussian-Bessel beams with controllable depth of focus. Background Technology

[0002] In fields such as laser precision machining, microscopic imaging, particle manipulation, and optical communication, the spatial morphology and energy distribution of a light beam have a decisive impact on system performance. Bessel beams have attracted widespread attention due to their non-diffraction and long depth of focal length characteristics. An ideal non-diffraction beam can maintain a constant transverse intensity distribution during transmission and can self-recover after being partially blocked, thus showing great application potential in precision manufacturing and optical measurement.

[0003] However, Bessel beams directly generated from standard-axis pyramids have significant drawbacks. In terms of axial intensity distribution, they exhibit pronounced oscillatory characteristics, resulting in uneven energy distribution along the propagation direction. This non-uniformity is particularly detrimental in precision laser processing, where high-quality processing requires a stable and uniform axial energy distribution; otherwise, it can lead to decreased processing accuracy or insufficient consistency in the processed area.

[0004] To address the aforementioned issues, existing research has attempted to improve axial intensity uniformity through phase function optimization. For example, existing Gaussian-Bessel beam generation methods based on higher-order surfaces propose using higher-order polynomial phase functions instead of traditional linear axial pyramidal phase functions, which can improve beam uniformity to some extent. However, this method has two significant drawbacks: first, the initial phase distribution in the optimization process is usually set to all zero values ​​or random values, resulting in slow iterative convergence and excessive computational time and resources consumed in optimization calculations; second, the focal length of the optimized result lacks determinism, making it difficult to achieve flexible and controllable adjustment of the depth of focus; third, the optimization process lacks experimental feedback, failing to compensate for environmental noise in the actual optical path (such as tail collapse caused by vibration). These shortcomings prevent users from quickly obtaining Bessel beams with specified depth of focus and high uniformity in different processing scenarios, greatly limiting its practicality. Summary of the Invention

[0005] In view of this, it is necessary to provide a method, apparatus and storage medium for generating Gaussian-Bessel beams with controllable focal depth, so as to achieve the purpose of rapidly acquiring Bessel beams with a specified focal depth and high uniformity.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for generating Gaussian-Bessel beams with controllable focal depth, comprising: Based on the preset target non-diffraction propagation length, the phase delay function of the standard axis conical mirror is constructed; The initial population for the genetic algorithm is determined based on the phase delay function, and the cost function of the genetic algorithm is minimized by an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity along the optical axis. A difference field matrix is ​​constructed based on the numerically simulated light intensity and the measured light intensity. The difference field matrix is ​​then used as a constraint to minimize the cost function. The optimal radial phase function is iteratively updated to obtain the target phase function. Based on the target phase function, a Gaussian-Bessel beam with controllable focal depth is generated.

[0007] In one possible implementation, the cost function is determined in the following way: The intensity of the numerically simulated light was calculated based on Fresnel diffraction theory. The cost function is constructed based on the numerically simulated light intensity and the target light intensity distribution.

[0008] In one possible implementation, the measured light intensity is determined in the following way: Based on the optimal radial phase function, a phase hologram is generated; The phase hologram is loaded onto a spatial light modulator to form a light field, and the measured light intensity is obtained through a CCD camera.

[0009] In one possible implementation, the phase delay function is expressed as follows:

[0010] in, Indicates the beam waist radius and wavenumber. , Indicates the wavelength of the incident light beam. Indicates radius, This indicates the length of the target's non-diffraction propagation.

[0011] In one possible implementation, the expression for the difference field matrix is ​​as follows:

[0012] in, Indicates the first Numerical simulation of light intensity in the next iteration. Indicates the first The measured light intensity of the next iteration. Indicates the first indivual Sampling points on the axis This indicates the number of sampling points on the axis.

[0013] In one possible implementation, the cost function is expressed as follows:

[0014] in, Indicates the first indivual Sampling points on the axis Indicates the first indivual Numerical simulation of light intensity at sampling points on the axis Indicates the number of sampling points on the axis. This represents the desired target light intensity distribution.

