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:

A gas-rich cosmic web revealed by the partitioning of the missing baryons

Abstract

Approximately half of the Universe’s dark matter resides in collapsed halos; significantly less than half of the baryonic matter (protons and neutrons) remains confined to halos. A small fraction of baryons are in stars and the interstellar medium within galaxies. The majority are diffuse (<10−3 cm−3) and ionized (neutral fraction <10−4), located in the intergalactic medium (IGM) and in the halos of galaxy clusters, groups and galaxies. This diffuse ionized gas is notoriously difficult to measure, but has wide implications for galaxy formation, astrophysical feedback and precision cosmology. Recently, the dispersion of extragalactic fast radio bursts (FRBs) has been used to measure the total content of cosmic baryons. Here we present a large cosmological sample of FRB sources localized to their host galaxies. We have robustly partitioned the missing baryons into the IGM, galaxy clusters and galaxies, providing a late-Universe measurement of the cosmic baryon abundance, \({\varOmega }_{{\mathrm{b}}}{h}_{70}=0.05{1}_{-0.006}^{+0.006}\), where Ωb is the baryon density parameter and h70 is the scaled Hubble constant. Our results indicate efficient feedback processes that can deplete galaxy halos and enrich the IGM (total baryon fraction in the IGM is \({f}_{{\rm{IGM}}}=0.7{6}_{-0.11}^{+0.10}\)), agreeing with the baryon-rich cosmic web scenario seen in cosmological simulations. Our results may reduce the ‘S8 tension’ in cosmology, as strong feedback leads to suppression of the matter power spectrum.

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

Access options

Buy this article

USD 39.95

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

Fig. 1: A full account and partition of the missing baryons.
Fig. 2: An MCMC fit of extragalactic gas parameters to a sample of localized FRBs.
Fig. 3: The extragalactic DM distribution of FRBs prefers a gas-rich IGM.
Fig. 4: A 10% measurement of the present-day baryon parameter.

Similar content being viewed by others

Data availability

The FRB data presented here are publicly available in a CSV file (Supplementary Data 1) and at the following link: https://github.com/liamconnor/frb_baryon_connor2024/blob/main/data/frbsample_connor0924.csv.

Code availability

We have created a reproduction package for our work that includes all code used for our data analysis and the production of each figure. We have placed this code on GitHub at https://github.com/liamconnor/frb_baryon_connor2024.

References

  1. Ravi, V. et al. The host galaxy and persistent radio counterpart of FRB 20201124A. Mon. Not. R. Astron. Soc. 513, 982–990 (2022).

    Article  ADS  Google Scholar 

  2. Lorimer, D. R., Bailes, M., McLaughlin, M. A., Narkevic, D. J. & Crawford, F. A bright millisecond radio burst of extragalactic origin. Science 318, 777–780 (2007).

    Article  ADS  Google Scholar 

  3. Macquart, J. P. et al. A census of baryons in the Universe from localized fast radio bursts. Nature 581, 391–395 (2020).

    Article  ADS  Google Scholar 

  4. Cordes, J. M. & Chatterjee, S. Fast radio bursts: an extragalactic enigma. Annu. Rev. Astron. Astrophys. 57, 417–465 (2019).

    Article  ADS  Google Scholar 

  5. Petroff, E., Hessels, J. W. T. & Lorimer, D. R. Fast radio bursts at the dawn of the 2020s. Astron. Astrophys. Rev. 30, 2 (2022).

    Article  ADS  Google Scholar 

  6. Sharma, K. et al. Preferential occurrence of fast radio bursts in massive star-forming galaxies. Nature 635, 61–66 (2024).

    Article  Google Scholar 

  7. McQuinn, M. The evolution of the intergalactic medium. Annu. Rev. Astron. Astrophys. 54, 313–362 (2016).

    Article  ADS  Google Scholar 

  8. Connor, L. et al. Deep synoptic array science: two fast radio burst sources in massive galaxy clusters. Astrophys. J. Lett. 949, L26 (2023).

