Abstract
The Fermi bubbles are giant, γ-ray-emitting lobes emanating from the nucleus of the Milky Way discovered in ~1–100 GeV data collected by the Large Area Telescope on board the Fermi Gamma-Ray Space Telescope. Previous work has revealed substructure within the Fermi bubbles that has been interpreted as a signature of collimated outflows from the Galaxy’s supermassive black hole. Here we show via a spatial template analysis that much of the γ-ray emission associated with the brightest region of substructure—the so-called cocoon—is probably due to the Sagittarius dwarf spheroidal galaxy (dSph). This large Milky Way satellite is viewed through the Fermi bubbles from the position of the Solar System. As a tidally and ram-pressure stripped remnant, the Sagittarius dSph has no ongoing star formation, but we nevertheless demonstrate that the dwarf’s millisecond pulsar population can plausibly supply the γ-ray signal that our analysis associates with its stellar template. The measured spectrum is naturally explained by inverse Compton scattering of cosmic microwave background photons by high-energy electron–positron pairs injected by millisecond pulsars belonging to the Sagittarius dSph, combined with these objects’ magnetospheric emission. This finding plausibly suggests that millisecond pulsars produce significant γ-ray emission among old stellar populations, potentially confounding indirect dark-matter searches in regions such as the Galactic Centre, the Andromeda galaxy and other massive Milky Way dSphs.
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Data availability
All data analysed in this study are publicly available. Fermi-LAT data are available from https://fermi.gsfc.nasa.gov/ssc/data/ and Gaia data are available from https://gea.esac.esa.int/archive/. The statistical pipeline, astrophysical templates and gamma-ray observations necessary to reproduce our main results are publicly available via Zenodo at https://doi.org/10.5281/zenodo.6210967.
Code availability
Fermi-LAT data used in our study were reduced and analysed using the standard FERMITOOLS V1.0.1 software package available from https://github.com/fermi-lat/Fermitools-conda/wiki. The performance of the Fermi-LAT was modelled with the P8R3_ULTRACLEANVETO_V2 instrument response functions. Spectral analysis and fitting were performed using custom MATHEMATICA code created by the authors, which is available from RMC upon reasonable request.
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Acknowledgements
R.M.C. acknowledges support from the Australian Government through the Australian Research Council under award number DP190101258 (shared with M.R.K.) and hospitality from the Virginia Institute of Technology, the Max-Planck Institut für Kernphysik and the GRAPPA Institute at the University of Amsterdam supported by the Kavli IPMU at the University of Tokyo. O.M. is supported by the GRAPPA Prize Fellowship and JSPS KAKENHI grant numbers JP17H04836, JP18H04340, JP18H04578 and JP20K14463. This work was supported by World Premier International Research Centre Initiative (WPI Initiative), MEXT, Japan. D.M. acknowledges support from the Australian Government through a Future Fellowship from the Australian Research Council, award number FT160100206. M.R.K. acknowledges support from the Australian Government through the Australian Research Council, award numbers DP190101258 (shared with R.M.C.) and FT180100375. The work of S.A. was supported by MEXT KAKENHI grant numbers JP20H05850 and JP20H05861. The work of S.H. is supported by the US Department of Energy Office of Science under award number DE-SC0020262 and NSF grant numbers AST-1908960 and PHY-1914409 and by the Japan Society for the Promotion of Science KAKENHI grant number JP22K03630. The work of D.S. is supported by the US Department of Energy Office of Science under award number DE-SC0020262. T.V. and A.R.D. acknowledge the support of the Australian Research Council’s Centre of Excellence for Dark Matter Particle Physics (CDM) CE200100008. A.J.R. acknowledges support from the Australian Government through the Australian Research Council under award number FT170100243. R.M.C. thanks E. Berkhuijsen, R. Beck, R. Ekers, M. Roth and T. Siegert for useful communications.
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R.M.C. initiated the project and led the spectral analysis and theoretical interpretation. O.M constructed the astrophysical templates, designed the analysis pipeline and performed the data analysis of the γ-ray observations. D.M., M.R.K., S.A., S.H., M.G.B, C.G., F.A., J.A.H., D.S., and A.J.R. provided theoretical insights and interpretation and gave advice about statistical analysis. T.V. and A.R.D. provided insights on the expected distribution of dark matter. R-Z.Y. performed an initial γ-ray data analysis. M.D.F helped with radio data. The main text was written by R.M.C., M.R.K. and O.M., and the Methods was written by O.M., R.M.C. and M.R.K. All authors were involved in the interpretation of the results and reviewed the manuscript.
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Extended data
Extended Data Fig. 1 The stellar density templates for the Sgr dSph used in this study.
Each map has been normalized, so the units are arbitrary; the color scale is logarithmic. Morphological differences among the templates are due to different stellar candidates (red clump or RR Lyrae), search algorithms, and search target (the dwarf remnant or the stream). Data sources are as follows: Model I, ref. 8; Model II, ref. 39; Model III, ref. 40; Model IV and Model V, ref. 41. Detailed descriptions of these templates are given in the S.I. sec. 2.
Extended Data Fig. 2 Goodness of fit computation for the best-fitting baseline + Sgr dSph model.