[0015] Secondly, the present invention also provides a Gaussian-Bessel beam generating device with controllable focal depth, comprising: The building unit is used to construct the phase delay function of the standard axis conical mirror based on the preset target non-diffraction propagation length; An optimization unit is used to determine the initial population of the genetic algorithm based on the phase delay function, and to minimize the cost function of the genetic algorithm through an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity in the optical axis direction; The update unit is used to construct a difference field matrix based on the numerically simulated light intensity and the measured light intensity, and to minimize the cost function using the difference field matrix as a constraint, and iteratively update the optimal radial phase function to obtain the target phase function; The generation unit is used to generate a Gaussian-Bessel beam with controllable focal depth based on the target phase function.

[0016] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the depth-of-focus controllable Gaussian-Bessel beam generation method described in any of the above implementations.

[0017] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, is capable of implementing the steps in the depth-of-focus controllable Gauss-Bessel beam generation method described in any of the above implementations.

[0018] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the depth-of-focus controllable Gaussian-Bessel beam generation method described in any of the above implementations.

[0019] The beneficial effects of this invention are as follows: The Gaussian-Bessel beam generation method, apparatus, and storage medium with controllable focal depth provided by this invention introduce a standard-axis conical phase corresponding to the target's non-diffraction propagation length as a fixed initial value during the optimization process. This avoids the slow convergence and uncontrollable focal depth problems caused by random or zero initial values ​​in traditional methods, thereby achieving rapid, flexible, and adjustable focal depth. By acquiring the measured light intensity along the optical axis and comparing it point-by-point with the numerically simulated light intensity to construct a difference field matrix, this matrix is ​​fed back to the optimization process to iteratively update the phase function. This not only improves the uniformity of axial intensity but also effectively suppresses tail energy collapse and attenuation caused by environmental noise under long focal depth conditions, exhibiting high robustness and practicality. This technology is suitable for scenarios with extremely high requirements for uniformity and focal depth, such as laser precision machining, long focal depth microscopic imaging, and optical communication. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic flowchart of an embodiment of the depth-of-focus controllable Gaussian-Bessel beam generation method provided by the present invention; Figure 2 This is a schematic diagram of the optical path design provided by the present invention; Figure 3 A schematic diagram of the process for generating a high-uniform Gaussian-Bessel beam with controllable focal depth based on experimental-simulation closed-loop optimization provided by the present invention. Figure 4 A schematic diagram of the simulation results for Gaussian-Bessel beam axial optimization provided by this invention; Figure 5 A schematic diagram of the experimental results provided by this invention; Figure 6 A schematic diagram of an embodiment of the depth-of-focus controllable Gaussian-Bessel beam generation device provided by the present invention; Figure 7 A schematic diagram of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0024] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] This invention provides a method, apparatus, and storage medium for generating Gaussian-Bessel beams with controllable depth of focus, which will be described below.

[0027] Figure 1 A schematic flowchart of an embodiment of the depth-of-focus controllable Gaussian-Bessel beam generation method provided by the present invention is shown below. Figure 1 As shown, the method for generating Gaussian-Bessel beams with controllable depth of focus includes: S101. Based on the preset target non-diffraction propagation length, construct the phase delay function of the standard axis conical mirror; S102. Determine the initial population of the genetic algorithm based on the phase delay function, and minimize the cost function of the genetic algorithm through an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity in the optical axis direction; S103. Construct a difference field matrix based on the numerically simulated light intensity and the measured light intensity, and use the difference field matrix as a constraint to minimize the cost function, iteratively update the optimal radial phase function, and obtain the target phase function; S104. Based on the target phase function, generate a Gaussian-Bessel beam with controllable focal depth.

[0028] In S101, based on the target's non-diffraction propagation length, the phase delay function of the standard axis conical mirror that can generate Bessel beams with the same propagation length is determined as the initial phase distribution for the optimization algorithm, so as to achieve controllable adjustment of the depth of focus.