    Article  ADS  Google Scholar 

  9. Niu, C. H. et al. A repeating fast radio burst associated with a persistent radio source. Nature 606, 873–877 (2022).

    Article  ADS  Google Scholar 

  10. Walker, C. R. H. et al. The dispersion measure contributions of the cosmic web. Astron. Astrophys. 683, A71 (2024).

    Article  Google Scholar 

  11. James, C. W. et al. A measurement of Hubble’s constant using fast radio bursts. Mon. Not. R. Astron. Soc. 516, 4862–4881 (2022).

    Article  ADS  Google Scholar 

  12. Prochaska, J. X. & Zheng, Y. Probing Galactic haloes with fast radio bursts. Mon. Not. R. Astron. Soc. 485, 648–665 (2019).

    ADS  Google Scholar 

  13. Connor, L. & Ravi, V. The observed impact of galaxy halo gas on fast radio bursts. Nat. Astron. 6, 1035–1042 (2022).

    Article  ADS  Google Scholar 

  14. Sun, M. et al. Chandra studies of the X-ray gas properties of galaxy groups. Astrophys. J. 693, 1142–1172 (2009).

    Article  ADS  Google Scholar 

  15. Bulbul, E. et al. The SRG/eROSITA All-Sky Survey: the first catalog of galaxy clusters and groups in the Western Galactic Hemisphere. Astron. Astrophys. 685, A106 (2024).

    Article  Google Scholar 

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

    Article  Google Scholar 

  17. Hilton, M. et al. The Atacama Cosmology Telescope: a catalog of >4000 Sunyaev–Zel’dovich galaxy clusters. Astrophys. J. Suppl. Ser. 253, 3 (2021).

    Article  ADS  Google Scholar 

  18. Gonzalez, A. H., Sivanandam, S., Zabludoff, A. I. & Zaritsky, D. Galaxy cluster baryon fractions revisited. Astrophys. J. 778, 14 (2013).

    Article  ADS  Google Scholar 

  19. Dai, X., Bregman, J. N., Kochanek, C. S. & Rasia, E. On the baryon fractions in clusters and groups of galaxies. Astrophys. J. 719, 119–125 (2010).

    Article  ADS  Google Scholar 

  20. Vikram, V., Lidz, A. & Jain, B. A measurement of the galaxy group-thermal Sunyaev–Zel’dovich effect cross-correlation function. Mon. Not. R. Astron. Soc. 467, 2315–2330 (2017).

    ADS  Google Scholar 

  21. Zwaan, M. A., Meyer, M. J., Staveley-Smith, L. & Webster, R. L. The HIPASS catalogue: ΩH I and environmental effects on the H i mass function of galaxies. Mon. Not. R. Astron. Soc. 359, L30–L34 (2005).

    Article  ADS  Google Scholar 

  22. Walter, F. et al. The evolution of the baryons associated with galaxies averaged over cosmic time and space. Astrophys. J. 902, 111 (2020).

    Article  ADS  Google Scholar 

  23. Fukugita, M., Hogan, C. J. & Peebles, P. J. E. The cosmic baryon budget. Astrophys. J. 503, 518–530 (1998).

    Article  ADS  Google Scholar 

  24. Madau, P. & Dickinson, M. Cosmic star-formation history. Annu. Rev. Astron. Astrophys. 52, 415–486 (2014).

    Article  ADS  Google Scholar 

  25. Salpeter, E. E. The luminosity function and stellar evolution. Astrophys. J. 121, 161 (1955).

    Article  ADS  Google Scholar 

  26. Gallazzi, A., Brinchmann, J., Charlot, S. & White, S. D. M. A census of metals and baryons in stars in the local Universe. Mon. Not. R. Astron. Soc. 383, 1439–1458 (2008).

    Article  ADS  Google Scholar 

  27. Leja, J. et al. A new census of the 0.2 < z < 3.0 Universe. I. The stellar mass function. Astrophys. J. 893, 111 (2020).

    Article  ADS  Google Scholar 

  28. Tumlinson, J., Peeples, M. S. & Werk, J. K. The circumgalactic medium. Annu. Rev. Astron. Astrophys. 55, 389–432 (2017).

    Article  ADS  Google Scholar 

  29. Sorini, D., Davé, R., Cui, W. & Appleby, S. How baryons affect haloes and large-scale structure: a unified picture from the SIMBA simulation. Mon. Not. R. Astron. Soc. 516, 883–906 (2022).

