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The evolution of cosmic ray electrons in the cosmic web: seeding by AGN, star formation and shocks

T0 review · 5 major / 5 minor · reviewed 2026-08-09 · deepseek-v4-flash

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Pith's one-line read Shocks, not galaxies, seed most relativistic electrons in the cosmic web; galaxy feedback alone also cannot explain LOFAR's residual Faraday rotation.

desk verdict Ambitious simulation suite with a genuinely new combination of CRe injection mechanisms; the quantitative shock-dominance claim needs a robustness test on x_inj. read the letter →

arxiv 2501.19041 v1 pith:GJ4HCGDV submitted 2025-01-31 astro-ph.HE astro-ph.COastro-ph.GA

F. Vazza , C. Gheller , F Zanetti , M. Tsizh , E. Carretti , S. Mtchedlidze , M. Brueggen This is my paper · ORCID
classification astro-ph.HEastro-ph.COastro-ph.GA
keywords cosmicrayelectronswebcosmologicalMHDsimulationsdiffusiveshockaccelerationAGNfeedbackstarformationFaradayrotationprimordialmagneticfields
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

Using cosmological MHD simulations that inject and advect relativistic electrons from three sources simultaneously, this paper argues that structure-formation shocks, not galaxies, set the fossil electron budget of the cosmic web. Shock-injected electrons are the most volume-filling population and dominate the energy density of fossil relativistic electrons inside halos by $z=0$. The combined seeding by shocks, AGN jets, and star-forming winds is claimed to supply more than enough seed electrons to fuel large-scale radio emission. The paper also claims that even the most extreme feedback models magnetise only a small fraction of the volume, so the residual Faraday rotation recently measured with LOFAR cannot be explained by galaxy formation alone.

What carries the argument

The argument is carried by three run-time injection modules added to a GPU-accelerated cosmological MHD code: an on-the-fly shock finder that computes Mach numbers and injects electrons with a diffusive-shock-acceleration efficiency $\xi_e(M)$ (with a low-Mach cutoff at $M_{\mathrm{thr}}=2.3$), an AGN feedback model that assigns black-hole masses from a gas-mass scaling relation and injects electrons at a fixed fraction $\xi_{\mathrm{AGN}}=10^{-3}$ of jet thermal density, and a star-formation feedback model injecting electrons at $\xi_{\mathrm{SF}}=10^{-5}$. A fourth ingredient is a 'mirror fluid' advected alongside each electron family with artificial exponential decay of timescale $\tau=0.1$ Gyr, whose ratio to the undecayed fluid recovers the time since last injection in every cell, and a precomputed library of Fokker-Planck electron spectra used to convert age, density, magnetic field, and redshift into synchrotron emission.

What would settle it

A targeted survey of residual Faraday rotation from polarised background sources at several redshifts, with the local intervening contribution removed, would decide the claim: the feedback-only models saturate near $0.1$ rad/m$^2$ out to $z\sim2$, while a primordial field with $B_{1\,\mathrm{Mpc}}=0.37$ nG reaches $1$–$3$ rad/m$^2$. A measurement at the primordial level where astrophysical contamination is demonstrably absent would support the paper's conclusion, whereas one at or below the feedback-only level would falsify its claim that galaxy formation alone cannot explain the LOFAR signal.

Watch

Extended reading notes

Core claim

The central claim is that structure-formation shocks, with Mach numbers of order a few, inject cosmic ray electrons everywhere in the cosmic web, and that this mechanism, not AGN or star formation, sets the fossil relativistic electron budget in halos. In the best-calibrated model, the number of shock-injected electrons per thermal proton inside halos is about $5.5\times10^{-4}$ for massive halos and $6.3\times10^{-4}$ for small halos at $z=0$, roughly an order of magnitude above the AGN contribution and two orders above star formation. The paper derives an approximate formula (Eqs. 5-6) giving the injected electron budget as a linear combination of the three injection efficiencies. It further claims that all astrophysical seeding combined fills at most a few tens of percent of the volume with magnetic fields above $10^{-15}$ G, and that the residual Faraday rotation observed by LOFAR rises to $1\text{--}3$ rad/m$^2$ only when a primordial field of $B_{1\,\mathrm{Mpc}}=0.37$ nG is included, so galaxy formation alone cannot explain the signal.

