pith. sign in

arxiv: 2603.24741 · v2 · submitted 2026-03-25 · 🌌 astro-ph.HE · astro-ph.GA

The diffuse gamma-ray sky of a Milky Way analogue: Local diversity and global constraints

Karin Kjellgren , Philipp Girichidis , Maria Werhahn , Ralf S. Klessen , Christoph Pfrommer , Juan Soler , Brian Reville , Jim Hinton
show 3 more authors
Patrick Hennebelle No\'e Brucy Simon C. O. Glover
This is my paper

Pith reviewed 2026-05-15 00:03 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GA
keywords gamma-ray emissioncosmic raysMilky Way analoguepion decayangular power spectrumdiffusion coefficientFermi-LATMHD simulation
0
0 comments X

The pith

A simulation of a Milky Way analogue reproduces observed gamma-ray luminosities and spectra without parameter tuning.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper employs cosmic-ray magnetohydrodynamic simulations to model a Milky Way-like galaxy and calculates its diffuse gamma-ray emission from pion decay in post-processing. This approach reveals that the simulated luminosities and spectral slopes align closely with Milky Way observations for various observer positions inside the galaxy. The morphology varies with local gas distributions, while the angular power spectrum consistently follows gas column density. A specific diffusion scaling of energy to the power 0.5 best matches the Fermi-LAT data, indicating that such simulations can capture essential aspects of galactic gamma-ray emission naturally.

Core claim

The simulated galaxy reproduces Milky Way-like gamma-ray luminosities and spectral slopes without parameter tuning. Comparisons with Fermi-LAT data show good agreement in both the all-sky spectrum and APS, with a diffusion coefficient scaling proportional to E^0.5 providing the best match. These results show that key features of Galactic gamma-ray emission arise naturally in self-consistent CR-MHD simulations, with gas density fluctuations primarily shaping emission morphology and CR transport governing spectral and structural properties.

What carries the argument

Post-processing computation of steady-state pion-decay gamma-ray emission from CR-MHD simulations of a Milky Way analogue galaxy.

If this is right

  • Total gamma-ray luminosity remains relatively stable across different observer locations.
  • The morphology of the gamma-ray sky varies strongly with local gas distribution.
  • The angular power spectrum traces gas column density rather than the smoother cosmic-ray energy density.
  • Key features of the Galactic gamma-ray emission arise naturally without parameter tuning.
  • Gas density fluctuations shape the emission morphology while cosmic-ray transport governs the spectral properties.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • This framework suggests that observations of gamma rays from other galaxies should account for local environmental variations to avoid misinterpreting transport properties.
  • Energy-dependent measurements of the angular power spectrum could further constrain the diffusion scaling in future studies.
  • The simulations could be used to predict how gamma-ray emission changes in galaxies with different masses or star formation histories.
  • If the steady-state assumption holds, it simplifies modeling but may miss time-variable effects in active regions.

Load-bearing premise

The scaling of the cosmic-ray diffusion coefficient with energy is chosen to match Fermi data rather than being derived from first principles in the simulation.

What would settle it

A measurement showing that the Milky Way's gamma-ray spectrum or angular power spectrum deviates from the predictions under an E^0.5 diffusion scaling would disprove the claimed agreement.

Figures

Figures reproduced from arXiv: 2603.24741 by Brian Reville, Christoph Pfrommer, Jim Hinton, Juan Soler, Karin Kjellgren, Maria Werhahn, No\'e Brucy, Patrick Hennebelle, Philipp Girichidis, Ralf S. Klessen, Simon C. O. Glover.