    Article  ADS  Google Scholar 

  30. Ramesh, R., Nelson, D. & Pillepich, A. The circumgalactic medium of Milky Way-like galaxies in the TNG50 simulation—I: Halo gas properties and the role of SMBH feedback. Mon. Not. R. Astron. Soc. 518, 5754–5777 (2023).

    Article  ADS  Google Scholar 

  31. Davé, R. et al. SIMBA: cosmological simulations with black hole growth and feedback. Mon. Not. R. Astron. Soc. 486, 2827–2849 (2019).

    Article  ADS  Google Scholar 

  32. Artale, M. C. et al. The large-scale distribution of ionized metals in IllustrisTNG. Mon. Not. R. Astron. Soc. 510, 399–412 (2022).

    Article  ADS  Google Scholar 

  33. Zhang, Y. et al. The hot circum-galactic medium in the eROSITA All Sky Survey I. X-ray surface brightness profiles. Astron. Astrophys. 690, A267 (2024).

    Article  Google Scholar 

  34. Hadzhiyska, B. et al. Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies. Preprint at https://arxiv.org/abs/2407.07152 (2024).

  35. Asgari, M. et al. KiDS-1000 cosmology: cosmic shear constraints and comparison between two point statistics. Astron. Astrophys. 645, A104 (2021).

    Article  Google Scholar 

  36. Amon, A. & Efstathiou, G. A non-linear solution to the S8 tension? Mon. Not. R. Astron. Soc. 516, 5355–5366 (2022).

    Article  ADS  Google Scholar 

  37. Cooke, R. J., Pettini, M. & Steidel, C. C. One percent determination of the primordial deuterium abundance. Astrophys. J. 855, 102 (2018).

    Article  ADS  Google Scholar 

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

    Article  Google Scholar 

  39. Wu, Q., Zhang, G.-Q. & Wang, F.-Y. An 8 percent determination of the Hubble constant from localized fast radio bursts. Mon. Not. R. Astron. Soc. 515, L1–L5 (2022).

    Article  ADS  Google Scholar 

  40. Hagstotz, S., Reischke, R. & Lilow, R. A new measurement of the Hubble constant using fast radio bursts. Mon. Not. R. Astron. Soc. 511, 662–667 (2022).

    Article  ADS  Google Scholar 

  41. Zou, H. et al. Project overview of the Beijing-Arizona Sky Survey. Publ. Astron. Soc. Pac. 129, 064101 (2017).

    Article  ADS  Google Scholar 

  42. Chambers, K. C. et al. The Pan-STARRS1 surveys. Preprint at https://arxiv.org/abs/1612.05560 (2016).

  43. Oke, J. B. et al. The Keck Low-Resolution Imaging Spectrometer. Publ. Astron. Soc. Pac. 107, 375 (1995).

    Article  ADS  Google Scholar 

  44. Faber, S. M. et al. The DEIMOS spectrograph for the Keck II Telescope: integration and testing. In Instrument Design and Performance for Optical/Infrared Ground-based Telescopes, Society of Photo-Optical Instrumentation Engineers Conference Series Vol. 4841 (eds Iye, M. & Moorwood, A. F. M.) 1657–1669 (Society of Photo-Optical Instrumentation Engineers, 2003).

  45. Wilson, J. C. et al. A wide-field infrared camera for the Palomar 200-inch telescope. In Instrument Design and Performance for Optical/Infrared Ground-based Telescopes, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 4841 (eds Iye, M. & Moorwood, A. F. M.) 451–458 (Society of Photo-Optical Instrumentation Engineers, 2003).

  46. Perley, D. A. Fully automated reduction of longslit spectroscopy with the low resolution imaging spectrometer at the Keck Observatory. Publ. Astron. Soc. Pac. 131, 084503 (2019).

    Article  ADS  Google Scholar 

  47. Aggarwal, K. et al. Probabilistic association of transients to their hosts (PATH). Astrophys. J. 911, 95 (2021).

    Article  ADS  Google Scholar 

  48. McLean, I. S. et al. MOSFIRE, the multi-object spectrometer for infra-red exploration at the Keck Observatory. In Ground-based and Airborne Instrumentation for Astronomy IV, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 84456 (eds McLean, I. S. et al.) 84460J (Society of Photo-Optical Instrumentation Engineers, 2012).

