vix.ing · top · new · best · stats · spec

Maximizing the information gain of a single ion microscope using bayes experimental design

2016/04/29 by Georg Jacob, Karin Groot-Berning, Ulrich G. Poschinger +2 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Electron Microscopy Techniques and Applications #Bayes' theorem #Bayesian experimental design #Design of experiments #Detector #Event (particle physics) #Extraction (chemistry) #Force Microscopy Techniques and Applications #Microscope #Nanoscopic scale #Quantum Information and Cryptography #Transmission (telecommunications) #quant-ph

paper · pdf · doi:10.1117/12.2227745

published as Proc. SPIE 9900, Quantum Optics, 99001A (April 29, 2016) · 8 pages, 7 figures, From SPIE Conference Volume 9900, Quantum Optics, Jürgen Stuhler; Andrew J. Shields; Brussels, Belgium, April 03, 2016

openalex publication_date 2016/04/29 · arxiv created 2016/05/17 · arxiv updated 2016/05/18 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05

Abstract

We demonstrate nanoscopic transmission microscopy, using a deterministic single particle source, and compare the resulting images in terms of signal-to-noise ratio with those of conventional Poissonian sources. Our source is realized by deterministic extraction of laser-cooled calcium ions from a Paul trap. Gating by the extraction event allows for the suppression of detector dark counts by six orders of magnitude. Using the Bayes experimental design method, the deterministic characteristics of this source are harnessed to maximize information gain, when imaging structures with a parametrizable transmission function. We demonstrate such optimized imaging by determining parameter values of one and two dimensional transmissive structures.

Citations

Cited by