These use our preferred set of templates (first entry in Table 1). In each of the 15 panels, one for each of the energy bins in our analysis pipeline, the blue histograms show the distribution of - ln L values produced in 100 Monte Carlo trials where we use our pipeline to fit a mock data set produced by drawing photons from the same set of templates used in the fit; orange dashed vertical lines show the 68% confidence range of this distribution, and black dashed vertical lines show the mean. Under the hypothesis that our best-fitting model for the real Fermi observations is a true representation of the data, and that disagreements between the model and the data are solely the result of photon counting statistics, the log-likelihood values for our best-fitting model should be drawn from the distributions shown by the blue histograms. For comparison, the red vertical line shows the actual measured log likelihoods for our best fit. The fact that these measured values are well within the range spanned by the Monte Carlo trials indicates that we cannot rule out this hypothesis, indicating that our model is as good a fit to the data as could be expected given the finite number of photons that Fermi has observed.
Extended Data Fig. 3 Measured photon counts (left), best-fit baseline + Sgr dSph model (middle), and the fractional residuals (Data - Model)/Model (right).
The images were constructed by summing the corresponding energy bins over the energy ranges displayed on top of each panel: [0.5, 1.0] GeV, [1.0, 4.0] GeV, [4.0, 15.8] GeV, from top to bottom. The maps have been smoothed with Gaussian filters of radii 1. 0∘, 0. 8∘, and 0. 5∘ for each energy range displayed, respectively (where these angular scales are determined by the Fermi-LAT point spread function at the low-edge of the energy interval for the former two, while the latter is determined by the angular resolution of the gas maps). The spectrum of baseline + Sgr dSph model components shown here can be seen in Fig. ??. The 4FGL30 γ-ray point sources included in the baseline model are represented by the red circles.
Extended Data Fig. 4 Results from our template mismatch tests.
Each of the coloured lines shows the results of a test where we generate synthetic data with one set of templates, and attempt to recover the Sgr dSph in those data using a different set. In the upper two panels, the horizontal axis shows the true, energy-integrated Sgr dSph photon flux in the synthetic data, while the vertical axis shows the value (with 1σ statistical error bars) retrieved by our pipeline; the black dashed lines indicate perfect recovery of the input, and the vertical bands show the photon flux we measure for the Sgr dSph in the real Fermi data. In the bottom two panels we plot the recovered energy flux in each energy bin (with 1σ statistical error bars), for the case where the injected photon flux most closely matches the real Sgr dSph flux; the black dashed line again shows perfect recovery of the injected signal. The left panels show experiments where we mismatch the Galactic hadronic and IC templates, while the right panels show experiments where we mismatch the FB templates; see Methods for details.
Extended Data Fig. 5 Results of our rotation and translation tests.
Left: change in TS when repeating the analysis using the default baseline + Sgr dSph model, but with the Sgr dSph rotated about its centre by the indicated angle (blue points); TS values > 0 indicate an improved fit (dashed grey line), with TS = 46.1 corresponding to a 5σ -significant improvement (red dashed line). Centre: same as the left panel, but for tests with the Sgr dSph template rotated about the Milky Way centre, rather than its own centre. Right: tests for translation of the Sgr dSph template. The true position of the Sgr dSph centre is the center of the plot, and the colour in each pixel indicates the change in TS if we displace the Sgr dSph centre to the indicated position; the maximum shown, at a displacement Δb ≈ − 4∘, has TS = 40.8, corresponding to 4.5σ significance. For comparison, white contours show the original, unshifted Sgr dSph template, and the green arrow shows the direction anti-parallel to the Sgr dSph’s proper motion, back along its past trajectory; red arrows show the projection of the green arrow in the ‘ and b directions.
Extended Data Fig. 6 Sgr dSph spectra derived from template analysis using different Galactic diffuse emission models.
In all cases the spectrum shown is the flux averaged over the entire ROI, not the flux within the footprint of the Sgr dSph template. The fiducial model is our default choice (first entry in Table 1), while other lines correspond to alternate foregrounds - models 2D A (red), 2D B (black), and 2D C (blue) for the Galactic IC foreground, and models Interpolated (dark green) and GALPROP 3D-gas (light green) for the Galactic hadronic + bremsstrahlung foreground. The error bars display 1σ statistical errors. See Table 1 and text for details.
Extended Data Fig. 7 Contribution of each template component to the γ-ray spectrum averaged over the entire ROI, for our default baseline + Sgr dSph model.
Components shown are as follows: π0 + brems is the Galactic hadronic plus bremsstrahlung foreground, ICS is the Galactic inverse Compton foreground, 4FGL indicates point sources from the 4th Fermi catalogue, Fermi Bubbles indicates the structured Fermi Bubble template, isotropic is the isotropic γ-ray background, ‘other’ includes the Sun and Moon, Loop I, and the Galactic Centre Excess, and Sgr stream indicates the Sgr dSph. The error bars display 1σ statistical errors.
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Crocker, R.M., Macias, O., Mackey, D. et al. Gamma-ray emission from the Sagittarius dwarf spheroidal galaxy due to millisecond pulsars. Nat Astron 6, 1317–1324 (2022). https://doi.org/10.1038/s41550-022-01777-x
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DOI: https://doi.org/10.1038/s41550-022-01777-x
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