Angularly resolved energy band reconstruction method and system based on event-type delay line detector output

Abstract

The application discloses an angular resolution energy band reconstruction method and system based on event type delay line detector output, and relates to the technical field of angular resolution photoelectron spectrum data processing. The method comprises the following steps: an event data acquisition step, in which discrete photoelectron events containing spatial coordinate information and event identification information are acquired by an event type delay line detector; a detection region identification step, in which events are attributed to corresponding detection regions or channels according to the event identification information or the spatial coordinate information; a region correction step, in which geometric correction and response correction are respectively performed on events in different regions or channels to eliminate systematic differences between regions; a coordinate mapping step, in which corrected event coordinates are mapped to energy-momentum coordinate space based on a preset dispersion relationship of an angular resolution energy analyzer; and an energy band reconstruction step, in which mapped events are statistically accumulated to reconstruct an angular resolution energy band distribution diagram.

Description

Technical Field

[0001] This invention relates to the field of angle-resolved photoelectron spectroscopy data processing and measurement methods, specifically to an angle-resolved band reconstruction method and system for output data of event-type delay line detectors. Background Technology

[0002] Angle-resolved photoemission spectroscopy (ARPES) is an important experimental technique for studying the electronic structure of materials. Its basic principle is to reconstruct the energy distribution of electrons in momentum space, i.e., the band structure, by measuring the kinetic energy and emission angle of photoelectrons in a sample. In traditional ARPES systems, photoelectrons are sorted by an angle-resolved energy analyzer, and the intensity distribution is recorded on the imaging plane by a detector using an integral method. The resulting data is typically a continuous two-dimensional or three-dimensional intensity image. Based on this integral detection data, the band structure reconstruction process can be directly accomplished using the geometric parameters and dispersion relations of the energy analyzer, and the relevant methods are relatively mature.

[0003] With the development of detection technology, event-based detectors have been gradually introduced into the field of photoelectron spectroscopy. Event-based detectors, represented by delay-line detectors, no longer output a continuous intensity distribution, but rather consist of multiple discrete photoelectron events. Each event typically contains spatial coordinate information and may further include temporal information or channel identification information. This type of detection method has significant advantages in multi-event resolution and time-resolved measurements, and therefore has been widely used in photoelectron momentum imaging and time-resolved photoelectron spectroscopy.

[0004] However, the change in the output data format of event-type detectors also brings new challenges to band structure reconstruction. First, event-type data exists as discrete events, and different events are not continuously distributed in time and space, making traditional pixel-integral-based reconstruction methods difficult to apply directly. Second, in practical systems, event-type detectors often have multiple detection regions or channels, and there may be systematic differences in geometric response, detection sensitivity, or temporal response between different regions. If these differences are not effectively handled, they will directly affect the accuracy of the band structure reconstruction results. Furthermore, the dispersion relation of angle-resolved energy analyzers is usually established based on a continuous detection plane. When the detector output is transformed into discrete event coordinates, the mapping relationship between detector coordinates and energy and momentum needs to be re-established, especially in the presence of multi-region stitching and response non-uniformity, making the mapping process even more complex.

[0005] Therefore, how to achieve accurate and reliable angle-resolved bandgap reconstruction for discrete optoelectronic event data output by event-type delay line detectors has become an urgent technical problem to be solved. Summary of the Invention

[0006] The present invention aims to solve the above-mentioned technical problems existing in the prior art, and provides a method and system for accurate and reliable angle-resolved bandgap reconstruction of discrete optoelectronic event data output by event-type delay line detectors.

