Gamma-ray heartbeat powered by the microquasar SS 433


Microquasars, the local siblings of extragalactic quasars, are binary systems comprising a compact object and a companion star. By accreting matter from their companions, microquasars launch powerful winds and jets, influencing the interstellar environment around them. Steady gamma-ray emission is expected to rise from their central objects, or from interactions between their outflows and the surrounding medium. The latter prediction was recently confirmed with the detection of SS 433 at high (TeV) energies1. In this report, we analyse more than ten years of gigaelectronvolt gamma-ray data from the Fermi Gamma-ray Space Telescope on this source. Detailed scrutiny of the data reveal emission in the vicinity of SS 433, co-spatial with a gas enhancement, and hints of emission possibly associated with a terminal lobe of one of the jets. Both gamma-ray excesses are relatively far from the central binary, and the former shows evidence of a periodic variation at the precessional period of SS 433, linking it with the microquasar. This result challenges obvious interpretations and is unexpected from previously published theoretical models. It provides us with a chance to unveil the particle transport from SS 433 and to probe the structure of the magnetic field in its vicinity.

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Fig. 1: Gamma-ray and atomic cloud images of the SS 433 region.
Fig. 2: SS 433 precession signal seen in Fermi J1913+0515.
Fig. 3: Analysis of Fermi-LAT data in precessional phases.

Data availability

The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.


  1. 1.

    Abeysekara, A. U. et al. Very-high-energy particle acceleration powered by the jets of the microquasar SS 433. Nature 562, 82–85 (2018).

    ADS  Google Scholar 

  2. 2.

    Fabrika, S. The jets and supercritical accretion disk in SS433. Astrophys. Space Phys. Rev. 12, 1–152 (2004).

    ADS  Google Scholar 

  3. 3.

    Shklovskii, I. S. Mass loss by SS433 and its effect on the x-ray and radio emission. Sov. Astron. 25, 315–319 (1981).

    ADS  Google Scholar 

  4. 4.

    Fabian, A. C. & Rees, M. J. SS 433: a double jet in action? Mon. Not. R. Astron. Soc. 187, 13–16 (1979).

    ADS  Google Scholar 

  5. 5.

    Margon, B., Ford, H. C., Grandi, S. A. & Stone, R. P. S. Enormous periodic Doppler shifts in SS 433. Astrophys. J. 233, L63–L68 (1979).

    ADS  Google Scholar 

  6. 6.

    Middleton, M. J. et al. NuSTAR reveals the hidden nature of SS433.Preprint at (2018).

  7. 7.

    Dubner, G. M., Holdaway, M., Goss, W. M. & Mirabel, I. F. A high-resolution radio study of the W50-SS 433 system and the surrounding medium. Astron. J. 116, 1842–1855 (1998).

    ADS  Google Scholar 

  8. 8.

    Su, Y. et al. The large-scale interstellar medium of SS 433/W50 revisited. Astrophys. J. 863, 103–119 (2018).

    ADS  Google Scholar 

  9. 9.

    Migliari, S., Fender, R. & Méndez, M. Iron emission lines from extended X-ray jets in SS 433: reheating of atomic nuclei. Science 297, 1673–1676 (2002).

    ADS  Google Scholar 

  10. 10.

    Davydov, V. V., Esipov, V. F. & Cherepashchuk, A. M. Spectroscopic monitoring of SS 433: a search for long-term variations of kinematic model parameters. Astron. Rep. 52, 487–506 (2008).

    ADS  Google Scholar 

  11. 11.

    Marshall, H. L., Canizares, C. R. & Schulz, N. S. The high-resolution X-ray spectrum of SS 433 using the Chandra HETGS. Astrophys. J. 564, 941–952 (2002).

    ADS  Google Scholar 

  12. 12.

    Vermeulen, R. C., Schilizzi, R. T., Icke, V., Fejes, I. & Spencer, R. E. Evolving radio structure of the binary star SS433 at a resolution of 15 marc s. Nature 328, 309–313 (1987).

    ADS  Google Scholar 

  13. 13.