  49. Oke, J. B. & Gunn, J. E. An efficient low resolution and moderate resolution spectrograph for the Hale Telescope. Publ. Astron. Soc. Pac. 94, 586 (1982).

    Article  ADS  Google Scholar 

  50. Prochaska, J. X. et al. pypeit/pypeit: Version 1.6.0. Zenodo https://doi.org/10.5281/zenodo.5548381 (2021).

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

    Article  ADS  Google Scholar 

  52. Mandigo-Stoba, M. S., Fremling, C. & Kasliwal, M. M. DBSP_DRP: a Python package for automated spectroscopic data reduction of dbsp data. J. Open Source Softw. 7, 3612 (2022).

    Article  ADS  Google Scholar 

  53. Kewley, L. J., Nicholls, D. C. & Sutherland, R. S. Understanding galaxy evolution through emission lines. Annu. Rev. Astron. Astrophys. 57, 511–570 (2019).

    Article  ADS  Google Scholar 

  54. Bannister, K. W. et al. The detection of an extremely bright fast radio burst in a phased array feed survey. Astrophys. J. Lett. 841, L12 (2017).

    Article  ADS  Google Scholar 

  55. Prochaska, J. X. et al. The low density and magnetization of a massive galaxy halo exposed by a fast radio burst. Science 366, 231–234 (2019).

    Article  ADS  Google Scholar 

  56. Bhardwaj, M. et al. A nearby repeating fast radio burst in the direction of M81. Astrophys. J. Lett. 910, L18 (2021).

    Article  ADS  Google Scholar 

  57. Kirsten, F. et al. A repeating fast radio burst source in a globular cluster. Nature 602, 585–589 (2022).

    Article  ADS  Google Scholar 

  58. Caleb, M. et al. A subarcsec localized fast radio burst with a significant host galaxy dispersion measure contribution. Mon. Not. R. Astron. Soc. 524, 2064–2077 (2023).

    Article  ADS  Google Scholar 

  59. Law, C. J. et al. realfast: real-time, commensal fast transient surveys with the Very Large Array. Astrophys. J. Suppl. Ser. 236, 8 (2018).

    Article  ADS  Google Scholar 

  60. Cordes, J. M. & Lazio, T. J. W. NE2001.I. A new model for the galactic distribution of free electrons and its fluctuations. Preprint at https://arxiv.org/abs/astro-ph/0207156 (2002).

  61. Ocker, S. K., Cordes, J. M. & Chatterjee, S. Electron density structure of the local Galactic disk. Astrophys. J. 897, 124 (2020).

    Article  ADS  Google Scholar 

  62. Ravi, V. et al. Deep Synoptic Array science: a 50 Mpc fast radio burst constrains the mass of the Milky Way circumgalactic medium. Astron. J. 169, 330 (2023).

    Article  Google Scholar 

  63. Cook, A. M. et al. An FRB sent me a DM: constraining the electron column of the Milky Way halo with fast radio burst dispersion measures from CHIME/FRB. Astrophys. J. 946, 58 (2023).

    Article  ADS  Google Scholar 

  64. Yang, X. et al. An extended halo-based group/cluster finder: application to the DESI legacy imaging surveys DR8. Astrophys. J. 909, 143 (2021).

    Article  ADS  Google Scholar 

  65. Gentile, G., Baes, M., Famaey, B. & van Acoleyen, K. Mass models from high-resolution H i data of the dwarf galaxy NGC 1560. Mon. Not. R. Astron. Soc. 406, 2493–2503 (2010).

    Article  ADS  Google Scholar 

  66. Faber, J. T. et al. A heavily scattered fast radio burst is viewed through multiple galaxy halos. Preprint at https://arxiv.org/abs/2405.14182 (2024).

  67. Ocker, S. K. et al. Scattering variability detected from the circumsource medium of FRB 20190520B. Mon. Not. R. Astron. Soc. 519, 821–830 (2023).

    Article  ADS  Google Scholar 

  68. Anna-Thomas, R. et al. Magnetic field reversal in the turbulent environment around a repeating fast radio burst. Science 380, 599–603 (2023).

    Article  ADS  Google Scholar 

  69. Lee, K.-G. et al. The FRB 20190520B sight line intersects foreground galaxy clusters. Astrophys. J. Lett. 954, L7 (2023).

    Article  ADS  Google Scholar 

  70. James, C. W. et al. The z–DM distribution of fast radio bursts. Mon. Not. R. Astron. Soc. 509, 4775–4802 (2022).

    Article  ADS  Google Scholar 

  71. Nelson, D. et al. The IllustrisTNG simulations: public data release. Comput. Astrophys. Cosmol. 6, 2 (2019).

    Article  ADS  Google Scholar 

  72. Zhang, Z. J., Yan, K., Li, C. M., Zhang, G. Q. & Wang, F. Y. Intergalactic medium dispersion measures of fast radio bursts estimated from IllustrisTNG simulation and their cosmological applications. Astrophys. J. 906, 49 (2021).

    Article  ADS  Google Scholar 

  73. Martizzi, D. et al. Baryons in the cosmic web of IllustrisTNG—I: Gas in knots, filaments, sheets, and voids. Mon. Not. R. Astron. Soc. 486, 3766–3787 (2019).

    Article  ADS  Google Scholar 

  74. Connor, L. Interpreting the distributions of FRB observables. Mon. Not. R. Astron. Soc. 487, 5753–5763 (2019).

    Article  ADS  Google Scholar 

  75. McQuinn, M. Locating the ‘missing’ baryons with extragalactic dispersion measure estimates. Astrophys. J. Lett. 780, L33 (2014).

    Article  ADS  Google Scholar 

  76. Shin, K. et al. Inferring the energy and distance distributions of fast radio bursts using the first CHIME/FRB catalog. Astrophys. J. 944, 105 (2023).

    Article  ADS  Google Scholar 

  77. Khrykin, I. S. et al. FLIMFLAM DR1: the first constraints on the cosmic baryon distribution from eight fast radio burst sight lines. Astrophys J. 973, 151 (2024).

    Article  Google Scholar 

  78. Bhardwaj, M. et al. A local universe host for the repeating fast radio burst FRB 20181030A. Astrophys. J. Lett. 919, L24 (2021).

    Article  ADS  Google Scholar 

  79. Marcote, B. et al. A repeating fast radio burst source localized to a nearby spiral galaxy. Nature 577, 190–194 (2020).

    Article  ADS  Google Scholar 

  80. Pastor-Marazuela, I. et al. Chromatic periodic activity down to 120 megahertz in a fast radio burst. Nature 596, 505–508 (2021).

    Article  ADS  Google Scholar 

  81. Orr, M. E., Burkhart, B., Lu, W., Ponnada, S. B. & Hummels, C. B. Objects may be closer than they appear: significant host galaxy dispersion measures of fast radio bursts in zoom-in simulations. Astrophys. J. Lett. 972, L26 (2024).

    Article  Google Scholar 

  82. Kovacs, T. O. et al. Dispersion rotation measures from fast radio burst host (FRB) host galaxies based on the TNG50 simulation. Astron. Astrophys. 690, A47 (2024).

    Article  Google Scholar 

  83. Yang, K. B., Wu, Q. & Wang, F. Y. Finding the missing baryons in the intergalactic medium with localized fast radio bursts. Astrophys. J. Lett. 940, L29 (2022).

    Article  ADS  Google Scholar 

  84. Shull, J. M., Smith, B. D. & Danforth, C. W. The baryon census in a multiphase intergalactic medium: 30% of the baryons may still be missing. Astrophys. J. 759, 23 (2012).

    Article  ADS  Google Scholar 

  85. Baptista, J. et al. Measuring the variance of the macquart relation in redshift–extragalactic dispersion measure modeling. Astrophys. J. 965, 57 (2024).

    Article  ADS  Google Scholar 

  86. Wu, X. & McQuinn, M. A measurement of circumgalactic gas around nearby galaxies using fast radio bursts. Astrophys. J. 945, 87 (2023).

    Article  ADS  Google Scholar 

  87. Lee, K.-G. et al. Constraining the cosmic baryon distribution with fast radio burst foreground mapping. Astrophys. J. 928, 9 (2022).