[0007] To achieve the above objectives, this invention provides an angle-resolved bandgap reconstruction method based on the output of an event-type delay line detector, comprising the following steps: Event data acquisition steps: Acquire photoelectron event data through an event-type delay line detector. The event data includes multiple discrete photoelectron events, and each photoelectron event contains at least spatial coordinate information and event identification information. Detection area identification step: Based on the event identification information or the spatial coordinate information, each photoelectron event is assigned to the corresponding detection area or channel; Regional calibration steps: Geometric calibration and response calibration are performed on the photoelectron events in different detection regions or channels respectively to eliminate systematic differences between different detection regions or channels; Coordinate mapping step: Based on the preset dispersion relation of the angle-resolved energy analyzer, the spatial coordinates of the corrected photoelectron events are mapped to the energy-momentum coordinate space to obtain the energy value and momentum value corresponding to each photoelectron event; Band reconstruction step: Based on the mapped energy-momentum coordinates, statistical accumulation is performed on all the photoelectron events to reconstruct the angle-resolved band distribution map.

[0008] Furthermore, in the region correction step, the geometric correction includes performing at least one of coordinate translation, rotation, stretching, or affine transformation on the detection region where there is geometric distortion or signal loss, in order to compensate for the geometric position deviation between different detection regions.

[0009] Furthermore, in the regional correction step, the response correction includes normalizing the detection sensitivity of different detection regions based on the reference spectral line characteristics to eliminate the difference in response sensitivity between different detection regions.

[0010] Furthermore, the photoelectronic event also includes a time stamp, and the area correction step further includes time correction to compensate for time response differences between different detection areas or channels based on the time stamp of the photoelectronic event.

[0011] Furthermore, in the coordinate mapping step, the dispersion relation is obtained through experimental calibration or a theoretical model; the experimental calibration includes: calibrating the mapping relationship between angular coordinates and detector coordinates by changing the analyzer bias scanning imaging boundary, and / or calibrating the mapping relationship between energy coordinates and detector coordinates by changing the electron kinetic energy scanning Fermi edge position.

[0012] Furthermore, in the band reconfiguration step, a two-dimensional or three-dimensional energy-momentum distribution is obtained through cumulative statistics or weighted statistics of the photoelectron events.

[0013] The present invention also provides an angle-resolved bandgap reconstruction system based on the output of an event-type delay line detector, comprising: An event-type detection data input module is used to acquire photoelectronic event data, which includes multiple discrete photoelectronic events, and each photoelectronic event includes at least spatial coordinate information and event identification information. The detection area identification module is used to assign events to corresponding detection areas or channels based on event identification information or spatial coordinate information. The region correction module is used to perform geometric and response corrections on the photoelectronic events in different detection regions; The coordinate mapping module is used to map the corrected spatial coordinates of the photoelectron event to the energy-momentum coordinate space based on the dispersion relation of the angle-resolved energy analyzer. The band reconstruction module is used to perform statistical analysis or accumulation of the photoelectron events based on the mapped energy-momentum coordinates to obtain the angle-resolved band distribution.

[0014] Furthermore, the photoelectronic event also includes a time stamp; the correction performed by the region correction module also includes time correction to compensate for the time response differences between different detection regions or channels based on the time stamp of the photoelectronic event.

[0015] Furthermore, in the coordinate mapping module, the dispersion relation is obtained through experimental calibration or a theoretical model; the experimental calibration includes: calibrating the mapping relationship between angular coordinates and detector coordinates by changing the analyzer bias scanning imaging boundary, and / or calibrating the mapping relationship between energy coordinates and detector coordinates by changing the position of the electron kinetic energy scanning Fermi edge.

[0016] Furthermore, the band reconstructing module obtains two-dimensional or three-dimensional energy-momentum distributions through event accumulation statistics or weighted statistics, and can display them in real time or process them offline.

[0017] Compared with the prior art, the present invention has the following beneficial effects: By establishing a complete reconstruction process from discrete photoelectron events to band distribution, the technical barrier that traditional reconstruction methods based on continuous integral images cannot directly process discrete event data has been overcome, and the effective utilization of event-type detection data has been realized.

[0018] By performing detection region identification and region correction steps, geometric correction and response correction are applied to event data from different detection regions or channels, effectively eliminating systematic errors such as geometric distortion and sensitivity differences caused by the multi-region structure of the detector, and ensuring the consistency and accuracy of band reconstruction.

