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.

  • Article
  • Published:

Black hole jets on the scale of the cosmic web

Abstract

When sustained for megayears (refs. 1,2), high-power jets from supermassive black holes (SMBHs) become the largest galaxy-made structures in the Universe3. By pumping electrons, atomic nuclei and magnetic fields into the intergalactic medium (IGM), these energetic flows affect the distribution of matter and magnetism in the cosmic web4,5,6 and could have a sweeping cosmological influence if they reached far at early epochs. For the past 50 years, the known size range of black hole jet pairs ended at 4.6–5.0 Mpc (refs. 7,8,9), or 20–30% of a cosmic void radius in the Local Universe10. An observational lack of longer jets, as well as theoretical results11, thus suggested a growth limit at about 5 Mpc (ref. 12). Here we report observations of a radio structure spanning about 7 Mpc, or roughly 66% of a coeval cosmic void radius, apparently generated by a black hole between \({4.4}_{-0.7}^{+0.2}\) and 6.3 Gyr after the Big Bang. The structure consists of a northern lobe, a northern jet, a core, a southern jet with an inner hotspot and a southern outer hotspot with a backflow. This system demonstrates that jets can avoid destruction by magnetohydrodynamical instabilities over cosmological distances, even at epochs when the Universe was 7 to \(1{5}_{-2}^{+6}\) times denser than it is today. How jets can retain such long-lived coherence is unknown at present.

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

Access options

Buy this article

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

Fig. 1: Deep radio images of a 7-Mpc-long, black-hole-driven outflow.
Fig. 2: Radio close-up of the centre of Porphyrion.
Fig. 3: Rest-frame ultraviolet–optical spectroscopy and radio–ultraviolet photometry of the host galaxy.
Fig. 4: Measurements overlaid on evolutionary tracks from dynamical modelling.

Similar content being viewed by others

Data availability

The LoTSS DR2 is publicly available68. The authors share this work’s proprietary LOFAR, uGMRT and Keck I telescope data, as well as the dynamical model runs and LoTSS–VLASS spectral indices, through Code Ocean.

Code availability

The dynamical model used to interpret the outflow is described by Hardcastle28 and available for download69. Analysis and plotting code specific to this work is available on Code Ocean70. There are no access restrictions.

References

  1. Hardcastle, M. J. et al. Radio-loud AGN in the first LoTSS data release. The lifetimes and environmental impact of jet-driven sources. Astron. Astrophys. 622, A12 (2019).

    Article  CAS  Google Scholar 

  2. Perucho, M., Martí, J.-M. & Quilis, V. Long-term FRII jet evolution: clues from three-dimensional simulations. Mon. Not. R. Astron. Soc. 482, 3718–3735 (2019).

    Article  ADS  CAS  Google Scholar 

  3. Dabhade, P., Saikia, D. J. & Mahato, M. Decoding the giant extragalactic radio sources. J. Astrophys. Astron. 44, 13 (2023).

    Article  ADS  Google Scholar 

  4. Ayromlou, M., Nelson, D. & Pillepich, A. Feedback reshapes the baryon distribution within haloes, in halo outskirts, and beyond: the closure radius from dwarfs to massive clusters. Mon. Not. R. Astron. Soc. 524, 5391–5410 (2023).

    Article  ADS  CAS  Google Scholar 

  5. Beck, A. M., Hanasz, M., Lesch, H., Remus, R. S. & Stasyszyn, F. A. On the magnetic fields in voids. Mon. Not. R. Astron. Soc. 429, L60–L64 (2013).

    Article  ADS  Google Scholar 

  6. Vazza, F. et al. Simulations of extragalactic magnetic fields and of their observables. Class. Quantum Gravity 34, 234001 (2017).

    Article  ADS  Google Scholar 

  7. Willis, A. G., Strom, R. G. & Wilson, A. S. 3C236, DA240; the largest radio sources known. Nature 250, 625–630 (1974).

    Article  ADS  Google Scholar 

  8. Machalski, J., Kozieł-Wierzbowska, D., Jamrozy, M. & Saikia, D. J. J1420–0545: the radio galaxy larger than 3C 236. Astrophys. J. 679, 149–155 (2008).

