Pith. sign in

REVIEW 4 major objections 4 minor 4 cited by

Simulating cosmic ray electron spectra and radio emission from an AGN jet outburst in a cool-core cluster

T0 review · 4 major / 4 minor · reviewed 2026-08-03 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read Radio spectral index maps of cluster jets can be read as maps of electron injection age, with the local magnetic field choosing whether the age is set by the last injection or the peak of the outburst.

desk verdict Useful forward-model framework, but the spectral-index–age connection is partly built into the uncalibrated sub-grid injection recipe, so the headline diagnostic is not yet demonstrated. read the letter →

arxiv 2601.10787 v1 pith:XX2FVI4Z submitted 2026-01-15 astro-ph.GA astro-ph.COastro-ph.HE

Léna Jlassi , Rainer Weinberger , Christoph Pfrommer , Maria Werhahn , Joseph Whittingham , Philipp Girichidis This is my paper · ORCID
classification astro-ph.GAastro-ph.COastro-ph.HE
keywords cosmicrayelectronsAGNjetsradiosynchrotronemissionspectralindexelectroncoolingFokker-Plancksolvercool-coreclustersmagnetohydrodynamics
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

This paper simulates a single AGN jet outburst in a cool-core cluster and follows cosmic-ray electron spectra along Lagrangian trajectories, computing the radio synchrotron emission they produce. Its central claim is a direct correspondence between observed radio spectral index and electron injection age, once the local magnetic field strength is known: in weak fields, the radio light at a given frequency comes from high-momentum electrons whose age is set by the last injection event, while in strong fields it comes from low-momentum electrons whose age is set by the maximum injection event in the past. If this holds, spectral index maps together with magnetic field estimates become a practical probe of jet duty cycle and injection history in real clusters. The paper also shows that adiabatic compression and dilution of the electron population in the rising bubbles roughly cancel in the total spectrum, so the total electron spectrum keeps a freely-cooling low-momentum branch and a steady-state high-momentum branch with decreasing normalization.

What carries the argument

The central object is the νc-effect, the relation p² ∝ ν_sync/B⊥ linking synchrotron frequency, electron momentum p, and perpendicular magnetic field B, combined with the split of each electron spectrum into a freely-cooling low-momentum branch and a steady-state high-momentum branch whose boundary (the transition momentum) moves with the magnetic field. Supporting machinery includes the sub-grid injection recipe — a fixed fraction (1%) of proton energy deposited as a p^-2.2 power law with an exponentially decreasing source function — and the adiabatic treatment that rescales spectra by r_jet = X_jet,f/X_jet,i for dilution and r_ρ^(α+2)/3 for compression, where X_jet is the jet mass fraction

What would settle it

Take a well-observed cluster lobe whose buoyancy age is known, measure the 150 MHz–1.4 GHz spectral index map and the magnetic field from Faraday rotation. The model predicts that in high-B regions the implied electron age equals the time since the peak of the outburst, while in low-B regions it equals the time since jet switch-off; if either age disagrees with the buoyancy age by more than the cooling-time uncertainties, the advection-only injection history or the dilution assumption is wrong.

Watch

Extended reading notes

Core claim

The paper establishes that, for a single jet outburst, each electron spectrum is a hybrid: low and intermediate momenta resemble a freely cooling population injected with a decaying source function, while high momenta form a steady-state slope (injection index steepened by one) whose normalization decreases with time. Because synchrotron frequency scales with electron momentum squared times the perpendicular magnetic field (the νc-effect), the part of the spectrum that lights a given radio frequency depends on the local magnetic field: strong fields select low momenta, weak fields select high momenta. The paper tracks two age definitions along each trajectory — the time of maximum injected e

Load-bearing premise

The electron injections that set every age and radio color come from an uncalibrated sub-grid recipe — 1% of the proton energy injected as a p^-2.2 power law only where the jet scalar exceeds 10^-3 and the gas moves faster than 3000 km/s, with momentum floor p=10 — so the connection between spectral index and age is only as reliable as this prescription for where and when acceleration happens.

Editorial extensions

If this is right

  • Observed spectral index maps of cluster radio lobes, combined with magnetic-field estimates, can be inverted to recover electron injection ages, distinguishing electrons last accelerated at jet switch-off (weak-field regions) from those set by the outburst's peak (strong-field regions).
  • A flat, young-looking spectral index at late times does not require ongoing particle acceleration: in the simulation, adiabatic compression flattens the 150 MHz–1.4 GHz spectrum long after the jet has shut off.
  • The total electron spectrum above p~100 is nearly unchanged when adiabatic and mixing effects are switched off, because compression and dilution cancel; individual regions, however, show strong differences.
  • The simulated jet produces radio powers consistent with observed FRI radio galaxies, so the framework can be applied to real systems, not just numerically convenient ones.
  • High-frequency radio emission is systematically less spatially extended than low-frequency emission from the same lobe, with the difference growing after jet shutoff — a direct observable sign of faster cooling of high-energy electrons.