Figure 1
Figure 1. Figure 1: Face-on and edge-on views of our simulation CRMHD at t = 1.50 Gyr. From left to right: Column density, a slice through the midplane of the CR energy density, and the projected gamma-ray emissivity from pion decay. Almost all of the mass is located in the galactic midplane. CR-driven outflows push gas out into the CGM, but of significantly lower column densities than the disk. The CRs diffuse out of the gal… view at source ↗
Figure 4
Figure 4. Figure 4: Comparison of the vertical scale height in our simulation com￾pared to Milky Way observations. The solid lines show the scale height of the simulation at t = 1.92 Gyr, calculated as 75% of the gas mass within a certain radial bin, in the cold (T < 5050 K) and warm (5050 K < T < 2 × 104 K) phase. All other data points are based on observations of the Milky Way: L06 = Levine et al. (2006), K&D08 = Kalberla &… view at source ↗
Figure 3
Figure 3. Figure 3: Estimates of the luminosity spectrum from neutral pion decay of the Milky Way from two different propagation models (dotted and dashed lines) (see [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: All-sky gamma-ray emission for different observers at the same moment in time (t = 1.92 Gyr). The left panel shows a slice through the midplane of the gas density with the positions of the observers marked in red. The right panels show Mollweide projections of the gamma-ray emission from pion decay in the energy range 0.56–1.0 GeV. of Strong et al. (2010) particularly well (see [PITH_FULL_IMAGE:figures/fu… view at source ↗
Figure 6
Figure 6. Figure 6: Histogram of the circularized bubble radii of 18 bubbles selected from one snapshot in our simulation, all from within 2.5 kpc of the solar circle. The dashed line shows the radius of the Local Bubble. 2008), the scale height in our simulation is well in line with ob￾servational estimates. 4. Variations in the gamma-ray sky and the role of local emission The left panel of [PITH_FULL_IMAGE:figures/full_fig… view at source ↗
Figure 7
Figure 7. Figure 7: Left panel: For bubble 6 in [PITH_FULL_IMAGE:figures/full_fig_p007_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Top: Distance within which 90% of the gamma-ray emission originates, as a function of galactic latitude, for a selection of 18 bubbles in one snapshot of our simulation. The black solid line shows the median evolution, and the shaded region marks the 25th and 75th percentiles. Bottom: Sky covering fraction of regions dominated by emission from different distances, in 1 kpc bins. ble (Zucker et al. 2022). T… view at source ↗
Figure 9
Figure 9. Figure 9: APS of the gamma-ray emission, column density, and projected CR energy as a function of multipoles ℓ. The solid lines are medians of several bubbles, the shaded regions are the 25th and 75th percentiles. The saw-tooth pattern, visible in the density and gamma-ray emission, are an imprint of the galactic disk, since it is a large-scale anisotropic feature that is more dominant in the even multipoles due to … view at source ↗
Figure 11
Figure 11. Figure 11: Comparison of gamma-ray fluxes to observations in different regions of the sky, for bubble 6 in [PITH_FULL_IMAGE:figures/full_fig_p009_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Comparison of the diffuse gamma-ray emission between our simulations (upper panels) and observations (lower panels) by Fermi-LAT (Scheel-Platz et al. 2023), in three different energy bands: 0.56-1.0 GeV (left), 10-17.8 GeV (middle), and 178-316 GeV (right). The top row shows the gamma-ray sky for the same bubble as in [PITH_FULL_IMAGE:figures/full_fig_p011_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: APS of the maps shown in [PITH_FULL_IMAGE:figures/full_fig_p011_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Histogram of the cell sizes of all the cells within 2 kpc of an ob￾server, averaged over 21 different bubbles and weighted by the gamma￾ray luminosity. In dark blue are cells with latitudes |b| < 20◦ , and in light blue cells with |b| > 20◦ . 7. Discussion 7.1. CR transport details The choice of CR transport parameters has a clear impact on the resulting gamma-ray spectrum. Our simulations assume one cons… view at source ↗
read the original abstract

Diffuse gamma-ray emission is a key tracer of cosmic rays (CRs) in galaxies, encoding information about their transport, energetics, and interactions with the interstellar medium. Interpreting the Milky Way gamma-ray sky is challenging because the observed emission depends on the three-dimensional distributions of CRs and gas, as well as the observer location within the Galaxy. Using the Rhea suite of CR-MHD simulations of a Milky Way analogue, we study how pion-decay gamma-ray emission varies with galactic environment, local conditions, and CR transport physics. Emission is computed in post-processing under steady-state assumptions, enabling analysis of luminosities, spectra, full-sky maps, and angular power spectra (APS) for multiple observer positions, including those inside Local-Bubble-like cavities. The simulated galaxy reproduces Milky Way-like gamma-ray luminosities and spectral slopes without parameter tuning. While total luminosity is relatively stable, the morphology of the gamma-ray sky varies strongly with observer location due to the complex local gas distribution, consistent with observations. For all observers, the APS traces gas column density rather than the smoother CR energy density, in agreement with previous studies. Comparisons with Fermi-LAT data show good agreement in both the all-sky spectrum and APS, with a diffusion coefficient scaling proportional to E^0.5 providing the best match. These results show that key features of Galactic gamma-ray emission arise naturally in self-consistent CR-MHD simulations. Gas density fluctuations primarily shape emission morphology, while CR transport governs spectral and structural properties. The Rhea simulations provide a physically grounded framework for interpreting diffuse gamma-ray observations and highlight the importance of local environment in tracing Galactic CR physics.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper presents results from the Rhea suite of CR-MHD simulations of a Milky Way analogue galaxy. Diffuse pion-decay gamma-ray emission is computed in post-processing under steady-state assumptions for multiple observer positions. The central claims are that the simulation reproduces Milky Way-like gamma-ray luminosities and spectral slopes without parameter tuning, that the all-sky spectrum and angular power spectra (APS) agree well with Fermi-LAT data when a diffusion coefficient scaling ∝ E^{0.5} is adopted, that emission morphology varies strongly with local gas distribution, and that APS traces gas column density rather than CR energy density.

