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New stringent LIV limits from astrophysical gamma-ray sources

*Corresponding author for this work
  • Universidade de São Paulo
    ,
  • Instituto de Física de São Carlos
Research Output:
Contribution to conference
Paper
Peer-review

Open access

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Author count
3
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Paper percentile
25

Abstract

Lorentz invariance violation (LIV) introduced as a generic modification to particle dispersion relation can change the photon energy threshold of pair-production, which modifies the extragalactic background light (EBL) absorption of gamma rays from astrophysical sources. In this note, we report an innovative data analysis that allows us to extract unprecedented information from the most updated data set composed of 111 energy spectra of 38 different sources measured by current gamma-ray observatories. The outcome technique and results maximize the chances to find or discriminate LIV signals in any future search and reduce the biases in current analyses. Therefore, we report stringent limits for the LIV energy scale at first and second leading order in high energy gamma-rays. These limits are better than the ones current available in the literature for subluminal searches of LIV, irrespectively of many tested uncertainties, such as, poor knowledge of the EBL, large uncertainties in the intrinsic energy spectra functional form, energy resolution, selection of spectra and the energy bins selection used in the calculation of the intrinsic energy spectra.

Publication Information

Output type

Research Output:
Contribution to conference
Paper
Peer-review

Original language

English

Publication milestones

  • Published - 2019

Publication status

Published - 2019

Publication IDs

  • Scopus: 85086248143

Related Event

Title

36th International Cosmic Ray Conference, ICRC 2019

Event type

Conference

Date

24/07/2019 - 01/08/2019

Location

MadisonUnited States

Funding Details

We acknowledge the support from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) through grants 2015/15897-1, 2016/24943-0, 2017/03680-3 and 2019/01653-4. We also acknowledge the National Laboratory for Scientific Computing (LNCC/MCTI, Brazil) for providing HPC resources of the SDumont supercomputer, which have contributed to the research results reported within this paper (sdumont.lncc.br).