Reading between the lines

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

  • If the field-dependent age connection holds in observations, it suggests a dating tool for cluster lobes: with a Faraday-rotation magnetic-field map, a single well-chosen radio frequency yields an electron age, and cross-checking against the buoyancy age of the associated X-ray cavity would test the assumed injection history.
  • The paper's dilution model treats CRe transport as purely advective. Real lobes likely experience diffusion and streaming; if those processes are significant, the high-momentum steady-state component would be erased faster than the r_jet scaling predicts, making the weak-field last-injection age an upper limit. A simulation with resolved transport would settle this.
  • The same framework naturally extends to multiple outbursts (double-double radio galaxies), where each event injects with the same decaying recipe; spectral index maps should then show nested age fronts obeying the same field-dependent rule. The authors identify continuous AGN activity as future work.
  • In the strong-field regime, the spectral-index age traces the time of maximum jet power, potentially turning radio lobes into records of AGN duty cycle — but only in the bright filaments and wakes where B is high and cooling is fast, not in the low-B lobe interiors.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 4 minor

Summary. The paper presents a 3D MHD simulation of a single, 50 Myr AGN jet outburst in a Perseus-like cool-core cluster, using Arepo. Cosmic ray protons are accelerated with a fixed efficiency xi_crp=0.1 and an exponential injection timescale tau_inj=10 Myr; cosmic ray electrons are assumed to receive a fixed fraction xi_cre=0.01 of the CRp energy, injected as a power law with slope alpha_inj=2.2 wherever X_jet>1e-3 and v>3000 km/s, with p_min capped at 10. The CRe spectra are evolved along Lagrangian tracer particles with the Fokker-Planck solver Crest, including adiabatic compression/dilution, Coulomb, bremsstrahlung, inverse Compton, and synchrotron losses, and post-processed with Crayon+ to produce synchrotron maps and spectra. The main results are: (i) the total electron spectrum develops a steady-state high-momentum slope alpha_inj+1 with decreasing normalization, while lower momenta resemble a freely cooling spectrum; (ii) the nu_c-effect means that at fixed radio frequency stronger B fields are illuminated by lower-momentum electrons and weaker B fields by higher-momentum electrons; (iii) the authors introduce two age measures, t_max_inj and t_last_inj, and argue that radio spectral index maps, combined with magnetic field estimates, can be read as maps of electron injection age and hence jet duty cycle.

Significance. If the central claim holds, the paper offers a physically motivated framework for interpreting resolved radio spectral-index maps of cluster AGN lobes in terms of CRe injection ages and AGN duty cycles, which would be valuable for connecting MHD simulations to observations. The forward modeling chain (Arepo-Crest-Crayon+) is credible, the idealized spectral tests in Figs. 3 and 11 are instructive, and the energy-budget check in Fig. 5 verifies internal consistency of the acceleration algorithms. However, the observational diagnostic is built on an uncalibrated sub-grid injection model and purely advective CRe transport; the age maps are defined from the same prescribed injection history that shapes the spectra. As a demonstration of what a given sub-grid model implies, the paper is sound; as a claim that observed radio properties can be used to infer underlying physics, it currently lacks the calibration and convergence evidence needed to be more than a model-dependent illustration.

major comments (4)
  1. [Sect. 2.3.3 and Sect. 3.4] The age–spectral-index connection is partly circular. The injection history is imposed by Eqs. (9)–(12): a power law with alpha_inj=2.2, efficiency xi_cre=0.01, thresholds X_jet>1e-3 and v>3000 km/s, and an exponential decay with tau_inj=10 Myr. The spectral index of fresh emission is then (alpha_inj-1)/2=0.6 by construction, and t_last_inj is defined as the time when 99.7% of the cumulative injected energy has been reached—an arbitrary cutoff of the same prescribed history. Fig. 10 therefore correlates two outputs of one model. To support the broader claim in the abstract that observers can infer MHD/CR physics from radio properties, the authors should either calibrate these parameters against resolved shock simulations or observations, or demonstrate explicitly that the age maps are insensitive to alpha_inj, tau_inj, the thresholds, and the 3-sigma cutoff. At minimum, the conclusions s
  2. [Sect. 2.4, Eq. (16), and Appendix B] The dilution treatment assumes n_cre scales with the jet mass fraction X_jet and that CRe transport is purely advective. This is load-bearing for the age maps because any diffusion or streaming of CRes relative to the jet gas would change the relation between the current spectral index and t_last_inj/t_max_inj. Appendix B already states that the tracer-based CRe mixing is only passive and differs from the CRp mass-flux treatment, and that discretization effects are visible in converging/diverging flows. The manuscript should quantify the associated uncertainty—for example, by comparing with a mass-flux-coupled CRe tracer or by estimating a diffusion timescale—or explicitly restrict the claims to the advective limit.
  3. [Sect. 2.2 and Figs. 7–10] No resolution or convergence study is presented. The simulation uses a radially varying target mass and jet-refined cells (V_jet,target=0.9 kpc^3), but the maps of spectral index and injection age, which are central to the paper's claim, are never shown to converge with respect to mesh resolution or tracer number. The patchiness noted in the intensity maps at late times is attributed to the constant tracer number, but this only underscores that the tracer discretization may affect the inferred age structure. A convergence test with higher mass resolution or tracer number, at least for the age fields and spectral index maps, is needed before these can be claimed as physical diagnostics.
  4. [Sect. 3.2 and Fig. 5] The statement that the jets produce radio powers consistent with observed FRI sources is not an independent validation: the normalization of the radio luminosity is set by the input L_jet=3e45 erg/s together with xi_cre=0.01 and xi_crp=0.1, and Fig. 5 confirms that the simulated CRp and CRe energies recover these chosen efficiencies. The figure is a useful internal consistency check, but the text should not present the FRI radio-power agreement as a prediction; it is a consequence of the chosen parameters. The discussion should distinguish between consistency and prediction.
minor comments (4)
  1. [Sect. 2.3.3] The speed threshold appears as '3 min =3000 km s−1'. This looks like a typesetting or copy-paste error; it should be v_min or similar.
  2. [References] Several references are incomplete or unpublished: Caprioli & Haggerty (2019) is listed only by title; Ruszkowski & Pfrommer (2023) and Werhahn et al. (2025) have no journal/volume/page. Please complete these entries before publication.
  3. [Fig. 3 caption] The caption says 'throughout 100 Myr of evolution' and the axes are not described in the text; adding a brief description of the units and line colors would improve readability.
  4. [Data Availability] The statement 'shared on reasonable request' is weak for a methods-oriented paper with code coupling; a persistent repository DOI for the analysis scripts and tracer outputs would strengthen reproducibility.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the spectral-index–age connection is a forward-model result, with uncalibrated sub-grid assumptions as limitations rather than circular inputs.

