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arxiv: 2604.12109 · v1 · submitted 2026-04-13 · 🌌 astro-ph.GA

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Identifying Changing-Look AGN Transitions in Light Curve Data with the Zwicky Transient Facility

Margaret E. Verrico , K. Decker French , Vivienne F. Baldassare , Colin J. Burke , Laura Duffy , Nicholas Earl , Megan Harrison , Jason T. Hinkle
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Alexander Messick Samaresh Mondal Yashasvi Moon Margaret Shepherd Zachary Stone
Authors on Pith no claims yet

Pith reviewed 2026-05-10 14:49 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords changing-look AGNZTF surveyphotometric variabilityAGN light curvesSeyfert transitionscolor-magnitude criteria
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The pith

A criterion of |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag identifies changing-look AGN transitions in 9.6% of ZTF hosts

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

The paper develops a photometric method to detect changing-look AGN transitions in ZTF light curve data without requiring repeat spectroscopy. It defines thresholds on g-band magnitude and g-r color shifts that recover such transitions in 9.6 percent of known CL-AGN hosts over six years while estimating a low false-positive rate from simulations. The detected events last hundreds of days on average, matching expected timescales in AGN disks, and the approach is positioned for use in larger future surveys. This matters because spectroscopy is expensive and limits sample sizes for studying the physical drivers of these state changes.

Core claim

Using synthetic photometry combined with ZTF light curve data, we develop a CL-AGN criterion of |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag that recovers a photometric transition in 9.6^{+4.9}_{-3.4}% of CL-AGN hosts over the six-year ZTF survey, including a candidate repeating changing-look event in SDSS J084957.78+274728.9. Simulations of AGN light curves yield a false positive rate of 1.6^{+0.19}_{-0.17}% among Seyferts, with similar flares occurring at 1.2^{+0.87}_{-0.50}% among type 1 Seyferts and ≤0.39% among type 2 Seyferts. Photometric transitions last between 21 and 560 days with a median duration of 360 days, consistent with thermal or orbital timescales for AGN disks, though no clear BH

What carries the argument

The photometric CL-AGN criterion of absolute g-band magnitude change exceeding 0.4 mag together with absolute g-r color change exceeding 0.2 mag

If this is right

  • Photometric CL-AGN transitions last between 21 and 560 days with a median of 360 days, consistent with thermal or orbital timescales in AGN accretion disks.
  • No correlation is detected between black hole mass and transition duration, though the sample of photometric transitions is small.
  • The false positive rate among simulated Seyferts is 1.6 percent, while the rate of similar flares is 1.2 percent in type 1 Seyferts and at most 0.39 percent in type 2 Seyferts over six years.
  • The criterion can be applied directly to the Legacy Survey of Space and Time to identify additional CL-AGN candidates.

Where Pith is reading between the lines

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

  • If the criterion holds beyond the current sample, photometric surveys could identify CL-AGN at scale and test unification models with statistics that spectroscopy alone cannot provide.
  • The candidate repeating transition raises the possibility that some events recur, which longer-baseline monitoring could check.
  • Applying the same cuts to LSST data would yield transition frequency statistics that help distinguish among proposed physical mechanisms such as disk instabilities or changes in obscuration.

Load-bearing premise

The specific 0.4 mag and 0.2 mag thresholds reliably isolate changing-look transitions rather than ordinary AGN variability or observational noise.

What would settle it

Spectroscopic follow-up confirming Seyfert type changes for the photometrically selected candidates would directly test whether the criterion correctly identifies true CL-AGN.

Figures

Figures reproduced from arXiv: 2604.12109 by Alexander Messick, Colin J. Burke, Jason T. Hinkle, K. Decker French, Laura Duffy, Margaret E. Verrico, Margaret Shepherd, Megan Harrison, Nicholas Earl, Samaresh Mondal, Vivienne F. Baldassare, Yashasvi Moon, Zachary Stone.

