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Validating the Universe in a Box

descriptionPublicationkeyboard_double_arrow_right Article 01 Dec 2020 Canada Publisher:Cambridge University Press (CUP)Journal:Philosophy of Science, volume 87, pages 1,221-1,233 (issn: 0031-8248, eissn: 1539-767X,

Authors: Smeenk, Chris; Gallagher, Sarah C.;

doi: 10.1086/710627 , 10.48550/arxiv.2001.09101

Validating the Universe in a Box

- Summary
- Subjects
- References
  (19)
- Metrics

Abstract

Computer simulations of the formation and evolution of large scale structure in the universe are integral to the enterprise of modern cosmology. Establishing the reliability of these simulations has been extremely challenging, primarily because of epistemic opacity. In this setting, robustness analysis defined by requiring converging outputs from a diverse ensemble of simulations is insufficient to determine simulation validity. Instead, we propose an alternative path of structured code validation that applies eliminative reasoning to isolate and reduce possible sources of error, a potential path that is already being explored by some cosmologists.

Comment: 13 pages. Accepted for publication in Philosophy of Science for the PSA2018 symposium proceedings issue

Country

Canada

Related Organizations

Subjects by Vocabulary

Microsoft Academic Graph classification: Computer science Structure (category theory) Cosmology Reliability engineering Reliability (statistics)

Keywords

History, Cosmology and Nongalactic Astrophysics (astro-ph.CO), FOS: Physical sciences, Astrophysics - Astrophysics of Galaxies, Philosophy, History and Philosophy of Science, Astrophysics of Galaxies (astro-ph.GA), Astrophysics - Cosmology and Nongalactic Astrophysics

19 references, page 1 of 2

Amendola, L. et al. (2018). Cosmology and fundamental physics with the Euclid satellite. Living Reviews in Relativity 21, 2.

Bullock, J. S. and M. Boylan-Kolchin (2017, August). Small-Scale Challenges to the ΛCDM Paradigm. Annual Reviews of Astronomy and Astrophysics 55, 343-387.

Franklin, A. (1989). The neglect of experiment. Cambridge: Cambridge University Press.

Frisch, M. (2015). Predictivism and old evidence: a critical look at climate model tuning. European Journal for the Philosophy of Science 5, 171-190.

Gueguen, M. (2019). On the robustness of cosmological simulations. Manuscript, under review.

Guo, Q., et al. (2011). From dwarf spheroidals to cD galaxies: simulating the galaxy population in a ΛCDM cosmology. Monthly Notices of the Royal Astronomical Society 413, 101-131.

Humphreys, P. (2009). The philosophical novelty of computer simulation methods. Synthese 169(3), 615-626.

Lenhard, J. (2019). Calculated Surprises: A Philosophy of Computer Simulation. Oxford: Oxford University Press.

Lenhard, J. and E. Winsberg (2010). Holism, entrenchment, and the future of climate model pluralism. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41(3), 253-262. [OpenAIRE]

Massimi, M. (2018). Three problems about multi-scale modelling in cosmology. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 64, 26 - 38.

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Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	3
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	3
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average