Significance. If the results hold after addressing the parameter choice, the work supplies a self-consistent CR-MHD framework for interpreting Galactic diffuse gamma-ray observations. It demonstrates that luminosities, spectral slopes, and APS-gas correlations emerge naturally from the simulations and match external Fermi data, while quantifying the impact of observer location inside Local-Bubble-like cavities. These elements provide a physically grounded basis for constraining CR transport and local ISM effects.

major comments (2)
  1. [Abstract] Abstract: The assertion that the simulated galaxy reproduces Milky Way-like gamma-ray luminosities and spectral slopes 'without parameter tuning' is contradicted by the post-processing procedure in which the diffusion coefficient energy scaling index is varied and selected (∝ E^{0.5}) to give the best match to Fermi-LAT all-sky spectrum and APS. Because this index is chosen after comparison to data rather than predicted from the fixed MHD run, the reported agreement is conditional on that choice and does not emerge parameter-free.
  2. [Post-processing section (methods)] Post-processing section (methods): The steady-state assumption used to compute gamma-ray emissivity from the time-dependent CR-MHD fields is load-bearing for the luminosity and spectral comparisons; the paper should quantify the error introduced by this approximation (e.g., via comparison to a time-dependent solution or an estimate of CR variability timescales) or demonstrate that it does not affect the claimed agreement with Fermi-LAT data.
minor comments (1)
  1. [Abstract and §4] Abstract and §4: The distinction between parameters fixed in the MHD evolution and those adjusted only in post-processing should be stated more explicitly to avoid reader confusion about the 'no tuning' claim.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed report. We address each major comment below and have revised the manuscript to improve clarity and address the concerns. The core scientific results on morphology, APS-gas correlations, and observer-position effects remain unchanged.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The assertion that the simulated galaxy reproduces Milky Way-like gamma-ray luminosities and spectral slopes 'without parameter tuning' is contradicted by the post-processing procedure in which the diffusion coefficient energy scaling index is varied and selected (∝ E^{0.5}) to give the best match to Fermi-LAT all-sky spectrum and APS. Because this index is chosen after comparison to data rather than predicted from the fixed MHD run, the reported agreement is conditional on that choice and does not emerge parameter-free.

    Authors: We agree that the diffusion scaling index was selected after comparing several values to the Fermi-LAT spectrum and APS. The CR-MHD simulation itself was not tuned to gamma-ray data, but the post-processing transport parameter was calibrated for best match. We have revised the abstract and methods to remove the unqualified phrase 'without parameter tuning' and instead state that the MHD and CR source parameters were not tuned to gamma-ray observations, while the diffusion index was chosen to optimize agreement with data. The morphology and APS results are robust across the explored range of indices. revision: yes

  2. Referee: [Post-processing section (methods)] Post-processing section (methods): The steady-state assumption used to compute gamma-ray emissivity from the time-dependent CR-MHD fields is load-bearing for the luminosity and spectral comparisons; the paper should quantify the error introduced by this approximation (e.g., via comparison to a time-dependent solution or an estimate of CR variability timescales) or demonstrate that it does not affect the claimed agreement with Fermi-LAT data.

    Authors: We acknowledge that the steady-state assumption requires justification. In the revised methods section we now include an estimate of CR variability timescales extracted directly from the time-dependent simulation outputs, showing that fractional changes in CR energy density between snapshots are small relative to the local diffusion and advection timescales. We argue that this supports the approximation for the integrated luminosities and spectra presented, and we note that a full time-dependent gamma-ray post-processing would be a substantial extension beyond the current scope. The agreement with Fermi-LAT data is presented as conditional on this approximation. revision: yes

Circularity Check

1 steps flagged

Diffusion scaling ∝ E^0.5 selected post hoc to match Fermi-LAT undercuts 'no parameter tuning' claim

specific steps
  1. fitted input called prediction [Abstract]
    "The simulated galaxy reproduces Milky Way-like gamma-ray luminosities and spectral slopes without parameter tuning. ... Comparisons with Fermi-LAT data show good agreement in both the all-sky spectrum and APS, with a diffusion coefficient scaling proportional to E^0.5 providing the best match."

    Emission is computed in post-processing; the diffusion scaling index is explicitly varied and selected to optimize agreement with Fermi-LAT observations. The 'best match' therefore follows by construction from the fitting step rather than emerging parameter-free from the underlying simulation physics.

full rationale

The paper asserts that the Rhea CR-MHD simulation reproduces Milky Way-like gamma-ray luminosities and spectral slopes without parameter tuning. However, the diffusion coefficient scaling is varied in post-processing and chosen specifically as the value (∝ E^0.5) that provides the best match to the Fermi-LAT all-sky spectrum and APS. This reduces the reported agreement to a fitted outcome rather than an untuned, first-principles prediction from the fixed MHD run. The core morphology and luminosity claims remain independent, but the spectral match is statistically forced by the selection process.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

Model rests on standard CR-MHD equations plus one fitted diffusion index; no new particles or forces are introduced.

free parameters (1)
  • diffusion coefficient energy scaling index = 0.5
    Set to 0.5 to achieve best match to Fermi-LAT spectrum and APS
axioms (2)
  • domain assumption Steady-state CR distribution and gamma-ray emissivity in post-processing
    Invoked to compute emission maps from simulation snapshots without evolving CRs further
  • standard math Pion-decay dominance for diffuse gamma-ray production
    Standard assumption in galactic CR gamma-ray modeling

pith-pipeline@v0.9.0 · 5648 in / 1442 out tokens · 58539 ms · 2026-05-15T00:03:19.580883+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

96 extracted references · 96 canonical work pages · 1 internal anchor

  1. [1]

    Abazajian, K. N. 2011, J. Cosmology Astropart. Phys., 2011, 010

    work page 2011

  2. [2]

    Abazajian, K. N. & Kaplinghat, M. 2012, Phys. Rev. D, 86, 083511

    work page 2012

  3. [3]

    2016, ApJS, 223, 26

    Acero, F., Ackermann, M., Ajello, M., et al. 2016, ApJS, 223, 26

    work page 2016

  4. [4]

    2015, ApJ, 799, 86

    Ackermann, M., Ajello, M., Albert, A., et al. 2015, ApJ, 799, 86

    work page 2015

  5. [5]

    2017, ApJ, 840, 43

    Ackermann, M., Ajello, M., Albert, A., et al. 2017, ApJ, 840, 43

    work page 2017

  6. [6]

    2012, ApJ, 755, 164

    Ackermann, M., Ajello, M., Allafort, A., et al. 2012, ApJ, 755, 164

    work page 2012

  7. [7]

    S., & Garrappa, S

    Ajello, M., Di Mauro, M., Paliya, V . S., & Garrappa, S. 2020, ApJ, 894, 88

    work page 2020

  8. [8]

    2021, Phys

    Amenomori, M., Bao, Y ., Bi, X., et al. 2021, Phys. Rev. Lett., 126, 141101

    work page 2021

  9. [9]

    C., & Jiang, Y .-F

    Armillotta, L., Ostriker, E. C., & Jiang, Y .-F. 2022, ApJ, 929, 170

    work page 2022

  10. [10]

    2019, A&A, 632, A127

    Bacchini, C., Fraternali, F., Pezzulli, G., et al. 2019, A&A, 632, A127

    work page 2019

  11. [11]

    J., et al

    Bartoli, B., Bernardini, P., Bi, X. J., et al. 2015, ApJ, 806, 20

    work page 2015

  12. [12]

    F., Barbareschi, L., Caraveo, P

    Bignami, G. F., Barbareschi, L., Caraveo, P. A., et al. 1981, in International Cos- mic Ray Conference, V ol. 1, International Cosmic Ray Conference, 182–185

    work page 1981

  13. [13]

    F., Fichtel, C

    Bignami, G. F., Fichtel, C. E., Kniffen, D. A., & Thompson, D. J. 1975, ApJ, 199, 54

    work page 1975

  14. [14]

    & Cox, D

    Boulares, A. & Cox, D. P. 1990, ApJ, 365, 544

    work page 1990

  15. [15]

    Buck, T., Pfrommer, C., Pakmor, R., Grand, R. J. J., & Springel, V . 2020, MN- RAS, 497, 1712

    work page 2020

  16. [16]

    2023, Phys

    Cao, Z., Aharonian, F., An, Q., et al. 2023, Phys. Rev. Lett., 131, 151001

    work page 2023

  17. [17]

    2015, ApJ, 806, 240

    Casandjian, J.-M. 2015, ApJ, 806, 240

    work page 2015

  18. [18]

    S., Ruszkowski, M., Werhahn, M., & Pfrommer, C

    Chiu, H.-H. S., Ruszkowski, M., Werhahn, M., & Pfrommer, C. 2024, ApJ, 976, 136

    work page 2024

  19. [19]

    & Povich, M

    Chomiuk, L. & Povich, M. S. 2011, AJ, 142, 197

    work page 2011

  20. [20]

    C., Glover, S

    Clark, P. C., Glover, S. C. O., Ragan, S. E., & Duarte-Cabral, A. 2019, MNRAS, 486, 4622

    work page 2019

  21. [21]

    Cox, D. P. & Reynolds, R. J. 1987, ARA&A, 25, 303

    work page 1987

  22. [22]

    & Dubois, Y

    Dashyan, G. & Dubois, Y . 2020, A&A, 638, A123

    work page 2020

  23. [23]

    P., Hooper, D., et al

    Daylan, T., Finkbeiner, D. P., Hooper, D., et al. 2016, Physics of the Dark Uni- verse, 12, 1 Dörner, J., Hellrung, J., Becker Tjus, J., & Fichtner, H. 2025, in 39th Interna- tional Cosmic Ray Conference, 634

    work page 2016

  24. [24]

    Dundovic, A., Pezzi, O., Blasi, P., Evoli, C., & Matthaeus, W. H. 2020, Phys. Rev. D, 102, 103016

    work page 2020

  25. [25]

    2022, ApJ, 941, 162

    Elia, D., Molinari, S., Schisano, E., et al. 2022, ApJ, 941, 162

    work page 2022

  26. [26]

    2020, Phys

    Evoli, C., Morlino, G., Blasi, P., & Aloisio, R. 2020, Phys. Rev. D, 101, 023013

    work page 2020

  27. [27]

    K., & Zweibel, E

    Farber, R., Ruszkowski, M., Yang, H.-Y . K., & Zweibel, E. G. 2018, ApJ, 856, 112

    work page 2018

  28. [28]

    2018, MNRAS, 479, 3042

    Girichidis, P., Naab, T., Hanasz, M., & Walch, S. 2018, MNRAS, 479, 3042

    work page 2018

  29. [29]

    2016, ApJ, 816, L19

    Girichidis, P., Naab, T., Walch, S., et al. 2016, ApJ, 816, L19

    work page 2016

  30. [30]

    2020, MNRAS, 491, 993

    Girichidis, P., Pfrommer, C., Hanasz, M., & Naab, T. 2020, MNRAS, 491, 993

    work page 2020

  31. [31]

    2022, MNRAS, 510, 3917

    Girichidis, P., Pfrommer, C., Pakmor, R., & Springel, V . 2022, MNRAS, 510, 3917

    work page 2022

  32. [32]

    2024, MNRAS, 527, 10897

    Girichidis, P., Werhahn, M., Pfrommer, C., Pakmor, R., & Springel, V . 2024, MNRAS, 527, 10897

    work page 2024

  33. [33]

    Glover, S. C. O. & Clark, P. C. 2012, MNRAS, 421, 116

    work page 2012

  34. [34]

    Glover, S. C. O., Federrath, C., Mac Low, M.-M., & Klessen, R. S. 2010, MN- RAS, 404, 2 Göller, J., Girichidis, P., Brucy, N., et al. 2025, A&A, 704, A331

    work page 2010

  35. [35]

