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Six years of ZTF observations yield catalogs of 28,504 AGN flares and 1,984 high-confidence events.

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2026-05-19 02:41 UTC

load-bearing objection This paper releases two new AGN flare catalogs from ZTF DR23 using standard detection methods, but offers little quantitative validation of the detections. the 2 major comments →

arxiv 2507.20232 v3 submitted 2025-07-27 astro-ph.HE astro-ph.GA

A Systematic Search for Active Galactic Nucleus Flares in ZTF Data Release 23

Lei He , Zheng-Yan Liu , Rui Niu , Ming-Shen Zhou , Pu-Run Zou , Bing-Zhou Gao , Run-Duo Liang , Liang-Gui Zhu
show 8 more authors
Jian-Min Wang Ning Jiang Zhen-Yi Cai Ji-an Jiang Zi-Gao Dai Ye-Fei Yuan Yong-Jie Chen Wen Zhao
This is my paper
classification astro-ph.HE astro-ph.GA
keywords AGN flaresZTFBayesian blocksGaussian processestransient catalogsactive galactic nucleivariabilitytime-domain astronomy
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper performs a systematic search for extreme outbursts in active galactic nuclei by processing six years of Zwicky Transient Facility Data Release 23 light curves for a sample of well-sampled AGNs and candidates. It applies Bayesian blocks and Gaussian processes to flag deviations from typical stochastic variability, producing a coarse catalog of 28,504 flares and a refined catalog of 1,984 higher-confidence cases after stricter selection. The work examines the flares' spatial and temporal properties, their links to host AGN types, and possible associations with supernovae, tidal disruption events, blazars, or rarer phenomena. The resulting public catalogs supply a ready resource for investigating energetic transient processes in AGNs.

Core claim

Using six years of data from Zwicky Transient Facility Data Release 23, the authors construct the AGN Flare Coarse Catalog containing 28,504 flares identified via Bayesian blocks and Gaussian Processes, and the AGN Flare Refined Catalog comprising 1,984 high-confidence flares selected using stricter criteria. Analysis of these events reveals their spatial distribution, temporal characteristics, host AGN types, and potential origins, with some linked to known supernovae, tidal disruption events, blazars, binary black hole mergers, or microlensing.

What carries the argument

Bayesian blocks and Gaussian Processes applied to AGN light curves to isolate flares as extreme deviations from typical stochastic variability.

Load-bearing premise

The detections from Bayesian blocks and Gaussian processes reliably separate genuine AGN flares from noise, artifacts, or non-AGN transients within the sampled light curves.

What would settle it

Follow-up spectroscopy or multi-wavelength monitoring that shows a large fraction of the 1,984 refined flares lack AGN activity or match known non-AGN transient classes instead.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Some flares associate with known supernovae, tidal disruption events, or blazars.
  • A smaller subset may connect to binary black hole mergers or microlensing events.
  • The catalogs support statistical study of flare rates, durations, and host-galaxy properties.
  • Public release enables community-wide follow-up and cross-survey comparisons.

Where Pith is reading between the lines

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

  • Cross-matching the refined catalog with future surveys such as LSST could test whether flare rates scale with AGN accretion state.
  • Time-resolved spectroscopy of a subset of events would distinguish between accretion-disk instabilities and external triggers.
  • Statistical comparison of flare timing with radio or X-ray monitoring could reveal whether the outbursts coincide with jet activity.
  • Machine-learning re-analysis of the same light curves might quantify completeness and purity of the current selection.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 3 minor

Summary. The manuscript presents a systematic search for AGN flares using six years of ZTF Data Release 23 photometry on a sample of well-sampled AGNs and AGN candidates. It constructs the AGN Flare Coarse Catalog (AGNFCC) containing 28,504 flares identified with Bayesian blocks and Gaussian Processes, and the AGN Flare Refined Catalog (AGNFRC) with 1,984 high-confidence flares selected via stricter criteria. The work examines spatial distributions, temporal properties, host AGN types, and possible physical origins, noting associations with supernovae, tidal disruption events, blazars, and a few candidate links to binary black hole mergers or microlensing. The catalogs are released publicly via GitHub.

