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      The Causal Closure of Physics in Real World Contexts

      research-article
      Foundations of Physics
      Springer US

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          Abstract

          The causal closure of physics is usually discussed in a context free way. Here I discuss it in the context of engineering systems and biology, where strong emergence takes place due to a combination of upwards emergence and downwards causation (Ellis, Emergence in Solid State Physics and Biology, 2020, arXiv:2004.13591). Firstly, I show that causal closure is strictly limited in terms of spatial interactions because these are cases that are of necessity strongly interacting with the environment. Effective Spatial Closure holds ceteris parabus, and can be violated by Black Swan Events. Secondly, I show that causal closure in the hierarchy of emergence is a strictly interlevel affair, and in the cases of engineering and biology encompasses all levels from the social level to the particle physics level. However Effective Causal Closure can usefully be defined for a restricted set of levels, and one can experimentally determine Effective Theories that hold at each level. This does not however imply those effective theories are causally complete by themselves. In particular, the particle physics level is not causally complete by itself in the contexts of solid state physics (because of interlevel wave–particle duality), digital computers (where algorithms determine outcomes), or biology (because of time dependent constraints). Furthermore Inextricably Intertwined Levels occur in all these contexts.

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          • Record: found
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          The molecular biology of memory storage: a dialogue between genes and synapses.

          E R Kandel (2001)
          One of the most remarkable aspects of an animal's behavior is the ability to modify that behavior by learning, an ability that reaches its highest form in human beings. For me, learning and memory have proven to be endlessly fascinating mental processes because they address one of the fundamental features of human activity: our ability to acquire new ideas from experience and to retain these ideas over time in memory. Moreover, unlike other mental processes such as thought, language, and consciousness, learning seemed from the outset to be readily accessible to cellular and molecular analysis. I, therefore, have been curious to know: What changes in the brain when we learn? And, once something is learned, how is that information retained in the brain? I have tried to address these questions through a reductionist approach that would allow me to investigate elementary forms of learning and memory at a cellular molecular level-as specific molecular activities within identified nerve cells.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Artificial neural networks: a tutorial

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The fundamental constants and their variation: observational and theoretical status

                Bookmark

                Author and article information

                Contributors
                george.ellis@uct.ac.za
                Journal
                Found Phys
                Found Phys
                Foundations of Physics
                Springer US (New York )
                0015-9018
                1572-9516
                18 August 2020
                : 1-41
                Affiliations
                GRID grid.7836.a, ISNI 0000 0004 1937 1151, Mathematics Department, , University of Cape Town, ; Cape Town, South Africa
                Author information
                http://orcid.org/0000-0001-8484-0629
                Article
                366
                10.1007/s10701-020-00366-0
                7431902
                74012bf4-ec9d-425b-a8b5-b6559c7520e4
                © Springer Science+Business Media, LLC, part of Springer Nature 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 9 June 2020
                : 22 July 2020
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