Galaxy clusters, the Universe’s largest halo structures, are filled with an X-ray-emitting gas with a temperature between 10 million and 100 million degrees. Their evolution is shaped by energetic processes such as feedback from supermassive black holes (SMBHs) and mergers with other cosmic structures1,2,3. The imprints of these processes on gas kinematics remain largely unknown, restricting our understanding of energy conversion within clusters4. High-resolution spectral mapping with the X-Ray Imaging and Spectroscopy Mission (XRISM) observatory5 offers a way forward6,7. Here we present XRISM kinematic measurements of the Perseus cluster, radially covering the extent of its cool core. We find direct evidence for at least two dominant drivers of gas motions operating on distinct physical scales: a small-scale driver in the inner approximately 60 kpc, probably associated with the SMBH feedback; and a large-scale driver in the outer core, powered by mergers. This finding suggests that, during the active phase, SMBH feedback drives gas motions, which, if fully dissipated into heat, could have a substantial role in offsetting radiative cooling losses in the Perseus core. Our study underscores the necessity of kinematic mapping observations of extended sources to robustly characterize the velocity fields and their role in the evolution of massive halos. It further offers a kinematic diagnostic for SMBH feedback models.
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Data availability
The observational data analysed during this study are available in the NASA HEASARC repository (https://heasarc.gsfc.nasa.gov/docs/xrism/). XRISM observation IDs 000154000, 000155000, 000156000, 000157000 and 000158000 were used, in addition to Chandra observation IDs 3209, 4289, 4946–4953, 6139, 6145, 6146, 11713–11716, 12025, 12033, 12036 and 12037. The atomic databases used in this study are available online at AtomDB (http://www.atomdb.org/).
Code availability
Publicly released versions of the FLASH code are available via the Flash Center for Computational Science’s website (https://flash.rochester.edu/). Our turbulent simulation set-ups used the FLASH built-in Stir unit. The base simulation code AREPO is publicly available at https://arepo-code.org/ and https://gitlab.mpcdf.mpg.de/vrs/arepo. The specific branch of AREPO used in this study includes a custom AGN implementation developed by Rainer Weinberger, as described in ref. 78. This branch is not publicly available, but access may be granted by the code developer upon reasonable request.
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Acknowledgements
This work was supported by JSPS KAKENHI grant numbers JP22H00158, JP22H01268, JP22K03624, JP23H04899, JP21K13963, JP24K00638, JP24K17105, JP21K13958, JP21H01095, JP23K20850, JP24H00253, JP21K03615, JP24K00677, JP20K14491, JP23H00151, JP19K21884, JP20H01947, JP20KK0071, JP23K20239, JP24K00672, JP24K17104, JP24K17093, JP20K04009, JP21H04493, JP20H01946, JP23K13154, JP19K14762, JP20H05857, JP23K03459 and JP25K23398. Additional support came from NASA grant numbers 80NSSC23K0650, 80NSSC20K0733, 80NSSC18K0978, 80NSSC20K0883, 80NSSC20K0737, 80NSSC24K0678, 80NSSC18K1684, 80NNSC22K1922 and 80GSFC21M0002. A.B. was supported by JSPS KAKENHI grant number JP23H01211. E.B. acknowledges support from NASA grants 80NSSC24K1148 and 80NSSC24K1774. L.C. acknowledges support from NASA grant 80NSSC25K7064. C.D. acknowledges support from STFC through grant ST/T000244/1. R.F. was supported by JSPS KAKENHI grant number JP23K03454. L.G. acknowledges financial support from the Canadian Space Agency (grant 18XARMSTMA). Y.M. was supported by JSPS KAKENHI grant number JP23K22548. M.M. acknowledges support from Yamada Science Foundation. P.P. acknowledges support from NASA grants 80NSSC18K0988 and 80NSSC23K1656 and NASA contract NAS8-0360. M.S. acknowledges the support by the RIKEN Pioneering Project Evolution of Matter in the Universe (r-EMU) and Rikkyo University Special Fund for Research (Rikkyo SFR). A.T. and the present research are in part supported by the Kagoshima University postdoctoral research programme (KU-DREAM). Y.T. was supported by the Strategic Research Center of Saitama University. S.Y. acknowledges support by the RIKEN SPDR Program. I.Z., A.H. and C.Z. acknowledge partial support from the Alfred P. Sloan Foundation through the Sloan Research Fellowship. I.Z. performed part of the work at the Kavli Institute for Theoretical Physics (KITP) supported by grant NSF PHY-2309135. C.Z. was supported by the GACR grant 21-13491X. J.H.