Load-bearing premise

The entire electron budget rests on assumed efficiency fractions for AGN jets and star-forming winds ($\xi_{\mathrm{AGN}}=10^{-3}$, $\xi_{\mathrm{SF}}=10^{-5}$), which are calibrated after the fact to reproduce observed radio luminosity functions; if real acceleration is much less efficient, the claim that combined seeding is 'more than enough' weakens.

Editorial extensions

If this is right

  • Radio emission from cluster outskirts and filaments should be powered mostly by pre-existing fossil electrons re-energised by weak shocks or turbulence rather than by freshly accelerated thermal electrons.
  • The total number of relic electrons per proton in a halo is a linear combination of the three injection efficiencies (Eqs. 5-6), so future work only needs to pin down those efficiencies to predict the seed population.
  • If the LOFAR residual Faraday rotation is real, an astrophysical-only explanation is excluded at the simulated level, and a primordial magnetic field of order $0.37$ nG on megaparsec scales is required.
  • Deep radio surveys should see a nearly connected, faint synchrotron web from shock-seeded electrons, with the strongest connection when a primordial field supplies the magnetisation.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Because the budget formula is linear in the three efficiencies, a natural test is to plug efficiencies measured from higher-resolution or kinetic-plasma simulations into Eqs. 5-6 and see whether the predicted seed populations shift by less than the model-to-model scatter.
  • If the fossil reservoir is as large as claimed, faint diffuse radio emission from old shock electrons should be present even in regions with no currently visible shock; existing stacking limits are close to this predicted level.
  • The same age-tracking machinery could be applied to cross-correlate predicted synchrotron emission with thermal Sunyaev-Zeldovich maps, which would isolate the shock-seeded component from galactic confusion without extra spectral-ageing assumptions.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 5 minor

Summary. This paper presents a new suite of ENZO MHD cosmological simulations (42.5 Mpc box, 1024^3 cells) that simultaneously track, at run time, the injection and advection of cosmic-ray electrons (CRe) from three mechanisms: structure-formation shocks, AGN feedback, and star-formation feedback, together with magnetic-field injection from the latter two. A mirror-fluid technique is used to estimate the age of CRe since last injection, and post-processing with pre-tabulated ROGER spectra converts the CRe fields into synchrotron and Faraday-rotation predictions. The sub-grid galaxy-formation models are calibrated against the cosmic star formation history, stellar mass functions, and AGN radio luminosity functions, with run B4 identified as the best overall. The main claims are that shocks dominate the volume-filling and halo budget of fossil CRe, that AGN dominate over star formation as a CRe source, that astrophysical sources alone cannot explain the LOFAR residual Faraday rotation, and that the combined seeding is more than sufficient to fuel large-scale diffuse radio emission.

Significance. If the central claims hold, this would be a valuable step: it is one of the first cosmological simulations to evolve CRe and magnetic fields from multiple astrophysical injection channels at run time, and it introduces a cheap and elegant age-tracing method that could be reused by other groups. The paper also makes a concrete, falsifiable statement about the maximum contribution of galaxy formation to cosmic magnetisation, and it provides a simple fitting formula for the fossil CRe budget in halos. The authors are commendably explicit about many limitations, including the ad hoc nature of several efficiencies and the failure of the star-formation radio luminosity function. However, the headline shock-dominance claim and the quantitative budget formulas are more sensitive to uncalibrated parameters than the text suggests, and the evidence presented is partly in number density rather than energy density.

