Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

A large light-mass component of cosmic rays at 1017–1017.5 electronvolts from radio observations

A Corrigendum to this article was published on 20 July 2016

This article has been updated

Abstract

Cosmic rays are the highest-energy particles found in nature. Measurements of the mass composition of cosmic rays with energies of 1017–1018 electronvolts are essential to understanding whether they have galactic or extragalactic sources. It has also been proposed that the astrophysical neutrino signal1 comes from accelerators capable of producing cosmic rays of these energies2. Cosmic rays initiate air showers—cascades of secondary particles in the atmosphere—and their masses can be inferred from measurements of the atmospheric depth of the shower maximum3 (Xmax; the depth of the air shower when it contains the most particles) or of the composition of shower particles reaching the ground4. Current measurements5 have either high uncertainty, or a low duty cycle and a high energy threshold. Radio detection of cosmic rays6,7,8 is a rapidly developing technique9 for determining Xmax (refs 10, 11) with a duty cycle of, in principle, nearly 100 per cent. The radiation is generated by the separation of relativistic electrons and positrons in the geomagnetic field and a negative charge excess in the shower front6,12. Here we report radio measurements of Xmax with a mean uncertainty of 16 grams per square centimetre for air showers initiated by cosmic rays with energies of 1017–1017.5 electronvolts. This high resolution in Xmax enables us to determine the mass spectrum of the cosmic rays: we find a mixed composition, with a light-mass fraction (protons and helium nuclei) of about 80 per cent. Unless, contrary to current expectations, the extragalactic component of cosmic rays contributes substantially to the total flux below 1017.5 electronvolts, our measurements indicate the existence of an additional galactic component, to account for the light composition that we measured in the 1017–1017.5 electronvolt range.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Energy resolution.
Figure 2: Measurements of 〈Xmax〉.
Figure 3: Composition model fits.
Figure 4: p-value distribution for the four-component model.

Similar content being viewed by others

Change history

References

  1. IceCube Collaboration. Evidence for high-energy extraterrestrial neutrinos at the IceCube detector. Science 342, 1242856 (2013)

  2. Murase, K., Ahlers, M. & Lacki, B. Testing the hadronuclear origin of PeV neutrinos observed with IceCube. Phys. Rev. D 88, 121301 (2013)

    Article  ADS  Google Scholar 

  3. Aab, A. et al. Depth of maximum of air-shower profiles at the Pierre Auger Observatory. II. Composition implications. Phys. Rev. D 90, 122006 (2014)

    Article  ADS  Google Scholar 

  4. Apel, W. et al. Ankle-like feature in the energy spectrum of light elements of cosmic rays observed with KASCADE-Grande. Phys. Rev. D 87, 081101 (2013)

    Article  ADS  Google Scholar 

  5. Kampert, K.-H. & Unger, M. Measurements of the cosmic ray composition with air shower experiments. Astropart. Phys. 35, 660–678 (2012)

    Article  ADS  Google Scholar 

  6. Allan, H. R. in Progress in Elementary Particle and Cosmic Ray Physics Vol. 10 (eds Wilson, J. G. & Wouthuysen, S. A. ) 171–302 (North-Holland Pub. Co., 1971)

  7. Falcke, H. & Gorham, P. W. Detecting radio emission from cosmic ray air showers and neutrinos with a digital radio telescope. Astropart. Phys. 19, 477–494 (2003)

    Article  ADS  Google Scholar 

  8. Falcke, H. et al. Detection and imaging of atmospheric radio flashes from cosmic ray air showers. Nature 435, 313–316 (2005)

    Article  CAS  ADS  Google Scholar 

  9. Huege, T. The renaissance of radio detection of cosmic rays. Braz. J. Phys. 44, 520–529 (2014)

    Article  ADS  Google Scholar 

  10. Apel, W. et al. Reconstruction of the energy and depth of maximum of cosmic-ray air showers from LOPES radio measurements. Phys. Rev. D 90, 062001 (2014)

    Article  ADS  Google Scholar 

  11. Belov, K. et al. Towards determining the energy of the UHECRs observed by the ANITA detector. AIP Conf. Proc. 1535, 209–213 (2013)

    Article  CAS  ADS  Google Scholar 

  12. Werner, K. & Scholten, O. Macroscopic treatment of radio emission from cosmic ray air showers based on shower simulations. Astropart. Phys. 29, 393–411 (2008)

