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Efficient use of Monte Carlo: The Fast Correlation Coefficient
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0002-7595-8024
(Laboratory for Reactor Physics Systems Behaviour, Paul Scherrer Institut, Villigen, Switzerland)
NRG.
2018 (English)In: Article in journal (Refereed) Submitted
##### Abstract [en]

Monte Carlo methods are increasingly used for Nuclear Data evaluation and propagation. In particular, the Total Monte Carlo (TMC) Method [1] has proved to be an efficient tool. A disadvantage of MC is that statistical uncertainties are also introduced. For evaluating the propagated nuclear data uncertainty, this was addressed with the so-called Fast-TMC method \cite{Rochman14}, which has become the standard route for TMC uncertainty propagation.Today, the standard way to visualize and interpret Nuclear Data (ND) co-variances is by the use of the Person correlation coefficient.$\rho = \frac{{{\mathop{\rm cov}} ({x},{y})}}{{{\sigma _{{x}}} \cdot {\sigma _{{y}}}}},$where x or y can be any parameter dependent on ND. As addressed in \cite{Rochman14}, $\sigma$ has both a ND component, $\sigma_{ND}$, and a statistical component, $\sigma_{stat}$. The contribution from $\sigma_{stat}$ decreases the value of $\rho$, and hence it is easy to underestimate the impact of the correlation. One way to address this is to minimize $\sigma_{stat}$ by using longer run-times. Alternatively, as proposed here, a so-called fast correlation coefficient is used,${\rho _{fast}} = \frac{{{\mathop{\rm cov}} (x,y) - {\mathop{\rm cov}} ({x_{stat}},{y_{stat}})}}{{\sqrt {\sigma _x^2 - \sigma _{x,stat}^2} \cdot \sqrt {\sigma _y^2 - \sigma _{y,stat}^2} }}$In many cases, ${\mathop{\rm cov}} ({x_{stat}},{y_{stat}})$ can be assumed to be zero.The paper explores two examples, correlations from the NRG High Flux Reactor spectrum \cite{Asquith16} and the correlations between different integral criticality experiments. The impact of the use of $\rho_{fast}$ is quantified, and the implication of the results are discussed.

2018.
##### National Category
Subatomic Physics
##### Identifiers
OAI: oai:DiVA.org:uu-339229DiVA, id: diva2:1175196
##### Conference
4th edition of the International Workshop on Nuclear Data Covariances, 2017
Available from: 2018-01-17 Created: 2018-01-17 Last updated: 2018-01-17

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Helgesson, PetterSjöstrand, Henrik

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Applied Nuclear Physics
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Subatomic Physics

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Cite
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