Pith. sign in

REVIEW 5 major objections 6 minor 59 references

Testing Colour-magnitude Pattern as A Method in the Search for Changing-Look AGNs

T0 review · 5 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read Five of nine colour-selected candidates showed the type 2 to type 1 changing-look transition.

desk verdict Useful candidate screen, but the 'five of nine type 2→1' claim is overstated and the paper itself concedes the main caveat. read the letter →

arxiv 2412.12420 v1 pith:IVXT4SEG submitted 2024-12-17 astro-ph.GA

classification astro-ph.GA
keywords changing-lookAGNbluer-when-brightercolour-magnitudediagramvariabilitytype2broademissionlinesphotometricselectionaccretionmode
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

The paper tests a simple selection recipe: among AGNs previously classified as type 2, pick those whose optical colour gets bluer as they brighten. Following that pattern through recent photometric surveys produced 73 candidates, and spectroscopy of nine of them revealed five type 2 to type 1 transitions, including two already reported elsewhere. The authors argue that the bluer-when-brighter slope is an efficient and direct way to mine time-domain photometry for changing-look AGNs, and that adding flare-like amplitude and mid-infrared brightening can sharpen the selection further.

What carries the argument

The central object is the colour-magnitude diagram slope $k$ from the linear fit $z_g - z_r = k\,z_r + c$ to ZTF photometry. A type 2 AGN with a positive slope, meaning bluer when brighter, is a candidate; the paper uses $k \geq 0.1$ and then visually verifies the pattern. The companion diagnostic is the multi-band light-curve shape: confirmed transitions showed a flare-like brightening of $\Delta z_g \gtrsim 1$ mag and simultaneous mid-infrared brightening, with the W1-W2 colour moving from galaxy-like to AGN-like, while false positives had smaller optical changes and flat or decaying mid-infrared emission.

What would settle it

Obtain spectra of the remaining unobserved bluer-when-brighter candidates and compare the confirmed fraction with the 5-in-9 rate reported here; if the success rate drops well below that level, the method's efficiency does not generalise.

Watch

Extended reading notes

Core claim

The central claim is that a bluer-when-brighter colour-magnitude pattern in previously type 2 AGNs is a practical, low-cost selector of changing-look AGNs. Analysing recent $z_g-z_r$ versus $z_r$ photometry from ZTF for more than ten thousand SDSS type 2 AGNs, the paper selects 73 sources with the strongest such pattern; 13 of these were already known changing-look AGNs. New spectroscopy of nine candidates confirmed five (over 50 per cent) as type 2 to type 1 transitions, with three newly discovered. The failures, plus the three observed type 1 AGNs with redder-when-brighter slopes, show that the simple slope criterion alone is not perfect, but the colour pattern acts as a strong initial sieve.

Load-bearing premise

The bluer-when-brighter colour pattern is assumed to trace the same intrinsic accretion change that turns on broad emission lines, rather than variable dust extinction or dilution by the host galaxy.

Editorial extensions

If this is right

  • The selection pipeline can be re-run on any wide-field time-domain survey with two optical bands, producing large candidate lists for follow-up spectroscopy.
  • Adding a minimum blue-flare amplitude and a mid-infrared brightening condition should cut the false-positive rate seen in the four failed candidates.
  • The confirmed changing-look AGNs all have Eddington ratios near $10^{-2}$, supporting the picture that these transitions track a switch between accretion modes rather than extreme obscuration changes.
  • The same colour idea can be reversed, looking for redder-when-brighter type 1 AGNs as candidates for type 1 to type 2 transitions, though the first three observed sources did not change.

