Journal article
A Bayesian perspective on single-shot laser characterization
- Abstract:
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We introduce a Bayesian framework for measuring spatio-temporal couplings (STCs) in ultra-intense lasers that reconceptualizes what constitutes a ’single-shot’ measurement. Moving beyond traditional distinctions between single- and multi-shot devices, our approach provides rigorous criteria for determining when measurements can truly resolve individual laser shots rather than statistical averages. By contextualizing single measurements, this framework shows that single-shot capability is not an intrinsic device property but emerges from the relationship between measurement precision and predictability. Implementing this approach with a new measurement device at the ATLAS-3000 petawatt laser, we provide the first quantitative uncertainty bounds on pulse front tilt and curvature. Notably, we observe that our Bayesian method reduces uncertainty by up to 60% compared to traditional approaches. Through this analysis, we reveal how the interplay between measurement precision and intrinsic system variability defines achievable resolution—insights that have direct implications for applications where precise control of laser-matter interaction is critical.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, eps, 10.8MB, Terms of use)
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- Publisher copy:
- 10.1073/pnas.2510645122
Authors
- Publisher:
- National Academy of Sciences
- Journal:
- Proceedings of the National Academy of Sciences More from this journal
- Volume:
- 122
- Issue:
- 43
- Article number:
- e2510645122
- Publication date:
- 2025-10-24
- Acceptance date:
- 2025-09-02
- DOI:
- EISSN:
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1091-6490
- ISSN:
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0027-8424
- Language:
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English
- Keywords:
- Pubs id:
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2300180
- Local pid:
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pubs:2300180
- Deposit date:
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2025-10-17
Terms of use
- Copyright holder:
- Esslinger et al.
- Copyright date:
- 2025
- Rights statement:
- Copyright © 2025 the Author(s). Published by PNAS. This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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