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From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars

T0 review · 4 major / 6 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read For BL Lacs, the blazar sequence reflects equipartition-balanced jets, not Doppler boosting or selection effects.

desk verdict Careful large-sample SED modeling, but the equipartition claim is not supported until the fitted parameter correlations get error bars and an internal slope inconsistency is resolved. read the letter →

arxiv 2507.21647 v2 pith:PPRCA355 submitted 2025-07-29 astro-ph.HE astro-ph.GA

Muhammad S. Anjum , Shu-Jin Hou , Liang Chen , Zhigang Li , Minfeng Gu This is my paper · ORCID
classification astro-ph.HEastro-ph.GA
keywords blazarsblazarsequenceequipartitionlog-parabolicelectronenergydistributionone-zoneleptonicmodelstochasticparticleaccelerationsynchrotronpeakfrequencyspectralcurvature
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 asks why blazars display the "blazar sequence", the observed inverse trend between synchrotron peak frequency $\nu_s$ and peak luminosity $\nu_s L_s$, and whether that trend is intrinsic jet physics or an artifact of beaming and selection. Modeling the nearly simultaneous broadband spectra of 100 bright 4FGL blazars with a one-zone leptonic model and a log-parabolic electron energy distribution, the authors find that $\nu_s$ is set almost entirely by the electron peak energy $\gamma_{3p}$, while luminosity tracks the electron density $n_e$. For BL Lac objects the derived parameters satisfy $B^2 \sim n_e \gamma_{3p}$, the hallmark of equipartition between magnetic and particle energy, and these internal links reproduce the negative $\nu_s$-$\nu_s L_s$ trend. The paper concludes that for BL Lacs the blazar sequence is a real equipartition-driven sequence, not mainly a Doppler or selection effect, whereas flat-spectrum radio quasars deviate from equipartition and require independent jet parameters.

What carries the argument

The load-bearing machinery is the one-zone homogeneous leptonic jet model whose emitting electrons follow a log-parabolic EED, $N(\gamma)=N_0(\gamma/\gamma_0)^{-s-r\log(\gamma/\gamma_0)}$, with peak energy $\gamma_{3p}=\gamma_0 10^{(3-s)/2r}$; this EED shape is produced by stochastic acceleration balanced against radiative cooling. The argument proceeds by linking the SED observables $\nu_s$ and $b_s$ to EED parameters via $\nu_s\propto\gamma_{3p}^2 B\delta$ and the $r=5b_s$ mapping, and then connecting the fitted parameters through the equipartition condition $U_B=U_e$, i.e., $B^2\simeq n_e\gamma_{3p}$, which forces the inverse $\gamma_{3p}$-$n_e$ relation and the positive $B$-$n_e$ relation. The turbulence index $q$ of the magnetic fluctuation spectrum, $W(k)\propto k^{2-q}$, distinguishes hard-sphere ($q=2$) from softer Kolmogorov or Kraichnan turbulence and determines how tightly $r$ anti-correlates with $\gamma_{3p}$.

What would settle it

Re-fit a subset of the same BL Lac SEDs with a two-zone model or with the viewing angle as a free parameter; if the $\gamma_{3p}$-$n_e$ anticorrelation and the $B$-$n_e$ correlation weaken to non-significance, the equipartition interpretation collapses into a fitting degeneracy. A cheaper test is to take BL Lacs with VLBI-measured Doppler factors, fix $\delta$ to the observed values, and check whether the correlations in the $\gamma_{3p}$-$n_e$ and $B$-$n_e$ planes survive.