Reading between the lines

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

  • If the bluer-when-brighter slope is a genuine precursor of broad-line turn-on, next-generation time-domain surveys could pre-select AGNs for spectroscopy years before the transition is spectroscopically confirmed.
  • Three of the five confirmed sources already had weak broad H-alpha in their older SDSS spectra, so the method may partly be detecting host-galaxy dilution of a persistent broad-line region; high-spatial-resolution or spectropolarimetric observations could test whether the broad lines ever truly disappear.
  • The false positives show that a pure colour slope can arise without a type change; combining the slope with a threshold on the amplitude of the blue flare may convert the sieve into a more precise classifier, a test the authors say they plan.
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

5 major / 6 minor

Summary. The paper proposes a photometric pre-selection method for finding changing-look AGNs (CLAGNs). For SDSS type 2 AGNs, the authors fit the ZTF zg-zr colour versus zr magnitude relation and select sources with bluer-when-brighter slopes k >= 0.1, yielding 73 candidates after visual inspection. They obtained LJT/DOT spectra for nine of these candidates and report five CLAGNs (three newly confirmed here, two previously reported in Wang et al. 2024), and they observed three type 1 AGNs with redder-when-brighter slopes but found no type 1 to type 2 transitions. The paper also compares optical and MIR variability of successes and failures and proposes refined selection criteria for future follow-up.

Significance. If the interpretation is accepted, the method is valuable because it uses wide-field time-domain photometry to catch recent CL events that spectroscopic surveys may miss, and the 73-object candidate list is a useful resource. The paper's transparency about the limitations (the type 1.9 nature of three confirmed cases, the strong host-galaxy contribution, and the alternative dilution/EUV scenario) is commendable. However, these same limitations mean that the headline claim of five type 2 to type 1 transitions is not established, and the reported success rate cannot yet be read as a validated efficiency. The core photometric selection remains promising and the observational material is useful, but the claim needs to be reframed and quantified.

major comments (5)
  1. [Abstract; Section 5; Table 3] The abstract's claim that five of nine candidates 'showed the CL transition from type 2 to type 1' is stronger than the data support. Table 3 lists broad H-alpha detections in the SDSS spectra of J0751+4948, J1020+2437, and J1344+5126, and Section 5 concedes that these sources were mostly type 1.9, not pure type 2. The observed spectral evolution is therefore mainly a strengthening of an already-present broad H-alpha and the appearance of broad H-beta; this is a type 1.9 to type 1 change or an apparent CL phenomenon, not a type 2 to type 1 transition. Because the stated success rate is the central quantitative result, the abstract and Section 5 should be rewritten to state the actual measured changes and to separate pure type 2 to type 1 events from type 1.9 to type 1 events.
  2. [Section 5; Table 1] The count of five successes also includes J1150+3503, whose DOT spectrum is described in Section 4 as being of bad quality and whose CL identification is taken from Wang et al. (2024). The tally should be presented as three new confirmations plus two previously reported sources, one of which is not re-confirmed in this paper. The current phrasing ('two have already been identified as CLAGNs in Wang et al. 2024, and three are newly discovered by us') obscures this important distinction.
  3. [Section 5] The paper itself advances an alternative interpretation that undermines the method's specificity: it states that host-galaxy emission was strong or dominant in the SDSS spectra, and cites J. Li et al. (in preparation) for a scenario in which short-term EUV variations make an intrinsically type 1 AGN appear type 1.8/1.9 or type 2 at low continuum states, so that 'the CLAGNs have always been type 1.' Under this scenario, both the BWB colour pattern and the apparent broad-line turn-on are driven by continuum brightening diluting a persistent BLR, not by a genuine BLR state change. The paper does not provide host-subtracted or continuum-normalized broad-line luminosity measurements to distinguish these cases; the EWs in Table 3 are not sufficient because they depend on the continuum. The conclusion that the method 'can effectively find CLAGNs' should therefore be softened to 'CL-like spectral variability,' or the analysis should quantify how many of the five objects show intrinsic broad-line turn-on rather than dilution.
  4. [Section 4.1.3; Figure 5] J1203+6053 is one of the three newly confirmed CLAGNs, but its identification rests on a noisy DOT spectrum that captures only half of H-alpha, and no difference spectrum was obtained. The text says the presence of broad H-alpha and H-beta 'suggests' this is a CLAGN. Given that the overall success count depends on this object, the paper should either present a better-quality spectrum or explicitly classify J1203+6053 as a tentative CLAGN, and the success rate should be reported with confidence levels per object.
  5. [Section 2.2; Section 5] The selection thresholds (k >= 0.1, N_zr > 43, visual inspection, and k <= -0.7 for type 1) are chosen from the data distributions, and no comparison sample of type 2 AGNs without BWB patterns was observed. As a result, the 5/9 rate cannot be interpreted as an efficiency or specificity of the method; it is a proof-of-concept demonstration that the method can find CL-like objects. The phrase 'results prove that this rather simple method can effectively find CLAGNs' overstates what a nine-object pilot with hand-tuned thresholds can establish. A control sample or a blinded prediction would be needed to support an efficiency claim.
minor comments (6)
  1. [Section 2.2] The first sentence is garbled; the SQL query description ('We used the SQL query tool of the SDSS SkyServer have decent spectra...') needs rewriting.
  2. [Figure 2] The horizontal axis is labelled 'A values'; it should be 'k values'.
  3. [Section 5; Section 4.3] 'none CL-AGNs' should be 'non-CL-AGNs', 'greater than 50 per cent' is colloquial, and '~2000 day' should be '~2000 days'.
  4. [Section 3.2] The sentence 'the above systematic uncertainties were include' should read 'included'.
  5. [Table 1] The quoted k uncertainties (±0.001 to ±0.04) appear to come from simple linear fits that ignore the correlated nature of the magnitude errors; the fitting method should be stated briefly.
  6. [Section 4] The text says 'PYTHON QSO fitting code'; the language should be written as 'Python'.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: photometric BWB selection and spectroscopic confirmation are independent.