[0029] The fixed initial phase distribution is defined by the phase function of the standard axis conical mirror. Different standard phases correspond to different target non-diffraction propagation lengths, thereby achieving rapid and adjustable depth of focus.

[0030] In S102, a cost function is constructed by combining Fresnel diffraction theory with the target light intensity distribution. A hybrid optimization method combining genetic algorithm and unconstrained optimization algorithm is used to iteratively search for the optimal radial phase function in order to minimize the cost function and achieve the target light intensity distribution.

[0031] In the hybrid optimization algorithm, the population initialization of the genetic algorithm is based on the initial phase in step S101, which provides global search capability. The unconstrained optimization algorithm performs local fine search after the genetic algorithm converges. Combined with the fixed initial phase distribution, the convergence time can be significantly shortened and the optimization accuracy can be improved.

[0032] A hologram is generated based on the optimized phase function, and a light field is formed by loading the hologram through a spatial light modulator. The measured light intensity along the optical axis is obtained using a CCD camera.

[0033] In S103, the difference field matrix is ​​composed of the point-by-point relative deviation between the measured light intensity and the numerically simulated light intensity. The loss function of the genetic algorithm is embedded through closed-loop feedback to eliminate energy attenuation and axis deflection caused by optical path mismatch, mechanical vibration or temperature drift. This feedback is different from pure numerical differential residual judgment.

[0034] The measured light intensity is compared with the numerically simulated light intensity point by point to construct the difference field matrix. This difference field is then embedded into the cost function as a constraint condition. The phase function is iteratively updated through closed-loop feedback to suppress tail energy collapse at long focal depths.

[0035] A difference field matrix is ​​constructed based on the numerically simulated light intensity and the measured light intensity. The difference field matrix is ​​then used as a constraint to minimize the cost function. The optimal radial phase function is iteratively updated to obtain the target phase function. In S104, based on the target phase function obtained from the final update, high uniformity of beam axial intensity and stability at long focal depth are achieved, generating a Gaussian-Bessel beam with controllable focal depth.

[0036] In summary, the depth-of-focus Gaussian-Bessel beam generation method provided in this invention introduces a standard-axis conical phase corresponding to the target's non-diffraction propagation length as a fixed initial value during the optimization process. This avoids the slow convergence and uncontrollable depth-of-focus issues caused by random or zero initial values ​​in traditional methods, thus achieving rapid and flexible controllability of the depth of focus. By acquiring the measured light intensity along the optical axis and comparing it point-by-point with the numerically simulated light intensity to construct a difference field matrix, this matrix is ​​fed back to the optimization process to iteratively update the phase function. This not only improves the uniformity of axial intensity but also effectively suppresses tail energy collapse and attenuation caused by environmental noise under long depth-of-focus conditions, exhibiting high robustness and practicality. This technology is suitable for scenarios with extremely high requirements for uniformity and depth of focus, such as laser precision machining, long depth-of-focus microscopic imaging, and optical communication.

[0037] In some embodiments of the present invention, the expression for the phase delay function is as follows:

[0038] in, Indicates the beam waist radius and wavenumber. , Indicates the wavelength of the incident light beam. Indicates radius, This indicates the length of the target's non-diffraction propagation.

[0039] For example, the target non-diffraction propagation length is set to 600. mm 1000 mm 1400 mm The phase delay function of the standard axis conical mirror that can generate a Bessel beam with a corresponding propagation length is determined and used as the initial phase distribution for the optimization algorithm to achieve controllable adjustment of the depth of focus.

[0040] This step is crucial for solving the problem of depth-of-focus control in axially highly uniform Bessel beams. For the diffraction-free length requiring optimization, the corresponding standard-axis conical phase delay function that generates Bessel beams with the same propagation length is... t ( r ).

[0041] As shown in the above equation, the non-diffraction length is linearly related to the phase delay function of the standard axis conic mirror. Treating it as a high-order polynomial with zero higher-order terms can serve as the initial phase distribution for the optimization process. Existing methods use random or all-zero values ​​as initial values ​​for global search, resulting in long optimization times, highly random optimization effects, and an inability to achieve flexible depth-of-focus control.

[0042] This invention employs a fixed initial optimization value. Before and after optimization, the equivalent cone angle of the axial cone mirror remains almost unchanged, only the profile profile changes, ensuring that the optimization process converges within the predetermined depth of focus, resulting in a more efficient search. By selecting different initial optimization values, the depth of focus of axially highly uniform Bessel beams can be controlled.

[0043] In some embodiments of the present invention, the measured light intensity is determined in the following manner: Based on the optimal radial phase function, a phase hologram is generated; The phase hologram is loaded onto a spatial light modulator to form a light field, and the measured light intensity is obtained through a CCD camera.

[0044] A hologram is generated based on the optimized phase function, and a light field is formed by loading the hologram through a spatial light modulator. The measured light intensity along the optical axis is obtained using a CCD camera.

[0045] Using the solved phase delay function, a phase hologram is generated and loaded onto a programmable diffractive optical device, i.e., a spatial light modulator. An optical path system is then designed for experimentation. For example... Figure 2 This is a schematic diagram of the optical path design provided by the present invention. The optical path is as follows: Figure 2 As shown.

[0046] The components are listed below according to the beam propagation trajectory: 1. Laser, 2. Polarizer, 3. Attenuator, 4. First reflector, 5. Second reflector, 6. Programmable diffractive optical device (spatial light modulator), 7. First lens, 8. Third reflector, 9. Fourth reflector, 10. Second lens, 11. Motion guide rail, 12. CCD (camera).

[0047] In the optical path design, to reduce the working distance of the moving guide rail, this design uses a first lens ( ), and the second lens ( A 4f system is formed to compress the depth of focus of the Gaussian-Bessel beam and shorten the axial working distance without changing the beam energy and quality. A motion guide rail is used to control the CCD camera at 0.2... Data is collected at regular intervals.

[0048] In some embodiments of the present invention, the cost function is determined in the following manner: The intensity of the numerically simulated light was calculated based on Fresnel diffraction theory. The cost function is constructed based on the numerically simulated light intensity and the target light intensity distribution.

[0049] In some embodiments of the present invention, the expression of the cost function is as follows:

[0050] in, Indicates the first indivual Sampling points on the axis Indicates the first indivual Numerical simulation of light intensity at sampling points on the axis Indicates the number of sampling points on the axis. This represents the desired target light intensity distribution.

[0051] In some embodiments of the present invention, the expression for the difference field matrix is ​​as follows:

[0052] in, Indicates the first Numerical simulation of light intensity in the next iteration. Indicates the first The measured light intensity of the next iteration. Indicates the first indivual Sampling points on the axis This indicates the number of sampling points on the axis.

[0053] This invention first generates an initial phase population using a genetic algorithm (GA), and uses a specified depth of focus as a hard design constraint. The loss function of GA is defined as:

[0054] in, The intensity of the i-th sampling point on the z-axis is calculated using the Fresnel diffraction formula. m It is the number of sampling points on the axis. M The desired uniform intensity distribution is achieved. After GA convergence, the final optimal phase function is propagated through a rigorous numerical model to obtain the simulated axial intensity, which is then encoded into a phase-type spatial light modulator (SLM) for experimental implementation.

[0055] The simulation intensity of the k-th iteration is denoted as Experimental intensity Recorded by a CCD camera. Then, the relative deviation for the k-th iteration is calculated:

[0056] in, z This represents the axial sampling point. To ensure consistency of the difference field, the simulation step size is set to be the same as the physical sampling interval, thus making the simulated and measured axial intensity vectors the same length. The difference field matrix is ​​then embedded in the GA loss function:

[0057] in It is the first k The target matrix of the next iteration γ This is the intensity compensation coefficient for experimental calibration. Iteration continues until the deviation falls below the preset convergence threshold.

[0058] This dynamic compensation strategy effectively suppresses tail energy collapse in long focal depth, high uniformity Bessel beams by iteratively updating the phase function through closed-loop feedback, thus ensuring axial intensity uniformity in the actual optical path.

[0059] Figure 3 This is a flowchart illustrating the depth-controllable, highly uniform Gaussian-Bessel beam generation method based on experimental-simulation closed-loop optimization provided by the present invention. This method combines a fixed initial phase distribution of the standard-axis conical mirror with difference field feedback compensation in the experimental-simulation closed loop, achieving flexible and controllable adjustment of the beam's focal depth and high uniformity under long focal depth conditions. Figure 3 As shown, the embodiments of the present invention and their implementation process are as follows: Step S301: Set the target non-diffraction propagation length to 600. mm 1000 mm 1400 mm The phase delay function of the standard axis conical mirror that can generate Bessel beams with corresponding propagation lengths is determined and used as the initial phase distribution for the optimization algorithm to achieve controllable adjustment of the depth of focus; Step S302: Construct a cost function by combining Fresnel diffraction theory with the target light intensity distribution, and use a hybrid optimization method combining genetic algorithm and unconstrained optimization algorithm to iteratively search for the optimal radial phase function; Step S303: Generate a hologram based on the optimized phase function, and load the hologram through a spatial light modulator to form a light field; Step S304: Use a CCD camera to acquire the measured light intensity along the optical axis, compare it point by point with the numerical simulation light intensity, construct the difference field matrix, and embed the difference field as a constraint condition into the cost function, feed it back to the optimization process to iteratively update the phase function, so as to improve the uniformity of the beam axial intensity and the stability at long focal depths.

[0060] Step S301 is crucial for solving the problem of depth-of-focus control in axially highly uniform Bessel beams. For the diffraction-free length requiring optimization, the corresponding standard-axis conical phase delay function that generates Bessel beams with the same propagation length is... t ( r )for:

[0061] in, ω The beam waist radius and wavenumber are given. , It is the wavelength of the incident light beam. It is the radius, Z max The target has no diffraction length.

[0062] As shown in the above equation, the non-diffraction length is linearly related to the phase delay function of the standard-axis cone. Treating it as a high-order polynomial with zero higher-order terms can serve as the initial phase distribution for the optimization process. Existing methods use random or all-zero values ​​as initial optimization values ​​for global searching, resulting in long optimization times, highly random optimization effects, and an inability to achieve flexible depth-of-focus control. This invention uses a fixed initial optimization value. Before and after optimization, the equivalent cone angle of the axial cone remains almost unchanged; only the profile profile changes, ensuring convergence of the optimization process within the predetermined depth-of-focus range and making the search more efficient. By selecting different initial optimization values, the depth-of-focus of axially highly uniform Bessel beams can be controlled.

[0063] This invention uses a combined feedback optimization algorithm of genetic algorithm and unconstrained optimization algorithm to search for the optimal radial phase delay, and solves the phase delay function by minimizing the cost function to obtain the coefficient values ​​of each term of the higher-order surface.

[0064] This invention requires optimizing various coefficients in higher-order surfaces. The more optimization terms there are, the longer the algorithm runs; too few optimization terms will result in insufficient fitting of the higher-order surface, making it difficult to achieve the desired effect. Therefore, in this invention, the optimization time and results under different orders were compared and weighed, and a quartic surface was ultimately selected as more suitable.

[0065] Figure 4 This is a schematic diagram of the simulation results for Gaussian-Bessel beam axial optimization provided by the present invention. The simulation results obtained from the embodiment are as follows: Figure 4 As shown, Figure 4 (a), (b), and (c) in the text correspond to 600 respectively. mm 1000 mm 1400 mm Axial intensity distribution of Gaussian-Bessel beams Figure 4 (d), (e), and (f) in the diagram correspond to their respective phase holograms.

[0066] Using the solved phase delay function, a phase hologram is generated and loaded onto a programmable diffractive optical device, i.e., a spatial light modulator. An optical path system is then designed for experimentation. The optical path is as follows: Figure 2 As shown.

[0067] Step S304 is crucial for resolving the axial intensity non-uniformity problem caused by alignment errors in actual optical paths. In actual optical paths, factors such as temperature drift, mechanical vibration, air dust, and residual alignment errors collectively cause beam axis deflection. This tilted wavefront introduces an asymmetric phase factor, disrupting the spatial frequency mapping of diffraction, thereby causing a shift and broadening of the Fourier spectrum of the simulated phase function. As the depth of focus increases, this wavefront mismatch is further amplified, leading to tail energy collapse in long depth-of-focus beams.

[0068] To address this issue, this invention proposes a differential field feedback strategy based on an experiment-simulation closed loop. Specifically, an initial phase population is first generated using a genetic algorithm, with a predetermined depth of focus serving as a hard design constraint. The loss function of the GA is defined as:

[0069] in, The intensity of the i-th sampling point on the z-axis is calculated using the Fresnel diffraction formula. m It is the number of sampling points on the axis. M The desired uniform intensity distribution is achieved. After GA convergence, the final optimal phase function is propagated through a rigorous numerical model to obtain the simulated axial intensity, which is then encoded into a phase-type spatial light modulator (SLM) for experimental implementation.

[0070] The simulation intensity of the k-th iteration is denoted as Experimental intensity Recorded by a CCD camera. Then, the relative deviation for the k-th iteration is calculated:

[0071] in, z This represents the axial sampling point. To ensure consistency of the difference field, the simulation step size is set to be the same as the physical sampling interval, thus making the simulated and measured axial intensity vectors the same length. The difference field matrix is ​​then embedded in the GA loss function:

[0072] in It is the first k The target matrix of the next iteration γ This is the intensity compensation coefficient for experimental calibration. Iteration continues until the deviation falls below the preset convergence threshold.

[0073] This dynamic compensation strategy effectively suppresses tail energy collapse in long focal depth, high uniformity Bessel beams by iteratively updating the phase function through closed-loop feedback, thus ensuring axial intensity uniformity in the actual optical path.

[0074] Figure 5This is a schematic diagram of the experimental results provided by the present invention. The experimental results are as follows: Figure 5 As shown. Figure 5 In figures (a), (b), and (c), the two fitted curves represent the 600 curves that have undergone preliminary optimization according to this invention but have not been compensated for by experimental-simulation feedback. , 1000 1500 Simulation and experimental results of Gaussian-Bessel beams are compared. Clearly, with increasing axial distance, there is a significant tail collapse in the intensity distribution, a phenomenon that intensifies with increasing depth of focus.

[0075] Figure 5 Figures (d), (e), and (f) show a comparison of the experimental results before and after experimental-simulation feedback compensation under three different diffraction distances. Through the feedback compensation of this invention, the on-axis intensity was further adjusted.

[0076] Figure 5 Figures (g), (h), and (i) in the figure compare the axial intensity distribution generated by the standard axis conic mirror with the same non-diffraction distance and the axial intensity distribution after complete optimization by the present invention. The uniformity of axial intensity is greatly improved without changing the non-diffraction distance.

[0077] The method described in this invention, based on the linear relationship between the maximum non-diffraction distance and the phase delay function of the standard-axis conical mirror, begins optimization with a fixed initial phase distribution. This significantly accelerates algorithm convergence and improves stability. While ensuring high axial uniformity of the Gaussian-Bessel beam, it greatly enhances the flexible control capability of its focal depth, allowing for rapid adjustment according to actual processing requirements. Simultaneously, through experimental-simulation closed-loop difference field feedback, it achieves coupling between numerical optimization and physical experiments, improving the robustness of optical field control under ultra-long focal depth conditions (greater than 1000). This method can effectively suppress tail energy decay and obtain a highly uniform axial light field distribution. It is suitable for scenarios with extremely high requirements for depth of focus control and uniformity, such as laser precision processing, long focal depth microscopy, and deep optical communication.

[0078] To better implement the depth-of-focus controllable Gaussian-Bessel beam generation method in this invention embodiment, based on the depth-of-focus controllable Gaussian-Bessel beam generation method, correspondingly, as... Figure 6 As shown, this embodiment of the invention also provides a Gaussian-Bessel beam generating device with controllable depth of focus. The Gaussian-Bessel beam generating device 600 with controllable depth of focus includes: The construction unit 601 is used to construct the phase delay function of the standard axis conical mirror based on the preset target non-diffraction propagation length; The optimization unit 602 is used to determine the initial population of the genetic algorithm based on the phase delay function, and to minimize the cost function of the genetic algorithm through an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity in the optical axis direction. Update unit 603 is used to construct a difference field matrix based on the numerically simulated light intensity and the measured light intensity, and use the difference field matrix as a constraint to minimize the cost function, iteratively update the optimal radial phase function, and obtain the target phase function; The generation unit 604 is used to generate a Gaussian-Bessel beam with controllable focal depth based on the target phase function.

[0079] The depth-of-focus controllable Gaussian-Bessel beam generating device 600 provided in the above embodiments can realize the technical solutions described in the embodiments of the depth-of-focus controllable Gaussian-Bessel beam generating method. The specific implementation principles of each module or unit can be found in the corresponding content in the embodiments of the depth-of-focus controllable Gaussian-Bessel beam generating method, which will not be repeated here.

[0080] like Figure 7 As shown, the present invention also provides an electronic device 700. The electronic device 700 includes a processor 701, a memory 702, and a display 703. Figure 7 Only some components of the electronic device 700 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0081] In some embodiments, processor 701 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 702 or process data, such as the depth-of-focus controllable Gauss-Bessel beam generation method of the present invention.

[0082] In some embodiments, processor 701 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 701 may be local or remote. In some embodiments, processor 701 may be implemented on a cloud platform. In some embodiments, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, or any combination thereof.

[0083] In some embodiments, memory 702 may be an internal storage unit of electronic device 700, such as a hard disk or memory of electronic device 700. In other embodiments, memory 702 may also be an external storage device of electronic device 700, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 700.

[0084] Furthermore, the memory 702 may include both internal storage units of the electronic device 700 and external storage devices. The memory 702 is used to store application software and various types of data installed on the electronic device 700.

[0085] In some embodiments, display 703 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an organic light-emitting diode (OLED) touchscreen. Display 703 is used to display information from electronic device 700 and to display a visual user interface. Components 701-703 of electronic device 700 communicate with each other via a system bus.

[0086] In one embodiment, when processor 701 executes the depth-of-focus controllable Gaussian-Bessel beam generation program in memory 702, the following steps can be implemented: Based on the preset target non-diffraction propagation length, the phase delay function of the standard axis conical mirror is constructed; The initial population for the genetic algorithm is determined based on the phase delay function, and the cost function of the genetic algorithm is minimized by an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity along the optical axis. A difference field matrix is ​​constructed based on the numerically simulated light intensity and the measured light intensity. The difference field matrix is ​​then used as a constraint to minimize the cost function. The optimal radial phase function is iteratively updated to obtain the target phase function. Based on the target phase function, a Gaussian-Bessel beam with controllable focal depth is generated.

[0087] It should be understood that when the processor 701 executes the depth-of-focus controllable Gauss-Bessel beam generation program in the memory 702, in addition to the functions mentioned above, it can also perform other functions, as can be found in the description of the corresponding method embodiments above.