full rationale

The paper's core derivation is a forward calculation: an uncalibrated sub-grid injection model (Sect. 2.3.3) feeds a Fokker-Planck solver (Crest) that evolves CRe spectra with standard adiabatic, Coulomb, and radiative losses, and Crayon+ converts the resulting spectra into synchrotron emission via Eq. (17). The radio spectral index maps and the t_max/t_last age maps are both outputs of this same model, but the connection between them is not definitional: it is established through momentum-dependent cooling timescales and the νc-effect (Eq. 20), which determine which part of the spectrum dominates at a given frequency for a given magnetic field. The age definitions themselves are post-processing labels of the injection history, not quantities that were fit to the spectra. The statement that radio powers are 'consistent with observed powers of FRI radio galaxies' is a sanity check, not a fitted prediction: ξ_cre=0.01 and the jet luminosity are chosen inputs, and the paper does not claim to have tuned them to the observed radio power. Self-citations to Crest, Crayon+, and the jet model are methodological references, not load-bearing justifications of the central claim. Appendix B explicitly documents the discretization difference between tracer-based CRe mixing and CRp mass-flux advection, which is a stated limitation rather than a concealed circular step. The uncalibrated nature of the sub-grid acceleration thresholds and efficiencies is a correctness/robustness concern, not a circularity of the derivation chain.

Assumptions & free parameters 7 free parameters · 6 assumptions · 0 invented entities

The central results are produced by a chain of uncalibrated sub-grid choices: CRp/CRe acceleration efficiencies, injection slope and timescale, injection criteria, and the p_min cap. The dilution/adiabatic treatment assumes CRes stay locked to jet material. No new physical entities are introduced; all results are numerical consequences of these inputs plus standard loss/emission physics.

free parameters (7)
  • CRp acceleration efficiency xi_crp = 0.1
    Eq. (3); chosen input setting CRp energy; no independent calibration.
  • CRe acceleration efficiency xi_cre = 0.01
    Eq. (9); chosen input setting electron normalization and radio luminosity; FRI-power consistency in Fig. 6 is conditional on it.
  • Injection timescale tau_inj = 10 Myr
    Eqs. (5)-(7); exponential decay rate; chosen to match time in jet spine; controls spectral shape.
  • Injected electron spectral index alpha_inj = 2.2
    Eq. (10); sets steady-state slope 3.2 and radio spectral index ~0.6; motivated by modified DSA but chosen.
  • Maximum allowed minimum injection momentum p_min = 10
    Sect. 2.3.3; cap on p_min due to relativistic MHD corrections; creates p=10 feature in Fig. 4.
  • Injection speed threshold v_min = 3000 km/s
    Sect. 2.3.3; plus X_jet>10^-3; determines which tracers receive injected power law, shaping age maps.
  • Initial magnetic-to-thermal pressure ratios X_B,ICM and X_B,jet = 0.0125 / 0.1
    Sect. 2.1-2.2; set magnetic field maps and hence nu_c-effect; from Ehlert et al. 2023 / jet model.
assumptions (6)
  • standard math Standard synchrotron emissivity formula and Fokker-Planck loss terms (Coulomb, bremsstrahlung, IC, synchrotron) as implemented in Crest.
    Used in Eqs. (17)-(20) and Sect. 2.3.2; well-established physics, but code correctness is taken on trust from previous papers.
  • ad hoc to paper DSA at unresolved internal shocks is represented by a power-law injection with alpha_inj=2.2, efficiency xi_cre=0.01, and criteria X_jet>10^-3, v>3000 km/s.
    Sect. 2.3.3, Eqs. (9)-(12); no resolved shock model or calibration; this is the engine producing the CRe spectra.
  • domain assumption CRe transport is purely advective; no diffusion, streaming, or reacceleration beyond the sub-grid injection.
    Sect. 2.3.1 states advection is the only transport process; physically questionable for collisionless CRs in turbulent ICM; affects age maps.
  • domain assumption CRe dilution is captured by scaling f(p) with X_jet,f/X_jet,i (Eq. 16), and adiabatic compression by density ratio rho_f/rho_i (Eq. 13).
    Sect. 2.4; assumes CRe number density tracks jet mass fraction exactly; authors note tracer discretization limits in App. B.
  • domain assumption Velocity-field tracer particles and the post-processing Voronoi reconstruction faithfully represent Lagrangian fluid histories and continuous CRe fields.
    Sect. 2.3.2; Appendix B documents deviations from mass-conserving flows, especially in converging/diverging flows.
  • domain assumption Perseus-like initial conditions (density, temperature, turbulence, magnetic ratio) approximate a real cool-core cluster.
    Sect. 2.1, taken from Ehlert et al. 2023; idealized single realization, no ensemble.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Simulating cosmic ray electron spectra and radio emission from an AGN jet outburst in a cool-core cluster." pith.science (2026). https://pith.science/paper/XX2FVI4Z