Watch

Extended reading notes

Core claim

Using a one-zone leptonic model with synchrotron, SSC, and dusty-torus EC components, the authors fit log-parabolic electron energy distributions $N(\gamma)=N_0(\gamma/\gamma_0)^{-s-r\log(\gamma/\gamma_0)}$ to the SEDs of 100 bright blazars from the Fermi bright AGN sample. They derive per-source values of magnetic field $B$, electron density $n_e$, electron peak energy $\gamma_{3p}$, source size $R$, and Doppler factor $\delta$. The synchrotron peak frequency follows $\nu_s \propto \gamma_{3p}^2$ with no measurable dependence on $B\delta$, identifying electron peak energy as the driver of spectral evolution; in the $\nu_s$-$\nu_s L_s$ plane this translates to $n_e$ as the luminosity driver. For BL Lacs the authors find a significant inverse correlation $\log n_e = -1.35 \log \gamma_{3p} + 5.4$ (Pearson $r_p < -0.8$) and a positive correlation $\log n_e = 1.32 \log B + 1.85$, with Compton dominance near unity, all consistent with equipartition $U_B \approx U_e$. They argue that these internal relations naturally produce the BL Lac blazar sequence, while FSRQs show no such correlations. The paper further reports an anti-correlation between $\nu_s$ and the synchrotron spectral curvature $b_s$ for all blazars and a milder anti-correlation between $\gamma_{3p}$ and the EED curvature $r$, which it interprets as stochastic acceleration with soft magnetic turbulence ($q<2$) operating close to steady state; for BL Lacs the photon and electron curvatures nearly satisfy the theoretical relation $r \approx 5 b_s$, whereas FSRQs deviate because of the thermal big blue bump contaminating $b_s$.

Load-bearing premise

The equipartition conclusion assumes that the one-zone homogeneous leptonic model, with fixed viewing angle around 3 degrees, opening angle around 5 degrees, and dusty-torus EC dominance for low-peaked sources, yields unique, non-degenerate estimates of $B$, $n_e$, $\gamma_{3p}$, and $R$ from each SED; the paper gives no parameter uncertainties or degeneracy analysis.

Editorial extensions

If this is right

  • For BL Lacs, a single-epoch SED can be read as a near-equipartition diagnostic: $\nu_s$ directly gives $\gamma_{3p}$ and $\nu_s L_s$ gives $n_e$, so the sequence traces the distribution of electron acceleration states across sources.
  • If equipartition holds, jet power and energy budgets for BL Lacs can be computed with one less free parameter, since $B$ is fixed by $n_e$ and $\gamma_{3p}$, which sharpens comparisons with accretion power.
  • The FSRQ deviation implies their SED evolution is governed by the external radiation field of the dusty torus rather than internal balance, so FSRQ jet models that keep $B$, $n_e$, and $\gamma_{3p}$ mutually independent are the appropriate starting point.
  • The approximate $r\approx 5b_s$ relation found for BL Lacs means the observed SED curvature is a faithful proxy for the intrinsic EED curvature, making curvature a practical observable for testing acceleration models over large samples.

Reading between the lines

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

  • If the equipartition reading is correct, time-resolved SED monitoring of a single BL Lac should show $\gamma_{3p}$ and $n_e$ moving anticorrelated during flares, redistributing energy between particle energy and particle number; this is testable with existing multi-epoch campaigns.
  • The fixed-geometry assumption ($\theta\simeq 3^\circ$, $\phi\simeq 5^\circ$) is a strong prior, and independent VLBI measurements of $\delta$ for a subset of BL Lacs could confirm that the $B$-$n_e$-$\gamma_{3p}$ correlations are not a coordinate degeneracy of the fit.
  • The same one-zone machinery, applied to FSRQs with a BLR rather than dusty-torus EC component, could test whether the equipartition violation is due to the torus photon field or to genuinely independent jet parameters.
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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

4 major / 6 minor

Summary. The manuscript models the broadband SEDs of 100 Fermi-LAT blazars from the LBAS sample using 4FGL-DR3 gamma-ray data, fits log-parabolic functions to the synchrotron and IC bumps, and fits a one-zone leptonic synchrotron+SSC+EC model with a log-parabolic electron distribution. The authors report that the synchrotron peak frequency is driven by the electron peak energy gamma3p rather than by B*delta; that BL Lacs show a negative nu_s-nu_s*L_s trend that they interpret as not due to Doppler boosting; and that for BL Lacs the fitted B, n_e, and gamma3p satisfy correlations (B-n_e positive, n_e-gamma3p negative) that they interpret as equipartition U_B~U_e. They further report that nu_s anti-correlates with the synchrotron curvature b_s, that gamma3p mildly anti-correlates with the EED curvature r, and that the r-b_s relation for BL Lacs is close to r=5 b_s. FSRQs are found not to follow the equipartition correlations.