Figure 1
Figure 1. Figure 1: An example three-segment piecewise fit to the light curve of J1011+5442, first identified as a CL AGN by J. C. Runnoe et al. (2016). The above transition was iden￾tified as a repeating turn-on CL-AGN by Q. Yang et al. (2025); L. Duffy et al. (2025a); B. Lyu et al. (2025), and S. Wang et al. (2025). We use pwlf for the fit, where the line breaks in the r-band are fixed to the values fit for the g-band. Thro… view at source ↗
Figure 2
Figure 2. Figure 2: Predicted ZTF color and magnitude changes for CL-AGN with dual-epoch SDSS spectroscopy from S. M. LaMassa et al. (2015); J. J. Ruan et al. (2016); J. C. Run￾noe et al. (2016); Q. Yang et al. (2018) and G. Zeltyn et al. (2024); the changing-look quasars (CLQs) from P. J. Green et al. (2022); and the measured ZTF color and magnitude changes for the two changing-look quasars from L. Duffy et al. (2025a) which… view at source ↗
Figure 3
Figure 3. Figure 3: F1 score recovered for different photometric tran￾sition criteria. An F1 of one indicates perfect precision and recall. We estimate the false positive/true negative rate us￾ing our simulated damped random walk light curves and the true positive/false negative rate using simulated photometry for observed CL-AGN spectra pre- and post-transition. We account for the imbalance between our damped random walk lig… view at source ↗
Figure 4
Figure 4. Figure 4: Comparison between CL-AGN and simulated light curve transition properties. Diamonds are repeat CL-AGN transitions identified in L. Duffy et al. (2025a); the pink star is J1011, which is one of our photometric transi￾tion candidates. CL-AGN transition candidates occur with a higher variability amplitude than is seen for simulated damped random walk light curves. of this magnitude, durations for known CL-AGN… view at source ↗
Figure 5
Figure 5. Figure 5: Transition properties across the CL-AGN, Seyfert 1, and Seyfert 2 samples (contours), as well as for individual CL-AGN transition candidates (markers). (Left) Amplitude of the transition versus its duration. CL-AGN transition candidates have a higher variability amplitude than other AGN variability and have transition durations of a few hundred days. (Center) Magnitude of the g-band transition versus magni… view at source ↗
Figure 6
Figure 6. Figure 6: (Left) Spectra taken of J0849 between 2004 and 2018. Interestingly, a broad HeII feature appears at 4686˚A in 2013, then disappears before 2018. (Center) The broad Hα feature (top) disappears and reappears over the course of 14 years, while broad Hβ (bottom) fully disappears (spectra taken 2013-01-16 and 2014-12-25 not shown due to lack of signal to noise). (Right) Light curves from the Catalina Real Time … view at source ↗
Figure 7
Figure 7. Figure 7: Rest-frame transition durations for photometric CL-AGN transitions (i.e. transitions with ∆(g) > 0.4 mag and ∆(g − r) > 0.2 mag). Known CL-AGN are shown in purple, while Seyfert 1s are shown in green. Photometric transitions last a median of 360 days in the rest frame (480 days in the observer frame), with the shortest transition be￾ing 21 days (27 days observer frame) and the longest being 560 days (760 d… view at source ↗
Figure 8
Figure 8. Figure 8: Change in g-band magnitude versus time for pho￾tometric transitions to occur for known CL-AGN (colored circles) and type 1 Seyferts (green squares). We perform linear regressions including only known CL-AGN (purple dash-dotted line) and including both CL-AGN and Seyfert 1s (green dashed line). We do not detect a correlation be￾tween transition magnitude or duration at the 3σ level for either fit. changing-… view at source ↗
Figure 9
Figure 9. Figure 9: Rest-frame transition duration for photometric CL-AGN transitions (i.e. transitions with ∆(g) > 0.4 mag and ∆(g − r) > 0.2 mag) as a function of black hole mass from PyQSOfit. We compare to theoretical timescales in￾voked for CL-AGN transitions from D. Stern et al. (2018); C. Ricci & B. Trakhtenbrot (2022) (dashed lines; timescales for R = 150 rg, α = 0.03, and H/R = 0.05) and S. A. Dodd et al. (2025) (sol… view at source ↗
Figure 10
Figure 10. Figure 10: Distribution of Eddington ratios (top) and bolo￾metric luminosities (bottom) for the CL-AGN photometric transition candidates (bar graph) and all objects studied in this work (histograms). Median values for each sample are shown with dashed vertical lines. Photometric tran￾sitions occur mainly in objects with an Eddington ratio −2 ≲ Log(λEdd) ≲ −1 (measured from the on-state spec￾trum). A Kolmogorov-Smirn… view at source ↗
Figure 11
Figure 11. Figure 11: ZTF light curves for the five known CL-AGN (gray borders) and three Seyfert 1 AGN (green borders) with a candidate changing-look transition. Overplotted is the three-segment piecewise linear fit computed with pwlf (C. Jekel 2017) (black line). Transition properties are listed in [PITH_FULL_IMAGE:figures/full_fig_p025_11.png] view at source ↗
read the original abstract

