In theoretical physics, fine-tuning is the process in which parameters of a model must be adjusted very precisely in order to fit with certain observations.
Theories requiring fine-tuning are regarded as problematic in the absence of a known mechanism to explain why the parameters happen to have precisely the observed values that they return. The heuristic rule that parameters in a fundamental physical theory should not be too fine-tuned is called naturalness.[1][2]
Background
editThis section needs additional citations for verification. (June 2023) |
The idea that naturalness will explain fine tuning was brought into question by Nima Arkani-Hamed, a theoretical physicist, in his talk "Why is there a Macroscopic Universe?", a lecture from the mini-series "Multiverse & Fine Tuning" from the "Philosophy of Cosmology" project, a University of Oxford and Cambridge Collaboration 2013. In it he describes how naturalness has usually provided a solution to problems in physics; and that it had usually done so earlier than expected. However, in addressing the problem of the cosmological constant, naturalness has failed to provide an explanation though it would have been expected to have done so a long time ago.
The necessity of fine-tuning leads to various problems that do not show that the theories are incorrect, in the sense of falsifying observations, but nevertheless suggest that a piece of the story is missing. For example, the cosmological constant problem (why is the cosmological constant so small?); the hierarchy problem; and the strong CP problem, among others.
Example
editAn example of a fine-tuning problem considered by the scientific community to have a plausible "natural" solution is the cosmological flatness problem, which is solved if inflationary theory is correct: inflation forces the universe to become very flat, answering the question of why the universe is today observed to be flat to such a high degree.[citation needed]
Measurement
editAlthough fine-tuning was traditionally measured by ad hoc fine-tuning measures, such as the Barbieri-Giudice-Ellis measure, over the past decade many scientists recognized that fine-tuning arguments were a specific application of Bayesian statistics.[3][4][5][6][7][8]
See also
editReferences
edit- ^ Grinbaum, Alexei (1 February 2012). "Which Fine-Tuning Arguments Are Fine?". Foundations of Physics. 42 (5): 615–631. arXiv:0903.4055. Bibcode:2012FoPh...42..615G. doi:10.1007/s10701-012-9629-9. S2CID 15590514.
- ^ Giudice, Gian (2008). "Naturally Speaking: The Naturalness Criterion and Physics at the LHC". LHC Perspectives. Perspectives on LHC Physics. pp. 155–178. arXiv:0801.2562. Bibcode:2008plnc.book..155G. doi:10.1142/9789812779762_0010. ISBN 978-981-277-975-5. S2CID 15078813.
- ^ Barbieri, Riccardo; Giudice, Gian Francesco (August 1988). "Upper bounds on supersymmetric particle masses". Nuclear Physics B. 306 (1): 63–76. Bibcode:1988NuPhB.306...63B. doi:10.1016/0550-3213(88)90171-X.
- ^ Fowlie, Andrew; Balazs, Csaba; White, Graham; Marzola, Luca; Raidal, Martti (17 August 2016). "Naturalness of the relaxion mechanism". Journal of High Energy Physics. 2016 (8): 100. arXiv:1602.03889. Bibcode:2016JHEP...08..100F. doi:10.1007/JHEP08(2016)100. S2CID 119102534.
- ^ Fowlie, Andrew (10 July 2014). "CMSSM, naturalness and the ?fine-tuning price? of the Very Large Hadron Collider". Physical Review D. 90 (1): 015010. arXiv:1403.3407. Bibcode:2014PhRvD..90a5010F. doi:10.1103/PhysRevD.90.015010. S2CID 118362634.
- ^ Fowlie, Andrew (15 October 2014). "Is the CNMSSM more credible than the CMSSM?". The European Physical Journal C. 74 (10): 3105. arXiv:1407.7534. Bibcode:2014EPJC...74.3105F. doi:10.1140/epjc/s10052-014-3105-y. S2CID 119304794.
- ^ Cabrera, Maria Eugenia; Casas, Alberto; Austri, Roberto Ruiz de (2009). "Bayesian approach and naturalness in MSSM analyses for the LHC". Journal of High Energy Physics. 2009 (3): 075. arXiv:0812.0536. Bibcode:2009JHEP...03..075C. doi:10.1088/1126-6708/2009/03/075. S2CID 18276270.
- ^ Fichet, Sylvain (18 December 2012). "Quantified naturalness from Bayesian statistics". Physical Review D. 86 (12): 125029. arXiv:1204.4940. Bibcode:2012PhRvD..86l5029F. doi:10.1103/PhysRevD.86.125029. S2CID 119282331.
External links
edit
Quotations related to Fine-tuning (physics) at Wikiquote