Significance. If the detections hold, this is a useful catalog paper that supplies a large, public resource for time-domain studies of AGN transients. The adoption of standard Bayesian blocks and Gaussian Process techniques for variability detection is appropriate and reproducible. Public data release is a clear strength that enables community follow-up and cross-survey comparisons.

major comments (2)
  1. [Methods] Methods section on flare detection: no quantitative validation is provided for the Bayesian blocks plus Gaussian Process pipeline, such as false-positive rates, recovery fractions from simulated light curves, or cross-matches to independent transient surveys. This directly affects in the reported sizes of both the AGNFCC (28,504) and AGNFRC (1,984).
  2. [Catalog Construction] Selection of the refined catalog: the stricter criteria that reduce the sample from 28,504 to 1,984 flares are not given with explicit numerical thresholds or a step-by-step breakdown, limiting reproducibility and assessment of selection biases.
minor comments (3)
  1. [Abstract] Abstract: the parent sample size (number of AGNs/AGN candidates searched) is not stated, which would help readers interpret the overall flare detection rate.
  2. [Discussion] Discussion: associations with rare events such as binary black hole mergers or microlensing are mentioned but lack quantitative details on the matching criteria or probability estimates.
  3. [Figures] Figures: ensure all light-curve panels include error bars, time baselines, and consistent y-axis scaling for easy visual comparison across examples.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive review and for recognizing the potential utility of the public AGN flare catalogs. We address the two major comments below and have revised the manuscript to strengthen the presentation of methods and catalog construction.

read point-by-point responses

  1. Referee: [Methods] Methods section on flare detection: no quantitative validation is provided for the Bayesian blocks plus Gaussian Process pipeline, such as false-positive rates, recovery fractions from simulated light curves, or cross-matches to independent transient surveys. This directly affects in the reported sizes of both the AGNFCC (28,504) and AGNFRC (1,984).

    Authors: We agree that quantitative validation metrics were not included in the original submission. In the revised manuscript we have added a dedicated validation subsection (now Section 3.3) that reports recovery fractions and false-positive rates obtained by injecting synthetic flares into simulated AGN light curves generated with the same sampling and noise properties as the ZTF data. We also include a limited cross-match analysis against publicly available transient catalogs from ASAS-SN and ATLAS. These additions supply the requested quantitative assessment and allow readers to evaluate the reliability of the reported catalog sizes. revision: yes

  2. Referee: [Catalog Construction] Selection of the refined catalog: the stricter criteria that reduce the sample from 28,504 to 1,984 flares are not given with explicit numerical thresholds or a step-by-step breakdown, limiting reproducibility and assessment of selection biases.

    Authors: We acknowledge that the original text described the refined-catalog selection only in general terms. The revised manuscript now contains an expanded Section 4.2 that provides a numbered, step-by-step breakdown of the filtering process together with the explicit numerical thresholds applied at each stage (e.g., minimum significance, minimum duration, and amplitude cuts). A new summary table lists these thresholds, and we briefly discuss the selection biases that may be introduced. These changes directly improve reproducibility. revision: yes

Circularity Check

0 steps flagged

No significant circularity; observational catalog from public data using standard methods

full rationale

The paper constructs two flare catalogs (AGNFCC and AGNFRC) from six years of ZTF DR23 public survey data by applying established Bayesian blocks and Gaussian process techniques to a pre-defined sample of well-sampled AGNs and candidates. No derivation chain reduces to self-definition, fitted inputs renamed as predictions, or load-bearing self-citations. The central output is an empirical catalog with explicit selection criteria, counts, and cross-matches; detection reliability is an external validation issue rather than an internal circularity flaw. The work is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on standard time-series change-point detection methods and the assumption that the input AGN sample is well-characterized; no new physical entities or ad-hoc constants are introduced in the abstract.

axioms (1)
  • domain assumption Bayesian blocks and Gaussian processes can be applied directly to ZTF light curves to identify statistically significant flares.
    Invoked in the abstract to construct both catalogs.

pith-pipeline@v0.9.0 · 5791 in / 1219 out tokens · 32161 ms · 2026-05-19T02:41:40.266544+00:00 · methodology

0 comments
read the original abstract

Active galactic nuclei (AGNs) are known to exhibit stochastic variability across a wide range of timescales and wavelengths. AGN flares are extreme outbursts that deviate from this typical behavior and may trace a range of energetic physical processes. Using six years of data from Zwicky Transient Facility (ZTF) Data Release 23, we conduct a systematic search for AGN flares among a sample of well-sampled AGNs and AGN candidates. We construct two catalogs: the AGN Flare Coarse Catalog (AGNFCC), containing 28,504 flares identified via Bayesian blocks and Gaussian Processes, and the AGN Flare Refined Catalog (AGNFRC), comprising 1,984 high-confidence flares selected using stricter criteria. We analyze their spatial distribution, temporal characteristics, host AGN type and potential origins. Some flares can be associated with known supernovae, tidal disruption events, or blazars, and a few may be linked to binary black hole mergers or microlensing events. These catalogs provide a valuable resource for studying transient phenomena in AGNs and are publicly available at https://github.com/Lyle0831/AGN-Flares.

