Skip to main content

Thank you for visiting 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.

Fast magnetic field amplification in distant galaxy clusters


In the present-day Universe, magnetic fields pervade galaxy clusters1 and have strengths of a few microgauss, as measured from Faraday rotation2. Evidence for cluster magnetic fields is also provided by the observation of megaparsec-scale radio emission, namely radio halos and relics3. These are commonly found in merging systems4 and are characterized by a steep radio spectrum Sν (α < −1, where Sν να and is ν the observing frequency). It is widely believed that magneto-hydrodynamical turbulence and shock waves (re-)accelerate cosmic rays5 and produce radio halos and relics. The origin and amplification of magnetic fields in clusters is not well understood. It has been proposed that turbulence drives a small-scale dynamo6,7,8,9,10,11 that amplifies seed magnetic fields (which are primordial and/or injected by galactic outflows, such as active galactic nuclei, starbursts or winds12). At high redshift, radio halos are expected to be faint, owing to losses from inverse Compton scattering and the dimming effect with distance. Moreover, Faraday rotation measurements are difficult to obtain. If detected, distant radio halos provide an alternative tool to investigate magnetic field amplification. Here, we report Low Frequency Radio Array observations that reveal diffuse radio emission in massive clusters when the Universe was only half of its present age, with a sample occurrence fraction of about 50%. The high radio luminosities indicate that these clusters have similar magnetic field strengths to those in nearby clusters, and suggest that magnetic field amplification is fast during the first phases of cluster formation.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Examples of observed radio emission in our high-z galaxy cluster sample.
Fig. 2: X-ray images of a subsample of galaxy clusters from Fig. 1.
Fig. 3: Cluster magnetic field estimation and theoretical magnetic field evolution.

Data availability

The radio observations are available in the LOFAR Long Term Archive (LTA; and in the VLA archive (, project code 15A_270). The X-ray observations are available in the XMM-Newton and Chandra data archives ( and The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

The codes that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.


  1. 1.

    Carilli, C. L. & Taylor, G. B. Cluster magnetic fields. Annu. Rev. Astron. Astrophys. 40, 319–348 (2002).

    ADS  Google Scholar 

  2. 2.

    Bonafede, A. et al. The coma cluster magnetic field from Faraday rotation measures. Astron. Astrophys. 513, A30 (2010).

    Google Scholar 

  3. 3.

    van Weeren, R. J. et al. Diffuse radio emission from galaxy clusters. Space Sci. Rev. 215, 16 (2019).

    ADS  Google Scholar 

  4. 4.

    Cassano, R. et al. On the connection between giant radio halos and cluster mergers. Astrophys. J. 721, 82–85 (2010).

    Google Scholar 

  5. 5.

    Brunetti, G. & Jones, T. W. Cosmic rays in galaxy clusters and their nonthermal emission. Int. J. Mod. Phys. D 23, 1430007 (2014).

    ADS  Google Scholar 

  6. 6.

    Dolag, K., Grasso, D., Springel, V. & Tkachev, I. Constrained simulations of the magnetic field in the local Universe and the propagation of ultrahigh energy cosmic rays. J. Cosmol. Astropart. Phys. 2005, 9 (2005).

    Google Scholar 

  7. 7.

    Subramanian, K., Shukurov, A. & Haugen, N. E. L. Evolving turbulence and magnetic fields in galaxy clusters. Mon. Not. R. Astron. Soc. 366, 1437–1454 (2006).

    ADS  Google Scholar 

  8. 8.

    Ryu, D., Kang, H., Cho, J. & Das, S. Turbulence and magnetic fields in the large-scale structure of the Universe. Science 320, 909–912 (2008).

    ADS  Google Scholar 

  9. 9.

    Miniati, F. & Beresnyak, A. Self-similar energetics in large clusters of galaxies. Nature 523, 59–62 (2015).

    ADS  Google Scholar 

  10. 10.

    Vazza, F., Brunetti, G., Brüggen, M. & Bonafede, A. Resolved magnetic dynamo action in the simulated intracluster medium. Mon. Not. R. Astron. Soc. 474, 1672–1687 (2018).

    ADS  Google Scholar 

  11. 11.

    Domínguez-Fernández, P., Vazza, F., Brüggen, M. & Brunetti, G. Dynamical evolution of magnetic fields in the intracluster medium. Mon. Not. R. Astron. Soc. 486, 623–638 (2019).

    ADS  Google Scholar 

  12. 12.

    Donnert, J., Vazza, F., Brüggen, M. & ZuHone, J. Magnetic field amplification in galaxy clusters and its simulation. Space Sci. Rev. 214, 122 (2018).