    Safi-Harb, S. & Ögelman, H. ROSAT and ASCA observations of W50 associated with the peculiar source SS 433. Astrophys. J. 483, 868–881 (1997).

    ADS  Google Scholar 

  14. 14.

    Reynoso, M. M., Romero, G. E. & Christiansen, H. R. Production of gamma rays and neutrinos in the dark jets of the microquasar SS433. Mon. Not. R. Astron. Soc. 387, 1745–1754 (2008).

    ADS  Google Scholar 

  15. 15.

    Bosch-Ramon, V., Aharonian, F. A. & Paredes, J. M. Electromagnetic radiation initiated by hadronic jets from microquasars in the ISM. Astron. Astrophys. 432, 609–618 (2005).

    ADS  Google Scholar 

  16. 16.

    Bordas, P., Yang, R., Kafexhiu, E. & Aharonian, F. Detection of persistent gamma-ray emission toward SS433/W50. Astrophys. J. 807, L8–L12 (2015).

    ADS  Google Scholar 

  17. 17.

    Xing, Y., Wang, Z., Zhang, X., Chen, Y. & Jithesh, V. Fermi observation of the jets of the microquasar SS 433. Astrophys. J. 872, 25–29 (2019).

    ADS  Google Scholar 

  18. 18.

    Rasul, K., Chadwick, P. M., Graham, J. A. & Brown, A. M. Gamma-rays from SS433: evidence for periodicity. Mon. Not. R. Astron. Soc. 485, 2970–2975 (2019).

    ADS  Google Scholar 

  19. 19.

    Sun, X. et al. Tentative evidence of spatially extended GeV emission from SS433/W50. Astron. Astrophys. 626, 113–118 (2019).

    Google Scholar 

  20. 20.

    Gaia Collaboration The Gaia mission. Astron. Astrophys. 595, 1–36 (2016).

    Google Scholar 

  21. 21.

    Aharonian, F. A. & Atoyan, A. M. Gamma rays from galactic sources with relativistic jets. N. Astron. Rev. 42, 579–584 (1998).

    ADS  Google Scholar 

  22. 22.

    Romero, G. E., Torres, D. F., KaufmanBernadó, M. M. & Mirabel, I. F. Hadronic gamma-ray emission from windy microquasars. Astron. Astrophys. 410, L1–L4 (2003).

    ADS  Google Scholar 

  23. 23.

    Reynoso, M. M., Christiansen, H. R. & Romero, G. E. Gamma-ray absorption in the microquasar SS433. Astropart. Phys. 28, 565–572 (2008).

    ADS  Google Scholar 

  24. 24.

    MAGIC Collaboration Constraints on particle acceleration in SS433/W50 from MAGIC and H.E.S.S. observations. Astron. Astrophys. 612, 14–21 (2018).

    Google Scholar 

  25. 25.

    Blundell, K. M. & Bowler, M. G. Symmetry in the changing jets of SS 433 and its true distance from us. Astrophys. J. 616, L159–L162 (2004).

    ADS  Google Scholar 

  26. 26.

    Monceau-Baroux, R., Porth, O., Meliani, Z. & Keppens, R. The SS433 jet from subparsec to parsec scales. Astron. Astrophys. 574, 143–149 (2015).

    ADS  Google Scholar 

  27. 27.

    Monceau-Baroux, R., Porth, O., Meliani, Z. & Keppens, R. The SS433 jet from subparsec to parsec scales (corrigendum). Astron. Astrophys. 607, 4 (2017).

    ADS  Google Scholar 

  28. 28.

    Atwood, W. B. et al. The large area telescope on the Fermi gamma-ray space telescope mission. Astrophys. J. 697, 1071–1102 (2009).

    ADS  Google Scholar 

  29. 29.

    Fermi Science Tools. (2020).

  30. 30.

    Abdollahi, S. et al. Fermi large area telescope fourth source catalog. Astrophys. J. Suppl. Ser. 247, 33–69 (2020).

    ADS  Google Scholar 

  31. 31.

    LAT Background models. (2020).

  32. 32.

    Acero, F. et al. Fermi large area telescope third source catalog. Astrophys. J. Suppl. Ser. 218, 23–63 (2015).

    ADS  Google Scholar 

  33. 33.

    Wood, M. et al. Fermipy: an open-source Python package for analysis of Fermi-LAT data. In Proc. 35th International Cosmic Ray Conference 824 (Proceedings of Science, 2017);

  34. 34.

    Ackermann, M. et al. The Fermi large area telescope on orbit: event classification, instrument response functions, and calibration. Astrophys. J. Suppl. Ser. 203, 4–73 (2012).

    ADS  Google Scholar 

  35. 35.

    Aeff systematics. (2020).

  36. 36.

    Abdo, A. A. et al. The second Fermi large area telescope catalog of gamma-ray pulsars. Astrophys. J. Suppl. Ser. 208, 17–75 (2013).

    ADS  Google Scholar 

  37. 37.

    de Jager, O. C., Raubenheimer, B. C. & Swanepoel, J. W. H. A powerful test for weak periodic signals with unknown light curve shape in sparse data. Astron. Astrophys. 221, 180–190 (1989).

    ADS  Google Scholar 

  38. 38.

    de Jager, O. C. & Büsching, I. The H-test probability distribution revisited: improved sensitivity. Astron. Astrophys. 517, L9–L11 (2010).

    ADS  MATH  Google Scholar 

  39. 39.

    Hobbs, G. B., Edwards, R. T. & Manchester, R. N. TEMPO2, a new pulsar-timing package – I. An overview. Mon. Not. R. Astron. Soc. 369, 655–672 (2006).

    ADS  Google Scholar 

  40. 40.

    Ray, P. S. et al. Precise γ -ray timing and radio observations of 17 fermi γ -ray pulsars. Astrophys. J. Suppl. Ser. 194, 17–44 (2011).

    ADS  Google Scholar 

  41. 41.

    Abdo, A. A. et al. PSR J1907+0602: a radio-faint gamma-ray pulsar powering a bright Tev pulsar wind nebula. Astrophys. J. 711, 64–74 (2010).

    ADS  Google Scholar 

  42. 42.

    Li, J. et al. GeV detection of HESS J0632+057. Astrophys. J. 846, 169–175 (2017).

    ADS  Google Scholar 

  43. 43.

    Jackson, B. et al. An algorithm for optimal partitioning of data on an interval. IEEE Signal Process. Lett. 12, 105–108 (2015).

    ADS  Google Scholar 

  44. 44.

    Scargle, J. D., Norris, J. P., Jackson, B. & Chiang, J. Studies in astronomical time series analysis. VI. Bayesian block representations. Astrophys. J. 764, 167–192 (2013).

    ADS  Google Scholar 

  45. 45.

    Reich, W., Reich, P. & Fuerst, E. The Effelsberg 21 CM radio continuum survey of the galactic plane between L = 357 deg and L = 95.5 deg.Astron. Astrophys. Suppl. Ser. 83, 539–568 (1990).

    ADS  Google Scholar 

  46. 46.

    Preliminary LAT 8-year Point Source List (FL8Y). (2018).

  47. 47.

    Lomb, N. R. Least-squares frequency analysis of unequally spaced data. Astrophys. Space Sci. 39, 447–462 (1976).

    ADS  Google Scholar 

  48. 48.

    Scargle, J. D. Studies in astronomical time series analysis. II. Statistical aspects of spectral analysis of unevenly spaced data. Astrophys. J. 263, 835–853 (1982).

    ADS  Google Scholar 

  49. 49.

    Israel, G. The Basics of X-Ray Timing. In Urbino 2008: High Energy Astrophysics Summer School (Urbino, 2008);

  50. 50.

    LAT temporal caveats. (2020).

  51. 51.

    Foster, G. Wavelets for period analysis of unevenly sampled time series. Astron. J. 112, 1709 (1996).

    ADS  Google Scholar 

  52. 52.

    Peek, J. E. G. et al. The GALFA-HI survey: data release 1. Astrophys. J. Suppl. Ser. 194, 20–32 (2011).

    ADS  Google Scholar 

  53. 53.

    Peek, J. E. G. et al. The GALFA-HI survey: data release 2. Astrophys. J. Suppl. Ser. 234, 2–16 (2018).