[0019] Through the coordinate mapping step, based on the preset dispersion relation of the angle-resolved energy analyzer, the corrected event coordinates are mapped to the energy-momentum coordinate space, establishing an accurate correspondence between the detector coordinates and physical quantities (energy and momentum), and realizing the transformation from raw detection data to physically interpretable results.

[0020] By statistically accumulating the mapped events through the band reconstruction step, discrete event data is transformed into a continuous band distribution map, thus fully realizing the entire process reconstruction from the output of the event-type detector to the angle-resolved band distribution. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the reconstruction process from event-type detection data to band coordinates in this invention.

[0022] Figure 2 This is a schematic diagram of the boundary displacement and angle calibration under bias scanning according to the present invention.

[0023] Figure 3 This is a schematic diagram illustrating the calibration of the energy dispersion coefficient at the Fermi edge position in this invention.

[0024] Figure 4 This is a schematic diagram illustrating the compensation and band reconstruction of the missing signal at the center of the detection region in this invention.

[0025] Figure 5 This is a schematic diagram of the Fermi edge of the detection area of ​​the present invention being flattened.

[0026] Figure 6 This is a block diagram of the angle-resolved bandgap reconstruction system based on the output of an event-type delay line detector according to the present invention. Detailed Implementation

[0027] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0028] This invention aims to achieve accurate and reliable angle-resolved bandgap reconstruction of discrete photoelectron event data output from event-type delay line detectors. This invention provides an angle-resolved bandgap reconstruction method based on the output of an event-type delay line detector, the process of which is as follows: Figure 1 As shown. The specific steps are as follows: (1) Event data acquisition steps Photoelectronic event data is acquired using an event-based delay line detector. Each event is recorded as (startctr, x, y, t), where startctr is the external trigger cycle number, x and y are the two-dimensional spatial coordinates of the detector, and t is the timestamp relative to the start of the cycle. These events are stored in list form, constituting the event data. The event data includes multiple discrete photoelectronic events, each of which contains at least spatial coordinate information (x, y) and event identification information (such as startctr, t, or a region identifier).

[0029] In this embodiment, the delay line detector has a dual-region structure. The effective imaging surface of the detector is composed of two microchannel plates (MCPs) spliced ​​together, with a signal loss band of approximately 70 channels in between. In the raw event data output by the detector, the x-coordinate range of each event is 0-1024 channels, and the y-coordinate range is 0-1024 channels.

[0030] (2) Detection area identification steps Based on event identification information or spatial coordinate information, each photoelectron event is assigned to a corresponding detection area or channel. In this embodiment, the detector has a dual-region structure, and the x-coordinate in the spatial coordinate information of the photoelectron event is used for region determination. Based on the range of x-coordinate values, the photoelectron events are divided into: Left region: x ≤ 470 channels; Missing region: 471 ≤ x ≤ 540 channels (events in this region can be marked as invalid or ignored); Right side region: x ≥ 541 channels; Events with missing middle regions can be removed or compensated for by interpolation in subsequent processing. In this embodiment, they are marked and ignored.

[0031] In this embodiment, the attribution of photoelectronic events is determined directly using spatial coordinate information; in other embodiments, if the event identification information contains clear area identification information (left area or right area), the attribution can also be determined directly based on the event identification information.

[0032] (3) Regional calibration steps Geometric and response corrections are performed on photoelectron events in different detection regions or channels to eliminate systematic differences between them. The corrections include: a) Geometric correction: For the missing middle band, apply segmented lateral displacement correction to the data on both the left and right sides respectively. For example... Figure 4As shown, the reference imaging state is first obtained under the condition that the analyzer x-bias is 10°. Figure 4 In (a) of the diagram, the band structure is continuously imaged on the detector surface to determine the ideal stitching position. Subsequently, under normal measurement conditions (x-bias voltage of 0°), imaging data with a central missing band is obtained. Figure 4 (b)). By comparing with the reference state, it was determined that the left region needs to be shifted 45 channels to the right, and the right region needs to be shifted 25 channels to the left, so that the data on both sides are stitched together in the x-direction, compensating for the missing central region and restoring the continuous band distribution. Figure 4 (c)). The new coordinates x′ after translation are calculated as follows: For events in the left region: x′ = x + 45; For events in the right-hand region: x′ = x - 25; For events with missing middle regions: they will not participate in subsequent processing.