@misc{pith2026260110787,
  author       = {Pith},
  title        = {Pith review of: Simulating cosmic ray electron spectra and radio emission from an AGN jet outburst in a cool-core cluster},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XX2FVI4Z}},
  note         = {Machine review of arXiv:2601.10787}
}
read the original abstract

Active galactic nucleus (AGN) powered jets can accelerate cosmic ray electrons, leading to the observed radio synchrotron emission. To simulate this emission, jet dynamics in galaxy clusters must be coupled to electron spectral modelling. We run magneto-hydrodynamic (MHD) simulations of a single AGN jet outburst in a Perseus-like galaxy cluster and adopt a sub-grid model for the acceleration of cosmic ray protons and electrons at unresolved internal shocks in the jet. We evolve cosmic ray electron spectra along Lagrangian trajectories using the Fokker-Planck solver Crest and compute the non-thermal emission using Crayon+. The resulting total electron spectrum reaches a steady-state slope at high momenta, with a gradually decreasing normalization over time, while the lower-momentum portion continues to resemble a freely cooling spectrum. The interaction of the jets with the turbulent cluster environment inflates lobes which rise buoyantly, induce amplification of the magnetic fields and uplift old cosmic ray populations in the wake of the bubbles. We connect radio spectral indices to electron injection ages: at a given radio frequency, weaker magnetic fields are illuminated by higher momenta electrons, whose age is determined by the last injection event. On the other hand, stronger magnetic fields are illuminated by lower momenta electrons, whose age is determined by the maximum energy injection event in the past. This powerful approach allows us to relate the underlying MHD properties to electron spectra and the resulting radio synchrotron emission, thereby enabling us to infer the underlying physics from observed radio properties.

Figures

Figures reproduced from arXiv: 2601.10787 by the authors.

Figure 1
Figure 1. Projections of a single jet outburst in a Perseus-like cluster showing volume-weighted quantities from left to right: mass density, magnetic field, jet mass fraction, CRp energy density. All projections have a depth ± 60 kpc from the cluster centre. The low-density jet-inflated lobes drag up gas in their wake, amplifying the magnetic field. In contrast to the gas density, in which only the lobes are visible, the mix… view at source ↗
Figure 2
Figure 2. Idealized non-thermal spectra for a single CRe population experiencing compression, dilution, and both simultaneously (in addition to Coulomb and synchrotron/inverse Compton cooling, which narrows the distribution at low and high momenta, respectively). The initial and final CRe distributions are shown as black dotted and dashed lines, respectively. In each case, the vector arrow is calculated based on the expected … view at source ↗
Figure 3
Figure 3. Idealized non-thermal spectra for a single CRe population showing different scenario throughout 100 Myr of evolution. All acceleration events correspond to a power-law CRe population with the same power-law index of αinj = 2.2, shown in dashed lines. Left: freely cooling spectrum–a single acceleration event followed by cooling. The arrow shows the location of the transition momentum between the non-cooled and cooled… view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: Volume-weighted non-thermal electron spectra throughout 220 Myr of evolution of which the jet is active for the first 50 Myr. Left: adiabatic changes and mixing effects are switched off and the peak of the spectrum in the mid-momenta range changes relatively little aft…
Figure 5
Figure 5. Figure 5: Top row: Time evolution of the jet, CRp and CRe energies. The latter is shown with two models: one with only adiabatic and mixing terms, and one with adiabatic and mixing effects, Coulomb and radiative losses. Bottom row: Time evolution of the energy fractions ξ betwee…
Figure 6
Figure 6. Figure 6: Time evolution of the total radio luminosity for a single jet out￾burst between 10 MHz and 100 GHz. The vertical dashed line indicates the ν = 150 MHz frequency, and the horizontal dashed line the FRI￾FRII radio power divide observed at this frequency (Mingo et al. 201…
Figure 7
Figure 7. Figure 7: Synchrotron intensity maps of our single jet outburst at different epochs (left to right) at 150 MHz and 1.4 GHz (top and bottom). We inte￾grated the synchrotron emissivity along a line of sight of ±220 kpc centred on the cluster. We smooth the intensity maps using a t…
Figure 8
Figure 8. Figure 8: Thin projections of depth ± 7 kpc shown at two different times for the following volume-averaged quantities, from left to right: a) synchrotron emissivity at ν = 150 MHz, b) value of the distribution function at p(ν, B⊥), c) magnetic field perpendicular to the line of …
Figure 9
Figure 9. Figure 9: Thin volume-averaged projections of depth ±7 kpc. Left: time of maximum injection, when the injected energy density is highest. Right: time of last injection, when the cumulative injected energy density of a Lagrangian tracer has reached 99.7% of its final value. Short…
Figure 10
Figure 10. Figure 10: Top: multi-epoch spectral index maps between 150 MHz and 1.4 GHz, where larger values correspond to older, more cooled plasma. Middle and bottom: thick projections of depth ±220 kpc centred on the cluster showing the time of last injection and the time of maximum inje…
Figure 11
Figure 11. Figure 11: Figure summarizing which age definition connects to which momentum range in the electron spectrum depending on the magnetic field strength. For a tracer spectrum at a given time, the magnetic field strength determines which momentum dominates the emission at a given f…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Simulating realistic radio morphologies of Fanaroff-Riley I jets in a self-regulating cool-core cluster