major comments (5)
  1. [§2.4, Eq. (3); §5, Eq. (5)] The claim that shocks dominate the fossil CRe budget is not robust to the injection momentum parameter x_inj in Eq. (3). In the strong-shock limit (alpha_inj -> 4), Eq. (3) gives xi_e proportional to x_inj^3 exp(-x_inj^2), so changing x_inj from 3.5 to 4.0 reduces xi_e by roughly a factor of 30, and changing it to 3.0 increases it by roughly a factor of 16. With x_inj = 4.0, the shock coefficient in Eq. (5) drops from 5.51e-4 to about 2e-5, which is below the AGN coefficient 4.9e-5; the central result that shocks dominate halo CRe would then no longer hold. The paper does not provide a sensitivity scan in x_inj, and no shock-related observable is used to anchor this parameter. Please add such a test, or substantially soften the dominance claim.
  2. [Abstract; §3.5, Figs. 19–20] The abstract claims that shocks dominate the energy density of fossil relativistic electrons in halos, but the quantitative evidence shown in Figs. 19 and 20 is the ratio of CRe number density to thermal-proton number density. Because the injected electrons start at Lorentz factors of only a few to a few tens and the spectra are steep, the number density can be dominated by the low-energy cutoff while the energy density is dominated by a different population or by another mechanism. The paper does not show an energy-density comparison, and no argument is given that number-density ratios track energy-density ratios across the three injection channels. Please present energy-density ratios, or revise the claim to refer to number density.
  3. [§2.6 and §3.3] The star-formation CRe model is calibrated to the high-luminosity end of the radio luminosity function, but Sec. 3.3 states that the resulting luminosity function underpredicts low-power galaxies and overpredicts high-luminosity objects, and that the mismatch is larger than any realistic observational bias. Since the quantitative budget in Eq. (5) includes the star-formation term with xi_SF = 1e-5, and since the paper's conclusion that the combination of mechanisms is sufficient to fuel radio emission depends on the total budget, a component whose calibration demonstrably fails at the population level cannot be treated as a robust prediction. The authors should either remove the SF term from the headline budget, quantify how the SF mismatch propagates into the total, or provide a calibration that reproduces the observed SF radio luminosity function more closely.
  4. [§4 and §3.6] The paper's conclusion that galaxy formation alone cannot explain the LOFAR residual Faraday rotation depends on the simulated volume filling factors of astrophysical magnetic fields, yet Sec. 4 explicitly states that the convergence of the volume filling factor of magnetic fields and CRe injected by galaxies has not been assessed. Given that the dynamo and feedback prescriptions are sub-grid and resolution-dependent, the filling factors in Fig. 18 and the resulting RM comparison in Fig. 22 could change with resolution or with the assumed dynamo threshold. Please provide a resolution study (even at lower volume) or explicitly restrict the RM conclusion to the tested resolution regime.
  5. [§5, Eqs. (5)–(6)] The normalization of the shock term in the fitting formula appears inconsistent with Eq. (3). For x_inj = 3.5 and strong shocks, Eq. (3) gives xi_e of order 1.3–1.5e-4 depending on Mach number, whereas Eqs. (5)–(6) normalize the shock coefficient to xi_e,M>=5 = 4.6e-4. This factor-of-three discrepancy is not explained; if xi_e,M>=5 is intended as an effective calibrated value that includes a Mach-number distribution or other physics, that should be stated explicitly. As written, the fitting formula mixes a nominally theoretical injection efficiency with a differently normalized coefficient, which makes its predictive content unclear.
minor comments (5)
  1. [§2.3, near Eq. (1)] The citation 'Sarazin e.g. 1999' should read 'Sarazin 1999'.
  2. [§1] The phrase 'By an large' should be 'By and large'.
  3. [§3.6] The in-text reference to 'Figure 3.5' should be 'Figure 23'.
  4. [§3.3] The symbol 'R500 3' in the first paragraph appears to be a formatting artifact; it should read 'R500' or 'R_{500}'.
  5. [References] There are several typographical issues in the reference list, e.g., 'Vog elsberger' should be 'Vogelsberger' and 'Fanaro ff-Riley' should be 'Fanaroff-Riley'.

Circularity Check

1 steps flagged · score 6.0 of 10

Fossil CRe budget predictions for AGN and star formation reduce to a posteriori calibrated efficiencies; shock-dominance claim retains independent content.

  1. fitted input called prediction [Sec. 2.5, Sec. 2.6, and Sec. 5, Eq. (5)]
    "This specific value of ξAGN has been calibrated a-posteriori, based on the comparison between the simulated radio luminosity function of our AGN with the observed one (Sec. 3.3) ... we calibrate a reasonable value for such "macroscopic" injection efficiency to ξSF = 10−5 as fiducial value, as this ensures that the synchrotron emission from star forming galaxies in the high luminosity end of our distribution is in line with observations ... NCRe/Nth = 5.51·10−4 ξe,M≥5/4.6·10−4 + 4.9·10−5 ξAGN/2·10−4 + 6·10−6 ξSF/10−5."

