Wide-field tomographic computational astronomy imaging system and apparatus
The wide-area tomographic computational astronomical imaging system solves the problem of balancing wide-area coverage and high resolution, realizing a high-precision three-dimensional spatial distribution model and physical parameter map, supporting cosmological research.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TSINGHUA UNIVERSITY
- Filing Date
- 2026-03-16
- Publication Date
- 2026-06-02
AI Technical Summary
Existing astronomical observation technologies struggle to balance wide-area coverage, spatial resolution, and the acquisition of three-dimensional/multi-dimensional information, thus limiting the efficiency of detecting large-scale structures of the universe, the internal structures of galaxies, and exoplanets.
A wide-area tomographic computational astronomical imaging system is adopted, including a snapshot spectral imaging module, a redshift solution module, and a tomographic data visualization module. The system processes three-dimensional hyperspectral data through a hybrid algorithm to generate a three-dimensional spatial distribution model and physical parameter maps.
It achieves high-precision cosmological tomography of a wide-area sky, provides a reliable three-dimensional spatial distribution model and physical parameter map, and supports cutting-edge research on the large-scale structure of the universe, galaxy evolution and dark matter distribution.
Smart Images
Figure CN121832081B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of astronomical imaging technology, and in particular to a wide-area tomographic computational astronomical imaging system and apparatus. Background Technology
[0002] Astronomical observation is a primary means for humanity to explore fundamental scientific questions such as the origin of the universe, the evolution of galaxies, and the habitability of exoplanets. Therefore, precise observations of large field-of-view skies are necessary to meet the needs of cutting-edge astronomical research.
[0003] In related technologies, traditional mainstream astronomical observations rely on the acquisition and interpretation of single or limited-band data from two-dimensional projection images of celestial objects, resulting in limited interpretation of three-dimensional information about celestial bodies. While large-scale spectroscopic surveys have enabled wide-area sky observations and the acquisition of massive amounts of data, this wide coverage comes at the cost of spatial resolution, making it difficult to clearly present galactic details, distinguish small galactic structures, or capture faint stars, thus hindering the efficiency of studying galactic internal structures and detecting exoplanets. Integral Field Unit (IFU) technology can acquire two-dimensional projection plane spectra of celestial objects in a single exposure, improving observation efficiency, but sacrifices are made to meet overall requirements. For example, when observing isolated variable stars in distant galaxies, interference from surrounding celestial bodies makes accurate luminosity measurements impossible. Furthermore, when studying stellar chemical abundance, regionally averaged spectra can mask the unique chemical characteristics of individual stars, affecting in-depth research into star formation and evolution mechanisms. Therefore, a wide-area tomographic computational astronomical imaging system is urgently needed to achieve high-resolution and multi-dimensional synchronous precision observations of large-field-of-view sky areas, thereby meeting the needs of next-generation cutting-edge astronomical research. Summary of the Invention
[0004] This disclosure aims to at least partially address one of the technical problems in the related art.
[0005] Therefore, the first objective of this disclosure is to propose a wide-area tomographic computational astronomical imaging system. Through a snapshot spectral imaging module, a redshift solution module, a tomographic data visualization module, and a control module, it achieves high-precision cosmological tomography of a wide-area sky region, transforming three-dimensional hyperspectral data into an intuitive and reliable three-dimensional spatial distribution model and physical parameter map, providing reliable technical support for cutting-edge research on the large-scale structure of the universe, galaxy evolution, and dark matter distribution.
[0006] To achieve the above objectives, a first aspect of this disclosure proposes a wide-area tomographic computational astronomical imaging system, comprising a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module, wherein...
[0007] The snapshot spectral imaging module is used to directly couple with the telescope's main focal plane to capture full-field-of-view three-dimensional hyperspectral data of the observation field;
[0008] The redshift calculation module is connected to the snapshot spectral imaging module and is used to process the three-dimensional hyperspectral data based on the three-dimensional hyperspectral data through a hybrid algorithm to retrieve the target redshift value, three-dimensional spatial coordinates and physical parameters of the target celestial body.
[0009] The tomographic data visualization module is connected to the redshift calculation module and is used to construct a multidimensional tomographic dataset based on the target redshift value, the three-dimensional spatial coordinates and the physical parameters, and generate a three-dimensional tomographic map based on the multidimensional tomographic dataset through pseudo-color annotation and three-dimensional modeling methods.
[0010] The control module is connected to the snapshot spectral imaging module and is used to configure the snapshot spectral imaging module based on the observed target parameters.
[0011] The wide-area tomographic computational astronomical imaging system of this invention may also have the following additional technical features:
[0012] Optionally, the snapshot spectral imaging module includes a telescope optical unit and a compressed sensing snapshot spectral imaging chip, wherein...
[0013] The telescope's optical unit is used to collect light signals from the target scene;
[0014] The compressed sensing snapshot spectral imaging chip has its photosensitive surface directly coupled to the main focal plane of the telescope optical unit, and is used to capture full-field three-dimensional hyperspectral data of the target scene. The three-dimensional hyperspectral data includes spatial two-dimensional information and spectral one-dimensional information.
[0015] The compressed sensing snapshot spectral imaging chip integrates a coded mask, and is also used to acquire the size of the coded mask, field-of-view adaptation parameters, and exposure parameters.
[0016] Optionally, the redshift calculation module includes a data interface module, a template matching module, a physical information neural network module, and a mapping module, wherein,
[0017] The data interface module is used to acquire three-dimensional hyperspectral data of the target celestial body;
[0018] The template matching module is connected to the data interface module and is used to extract the spectral curves of each pixel in the spatial dimension of the three-dimensional hyperspectral data, and to compare the spectral curves with a preset astronomical spectral template database to determine the target matching template, and to obtain the preliminary redshift value of the corresponding pixel through the target matching template.
[0019] The physical information neural network module is connected to the template matching module and is used to construct a physical information neural network by taking the preliminary redshift value as an initial constraint, and to perform joint inversion on the preliminary redshift value and physical parameters through the physical information neural network to obtain the target redshift value and physical parameters.
[0020] The mapping module is connected to the physical information neural network module and is used to calculate the radial distance of the target celestial body based on Hubble's law according to the target redshift value, and to determine the three-dimensional spatial coordinates of the target celestial body in the three-dimensional space of the universe based on the corresponding celestial coordinates.
[0021] Optionally, the physical information neural network includes an input layer, a hidden layer, a constraint layer, and an output layer; the step of jointly inverting the preliminary redshift value and physical parameters through the physical information neural network to obtain the target redshift value and physical parameters includes:
[0022] The spectral curve, the preliminary redshift value, and the celestial coordinates are concatenated to obtain a fusion vector;
[0023] The first feature vector is obtained by performing a linear transformation on the fusion vector through the input layer.
[0024] The second feature vector is obtained by extracting the nonlinear correlation features from the first feature vector through the hidden layer;
[0025] The second feature vector is corrected by the constraint sub-layer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector. The constraint sub-layer includes the gravitational redshift formula constraint sub-layer, the stellar atmosphere model constraint sub-layer, and the radiation transfer equation constraint sub-layer.
[0026] The target redshift value and physical parameters are obtained by performing a linear transformation on the third feature vector through the output layer.
[0027] Optionally, the step of modifying the second feature vector using the constraint sublayer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector includes:
[0028] If the celestial body type identification result is a star, then the second feature vector is corrected by the constrained sublayer of the stellar atmosphere model, the constrained sublayer of the gravitational redshift formula, and the constrained sublayer of the radiation transfer equation to obtain the third feature vector;
[0029] If the celestial body type identification result is a galaxy, then the second feature vector is corrected by constraining the sublayer through the radiation transfer equation to obtain the third feature vector;
[0030] If the celestial body type identification result is an exoplanet, then the second feature vector is corrected by constraining the sublayer using the gravitational redshift formula to obtain the third feature vector.
[0031] Optionally, the tomographic data visualization module includes a 3D modeling module and a visualization rendering module, wherein,
[0032] The three-dimensional modeling module is used to construct a three-dimensional universe structure model based on the target redshift value and the three-dimensional spatial coordinates through a redshift-distance mapping relationship;
[0033] The visualization rendering module is connected to the 3D modeling module and is used to render the 3D universe structure model based on preset rules to obtain a 3D tomographic map.
[0034] Optionally, the visualization rendering module includes a large-scale structure rendering module, a local detail rendering module, and an output module, wherein...
[0035] The large-scale structure rendering module is used to perform layered volume rendering of the three-dimensional universe structure model by mapping the spatial density distribution of celestial bodies through brightness or opacity, so as to obtain a visualized large-scale universe structure.
[0036] The local detail rendering module is connected to the large-scale structure rendering module and is used to generate a pseudo-color heat map in the local three-dimensional space region of the target, wherein hue is used to map the distribution of chemical abundance in the physical parameters, and brightness or saturation is used to map the distribution of temperature in the physical parameters.
[0037] The output module is connected to the local detail rendering module and is used to display the visualization results generated by the large-scale structure rendering module and the local detail rendering module.
[0038] Optionally, the tomographic data visualization module further includes an interactive display module, wherein the interactive display module is connected to the output module and is used to provide an interactive interface for three-dimensional perspective transformation, spatial slicing, and rendering parameter adjustment.
[0039] Optionally, configuring the snapshot spectral imaging module based on the observed target parameters includes:
[0040] Obtain the right ascension and declination of the target celestial region;
[0041] Based on the right ascension, the declination, and the telescope's optical parameters, the size of the coded mask covering the target sky region's field of view is calculated.
[0042] Based on the right ascension, the declination, and the telescope environment parameters, the field of view adaptation parameters are calculated.