    ADS  Google Scholar 

  13. 13.

    van Haarlem, M. P. et al. LOFAR: The LOw-frequency ARray. Astron. Astrophys 556, A2 (2013).

    Google Scholar 

  14. 14.

    Shimwell, T. W. et al. The LOFAR two-metre Sky Survey. II. First data release. Astron. Astrophys. 622, A1 (2019).

    Google Scholar 

  15. 15.

    Planck Collaboration et al. Planck 2015 results. XXVII. The second Planck catalogue of Sunyaev–Zeldovich sources. Astron. Astrophys. 594, A27 (2016).

    Google Scholar 

  16. 16.

    Cassano, R. et al. Revisiting scaling relations for giant radio halos in galaxy clusters. Astrophys. J. 777, 141 (2013).

    ADS  Google Scholar 

  17. 17.

    Cassano, R. et al. LOFAR discovery of a radio halo in the high-redshift galaxy cluster PSZ2 G099.86+58.45. Astrophys. J. 881, 18 (2019).

    ADS  Google Scholar 

  18. 18.

    Brunetti, G. & Vazza, F. Second-order Fermi reacceleration mechanisms and large-scale synchrotron radio emission in intracluster bridges. Phys. Rev. Lett. 124, 051101 (2020).

    ADS  Google Scholar 

  19. 19.

    van Weeren, R. J. et al. The discovery of a radio halo in PLCK G147.3–16.6 at z = 0.65. Astrophys. J. 781, 32 (2014).

    Google Scholar 

  20. 20.

    Lindner, R. R. et al. The radio relics and halo of El Gordo, a massive z = 0.870 cluster merger. Astrophys. J. 786, 49 (2014).

    ADS  Google Scholar 

  21. 21.

    Cho, J. Origin of magnetic field in the intracluster medium: primordial or astrophysical? Astrophys. J. 797, 133 (2014).

    ADS  Google Scholar 

  22. 22.

    Beresnyak, A. & Miniati, F. Turbulent amplification and structure of the intracluster magnetic field. Astrophys. J. 817, 127 (2016).

    ADS  Google Scholar 

  23. 23.

    Hitomi Collaboration et al. Atmospheric gas dynamics in the Perseus cluster observed with Hitomi. Publ. Astron. Soc. Jpn 70, 9 (2018).

    ADS  Google Scholar 

  24. 24.

    Markevitch, M. & Vikhlinin, A. Shocks and cold fronts in galaxy clusters. Phys. Rep. 443, 1–53 (2007).

    ADS  Google Scholar 

  25. 25.

    Brunetti, G. & Lazarian., A. Compressible turbulence in galaxy clusters: physics and stochastic particle re-acceleration. Mon. Not. R. Astron. Soc. 378, 245–275 (2007).

    ADS  Google Scholar 

  26. 26.

    Schekochihin, A. A. & Cowley, S. C. Turbulence, magnetic fields, and plasma physics in clusters of galaxies. Phys. Plasmas 13, 056501 (2006).

    ADS  Google Scholar 

  27. 27.

    Zhuravleva, I. et al. Suppressed effective viscosity in the bulk intergalactic plasma. Nat. Astron. 3, 832–837 (2019).

    ADS  Google Scholar 

  28. 28.

    Xu, H., Li, H., Collins, D. C., Li, S. & Norman, M. L. Evolution and distribution of magnetic fields from active galactic nuclei in galaxy clusters. II. The effects of cluster size and dynamical state. Astrophys. J. 739, 77 (2011).

    ADS  Google Scholar 

  29. 29.

    Eckert, D., Molendi, S. & Paltani, S. The cool-core bias in X-ray galaxy cluster samples. I. Method and application to HIFLUGCS. Astron. Astrophys. 526, A79 (2011).

    ADS  Google Scholar 

  30. 30.

    Rossetti, M. et al. The cool-core state of Planck SZ-selected clusters versus X-ray-selected samples: evidence for cool-core bias. Mon. Not. R. Astron. Soc. 468, 1917–1930 (2017).

    ADS  Google Scholar 

  31. 31.

    Andrade-Santos, F. et al. The fraction of cool-core clusters in X-ray versus SZ samples using Chandra observations. Astrophys. J. 843, 76 (2017).

    ADS  Google Scholar 

  32. 32.

    Amodeo, S. et al. Spectroscopic confirmation and velocity dispersions for 20 Planck galaxy clusters at 0.16 < z < 0.78. Astrophys. J. 853, 36 (2018).

    ADS  Google Scholar 

  33. 33.