    In Eq. (5), the predicted fossil CRe budget from AGN and from star formation is written as a direct rescaling of ξAGN and ξSF, the same efficiencies that were calibrated a posteriori to reproduce the observed radio luminosity functions (Secs. 2.5, 2.6, 3.3). Because the radio luminosity in Sec. 2.7 is computed by normalizing template synchrotron spectra to the actual CRe number density injected with n_CRe,AGN = ξAGN n_jet and n_CRe,SF = ξSF n_g, the radio luminosity and the fossil CRe number are proportional to the same fitted parameters. Thus the AGN and SF terms in the final Eq. (5) are not independent predictions from first principles; they are restatements of the calibration inputs.

full rationale

The paper's headline result that shocks are the most volume-filling and dominant source of fossil CRe does not reduce to a fit by construction: the shock injection efficiency in Eq. (3) follows from DSA with a fixed injection momentum x_inj = 3.5, cited to kinetic PIC simulations, and is not calibrated a posteriori to radio luminosity functions. The volume-filling and halo-budget comparisons (Figs. 19-20) are simulation outputs rather than definitions. However, the paper also presents as a prediction the total fossil CRe budget in Eq. (5), and for the AGN and star formation contributions this budget is linearly proportional to ξAGN and ξSF, which the paper explicitly states were calibrated a posteriori to match observed radio luminosity functions. Since the radio luminosity used for that calibration is itself computed from the same CRe densities (Sec. 2.7), the AGN and SF terms of Eq. (5) merely re-express the fitted inputs. This is fitted-input-called-prediction circularity for those terms. The 'more than enough' conclusion is only partially affected because the dominant shock term carries independent content. No other circularity was found: the self-citation to Vazza & Botteon (2024) for the required CRe budget in observed radio halos is an external, equipartition-based estimate and is not derived from the present model; the cited prior simulations and PIC results are used as ordinary external evidence.

Assumptions & free parameters 5 free parameters · 5 assumptions · 1 invented entities

The central claims rest on a network of calibrated sub-grid parameters: the CRe injection efficiencies for shocks, AGN, and star formation are all fitted to observations, and the primordial field normalization is chosen with an eye on the LOFAR data that later serves as the comparison. The qualitative dominance of shocks is less sensitive to these choices, but the quantitative electron budget formulas explicitly depend on the fitted efficiencies.

free parameters (5)
  • xi_e (shock CRe injection efficiency as function of Mach number) = 4.6e-4 normalization applied at M >= 5; injection model from Kang (2024) with xinj = 3.5
    This efficiency determines the normalization of all shock-injected CRe and is calibrated to reproduce known cluster radio emission. The paper uses it as a fiducial value.
  • xi_AGN (fraction of jet gas injected as CRe) = 10^-3
    Calibrated a posteriori to match the observed radio luminosity function of AGN (Sec. 3.3), stated in Sec. 2.5.
  • xi_SF (fraction of gas in star forming cells injected as CRe) = 10^-5
    Calibrated using preliminary small-volume tests to match the high-luminosity end of the star forming radio luminosity function (Sec. 2.6).
  • epsilon_dyn (dynamo conversion factor) = Federrath et al. 2014 prescription
    Sub-grid dynamo amplification factor used to generate magnetic fields in halos; adopted from previous calibrated work, affects all magnetic field and Faraday rotation predictions.
  • B_1Mpc (primordial magnetic field normalization for C1 and C2 runs) = 0.37 nG
    Chosen to be 5 times lower than the CMB-based upper limit specifically to match the LOFAR Faraday rotation data (Sec. 2.2), which is then used as the comparison data for the Faraday rotation conclusion.
assumptions (5)
  • standard math Standard MHD equations with an ideal gas and primordial composition cooling
    The simulation framework assumes ideal MHD and equilibrium cooling with primordial composition, stated in Sec. 2.1.
  • domain assumption Diffusive shock acceleration injection model with xinj = 3.5 and M threshold 2.3
    The electron injection efficiency is assumed to follow the Kang (2024) semi-analytical prescription, stated in Sec. 2.4.
  • domain assumption SMBH mass is assigned via a gas mass scaling relation and Bondi accretion with ad hoc boosts
    The simulation assumes every gas density peak hosts an SMBH with mass from the Gaspari et al. relation and uses alpha_B boost parameters, stated in Sec. 2.5.
  • domain assumption Cosmic ray electrons are passively advected with no diffusion, streaming, or reacceleration
    The model treats CRe as a frozen passive fluid and neglects diffusion, justified in Sec. 2.3 and Sec. 4.
  • ad hoc to paper Sub-grid dynamo amplification is active only above 10 times the cosmic mean density
    The dynamo prescription is switched off in low density regions based on previous work, stated in Sec. 2.2.
invented entities (1)
  • Mirror fluid for age determination of CRe
    purpose: An artificially decaying copy of each CRe fluid used to estimate the time since last injection in every cell.
    This is a numerical bookkeeping device, not a physical entity. Its validity is tested internally by varying the decay timescale in the appendix.