    astro-ph.GA 2026-06 unverdicted novelty 7.0 of 10

    Self-regulating AGN jets in MHD simulations of cool-core clusters yield realistic FRI radio morphologies viewed along the jet axis and account for frequency-independent lobe extents via 1-50 μG fields allowing both yo...

  2. Non-thermal emission in jets and winds: Expected emission and spectral index distributions

    astro-ph.HE 2026-07 conditional novelty 6.0 of 10

    Self-consistent CRE evolution in RMHD simulations produces distinct spectral-index gradients that distinguish compact AGN jets from winds even when morphology is ambiguous.

  3. The Radio--X-ray Correlation of High-Redshift AGN: A Numerical Study of Inverse-Compton Scattering of the CMB Photons in Relativistic Jets

    astro-ph.HE 2026-05 unverdicted novelty 6.0 of 10

    3D RMHD simulations with hybrid particle tracking reproduce the weak radio and strong X-ray redshift evolution in AGN jets via IC/CMB, including the (1+z)^4 X-ray scaling and the alpha-z relation.

  4. Active galactic nucleus driven jet feedback in cosmologically forming cool-core galaxy clusters I: The effect of hierarchical assembly on intra-cluster medium properties

    astro-ph.GA 2026-06 unverdicted novelty 4.0 of 10

    Cosmological simulations with AGN jet feedback reproduce observed cool-core cluster ICM properties more accurately than isolated simulations or IllustrisTNG due to merger-driven effects on gas velocity and warm gas abundance.

Reference graph

Works this paper leans on

87 extracted references · cited by 4 Pith papers

  1. [1]

    A., Kelner, S

    Aharonian, F. A., Kelner, S. R., & Prosekin, A. Y . 2010, Physical Review D, 82, 043002

    2010

  2. [2]

    I., Leer, E., & Skadron, G

    Axford, W. I., Leer, E., & Skadron, G. 1977, in International Cosmic Ray Con- ference, V ol. 11, 132

    1977

  3. [3]

    S., Dubois, Y ., Pellissier, A., et al

    Beckmann, R. S., Dubois, Y ., Pellissier, A., et al. 2022, Astronomy & Astro- physics, 665, A129

    2022

  4. [4]

    2024, Journal of Open Source Software, 9, 6296 Bîrzan, L., McNamara, B

    Berlok, T., Jlassi, L., Puchwein, E., & Haugbølle, T. 2024, Journal of Open Source Software, 9, 6296 Bîrzan, L., McNamara, B. R., Nulsen, P. E. J., Carilli, C. L., & Wise, M. W. 2008, The Astrophysical Journal, 686, 859

    2024

  5. [5]

    A., McNamara, B

    Birzan, L., Rafferty, D. A., McNamara, B. R., Wise, M. W., & Nulsen, P. E. J. 2004, The Astrophysical Journal, 607, 800

    2004

  6. [6]

    2019, Annual Review of Astronomy and Astrophysics, 57, 467

    Blandford, R., Meier, D., & Readhead, A. 2019, Annual Review of Astronomy and Astrophysics, 57, 467

    2019

  7. [7]

    2017, Astronomy & Astrophysics, 606, A98

    Brienza, M., Godfrey, L., Morganti, R., et al. 2017, Astronomy & Astrophysics, 606, A98

    2017

  8. [8]

    & Jones, T

    Brunetti, G. & Jones, T. W. 2014, International Journal of Modern Physics D, 23, 1430007

    2014

Show all 87 references
  1. [9]

    & Haggerty, C

    Caprioli, D. & Haggerty, C. C. 2019, The Issue with Diffusive Shock Accelera- tion

    2019

  2. [10]

    & Giacinti, G

    Cerutti, B. & Giacinti, G. 2023, Astronomy & Astrophysics, 676, A23

    2023

  3. [11]

    2023, Monthly Notices of the Royal Astro- nomical Society, 522, 2850

    Chen, Y .-H., Heinz, S., & Hooper, E. 2023, Monthly Notices of the Royal Astro- nomical Society, 522, 2850

    2023

  4. [12]

    2003, The Astrophysical Journal, 590, 225

    Churazov, E., Forman, W., Jones, C., & Böhringer, H. 2003, The Astrophysical Journal, 590, 225

    2003

  5. [13]

    H., Ineson, J., & Hardcastle, M

    Croston, J. H., Ineson, J., & Hardcastle, M. J. 2018, Monthly Notices of the Royal Astronomical Society, 476, 1614

    2018

  6. [14]

    P., Fendt, C., & Vaidya, B

    Dubey, R. P., Fendt, C., & Vaidya, B. 2023, The Astrophysical Journal, 952, 1

    2023

  7. [15]