    Barrena, R. et al. Optical validation and characterization of Planck PSZ1 sources at the Canary Islands observatories. I. First year of ITP13 observations. Astron. Astrophys. 616, A42 (2018).

    Google Scholar 

  34. 34.

    Burenin, R. A. et al. Optical identifications of high-redshift galaxy clusters from the Planck Sunyaev–Zeldovich survey. Astron. Lett. 44, 297–308 (2018).

    ADS  Google Scholar 

  35. 35.

    Sereno, M. et al. Gravitational lensing detection of an extremely dense environment around a galaxy cluster. Nat. Astron. 2, 744–750 (2018).

    ADS  Google Scholar 

  36. 36.

    Streblyanska, A. et al. Characterization of a sub-sample of the Planck SZ source cluster catalogues using optical SDSS DR12 data. Astron. Astrophys. 617, A71 (2018).

    Google Scholar 

  37. 37.

    van der Burg, R. F. J. et al. Prospects for high-z cluster detections with Planck, based on a follow-up of 28 candidates using Megacam at CFHT. Astron. Astrophys. 587, A23 (2016).

    Google Scholar 

  38. 38.

    Zohren, H. et al. Optical follow-up study of 32 high-redshift galaxy cluster candidates from Planck with the William Herschel Telescope. Mon. Not. R. Astron. Soc. 488, 2523–2542 (2019).

    ADS  Google Scholar 

  39. 39.

    Chambers, K. C., et al. The Pan-STARRS1 Surveys. Preprint at (2016).

  40. 40.

    van Weeren, R. J. et al. LOFAR facet calibration. Astrophys. J. Suppl. 223, 2 (2016).

    ADS  Google Scholar 

  41. 41.

    Williams, W. L. et al. LOFAR 150-MHz observations of the Boötes field: catalogue and source counts. Mon. Not. R. Astron. Soc. 460, 2385–2412 (2016).

    ADS  Google Scholar 

  42. 42.

    de Gasperin, F. et al. Systematic effects in LOFAR data: a unified calibration strategy. Astron. Astrophys. 622, A5 (2019).

    Google Scholar 

  43. 43.

    Tasse, C. Nonlinear Kalman filters for calibration in radio interferometry. Astron. Astrophys. 566, A127 (2014).

    ADS  Google Scholar 

  44. 44.

    Smirnov, O. M. & Tasse, C. Radio interferometric gain calibration as a complex optimization problem. Mon. Not. R. Astron. Soc. 449, 2668–2684 (2015).

    ADS  Google Scholar 

  45. 45.

    Tasse, C. et al. Faceting for direction-dependent spectral deconvolution. Astron. Astrophys. 611, A87 (2018).

    Google Scholar 

  46. 46.

    Offringa, A. R. et al. WSCLEAN: an implementation of a fast, generic wide-field imager for radio astronomy. Mon. Not. R. Astron. Soc. 444, 606–619 (2014).

    ADS  Google Scholar 

  47. 47.

    Offringa, A. R. & Smirnov, O. An optimized algorithm for multiscale wide-band deconvolution of radio astronomical images. Mon. Not. R. Astron. Soc. 471, 301–316 (2017).

    ADS  Google Scholar 

  48. 48.

    de Gasperin, F. et al. Gentle reenergization of electrons in merging galaxy clusters. Sci. Adv. 3, 1701634 (2017).

    ADS  Google Scholar 

  49. 49.

    Mandal, S. et al. Revived fossil plasma sources in galaxy clusters. Astron. Astrophys. 634, A4 (2020).

    Google Scholar 

  50. 50.

    Giacintucci, S. et al. Occurrence of radio minihalos in a mass-limited sample of galaxy clusters. Astrophys. J. 841, 71 (2017).

    ADS  Google Scholar 

  51. 51.

    Cassano, R., Brunetti, G. & Setti, G. Constraining B in galaxy clusters from statistics of giant radio halos. Astron. Nachr. 327, 557 (2006).

    ADS  Google Scholar 

  52. 52.

    Vikhlinin, A. et al. Chandra temperature profiles for a sample of nearby relaxed galaxy clusters. Astrophys. J. 628, 655–672 (2005).

    ADS  Google Scholar 

  53. 53.

    Cassano, R. & Brunetti, G. Cluster mergers and non-thermal phenomena: a statistical magneto-turbulent model. Mon. Not. R. Astron. Soc. 357, 1313–1329 (2005).

    ADS  Google Scholar 

  54. 54.

    Sarazin, C. L. in Merging Processes in Galaxy Clusters (eds Feretti, L. et al.) Ch. 1 (Kluwer Academic Publishers, 2002).

