Optical-Memory Transport Imaging: Extension to Stochastic Diffusion

Abstract

Finite-memory optical tracers can encode transport properties through their previously experienced excitation. Using such memory features, harboured in the population of excitable long-lived electronic states within the emitters, instantaneous localization assessments are not needed to determine their transport properties. Here we formulate this principle for monitoring of stochastic transport extracted from transport-history integral over conditional transport histories. Under structured illumination, this history yields a measurable transfer-function response from which scalar and tensor diffusion are reconstructed without time-resolved acquisition. Fisher-information analysis identifies the optimal operating regime and yields first-principles, parameter-free predictions of scalar and tensor reconstruction precision, in quantitative agreement with independent Monte Carlo simulations. These results establish finite optical memory as a general principle for stochastic transport imaging.

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BibTeX RIS

BibTeX

@misc{liu2026opticalmemory,
  title = {{Optical-Memory Transport Imaging: Extension to Stochastic Diffusion}},
  author = {Haichun Liu and Jerker Widengren},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.25946},
  eprint = {2609.25946},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.25946},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - Optical-Memory Transport Imaging: Extension to Stochastic Diffusion
AU  - Haichun Liu
AU  - Jerker Widengren
PY  - 2026
DA  - 2026/09/22
PB  - arXiv
DO  - 10.48550/arxiv.2609.25946
UR  - https://arxiv.org/abs/2609.25946
AB  - Finite-memory optical tracers can encode transport properties through their previously experienced excitation. Using such memory features, harboured in the population of excitable long-lived electronic states within the emitters, instantaneous localization assessments are not needed to determine their transport properties. Here we formulate this principle for monitoring of stochastic transport extracted from transport-history integral over conditional transport histories. Under structured illumination, this history yields a measurable transfer-function response from which scalar and tensor diffusion are reconstructed without time-resolved acquisition. Fisher-information analysis identifies the optimal operating regime and yields first-principles, parameter-free predictions of scalar and tensor reconstruction precision, in quantitative agreement with independent Monte Carlo simulations. These results establish finite optical memory as a general principle for stochastic transport imaging.
ER  -

Abstract

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