dc.contributor.advisor | Manoharan, Vinothan N. | |
dc.contributor.author | Alexander, Ronald D. | |
dc.date.accessioned | 2020-10-16T14:15:45Z | |
dc.date.created | 2020-05 | |
dc.date.issued | 2020-05-14 | |
dc.date.submitted | 2020 | |
dc.identifier.citation | Alexander, Ronald D. 2020. Generative Models for Digital Holographic Microscopy. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. | |
dc.identifier.uri | https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365842 | * |
dc.description.abstract | In the past few years, the venerable field of holographic microscopy has been revitalized by computational data analysis. It is now possible to fit a generative (forward) model of scattering directly to experimentally obtained holograms. This approach enables precision measurements: it allows the motion of colloidal particles and biological organisms to be tracked with nanometer-scale precision and their optical properties inferred on a particle-by-particle basis. In this thesis, I discuss how the model-based inference approach to holographic microscopy is opening up new applications. I also discuss how it must evolve to meet the needs of new applications that demand lower systematic uncertainties and maximum precision. In this context, I present some new and previous results on how modeling the optical train of the microscope can enable better measurements of the positions of spherical and nonspherical colloidal particles. Finally, I discuss how machine learning might play a role in future advances. Though I do not exhaustively catalogue all the developments in this field, I hope that by presenting a few examples and some new results I can spotlight open questions and opportunities. | |
dc.description.sponsorship | Physics | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dash.license | LAA | |
dc.subject | Generative Modeling | |
dc.subject | Holography | |
dc.subject | | |
dc.title | Generative Models for Digital Holographic Microscopy | |
dc.type | Thesis or Dissertation | |
dash.depositing.author | Alexander, Ronald D. | |
dc.date.available | 2020-10-16T14:15:45Z | |
thesis.degree.date | 2020 | |
thesis.degree.grantor | Graduate School of Arts & Sciences | |
thesis.degree.grantor | Graduate School of Arts & Sciences | |
thesis.degree.level | Doctoral | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Philosophy | |
thesis.degree.name | Doctor of Philosophy | |
dc.contributor.committeeMember | Samuel, Aravinthan | |
dc.contributor.committeeMember | Rycroft, Chris | |
dc.type.material | text | |
thesis.degree.department | Physics | |
thesis.degree.department | Physics | |
dash.identifier.vireo | | |
dash.author.email | ronaldalexander0@gmail.com | |