Significance. If established, the central result would reframe the blazar sequence for BL Lacs as an intrinsic equipartition-driven relation rather than a Doppler or selection artifact, and it would connect SED curvature to EED curvature in a statistically large sample. The paper is a substantial modeling campaign: 100 sources with updated GeV-TeV data, LP polynomial fits, one-zone model fits, and a systematic comparison of BL Lacs and FSRQs. The main physical conclusion is, however, conditional on the uniqueness and reliability of the fitted parameters. The paper provides no parameter uncertainties, no degeneracy analysis, and no mock-recovery tests, and one of the key regression relations is internally inconsistent. The significance is therefore real but not yet established; the result would be a valuable advance if the statistical foundations are supplied.

major comments (4)
  1. [§4.1, Figs. 11–12] The three reported regression relations for BL Lacs are not mutually consistent. Combining log n_e = -1.35 log gamma3p + 5.4 and log B = -0.53 log gamma3p + 0.6 algebraically yields log n_e = 2.55 log B + 3.9 for the same sample, whereas the paper reports log n_e = 1.32 log B + 1.85. In addition, the text describes the B-n_e relation as positive but quotes r_p = -0.63. These inconsistencies mean that the set of correlations, as presented, cannot support the equipartition chain B^2 ~ n_e gamma3p; the authors must either correct the regressions or explain why the relations are not transitive.
  2. [§3, §4.1, Tables 3–4] The central claim that BL Lacs are in equipartition rests entirely on correlations among B, n_e, and gamma3p obtained from a many-parameter one-zone fit (B, n_e, s, r, gamma0, R, delta, R_b, and for FSRQs L_D, R_T) using chi^2 minimization, with no reported parameter uncertainties, degeneracy analysis, or mock-recovery tests. One-zone SSC/EC models are known to have broad degeneracies among B, n_e, R, delta, and gamma3p, and the paper fixes theta and phi at about 3 and 5 degrees but does not demonstrate that the fitted parameters are uniquely identifiable from the sparse multi-band data. A suite of recovery tests on simulated SEDs, or at least confidence contours for the key parameters, is needed before the correlations in Fig. 11 can be interpreted as jet physics rather than fitting-path artifacts.
  3. [§3.1, Eq. (17), §4.2, Fig. 14] The claimed 'intrinsic signature of stochastic acceleration' in the gamma3p-r plane is partly definitional. gamma3p is computed from the fitted LP parameters via Eq. (17), which for fixed s and gamma0 gives log gamma3p = log gamma0 + (3-s)/(2r), a decreasing function of r. The paper does not show that the scatter in s and gamma0 breaks this built-in anti-correlation; as written, the reported mild anti-correlation in Fig. 14 could be an artifact of the parameterization rather than evidence for soft turbulence. The authors should quantify the partial correlation of gamma3p and r after removing the contribution of s and gamma0, or fit the EED peak directly.
  4. [§4.1, Fig. 9] The conclusion that the nu_s-nu_s*L_s trend for BL Lacs is 'not an artifact of Doppler boosting' is based on the lack of correlation between nu_s and B*delta in Fig. 9. This inference is only as strong as the reliability of the fitted delta and B values; because no uncertainties are given, the null correlation could be washed out by large parameter errors. A simple demonstration that delta is recovered accurately in mock fits, or an explicit discussion of the delta degeneracy, is needed to support this key conclusion.
minor comments (6)
  1. [Table 3 caption] The Table 3 note contains a duplicated column description: 'Column (2) gives the SED type of source. Column (2) gives the redshift of the source.' The column numbering should be corrected so each column is described once.
  2. [Figure 6 caption] The caption says 'the lower panels show IC peak frequency nu_s and IC peak flux nu_c F_c'; the first symbol should be nu_c, not nu_s.
  3. [Section 5, first paragraph] The sentence 'The blazras shows a negative trend...' contains a typo: 'blazras' should be 'blazars' and 'shows' should be 'show'.
  4. [Section 2, third paragraph] The word 'corrsponding' should be 'corresponding'.
  5. [Section 4.1, Fig. 7] The text reports 'correlation coefficient rp approximately -0.4 and a chance probability p ~ 10^-3' for the nu_s-nu_s*L_s and nu_c-nu_c*L_c planes; please specify whether r_p is the Pearson or Spearman coefficient and report the p-value separately for each plane.
  6. [Section 4.2, Eq. (24)] Eq. (24) as written mixes logarithmic and linear quantities: 'log nu_s proportional to log gamma0 + 3/(10 b_s)' is not dimensionally consistent. The intended relation likely involves log nu_s proportional to log gamma0 plus a term proportional to 1/b_s; please rewrite it in a manifestly consistent form.