[0043] Calculate the exposure parameters required for spectral acquisition based on the celestial characteristics of the target sky region;
[0044] The snapshot spectral imaging module is configured based on the coded mask size, the field of view adaptation parameters, and the exposure parameters.
[0045] To achieve the above objectives, a first aspect of this disclosure provides a wide-area tomographic computational astronomical imaging apparatus, the apparatus including the wide-area tomographic computational astronomical imaging system.
[0046] In summary, the wide-area tomographic computational astronomical imaging system and apparatus disclosed herein include a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module. The snapshot spectral imaging module is directly coupled to the telescope's main focal plane to capture full-field-of-view three-dimensional hyperspectral data. The redshift calculation module, connected to the snapshot spectral imaging module, processes the three-dimensional hyperspectral data using a hybrid algorithm to retrieve the target redshift value, three-dimensional spatial coordinates, and physical parameters of the target celestial object. The tomographic data visualization module, also connected to the redshift calculation module, constructs a multi-dimensional tomographic dataset based on the target redshift value, three-dimensional spatial coordinates, and physical parameters, and generates a three-dimensional tomographic map based on the multi-dimensional tomographic dataset using pseudo-color annotation and three-dimensional modeling methods. The control module, connected to the snapshot spectral imaging module, configures the snapshot spectral imaging module based on the observed target parameters. This disclosure enables high-precision cosmological tomography of a wide-area sky region through a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module. It transforms three-dimensional hyperspectral data into an intuitive and reliable three-dimensional spatial distribution model and physical parameter map, providing reliable technical support for cutting-edge research on the large-scale structure of the universe, galaxy evolution, and dark matter distribution.
[0047] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description
[0048] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:
[0049] Figure 1 This is a schematic diagram of the structure of a wide-area tomographic computational astronomical imaging system provided in an embodiment of the present disclosure;
[0050] Figure 2This is a schematic diagram of a hyperspectral snapshot chromatography provided in an embodiment of the present disclosure, wherein A is a hyperspectral image, B is a normalized fluorescence spectrum of six selected different spatial locations, C is a spectrum at 5050 Å, D is a spectrum at 6563 Å and E is a spectrum at 8542 Å.
[0051] Figure 3 This is a schematic diagram of a tomographic image provided in an embodiment of the present disclosure. Detailed Implementation
[0052] Embodiments of this disclosure are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.
[0053] In related technologies, traditional mainstream astronomical observations rely on the acquisition and interpretation of single or limited-band data from two-dimensional projection images of celestial objects. However, this method inherently loses information about the three-dimensional spatial distribution and physical state of celestial objects along the line of sight. For example, in the study of interstellar dust in the Milky Way, extinction measurements based on two-dimensional images can usually only plot the projection distribution of local sky regions, or are forced to assume that the extinction curve is uniform over a wide area. In reality, the dust density, composition, and extinction effect vary significantly in different regions. This information bias caused by the inherent limitations of two-dimensional observation directly affects the inference of the evolutionary history of large-scale structures in the universe, as well as the accuracy of judging the composition and habitability of exoplanets when analyzing their atmospheric spectra.
[0054] Furthermore, to compensate for the low efficiency of single-target observations and the difficulty in conducting large-sample statistical studies, large-scale spectroscopic survey instruments have emerged, such as the Guo Shoujing Telescope (LAMOST). These instruments, through their large field-of-view design and multi-target fiber optic spectroscopy, have achieved efficient acquisition of the spectra of massive amounts of celestial objects across a wide area of the sky. However, this wide-area coverage capability usually comes at the cost of spatial resolution. LAMOST's angular resolution is far lower than that of instruments like the Hubble Space Telescope, which focus on high-resolution imaging. This makes it difficult to clearly resolve the fine structure of galaxies, distinguish members of dense galaxy groups, or effectively capture faint stars and remnants. Therefore, these shortcomings limit astronomers' in-depth research into the internal dynamics of galaxies, merger histories, and populations of faint objects (such as metal-poor stars). In exoplanet detection, it is also difficult to accurately locate and confirm candidate objects within a crowded field of view.
[0055] Furthermore, the development of IFU technology has brought new dimensions to astronomical observation. Specifically, IFU can obtain the spectrum of every spatial pixel on the two-dimensional projection plane of the observed target in a single exposure, forming a data cube (two-dimensional spatial coordinates plus one-dimensional spectral information), significantly improving the efficiency of three-dimensional hyperspectral data acquisition. It has been successfully applied to the overall spectroscopic observation of nearby objects such as the Andromeda Galaxy. However, existing IFU technology is caught in a dilemma of balancing overall observation with local accuracy in practical applications. Its field of view is usually fixed and limited: when sparse sampling or increasing the scale of individual spatial pixels is used to cover a larger sky area, spatial details are lost; while when dense sampling is used to pursue high spatial resolution, the field of view is greatly compressed, making it unsuitable for wide-area sky surveys. It should be noted that when IFU observes a region containing multiple celestial objects, it obtains the spatial average of the spectra of all light sources in that region. This makes it easy for the signal of an isolated variable star in a distant galaxy to be contaminated by the bright background light of the surrounding galaxy, making accurate photometry impossible. When studying stellar chemical abundance, the average spectrum of the region will completely obscure individual stars with special chemical characteristics (such as extremely high alpha abundance or extremely strong r-process element signals), and these individuals are key clues to revealing extreme astrophysical processes or early galaxy formation mechanisms.
[0056] In summary, the existing astronomical observation technology system suffers from a core contradiction: wide-area coverage, high spatial resolution, and the acquisition of three-dimensional / multi-dimensional information cannot be simultaneously achieved. Therefore, there is an urgent need for a wide-area tomographic computational astronomical imaging system that can fundamentally and collaboratively resolve these contradictions, enabling high-resolution, multi-dimensional, synchronous, and precise observations of large field-of-view sky areas to meet the needs of next-generation cutting-edge astronomical scientific research.
[0057] The wide-area tomographic computational astronomical imaging system of this disclosure will be described in detail below with reference to specific embodiments.
[0058] Figure 1 This disclosure provides a wide-area tomographic computational astronomical imaging system. For example... Figure 1 As shown, this wide-area tomographic computational astronomical imaging system may include a snapshot spectral imaging module 101, a redshift calculation module 102, a tomographic data visualization module 103, and a control module 104.
[0059] The snapshot spectral imaging module 101 is used to directly couple with the telescope's main focal plane to capture full-field-of-view three-dimensional hyperspectral data of the observation field;
[0060] The redshift calculation module 102 is connected to the snapshot spectral imaging module 101. It is used to process the three-dimensional hyperspectral data based on the three-dimensional hyperspectral data through a hybrid algorithm to retrieve the target redshift value, three-dimensional spatial coordinates and physical parameters of the target celestial body.
[0061] The tomographic data visualization module 103 is connected to the redshift calculation module 102 and is used to construct a multidimensional tomographic dataset based on the target redshift value, three-dimensional spatial coordinates and physical parameters, and generate a three-dimensional tomographic map based on the multidimensional tomographic dataset through pseudo-color annotation and three-dimensional modeling methods.
[0062] The control module 104 is connected to the snapshot spectral imaging module 101 and is used to configure the snapshot spectral imaging module based on the observed target parameters.
[0063] In one embodiment of this disclosure, the snapshot spectral imaging module includes a telescope optical unit 1011 and a compressed sensing snapshot spectral imaging chip 1012, wherein
[0064] The telescope optical unit 1011 is used to collect light signals from the target scene;
[0065] The compressed sensing snapshot spectral imaging chip 1012 has its photosensitive surface directly coupled to the main focal plane of the telescope's optical unit. It is used to capture full-field three-dimensional hyperspectral data of the target scene. The three-dimensional hyperspectral data includes spatial two-dimensional information and spectral one-dimensional information.
[0066] Among them, the compressed sensing snapshot spectral imaging chip integrates a coded mask, and is also used to obtain the coded mask size, field of view adaptation parameters and exposure parameters.
[0067] In one embodiment of this disclosure, the size of the mask pixel unit is determined based on seeing resolution limitations to ensure that the acquisition accuracy is adapted to the observation environment.
[0068] In one embodiment of this disclosure, the pixel unit size of the above-mentioned coding mask is determined according to the seeing resolution limit in the observation environment of the telescope optical unit, and the overall size of the coding mask and the coding array layout are determined according to the field of view size of the telescope optical unit, so as to achieve full coverage of the field of view and optical matching with the main focal plane.
[0069] In one embodiment of this disclosure, the compressed sensing snapshot spectral imaging chip also integrates a high-speed data readout unit. The high-speed data readout unit has a spectral response range of 300-1100nm and a data transmission rate of not less than 5Gbps, and is used to output hyperspectral data in real time.
[0070] In one embodiment of this disclosure, the redshift calculation module 102 may further include a data interface module 1021, a template matching module 1022, a physical information neural network module 1023, and a mapping module 1024, wherein,
[0071] Data interface module 1021 is used to acquire three-dimensional hyperspectral data of the target celestial body;
[0072] The template matching module 1022 is connected to the data interface module 1021 and is used to extract the spectral curves of each pixel in the spatial dimension of the three-dimensional hyperspectral data, and to determine the target matching template by comparing the spectral curves with the preset astronomical spectral template database, and to obtain the preliminary redshift value of the corresponding pixel through the target matching template.
[0073] The physical information neural network module 1023 is connected to the template matching module 1022. It is used to construct the physical information neural network by taking the initial redshift value as the initial constraint, and to perform joint inversion of the initial redshift value and physical parameters through the physical information neural network to obtain the target redshift value and physical parameters.
[0074] The mapping module 1024 is connected to the physical information neural network module 1023 and is used to calculate the radial distance of the target celestial body based on Hubble's law according to the target redshift value, and determine the three-dimensional spatial coordinates of the target celestial body in the three-dimensional space of the universe based on the corresponding celestial coordinates.
[0075] In one embodiment of this disclosure, the template matching module 1022 can be used in a three-dimensional hyperspectral data cube. In the context of each pixel position in the spatial dimension Perform a traversal and extract the spectral curve of each pixel. .
[0076] In one embodiment of this disclosure, the spectral curve corresponding to each pixel is compared one by one with the standard templates in the preset astronomical spectral template database using correlation coefficient, cross-correlation peak or minimum residual matching algorithm to determine the optimal template with the highest matching degree. The built-in redshift label of the optimal template is directly extracted and used as the preliminary redshift value of the pixel spectrum.
[0077] In one embodiment of this disclosure, the aforementioned preset astronomical spectral template database may include the LAMOST and Hubble Telescope spectral libraries.
[0078] In one embodiment of this disclosure, the aforementioned physical information neural network may include an input layer, a hidden layer, a constraint layer, and an output layer. In another embodiment of this disclosure, the method for jointly inverting the preliminary redshift value and physical parameters using the physical information neural network to obtain the target redshift value and physical parameters may include the following steps:
[0079] Step 1: Concatenate the spectral curve, preliminary redshift value, and celestial coordinates to obtain the fusion vector;
[0080] Step 2: Perform a linear transformation on the fused vector through the input layer to obtain the first feature vector;
[0081] Step 3: Extract the non-linear correlation features from the first feature vector through the hidden layer to obtain the second feature vector;
[0082] Step 4: The second feature vector is corrected by the constraint sub-layer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector. The constraint sub-layer includes the gravitational redshift formula constraint sub-layer, the stellar atmosphere model constraint sub-layer, and the radiation transfer equation constraint sub-layer.
[0083] Step 5: Perform a linear transformation on the third feature vector through the output layer to obtain the target redshift value and physical parameters.
[0084] In one embodiment of this disclosure, the constraint sublayers corresponding to the identification results of different celestial body types are also different.
[0085] Specifically, in one embodiment of this disclosure, the method of modifying the second feature vector using the constraint sublayer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector may include: if the celestial body type identification result is a star, then modifying the second feature vector through the stellar atmosphere model constraint sublayer, the gravitational redshift formula constraint sublayer, and the radiation transfer equation constraint sublayer to obtain the third feature vector; if the celestial body type identification result is a galaxy, then modifying the second feature vector through the radiation transfer equation constraint sublayer to obtain the third feature vector; if the celestial body type identification result is an exoplanet, then modifying the second feature vector through the gravitational redshift formula constraint sublayer to obtain the third feature vector.
[0086] In one embodiment of this disclosure, the physical parameters obtained by the physical information neural network may include temperature and chemical abundance.
[0087] In one embodiment of this disclosure, the aforementioned physical information neural network can support both offline batch processing and online real-time inference modes. Furthermore, in one embodiment of this disclosure, the redshift calculation accuracy achieved by the aforementioned physical information neural network module is better than ±0.0005.
[0088] In one embodiment of this disclosure, a target redshift value is obtained. Subsequently, based on Hubble's law v=H0D and the redshift velocity relationship v=cz, the radial distance D=cz / H0 of the target celestial body can be obtained. Furthermore, in one embodiment of this disclosure, the three-dimensional spatial coordinates (x, y, z) of the target celestial body in the three-dimensional space of the universe are obtained based on the celestial coordinates (RA, Dec) and the radial distance D, providing a basis for subsequent spatial structure reconstruction and tomographic visualization.
[0089] In one embodiment of this disclosure, a method for obtaining the three-dimensional spatial coordinates (x, y, z) of a target celestial body in three-dimensional space of the universe based on celestial coordinates (RA, Dec) and radial distance D may include:
[0090]
[0091] In one embodiment of this disclosure, a high-dimensional tomographic dataset is constructed based on the target redshift value z, the three-dimensional spatial coordinates (x, y, z) of the target celestial body, the temperature T, and the chemical abundance A output by the redshift calculation module block. The target redshift value determines the radial depth of the model; the three-dimensional spatial coordinates define the spatial distribution of the celestial body; and the physical parameters of temperature and chemical abundance serve as additional scalar fields used to render the physical state of the celestial body.
[0092] In one embodiment of this disclosure, the tomographic data visualization module 103 may include a 3D modeling module 1031 and a visualization rendering module 1032, wherein,
[0093] The 3D modeling module 1031 is used to construct a 3D universe structure model based on the target redshift value and 3D spatial coordinates through the redshift-distance mapping relationship;
[0094] The visualization rendering module 1032 is connected to the 3D modeling module 1031 and is used to render the 3D universe structure model based on preset rules to obtain a 3D tomographic map.
[0095] In one embodiment of this disclosure, at a large scale (such as galaxy clusters, superclusters, and cosmic filamentary structures), a three-dimensional cosmic structure model can be constructed based on the redshift-distance mapping relationship.
[0096] In one embodiment of this disclosure, the visualization rendering module 1032 includes a large-scale structure rendering module 10321, a local detail rendering module 10322, and an output module 10323, wherein...
[0097] The large-scale structure rendering module 10321 is used to perform layered volume rendering of a three-dimensional universe structure model by mapping the spatial density distribution of celestial bodies through brightness or opacity, so as to obtain a visualized large-scale universe structure.
[0098] The local detail rendering module 10322 is connected to the large-scale structure rendering module 10321 and is used to generate a pseudo-color heat map in the local three-dimensional space region of the target. The hue is used to map the distribution of chemical abundance in the physical parameters, and the brightness or saturation is used to map the distribution of temperature in the physical parameters.
[0099] The output module 10323 is connected to the local detail rendering module 10322 and is used to display the visualization results generated by the large-scale structure rendering module and the local detail rendering module.
[0100] In one embodiment of this disclosure, the distribution of celestial objects at different distances is visualized through redshift-layered rendering, showcasing the morphology of large-scale cosmological structures, galaxy clusters, and the spatial distribution of dark matter halos. Furthermore, in another embodiment of this disclosure, celestial object density can be rendered using volume rendering, reflecting galaxy density distribution through brightness or opacity.
[0101] In one embodiment of this disclosure, spatial differences in physical parameters can be displayed in the form of a pseudo-color heatmap within a local three-dimensional spatial region of a target (such as a single galaxy or star-forming region). In one embodiment, hue represents the distribution of chemical abundance, such as variations in the content of metallic elements; value or saturation represents the temperature distribution, creating a thermal visual contrast; additional parameter layers, such as dust density distribution, can be overlaid to achieve composite visualization of multiple physical quantities. Based on this, users can observe changes in local physical characteristics with spatial depth by sliding the redshift layer or selecting a specific celestial region.
[0102] In one embodiment of this disclosure, the tomographic data visualization module may further include an interactive display module 10324, wherein the interactive display module 10324 is connected to the output module 10323 and is used to provide an interactive interface for three-dimensional perspective transformation, spatial slicing, and rendering parameter adjustment.
[0103] In one embodiment of this disclosure, the interactive display module can provide interactive functions such as 3D zooming, rotation, slicing, and transparency adjustment in the visualization interface, supporting users to focus on specific sky areas, extract personalized data, or conduct parameter comparison analysis. Furthermore, in one embodiment of this disclosure, it is also compatible with mainstream astronomical data formats such as FITS and HDF5, and can directly interface with analysis software such as Astropy and IRAF, realizing an integrated scientific research workflow from redshift inversion and 3D reconstruction to visualization analysis.
[0104] In one embodiment of this disclosure, the method for configuring a snapshot spectral imaging module based on observed target parameters may include the following steps:
[0105] Step S1: Obtain the right ascension and declination of the target celestial region;
[0106] Step S2: Based on right ascension and declination and the telescope's optical parameters, the size of the coded mask covering the target sky region's field of view is calculated.
[0107] Step S3: Based on right ascension and declination and telescope environmental parameters, the field of view adaptation parameters are calculated.
[0108] Step S4: Calculate the exposure parameters required for spectral acquisition based on the celestial characteristics of the target sky region;
[0109] Step S5: Configure the snapshot spectral imaging module based on the coded mask size, field of view adaptation parameters, and exposure parameters.
[0110] In one embodiment of this disclosure, the aforementioned telescope optical parameters may include the telescope focal length and the field of view of the target sky region.
[0111] In one embodiment of this disclosure, the width of the coding mask (corresponding to the right ascension direction) is: And the height of the coding mask (corresponding to the declination direction). , where f
[0112] ΔRA is the telescope focal length, and ΔDec is the field of view of the target sky region. The declination of the center of the target celestial region.
[0113] In one embodiment of this disclosure, detailed descriptions of steps S3 to S4 can be found in the prior art, and will not be repeated here.
[0114] In one embodiment of this disclosure, before observation, the control module 104 can configure the coded mask size, field-of-view adaptation parameters, and exposure parameters to the snapshot spectral imaging module; after the observation is started, the snapshot spectral imaging module acquires full-field three-dimensional hyperspectral data at once and transmits it to the redshift calculation module in real time; the redshift calculation module processes the data through "template matching + physical information network" and outputs the target redshift value, three-dimensional spatial coordinates, and physical parameters; the tomographic data visualization module generates a pseudo-color three-dimensional tomographic map, supporting interactive analysis and observation parameter feedback optimization by researchers, forming a closed-loop process.