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Cite this review

Pith. "Pith review of The evolution of cosmic ray electrons in the cosmic web: seeding by AGN, star formation and shocks." pith.science (2026). https://pith.science/paper/GJ4HCGDV

@misc{pith2026250119041,
  author       = {Pith},
  title        = {Pith review of: The evolution of cosmic ray electrons in the cosmic web: seeding by AGN, star formation and shocks},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GJ4HCGDV}},
  note         = {Machine review of arXiv:2501.19041}
}
read the original abstract

Several processes in the Universe convert a fraction of gas kinetic energy into the acceleration of relativistic electrons, making them observable at radio wavelengths, or contributing to a dormant reservoir of low-energy cosmic rays in cosmic structures. We present a new suite of cosmological simulations, with simple galaxy formation models calibrated to work at a specific spatial resolution, tailored to study all most important processes of injection of relativistic electrons in evolving large-sale structures: accretion and merger shocks, feedback from active galactic nuclei and winds from star forming regions. We also follow the injection of magnetic fields by active galactic nuclei and star formation, and compute the observational signatures of these mechanisms. We find that the injection of cosmic ray electrons by shocks is the most volume filling process, and that it also dominates the energy density of fossil relativistic electrons in halos. The combination of the seeding mechanisms studied in this work, regardless of the uncertainties related to physical or numerical uncertainties, is more than enough to fuel large-scale radio emissions with a large amount of seed fossil electrons. We derive an approximated formula to predict the number of fossil cosmic ray electrons injected by z=0 by the total activity of shocks, AGN and star formation in the volume of halos. By looking at the maximum possible contribution to the magnetisation of the cosmic web by all our simulated sources, we conclude that galaxy formation-related processes, alone, cannot explain the values of Faraday Rotation of background polarised sources recently detected using LOFAR.

Figures

Figures reproduced from arXiv: 2501.19041 by the authors.

