A Network Account of Models in High Energy Physics Experiments.
I propose an account of the model-based structure of the present-day high energy physics experiments in which the relations among the theoretical, experimental and simulation models constitute a non-linear structure that is akin to a network of models (NoM). I argue that while the proposed NoM subsu...
| Published in: | Philosophy of Science Vol. 90; no. 4; pp. 777 - 797 |
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| Format: | Article |
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Cambridge University Press
Oct2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=173151305&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 173151305 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00318248 PSC jtl: Philosophy of Science issn: 00318248 maglogo: N pubinfo: dt: Oct2023 vid: 90 iid: 4 pid: 15979 pub: Cambridge University Press artinfo: ui: 173151305 10.1017/psa.2023.73 ppf: 777 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 894KB tig: atl: A Network Account of Models in High Energy Physics Experiments. aug: au: Karaca, Koray affil: University of Twente, Enschede, Netherlands su: Physics experiments Collisions (Nuclear physics) Acquisition of data Stochastic learning models sug: subj: Physics experiments Collisions (Nuclear physics) Acquisition of data Stochastic learning models ab: I propose an account of the model-based structure of the present-day high energy physics experiments in which the relations among the theoretical, experimental and simulation models constitute a non-linear structure that is akin to a network of models (NoM). I argue that while the proposed NoM subsumes Suppes' hierarchy of models (HoM) as the model-based characterization of the inference leading from the data to the validity or invalidity of the hypothesis tested in an experiment, it involves a model-based characterization of the inference leading from the collision of particles to the acquisition of data, which is missing in Suppes' HoM. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Philosophy of Science is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Philosophy of Science holder: Cambridge University Press dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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