    Article  ADS  Google Scholar 

  88. Madhavacheril, M. S., Battaglia, N., Smith, K. M. & Sievers, J. L. Cosmology with the kinematic Sunyaev–Zeldovich effect: breaking the optical depth degeneracy with fast radio bursts. Phys. Rev. D 100, 103532 (2019).

    Article  ADS  Google Scholar 

  89. Reischke, R., Neumann, D., Bertmann, K. A., Hagstotz, S. & Hildebrandt, H. Calibrating baryonic feedback with weak lensing and fast radio bursts. Preprint at https://arxiv.org/abs/2309.09766 (2023).

  90. Peñarrubia, J., Gómez, F. A., Besla, G., Erkal, D. & Ma, Y.-Z. A timing constraint on the (total) mass of the Large Magellanic Cloud. Mon. Not. R. Astron. Soc. 456, L54–L58 (2015).

    Article  ADS  Google Scholar 

  91. Böhringer, H., Chon, G. & Fukugita, M. The extended ROSAT-ESO flux-limited X-ray galaxy cluster survey (REFLEX II). VII. The mass function of galaxy clusters. Astron. Astrophys. 608, A65 (2017).

    Article  ADS  Google Scholar 

  92. Bahcall, N. A. & Cen, R. The mass function of clusters of galaxies. Astrophys. J. Lett. 407, L49 (1993).

    Article  ADS  Google Scholar 

  93. Fukugita, M. & Peebles, P. J. E. The cosmic energy inventory. Astrophys. J. 616, 643–668 (2004).

    Article  ADS  Google Scholar 

  94. Prochaska, J. X., Weiner, B., Chen, H. W., Mulchaey, J. & Cooksey, K. Probing the intergalactic medium/galaxy connection. V. On the origin of Lyα and O vi absorption at z < 0.2. Astrophys. J. 740, 91 (2011).

    Article  ADS  Google Scholar 

  95. Werk, J. K. et al. The COS-Halos Survey: physical conditions and baryonic mass in the low-redshift circumgalactic medium. Astrophys. J. 792, 8 (2014).

    Article  ADS  Google Scholar 

  96. Péroux, C. & Howk, J. C. The cosmic baryon and metal cycles. Annu. Rev. Astron. Astrophys. 58, 363–406 (2020).

    Article  ADS  Google Scholar 

  97. Conroy, C. Modeling the panchromatic spectral energy distributions of galaxies. Annu. Rev. Astron. Astrophys. 51, 393–455 (2013).

    Article  ADS  Google Scholar 

  98. Conroy, C. & van Dokkum, P. Counting low-mass stars in integrated light. Astrophys. J. 747, 69 (2012).

    Article  ADS  Google Scholar 

  99. Paul, S., Santos, M. G., Chen, Z. & Wolz, L. A first detection of neutral hydrogen intensity mapping on Mpc scales at z ≈ 0.32 and z ≈ 0.44. Preprint at https://arxiv.org/abs/2301.11943 (2023).

  100. Leja, J. et al. A new census of the 0.2 < z < 3.0 Universe. II. The star-forming sequence. Astrophys. J. 936, 165 (2022).

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We thank F. Walter, X. Prochaska and M. Oei for informative conversations. We also thank D. Nelson and C. Walker for their considerable help with IllustrisTNG.

Author information

Authors and Affiliations

Authors

Contributions

V.R. and G. Hallinan led the development of the DSA-110. D.H., M.H., J.L., P.R., S.W. and D.W. contributed to the construction of the DSA-110. L.C. conceived of and performed the analysis techniques for studying the FRB sample, as well as the multiwavelength baryon analysis. L.C. led the writing of the paper, with assistance from all co-authors. K.S., V.R., L.C., C.L., J.S., J.F., N.K. and M.S. all conducted the optical/infrared follow-up observations presented in this work. K.S. and V.R. undertook the majority of the optical/infrared host-galaxy data analysis and interpretation. V.R., C.L., L.C., G. Hellbourg and R.H. developed the software pipeline for detecting FRBs on the DSA-110. R.M.K. led the investigation of ray tracing in the IllustrisTNG simulation.

Corresponding author

Correspondence to Liam Connor.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Astronomy thanks Q. Wu and the other, anonymous, reviewers(s) for their contribution to the peer review of this work.