full rationale

The paper's derivation chain is not circular. The selection method fits a colour-magnitude slope k to archival ZTF light curves and selects type 2 AGN candidates with bluer-when-brighter behaviour. The claimed result, five of nine observed candidates showing type 2 to type 1 transitions, is then tested with new LJT and DOT spectra; the spectroscopic classification does not enter the photometric selection, so the success rate is an independent empirical outcome rather than a quantity forced by the fit. The self-citation to Zhu et al. (2024) supplies the motivating observation that CLAGNs show BWB patterns, but this premise is externally corroborated by earlier literature (Yang et al. 2018) and by the fact that 13 of the 73 candidates were already reported as CLAGNs by independent groups, and the current spectroscopic observations are new data. The paper explicitly frames the post-hoc comparison of confirmed versus non-confirmed sources (e.g., Δzg > 1 mag, MIR brightening) as a future refinement to be tested, not as the evidence for the method's success. The authors also openly concede that three of the four observed CLAGNs had broad Hα in their SDSS spectra and were mostly type 1.9, and they cite an in-preparation simulation for host-galaxy dilution as an alternative explanation; this weakens the physical interpretation of the type transitions but does not make the selection-to-confirmation logic circular. No equation is defined in terms of the target result, no fitted parameter is renamed as a prediction, and no load-bearing argument reduces to a self-citation chain. Central claim is self-contained against the new spectra.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The selection method depends on several hand-chosen cutoffs: k >= 0.1, k <= -0.7, minimum ZTF points 43 and 70, a one-day pairing window, per-source CM slope k, and subjective MIR outlier clipping. The physical axioms are standard AGN classification and the assumption that BWB color changes track intrinsic accretion changes rather than dust or obscuration; the latter is flagged as an interpretation in Section 5. There are no invented entities. The virial mass and Eddington ratio estimates use standard published scaling relations.

