activity
20142026
most citedExperimentally quantifying the advantages of weak-value-based metrology

118 citations · 123 across the 5 of their papers we have counts for

collaborators

6 papers

physics.optics2026

Shot Noise Limited Triangulation

John C. Howell, Andrew N. Jordan

We design a system-level architecture for approaching the shot noise limit for passive triangulation of a quasi-monochromatic point source. Our emphasis is not in the novelty of th…

eess.SP2025

Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder

Robert Czupryniak, Abhishek Chakraborty, Andrew N. Jordan +1

We apply machine learning methods to demonstrate range superresolution in remote sensing radar detection. Specifically, we implement a denoising autoencoder to estimate the distanc…

quant-ph2025

Superoscillations and Physical Applications

Andrew N. Jordan, John C. Howell, Nicholas Vamivakas +1

This book chapter gives a selective review of physical implementations and applications of superoscillations and associated phenomena. We introduce the field by reviewing simple ex…

physics.optics2024

Reconstructing Superoscillations Buried Deeply in Noise

Derek D. White, Shunxing Zhang, Barbara Soda +4

We utilize a method using frequency combs to construct waves that feature superoscillations - local regions of the wave that exhibit a change in phase that the bandlimits of the wa…

eess.SP2024★ 5 cited

The Best Radar Ranging Pulse to Resolve Two Reflectors

Andrew N. Jordan, John C. Howell, Achim Kempf +2

Previous work established fundamental bounds on subwavelength resolution for the radar range resolution problem, called superradar [Phys. Rev. Appl. 20, 064046 (2023)]. In this wor…

quant-ph2014★ 118 cited

Experimentally quantifying the advantages of weak-value-based metrology

Gerardo I. Viza, Julián Martínez-Rincón, Gabriel B. Alves +2

We experimentally investigate the relative advantages of implementing weak-value-based metrology versus standard methods. While the techniques outlined herein apply more generally,…