    Article  ADS  Google Scholar 

  13. van Haarlem, M. et al. LOFAR: the LOw-Frequency ARray. Astron. Astrophys. 556, A2 (2013)

    Article  Google Scholar 

  14. Schellart, P. et al. Detecting cosmic rays with the LOFAR radio telescope. Astron. Astrophys. 560, A98 (2013)

    Article  Google Scholar 

  15. Schellart, P. et al. Probing atmospheric electric fields in thunderstorms through radio emission from cosmic-ray-induced air showers. Phys. Rev. Lett. 114, 165001 (2015)

    Article  CAS  ADS  Google Scholar 

  16. Huege, T., Ludwig, M. & James, C. Simulating radio emission from air showers with CoREAS. AIP Conf. Proc. 1535, 128–132 (2013)

    Article  CAS  ADS  Google Scholar 

  17. Heck, D., Knapp, J., Capdevielle, J. N., Schatz, G. & Thouw, T. CORSIKA: a Monte Carlo code to simulate extensive air showers. Report No. FZKA 6019 (Forschungszentrum Karlsruhe, 1998)

  18. Buitink, S. et al. Method for high precision reconstruction of air shower X max using two-dimensional radio intensity profiles. Phys. Rev. D 90, 082003 (2014)

    Article  ADS  Google Scholar 

  19. Ostapchenko, S. QGSJET-II: results for extensive air showers. Nucl. Phys. B 151, 147–150 (2006)

    Article  CAS  Google Scholar 

  20. Pierog, T. & Werner, K. EPOS model and ultra high energy cosmic rays. Nucl. Phys. B 196, 102–105 (2009)

    Article  CAS  Google Scholar 

  21. Aab, A. et al. Muons in air showers at the Pierre Auger Observatory: mean number in highly inclined events. Phys. Rev. D 91, 032003 (2015)

    Article  ADS  Google Scholar 

  22. Aloisio, R. et al. A dip in the UHECR spectrum and the transition from galactic to extragalactic cosmic rays. Astropart. Phys. 27, 76–91 (2007)

    Article  ADS  Google Scholar 

  23. Stanev, T., Biermann, P. & Gaisser, T. Cosmic rays. IV. The spectrum and chemical composition above 10 GeV. Astron. Astrophys. 274, 902–915 (1993)

    CAS  ADS  Google Scholar 

  24. Calvez, A., Kusenko, S. & Nagataki, S. Role of galactic sources and magnetic fields in forming the observed energy-dependent composition of ultrahigh-energy cosmic rays. Phys. Rev. Lett. 105, 091101 (2010)

    Article  ADS  Google Scholar 

  25. Jokipii, J. R. & Morfill, G. Ultra-high-energy cosmic rays in a galactic wind and its termination shock. Astrophys. J. 312, 170–177 (1987)

    Article  ADS  Google Scholar 

  26. Letessier-Selvon, A. et al. Highlights from the Pierre Auger Observatory. Braz. J. Phys. 44, 560–570 (2014)

    Article  ADS  Google Scholar 

  27. Abu-Zayyad, T. et al. Measurement of the cosmic-ray energy spectrum and composition from 1017 to 1018.3 eV using a hybrid technique. Astrophys. J. 557, 686–699 (2001)

    Article  ADS  Google Scholar 

  28. Knurenko, S. & Sabourov, A. The depth of maximum shower development and its fluctuations: cosmic ray mass composition at E 0 ≥ 1017 eV. Astrophys. Space Sci. Trans. 7, 251–255 (2011)

    Article  CAS  ADS  Google Scholar 

  29. Berezhnev, S. F. et al. Tunka-133: primary cosmic ray mass composition in the energy range 6 · 1015−1018 eV. Proc. 32nd Int. Cosmic Ray Conf. 1, 209–212 (2011)

    Google Scholar 

  30. Buitink, S. et al. Amplified radio emission from cosmic ray air showers in thunderstorms. Astron. Astrophys. 467, 385–394 (2007)

    Article  ADS  Google Scholar 

  31. Schellart, P. et al. Polarized radio emission from extensive air showers measured with LOFAR. J. Cosmol. Astropart. Phys. 10, 014 (2014)

