Amount of Information and Measurement Uncertainty
Physical Science International Journal,
Page 1-8
DOI:
10.9734/psij/2020/v24i330179
Abstract
Aims: To acquaint specialists in the field of physics and technology, experimenters and theoreticians with the possibilities of using information theory to analyze the results of an experiment, without a statistical and subjective expert approach.
Place and Duration of Study: Mechanical & Refrigeration Consultation Expert, between December 2019 and February 2020.
Methodology: Using the information approach and calculating the amount of information contained in the model of measuring a physical constant, we formulate a quantitative indicator for analyzing the results of the experiment.
Results: The appropriateness of applying the described approach is checked when studying the database when measuring various physical constants. The approach is applicable to the analysis of results obtained both for a long and a short period of time.
Conclusion: The information-theoretical approach allows us to formulate a universal indicator of the threshold mismatch between the model and the phenomenon, applicable to all scientific and technical fields in which the International System of Units (SI) is used.
Keywords:
- CODATA
- Boltzmann constant
- Planck constant
- gravitational constant
- Hubble constant
- international system of units
- mathematical modeling
- relative uncertainty
How to Cite
References
(Accessed 10 March 2020)
Available:https://www.stm-assoc.org/2018_10_04_STM_Report_2018.pdf
Scientific and Technical Journal Articles, World Bank Data; 2019.
(Accessed 10 March 2020)
Available:https://data.worldbank.org/indicator/IP.JRN.ARTC.SC
Milton MJT, Possolo A. Trustworthy data underpin reproducible research. Nature Physics. 2020;16(2):117–119.
(Accessed 10 March 2020)
Available:https://sci-hub.tw/10.1038/s41567-019-0780-5
Gelman A. Essay: The experiments are fascinating. But nobody can repeat them. The New York Times; 2018.
(Accessed 10 March 2020)
Available:https:
//www.nytimes.com/2018/11/19/science/science-research-fraud-reproducibility.html
Trouble at the Lab. The Economist.
(Accessed 10 March 2020)
Available:https://www.economist.com/briefing/2013/10/18/trouble-at-the-lab
Chapman CA, Bicca-Marques JC, Calvignac-Spencer S, Fan P, Peter J, Fashing PJ, Jan Gogarten J, et al. Games academics play and their consequences: How authorship, h-index and journal impact factors are shaping the future of academia. Proceedings of the Royal Society B: Biological Sciences. 2019;286: 1-9.
(Accessed 11 March 2020)
Available:https://sci-hub.tw/10.1098/rspb.2019.2047
Buchanan M. The certainty of uncertainty. Nature Physics. 2020;16(2):120–120.
(Accessed 11 March 2020)
Available:https://sci-hub.tw/10.1038/s41567-020-0786-z
Baker M. Is there a reproducibility crisis? Nature. 2017;533:452-454.
(Accessed 11 March 2020)
Available:https://www.nature.com/news/
polopoly_fs/1.19970!/menu/main/topColumns/topLeftColumn/pdf/533452a.pdf
Wang L, Sofer Z, Pumera M. Will any crap we put into graphene increase its electro-catalic effect? ACS Nano. 2020;14:21–25.
(Accessed 11 March 2020)
Available:https://sci-hub.tw/10.1021/acsnano.9b00184
Freedman LP, Cockburn IM, Simcoe TS. The economics of reproducibility in preclinical research. PLoS Biol. 2015;13(6):e1002165.
(Accessed 11 March 2020)
Available:https://doi.org/10.1371/journal.pbio.1002165
Chang AC, Phillip L. Is economics research replicable? Sixty Published Papers from Thirteen Journals Say “Usually Not”. Finance and Economics Discussion Series. Washington: Board of Governors of the Federal Reserve System. 2015;1-26.
(Accessed 11 March 2020)
Available:http://dx.doi.org/10.17016/FEDS.2015.083
Menin B. Uncertainty assessment of refrigeration equipment using an information approach. Journal of Applied Mathematics and Physics. 2020;8(1):23–37.
(Accessed 30 January 2020)
Available:https://www.scirp.org/journal/Paperabs.aspx?PaperID=97483
Open Science Collaboration. Estimating the reproducibility of psychological science. Science. 2015;349:aac4716.
(Accessed 11 March 2020)
Available:https://sci-hub.tw/10.1126/science.aac4716
Menin B. Information measure approach for calculating model uncertainty of physical phenomena. American Journal of Computational and Applied Mathematics. 2017;7(1):11–24.
(Accessed 11 March 2020)
Available:http://article.sapub.org/10.5923.j.ajcam.20170701.02.html
Brillouin L. Science and information theory. Dover, New York; 2004.
Menin B. Progress in reducing the uncertainty of measurement of Planck’s constant in terms of the information approach. Physical Science International Journal. 2019;21(2):1–11.
(Accessed 11 March 2020)
Available:http://www.journalpsij.com/index.php/PSIJ/article/view/30104/56478
Menin B. Hubble constant tension in terms of information approach. Physical Science International Journal. 2019;23(4):1–15.
(Accessed 11 March 2020)
Available:https://doi.org/10.9734/psij/2019/v23i430165
Menin B. Precise measurements of the gravitational constant: Revaluation by the information approach. Journal of Applied Mathematics and Physics. 2019;7(6): 1272–1288.
(Accessed 11 March 2020)
Available:http://file.scirp.org/pdf/JAMP_2019062614403787.pdf
Menin B. The Boltzmann constant: Evaluation of measurement relative uncertainty using the information approach. Journal of Applied Mathematics and Physics. 2019;7(3):486–504.
(Accessed 11 March 2020)
Available:10.4236/jamp.2019.73035
Gorban II. The physical-mathematical theory of hyper-random phenomena. Computer Science Journal of Moldova. 2017;25(2):145–194.
(Accessed 11 March 2020)
Available:http://www.math.md/files/csjm/v25-n2/v25-n2-(pp145-194).pdf
-
Abstract View: 1467 times
PDF Download: 686 times