    Article  ADS  CAS  Google Scholar 

  9. Oei, M. S. S. L. et al. The discovery of a radio galaxy of at least 5 Mpc. Astron. Astrophys. 660, A2 (2022).

    Article  Google Scholar 

  10. Correa, C. M. et al. Redshift-space effects in voids and their impact on cosmological tests. Part I: the void size function. Mon. Not. R. Astron. Soc. 500, 911–925 (2021).

    Article  ADS  CAS  Google Scholar 

  11. Perucho, M. Dissipative processes and their role in the evolution of radio galaxies. Galaxies 7, 70 (2019).

    Article  ADS  Google Scholar 

  12. Andernach, H., Jiménez-Andrade, E. F. & Willis, A. G. Discovery of 178 giant radio galaxies in 1059 deg2 of the Rapid ASKAP Continuum Survey at 888 MHz. Galaxies 9, 99 (2021).

    Article  ADS  Google Scholar 

  13. Dabhade, P. et al. Giant radio galaxies in the LOFAR Two-metre Sky Survey. I. Radio and environmental properties. Astron. Astrophys. 635, A5 (2020).

    Article  Google Scholar 

  14. Oei, M. S. S. L. et al. Measuring the giant radio galaxy length distribution with the LoTSS. Astron. Astrophys. 672, A163 (2023).

    Article  Google Scholar 

  15. Mostert, R. I. J. et al. Constraining the giant radio galaxy population with machine learning and Bayesian inference. Preprint at https://arxiv.org/abs/2405.00232 (2024).

  16. Hardcastle, M. J. et al. The LOFAR Two-Metre Sky Survey. VI. Optical identifications for the second data release. Astron. Astrophys. 678, A151 (2023).

    Article  Google Scholar 

  17. Heckman, T. M. & Best, P. N. The coevolution of galaxies and supermassive black holes: insights from surveys of the contemporary universe. Annu. Rev. Astron. Astrophys. 52, 589–660 (2014).

    Article  ADS  Google Scholar 

  18. Hardcastle, M. Interpreting radiative efficiency in radio-loud AGNs. Na. Astron. 2, 273–274 (2018).

    Article  ADS  Google Scholar 

  19. Buttiglione, S. et al. An optical spectroscopic survey of the 3CR sample of radio galaxies with z < 0.3. II. Spectroscopic classes and accretion modes in radio-loud AGN. Astron. Astrophys. 509, A6 (2010).

    Article  Google Scholar 

  20. Williams, W. L. et al. LOFAR-Boötes: properties of high- and low-excitation radio galaxies at 0.5 < z < 2.0. Mon. Not. R. Astron. Soc. 475, 3429–3452 (2018).

    Article  ADS  CAS  Google Scholar 

  21. Oei, M. S. S. L. et al. Luminous giants populate the dense Cosmic Web. The radio luminosity–environmental density relation for radio galaxies in action. Astron. Astrophys. 686, A137 (2024).

    Article  Google Scholar 

  22. Wen, Z. L. & Han, J. L. A catalog of 1.58 million clusters of galaxies identified from the DESI Legacy Imaging Surveys. Astrophys. J. Suppl. Ser. 272, 39 (2024).

    Article  ADS  Google Scholar 

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

    Article  Google Scholar 

  24. Ineson, J. et al. Radio-loud active galactic nucleus: is there a link between luminosity and cluster environment? Astrophys. J. 770, 136 (2013).

    Article  ADS  Google Scholar 

  25. Ineson, J. et al. The link between accretion mode and environment in radio-loud active galaxies. Mon. Not. R. Astron. Soc. 453, 2682–2706 (2015).

    Article  ADS  Google Scholar 

  26. Forero-Romero, J. E., Hoffman, Y., Gottlöber, S., Klypin, A. & Yepes, G. A dynamical classification of the cosmic web. Mon. Not. R. Astron. Soc. 396, 1815–1824 (2009).

    Article  ADS  Google Scholar 

  27. van Weeren, R. J. et al. Radio observations of ZwCl 2341.1+0000: a double radio relic cluster. Astron. Astrophys. 506, 1083–1094 (2009).