free parameters (6)
  • BWB slope threshold k >= 0.1 for type 2 candidates = 0.1
    Chosen as a starting point from the k distribution of SDSS type 2 AGNs; approximately 1.4 percent of the sample satisfies it, not derived from CL theory.
  • Redder-when-brighter threshold k <= -0.7 for type 1 candidates = -0.7
    Chosen for the type 1 AGN test; about 8.9 percent of type 1 AGNs satisfy it; no positive transitions found in three observed sources.
  • Minimum ZTF zr data points = 43 for type 2, 70 for type 1
    Read from the distribution of ZTF data points; affects sample size and the reliability of the per-source CM slope fit.
  • Time coincidence window for zg and zr magnitudes = 1 day
    Required magnitudes at the two bands be taken within one day to compute zg - zr; chosen operationally, not from a physical model.
  • Per-source CM slope k = Varies; examples in Table 1: 0.376, 0.679, 0.11, 0.401
    Linear fit of zg - zr = k * zr + c for each source; this is the central selection variable and is also used to discuss CL versus non-CL separation.
  • MIR outlier clipping = 1-2 obvious outliers per light curve
    Used in calculating Delta W1 and Delta W2 in Table 1; the choice of outliers is subjective and not precisely specified.
assumptions (5)
  • domain assumption Sources classified as galaxy with subclass AGN in SDSS DR16 are type 2 AGNs, and sources classified as QSO are type 1 AGNs.
    Used in Section 2.2 to define the parent samples; later analysis shows at least three of the confirmed sources were actually type 1.9, so this classification is imperfect.
  • domain assumption BWB color-magnitude behavior indicates intrinsic accretion or EUV changes, not variable obscuration or host-galaxy dilution.
    Section 5 interprets the CM slope physically and cites Yang et al. 2018; the same section also considers an alternative EUV-dilution scenario that could explain apparent CL behavior.
  • domain assumption Turn-on or strengthening of broad lines between SDSS and 2024 spectra is a genuine change in the AGN broad-line region emission.
    Core of CL identification; the paper notes host-galaxy contribution was strong or dominant in SDSS spectra, so part of the apparent change could be dilution of a persistent broad-line region.
  • standard math Vestergaard and Peterson 2006 virial mass formula and the Richards et al. 2006 bolometric correction apply to these sources.
    Used in Section 4 to estimate MBH and Eddington ratio; standard AGN scaling relations, but systematic uncertainties are large for noisy spectra.
  • domain assumption Photometric calibration differences among ZTF, CRTS, ATLAS, and WISE are small enough not to create artificial BWB slopes.
    Section 2 describes quality cuts (catflags = 0, chi < 4) but no explicit cross-survey calibration is performed; combining heterogeneous photometry could affect color slopes.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Testing Colour-magnitude Pattern as A Method in the Search for Changing-Look AGNs." pith.science (2026). https://pith.science/paper/IVXT4SEG

@misc{pith2026241212420,
  author       = {Pith},
  title        = {Pith review of: Testing Colour-magnitude Pattern as A Method in the Search for Changing-Look AGNs},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/IVXT4SEG}},
  note         = {Machine review of arXiv:2412.12420}
}
read the original abstract

We develop a simple method to search for changing-look (CL) active galactic nucleus (AGN) candidates, and conduct a test run. In this method, optical variations of AGNs are monitored and CL-AGNs may appear to have a pattern of being bluer when in brightening flare-like events. Applying this method, previously-classified type 2 AGNs that show the bluer-when-brighter (BWB) pattern are selected. Among more than ten thousands type 2 AGNs classified in the Sloan Digital Sky Survey (SDSS), we find 73 candidates with possibly the strongest BWB pattern. We note that 13 of them have previously been reported as CL-AGNs. We have observed nine candidates, and found that five among them showed the CL transition from type 2 to type 1. In addition, we also test extending the selection to previously-classified type 1 AGNs in the SDSS by finding sources with a possible redder-when-brighter pattern, but none of the three sources observed by us is found to show the transition from type 1 to type 2. We discuss the variation properties in both the success and failure cases, and plan to observe more candidates selected with the method. From the observational results, a detailed comparison between the CL-AGNs and none CL-AGNs will help quantitatively refine the selection criteria and in turn allow us to configure the general properties of CLAGNs.

Figures

Figures reproduced from arXiv: 2412.12420 by the authors.

