Earman, John (2023) Evaluating the Symmetry to Reality Inference: Not All Symmetry Signals Redundancy. [Preprint]
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Abstract
The symmetry to reality inference (StRI) is concerned with how fundamental theories in physics describe/represent genuine features of the world. StRI asserts that symmetry related models of a theory describe/represent/correspond to the same physical reality. Accepting StRI implies that theories in mathematical physics routinely involve redundancy in their descriptive apparatuses since it is a commonplace that the symmetries of field equations/equations of motion are not shared by typical solutions. There is a good motivation for StRI in cases that physicists would classify of gauge symmetries; namely, if the gauge variables had worldly counterparts then determinism in guise of a good Cauchy problem for the field equations/equations of motion would fail. It is argued that outside of such cases StRI leads to a distorted picture of how theories of mathematical physics represent the physical world. However, the way I propose to draw the line between gauge and non-gauge symmetries can be blurred by clever reformulations of theories. In particular, in some instances it appears to be all too easy to make diffeomorphism invariance look like a gauge symmetry. It seems more productive to discuss such issues than to tilt with the special pleading for StRI.
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Item Type: | Preprint | ||||||
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Keywords: | symmetries and invariants, determinism/indeterminism | ||||||
Subjects: | Specific Sciences > Physics > Classical Physics General Issues > Determinism/Indeterminism Specific Sciences > Physics > Relativity Theory Specific Sciences > Physics > Symmetries/Invariances |
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Depositing User: | John Earman | ||||||
Date Deposited: | 14 Jun 2023 17:08 | ||||||
Last Modified: | 14 Jun 2023 17:08 | ||||||
Item ID: | 22211 | ||||||
Subjects: | Specific Sciences > Physics > Classical Physics General Issues > Determinism/Indeterminism Specific Sciences > Physics > Relativity Theory Specific Sciences > Physics > Symmetries/Invariances |
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Date: | 13 June 2023 | ||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/22211 |
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