[0033] b) Response correction: Energy benchmark unification based on Fermi edge characteristics. For example... Figure 5 As shown, the Fermi edges in the left and right regions are tilted or bent before correction. Figure 5 (a) is due to differences in detection sensitivity and geometric distortion in different regions. This embodiment performs response correction through the following steps: First, reference data is collected near the Fermi level to extract the actual location of the Fermi edge in each region. For each region, a scan along the y-direction is performed to obtain the curve of photoelectron intensity versus the y-coordinate. The y-coordinate corresponding to the Fermi edge is then determined by fitting the curve. f,left and y f,right Ideally, the Fermi edge should be a horizontal straight line, i.e., y = 0. f It should be a constant.

[0034] Secondly, correction functions are obtained by fitting them to the left and right regions respectively. Assume the Fermi edge position y in the left region is... f,left The y-coordinate changes linearly with the original y-coordinate: f,left = a left · y + b left The response correction for the left region is: y′ = (yb left ) / a left Similarly, the response correction for the right-hand region is: y′ = (yb right ) / a right , where a right b right These are the fitting parameters for the right-hand region.

[0035] In this embodiment, the left region is fitted to obtain a. left = 1.02, b left= -10, meaning the left region needs to be compressed downwards by approximately 2% and shifted upwards by 10 channels; the right region is fitted to obtain a. right = 0.98, b right = 15, meaning the right-side area needs to be stretched upwards by about 2% and shifted downwards by 15 channels.

[0036] After geometric and response corrections, the corrected event coordinates (x′, y′) are obtained. The correction parameters can be obtained through pre-calibration (as shown in this embodiment) or dynamically updated based on experimental data during the measurement process.

[0037] By employing detection area identification and area correction steps, event data from different detection areas or channels undergo independent geometric and response corrections, effectively eliminating systematic errors such as geometric distortion, sensitivity differences, and non-uniform response caused by the multi-region structure of the detector. For example... Figure 4 (c) and Figure 5 As shown in (b) in the figure, after correction, the data that originally had missing central bands or tilted Fermi edges can be restored to a continuous and flat band distribution, which significantly improves the consistency and accuracy of band reconstruction.

[0038] (4) Coordinate mapping steps Based on the preset dispersion relation of the angle-resolved energy analyzer, the spatial coordinates (x′, y′) of the corrected photoelectron events are mapped to the energy-momentum coordinate space to obtain the energy and momentum values ​​corresponding to each photoelectron event. The specific calibration process is as follows: a) Angle calibration: such as Figure 2 As shown, by changing the analyzer's x-direction bias (-4°, -2°, 0°, 2°, 4°), the displacement of the imaging boundary in the detector's x-direction is obtained. For each bias setting, a Fermi surface image of the reference sample is acquired, and the x-coordinate of the effective imaging boundary is extracted. A linear relationship between the boundary displacement Δx and the angle change Δθ is established, and the unit channel angular resolution Δθ is obtained by fitting. In this embodiment, Δθ = 0.057 deg / channel.

[0039] Using the detector's central channel x0 = 512 in the x-direction as a reference, the angle mapping relationship is obtained as follows: θ = Δθ × (x′ - x0); b) Energy calibration: such as Figure 3 As shown, by changing the set electronic kinetic energy E k (2.30 eV, 2.31 eV, 2.32 eV, 2.33 eV, 2.34 eV), obtain the channel coordinates y of the Fermi edge in the y-direction of the detector. f For each kinetic energy setting, acquire a Fermi surface image and extract the y-coordinate corresponding to the Fermi edge. Using y...f With E k The linear relationship between the values ​​is used to fit the energy resolution per channel (ΔE). In this embodiment, ΔE = 2.5 meV / channel.