    Article  ADS  Google Scholar 

  28. Hardcastle, M. J. A simulation-based analytic model of radio galaxies. Mon. Not. R. Astron. Soc. 475, 2768–2786 (2018).

    Article  ADS  Google Scholar 

  29. Planck Collaboration et al. Planck 2018 results. VI. Cosmological parameters. Astron. Astrophys. 641, A6 (2020).

    Article  Google Scholar 

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

    Article  Google Scholar 

  31. Shimwell, T. W. et al. The LOFAR Two-metre Sky Survey. V. Second data release. Astron. Astrophys. 659, A1 (2022).

    Article  Google Scholar 

  32. Shimwell, T. W. et al. The LOFAR Two-metre Sky Survey. I. Survey description and preliminary data release. Astron. Astrophys. 598, A104 (2017).

    Article  Google Scholar 

  33. Tasse, C. et al. DDFacet: facet-based radio imaging package. Astrophysics Source Code Library, record ascl:2305.008 (2023).

  34. van Weeren, R. J. et al. LOFAR observations of galaxy clusters in HETDEX. Extraction and self-calibration of individual LOFAR targets. Astron. Astrophys. 651, A115 (2021).

    Article  Google Scholar 

  35. 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).

    Article  ADS  Google Scholar 

  36. Morabito, L. K. et al. Sub-arcsecond imaging with the International LOFAR Telescope. I. Foundational calibration strategy and pipeline. Astron. Astrophys. 658, A1 (2022).

    Article  Google Scholar 

  37. Jackson, N. et al. LBCS: the LOFAR Long-Baseline Calibrator Survey. Astron. Astrophys. 595, A86 (2016).

    Article  Google Scholar 

  38. Jackson, N. et al. Sub-arcsecond imaging with the International LOFAR Telescope. II. Completion of the LOFAR Long-Baseline Calibrator Survey. Astron. Astrophys. 658, A2 (2022).

    Article  Google Scholar 

  39. Gupta, Y. et al. The upgraded GMRT: opening new windows on the radio Universe. Curr. Sci. 113, 707–714 (2017).

    Article  ADS  Google Scholar 

  40. Intema, H. T. SPAM: Source Peeling and Atmospheric Modeling. Astrophysics Source Code Library, record ascl:1408.006 (2014).

  41. Mohan, N. & Rafferty, D. PyBDSF: Python Blob Detection and Source Finder. Astrophysics Source Code Library, record ascl:1502.007 (2015).

  42. Blandford, R. D. & Znajek, R. L. Electromagnetic extraction of energy from Kerr black holes. Mon. Not. R. Astron. Soc. 179, 433–456 (1977).

    Article  ADS  Google Scholar 

  43. Alam, S. et al. The eleventh and twelfth data releases of the Sloan Digital Sky Survey: final data from SDSS-III. Astrophys. J. Suppl. Ser. 219, 12 (2015).

    Article  ADS  Google Scholar 

  44. Dey, A. et al. Overview of the DESI Legacy Imaging Surveys. Astron. J. 157, 168 (2019).

    Article  ADS  CAS  Google Scholar 

  45. Duncan, K. J. All-purpose, all-sky photometric redshifts for the Legacy Imaging Surveys Data Release 8. Mon. Not. R. Astron. Soc. 512, 3662–3683 (2022).

    Article  ADS  CAS  Google Scholar 

  46. Oke, J. B. et al. The Keck low-resolution imaging spectrometer. Publ. Astron. Soc. Pac. 107, 375 (1995).

    Article  ADS  Google Scholar 

  47. McCarthy, J. K. et al. in Proc. SPIE Conference on Optical Astronomical Instrumentation (ed. D’Odorico, S.) 81–92 (SPIE, 1998).

  48. Steidel, C. C. et al. A survey of star-forming galaxies in the 1.4 z 2.5 redshift desert: overview. Astrophys. J. 604, 534–550 (2004).

    Article  ADS  CAS  Google Scholar 

  49. Rockosi, C. et al. in Proc. Ground-based and Airborne Instrumentation for Astronomy III (eds McLean, I. S., Ramsay, S. K. & Takami, H.) 77350R (SPIE, 2010).