    Dunn, R. J. H. & Fabian, A. C. 2004, Monthly Notices of the Royal Astronomical Society, 355, 862

    2004

  8. [16]

    Dursi, L. J. & Pfrommer, C. 2008, The Astrophysical Journal, 677, 993

    2008

  9. [17]

    2018, Monthly Notices of the Royal Astronomical Society, 481, 2878

    Ehlert, K., Weinberger, R., Pfrommer, C., Pakmor, R., & Springel, V . 2018, Monthly Notices of the Royal Astronomical Society, 481, 2878

    2018

  10. [18]

    2023, Monthly Notices of the Royal Astronomical Society, 518, 4622

    Ehlert, K., Weinberger, R., Pfrommer, C., Pakmor, R., & Springel, V . 2023, Monthly Notices of the Royal Astronomical Society, 518, 4622

    2023

  11. [19]

    J., & Krause, M

    English, W., Hardcastle, M. J., & Krause, M. G. H. 2016, Monthly Notices of the Royal Astronomical Society, 461, 2025

    2016

  12. [20]

    A., Pfrommer, C., Miniati, F., & Subramanian, K

    Ensslin, T. A., Pfrommer, C., Miniati, F., & Subramanian, K. 2011, Astronomy & Astrophysics, 527, A99 Enßlin, T. A., Pfrommer, C., Springel, V ., & Jubelgas, M. 2007, Astronomy & Astrophysics, 473, 41

    2011

  13. [21]

    Fanaroff, B. L. & Riley, J. M. 1974, Monthly Notices of the Royal Astronomical Society, 167, 31P

    1974

  14. [22]

    1949, Physical Review, 75, 1169

    Fermi, ENRICO. 1949, Physical Review, 75, 1169

    1949

  15. [23]

    J., et al

    Gendron-Marsolais, M.-L., Hlavacek-Larrondo, J., van Weeren, R. J., et al. 2020, Monthly Notices of the Royal Astronomical Society, 499, 5791

    2020

  16. [24]

    2013, Monthly Notices of the Royal Astronomical Society, 435, 1426

    Genel, S., V ogelsberger, M., Nelson, D., et al. 2013, Monthly Notices of the Royal Astronomical Society, 435, 1426

    2013

  17. [25]

    & Mathews, W

    Guo, F. & Mathews, W. G. 2011, The Astrophysical Journal, 728, 121

    2011

  18. [26]

    Guo, F. & Oh, S. P. 2008, Monthly Notices of the Royal Astronomical Society, 384, 251

    2008

  19. [27]

    Hardcastle, M. J. & Krause, M. G. H. 2013, Monthly Notices of the Royal As- tronomical Society, 430, 174

    2013

  20. [28]

    Hardcastle, M. J. & Krause, M. G. H. 2014, Monthly Notices of the Royal As- tronomical Society, 443, 1482 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al. 2018, Publications of the Astronomical Society of Japan, 70, 9

    2014

  21. [29]

    A., Krause, M

    Horton, M. A., Krause, M. G. H., & Hardcastle, M. J. 2020, Monthly Notices of the Royal Astronomical Society, 499, 5765

    2020

  22. [30]

    A., Shabala, S

    Jerrim, L. A., Shabala, S. S., Yates-Jones, P. M., et al. 2024, Monthly Notices of the Royal Astronomical Society, 531, 2532

    2024

  23. [31]

    Jones, T. W. & Kang, H. 2005, Astroparticle Physics, 24, 75

    2005

  24. [32]

    Jones, T. W. & Owen, F. N. 1979, The Astrophysical Journal, 234, 818

    1979

  25. [33]

    Lacki, B. C. & Thompson, T. A. 2010, The Astrophysical Journal, 717, 196

    2010

  26. [34]

    Ledlow, M. J. & Owen, F. N. 1996, The Astronomical Journal, 112, 9

    1996

  27. [35]

    G., Faltenbacher, A., & Brighenti, F

    Mathews, W. G., Faltenbacher, A., & Brighenti, F. 2006, The Astrophysical Jour- nal, 638, 659

    2006

  28. [36]

    H., Bell, A

    Matthews, J. H., Bell, A. R., & Blundell, K. M. 2020, New Astronomy Reviews, 89, 101543

    2020

  29. [37]

    H., Bell, A

    Matthews, J. H., Bell, A. R., Blundell, K. M., & Araudo, A. T. 2019, Monthly Notices of the Royal Astronomical Society, 482, 4303

    2019

  30. [38]

    Meenakshi, M., Mukherjee, D., Bodo, G., Rossi, P., & Harrison, C. M. 2024, Monthly Notices of the Royal Astronomical Society, 533, 2213

    2024

  31. [39]

    J., Jones, T

    Mendygral, P. J., Jones, T. W., & Dolag, K. 2012, The Astrophysical Journal, 750, 166

    2012

  32. [40]

    H., Hardcastle, M

    Mingo, B., Croston, J. H., Hardcastle, M. J., et al. 2019, Monthly Notices of the Royal Astronomical Society, 488, 2701

    2019

  33. [41]

    2010, IEEE Transactions on Plasma Science, 38, 2236

    Miyoshi, T., Terada, N., Matsumoto, Y ., et al. 2010, IEEE Transactions on Plasma Science, 38, 2236