Figure 1
Figure 1. Colour-magnitude diagrams for the four CLAGNs re￾ported in this work. From top to bottom: J0751+4948, J1020+2437, J1203+6053, and J1344+5126. Their k values determined from a linear fit (solid line in each panel) are respectively 0.376±0.004, 0.679±0.008, 0.110±0.009, and 0.401±0.003. 2.2 Target selection We used the SQL query tool of the SDSS SkyServer1 have decent spectra that cover the Hα and Hβ BELs, we further … view at source ↗
Figure 2
Figure 2. Distributions of the k values (the slopes) of the linear fits to each AGN’s CM variation data points. A dashed line at k = 0.1 is drawn, type 2 AGNs above which are checked as potential CLAGN candidates [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Optical and MIR light curves (left) and spectra (right) of J0751+4948. Two vertical dashed lines in the left panel mark the observation times of the SDSS and LJT spectra shown in the right upper panel. The two spectra are vertically shifted for clarity. In the right lower panel, a difference spectrum between the two spectra is shown.                      [PITH_FULL_IMAGE:figures/ful… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Same as [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]
Figure 5
Figure 5. Figure 5: Same as [PITH_FULL_IMAGE:figures/full_fig_p006_5.png]
Figure 6
Figure 6. Figure 6: Same as [PITH_FULL_IMAGE:figures/full_fig_p007_6.png]
Figure 7
Figure 7. Figure 7: Spectra of three type 1 AGNs we tested, displayed from top to bottom: J1127+2654, J1527+2233, and J1606+2903. For each source, a difference spectrum is made and shown. tablish some characteristics of CLAGNs for their variability aspect. It has been summarized from anal…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

59 extracted references · 4 canonical work pages

  1. [1]

    Ahumada R., et al., 2020, @doi [ ] 10.3847/1538-4365/ab929e , https://ui.adsabs.harvard.edu/abs/2020ApJS..249....3A 249, 3

  2. [2]

    Antonucci R., 1993, @doi [ ] 10.1146/annurev.aa.31.090193.002353 , https://ui.adsabs.harvard.edu/abs/1993ARA&A..31..473A 31, 473

  3. [3]

    J., 1999, @doi [ ] 10.1086/312114 , https://ui.adsabs.harvard.edu/abs/1999ApJ...519L.123A 519, L123

    Aretxaga I., Joguet B., Kunth D., Melnick J., Terlevich R. J., 1999, @doi [ ] 10.1086/312114 , https://ui.adsabs.harvard.edu/abs/1999ApJ...519L.123A 519, L123

  4. [4]

    C., et al., 2019, @doi [ ] 10.1088/1538-3873/aaecbe , https://ui.adsabs.harvard.edu/abs/2019PASP..131a8002B 131, 018002

    Bellm E. C., et al., 2019, @doi [ ] 10.1088/1538-3873/aaecbe , https://ui.adsabs.harvard.edu/abs/2019PASP..131a8002B 131, 018002

  5. [5]

    Cai Z.-Y., Wang J.-X., Zhu F.-F., Sun M.-Y., Gu W.-M., Cao X.-W., Yuan F., 2018, @doi [ ] 10.3847/1538-4357/aab091 , https://ui.adsabs.harvard.edu/abs/2018ApJ...855..117C 855, 117

  6. [6]

    D., Rudy R

    Cohen R. D., Rudy R. J., Puetter R. C., Ake T. B., Foltz C. B., 1986, @doi [ ] 10.1086/164758 , https://ui.adsabs.harvard.edu/abs/1986ApJ...311..135C 311, 135

  7. [7]

    D., et al., 2014, @doi [ ] 10.1088/0004-637X/796/2/134 , https://ui.adsabs.harvard.edu/abs/2014ApJ...796..134D 796, 134

    Denney K. D., et al., 2014, @doi [ ] 10.1088/0004-637X/796/2/134 , https://ui.adsabs.harvard.edu/abs/2014ApJ...796..134D 796, 134

  8. [8]

    C., 2019, @doi [ ] 10.1093/mnrasl/sly213 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.483L..17D 483, L17

    Dexter J., Begelman M. C., 2019, @doi [ ] 10.1093/mnrasl/sly213 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.483L..17D 483, L17

Show all 59 references
  1. [9]

    arXiv:2408.07335

    Dong Q., Zhang Z.-X., Gu W.-M., Sun M., Zheng Y.-G., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2408.07335 , https://ui.adsabs.harvard.edu/abs/2024arXiv240807335D p. arXiv:2408.07335