    Article  ADS  Google Scholar 

  32. The Pierre Auger Collaboration. Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS). Astropart. Phys. 35, 591–607 (2012)

  33. Alvarez-Muñiz, J. et al. Monte Carlo simulations of radio pulses in atmospheric showers using ZHAireS. Astropart. Phys. 35, 325–341 (2012)

    Article  ADS  Google Scholar 

  34. Huege, T. et al. The convergence of EAS radio emission models and a detailed comparison of REAS3 and MGMR simulations. Nucl. Instrum. Methods Phys. Res. A 662 (Suppl.) S179–S186 (2012)

    Article  CAS  Google Scholar 

  35. James, C., Falcke, H., Huege, T. & Ludwig, M. General description of electromagnetic radiation processes based on instantaneous charge acceleration in “endpoints”. Phys. Rev. E 84, 056602 (2011)

    Article  ADS  Google Scholar 

  36. Zas, E., Halzen, F. & Stanev, T. Electromagnetic pulses from high-energy showers: implications for neutrino detection. Phys. Rev. D 45, 362–376 (1992)

    Article  CAS  ADS  Google Scholar 

  37. Belov, K. et al. Accelerator measurements of magnetically induced radio emission from particle cascades with applications to cosmic-ray air showers. Phys. Rev. Lett. (in the press). Preprint at http://arXiv.org/abs/1507.07296 (2015)

  38. Thoudam, S. et al. LORA: a scintillator array for LOFAR to measure extensive air showers. Nucl. Instrum. Methods Phys. Res. A 767, 339–346 (2014)

    Article  CAS  ADS  Google Scholar 

  39. Thoudam, S. et al. Measurement of the cosmic-ray energy spectrum above 1016 eV with the LOFAR Radboud Air Shower Array. Astropart. Phys. 73, 34–43 (2016)

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We acknowledge financial support from the Netherlands Organization for Scientific Research (NWO), VENI grant 639-041-130, the Netherlands Research School for Astronomy (NOVA), the Samenwerkingsverband Noord-Nederland (SNN) and the Foundation for Fundamental Research on Matter (FOM). We acknowledge funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC (grant agreement no. 227610) and under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 640130). LOFAR, the Low Frequency Array designed and constructed by ASTRON, has facilities in several countries that are owned by various parties (each with their own funding sources) and that are collectively operated by the International LOFAR Telescope (ILT) foundation under a joint scientific policy.

Author information

Authors and Affiliations

Authors

Contributions

All authors are part of the LOFAR collaboration and have contributed to the design, construction, calibration and maintenance of LOFAR and/or LORA. The first thirteen authors constitute the Cosmic Ray Key Science Project and have contributed to the acquisition, calibration and analysis of cosmic-ray radio data and LORA data. The manuscript was written by S.B. and subjected to an internal collaboration-wide review process. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to S. Buitink.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Fitted lateral distributions.

Lateral distribution of radio-pulse power for all 118 measured showers (red circles) and the corresponding best-fitting CoREAS simulation (blue squares). The distance to the shower axis is the distance between the antenna and the axis of the air shower. Therefore, a value of 0 corresponds to an antenna that is located at the position where the shower axis reaches the ground. The ID numbers are unique values that are used to label the detected air showers. a.u., arbitrary units.

Extended Data Figure 2 Fitted lateral distributions.

Continuation of Extended Data Fig. 1.

Extended Data Figure 3 Fitted lateral distributions.

Continuation of Extended Data Fig. 2.

Extended Data Figure 4 Fitted lateral distributions.

Continuation of Extended Data Fig. 3.

Extended Data Figure 5 Fitted lateral distributions.

Continuation of Extended Data Fig. 4.

Extended Data Figure 6 Distribution of uncertainty on Xmax.

The distribution of the uncertainty on Xmax for all showers used in this analysis. The mean value is 16 g cm−2.

Extended Data Figure 7 Energy reconstruction.

Distributions of the ratio between true (Etrue) and reconstructed (Ereco) energy for proton (blue solid line) and iron (red dashed line) showers. The two types of showers have a systematic offset of the order of 1%.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Buitink, S., Corstanje, A., Falcke, H. et al. A large light-mass component of cosmic rays at 1017–1017.5 electronvolts from radio observations. Nature 531, 70–73 (2016). https://doi.org/10.1038/nature16976

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature16976

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing