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Shape Dynamics

  • Tim A. KoslowskiEmail author
Conference paper
Part of the Springer Proceedings in Physics book series (SPPHY, volume 157)

Abstract

Barbour’s formulation of Mach’s principle requires a theory of gravity to implement local relativity of clocks, local relativity of rods and spatial covariance. It turns out that relativity of clocks and rods are mutually exclusive. General Relativity implements local relativity of clocks and spatial covariance, but not local relativity of rods. It is the purpose of this contribution to show how Shape Dynamics, a theory that is locally equivalent to General Relativity, implements local relativity of rods and spatial covariance and how a BRST formulation, which I call Doubly General Relativity, implements all of Barbour’s principles.

Keywords

Gauge Theory Class Constraint Ghost Number Hamilton Constraint Constant Mean Curvature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Research at the Perimeter Institute is supported in part by the Government of Canada through NSERC and by the Province of Ontario through MEDT.

References

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    Barbour, J.: Shape dynamics: an introduction. In: Finster, F., Müller, O., Nardmann, M., Tolksdorf, J., Zeidler, E. (eds.) Quantum Field Theory and Gravity: Conceptual and Mathematical Advances in the Search for a Unified Framework, pp. 257–298. Basel, Birkhäuser (2012)CrossRefGoogle Scholar
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    Gomes, H., Koslowski, T.: The link between general relativity and shape dynamics. Class. Quantum Grav. 29, 075009 (2012). doi: 10.1088/0264-9381/29/7/075009 ADSCrossRefMathSciNetGoogle Scholar
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    Gomes, H., Koslowski, T.: Symmetry Doubling: Doubly General Relativity. ArXiv e-prints arXiv:1206.4823 [gr-qc] (2012)

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Perimeter Institute for Theoretical PhysicsWaterlooCanada
  2. 2.Department of Mathematics and StatisticsUniversity of New BrunswickFrederictonCanada

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