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Autori principali: Schultze, Steffen, Grubmüller, Helmut
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2510.25654
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author Schultze, Steffen
Grubmüller, Helmut
author_facet Schultze, Steffen
Grubmüller, Helmut
contents MINFLUX microscopy allows for localization of fluorophores with nanometer precision using targeted scanning with an illumination profile with a minimum. However, current scanning patterns and the overall procedure are based on heuristics, and may therefore be suboptimal. Here we present a rigorous Bayesian that offers maximal resolutions from either minimal detected photons or minimal exposures. We estimate using simulated localization runs that this approach should reduce the number of photons required for 1 nm resolution by a factor of about four.
format Preprint
id arxiv_https___arxiv_org_abs_2510_25654
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bayesian MINFLUX localization microscopy
Schultze, Steffen
Grubmüller, Helmut
Computational Physics
Data Analysis, Statistics and Probability
MINFLUX microscopy allows for localization of fluorophores with nanometer precision using targeted scanning with an illumination profile with a minimum. However, current scanning patterns and the overall procedure are based on heuristics, and may therefore be suboptimal. Here we present a rigorous Bayesian that offers maximal resolutions from either minimal detected photons or minimal exposures. We estimate using simulated localization runs that this approach should reduce the number of photons required for 1 nm resolution by a factor of about four.
title Bayesian MINFLUX localization microscopy
topic Computational Physics
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2510.25654