[0040] Using the detector's central channel y0 = 512 in the y-direction as a reference, the energy mapping relationship is obtained as follows: E = E f + ΔE × (y′ - y0); Where E f For Fermi energy (E in this embodiment) f = 0 eV (reference value).

[0041] Finally, (x′, y′) is mapped to the departure angle θ and kinetic energy E, and the corresponding momentum k is calculated using the momentum conversion formula: k = sinθ; Where m is the electron mass. is the reduced Planck constant.

[0042] Through a coordinate mapping step, based on the preset dispersion relation of the angle-resolved energy analyzer, the corrected event coordinates are accurately mapped to the energy-momentum coordinate space. This is achieved through experimental calibration (e.g., ...). Figure 2 , Figure 3 The bias scan and Fermi edge scan shown (or theoretical model) established a precise correspondence between detector coordinates and physical quantities such as angle and energy, realizing the conversion from raw detection data to a physically meaningful band structure.

[0043] (5) Band reconfiguration steps Based on the mapped energy-momentum coordinates (E, k), statistical accumulation is performed on all photoelectron events to reconstruct an angle-resolved band structure. In this embodiment, the energy range is set to -0.5 eV to 0.5 eV (relative to E_f), the energy step size is 2.5 meV, corresponding to 200 energy channels; the momentum range is -1.0 Å. - ¹ to 1.0 Å - ¹, momentum step size is 0.01 Å - ¹, corresponding to 200 momentum channels. A 200×200 two-dimensional histogram is constructed, and for each event's (E, k) coordinate, the count in the corresponding grid cell is incremented by 1.

[0044] After the statistics are completed, the count values ​​of each grid are converted into intensity values, resulting in the Ek dispersion relation diagram, i.e., the angle-resolved band structure diagram. The statistical process can use simple counting or weighted statistics based on the event's time information, intensity information, etc. In this embodiment, for events containing time identifiers, different weights can be assigned according to the time window, supporting time-resolved band structure reconstruction.

[0045] The reconstruction results can be displayed in real time (e.g., by updating the bandgap image on a computer screen in real time) or stored offline as a data file for subsequent analysis.

[0046] Through a band reconstruction step, the mapped events are statistically accumulated, transforming discrete event data into a continuous band distribution map. This completes the entire reconstruction process from the output of an event-type detector to the angle-resolved band distribution. The reconstruction results can be displayed in real time or processed offline, supporting the generation of two-dimensional and three-dimensional energy-momentum distribution maps to meet the needs of different application scenarios.

[0047] Through the above five steps, this embodiment realizes the complete reconstruction from discrete optoelectronic event data output by an event-type delay line detector to a continuous angle-resolved bandgap diagram, solving the technical problem that traditional integral methods are difficult to apply to event-type detection data in the prior art.

[0048] This invention also provides an angle-resolved bandgap reconstruction system based on the output of an event-type delay line detector, used to implement the above-described method. For example... Figure 6 As shown, the system includes the following modules: (1) Event-based detection data input module This module connects to an event-driven delay line detector to acquire photoelectron event data. The data interface can be a high-speed data acquisition card, a USB interface, or a network interface, supporting real-time data stream reception or offline file reading. The received photoelectron event data includes multiple discrete photoelectron events, each containing at least spatial coordinate information (x, y) and event identification information (such as region identifier, timestamp, etc.). In this embodiment, the input module receives data in the format (startctr, x, y, t) and performs buffering and preprocessing, such as data format verification and timestamp parsing.

[0049] (2) Detection area identification module This module assigns each event to a corresponding detection area or channel based on event identification information. In this embodiment, the detection area identification module incorporates detector geometric parameters, including the boundary coordinates and area number of each area. For an input event, its x-coordinate determines its corresponding area: If x ≤ 470, the region is labeled "left". If 471 ≤ x ≤ 540, the region is identified as "missing intermediate" (and can be marked as invalid). If x ≥ 541, the region is labeled "right side"; The identification results, along with the event data, are passed to subsequent modules. Events marked as invalid can be directly filtered out and not involved in further processing.