  2. [10]

    J., et al., 2009, @doi [ ] 10.1088/0004-637X/696/1/870 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..870D 696, 870

    Drake A. J., et al., 2009, @doi [ ] 10.1088/0004-637X/696/1/870 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..870D 696, 870

  3. [11]

    P., 2001, @doi [ ] 10.1086/321331 , https://ui.adsabs.harvard.edu/abs/2001ApJ...554..240E 554, 240

    Eracleous M., Halpern J. P., 2001, @doi [ ] 10.1086/321331 , https://ui.adsabs.harvard.edu/abs/2001ApJ...554..240E 554, 240

  4. [12]

    Feng J., Cao X., Li J.-w., Gu W.-M., 2021, @doi [ ] 10.3847/1538-4357/ac07a6 , https://ui.adsabs.harvard.edu/abs/2021ApJ...916...61F 916, 61

  5. [13]

    Frederick S., et al., 2019, @doi [ ] 10.3847/1538-4357/ab3a38 , https://ui.adsabs.harvard.edu/abs/2019ApJ...883...31F 883, 31

  6. [14]

    Gezari S., et al., 2017, @doi [ ] 10.3847/1538-4357/835/2/144 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..144G 835, 144

  7. [15]

    J., et al., 2020, @doi [ ] 10.1093/mnras/stz3244 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.4925G 491, 4925

    Graham M. J., et al., 2020, @doi [ ] 10.1093/mnras/stz3244 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.4925G 491, 4925

  8. [16]

    J., et al., 2022, @doi [ ] 10.3847/1538-4357/ac743f , https://ui.adsabs.harvard.edu/abs/2022ApJ...933..180G 933, 180

    Green P. J., et al., 2022, @doi [ ] 10.3847/1538-4357/ac743f , https://ui.adsabs.harvard.edu/abs/2022ApJ...933..180G 933, 180

  9. [17]

    Guo H., Shen Y., Wang S., 2018, PyQSOFit: Python code to fit the spectrum of quasars , Astrophysics Source Code Library, record ascl:1809.008 ( @eprint ascl 1809.008 )

  10. [18]

    arXiv:2408.00402

    Guo W.-J., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2408.00402 , https://ui.adsabs.harvard.edu/abs/2024arXiv240800402G p. arXiv:2408.00402

  11. [19]

    Guo W.-J., et al., 2024b, @doi [ ] 10.3847/1538-4365/ad118a , https://ui.adsabs.harvard.edu/abs/2024ApJS..270...26G 270, 26

  12. [20]

    Katebi R., et al., 2019, @doi [ ] 10.1093/mnras/stz1552 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.4057K 487, 4057

  13. [21]

    Kumar B., et al., 2018, Bulletin de la Societe Royale des Sciences de Liege, https://ui.adsabs.harvard.edu/abs/2018BSRSL..87...29K 87, 29

  14. [22]

    M., et al., 2015, @doi [ ] 10.1088/0004-637X/800/2/144 , https://ui.adsabs.harvard.edu/abs/2015ApJ...800..144L 800, 144

    LaMassa S. M., et al., 2015, @doi [ ] 10.1088/0004-637X/800/2/144 , https://ui.adsabs.harvard.edu/abs/2015ApJ...800..144L 800, 144

  15. [23]

    Lawrence A., 1987, @doi [ ] 10.1086/131989 , https://ui.adsabs.harvard.edu/abs/1987PASP...99..309L 99, 309

  16. [24]

    L \'o pez-Navas E., et al., 2022, @doi [ ] 10.1093/mnrasl/slac033 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.513L..57L 513, L57

  17. [26]

    L \'o pez-Navas E., et al., 2023b, @doi [ ] 10.1093/mnras/stad1893 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524..188L 524, 188

  18. [28]

    L., et al., 2016b, @doi [ ] 10.1093/mnras/stv2997 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.457..389M 457, 389

    MacLeod C. L., et al., 2016b, @doi [ ] 10.1093/mnras/stv2997 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.457..389M 457, 389

