Determining the Proximity Effect Induced Magnetic Moment in Graphene by Polarized Neutron Reflectivity and X-ray Magnetic Circular Dichroism

Aboljadayel, Razan; Kinane, C. J.; Vaz, C. A. F.; Love, D. M.; Weatherup, Robert S.; Braeuninger‐Weimer, Philipp; Martin, M. -B.; Ionescu, A.; Caruana, A. J.; Charlton, T. R.; Llandro, J.; Monteiro, Pedro M. S.; Barnes, C. H. W.; Hofmann, S.; Langridge, S.

doi:10.48550/arxiv.2101.09946

Cited by 2 publications

(2 citation statements)

References 52 publications

(97 reference statements)

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“…This work will not introduce Bayesian or sampling methods for neutron and X-ray reflectometry analysis. For those unfamiliar with these techniques, we suggest the work of Sivia and co-workers (Sivia & Webster, 1998;Sivia & Skelling, 2006) and more recent work focusing on reflectometry analysis (Hughes et al, 2019;McCluskey et al, 2020;Nelson & Prescott, 2019;Aboljadayel et al, 2021). We hope that this paper will inform best practices in data sharing from reflectometry analysis and inspire software developers to enable these to be accessed easily by the user.…”

Section: Introductionmentioning

confidence: 96%

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

McCluskey¹,

Caruana²,

Kinane³

et al. 2023

J Appl Cryst

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As a result of the availability of modern software and hardware, Bayesian analysis is becoming more popular in neutron and X-ray reflectometry analysis. The understandability and replicability of these analyses may be harmed by inconsistencies in how the probability distributions central to Bayesian methods are represented in the literature. Herein advice is provided on how to report the results of Bayesian analysis as applied to neutron and X-ray reflectometry. This includes the clear reporting of initial starting conditions, the prior probabilities, the results of any analysis and the posterior probabilities that are the Bayesian equivalent of the error bar, to enable replicability and improve understanding. It is believed that this advice, grounded in the authors' experience working in the field, will enable greater analytical reproducibility in the work of the reflectometry community, and improve the quality and usability of results.

show abstract

Section: Introductionmentioning

confidence: 96%

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

McCluskey¹,

Caruana²,

Kinane³

et al. 2023

J Appl Cryst

View full text Add to dashboard Cite

show abstract

“…This work will not introduce Bayesian or sampling methods for neutron and X-ray reflectometry analysis. For those unfamiliar with these techniques, we suggest the work of Sivia and co-workers [5,15] and more recent work focusing on reflectometry analysis [7,14,16,17]. We hope that this work will inform best practices in data sharing from reflectometry analysis and inspire software developers to enable these to be accessed easily by the user.…”

Section: Introductionmentioning

confidence: 99%

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

McCluskey¹,

Caruana²,

Kinane³

et al. 2022

Preprint

View full text Add to dashboard Cite

Driven by the availability of modern software and hardware, Bayesian analysis is becoming more popular in neutron and X-ray reflectometry analysis. The understandability and replicability of these analyses may be harmed by inconsistencies in how the probability distributions central to Bayesian methods are represented in the literature. Herein, we provide advice on how to report the results of Bayesian analysis as applied to neutron and X-ray reflectometry. This includes the clear reporting of initial starting conditions, the prior probabilities, and results of any analysis, and the posterior probabilities that are the Bayesian equivalent of the error bar, to enable replicability and improve understanding. We believe that this advice, grounded in our experience working in the field, will enable greater analytical reproducibility among the reflectometry community, as well as improve the quality and usability of results.

show abstract

Determining the Proximity Effect Induced Magnetic Moment in Graphene by Polarized Neutron Reflectivity and X-ray Magnetic Circular Dichroism

Cited by 2 publications

References 52 publications

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

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