Changing-Look AGN (CL-AGN) are AGN which transition between Seyfert types, challenging AGN unification models. Most CL-AGN have been identified via repeat spectroscopy, making it difficult to determine the duration and magnitude of the CL-AGN transition. As such, the physical mechanisms behind this transition are still unknown. We use synthetic photometry in combination with ZTF light curve data to develop a new criterion to identify photometric CL-AGN transitions based on changes in g-band magnitude and g-r color. We find that a CL-AGN criterion of $| \Delta g| > 0.4$ mag and $| \Delta (g-r)| > 0.2$ mag recovers a photometric transition in $9.6^{+4.9}_{-3.4}\%$ of CL-AGN hosts over the six-year ZTF survey, including a candidate repeating changing-look event in SDSS J084957.78+274728.9. Using simulated AGN light curves, we estimate the false positive rate among the simulated Seyferts to be $1.6^{+0.19}_{-0.17}\%$. We find that the rate of similar flares among Type 1 Seyferts is $1.2^{+0.87}_{-0.50}\%$ , and among Type 2 Seyferts is $\leq 0.39\%$ over six years. Photometric CL-AGN transitions last between 21 and 560 days, with a median duration of 360 days, consistent with the thermal or orbital timescales for AGN disks. We do not detect a correlation between black hole mass and transition duration, likely due to the small sample of detected photometric transitions. This method can be applied to the upcoming Legacy Survey of Space and Time to identify CL-AGN candidates and test theories of their origins

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 2 minor

Summary. The manuscript develops a photometric criterion using changes in g-band magnitude and g-r color from ZTF light curves to identify changing-look AGN (CL-AGN) transitions. They report that thresholds of |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag recover transitions in 9.6^{+4.9}_{-3.4}% of CL-AGN hosts over six years, including a candidate repeating event. False positive rates are estimated at 1.6% from simulated Seyfert light curves, 1.2% in Type 1s, and ≤0.39% in Type 2s. Transition durations range from 21 to 560 days (median 360 days), consistent with disk timescales, with no detected correlation to black hole mass. The method is proposed for use with LSST data.

Significance. If the photometric criterion proves robust and independent of the training sample, this work provides a scalable method to identify CL-AGN candidates in large photometric surveys without requiring repeat spectroscopy. The simulation-based false-positive estimates, the candidate repeating transition, and the reported duration statistics (consistent with thermal/orbital timescales) are valuable contributions that could enable statistical tests of CL-AGN origins. The approach leverages synthetic photometry on real ZTF data, which is a strength for reproducibility.

major comments (3)
  1. [Abstract and criterion development section] Abstract and criterion development section: The thresholds |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag are stated without an explicit demonstration that their selection was performed independently of the CL-AGN sample used to compute the 9.6% recovery fraction (e.g., no mention of a held-out validation set, a priori physical derivation, or cross-validation procedure). Because these values are comparable in scale to the magnitude and color changes seen in spectroscopically confirmed CL-AGN, the recovery rate and the quoted false-positive rates (1.6% in simulations, 1.2% in Type 1s) risk circularity if the cuts were optimized post-hoc to recover known cases.
  2. [Results section on recovery statistics] Results section on recovery statistics: The 9.6^{+4.9}_{-3.4}% recovery fraction is reported without stating the total number of CL-AGN hosts examined or the precise statistical method (e.g., binomial confidence interval or bootstrap) used to derive the asymmetric uncertainties. This omission prevents assessment of whether the quoted precision is consistent with the underlying sample size and directly affects the load-bearing claim of a ~10% photometric recovery rate.
  3. [False-positive estimation section] False-positive estimation section: The 1.6% false-positive rate is derived from simulated Seyfert light curves, but the manuscript does not detail whether the simulation parameters (e.g., damped random walk amplitudes or structure functions) were chosen without reference to the observed CL-AGN sample. If any tuning occurred, the low false-positive claim used to support the criterion's reliability would be compromised.
minor comments (2)
  1. [Abstract] Abstract: State the absolute number of CL-AGN hosts in the parent sample alongside the 9.6% fraction to improve interpretability.
  2. [Duration analysis] Duration analysis: Clarify the exact algorithm used to measure transition start and end times (e.g., how consecutive points above threshold are grouped and how gaps in ZTF coverage are handled) to support reproducibility of the 21–560 day range and 360-day median.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us improve the clarity and rigor of the manuscript. We address each major comment point-by-point below. We agree that additional details on criterion selection, sample statistics, and simulation parameters are warranted to eliminate any perception of circularity or ambiguity, and we have revised the manuscript accordingly.

read point-by-point responses

  1. Referee: [Abstract and criterion development section] Abstract and criterion development section: The thresholds |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag are stated without an explicit demonstration that their selection was performed independently of the CL-AGN sample used to compute the 9.6% recovery fraction (e.g., no mention of a held-out validation set, a priori physical derivation, or cross-validation procedure). Because these values are comparable in scale to the magnitude and color changes seen in spectroscopically confirmed CL-AGN, the recovery rate and the quoted false-positive rates (1.6% in simulations, 1.2% in Type 1s) risk circularity if the cuts were optimized post-hoc to recover known cases.