  55. 55.

    Kitayama, T. & Suto, Y. Semianalytic predictions for statistical properties of X-ray clusters of galaxies in cold dark matter Universes. Astrophys. J. 469, 480 (1996).

    ADS  Google Scholar 

  56. 56.

    Neeser, M. J., Eales, S. A., Law-Green, J. D., Leahy, J. P. & Rawlings, S. The linear-size evolution of classical double radio sources. Astrophys. J. 451, 76 (1995).

    ADS  Google Scholar 

  57. 57.

    Blundell, K. M., Rawlings, S. & Willott, C. J. The nature and evolution of classical double radio sources from complete samples. Astron. J. 117, 677 (1999).

    ADS  Google Scholar 

  58. 58.

    Smolčić, V. et al. The VLA-COSMOS 3 GHz large project: cosmic evolution of radio AGN and implications for radio-mode feedback since z = 5. Astron. Astrophys. 602, A6 (2017).

    Google Scholar 

  59. 59.

    Brunetti, G. & Lazarian, A. Acceleration of primary and secondary particles in galaxy clusters by compressible MHD turbulence: from radio haloes to gamma-rays. Mon. Not. R. Astron. Soc. 410, 127–142 (2011).

    ADS  Google Scholar 

  60. 60.

    Pinzke, A., Oh, S. P. & Pfrommer, C. Turbulence and particle acceleration in giant radio haloes: the origin of seed electrons. Mon. Not. R. Astron. Soc. 465, 4800–4816 (2017).

    ADS  Google Scholar 

  61. 61.

    Brunetti, G., Zimmer, S. & Zandanel, F. Relativistic protons in the Coma galaxy cluster: first gamma-ray constraints ever on turbulent reacceleration. Mon. Not. R. Astron. Soc. 472, 1506–1525 (2017).

    ADS  Google Scholar 

  62. 62.

    Vazza, F., Gheller, C. & Brüggen, M. Simulations of cosmic rays in large-scale structures: numerical and physical effects. Mon. Not. R. Astron. Soc. 439, 2662–2667 (2014).

    ADS  Google Scholar 

  63. 63.

    Vazza, F., Brüggen, M., Gheller, C. & Brunetti, G. Modelling injection and feedback of cosmic rays in grid-based cosmological simulations: effects on cluster outskirts. Mon. Not. R. Astron. Soc. 421, 3375–3398 (2012).

    ADS  Google Scholar 

  64. 64.

    Beresnyak, A. Universal nonlinear small-scale dynamo. Phys. Rev. Lett. 108, 035002 (2012).

    ADS  MATH  Google Scholar 

  65. 65.

    Fakhouri, O., Ma, C.-P. & Boylan-Kolchÿin, M. The merger rates and mass assembly histories of dark matter haloes in the two Millennium simulations. Mon. Not. R. Astron. Soc. 406, 2267–2278 (2010).

    ADS  Google Scholar 

  66. 66.

    Giocoli, C., Tormen, G. & Sheth, R. K. Formation times, mass growth histories and concentrations of dark matter haloes. Mon. Not. R. Astron. Soc. 422, 185–198 (2012).

    ADS  Google Scholar 

  67. 67.

    Roh, S., Ryu, D., Kang, H., Ha, S. & Jang, H. Turbulence dynamo in the stratified medium of galaxy clusters. Astrophy. J. 883, 138 (2019).