[0115] The wide-area tomographic computational astronomical imaging system disclosed herein includes a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module. The snapshot spectral imaging module is directly coupled to the telescope's main focal plane to capture full-field-of-view three-dimensional hyperspectral data. The redshift calculation module, connected to the snapshot spectral imaging module, processes the three-dimensional hyperspectral data using a hybrid algorithm to retrieve the target redshift value, three-dimensional spatial coordinates, and physical parameters of the target celestial object. The tomographic data visualization module, also connected to the redshift calculation module, constructs a multi-dimensional tomographic dataset based on the target redshift value, three-dimensional spatial coordinates, and physical parameters, and generates a three-dimensional tomographic map based on the multi-dimensional tomographic dataset using pseudo-color annotation and three-dimensional modeling methods. The control module, connected to the snapshot spectral imaging module, configures the snapshot spectral imaging module based on the observed target parameters. This disclosure enables high-precision cosmological tomography of a wide-area sky region through a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module. It transforms three-dimensional hyperspectral data into an intuitive and reliable three-dimensional spatial distribution model and physical parameter map, providing reliable technical support for cutting-edge research on the large-scale structure of the universe, galaxy evolution, and dark matter distribution.
[0116] Based on the above description, the execution process of the aforementioned wide-area tomographic computational astronomical imaging system is illustrated. For example, using the observatory's 2.4m telescope as the platform, a custom-designed 54mm × 40mm low-expansion silicon-based focal plane target is directly coupled to the telescope's main focal plane. A Yuheng compressed sensing snapshot spectral imaging chip is integrated with the target surface, eliminating the need for intermediate optical components. Furthermore, considering the observatory's typical seeing of 0.8 arcseconds and a field of view of 0.5° × 0.5°, a 14072 × 10560 coded mask with a 3.2μm pixel unit size is designed. A single exposure can acquire full-field three-dimensional hyperspectral data. Redshift values and celestial three-dimensional parameters are rapidly calculated using SDSS DR17 data template matching and a physical information network. Combined with a pseudo-color three-dimensional visualization module, the full-field 6 arcminutes corresponding to the telescope's focal plane can be clearly distinguished. Within 6 arcminutes: Hyperspectral layering of the foreground galaxy NGC 7320 in the Stephen Quintet (e.g.) Figure 2 As shown), and direct 3D redshift tomography of the IC 1101 galaxy (as shown). Figure 3 (As shown). Figure A is a hyperspectral image, where each pixel contains complete spectral information. For example, Figure B shows normalized fluorescence spectra at six different spatial locations. Figure C is a 5050 angstrom spectrum, which clearly tomographically analyzes the abundance of metallic elements in galaxies. Figures D and E are 6563 angstrom and 8542 angstrom spectra, respectively, tomographically analyzing and visually displaying star-forming regions and interstellar dust distribution. Figure 3By mapping the redshift values of different spatial locations to the distance z from Earth, a 3D tomographic image of the structure is created.
[0117] This disclosure also provides a wide-area tomographic computational astronomical imaging apparatus, which includes a wide-area tomographic computational astronomical imaging system.
[0118] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this disclosure all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0119] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.
[0120] This disclosure is intended to provide implementation schemes for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.
[0121] The acquisition, transmission, storage, use, and processing of data in this disclosed technical solution all comply with the relevant provisions of national laws and regulations.
[0122] It should be noted that in the embodiments disclosed herein, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary and are intended only to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used such solutions.
[0123] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0124] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0125] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.
[0126] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.
[0127] It should be understood that various parts of this disclosure can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0128] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.
[0129] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0130] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.
Claims
1. A wide-area tomographic computational astronomical imaging system, characterized in that, The system includes a snapshot spectral imaging module, a redshift calculation module, a tomographic data visualization module, and a control module, wherein... The snapshot spectral imaging module is used to directly couple with the telescope's main focal plane to capture full-field-of-view three-dimensional hyperspectral data of the observation field; The redshift calculation module is connected to the snapshot spectral imaging module and is used to process the three-dimensional hyperspectral data based on the three-dimensional hyperspectral data through a hybrid algorithm to retrieve the target redshift value, three-dimensional spatial coordinates and physical parameters of the target celestial body. The tomographic data visualization module is connected to the redshift calculation module and is used to construct a multidimensional tomographic dataset based on the target redshift value, the three-dimensional spatial coordinates and the physical parameters, and generate a three-dimensional tomographic map based on the multidimensional tomographic dataset through pseudo-color annotation and three-dimensional modeling methods. The control module is connected to the snapshot spectral imaging module and is used to configure the snapshot spectral imaging module based on the observed target parameters.
2. The system according to claim 1, characterized in that, The snapshot spectral imaging module includes a telescope optical unit and a compressed sensing snapshot spectral imaging chip, wherein... The telescope's optical unit is used to collect light signals from the target scene; The compressed sensing snapshot spectral imaging chip has its photosensitive surface directly coupled to the main focal plane of the telescope optical unit, and is used to capture full-field three-dimensional hyperspectral data of the target scene. The three-dimensional hyperspectral data includes spatial two-dimensional information and spectral one-dimensional information. The compressed sensing snapshot spectral imaging chip integrates a coded mask and is also used to acquire the coded mask size, field-of-view adaptation parameters, and exposure parameters.
