4.4 Article

Junction conditions in Palatinif(R) gravity

Journal

CLASSICAL AND QUANTUM GRAVITY
Volume 37, Issue 21, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1361-6382/abb924

Keywords

f(R) gravity; junction conditions; Palatini approach; stellar structure

Funding

  1. Ramon y Cajal contract (Spain) [RYC-2013-13019]
  2. Atraccion de Talento Investigador programme of the Comunidad de Madrid (Spain) [2018-T1/TIC-10431]
  3. Ministerio de Ciencia, Innovacion y Universidades (Spain) [PID2019-108485GB-I00/AEI/10.13039/501100011033]
  4. FundacAo para a Ciencia e a Tecnologia (FCT, Portugal) [PTDC/FIS-OUT/29048/2017, PTDC/FIS-PAR/31938/2017]
  5. Spanish project (MINECO/FEDER, EU) [FIS2017-84440-C2-1-P]
  6. project H2020-MSCA-RISE-2017 [FunFiCO-777740]
  7. Generalitat Valenciana [SEJI/2017/042]
  8. Consolider Program [CPANPHY-1205388]
  9. Severo Ochoa grant (Spain) [SEV-2014-0398]
  10. FAPESQ-PB/CNPQ, Brazil [0015/2019]
  11. COST (European Cooperation in Science and Technology) [CA15117, CA18108]
  12. Fundação para a Ciência e a Tecnologia [PTDC/FIS-PAR/31938/2017] Funding Source: FCT

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We work out the junction conditions forf(R) gravity formulated in metric-affine (Palatini) spaces using a tensor distributional approach. These conditions are needed for building consistent models of gravitating bodies with an interior and exterior regions matched at some hypersurface. Some of these conditions depart from the standard Darmois-Israel ones of general relativity and from their metricf(R) counterparts. In particular, we find that the trace of the stress-energy momentum tensor in the bulk must be continuous across the matching hypersurface, though its normal derivative need not to. We illustrate the relevance of these conditions by considering the properties of stellar surfaces in polytropic models, showing that the range of equations of state with potentially pathological effects is shifted beyond the domain of physical interest. This confirms, in particular, that neutron stars and white dwarfs can be safely modelled within the Palatinif(R) framework.

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