Additional information

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

Extended data

Extended Data Fig. 1 Optical/IR images of nine DSA-110 discovered FRB fields.

This subset of sources are the FRBs that did not make it into our companion paper’s host galaxy analysis, either because they were discovered after November 2023 or because their host did not meet the r ~ 23.5 mag criteria. Each image is centred on the host galaxy candidate preferred by PATH, identified by cyan cross-hairs6. The 90% confidence FRB localization regions are marked as red ellipses. All images were smoothed with a Gaussian kernel of σ = 0. 2 – 0. 4 to improve visibility.

Extended Data Fig. 2 The DM and total baryon distributions in IllustrisTNG.

Panels a-d show Macquart Relations for different components of diffuse cosmic gas from a mock FRB survey10. We plot \({{\rm{DM}}}_{{\rm{ex}}/{z}_{\rm s}}\) for intervening halos (green, panel a), the IGM (grey, b), and total DM (black, c). The solid curves are the mean extragalactic DM at that redshift. Panel d shows the total extragalactic DM distribution after including a log-normal host DM distribution, where the heatmap is the log probability and the redpoints are the actual samples. Panel e is a radial treemap showing the partition of baryons in TNG300-1.

Extended Data Fig. 3 Examples of cosmic DM distributions for different redshifts and cosmic baryon parameters.

The two upper rows show the 2D P(DMIGM, DMX) distribution, which is the relative probability in DMIGM and DMX for FRBs at zs = 0.5 (top) and zs = 1.0 (middle) for increasing values of the halo gas fraction, fX. We use a bivariate log-normal distribution that has been calibrated to mock FRB surveys in the Illustris TNG300-1 simulation. The distribution ensures that DMIGM and DMX are correlated, since sightlines that pass through halos are more likely to pass through overdensities in the cosmic web and have large DMIGM. In order to compute our final likelihood function, the 2D distribution shown in the top two rows must be integrated along curves of constant cosmic DM, \({{\rm{DM}}}_{\cos }={{\rm{DM}}}_{{\rm{IGM}}}+{{\rm{DM}}}_{{\rm{X}}}\). The resulting \(P({{\rm{DM}}}_{{\rm{ex}}}| {z}_{\rm s},\overrightarrow{\theta })\) are show in the bottom row, with μhost = 4.5 and σhost = 0.7. The bottom left and bottom right likelihoods are not supported by our data.

Extended Data Fig. 4 A direct measurement of the diffuse gas content.

The value of \({{\rm{DM}}}_{\cos }={{\rm{DM}}}_{{\rm{IGM}}}+{{\rm{DM}}}_{{\rm{X}}}\) averaged over a large number of sightlines is a direct measure of the cosmic density of diffuse, ionized baryonic matter, fdΩb. We show the results from two different methods for estimating the ionized fraction of baryons, fd. The corner plot in panel a shows pairwise posteriors from an MCMC fit, which produces \({f}_{d}=0.9{3}_{-0.05}^{+0.04}\) after marginalizing over the host DM parameters. In panel b we plot the diffuse fraction of baryons as a function of redshift for our sample of localized FRBs with 1σ error bars (red markers). Over-plotted as black points are the zs > 0.2 sample we use to compute a weighted average of fd. The right side shows the probability P(fd) from kernel density estimation (KDE), where the red distribution is for the whole sample.

Extended Data Fig. 5 The matter budget in massive halos.

We plot the fraction of matter bound in massive groups and galaxy clusters above a given mass, defined here as M500. The left vertical axis shows the fraction of cosmic baryons within r500 of halos with mass greater than M500. The right vertical axis shows the total matter bound in halos. The divergence at low masses is due to the apparent scarcity of baryons in smaller halos.

Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1 and 2, Discussion on ‘comparison with simulations’, and Table 1 with extra information on the optical FRB host galaxies.

Supplementary Data 1 (download CSV )

Properties of the FRBs used in this work.

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

Connor, L., Ravi, V., Sharma, K. et al. A gas-rich cosmic web revealed by the partitioning of the missing baryons. Nat Astron 9, 1226–1239 (2025). https://doi.org/10.1038/s41550-025-02566-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41550-025-02566-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