3. The system according to claim 1, characterized in that, The redshift calculation module includes a data interface module, a template matching module, a physical information neural network module, and a mapping module, wherein... The data interface module is used to acquire three-dimensional hyperspectral data of the target celestial body; The template matching module is connected to the data interface module and is used to extract the spectral curves of each pixel in the spatial dimension of the three-dimensional hyperspectral data, and to compare the spectral curves with a preset astronomical spectral template database to determine the target matching template, and to obtain the preliminary redshift value of the corresponding pixel through the target matching template. The physical information neural network module is connected to the template matching module and is used to construct a physical information neural network by taking the preliminary redshift value as an initial constraint, and to perform joint inversion on the preliminary redshift value and physical parameters through the physical information neural network to obtain the target redshift value and physical parameters. The mapping module is connected to the physical information neural network module and is used to calculate the radial distance of the target celestial body based on Hubble's law according to the target redshift value, and to determine the three-dimensional spatial coordinates of the target celestial body in the three-dimensional space of the universe based on the corresponding celestial coordinates.
4. The system according to claim 3, characterized in that, The physical information neural network includes an input layer, a hidden layer, a constraint layer, and an output layer; the process of jointly inverting the preliminary redshift value and physical parameters through the physical information neural network to obtain the target redshift value and physical parameters includes: The spectral curve, the preliminary redshift value, and the celestial coordinates are concatenated to obtain a fusion vector; The first feature vector is obtained by performing a linear transformation on the fusion vector through the input layer. The second feature vector is obtained by extracting the nonlinear correlation features from the first feature vector through the hidden layer; The second feature vector is corrected by the constraint sub-layer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector. The constraint sub-layer includes the gravitational redshift formula constraint sub-layer, the stellar atmosphere model constraint sub-layer, and the radiation transfer equation constraint sub-layer. The target redshift value and physical parameters are obtained by performing a linear transformation on the third feature vector through the output layer.
5. The system according to claim 4, characterized in that, The step of modifying the second feature vector using the constraint sublayer corresponding to the celestial body type identification result through the constraint layer to obtain the third feature vector includes: If the celestial body type identification result is a star, then the second feature vector is corrected by the constrained sublayer of the stellar atmosphere model, the constrained sublayer of the gravitational redshift formula, and the constrained sublayer of the radiation transfer equation to obtain the third feature vector; If the celestial body type identification result is a galaxy, then the second feature vector is corrected by constraining the sublayer through the radiation transfer equation to obtain the third feature vector; If the celestial body type identification result is an exoplanet, then the second feature vector is corrected by constraining the sublayer using the gravitational redshift formula to obtain the third feature vector.
6. The system according to claim 1, characterized in that, The tomographic data visualization module includes a 3D modeling module and a visualization rendering module, wherein... The three-dimensional modeling module is used to construct a three-dimensional universe structure model based on the target redshift value and the three-dimensional spatial coordinates through a redshift-distance mapping relationship; The visualization rendering module is connected to the 3D modeling module and is used to render the 3D universe structure model based on preset rules to obtain a 3D tomographic map.
7. The system according to claim 6, characterized in that, The visualization rendering module includes a large-scale structure rendering module, a local detail rendering module, and an output module, wherein... The large-scale structure rendering module is used to perform layered volume rendering of the three-dimensional universe structure model by mapping the spatial density distribution of celestial bodies through brightness or opacity, so as to obtain a visualized large-scale universe structure. The local detail rendering module is connected to the large-scale structure rendering module and is used to generate a pseudo-color heat map in the local three-dimensional space region of the target, wherein hue is used to map the distribution of chemical abundance in the physical parameters, and brightness or saturation is used to map the distribution of temperature in the physical parameters. The output module is connected to the local detail rendering module and is used to display the visualization results generated by the large-scale structure rendering module and the local detail rendering module.
8. The system according to claim 7, characterized in that, The tomographic data visualization module also includes an interactive display module, which is connected to the output module and is used to provide interactive interfaces for three-dimensional perspective transformation, spatial slicing, and rendering parameter adjustment.
9. The system according to claim 1, characterized in that, The configuration of the snapshot spectral imaging module based on the observed target parameters includes: Obtain the right ascension and declination of the target celestial region; Based on the right ascension, the declination, and the telescope's optical parameters, the size of the coded mask covering the target sky region's field of view is calculated. Based on the right ascension, the declination, and the telescope environment parameters, the field of view adaptation parameters are calculated. Calculate the exposure parameters required for spectral acquisition based on the celestial characteristics of the target sky region; The snapshot spectral imaging module is configured based on the coded mask size, the field of view adaptation parameters, and the exposure parameters.
10. A wide-area tomographic computational astronomical imaging device, characterized in that, The apparatus includes the wide-area tomographic computational astronomical imaging system as described in any one of claims 1-9.