  50. Prochaska, J. et al. PypeIt: the Python spectroscopic data reduction pipeline. J. Open Source Softw. 5, 2308 (2020).

    Article  ADS  Google Scholar 

  51. Dawson, K. S. et al. The Baryon Oscillation Spectroscopic Survey of SDSS-III. Astron. J. 145, 10 (2013).

    Article  ADS  Google Scholar 

  52. Chambers, K. C. et al. The Pan-STARRS1 surveys. Preprint at https://arxiv.org/abs/1612.05560 (2019).

  53. Jarrett, T. H. et al. The Spitzer–WISE survey of the ecliptic poles. Astrophys. J. 735, 112 (2011).

    Article  ADS  Google Scholar 

  54. Calistro Rivera, G., Lusso, E., Hennawi, J. F. & Hogg, D. W. AGNfitter: a Bayesian MCMC approach to fitting spectral energy distributions of AGNs. Astrophys. J. 833, 98 (2016).

    Article  ADS  Google Scholar 

  55. Martínez-Ramírez, L. N. et al. AGNFITTER-RX: Modeling the radio-to-X-ray spectral energy distributions of AGNs. Astron. Astrophys. 688, A46 (2024).

  56. Pasini, T. et al. Radio galaxies in galaxy groups: kinematics, scaling relations, and AGN feedback. Mon. Not. R. Astron. Soc. 505, 2628–2637 (2021).

    Article  ADS  CAS  Google Scholar 

  57. Arnaud, M. et al. The universal galaxy cluster pressure profile from a representative sample of nearby systems (REXCESS) and the YSZ – M500 relation. Astron. Astrophys. 517, A92 (2010).

    Article  Google Scholar 

  58. Sun, M. et al. The pressure profiles of hot gas in local galaxy groups. Astrophys. J. Lett. 727, L49 (2011).

    Article  ADS  Google Scholar 

  59. Cooke, R. J. & Fumagalli, M. Measurement of the primordial helium abundance from the intergalactic medium. Nat. Astron. 2, 957–961 (2018).

    Article  ADS  Google Scholar 

  60. Lovisari, L., Reiprich, T. H. & Schellenberger, G. Scaling properties of a complete X-ray selected galaxy group sample. Astron. Astrophys. 573, A118 (2015).

    Article  ADS  Google Scholar 

  61. Ricciardelli, E., Quilis, V. & Planelles, S. The structure of cosmic voids in a ΛCDM Universe. Mon. Not. R. Astron. Soc. 434, 1192–1204 (2013).

    Article  ADS  Google Scholar 

  62. Upton Sanderbeck, P. R., D’Aloisio, A. & McQuinn, M. J. Models of the thermal evolution of the intergalactic medium after reionization. Mon. Not. R. Astron. Soc. 460, 1885–1897 (2016).

    Article  ADS  Google Scholar 

  63. Tuominen, T. et al. An EAGLE view of the missing baryons. Astron. Astrophys. 646, A156 (2021).

    Article  CAS  Google Scholar 

  64. Hardcastle, M. J. & Krause, M. G. H. Numerical modelling of the lobes of radio galaxies in cluster environments. Mon. Not. R. Astron. Soc. 430, 174–196 (2013).

    Article  ADS  Google Scholar 

  65. Barrows, R. S., Comerford, J. M., Stern, D. & Assef, R. J. A catalog of host galaxies for WISE-selected AGN: connecting host properties with nuclear activity and identifying contaminants. Astrophys. J. 922, 179 (2021).

    Article  ADS  CAS  Google Scholar 

  66. Chen, Z.-F., Pan, D.-S., Pang, T.-T. & Huang, Y. A catalog of quasar properties from the Baryon Oscillation Spectroscopic Survey. Astrophys. J. Suppl. Ser. 234, 16 (2018).

    Article  ADS  Google Scholar 

  67. Sweijen, F. GitHub repository for legacystamps. https://github.com/tikk3r/legacystamps (2021).

  68. LOFAR Collaboration. Website for LOFAR surveys data, including LoTSS DR2. https://lofar-surveys.org (2022).

  69. Hardcastle, M. J. GitHub repository for ‘A simulation-based analytic model of radio galaxies’. https://github.com/mhardcastle/analytic (2021).

  70. Oei, M. S. S. L. Code Ocean capsule for ‘Black hole jets on the scale of the cosmic web’. https://codeocean.com/capsule/3908804/tree (2024).

  71. Lang, D., Hogg, D. W. & Schlegel, D. J. WISE photometry for 400 million SDSS sources. Astron. J. 151, 36 (2016).

    Article  ADS  Google Scholar 

  72. Gordon, Y. A. et al. A quick look at the 3 GHz radio sky. I. Source statistics from the Very Large Array Sky Survey. Astrophys. J. Suppl. Ser. 255, 30 (2021).

    Article  ADS  CAS  Google Scholar 

  73. Helfand, D. J., White, R. L. & Becker, R. H. The last of FIRST: the final catalog and source identifications. Astrophys. J. 801, 26 (2015).

    Article  ADS  Google Scholar 

Download references

Acknowledgements

M.S.S.L.O. and R.J.v.W. acknowledge support from the VIDI research programme with project number 639.042.729, which is financed by the Dutch Research Council (NWO). M.S.S.L.O. also acknowledges support from the CAS–NWO programme for radio astronomy with project number 629.001.024, which is financed by the NWO. In addition, M.S.S.L.O., R.T. and R.J.v.W. acknowledge support from the ERC Starting Grant ClusterWeb 804208. M.J.H. acknowledges support from the UK STFC (ST/V000624/1). R.T. is grateful for support from the UKRI Future Leaders Fellowship (grant MR/T042842/1). A.B. acknowledges financial support from the European Union - Next Generation EU. F.d.G. acknowledges support from the ERC Consolidator Grant ULU 101086378. The work of D.S. was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). We thank F. Sweijen for making available legacystamps67. We thank R. Caniato and J.H. Croston for illuminating discussions. LOFAR data products were provided by the LOFAR Surveys Key Science project (LSKSP68) and were derived from observations with the International LOFAR Telescope (ILT). LOFAR30 is the LOw-Frequency 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 efforts of the LSKSP have benefited from funding from the European Research Council, NOVA, NWO, CNRS-INSU, the SURF Co-operative, the UK Science and Technology Funding Council and the Jülich Supercomputing Centre. We thank the staff of the GMRT, who made these observations possible. The GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and NASA. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Author information

Authors and Affiliations

Authors

Contributions

A.R.D.J.G.I.B.G. and M.S.S.L.O. discovered Porphyrion; M.J.H., assisted by citizen scientists, independently found the outflow as part of LOFAR Galaxy Zoo. M.S.S.L.O. coordinated the ensuing project. R.J.v.W., H.J.A.R. and M.J.H. advised M.S.S.L.O. throughout. A.B. re-reduced and imaged the 6.2″ and 19.8″ LOFAR data; R.J.v.W. contributed. R.T. reduced and imaged the 0.4″ LOFAR data. F.d.G. explored the use of LOFAR LBA data, which he reduced and imaged. M.S.S.L.O. wrote the uGMRT follow-up proposal. M.S.S.L.O. and H.T.I. reduced and imaged the uGMRT data. S.G.D., D.S. and H.J.A.R. were instrumental in securing Keck time (PI: S.G.D.). A.C.R. observed the host galaxy with the LRIS; A.C.R. and D.S. reduced the data. G.C.R. determined the SED and stellar mass of the host galaxy; M.S.S.L.O. contributed. M.J.H. determined core spectral indices of Mpc-scale outflows. M.S.S.L.O. determined the spurious association probability, the galaxy cluster distances and the circumgalactic cosmic web percentile. M.J.H. performed dynamical modelling; M.S.S.L.O. contributed. M.S.S.L.O. derived the deprojection and filament-heating formulae. M.S.S.L.O. wrote the article, with contributions from A.R.D.J.G.I.B.G., R.T. and A.C.R. All authors provided comments to improve the text.

Corresponding author

Correspondence to Martijn S. S. L. Oei.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Francesco Massaro and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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

Extended data figures and tables

Extended Data Fig. 1 ILT image of Porphyrion at a lower resolution of 19.8″.

