CIF: Small: Sequential and Compound Estimation for Computational Imaging Systems

Sponsor: National Science Foundation

Award Number: 1815896

Abstract:

The widespread use of imaging technologies across biology, chemistry, material science, medicine, and other fields is motivated by the great innate human ability for visual information processing. Imaging is often limited, however, by the damage to a sample caused by the imaging process, such as sputtering due to the incident ion or electron beam in scanned beam microscopy. With conventional methods, a sample may be destroyed before enough information has been gained to form a useful image. This project develops methods for reducing the necessary dose in microscopy systems. This may make it possible to image molecular or biological species not before imaged, or to increase the speed of imaging so that new dynamic phenomena are revealed. The project also includes dissemination of results to broad audiences through expository writing, general-audience talks, cross-disciplinary training, and production of teaching materials.

Poisson models are often exploited when measured signals are due to small numbers of detected particles. A major premise of this project is to combine the Poisson modeling of such detection counts with Poisson modeling of the numbers of interacting particles in low-current beams. The project develops theory and methods for the resulting compound estimation problems. The project explores the use of time-resolved sensing to reduce the uncertainty due to the source shot noise in compound processes. Furthermore, time-resolved sensing enables the decomposition of a data collection process into a sequence of less-damaging steps, and the project will develop theory and methods for sequential estimation and adaptive data collection. Analysis will inspire and be informed by proof-of-concept experiments. The ultimate limit of learning about a sample without damaging it is achieved with certain quantum-mechanical interaction-free measurements. The project will develop theory for sequential interaction-free measurements to establish when they may be superior to conventional measurements.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

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