Event
Ph.D. Dissertation Defense: Itay Ozer
Thursday, November 19, 2026
1:00 p.m.
AVW 2460
Announcement: Ph.D. Dissertation Defense
Name: Itay Ozer
Committee:
Professor (Chair): Prof. Saikat Guha
Professor: Prof. Mohammad Hafezi
Professor: Prof. Sanghamitra Dutta
Professor: Prof. Amit Ashok
Professor (Dean's Representative): Prof. Jay Deep Sau
Date/time: November 19th, 2026 at 1:00 PM to 3:00 PM
Location: AVW 2460
Title: Programmable Spatial-Mode Processing for Optical Imaging, Sensing, and Linear Interferometry
Abstract: Pre-detection processing of light enables physically optimal measurements by converting otherwise inaccessible optical information into measurable intensity, leading to fundamentally improved estimation precision beyond what is achievable with direct detection alone. In this dissertation we present the experimental development and demonstration of a programmable linear optical processor based spatial mode engineering. At the center of this work is the realization of spatial light modulator (SLM)-based reconfigurable spatial mode sorter using multi plane light conversion (MPLC), which enables high-dimensional unitary transformations on optical fields.
The core premise of this research is that conventional optical detection irreversibly discards information due to measurement constraints, whereas appropriately designed pre-detection optical processing can preserve and extract information that would otherwise be inaccessible. By implementing tailored mode transformations prior to detection, the systems developed in this work approach fundamental performance limits in estimation and discrimination tasks.
First, an adaptive super-resolution imaging framework is experimentally demonstrated, in which a programmable mode sorter is used in a two-stage measurement strategy to estimate sub-Rayleigh separations without prior knowledge of the object. By combining direct imaging for centroid estimation with spatial-mode demultiplexing for separation estimation, this approach overcomes limitations of traditional imaging systems and approaches quantum-optimal performance.
Second, the dissertation presents the experimental realization of a quantum-optimal coronagraph using spatial mode sorting, demonstrating enhanced sensitivity for detecting faint sources in the presence of bright backgrounds. This work highlights the utility of mode-selective detection in suppressing dominant modes and isolating weak signals.
Third, a general-purpose programmable linear optical interferometer is demonstrated using MPLC, enabling arbitrary unitary transformations on pixel-mode bases. This platform establishes MPLC as a scalable and flexible alternative to integrated photonics for high-dimensional optical processing, with applications in quantum information and classical optical computing.
Finally, an experimental implementation of quantum-optimal measurement strategies for optical parameter estimation is presented, validating theoretical predictions for optimal information extraction in realistic systems.
Across all contributions, this dissertation emphasizes experimental realization, including system design, calibration, error mitigation, and data processing. The results demonstrate that programmable spatial-mode processing is a powerful paradigm for enhancing optical sensing and information processing, bridging the gap between theoretical quantum limits and practical optical systems.