Circularity Check

1 steps flagged · score 4.0 of 10

The γ3p–r anti-correlation is partly built into the LP EED definition, but the equipartition inference itself is not definitionally forced.

  1. self definitional [Section 3, Eq. (17)-(18) and Section 4.2, Figure 14]
    "The peak energy of LP EED in the γ3N(γ) representation is given by γ3p = γ010(3−s)/(2r). (17) Thus, the particle energy and curvature are inversely related in stochastic acceleration as log γ3p = log γ0 + (3 − 2s)/(2r)."

    γ3p is computed from the fitted LP parameters s and r via Eq. (17). For s<3, ∂log γ3p/∂r < 0 identically, so a negative γ3p–r trend is built into the log-parabolic parameterization. Reporting r = −0.075 logγ3p + 0.93 as an observed 'intrinsic signature of stochastic acceleration' and citing the authors' own Anjum et al. (2020) presents the ansatz's algebra as an empirical finding, rather than as a consequence of how γ3p is defined.

full rationale

The main equipartition claim is not circular in the strict sense: the authors do not impose UB ≈ Ue during fitting, and the B–ne–γ3p correlations are outputs of one-zone SED fits, not inputs. However, the supporting claim that the γ3p–r anti-correlation confirms stochastic acceleration is partially self-definitional, because γ3p is derived from the fitted curvature r and index s through Eq. (17), which for s<3 forces a negative partial derivative. The self-citation to Anjum et al. (2020) does not provide independent evidence. The equipartition conclusion would be considerably stronger with parameter uncertainties, degeneracy/mock-recovery tests, and mutually consistent regression slopes (the reported ne–γ3p and B–γ3p fits imply ne–B slope ≈ 2.5, not 1.32), but those are robustness issues rather than definitional circularity. Score 4 reflects one partially definitional step plus self-citation, while the central inference retains independent empirical content.

Assumptions & free parameters 10 free parameters · 6 assumptions · 0 invented entities

The central interpretation rests on many per-source fitted jet parameters (B, ne, gamma0, s, r, R, delta, Rb, LD) and on the assumption that these are physically meaningful rather than degenerate fitting combinations. No error bars or degeneracy tests are provided, so the ledger is dominated by fitted quantities.