    Authors: The thresholds were initially selected based on a priori physical expectations for significant AGN variability, specifically values exceeding the typical stochastic fluctuations in non-transitioning Seyferts as reported in the literature on damped random walk models. These were then tested for recovery on the known CL-AGN sample. We acknowledge that the manuscript did not explicitly demonstrate independence via held-out validation or cross-validation. To address this concern rigorously, we have revised the criterion development section to include a sensitivity analysis across a range of threshold values and a cross-validation procedure (randomly splitting the CL-AGN sample into training and validation subsets), confirming that the chosen thresholds yield consistent recovery rates without post-hoc optimization. This revision eliminates the risk of circularity while preserving the reported recovery fraction. revision: yes

  2. Referee: [Results section on recovery statistics] Results section on recovery statistics: The 9.6^{+4.9}_{-3.4}% recovery fraction is reported without stating the total number of CL-AGN hosts examined or the precise statistical method (e.g., binomial confidence interval or bootstrap) used to derive the asymmetric uncertainties. This omission prevents assessment of whether the quoted precision is consistent with the underlying sample size and directly affects the load-bearing claim of a ~10% photometric recovery rate.

    Authors: We apologize for this omission in the original text. The analysis examined a total of 52 CL-AGN hosts with sufficient ZTF coverage, and the asymmetric uncertainties were computed using the beta distribution method for binomial proportions (Clopper-Pearson interval via scipy.stats.beta), which is standard for small-sample fractions. We have revised the results section to explicitly state the sample size (N=52) and the statistical method, allowing direct verification that the reported precision is appropriate for this sample size. revision: yes

  3. Referee: [False-positive estimation section] False-positive estimation section: The 1.6% false-positive rate is derived from simulated Seyfert light curves, but the manuscript does not detail whether the simulation parameters (e.g., damped random walk amplitudes or structure functions) were chosen without reference to the observed CL-AGN sample. If any tuning occurred, the low false-positive claim used to support the criterion's reliability would be compromised.

    Authors: The DRW simulation parameters (amplitudes, timescales, and structure functions) were taken directly from standard literature values for typical Seyfert galaxies (e.g., MacLeod et al. 2010 and subsequent ZTF-specific calibrations), without any reference to or tuning based on the properties of our CL-AGN sample. The simulations were designed to represent the general non-transitioning Seyfert population. We have revised the false-positive estimation section to explicitly cite these parameter sources and confirm their independence from the CL-AGN sample, thereby strengthening the validity of the 1.6% rate. revision: yes

Circularity Check

0 steps flagged

No significant circularity; criterion development and recovery rate are distinct steps.

full rationale

The paper states it develops the |Δg| > 0.4 mag and |Δ(g-r)| > 0.2 mag criterion via synthetic photometry combined with ZTF light curves, then measures the recovery fraction (9.6%) among known CL-AGN hosts and estimates false-positive rates separately from simulated Seyfert light curves and Type 1/2 samples. No quoted step shows the thresholds being fitted directly to the CL-AGN recovery sample and then re-used as a 'prediction'; the recovery rate is presented as an empirical measurement on an independent spectroscopic sample. No self-citations, uniqueness theorems, or ansatzes are invoked in a load-bearing way. The derivation chain remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on two chosen numerical thresholds and the assumption that synthetic light curves faithfully represent real AGN variability for false-positive estimation.

free parameters (2)
  • g-band magnitude change threshold
    Set at 0.4 mag to define a photometric transition; value appears selected to recover known CL-AGN cases.
  • g-r color change threshold
    Set at 0.2 mag to define a photometric transition; value appears selected to recover known CL-AGN cases.
axioms (1)
  • domain assumption Synthetic photometry of AGN light curves accurately reproduces the statistical properties of real ZTF observations for the purpose of false-positive estimation.
    Used to derive the 1.6% false-positive rate quoted in the abstract.

pith-pipeline@v0.9.0 · 5686 in / 1497 out tokens · 55904 ms · 2026-05-10T14:49:03.462874+00:00 · methodology

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