-L. acknowledges the Canadian Space Agency (CSA) grant 22EXPXRISM. S.U. acknowledges the supports from the National Science and Technology Council of Taiwan (111-2112-M-001-026-MY3) and by Program for Forming Japan’s Peak Research Universities (J-PEAKS), respectively. T.Y. and A.T. acknowledge support by NASA under award number 80GSFC24M0006. Part of this work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was supported by the JSPS Core-to-Core Program, JPJSCCA20220002. The simulations presented in this paper were carried out using the Midway computing cluster provided by the University of Chicago Research Computing Center. The software used in this work was developed in part by the DOE NNSA and DOE Office of Science supported Flash Center for Computational Science at the University of Chicago and the University of Rochester.
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C.Z., A. Heinrich and I.Z. performed the data analysis, explored systematic uncertainties, interpreted the results and prepared the paper. C.Z. also developed controlled simulations of stratified turbulence. E. Bellomi developed the tailored AGN feedback and sloshing simulations. As the leader of the Perseus cluster target team in the XRISM Science Team, I.Z. oversaw the work on the project. F.S.P. and M.E.E. calibrated the energy scale and gain and estimated calibration uncertainties. A.O., F.M., S. Ueda, J.M. and Y. Ichinohe contributed to the Resolve data analysis. M. Markevitch, A.O., K.F., S. Kobayashi, K. Matsushita, R.M. and Y. Fukazawa contributed to resolving the AGN contribution in spectral modelling. C.K. assisted with the NXB modelling and contributed to related discussions. T. Yaqoob provided valuable insights into the XRISM mirror uncertainties. B.V. and J.H.-L. provided the SITELLE analysis of the multiphase gas. E. Bellomi, M.E.E., Y. Fujita, J.H.-L., Y. Ichinohe, M. Markevitch, K. Matsushita, B.M., F.M., A.O., N.O., F.S.P., A. Simionescu, P.C.S., N.T., S. Ueda, B.V. and J.Z. reviewed the paper and contributed to discussions. The scientific goals of XRISM were discussed and developed over 7 years by the XRISM Science Team, all members of which are authors of this paper. All the instruments were prepared by the joint efforts of the team.
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Extended data figures and tables
Extended Data Fig. 1 X-ray structures within the Perseus core and default radial binning scheme adopted for the analysis.
(a) Residual X-ray/Chandra image of the Perseus cluster in the 2−8 keV band, with arrows highlighting prominent structures relevant to our analysis. (b) The color pixels and grey circles/annuli show detector and sky regions (No. 1–6 from inner to outer), respectively, with the black dashed circle marking the innermost sky region. White contours illustrate the regions that contribute 90% photons to each pointing based on our SIXTE simulations.
Extended Data Fig. 2 Gas radial velocity profiles for varied binning schemes (a) and spatial-spectral mixing (b).
Formatting is equivalent to Fig. 2. In panel (a), black triangles correspond to the full-FOV profile (broad radial bins), red circles to the nominal profile of Fig. 2, and blue squares to the profile of Fig. 3 (narrow radial bins). In panel (b), the red circles are unchanged from Fig. 2, while blue squares/black triangles show profiles where off-axis ARFs, and therefore SSM, are increased/decreased by 30% (Supplementary Information).
Extended Data Fig. 3 Constraints on AGN parameters: photon index Γ vs. flux between 2−10 keV.