The image, again at central wavelength λ = 2.08 m, highlights diffuse emission in the northern lobe and southern backflow. We show the same sky region and annotations as in Fig. 1. The contours denote significance at fixed multiples of the image noise s.d. (σ): 3σ, 5σ and 10σ.

Extended Data Fig. 2 VLBI close-up of the centre of Porphyrion.

Our ILT image of Porphyrion’s central 3.84′ × 3.84′ at λ = 2.08 m and 0.4″ resolution covers a third of the total jet system and reveals two radio-luminous AGN, detected at a significance of about 40σ (s.d.). We overlay the overarching jet axis (translucent white), determined from the northern lobe and southern hotspot (not shown), to scale for a jet radius of 1 kpc. The jet axis seems to pass through J152932.16+601534.4.

Extended Data Fig. 3 Rest-frame ultraviolet–optical spectroscopy of J152933.03+601552.5.

(This is the quasar-hosting galaxy 19″ NNE of the host galaxy of Porphyrion.) We identify redshifted hydrogen, carbon, oxygen, neon and magnesium lines, jointly implying zs = 0.799 ± 0.001. Forbidden lines from the narrow-line region of the quasar are shown in red. The spectrum has been measured with the LRIS on the W. M. Keck Observatory’s Keck I telescope.

Extended Data Fig. 4 Astrometric offsets for the host galaxy of Porphyrion.

All flux densities used in the inference of the host galaxy SED occur within an arcsecond of the Legacy-Surveys-DR10-identified host position. Coloured disks show 1σ (s.d.) astrometric uncertainties and grey circles denote angular distances from the Legacy-Surveys-DR10-identified host position. The stars mark all other Legacy-Surveys-DR10-identified sources in the angular vicinity of Porphyrion’s host.

Extended Data Fig. 5 Radio spectral indices around the centre and southern tip of Porphyrion.

The top panel, which covers 3′ × 3′, reveals SSA at metre wavelengths in the host galaxy, consistent with the fuelling of powerful jets. The bottom panel, which covers 2′ × 2′, reveals a hotspot with backflow. We show effective spectral indices α between 0.46 and 2.08 m, at a resolution of 6.2″. From light to dark, the contours denote thermal-noise-induced spectral index uncertainties (s.d.) of 0.05, 0.1, 0.2 and 0.3.

Extended Data Fig. 6 Radio spectral index distributions of the cores of Mpc-scale outflows.

Using LoTSS and VLASS data, we determined 924 effective spectral indices α between 0.1 and 2.08 m. In grey, we indicate the bins in which the core spectral indices of J152932.16+601534.4, the claimed host galaxy of Porphyrion, and J152933.03+601552.5 fall. The distribution suggests that the spectral index of J152932.16+601534.4 (α = −0.18 ± 0.06) is more typical of Mpc-scale outflows than the spectral index of J152933.03+601552.5. (For J152933.03+601552.5, owing to a VLASS non-detection, we show the LoTSS–uGMRT Band 4 spectral index.) The inset shows the same data as a function of redshift z. The orange subsample comprises Mpc-scale outflows whose redshifts differ at most Δz = 0.1 from those of either J152932.16+601534.4 or J152933.03+601552.5.

Extended Data Fig. 7 Probabilistic analysis of the distance to the nearest cluster.

DESI Legacy Imaging Surveys DR10 galaxy cluster redshift uncertainties induce multimodal, asymmetric probability distributions over measures of distance between the host galaxy of Porphyrion and the nearest galaxy cluster. We mark median-centred intervals containing 68% and 95% of all probability. The data suggest that Porphyrion does not originate from a cluster.

Extended Data Fig. 8 Environmental profiles assumed in our dynamical modelling.

We show the pressure, baryon density and temperature external to the outflow as a function of proper (rather than comoving) distance from the AGN of Porphyrion. The profiles consist of contributions from the presumed galaxy group of the outflow and the adjacent voids.

Extended Data Table 1 Flux densities Fν of Porphyrion’s host galaxy

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Oei, M.S.S.L., Hardcastle, M.J., Timmerman, R. et al. Black hole jets on the scale of the cosmic web. Nature 633, 537–541 (2024). https://doi.org/10.1038/s41586-024-07879-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-024-07879-y

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