[0050] (3) Area correction module This module performs geometric and response corrections for photoelectron events within different detection regions. The region correction module pre-stores correction parameters for each region, which can be obtained through calibration experiments or dynamically updated. In this embodiment, the correction parameters include: Geometric correction parameters: translation Δx of the left region left = 45 channels, right-side region translation Δx right = -25 channels; Response correction parameters: Linear correction coefficient a in the left region left = 1.02, b left = -10; Right region a right =0.98, b right = 15; For each event, select the corresponding correction parameters based on its region identifier, and calculate the corrected coordinates (x′, y′): Events in the left region: x′ = x + 45; y′ = (y + 10) / 1.02; Events in the right-hand region: x′ = x - 25; y′ = (y - 15) / 0.98; If the event contains a time stamp, the region correction module can also perform time correction for time response differences between different detection regions. For example, if there is a 10 ns electronic delay between the left and right regions, the timestamp t of the event in the left region can be corrected to t′ = t - 10 ns to eliminate the impact of time response differences on subsequent time-resolved measurements.

[0051] (4) Coordinate mapping module This module maps the corrected event coordinates (x′, y′) to energy-momentum coordinate space based on the dispersion relation of the angle-resolved energy analyzer. The coordinate mapping module pre-stores calibration parameters. Angle calibration parameters: Δθ = 0.057 deg / channel, x0 = 512 channels; Energy calibration parameters: ΔE = 2.5 meV / channel, y0 = 512 channels, E f = 0 eV; For each event, calculate: θ = Δθ × (x′ - x0); E = E f + ΔE × (y′ - y0); k = sinθ; The energy value E and momentum value k corresponding to the event are obtained. The coordinate mapping module supports multiple analyzer types. For non-hemispherical analyzers, corresponding calibration methods and mapping formulas can be used.

[0052] (5) Band reconfiguration module This module performs statistical analysis or accumulation of photoelectron events based on the mapped energy-momentum coordinates to obtain the angle-resolved band structure. The band reconstruction module includes a two-dimensional histogram buffer, which initializes the mesh based on user-defined energy and momentum ranges, energy step sizes, and momentum step sizes. For each event at (E, k), a count is incremented in the corresponding mesh cell.

[0053] In this embodiment, the band reconfiguration module supports two statistical modes: Cumulative statistics: Counts and accumulates all events, suitable for steady-state bandgap measurements. Weighted statistics: assigning weights based on the time signature or other characteristics of an event, suitable for time-resolved measurements or intensity correction. After the statistics are completed, the band distribution diagram can be displayed in real time (e.g., dynamically updated through a GUI interface), and the results can also be exported to common formats (e.g., TXT, HDF5, NPY, etc.) for offline analysis.

[0054] The five modules mentioned above can be integrated into an industrial control computer and implemented through software; alternatively, some modules (such as area correction and coordinate mapping) can be deployed in FPGA hardware for real-time processing, improving system throughput. Modules communicate with each other through shared memory, message queues, or data pipelines, forming a complete data processing pipeline.

[0055] In other embodiments, the event data may at least include spatial coordinate information, and optionally include time information, detection area identification information, or channel identification information. The data organization method may be as follows: Event list: Each line records information about one event, suitable for offline processing. Time series: A stream of events arranged in chronological order, suitable for real-time processing. Data frame format: Packs events over a period of time into a data frame, including a frame header and a timestamp. Those skilled in the art can choose a suitable data organization form based on the actual hardware interface and data processing requirements; all of these are equivalent alternatives to the present invention.