  19. [29]

    Mereghetti S., et al., 2021, @doi [Experimental Astronomy] 10.1007/s10686-021-09809-6 , https://ui.adsabs.harvard.edu/abs/2021ExA....52..309M 52, 309

  20. [30]

    Noda H., Done C., 2018, @doi [ ] 10.1093/mnras/sty2032 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.3898N 480, 3898

  21. [31]

    Panda S., \'S niegowska M., 2024, @doi [ ] 10.3847/1538-4365/ad344f , https://ui.adsabs.harvard.edu/abs/2024ApJS..272...13P 272, 13

  22. [32]

    Planck Collaboration et al., 2020, @doi [ ] 10.1051/0004-6361/201833910 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A...6P 641, A6

  23. [33]

    arXiv:2211.05132

    Ricci C., Trakhtenbrot B., 2022, @doi [arXiv e-prints] 10.48550/arXiv.2211.05132 , https://ui.adsabs.harvard.edu/abs/2022arXiv221105132R p. arXiv:2211.05132

  24. [34]

    T., et al., 2006, @doi [ ] 10.1086/506525 , https://ui.adsabs.harvard.edu/abs/2006ApJS..166..470R 166, 470

    Richards G. T., et al., 2006, @doi [ ] 10.1086/506525 , https://ui.adsabs.harvard.edu/abs/2006ApJS..166..470R 166, 470

  25. [35]

    P., et al., 2018, @doi [ ] 10.1093/mnras/sty2002 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.4468R 480, 4468

    Ross N. P., et al., 2018, @doi [ ] 10.1093/mnras/sty2002 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.4468R 480, 4468

  26. [36]

    P., Graham M

    Ross N. P., Graham M. J., Calderone G., Ford K. E. S., McKernan B., Stern D., 2020, @doi [ ] 10.1093/mnras/staa2415 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.2339R 498, 2339

  27. [37]

    J., et al., 2016, @doi [ ] 10.3847/0004-637X/826/2/188 , https://ui.adsabs.harvard.edu/abs/2016ApJ...826..188R 826, 188

    Ruan J. J., et al., 2016, @doi [ ] 10.3847/0004-637X/826/2/188 , https://ui.adsabs.harvard.edu/abs/2016ApJ...826..188R 826, 188

  28. [38]

    J., Anderson S

    Ruan J. J., Anderson S. F., Eracleous M., Green P. J., Haggard D., MacLeod C. L., Runnoe J. C., Sobolewska M. A., 2019, @doi [ ] 10.3847/1538-4357/ab3c1a , https://ui.adsabs.harvard.edu/abs/2019ApJ...883...76R 883, 76

  29. [39]

    C., et al., 2016, @doi [ ] 10.1093/mnras/stv2385 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.455.1691R 455, 1691

    Runnoe J. C., et al., 2016, @doi [ ] 10.1093/mnras/stv2385 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.455.1691R 455, 1691

  30. [40]

    I., Sunyaev R

    Shakura N. I., Sunyaev R. A., 1973, , https://ui.adsabs.harvard.edu/abs/1973A&A....24..337S 24, 337

  31. [41]

    J., et al., 2014, @doi [ ] 10.1088/0004-637X/788/1/48 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...48S 788, 48

    Shappee B. J., et al., 2014, @doi [ ] 10.1088/0004-637X/788/1/48 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...48S 788, 48

  32. [42]

    Sheng Z., Wang T., Jiang N., Yang C., Yan L., Dou L., Peng B., 2017, @doi [ ] 10.3847/2041-8213/aa85de , https://ui.adsabs.harvard.edu/abs/2017ApJ...846L...7S 846, L7

  33. [43]

    Sheng Z., et al., 2020, @doi [ ] 10.3847/1538-4357/ab5af9 , https://ui.adsabs.harvard.edu/abs/2020ApJ...889...46S 889, 46

  34. [44]

    Sniegowska M., Czerny B., Bon E., Bon N., 2020, @doi [ ] 10.1051/0004-6361/202038575 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A.167S 641, A167

  35. [45]

