Gravitationally Lensed Black Hole Emission Tomography
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Abstract (arXiv)
Measurements from the Event Horizon Telescope enabled the visualization of light emission around a black hole for the first time. So far, these measurements have been used to recover a 2D image under the assumption that the emission field is static over the period of acquisition. In this work, we propose BH-NeRF, a novel tomography approach that leverages gravitational lensing to recover the continuous 3D emission field near a black hole. Compared to other 3D reconstruction or tomography settings, this task poses two significant challenges: first, rays near black holes follow curved paths dictated by general relativity, and second, we only observe measurements from a single viewpoint. Our method captures the unknown emission field using a continuous volumetric function parameterized by a coordinate-based neural network, and uses knowledge of Keplerian orbital dynamics to establish correspondence between 3D points over time. Together, these enable BH-NeRF to recover accurate 3D emission fields, even in challenging situations with sparse measurements and uncertain orbital dynamics. This work takes the first steps in showing how future measurements from the Event Horizon Telescope could be used to recover evolving 3D emission around the supermassive black hole in our Galactic center.
Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 12 of its 50 references that are in the map. First posted on arXiv 7 Apr 2022.
Builds on
12 of 50 references.
References · 12
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Citing papers per year: 2022: 3; 2023: 6; 2024: 3; 2025: 7; 2026: 3.
22 papers.
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- 2022NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fieldscited by 152
- 2023SparseGS: Sparse View Synthesis using 3D Gaussian Splattingcited by 134
- 2024Advances in 3D Generation: A Surveycited by 63
- 2024SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problemscited by 24
- 2022Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fieldscited by 15
- 2025Reconstructing 4D Spatial Intelligence: A Surveycited by 14
- 2023Single View Refractive Index Tomography with Neural Fieldscited by 8
- 2023NeRFs: The Search for the Best 3D Representationcited by 7
- 2023Radar Fields: An Extension of Radiance Fields to SARcited by 7
- 2022Strong Lensing Source Reconstruction Using Continuous Neural Fieldscited by 6
- 2023Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Holecited by 5
- 2025Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fieldscited by 4
10 more
- 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weightscited by 3
- 2023Recovering a Molecule's 3D Dynamics from Liquid-phase Electron Microscopy Moviescited by 2
- 2026Dynamic Black-hole Emission Tomography with Physics-informed Neural Fieldscited by 1
- 2024Success Probability in Multi-View Imagingcited by 0
- 2025Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Tablecited by 0
- 2025Learning Null Geodesics for Gravitational Lensing Rendering in General Relativitycited by 0
- 2025Revealing Fine Structure in Protoplanetary Disks with Physics Constrained Neural Fieldscited by 0
- 2025NERD: Network-Regularized Diffusion Sampling For 3D Computed Tomographycited by 0
- 2026A Principled Self-Referenced Early Stopping Approach for Deep Image Priorcited by 0
- 2026Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomographycited by 0
- 2026Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomography24 Sep 2026
- 2026A Principled Self-Referenced Early Stopping Approach for Deep Image Prior24 May 2026
- 2026Dynamic Black-hole Emission Tomography with Physics-informed Neural Fields8 Feb 2026
- 2025NERD: Network-Regularized Diffusion Sampling For 3D Computed Tomography18 Nov 2025
- 2025Revealing Fine Structure in Protoplanetary Disks with Physics Constrained Neural Fields3 Sep 2025
- 2025Reconstructing 4D Spatial Intelligence: A Survey28 Jul 2025
- 2025Learning Null Geodesics for Gravitational Lensing Rendering in General Relativity21 Jul 2025
- 2025Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table13 Jun 2025
- 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights16 May 2025
- 2025Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields21 Apr 2025
- 2024SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problems6 Oct 2024
- 2024Success Probability in Multi-View Imaging15 Jul 2024
10 more
- 2024Advances in 3D Generation: A Survey31 Jan 2024
- 2023Radar Fields: An Extension of Radiance Fields to SAR20 Dec 2023
- 2023SparseGS: Sparse View Synthesis using 3D Gaussian Splatting30 Nov 2023
- 2023Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Hole11 Oct 2023
- 2023Single View Refractive Index Tomography with Neural Fields8 Sep 2023
- 2023Recovering a Molecule's 3D Dynamics from Liquid-phase Electron Microscopy Movies23 Aug 2023
- 2023NeRFs: The Search for the Best 3D Representation5 Aug 2023
- 2022Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields22 Nov 2022
- 2022NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields28 Oct 2022
- 2022Strong Lensing Source Reconstruction Using Continuous Neural Fields29 Jun 2022
- 2022NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fieldscited by 152
- 2023SparseGS: Sparse View Synthesis using 3D Gaussian Splattingcited by 134
- 2024Advances in 3D Generation: A Surveycited by 63
- 2022Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fieldscited by 15
- 2025Reconstructing 4D Spatial Intelligence: A Surveycited by 14
- 2023Single View Refractive Index Tomography with Neural Fieldscited by 8
- 2023NeRFs: The Search for the Best 3D Representationcited by 7
- 2023Radar Fields: An Extension of Radiance Fields to SARcited by 7
- 2022Strong Lensing Source Reconstruction Using Continuous Neural Fieldscited by 6
- 2023Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Holecited by 5
- 2025Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fieldscited by 4
- 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weightscited by 3
12 most cited of 20 All 20 (JSON)
- 2026Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomography24 Sep 2026
- 2026A Principled Self-Referenced Early Stopping Approach for Deep Image Prior24 May 2026
- 2026Dynamic Black-hole Emission Tomography with Physics-informed Neural Fields8 Feb 2026
- 2025Revealing Fine Structure in Protoplanetary Disks with Physics Constrained Neural Fields3 Sep 2025
- 2025Reconstructing 4D Spatial Intelligence: A Survey28 Jul 2025
- 2025Learning Null Geodesics for Gravitational Lensing Rendering in General Relativity21 Jul 2025
- 2025Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table13 Jun 2025
- 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights16 May 2025
- 2025Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields21 Apr 2025
- 2024Success Probability in Multi-View Imaging15 Jul 2024
- 2024Advances in 3D Generation: A Survey31 Jan 2024
- 2023Radar Fields: An Extension of Radiance Fields to SAR20 Dec 2023
12 newest of 20 All 20 (JSON)