    M., Hivon, E., Banday, A

    Gorski, K. M., Hivon, E., Banday, A. J., et al. 2005, ApJ, 622, 759

    work page 2005

  36. [36]

    A., Black, J

    Grenier, I. A., Black, J. H., & Strong, A. W. 2015, ARA&A, 53, 199

    work page 2015

  37. [37]

    2013, ApJ, 777, L38

    Hanasz, M., Lesch, H., Naab, T., et al. 2013, ApJ, 777, L38

    work page 2013

  38. [38]

    W., & Girichidis, P

    Hanasz, M., Strong, A. W., & Girichidis, P. 2021, Living Reviews in Computa- tional Astrophysics, 7, 2

    work page 2021

  39. [39]

    Huang, X., Enßlin, T., & Selig, M. 2016, J. Cosmology Astropart. Phys., 2016, 030

    work page 2016

  40. [40]

    H., Sormani, M

    Hunter, G. H., Sormani, M. C., Beckmann, J. P., et al. 2024, A&A, 692, A216

    work page 2024

  41. [41]

    M., Springel, V ., & Pfrommer, C

    Jacob, S., Pakmor, R., Simpson, C. M., Springel, V ., & Pfrommer, C. 2018, MN- RAS, 475, 570

    work page 2018

  42. [42]

    M., & Vila, G

    Kafexhiu, E., Aharonian, F., Taylor, A. M., & Vila, G. S. 2014, Phys. Rev. D, 90, 123014

    work page 2014

  43. [43]

    Kalberla, P. M. W. & Dedes, L. 2008, A&A, 487, 951

    work page 2008

  44. [44]

    Kennicutt, R. C. & Evans, N. J. 2012, ARA&A, 50, 531

    work page 2012

  45. [45]

    & Ostriker, E

    Kim, C.-G. & Ostriker, E. C. 2018, ApJ, 853, 173

    work page 2018

  46. [46]

    2025, A&A, 700, A124

    Kjellgren, K., Girichidis, P., Göller, J., et al. 2025, A&A, 700, A124

    work page 2025

  47. [47]

    J., del Palacio, S., et al

    Kornecki, P., Pellizza, L. J., del Palacio, S., et al. 2020, A&A, 641, A147

    work page 2020

  48. [48]

    Lacki, B. C. & Thompson, T. A. 2013, ApJ, 762, 29

    work page 2013

  49. [49]

    C., Thompson, T

    Lacki, B. C., Thompson, T. A., Quataert, E., Loeb, A., & Waxman, E. 2011, ApJ, 734, 107

    work page 2011

  50. [50]

    & Paul, J

    Lebrun, F. & Paul, J. A. 1978, A&A, 65, 187

    work page 1978

  51. [51]

    S., Blitz, L., & Heiles, C

    Levine, E. S., Blitz, L., & Heiles, C. 2006, ApJ, 643, 881

    work page 2006

  52. [52]

    Licquia, T. C. & Newman, J. A. 2015, ApJ, 806, 96

    work page 2015

  53. [53]

    2019, MNRAS, 486, 1094

    Mackey, J., Walch, S., Seifried, D., et al. 2019, MNRAS, 486, 1094

    work page 2019

  54. [54]

    M., & Oosterloo, T

    Marasco, A., Fraternali, F., Van Der Hulst, J. M., & Oosterloo, T. 2017, A&A, 607, A106

    work page 2017

  55. [55]

    2014, A&A, 564, A61

    Martin, P. 2014, A&A, 564, A61

    work page 2014

  56. [56]

    2010, A&A, 516, A67

    Maurin, D., Putze, A., & Derome, L. 2010, A&A, 516, A67

    work page 2010

  57. [57]

    M., Stanimirovi´c, S., & Rybarczyk, D

    McClure-Griffiths, N. M., Stanimirovi´c, S., & Rybarczyk, D. R. 2023, ARA&A, 61, 19 O’Neill, T. J., Zucker, C., Goodman, A. A., & Edenhofer, G. 2024, ApJ, 973, 136

    work page 2023

  58. [58]

    V ., Galli, D., et al

    Padovani, M., Ivlev, A. V ., Galli, D., et al. 2020, Space Sci. Rev., 216, 29

    work page 2020

  59. [59]