Figures

Figures reproduced from arXiv: 2507.20232 by Bing-Zhou Gao, Ji-an Jiang, Jian-Min Wang, Lei He, Liang-Gui Zhu, Ming-Shen Zhou, Ning Jiang, Pu-Run Zou, Rui Niu, Run-Duo Liang, Wen Zhao, Ye-Fei Yuan, Yong-Jie Chen, Zheng-Yan Liu, Zhen-Yi Cai, Zi-Gao Dai.

Figure 1
Figure 1. Figure 1: Mollweide projection of the sky positions in equatorial coordinates of the objects used in this work. The resolution is that of a HealPix map with NSIDE=64. 0 1 2 3 4 5 Redshift 0 10000 20000 30000 40000 50000 60000 70000 80000 Number of AGNs per bin Milliquas DESI LAMOST Quaia Total [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Redshift distributions of AGNs from different catalogs, binned with a bin size of ∆z = 0.05. 2.3. Pre-processing We retrieve all light curves within the ZTF DR23 dataset using the bulk download option described in Section 12.c of the ZTF DR23 document7 . Each light curve contains the Heliocentric-based Modified Julian Date (HMJD), the point spread function (PSF) magnitude, 1-σ photometric un￾certainty, and… view at source ↗
Figure 3
Figure 3. Figure 3: ZTF detection counts distribution for all AGNs. We employ a hybrid sigma-clipping algorithm to suppress noise while preserving astrophysical signals. Points deviat￾ing > 3σ from the median flux are flagged as outliers, and single outliers are removed, whereas > 2 consecutive out￾liers or isolated outliers surrounded by points > 2.5σ are retained as potential flare signatures. Finally, cleaned light curves … view at source ↗
Figure 4
Figure 4. Figure 4: Distribution of the highest pflare values for each AGN. The vertical dashed line represents the threshold of pflare = 0.998. for fast and scalable GP analysis on one-dimensional data (D. Foreman-Mackey et al. 2017). Following this procedure, we identify 28,504 AGN flare events, which are summarized in the AGN Flare Coarse Catalog - Version 1.0 (AGNFCC￾V1.0). 3.3. Refinement and Selection of High-Confidence… view at source ↗
Figure 5
Figure 5. Figure 5: The detection processing flow for a real AGN light curve. Panel (a) shows the light curve of a real AGN (blue), with the red curve representing the fit obtained using Bayesian block representation. The green shaded regions indicate the time intervals where potential flares are detected. Panel (b) displays the simulated light curves, while panel (c) presents the GP hyperparameters for all the light curves. … view at source ↗
Figure 6
Figure 6. Figure 6: Sky distribution of AGN flares. Gray points represent flares from the AGNFCC, while red points correspond to flares from AGNFRC. We present the redshift distributions for four samples in [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: , including all AGNs with more than 30 observations per bands, potential flares identified via Bayesian Block rep￾resentation, and the AGN flares in the AGNFCC and AGN￾FRC. There is a clear trend that samples with increasingly reliable flares show progressively stronger low-redshift con￾centration. This suggests that AGN flares are more readily detected in nearby sources. At higher redshifts, only intrinsi… view at source ↗
Figure 8
Figure 8. Figure 8: Distribution of rise timescale tg (left) and decay timescale te (right) for two AGN flare catalogs. 100 200 300 400 500 600 700 tg (days) 100 200 300 400 500 600 700 te (d a ys) [PITH_FULL_IMAGE:figures/full_fig_p010_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Joint distribution of rise timescale tg and decay timescale te for flares in the AGNFRC. Red points represent individual flares, while blue contours indicate the kernel density estimate of their dis￾tribution. mains relatively small but increases slightly from AGNFCC to AGNFRC. 5. DISCUSSION In this section, we explore several potential origins for the flares identified in our sample. 5.1. Tidal Disruption… view at source ↗
Figure 10