    2010

  34. [42]

    2021, Monthly Notices of the Royal Astronomical Society, 505, 2267 Müller, A., Pfrommer, C., Ignesti, A., et al

    Mukherjee, D., Bodo, G., Rossi, P., Mignone, A., & Vaidya, B. 2021, Monthly Notices of the Royal Astronomical Society, 505, 2267 Müller, A., Pfrommer, C., Ignesti, A., et al. 2021, Monthly Notices of the Royal Astronomical Society, 508, 5326

    2021

  35. [43]

    2011, Astronomy & Astrophysics, 526, A148

    Murgia, M., Parma, P., Mack, K.-H., et al. 2011, Astronomy & Astrophysics, 526, A148

    2011

  36. [44]

    F., Frenk, C

    Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, The Astrophysical Journal, 462, 563

    1996

  37. [45]

    F., Frenk, C

    Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, The Astrophysical Journal, 490, 493

    1997

  38. [46]

    L., et al

    Nishikawa, K., Mizuno, Y ., Gómez, J. L., et al. 2020, Monthly Notices of the Royal Astronomical Society, 493, 2652 O’Neill, B. J., Jones, T. W., Nolting, C., & Mendygral, P. J. 2019, The Astro- physical Journal, 884, 12

    2020

  39. [47]

    2011, Monthly Notices of the Royal As- tronomical Society, 418, 1392

    Pakmor, R., Bauer, A., & Springel, V . 2011, Monthly Notices of the Royal As- tronomical Society, 418, 1392

    2011

  40. [48]

    M., Kannan, R., & Springel, V

    Pakmor, R., Pfrommer, C., Simpson, C. M., Kannan, R., & Springel, V . 2016, Monthly Notices of the Royal Astronomical Society, 462, 2603

    2016

  41. [49]

    & Springel, V

    Pakmor, R. & Springel, V . 2013, Monthly Notices of the Royal Astronomical Society, 432, 176

    2013

  42. [50]

    Perrone, L. M. & Latter, H. 2022, Monthly Notices of the Royal Astronomical Society, 513, 4605

    2022

  43. [51]

    Peterson, J. R. & Fabian, A. C. 2006, Physics Reports, 427, 1

    2006

  44. [52]

    2013, The Astrophysical Journal, 779, 10

    Pfrommer, C. 2013, The Astrophysical Journal, 779, 10

    2013

  45. [53]

    & Dursi, L

    Pfrommer, C. & Dursi, L. J. 2010, Nature Physics, 6, 520

    2010

  46. [54]

    M., & Springel, V

    Pfrommer, C., Pakmor, R., Schaal, K., Simpson, C. M., & Springel, V . 2017, Monthly Notices of the Royal Astronomical Society, 465, 4500

    2017

  47. [55]

    Pfrommer, C., Werhahn, M., Pakmor, R., Girichidis, P., & Simpson, C. M. 2022, Monthly Notices of the Royal Astronomical Society, 515, 4229

    2022

  48. [56]

    P., & Pfrommer, C

    Pinzke, A., Oh, S. P., & Pfrommer, C. 2013, Monthly Notices of the Royal As- tronomical Society, 435, 1061

    2013

  49. [57]

    G., Roe, P

    Powell, K. G., Roe, P. L., Linde, T. J., Gombosi, T. I., & De Zeeuw, D. L. 1999, Journal of Computational Physics, 154, 284

    1999

  50. [58]

    A., McNamara, B

    Rafferty, D. A., McNamara, B. R., Nulsen, P. E. J., & Wise, M. W. 2006, The Astrophysical Journal, 652, 216

    2006

  51. [59]

    A., Bruggen, M., Heinz, S., & Pfrommer, C

    Ruszkowski, M., Ensslin, T. A., Bruggen, M., Heinz, S., & Pfrommer, C. 2007, Monthly Notices of the Royal Astronomical Society, 378, 662

    2007

  52. [60]

    & Pfrommer, C

    Ruszkowski, M. & Pfrommer, C. 2023, Cosmic Ray Feedback in Galaxies and Galaxy Clusters – a Pedagogical Introduction and a Topical Review of the

    2023

  53. [61]

    K., & Reynolds, C

    Ruszkowski, M., Yang, H.-Y . K., & Reynolds, C. S. 2017, The Astrophysical Journal, 844, 13

    2017

  54. [62]

    Rybicki, G. B. & Lightman, A. P. 1986, Radiative Processes in Astrophysics (New York, NY: Wiley)

    1986

  55. [63]

    N., Hardcastle, M

    Sabater, J., Best, P. N., Hardcastle, M. J., et al. 2019, Astronomy & Astrophysics, 622, A17

    2019

  56. [64]

    Sarazin, C. L. 1999, The Astrophysical Journal, 520, 529

    1999

  57. [65]

    P., De Bruyn, A

    Schoenmakers, A. P., De Bruyn, A. G., Rottgering, H. J. A., Van Der Laan, H., & Kaiser, C. R. 2000, Monthly Notices of the Royal Astronomical Society, 315, 371

    2000

  58. [66]

    Sijacki, D., Pfrommer, C., Springel, V ., & Enlin, T. A. 2008, Monthly Notices of the Royal Astronomical Society, 387, 1403

    2008

  59. [67]