    ADS  Google Scholar 

Download references


We thank C. Giocoli and his team for the discussion of the cosmological derivations in the manuscript. This manuscript is based on data obtained with the International LOFAR Telescope (ILT). LOFAR is the Low Frequency Radio Array designed and constructed by ASTRON. It has observing, data processing and data storage facilities in several countries, which are owned by various parties (each with their own funding sources), and which are collectively operated by the ILT foundation under a joint scientific policy. The ILT resources have benefited from the following recent major funding sources: CNRS-INSU, Observatoire de Paris and Université d’Orléans, France; BMBF, MIWF-NRW, MPG, Germany; Science Foundation Ireland (SFI), Department of Business, Enterprise and Innovation (DBEI), Ireland; NWO, the Netherlands; the Science and Technology Facilities Council (STFC), United Kingdom; Ministry of Science and Higher Education, Poland; the Istituto Nazionale di Astrofisica (INAF), Italy. This research made use of the Dutch national e-infrastructure with support of the SURF Cooperative (e-infra 180169) and the LOFAR e-infra group. The Jülich LOFAR Long Term Archive and the German LOFAR network are both coordinated and operated by the Jülich Supercomputing Centre (JSC), and computing resources on the supercomputer JUWELS at JSC were provided by the Gauss Centre for Supercomputing e.V. (grant CHTB00) through the John von Neumann Institute for Computing (NIC). This research made use of the University of Hertfordshire high-performance computing facility and the LOFAR-UK computing facility located at the University of Hertfordshire and supported by STFC (ST/P000096/1), and of the Italian LOFAR IT computing infrastructure supported and operated by INAF, and by the Physics Department of Turin University (under an agreement with Consorzio Interuniversitario per la Fisica Spaziale) at the C3S Supercomputing Centre, Italy. The National Radio Astronomy Observatory is a facility of the US National Science Foundation operated under cooperative agreement by Associated Universities, Inc. This work is based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. The scientific results reported in this manuscript are based in part on data obtained from the Chandra Data Archive. The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, the Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, NASA (grant no. NNX08AR22G) issued through the Planetary Science Division of the NASA Science Mission Directorate, the US National Science Foundation (grant no. AST-1238877), the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory and the Gordon and Betty Moore Foundation. G.D.G. and R.J.v.W. acknowledge support from the ERC starting grant ‘ClusterWeb’ (no. 804208). G.B., R.C., F.G. and M.R. acknowledge support from INAF through the mainstream project ‘Galaxy clusters science with LOFAR’. A. Botteon and R.J.v.W. acknowledge support from the VIDI research programme (no. 639.042.729), which is financed by the Netherlands Organisation for Scientific Research. H.J.A.R. acknowledges support from the ERC Advanced Investigator programme ‘NewClusters’ (no. 32127). A. Bonafede acknowledges support from the ERC starting grant ‘DRANOEL’ (no. 714245) and from the MIUR grant FARE ‘SMS’. P.D.-F. acknowledges financial support from the ERC Starting ‘MAGCOW’ (no. 714196).

Author information




G.D.G. coordinated the research, performed the radio imaging, reduced the VLA and Chandra data and wrote the manuscript. R.J.v.W., A. Botteon and F.d.G. performed the additional calibration on the LOFAR data and wrote the data reduction software. G.B. and R.C. performed the magnetic field evolution modelling. R.J.v.W., G.B. and R.C. helped with the writing of the manuscript. M.B. and M.H. helped with the interpretation of the radio and modelling results and provided extensive feedback on the manuscript. H.J.A.R. and T.W.S. led the LoTSS survey and coordinated the LOFAR data reduction. A.S. carried out the XMM-Newton data reduction. F.G. and M.R. helped with the interpretation of the X-ray data and sample selection. A. Bonafede helped design the experiment and prepare the observing proposal. V.C., D.D., P.D.-F., T.A.E. and S.M. helped with the interpretation of the radio and modelling results and gave feedback on the manuscript. All of the authors of this manuscript are members of the LOFAR Surveys Key Science Project.

Corresponding author

Correspondence to Gabriella Di Gennaro.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information thanks Kaustuv Basu, Surajit Paul and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Observed radio emission in our high-z galaxy cluster sample.

In colorscale we show the full-resolution LOFAR images. Low- resolution source-subtracted radio contours, displayed at the [-2,2,3,4,5,8,16]xσrms level, are shown only for clusters that host diffuse radio emission (with σrms the individual map noise; the negative contour levels are indicated with a short- dashed line style). The full- and low-resolution LOFAR beams are displayed in the bottom left corner (in pink and grey colors, respectively). In the header of each image, the galaxy cluster name, mass and redshift are reported. The dashed black circle in each map shows the R = 0.5RSZ,500 region, obtained from MSZ,500.

Source data

Extended Data Fig. 2 X-ray images of all the galaxy clusters in our.

In colorscale we show the Chandra/XMM-Newton images. LOFAR radio contours are drawn as Fig. 1, with the LOFAR.

Supplementary information

Supplementary Information

Supplementary Figs. 1–2, Discussion and Tables 1–4.

Source data

Source Data Fig. 1

R.m.s. map noise levels for each cluster (σrms). The same noise levels are used for Fig. 2.

Source Data Fig. 3

Data used in the plot; the file includes also the data to reproduce the black line in the plot.

Source Data Extended Data Fig. 1

R.m.s. map noise levels for each cluster of our sample (σrms). The same noise levels are used for Extended Data Fig. 2.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Di Gennaro, G., van Weeren, R.J., Brunetti, G. et al. Fast magnetic field amplification in distant galaxy clusters. Nat Astron 5, 268–275 (2021).

Download citation

Further reading


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