[0056] In other embodiments, the detection area is not limited to a left-right dual-region structure. The detection area can be: Physical partitioning: such as multi-region structures formed by splicing multiple MCPs; Logical partitioning: The effective surface of the detector is divided into multiple logical regions according to measurement requirements; Symmetrical or asymmetrical partitioning: can be divided according to the actual geometry of the detector; Multi-region structure: can have two, four or more regions; The number, shape, and boundaries of the regions can be adjusted according to the actual detector configuration and measurement requirements, all of which fall within the protection scope of this invention.

[0057] In other embodiments, region correction is not limited to translation correction and linear response correction. Correction methods may include: Geometric correction can include one or more of translation, rotation, stretching, affine transformation or nonlinear transformation, used to correct geometric distortions between different regions; Response correction: Normalization can be performed based on reference spectral lines (such as Fermi edge, atomic core energy level, characteristic peaks, etc.), or sensitivity calibration can be performed using a uniform light source or standard samples; Time correction: can compensate for differences in electronic delay, signal transmission delay, and detection response time in different regions; Calibration parameters can be obtained through pre-calibration or dynamically updated based on experimental data during measurement (e.g., real-time monitoring of reference spectral line positions and automatic parameter adjustment). Those skilled in the art can select an appropriate calibration method based on the specific system characteristics.

[0058] In other embodiments, coordinate mapping is not limited to linear mapping. The mapping relationship can be obtained in the following ways: Experimental calibration: In addition to bias scanning and Fermi edge scanning, full-area calibration can also be performed using standard samples with known band structures (such as polycrystalline gold, single-crystal copper, etc.); Theoretical model: Based on the analyzer's geometry and electric field distribution, the theoretical dispersion relation is obtained through numerical calculation; Hybrid approach: combining theoretical models and experimental calibration points for fitting to obtain a more accurate mapping relationship; For non-hemispherical analyzers (such as cylindrical mirror analyzers, conical mirror analyzers, etc.), corresponding coordinate mapping methods can be used, all of which are equivalent substitutions of this invention.

[0059] In other embodiments, band reconstructing is not limited to two-dimensional mesh statistics. Reconstruction methods may include: Cumulative statistics: Simply count and accumulate events; Weighted statistics: Different weights are assigned to events based on their time information, intensity information, confidence level, etc. Adaptive mesh: Automatically adjusts the mesh size based on event density to improve reconstruction quality; 3D reconstruction: For measurement data that includes a time dimension, the 3D energy-momentum-time distribution can be reconstructed; The reconstruction results can be presented as a two-dimensional energy-momentum distribution map, a three-dimensional display, or a data table, and can be displayed in real time or processed offline.

[0060] The method and system described in this invention can be implemented in the following ways: Pure software implementation: The data processing program runs on a general-purpose computer and is suitable for offline processing and real-time processing at low data rates; Hardware acceleration: Deploy computationally intensive modules (such as region correction and coordinate mapping) in FPGA, GPU or DSP to achieve high-speed real-time processing; Distributed implementation: Each functional module is distributed across different computing nodes and works collaboratively through a network. Inter-module communication can be achieved through various methods such as shared memory, message queues, data stream pipelines, and network protocols. Those skilled in the art can choose the appropriate implementation method based on system performance requirements and hardware conditions.

[0061] This invention is not only applicable to conventional angle-resolved photoelectron spectroscopy measurements, but also to the following scenarios: Time-resolved photoelectron spectroscopy: reconstructing the band structure under different time delays using time information in event data; Photoelectron momentum microscopy: reconstructing momentum space data from large-area parallel detection; Spin-resolved photoelectron spectroscopy: reconstructing the spin-resolved band structure by combining a spin detector; Multiphoton-excited photoelectron measurement: applicable to multiphoton ionization, suprathreshold ionization and other processes under strong laser fields; Other particle detection scenarios: such as measurement techniques based on event-based detectors, including electron energy loss spectroscopy and ion scattering spectroscopy.

