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  • Open Access

Achieving subtemporal resolution in the analysis of two-state single-molecule trajectories

Erik Clarkson and Tobias Ambjörnsson*

  • Centre for Environmental and Climate Science, Lund University, Lund, Sweden

  • *Contact author: tobias.ambjornsson@mgeo.lu.se
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Phys. Rev. Research 8, 013115 – Published 30 January, 2026

DOI: https://doi.org/10.1103/ccdh-hhx8

Abstract

Although spatial resolution in fluorescence microscopy and related fields has advanced to the nanometer scale, time resolution has remained essentially unchanged and is set by the camera system’s imaging time. Yet adequate time resolution is crucial for information acquisition about, for instance, dynamical processes in cells. This acquisition typically proceeds by analyzing biomolecular trajectories from single-particle tracking experiments, in terms of a standard discrete-time hidden Markov model. This type of analysis assumes, however, that subsampling time events that happen during imaging time can be neglected, which is rarely the case. To remedy this, we here introduce an algorithm that efficiently calculates the exact contribution of state switches to the likelihood of observed trajectories. This is made possible by our analytic derivation of generalized transition probabilities—which we call transition-accretion probabilities—that probabilistically capture unseen switching behavior during data acquisition. We do in-silico Bayesian model selection and parameter inference, and demonstrate that our subsampling time hidden Markov model approach outperforms the standard variant (applicable to slow kinetics). Our method and associated free-to-use software opens up for precise and reliable parameter estimation across a variety of single-molecule experiments, irrespective of the temporal resolution of the setup.

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Phys. Rev. Research 8, 013115– Published 30 January, 2026
  • Received 25 September 2025
  • Accepted 28 December 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by Bibsam.

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