    E., & Narayan, R

    Sironi, L., Rowan, M. E., & Narayan, R. 2021, The Astrophysical Journal Let- ters, 907, L44

    2021

  60. [68]

    & Spitkovsky, A

    Sironi, L. & Spitkovsky, A. 2014, The Astrophysical Journal Letters, 783, L21

    2014

  61. [69]

    2010, Monthly Notices of the Royal Astronomical Society, 401, 791

    Springel, V . 2010, Monthly Notices of the Royal Astronomical Society, 401, 791

    2010

  62. [70]

    F., Bryan, G

    Su, K.-Y ., Hopkins, P. F., Bryan, G. L., et al. 2021, Monthly Notices of the Royal Astronomical Society, 507, 175

    2021

  63. [71]

    & Finkbeiner, D

    Su, M. & Finkbeiner, D. P. 2012, The Astrophysical Journal, 753, 61

    2012

  64. [72]

    2018, The Astro- physical Journal, 865, 144 van Weeren, R

    Vaidya, B., Mignone, A., Bodo, G., Rossi, P., & Massaglia, S. 2018, The Astro- physical Journal, 865, 144 van Weeren, R. J., de Gasperin, F., Akamatsu, H., et al. 2019, Space Science Reviews, 215, 16

    2018

  65. [73]

    2021, Astronomy & Astro- physics, 653, A23

    Vazza, F., Wittor, D., Brunetti, G., & Brüggen, M. 2021, Astronomy & Astro- physics, 653, A23

    2021

  66. [74]

    Wang, C., Ruszkowski, M., & Yang, H.-Y . K. 2020, Monthly Notices of the Royal Astronomical Society, 493, 4065

    2020

  67. [75]

    M., & Aharonian, F

    Wang, J.-S., Reville, B., Liu, R.-Y ., Rieger, F. M., & Aharonian, F. A. 2021, Monthly Notices of the Royal Astronomical Society, 505, 1334 Article number, page 16 of 20 Léna Jlassi et al.: Simulating cosmic ray electron spectra and radio emission in cluster AGN jets

    2021

  68. [76]

    2017, Monthly Notices of the Royal Astronomical Society, 470, 4530

    Weinberger, R., Ehlert, K., Pfrommer, C., Pakmor, R., & Springel, V . 2017, Monthly Notices of the Royal Astronomical Society, 470, 4530

    2017

  69. [77]

    2020, The Astrophysical Journal Supplement Series, 248, 32

    Weinberger, R., Springel, V ., & Pakmor, R. 2020, The Astrophysical Journal Supplement Series, 248, 32

    2020

  70. [78]

    2023, Monthly Notices of the Royal Astronomical Society, 523, 1104

    Weinberger, R., Su, K.-Y ., Ehlert, K., et al. 2023, Monthly Notices of the Royal Astronomical Society, 523, 1104

    2023

  71. [79]

    2021, Monthly Notices of the Royal Astronomical Society, 508, 4072

    Werhahn, M., Pfrommer, C., & Girichidis, P. 2021, Monthly Notices of the Royal Astronomical Society, 508, 4072

    2021

  72. [80]

    2025, Steady-State or Not? The Evolution of Cosmic Ray Electron Spectra in Galaxies

    Werhahn, M., Pfrommer, C., Whittingham, J., et al. 2025, Steady-State or Not? The Evolution of Cosmic Ray Electron Spectra in Galaxies

    2025

  73. [81]

    2024, Zooming-in on Cluster Radio Relics – I

    Whittingham, J., Pfrommer, C., Werhahn, M., Jlassi, L., & Girichidis, P. 2024, Zooming-in on Cluster Radio Relics – I. How Density Fluctuations Explain the Mach Number Discrepancy, Microgauss Magnetic Fields, and Spectral Index Variations

    2024

  74. [82]

    2021, MNRAS, 506, 229

    Whittingham, J., Sparre, M., Pfrommer, C., & Pakmor, R. 2021, MNRAS, 506, 229

    2021

  75. [83]

    2019, Monthly Notices of the Royal Astronomical Society, 488, 2235

    Winner, G., Pfrommer, C., Girichidis, P., & Pakmor, R. 2019, Monthly Notices of the Royal Astronomical Society, 488, 2235

    2019

  76. [84]

    2020, Monthly Notices of the Royal Astronomical Society, 499, 2785

    Winner, G., Pfrommer, C., Girichidis, P., Werhahn, M., & Pais, M. 2020, Monthly Notices of the Royal Astronomical Society, 499, 2785

    2020

  77. [85]

    Yang, H.-Y . K. & Ruszkowski, M. 2017, The Astrophysical Journal, 850, 2

    2017

  78. [86]

    2019, The Astrophysical Journal Sup- plement Series, 245, 17

    Yang, X., Joshi, R., Gopal-Krishna, et al. 2019, The Astrophysical Journal Sup- plement Series, 245, 17

    2019

  79. [87]

    M., Turner, R

    Yates-Jones, P. M., Turner, R. J., Shabala, S. S., & Krause, M. G. H. 2022, Monthly Notices of the Royal Astronomical Society, 511, 5225 Article number, page 17 of 20 A&A proofs:manuscript no. main Appendix A: Cooling timescales In Fig. A.1, we show a range of cooling time cur...

    2022

Pith tools

Reviewed August 3, 2026 · model on record in the stance chip above.