[0062] Those skilled in the art can adjust the implementation details of the present invention according to specific application scenarios, but all adjustments will not depart from the core ideas of the present invention.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. 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. A method for angle-resolved bandgap reconstruction based on the output of an event-type delay line detector, characterized in that, Includes the following steps: Event data acquisition steps: Acquire photoelectron event data through an event-type delay line detector. The event data includes multiple discrete photoelectron events, and each photoelectron event contains at least spatial coordinate information and event identification information. Detection area identification step: Based on the event identification information or the spatial coordinate information, each photoelectron event is assigned to the corresponding detection area or channel; Regional calibration steps: Geometric calibration and response calibration are performed on the photoelectron events in different detection regions or channels respectively to eliminate systematic differences between different detection regions or channels; Coordinate mapping step: Based on the preset dispersion relation of the angle-resolved energy analyzer, the spatial coordinates of the corrected photoelectron events are mapped to the energy-momentum coordinate space to obtain the energy value and momentum value corresponding to each photoelectron event; Band reconstruction step: Based on the mapped energy-momentum coordinates, statistical accumulation is performed on all the photoelectron events to reconstruct the angle-resolved band distribution map; In the region correction step, the geometric correction includes performing at least one of coordinate translation, rotation, stretching or affine transformation on the detection region with geometric distortion or signal loss, in order to compensate for the geometric position deviation between different detection regions. In the region correction step, the response correction is based on Fermi edge features to unify the energy reference, including normalizing the detection sensitivity of different detection regions based on reference spectral line features to eliminate the difference in response sensitivity between different detection regions. The photoelectronic event also includes a time stamp, and the area correction step further includes time correction to compensate for time response differences between different detection areas or channels based on the time stamp of the photoelectronic event.

2. The angular-resolved bandgap reconstruction method according to claim 1, characterized in that, In the coordinate mapping step, the dispersion relation is obtained through experimental calibration or theoretical model; the experimental calibration includes: calibrating the mapping relationship between angular coordinates and detector coordinates by changing the analyzer bias scanning imaging boundary, and / or calibrating the mapping relationship between energy coordinates and detector coordinates by changing the electron kinetic energy scanning Fermi edge position.

3. The angular-resolved bandgap reconstruction method according to claim 1, characterized in that, In the band reconstruction step, a two-dimensional or three-dimensional energy-momentum distribution is obtained through cumulative statistics or weighted statistics of photoelectron events.

4. An angular-resolved bandgap reconstruction system based on the output of an event-type delay line detector, used to implement the angular-resolved bandgap reconstruction method according to any one of claims 1-3, characterized in that, include: An event-type detection data input module is used to acquire photoelectronic event data, which includes multiple discrete photoelectronic events, and each photoelectronic event includes at least spatial coordinate information and event identification information. The detection area identification module is used to assign events to corresponding detection areas or channels based on event identification information or spatial coordinate information. The region correction module is used to perform geometric and response corrections on the photoelectronic events in different detection regions; The coordinate mapping module is used to map the corrected spatial coordinates of the photoelectron event to the energy-momentum coordinate space based on the dispersion relation of the angle-resolved energy analyzer. The band reconstruction module is used to perform statistical analysis or accumulation of the photoelectron events based on the mapped energy-momentum coordinates to obtain the angle-resolved band distribution.

5. The angular-resolved bandgap reconstruction system according to claim 4, characterized in that, The photoelectronic event also includes a time stamp, and the correction performed by the area correction module also includes time correction to compensate for the time response differences between different detection areas or channels based on the time stamp of the photoelectronic event.

6. The angular-resolved bandgap reconstruction system according to claim 4, characterized in that, In the coordinate mapping module, the dispersion relation is obtained through experimental calibration or theoretical model; the experimental calibration includes: calibrating the mapping relationship between angular coordinates and detector coordinates by changing the analyzer bias scanning imaging boundary, and / or calibrating the mapping relationship between energy coordinates and detector coordinates by changing the electron kinetic energy scanning Fermi edge position.

7. The angular-resolved bandgap reconstruction system according to claim 4, characterized in that, The band reconstruction module obtains two-dimensional or three-dimensional energy-momentum distributions through event accumulation statistics or weighted statistics, and can display them in real time or process them offline.

Images