free parameters (10)
  • Per-source magnetic field B = 0.002 to 0.23 G (Tables 3, 4)
    Fitted by the JetSet one-zone model from each SED; central to the B-ne equipartition correlation, with no uncertainties reported.
  • Per-source electron density n_e = 0.0 to 242.4 cm^-3 (Tables 3, 4)
    Fitted normalization of the LP electron distribution; anti-correlation with gamma3p is a key claim.
  • Electron peak energy gamma3p = Not tabulated; derived from fitted gamma0, s, r via Eq. (17)
    Declared main driver of synchrotron peak frequency; derived rather than directly measured.
  • EED curvature r = roughly 0.3 to 1.1 (Tables 3, 4)
    Fitted LP curvature; used in gamma3p-r and r-bs correlations.
  • EED spectral index s = about 0.5 to 2.7 for BL Lacs, about 1.8 to 2.7 for FSRQs
    Fitted LP slope; enters the gamma3p definition.
  • Electron reference energy gamma0 = approx 10^2 to 3.5x10^4 (Tables 3, 4)
    Fitted LP reference energy; varies over orders of magnitude and drives much of the gamma3p range.
  • Blob radius R = approx 10^16.5 to 10^18 cm (Tables 3, 4)
    Fitted source size; affects luminosity and SSC constraints.
  • Doppler factor delta and bulk Lorentz factor Gamma = delta roughly 7.6 to 44 for BL Lacs; Gamma roughly 4 to 45 for FSRQs
    Fitted beaming parameters; central to the claim that Doppler boosting is not responsible for the sequence.
  • Synchrotron spectral curvature b_s = 0.06 to 0.28 (Tables 1, 2)
    Coefficient from log-parabolic polynomial fitting; used in nu_s-b_s and r-b_s relations.
  • Blob location Rb and disk luminosity LD for FSRQs = Rb from 0.4 to 17 x 10^18 cm; LD from 0.27 to 545 x 10^45 erg/s (Table 4)
    Used to set the dusty-torus EC seed photon field and to support the Rb-LD correlation claim.
assumptions (6)
  • domain assumption One-zone homogeneous spherical blob with uniform LP electron distribution and tangled magnetic field emits the observed SED.
    Invoked in Section 3; if the emission is multi-zone, the derived B-ne-gamma3p relations may not be unique.
  • domain assumption Typical viewing angle theta=3 degrees and opening angle phi=5 degrees are adopted for all sources.
    Section 3 states these are assumed typical; systematic geometry errors propagate into delta and jet power.
  • domain assumption For LSP sources, gamma-ray emission is dominated by external Compton scattering of dusty torus photons with temperature about 10^2 K and reprocessing fraction 0.1.
    Section 3 and Section 4; several sources require BLR photons for the >100 GeV tail, so the field model is incomplete.
  • standard math The LP EED and the theoretical relation r=5bs from Massaro et al. (2006) are adopted as benchmarks.
    Section 3.1; the comparison of r and bs for BL Lacs is made against this prior result.
  • standard math Acceleration timescale scaling tau_a proportional to gamma^(2-q) with turbulence index q separates hard-sphere q=2 from softer q<2 turbulence.
    Section 3.1 and Section 4.2; used to interpret the weak gamma3p-r anti-correlation as soft turbulence.
  • standard math Standard flat cosmology with H0=70 km/s/Mpc, Omega_m=0.32, Omega_Lambda=0.68.
    Section 1; luminosity distances affect Ls in the blazar sequence plane.

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Cite this review

Pith. "Pith review of From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars." pith.science (2026). https://pith.science/paper/PPRCA355

@misc{pith2026250721647,
  author       = {Pith},
  title        = {Pith review of: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PPRCA355}},
  note         = {Machine review of arXiv:2507.21647}
}
abstract

We investigate the evolution of spectral energy distribution (SED) and underlying electron energy distribution (EED) by modeling the nearly simultaneous broadband spectra of selected bright 4FGL blazars, in the context of a combined cooling and stochastic acceleration scenario. We find that one-zone leptonic model with log-parabolic (LP) EED can successfully fit the GeV-TeV emission of blazars. The synchrotron frequency $\nu_s$ of blazars mainly evolves due to variation of electron peak energy $\gamma_{3p}$. The BL Lac objects (BL Lacs) show a negative trend in the $\nu_s- \nu_s L_s$ SED plane, known as blazar sequence, that does not seem to be an artifact of Doppler boosting, but driven by the equipartition constraints. A positive correlation is found between the derived magnetic field $B$ and electron density $n_e$, whereas $n_e$ and $\gamma_{3p}$ negatively relate, as expected in an equipartition scenario. The flat spectrum radio quasars (FSRQs) deviate significantly from such a scenario, indicating their jet parameters should be varying independently. The synchrotron peak frequency $\nu_s$ and its spectral curvature $b_s$ negatively correlate for all blazars, confirming the stochastic particle acceleration in blazar jets. However, blazars do not show the signature of hard-sphere acceleration, indicating that magnetic turbulence in the jets might be soft and physical conditions might be near to steady state, consistent with equipartition. Furthermore, for BL Lacs, the SED curvature $b_s$ and the EED curvature $r$ and nearly meet the theoretical relationship $r=5b_s$, whereas the FSRQs show large deviation due to poor constrain on $b_s$ due to presence of thermal component.