    Stern D., et al., 2018, @doi [ ] 10.3847/1538-4357/aac726 , https://ui.adsabs.harvard.edu/abs/2018ApJ...864...27S 864, 27

  36. [46]

    A., Wilson A

    Storchi-Bergmann T., Baldwin J. A., Wilson A. S., 1993, @doi [ ] 10.1086/186867 , https://ui.adsabs.harvard.edu/abs/1993ApJ...410L..11S 410, L11

  37. [47]

    Tadhunter C., 2008, @doi [ ] 10.1016/j.newar.2008.06.004 , https://ui.adsabs.harvard.edu/abs/2008NewAR..52..227T 52, 227

  38. [48]

    E., Osterbrock D

    Tohline J. E., Osterbrock D. E., 1976, @doi [ ] 10.1086/182317 , https://ui.adsabs.harvard.edu/abs/1976ApJ...210L.117T 210, L117

  39. [49]

    L., et al., 2018, @doi [ ] 10.1088/1538-3873/aabadf , https://ui.adsabs.harvard.edu/abs/2018PASP..130f4505T 130, 064505

    Tonry J. L., et al., 2018, @doi [ ] 10.1088/1538-3873/aabadf , https://ui.adsabs.harvard.edu/abs/2018PASP..130f4505T 130, 064505

  40. [50]

    Trakhtenbrot B., et al., 2019, @doi [ ] 10.3847/1538-4357/ab39e4 , https://ui.adsabs.harvard.edu/abs/2019ApJ...883...94T 883, 94

  41. [51]

    M., Padovani P., 1995, @doi [ ] 10.1086/133630 , https://ui.adsabs.harvard.edu/abs/1995PASP..107..803U 107, 803

    Urry C. M., Padovani P., 1995, @doi [ ] 10.1086/133630 , https://ui.adsabs.harvard.edu/abs/1995PASP..107..803U 107, 803

  42. [52]

    M., 2006, @doi [ ] 10.1086/500572 , https://ui.adsabs.harvard.edu/abs/2006ApJ...641..689V 641, 689

    Vestergaard M., Peterson B. M., 2006, @doi [ ] 10.1086/500572 , https://ui.adsabs.harvard.edu/abs/2006ApJ...641..689V 641, 689

  43. [53]

    Wang C.-J., et al., 2019, @doi [Research in Astronomy and Astrophysics] 10.1088/1674-4527/19/10/149 , https://ui.adsabs.harvard.edu/abs/2019RAA....19..149W 19, 149

  44. [54]

    K., Brink T

    Wang J., Zheng W. K., Brink T. G., Xu D. W., Filippenko A. V., Gao C., Xie C. H., Wei J. Y., 2023, @doi [ ] 10.3847/1538-4357/acf5e0 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956..137W 956, 137

  45. [55]

    Wang S., et al., 2024, @doi [ ] 10.3847/1538-4357/ad3049 , https://ui.adsabs.harvard.edu/abs/2024ApJ...966..128W 966, 128

  46. [56]

    Winkler H., 1992, @doi [ ] 10.1093/mnras/257.4.677 , https://ui.adsabs.harvard.edu/abs/1992MNRAS.257..677W 257, 677

  47. [57]

    L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    Wright E. L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

  48. [58]

    Yang Q., et al., 2018, @doi [ ] 10.3847/1538-4357/aaca3a , https://ui.adsabs.harvard.edu/abs/2018ApJ...862..109Y 862, 109

  49. [59]

    Zeltyn G., et al., 2022, @doi [ ] 10.3847/2041-8213/ac9a47 , https://ui.adsabs.harvard.edu/abs/2022ApJ...939L..16Z 939, L16

  50. [60]

    Zeltyn G., et al., 2024, @doi [ ] 10.3847/1538-4357/ad2f30 , https://ui.adsabs.harvard.edu/abs/2024ApJ...966...85Z 966, 85

  51. [61]

    Zhu L.-T., Li J., Wang Z., Zhang J.-J., 2024, @doi [ ] 10.1093/mnras/stae1044 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.530.3538Z 530, 3538

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.