    ADS  Google Scholar 

  54. 54.

    Reid, M. J. et al. Trigonometric parallaxes of high mass star forming regions: the structure and kinematics of the Milky Way. Astrophys. J. 783, 130–143 (2014).

    ADS  Google Scholar 

  55. 55.

    Heyer, M. & Dame, T. M. Molecular clouds in the Milky Way. Annu. Rev. Astron. Astrophys. 53, 583–629 (2015).

    ADS  Google Scholar 

  56. 56.

    Fukui, Y. & Kawamura, A. Molecular clouds in nearby galaxies. Annu. Rev. Astron. Astrophys. 48, 547–580 (2010).

    ADS  Google Scholar 

  57. 57.

    Bergin, E. A. & Tafalla, M. Cold dark clouds: the initial conditions for star formation. Annu. Rev. Astron. Astrophys. 45, 339–396 (2007).

    ADS  Google Scholar 

  58. 58.

    ROSAT Xselect User Guide (HEASARC, 2014);

  59. 59.

    Brinkmann, W., Aschenbach, B. & Kawai, N. ROSAT observations of the W 50/SS 433 system. Astron. Astrophys. 312, 306–316 (1996).

    ADS  Google Scholar 

  60. 60.

    Aharonian, F. A. & Atoyan, A. M. On the emissivity of π0-decay gamma radiation in the vicinity of accelerators of galactic cosmic rays. Astron. Astrophys. 309, 917–928 (1996).

    ADS  Google Scholar 

  61. 61.

    Panferov, A. A. Jets of SS 433 on scales of dozens of parsecs. Astron. Astrophys. 599, 77–84 (2017).

    ADS  Google Scholar 

  62. 62.

    Goodall, P. T., Blundell, K. M. & Bell Burnell, S. J. Probing the history of SS 433as jet kinematics via decade-resolution radio observations of W 50. Mon. Not. R. Astron. Soc. 414, 2828–2837 (2011).

    ADS  Google Scholar 

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The Fermi LAT Collaboration acknowledges generous ongoing support from a number of agencies and institutes that have supported both the development and the operation of the LAT as well as scientific data analysis. These include the National Aeronautics and Space Administration and the Department of Energy in the United States, the Commissariat à l’Energie Atomique and the Centre National de la Recherche Scientifique/Institut National de Physique Nucléaire et de Physique des Particules in France, the Agenzia Spaziale Italiana and the Istituto Nazionale di Fisica Nucleare in Italy, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), High Energy Accelerator Research Organization (KEK) and Japan Aerospace Exploration Agency (JAXA) in Japan and the K. A. Wallenberg Foundation, the Swedish Research Council and the Swedish National Space Board in Sweden. Additional support for science analysis during the operations phase is gratefully acknowledged from the Istituto Nazionale di Astrofisica in Italy and the Centre National d’Études Spatiales in France. This work was performed in part under DOE Contract DE-AC02-76SF00515. J.L. acknowledges support from the Alexander von Humboldt Foundation and the National Natural Science Foundation of China via grant numbers NSFC-11673013 and NSFC-11733009. The work of D.F.T. was supported by grant numbers PGC2018-095512-B-I00, SGR2017-1383 and AYA2017-92402-EXP. J.L. and D.F.T. acknowledge discussions with the international team on ‘Understanding and unifying the gamma rays emitting scenarios in high mass and low mass X-ray binaries’ of the ISSI (International Space Science Institute), Beijing, as well as the support of the COST Action PHAROS (CA16214). E.d.O.W. acknowledges support from the Alexander von Humboldt Foundation. Work at the NRL is supported by NASA. We thank R. Bühler, F. Acero, J. Ballet, P. Bruel, S. Digel, G. Jóhannesson, D. J. Thompson and J. L. Racusin for their comments and suggestions. We thank P. Zhang for help with the weighted wavelet Z-transform. This publication uses data from the GALFA H i survey dataset obtained with ALFA on the Arecibo 305 m telescope. The Arecibo Observatory is operated by SRI International under a cooperative agreement with the National Science Foundation (AST-1100968) and in alliance with Ana G. Méndez-Universidad Metropolitana and the Universities Space Research Association. The GALFA H i surveys were funded by the NSF through grants to Columbia University, the University of Wisconsin and the University of California.

