Model uncertainty and reference value of the Planck constant

Statistical parametric models are proposed to explain the values of the Planck constant obtained by comparing electrical and mechanical powers and by counting atoms in Si 28 enriched crystals. They assume that uncertainty contributions -- having heterogeneous, datum-specific, variances -- might not be included in the error budgets of some of the measured values. Model selection and model averaging are used to investigate data consistency, to identify a reference value of the Planck constant, and to include the model uncertainty in the error budget.

[1]  Shun-ichi Amari,et al.  Methods of information geometry , 2000 .

[2]  J. Neyman Outline of a Theory of Statistical Estimation Based on the Classical Theory of Probability , 1937 .

[3]  C. A. Sanchez,et al.  A determination of Planck's constant using the NRC watt balance , 2014 .

[4]  Clemens Elster,et al.  Analysis of key comparisons: estimating laboratories' biases by a fixed effects model using Bayesian model averaging , 2010 .

[5]  Michael Stock,et al.  Calibration campaign against the international prototype of the kilogram in anticipation of the redefinition of the kilogram part I: comparison of the international prototype with its official copies , 2015 .

[6]  K. Pearson On the Criterion that a Given System of Deviations from the Probable in the Case of a Correlated System of Variables is Such that it Can be Reasonably Supposed to have Arisen from Random Sampling , 1900 .

[7]  M. Stock Watt balance experiments for the determination of the Planck constant and the redefinition of the kilogram , 2013 .

[8]  Clemens Elster,et al.  Objective Bayesian Inference for a Generalized Marginal Random Effects Model , 2016 .

[9]  B. Toman,et al.  Alternative analyses of measurements of the Planck constant , 2012 .

[10]  G. Mana,et al.  Model selection in the average of inconsistent data: an analysis of the measured Planck-constant values , 2012, 2007.09428.

[11]  Karl Pearson F.R.S. X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling , 2009 .

[12]  G. Mana,et al.  Accurate measurements of the Avogadro and Planck constants by counting silicon atoms , 2013 .

[13]  B. Taylor,et al.  CODATA recommended values of the fundamental physical constants: 2006 | NIST , 2007, 0801.0028.

[14]  Barry N. Taylor,et al.  Fundamental Physical Constants , 2019, Spin-Label Electron Paramagnetic Resonance Spectroscopy.

[15]  Richard Davis,et al.  Towards a new SI: a review of progress made since 2011 , 2014 .

[16]  D. B. Newell,et al.  A summary of the Planck constant measurements using a watt balance with a superconducting solenoid at NIST , 2015, 1501.06796.

[17]  G. Mana,et al.  Bayesian estimate of the degree of a polynomial given a noisy data sample , 2013, 1307.4602.

[18]  R. Steiner History and progress on accurate measurements of the Planck constant , 2013, Reports on progress in physics. Physical Society.

[19]  I Busch,et al.  Improved measurement results for the Avogadro constant using a 28Si-enriched crystal , 2015, 1512.05642.

[20]  Yasushi Azuma,et al.  Counting the atoms in a 28Si crystal for a new kilogram definition , 2011 .

[21]  C. Palmisano,et al.  Interval estimations in metrology , 2014, 1402.0248.

[22]  Volker Dose Bayesian estimate of the Newtonian constant of gravitation , 2007 .

[23]  M. Borys,et al.  The Correlation of the NA Measurements by Counting 28Si Atoms , 2015, 1512.06138.