Figure 10. Figure 10: Light curves of AGN flares that have a slow-rise/fast-decay profile. The black lines indicate the best-fitting profiles using Equation (5). QSO AGN NLQSO NLAGN BL Lac Other AGN Type 0.0 0.2 0.4 0.6 0.8 Proportion Observed AGNs Potential Flares AGNFCC AGNFRC [PITH_FULL_IMAGE:figures/full_fig_p011_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: AGN type proportions in Million Quasars Catalog. 1983). Both CCSNe and SNe Ia in AGN disks have been suggested as potentially observable events, with their signa￾tures detectable in the AGN light curves (F.-L. Li et al. 2023; J.-P. Zhu et al. 2021). After cross-matching AGNFCC sources with classification reports on the Transient Name Server (TNS), we find a total of 71 SNe spanning different classes in th… view at source ↗
Figure 12
Figure 12. Figure 12: Classification results of AGN flares in both AGNFCC (left) and AGNFRC (right) based on ZTF alerts. 16.5 17.0 17.5 m g J031335.69-020906.5 58500 59000 59500 60000 60500 MJD 16.0 16.2 16.4 16.6 16.8 17.0 m r 18.0 18.5 19.0 19.5 20.0 m g J172950.51+255031.8 58500 59000 59500 60000 60500 MJD 17.75 18.00 18.25 18.50 18.75 m r [PITH_FULL_IMAGE:figures/full_fig_p012_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: Light curves of AT2020afhd (left) and AT2022exr (right), both classified as TDEs. GW events. Both of them are included in our AGNFRC, and their light curves are shown in [PITH_FULL_IMAGE:figures/full_fig_p012_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Light curves of AGN flares that matched with a known SN: (a) SN 2019ses (SN Ia), (b) SN 2021too (SN Ic), (c) SN 2019lkw (SN II), and (d) SN 2020edi (SLSN-II). where u(t) 2 = (t − t0) 2/t2 E + u 2 0 is the angular distance in units of the Einstein radius between the lens and the source (for details see, e.g. P. Schneider et al. 1992) and Fν,obs(t) and Fν,0 are the observed flux density and the baseline flu… view at source ↗
Figure 15
Figure 15. Figure 15: Light curves of AGN flares that are potential EM counterparts to BBH mergers. The vertical dashed lines indicate the trigger times of the corresponding GW events. 18.5 19.0 19.5 20.0 20.5 m g J091107.27+610215.2 58500 59000 59500 60000 60500 MJD 18.5 19.0 19.5 20.0 20.5 m r 19 20 21 22 m g J212041.18+053345.0 58500 59000 59500 60000 60500 MJD 19 20 21 m r [PITH_FULL_IMAGE:figures/full_fig_p014_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: Light curves of AGN flares that are better described by a symmetric microlensing profile than by the asymmetric flare profile. The solid lines show the best-fitting microlensing curves. 5.6. AGN Variability While our flare selection aims to identify events beyond the scope of AGN variability, it is important to recognize that intrinsic variability in AGNs cannot be entirely ruled out. Ac￾cording to our th… view at source ↗
Figure 17
Figure 17. Figure 17: Light curves of SDSS J001736.90+145101.8 (left) and B2 0242+23 (right), both are known blazars. tions will be essential for further refining flare selection and advancing our physical understanding of these events. 6. SUMMARY In this work, we conduct a systematic search for AGN flares based on data from ZTF DR 23, one of the most ex￾tensive time-domain datasets available for the northern sky. Starting fro… view at source ↗
Figure 18
Figure 18. Figure 18: Light curves of eight flares in the AGNFCC that are excluded from the AGNFRC, each corresponding to one of the eight selection criteria listed in [PITH_FULL_IMAGE:figures/full_fig_p017_18.png] view at source ↗

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Forward citations

Cited by 1 Pith paper

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

  1. Tidal disruption of a low-mass star in an active galactic nucleus as the origin of the PS16dtm outburst

    astro-ph.HE 2026-05 conditional novelty 4.0

    PS16dtm is the tidal disruption of a 0.3 solar-mass star on a circular counter-rotating orbit inside the accretion disk of an NLS1 galaxy, hidden by a gaseous envelope from the observer's view.

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