Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders
Abstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that...
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Nature Portfolio
2024-12-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-024-01482-5 |
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| author | Alexander Scheinker Reeju Pokharel |
| author_facet | Alexander Scheinker Reeju Pokharel |
| author_sort | Alexander Scheinker |
| collection | DOAJ |
| description | Abstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements. |
| format | Article |
| id | doaj-art-945a8e67a2904660b35f96d008445253 |
| institution | Kabale University |
| issn | 2057-3960 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Computational Materials |
| spelling | doaj-art-945a8e67a2904660b35f96d0084452532024-12-22T12:36:45ZengNature Portfolionpj Computational Materials2057-39602024-12-0110111510.1038/s41524-024-01482-5Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencodersAlexander Scheinker0Reeju Pokharel1Applied Electrodynamics, Los Alamos National LaboratoryMaterial Science and Technology, Los Alamos National LaboratoryAbstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.https://doi.org/10.1038/s41524-024-01482-5 |
| spellingShingle | Alexander Scheinker Reeju Pokharel Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders npj Computational Materials |
| title | Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| title_full | Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| title_fullStr | Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| title_full_unstemmed | Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| title_short | Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| title_sort | enabling dynamic 3d coherent diffraction imaging via adaptive latent space tuning of generative autoencoders |
| url | https://doi.org/10.1038/s41524-024-01482-5 |
| work_keys_str_mv | AT alexanderscheinker enablingdynamic3dcoherentdiffractionimagingviaadaptivelatentspacetuningofgenerativeautoencoders AT reejupokharel enablingdynamic3dcoherentdiffractionimagingviaadaptivelatentspacetuningofgenerativeautoencoders |