The contours indicate the implied 1, 2, 3σ parameter regimes from the two independent approaches utilizing Chandra spectra for the ICM component. Pink contours are based on the ratio of fluxes between sky regions 1/2 and 1/3 in the 4−6 keV band, which lacks strong emission lines, while blue contours are from the measurements of the equivalent width of Fe He-α line complex (Methods). For modeling the ICM in this work, we fixed the AGN flux at 31 × 10−12 erg s−1 cm−2, shown as the black point with 1σ error bars of the photon index.
Extended Data Fig. 4 XRISM/Resolve spectra from detector regions 1-3 and their best-fit models.
For each region, we show a broad-band spectrum from 3–11 keV and a detailed view of the Fe XXV He-α triplet on the right. Pink, orange, blue, and green curves represent the best-fit models of the NXB, the combined scattered ICM, the ICM, and the AGN components, respectively. The cyan curves on the right show the Fe XXV He-α w line Gaussian component, while the red curves show the total models. Residuals normalized by the statistical errors, i.e., (data-model)/error, are displayed in the lower panels with two different binning schemes: black points correspond to the binning with minimum significance \({\sigma }_{\min }=3\), while purple points show the binning with \({\sigma }_{\min }=20\).
Extended Data Fig. 5 XRISM/Resolve spectra from detector regions 4-6 and their best-fit models.
Notations are equivalent to Extended Data Fig. 4.
Extended Data Fig. 6 Statistical 1σ uncertainties for the velocity maps presented in Fig. 3.
Velocity dispersion errors are shown on the left, while the bulk velocity errors are on the right. All other notations are the same as in Fig. 3.
Extended Data Fig. 7 Effective length of the Perseus cluster.
(a) A sketch of the effective length concept in a stratified cluster atmosphere. The length along the LOS, which corresponds to the region size that contributes most to the measured flux/spectra, increases with the projected distance from the cluster center. (b) A radial profile of the normalized X-ray surface brightness in Perseus, adapted from11, is shown in black. The effective length, defined as the region size where 50% of the flux is collected, is shown with the red curve. The shaded red region indicates the scales associated with 40–60% of the flux contribution. The blue dashed curve represents the X-ray-weighted LOS length scale.
Extended Data Fig. 8 Numerical simulations of stratified turbulence with various driving scales.
(a) Projected velocity dispersion along the LOS for the simulation run with the injection scale ℓinj = 500 kpc, weighted with (left) and without (right) X-ray emissivity, (b) Same as the panel (a) but for the run with ℓinj = 50 kpc. (c) Comparisons between the simulated emissivity-weighted velocity dispersion radial profiles and the XRISM measurement (see also Fig. 2). See Methods for the description of the simulations.
Extended Data Fig. 9 Azimuthally averaged velocity dispersion centered on the cluster core from the tailored sloshing simulations compared with the XRISM observations.
Red crosses show XRISM’s LOS velocity dispersion presented in this work. The shaded regions indicate the azimuthally-averaged X-ray emissivity-weighted velocity dispersion radial profiles from the simulations including only sloshing (blue) and sloshing plus AGN jet feedback (violet). Both simulations share the same initial conditions and are shown at the same epoch. This figure is a simplified adaptation of Fig. 1 from ref. 75.
Extended Data Fig. 10 Modeled radial velocity dispersion profiles produced by propagating sound waves.
(a) Assuming conserved energy flux Fsw ( ≡ αFagn) of the sound waves starting from the cluster radius r0 powered by the central AGN (Fagn = 5 × 1044 erg s−1). (b) Assuming sound waves compensate a fraction (β) of cooling loss everywhere within the radius \({r}_{\max }\). Red points are our measured velocity dispersion, same as in Fig. 2.
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The XRISM Collaboration. Disentangling multiple gas kinematic drivers in the Perseus galaxy cluster. Nature (2026). https://doi.org/10.1038/s41586-025-10017-x
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DOI: https://doi.org/10.1038/s41586-025-10017-x