Figure 1
Figure 1. Projected mean magnetic field intensity (top panels, in units of comoving Gauss) and projected mean mass-weighted gas temperature (bottom panels) across the full simulated 42Mpc3 volume in our B4 run at z ≈ 2 (left), for the z ≈ 1 (centre) and z ≈ 0 (right) epochs. Movies of some of our runs can be found at https://www.youtube.com/playlist?list=PL8ecsjnxOKP7LXQICrNBLHZkPgxh0jCzj. for our B4 model. The distribution o… view at source ↗
Figure 2
Figure 2. Same as [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Top projected mean (mass weighted) gas temperature (in units of [K]) across the entire simulated volume for our seven runs at z = 0.02. Bottom: for the same epoch and volume selection, projected mean (mass weighted) magnetic field strength (in units of [G]). The selected volume in all panels is about 21.25 × 42.5Mpc2 and the lenght along the line of sight is 42.5 Mpc. The second row of [PITH_FULL_IMAGE:figures/full… view at source ↗
Figures from the paper (21 more)
Figure 4
Figure 4. Figure 4: Cooling time for relativistic electrons underoging synchrotron and inverse compton losses (as in Eq.2), as function of their Lorentz factor and cosmic redshift, for two B = 0.1 µG and B = 10 µG. The solid black lines mark the region corresponding to our choice of the t…
Figure 5
Figure 5. Figure 5: Projected mean (CRe-weighted , only considering CRe from shocks) age of CRe since their last injection by shocks (in units of [Gyr]) across the entire simulated volume for our seven runs at z = 0.02 [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 6
Figure 6. Figure 6: Projected mean (CRe-weighted, only considering CRe from AGN) age of CRe since their last injection by AGN (in units of [Gyr]) across the entire simulated volume for our seven runs at z = 0.02. significant losses in dense environments, the presence of mul￾tiple complex …
Figure 7
Figure 7. Figure 7: Projected mean (CRe-weighted , only considering CRe from star formation) age of CRe since their last injection by star formation (in units of [Gyr]) across the entire simulated volume for our seven runs at z = 0.02 [PITH_FULL_IMAGE:figures/full_fig_p008_7.png]
Figure 8
Figure 8. Figure 8: Trend of injection efficiency of CRe (given in terms of the num￾ber of injected CRe with respect to the number of thermal particles) as a function of shock Mach number, for three different choices of the in￾jection momentum, xinj (the baseline model assumed in our simu…
Figure 9
Figure 9. Figure 9: Projected number of CRe across the full simulated 42.5Mpc3 volume in our B4 run (considering only 5 Mpc along the line of sight to better isolate single structures), for the z ≈ 2, z ≈ 1 and z ≈ 0 epochs (from top to bottom). The first column shows CRe injected by shoc…
Figure 10
Figure 10. Figure 10: Example of six different CR electrons spectra computed by our post-processing model, for different (random) variations of the combi￾nations between gas density, magnetic field strength, redshift and time elapsed since the injection of the initial power-law distributio…
Figure 11
Figure 11. Figure 11: History of the simulated cosmic star formation density (i.e. nor￾malised for Mpc3 comoving) in our suite of simulations, as a function of cosmic time. The grey points with error bars show the observed cosmic star formation derived in Madau & Dickinson (2014). 2.6. The…
Figure 12
Figure 12. Figure 12: Stellar mass luminosity function for our simulated galaxies in all models and for three different epochs, compared with the best-fit derived by McLeod et al. (2021) for observations at approximately equal redshift bins. The last panel shows the distribution of the ste…
Figure 11
Figure 11. Figure 11: This is the first global statistics to assess our subgrid im [PITH_FULL_IMAGE:figures/full_fig_p013_11.png]
Figure 13
Figure 13. Figure 13: Simulated scaling relations for the supermassive black holes modelled at run-time in our A3 and B4 runs, at three different epochs. The first column show the relation between the gas mass of the host galaxy and the SMBH mass, compared with the scaling relation inferre…
Figure 14
Figure 14. Figure 14: Evolution with cosmic time of the matter accretion rate onto star forming particles (red lines) and of the matter accretion rate onto AGN (blue lines) for our A3 and B4 models. onic mass. Therefore, this is the model in which our predictions for the total magnetic ene…
Figure 15
Figure 15. Figure 15: Projected mass weighted gas temperature (colors, in units of log10[K]) and over imposed contours of detectable synchrotron radio emission at 150MHz from CRe injected by AGN in a subselection of our volume (about 10 Mpc across) in six runs at z ≈ 1.0. the gas accretion…
Figure 16
Figure 16. Figure 16: Top row: evolving distribution function of radio power at 150 MHz from our simulated galaxies, in which only the radio emission from CRe injected by star formation is considered. Bottom row: evolving distribution function of radio power at 150 MHz from our simulated g…
Figure 17
Figure 17. Figure 17: Relation between the emitted radio power at 150 MHz and the stellar mass (top panel) or the specific star formation rate (bottom panel) for our A3 and B4 run at z = 1.065. density range typical of voids, in our C1 and C2 run with primor￾dial stochastic magnetic fields…
Figure 18
Figure 18. Figure 18 [PITH_FULL_IMAGE:figures/full_fig_p019_18.png]
Figure 20
Figure 20. Figure 20: Distribution of the ratio between CRe density and baryon den￾sity within R500 of our halos at three different epochs and for all runs. The solid lines show the distribution of CRe injected by shocks, the dotted lines by AGN and the dashed lines by star formation. emit…
Figure 21
Figure 21. Figure 21: Projected Rotation Measure maps (in units of [rad/m2 ] across the entire simulated volume for our seven runs at z = 0.02. Each panel is approximately 21.25 × 42.5 Mpc2 large [PITH_FULL_IMAGE:figures/full_fig_p022_21.png]
Figure 22
Figure 22. Figure 22: Trend of simulated rms of residual Faraday Rotation Measure, observed at z = 0 and for integrating out to increasingly larger redshift (up to z = 2.5), for our A3, B4 and C1 runs. The lines give the mean dispersion of the RRMf for 100 randomly selected lines of sight …
Figure 23
Figure 23. Figure 23: Projected mass weighted gas temperature (colors, in units of log10[K]) and over imposed contours of detectable synchrotron radio emission at 150 MHz from CRe accelerated by shocks in a subselection of our volume (about 20 Mpc across) in our nine runs at z = 0.02. Evol…
Figure 24
Figure 24. Figure 24: Distribution of the ratio between shock-injected CRe density and baryon density (bottom row) within R500 of our halos for the C1 and C2 runs at the end of the simulation. in our estimate of radio emission (Sec. 3.3), and it is deemed to be overall subdominant for the …

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Pith tools

Reviewed August 9, 2026 · model on record in the stance chip above.