Author information




J.L. led the observational analysis. J.L. and D.F.T. wrote the manuscript together, iterating on all aspects of the analysis, their interpretation and modelling. R.-Y.L. contributed to the theoretical interpretations. M.K. provided the timing ephemeris of gamma-ray pulsar PSR J1907+0602. E.d.O.W. participated in the interpretation of the results. Y.S. provided analysis and input for the neutral atomic gas. All authors discussed the contents of the paper and contributed to the preparation of the manuscript.

Corresponding author

Correspondence to Jian Li.

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Peer review information Nature Astronomy thanks Pol Bordas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Gamma-ray pulsar PSR J1907+0602’s contamination on SS 433 region.

a, 100 MeV – 300 GeV counts map of the Fermi-LAT field of the SS 433 region. The microquasar itself is noted with a bold cross. The fitted position of Fermi J1913+0515 and west excess are shown with green crosses. The regions used to produce pulse profiles are shown with dotted circles. b, Folded pulse profile of PSR J1907+0602 above 300 MeV with an ROI of 0.6. Two rotational pulse periods are shown, with a resolution of 100 phase bins per period. The Bayesian block decomposition is shown by red lines. The off-peak interval (ϕ=0.697–1.136) is defined by black dotted lines. c, Folded pulse profile of the photons centered on SS 433 with a radius of 0.6 above 100 MeV, using the ephemeris of PSR J1907+0602. Two rotational pulse periods are shown, with a resolution of 25 phase bins per period. The vertical error bar in (b) and (c) indicates the 68% credible interval.

Extended Data Fig. 2 Gamma-ray spectra of Fermi J1913+0515 and the west excess.

a, b, Fermi-LAT spectra of Fermi J1913+0515 (a) and the west excess (b).The maximum likelihood model (power law) fitted with gtlike is shown with a dashed line. The vertical error bar indicates the 68% credible interval and the upper limits are at the 99% confidence level.

Extended Data Fig. 3 Full period range timing analysis of Fermi J1913+0515.

Exposure-corrected Lomb-Scargle power spectra constructed from the 1–300 GeV weighted light curve of Fermi J1913+0515 covering the entire period range of the observation data (top panel, 0–700 days; bottom panel, 700–3800 days). The red dashed line indicates false alarm probability of 5% level corresponding to the full period range power spectra.

Extended Data Fig. 4 Precessional phase light curves of Fermi J1913+0515.

Precessional phase light curve of Fermi J1913+0515 flux (top panel) and TS values (bottom panel) in 1-300 GeV with a binning of 0.1. The vertical error bar indicates the 68% credible interval and the upper limits are at the 95% confidence level.

Extended Data Fig. 5 Stability of the timing signal.

a, cumulative likelihood analysis during precession phase 0.0–0.5 and 0.5–1.0. The TS of Fermi J1913+0515 in precession phase 0.0-0.5 and 0.5-1.0 are shown with blue squares and red triangles. The ΔTS of the flux deviation from a constant are shown with black dots. The TS of the flux difference between two precessional phase bins are shown with green stars. b, 2D plane contour plotting for the WWZ power spectrum.

Extended Data Fig. 6 Examples of simulations for a periodic, instantaneous injection of protons.

a, the contributions to 10 GeV cosmic rays at different distances from the injection point of 100 individual injection events, compared to the Galactic cosmic-ray sea (the black horizontal line). Each symbol/color represents a different distance (30, 35, 40, 45 and 50 pc) from injection to the interaction point. b, the cosmic-ray density at all energies. The green lines represent individual injection event (corresponding to 10, 20, 30... 100 in the x-axis of (a)), whereas the violet line shows the sum of the contribution of all injection events. c, the hadronic gamma-ray emission at 1 GeV at different distances. Symbol/color representations are the same with (a).

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Li, J., Torres, D.F., Liu, RY. et al. Gamma-ray heartbeat powered by the microquasar SS 433. Nat Astron 4, 1177–1184 (2020).

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