[0088] Furthermore, the embodiments of the present invention do not specifically limit the type of electronic device 700 mentioned. Electronic device 700 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, electronic device 700 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0089] Accordingly, embodiments of the present invention also provide a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the depth-of-focus controllable Gauss-Bessel beam generation method provided in the above-described method embodiments.

[0090] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to perform the steps or functions in the depth-of-focus controllable Gauss-Bessel beam generation method provided in the above-described method embodiments.

[0091] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0092] The above provides a detailed description of the method, apparatus, and storage medium for generating Gaussian-Bessel beams with controllable depth of focus provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for generating Gaussian-Bessel beams with controllable depth of focus, characterized in that, include: Based on the preset target non-diffraction propagation length, the phase delay function of the standard axis conical mirror is constructed; The initial population for the genetic algorithm is determined based on the phase delay function, and the cost function of the genetic algorithm is minimized by an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity along the optical axis. A difference field matrix is ​​constructed based on the numerically simulated light intensity and the measured light intensity. The difference field matrix is ​​then used as a constraint to minimize the cost function. The optimal radial phase function is iteratively updated to obtain the target phase function. Based on the target phase function, a Gaussian-Bessel beam with controllable focal depth is generated.

2. The method for generating Gaussian-Bessel beams with controllable depth of focus according to claim 1, characterized in that, The cost function is determined in the following way: The intensity of the numerically simulated light was calculated based on Fresnel diffraction theory. The cost function is constructed based on the numerically simulated light intensity and the target light intensity distribution.

3. The method for generating Gaussian-Bessel beams with controllable depth of focus according to claim 1, characterized in that, The measured light intensity was determined in the following way: Based on the optimal radial phase function, a phase hologram is generated; The phase hologram is loaded onto a spatial light modulator to form a light field, and the measured light intensity is obtained through a CCD camera.

4. The method for generating Gaussian-Bessel beams with controllable focal depth according to claim 1, characterized in that, The expression for the phase delay function is as follows: in, Indicates the beam waist radius and wavenumber. , Indicates the wavelength of the incident light beam. Indicates radius, This indicates the length of the target's non-diffraction propagation.

5. The method for generating Gaussian-Bessel beams with controllable depth of focus according to claim 1, characterized in that, The expression for the difference field matrix is ​​as follows: in, Indicates the first Numerical simulation of light intensity in the next iteration. Indicates the first The measured light intensity of the next iteration. Indicates the first indivual Sampling points on the axis This indicates the number of sampling points on the axis.

6. The method for generating Gaussian-Bessel beams with controllable focal depth according to claim 1, characterized in that, The expression for the cost function is as follows: in, Indicates the first indivual Sampling points on the axis Indicates the first indivual Numerical simulation of light intensity at sampling points on the axis Indicates the number of sampling points on the axis. This represents the desired target light intensity distribution.

7. A Gaussian-Bessel beam generation device with controllable depth of focus, characterized in that, include: The building unit is used to construct the phase delay function of the standard axis conical mirror based on the preset target non-diffraction propagation length; An optimization unit is used to determine the initial population of the genetic algorithm based on the phase delay function, and to minimize the cost function of the genetic algorithm through an unconstrained algorithm to obtain the optimal radial phase function; the optimal radial phase function is used to determine the measured light intensity in the optical axis direction; The update unit is used to construct a difference field matrix based on the numerically simulated light intensity and the measured light intensity, and to minimize the cost function using the difference field matrix as a constraint, and iteratively update the optimal radial phase function to obtain the target phase function; The generation unit is used to generate a Gaussian-Bessel beam with controllable focal depth based on the target phase function.

8. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is configured to execute the program stored in the memory to implement the steps in the depth-of-focus controllable Gaussian-Bessel beam generation method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the depth-of-focus controllable Gauss-Bessel beam generation method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps in the depth-of-focus controllable Gaussian-Bessel beam generation method as described in any one of claims 1 to 6.

Images