Gravitationally Lensed Black Hole Emission Tomography
Aviad Levis, Pratul P. Srinivasan, Andrew A. Chael, Ren Ng, Katherine L. Bouman
摘要
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.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper9
- NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance FieldsLiangchen Song, Anpei Chen, Zhong Li, Zhang Chen 等IEEE VR 2023 · 被引用 246 次
- Recovering a Molecule's 3D Dynamics from Liquid-phase Electron Microscopy MoviesEnze Ye, Yuhang Wang, Hong Zhang, Yiqin Gao 等ICCV 2023 · 被引用 4 次
- Single View Refractive Index Tomography with Neural FieldsBrandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan 等CVPR 2024 · 被引用 4 次
- UGoDIT: Unsupervised Group Deep Image Prior Via Transferable WeightsShijun Liang, Ismail Alkhouri, Siddhant Gautam, Qing Qu 等NeurIPS 2025 · 被引用 3 次
- Dynamic Black-hole Emission Tomography with Physics-informed Neural FieldsBerthy T. Feng, Andrew A. Chael, David Bromley, Aviad Levis 等CVPR 2026 · 被引用 1 次
它引用的顶会 Paper9
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional DomainsMatthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil 等NeurIPS 2020 · 被引用 4,036 次
- Nerfies: Deformable Neural Radiance FieldsKeunhong Park, Utkarsh Sinha, Jonathan T. Barron, Sofien Bouaziz 等ICCV 2021 · 被引用 1,442 次
- Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular VideoEdgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer 等ICCV 2021 · 被引用 617 次
- Animatable Neural Radiance Fields for Modeling Dynamic Human BodiesSida Peng, Junting Dong, Qianqian Wang, Shangzhan Zhang 等ICCV 2021 · 被引用 461 次
- In-the-Wild Single Camera 3D Reconstruction Through Moving Water SurfacesJinhui Xiong, Wolfgang HeidrichICCV 2021 · 被引用 24 次
相关 Paper
- Learning Null Geodesics for Gravitational Lensing Rendering in General RelativityMingyuan Sun, Zheng Fang, Jiaxu Wang, Kunyi Zhang 等ICCV 2025
- BHCast: Unlocking Black Hole Plasma Dynamics from a Single Blurry Image with Long-Term ForecastingRenbo Tu, Ali SaraerToosi, Nicholas S. Conroy, Gennady Pekhimenko 等CVPR 2026
- Inference of Black Hole Fluid-Dynamics from Sparse Interferometric MeasurementsAviad Levis, Daeyoung Lee, Joel A. Tropp, Charles F. Gammie 等ICCV 2021 · 被引用 10 次
- Revealing the 3D Cosmic Web through Gravitationally Constrained Neural FieldsBrandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan 等ICLR 2025
- Transient Neural Radiance Fields for Lidar View Synthesis and 3D ReconstructionAnagh Malik, Parsa Mirdehghan, Sotiris Nousias, Kyros Kutulakos 等NeurIPS 2023 · 被引用 40 次