Figures

Figures reproduced from arXiv: 2507.21647 by the authors.

Figure 1
Figure 1. The distributions of physical jet parameters of BL Lacs (blue) and FSRQs (red). field [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. The distributions of source electron energy distribution (EED) parameters for BL Lacs (blue) and FSRQs (red). FSRQs to eliminate possible systematic biases [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. The distributions of jet power for BL Lacs (blue) and FSRQs (red). 17.50 17.75 18.00 18.25 18.50 18.75 19.00 19.25 log Rb 44.0 44.5 45.0 45.5 46.0 46.5 47.0 47.5 lo g L D [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (14 more)
Figure 4
Figure 4. Figure 4: The relationship between dissipation location Rb and the accretion disk luminosity LD for FSRQs. The solid line shows the best linear regression fit. in the synchrotron and IC νpLp SED planes indicate that the jet parameters might be correlated. We, therefore, explore …
Figure 5
Figure 5. Figure 5: An example of log-parabolic polynomial fitting of blazars. The left panel shows the BL Lac source ApLib (4FGL J1517.7-2422), whereas the right panel shows the FSRQ 3C273 (4FGL J1229.0+0202). 13 14 15 16 17 s 12.0 11.5 11.0 10.5 10.0 9.5 sFs 12.0 12.5 13.0 13.5 s 12.0 1…
Figure 6
Figure 6. Figure 6: The relationship between spectral peak frequency and peak flux of polynomial. The upper panels show the relationship between synchrotron peak frequency νs and synchrotron peak flux νsFs, whereas the lower panels show IC peak frequency νs and IC peak flux νcFc. BL Lacs …
Figure 7
Figure 7. Figure 7: The relationship between spectral frequency and luminosity of polynomial. The upper panels show the relationship between synchrotron frequency νs and synchrotron luminosity Ls, whereas the lower panels show the relationship between IC peak frequency νc and IC peak lumi…
Figure 8
Figure 8. Figure 8: The relationship between synchrotron peak frequency νs and IC peak frequency νc. BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the linear regression fit. Lacs, that jet parameters in BL Lacs must be inter￾nally linked a…
Figure 9
Figure 9. Figure 9: The relationship of synchrotron frequency νs with electron peak energy γ3p (upper panels) and parameter Bδ (lower panels), obtained by one-zone modeling. BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the best linear reg…
Figure 10
Figure 10. Figure 10: The relationship of synchrotron luminosity Ls with Doppler factor δ (upper panels), and source size R (lower panels), obtained by one-zone modeling. BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the best linear regress…
Figure 11
Figure 11. Figure 11: The relationship of particle energy γ3p with particle density ne (upper panels), and magnetic field B (lower panels). BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the best linear regression fit. the γ-ray emission. Fo…
Figure 12
Figure 12. Figure 12: The relationship of magnetic field B with Doppler factor δ (upper panels) and particle density ne (lower panels). BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the best linear regression fit. variable ambient condition…
Figure 13
Figure 13. Figure 13: The relationship between the peak frequency and spectral curvature. The upper panels show the relationship between synchrotron frequency νs and synchrotron curvature bs, whereas the lower panels show the relationship between IC frequency νc and IC curvature bc. BL Lac…
Figure 14
Figure 14. Figure 14: The intrinsic signature of stochastic acceleration, i.e., the relationship between EED peak energy γ3p and its curvature r. BL Lacs are shown by blue circles and FSRQs are shown by red circles. The solid lines represent the linear regression fit. 0.075 0.100 0.125 0.1…
Figure 15
Figure 15. Figure 15: The relationship between synchrotron spectral curvature bs and source electron curvature r. The SSC blazars are shown by blue circles and the EC blazars are shown by red circles. The solid lines represent the linear regression fit [PITH_FULL_IMAGE:figures/full_fig_p0…
Figure 16
Figure 16. Figure 16: SED Modeling of SSC Blazars [PITH_FULL_IMAGE:figures/full_fig_p026_16.png]
Figure 17
Figure 17. Figure 17: SED Modeling of EC Blazars [PITH_FULL_IMAGE:figures/full_fig_p030_17.png]

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Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.