    2018, MNRAS, 478, 5278

    Pais, M., Pfrommer, C., Ehlert, K., & Pakmor, R. 2018, MNRAS, 478, 5278

    work page 2018

  60. [60]

    Paul, J., Casse, M., & Cesarsky, C. J. 1976, ApJ, 207, 62

    work page 1976

  61. [61]

    2021, MNRAS, 508, 4269

    Peschken, N., Hanasz, M., Naab, T., Wólta ´nski, D., & Gawryszczak, A. 2021, MNRAS, 508, 4269

    work page 2021

  62. [62]

    L., Wright, N

    Quintana, A. L., Wright, N. J., & Martínez García, J. 2025, MNRAS, 538, 1367

    work page 2025

  63. [63]

    2021, MNRAS, 504, 1039 Article number, page 13 of 16 A&A proofs:manuscript no

    Rathjen, T.-E., Naab, T., Girichidis, P., et al. 2021, MNRAS, 504, 1039 Article number, page 13 of 16 A&A proofs:manuscript no. aa58922-26corr

    work page 2021

  64. [64]

    A., Marshall, D

    Remy, Q., Grenier, I. A., Marshall, D. J., & Casandjian, J. M. 2017, A&A, 601, A78

    work page 2017

  65. [65]

    X., Remy, Q., Ravikularaman, S., et al

    Ren, H. X., Remy, Q., Ravikularaman, S., et al. 2025, A&A, 697, A42 Rodríguez Montero, F., Martin-Alvarez, S., Slyz, A., et al. 2024, MNRAS, 530, 3617

    work page 2025

  66. [66]

    & Araya, M

    Rojas-Bravo, C. & Araya, M. 2016, MNRAS, 463, 1068–1073

    work page 2016

  67. [67]

    & Pfrommer, C

    Ruszkowski, M. & Pfrommer, C. 2023, A&A Rev., 31, 4

    work page 2023

  68. [68]

    S., Hopkins, P

    Sands, I. S., Hopkins, P. F., Ponnada, S. B., et al. 2025, submitted to Phys. Rev. D, arXiv:2509.18351

    work page arXiv 2025

  69. [69]

    I., Knollmüller, J., Arras, P., et al

    Scheel-Platz, L. I., Knollmüller, J., Arras, P., et al. 2023, A&A, 680, A2

    work page 2023

  70. [70]

    Selig, M., Vacca, V ., Oppermann, N., & Enßlin, T. A. 2015, A&A, 581, A126

    work page 2015

  71. [71]

    2010, ApJ, 725, 2117

    Shalchi, A., Büsching, I., Lazarian, A., & Schlickeiser, R. 2010, ApJ, 725, 2117

    work page 2010

  72. [72]

    2025, ApJ, 987, 204

    Sike, B., Thomas, T., Ruszkowski, M., Pfrommer, C., & Weber, M. 2025, ApJ, 987, 204

    work page 2025

  73. [73]

    M., Pakmor, R., Marinacci, F., et al

    Simpson, C. M., Pakmor, R., Marinacci, F., et al. 2016, ApJ, 827, L29

    work page 2016

  74. [74]

    M., Pakmor, R., Pfrommer, C., Glover, S

    Simpson, C. M., Pakmor, R., Pfrommer, C., Glover, S. C. O., & Smith, R. 2023, MNRAS, 520, 4621

    work page 2023

  75. [75]

    C., Treß, R

    Sormani, M. C., Treß, R. G., Klessen, R. S., & Glover, S. C. O. 2017, MNRAS, 466, 407

    work page 2017

  76. [76]

    2010, MNRAS, 401, 791

    Springel, V . 2010, MNRAS, 401, 791

    work page 2010

  77. [77]

    & Hernquist, L

    Springel, V . & Hernquist, L. 2003, MNRAS, 339, 289

    work page 2003

  78. [78]

    W., Puget, J

    Stecker, F. W., Puget, J. L., Strong, A. W., & Bredekamp, J. H. 1974, ApJ, 188, L59

    work page 1974

  79. [79]

    Strong, A. W. & Moskalenko, I. V . 1998, ApJ, 509, 212

    work page 1998

  80. [80]

    W., Porter, T

    Strong, A. W., Porter, T. A., Digel, S. W., et al. 2010, ApJ, 722, L58

    work page 2010

Showing first 80 references.