A joint research team from the Early Universe and High-Redshift Galaxy Group at the Shanghai Astronomical Observatory (SHAO), Chinese Academy of Sciences, and the Optical–Infrared Observational Research Group at Sun Yat-sen University (SYSU), has recently made significant progress in improving the quality of long-term light curves for Active Galactic Nuclei (AGNs). By stacking multi-epoch images from the Zwicky Transient Facility (ZTF), the team has effectively enhanced the signal-to-noise ratio (SNR) of the observational data, enabling high-quality reconstruction of AGN light curves that were previously inaccessible due to their intrinsic faintness. This advancement reveals long-term variability and color-evolution characteristics with unprecedented clarity, providing critical observational constraints for probing the physical mechanisms and accretion dynamics of AGN central engines.

The research is jointly led by Zhen-Ya Zheng’s team at SHAO and Bin Ma’s team at SYSU. The results have been published in The Astrophysical Journal Supplement Series with the title “Optimizing Long-term Variability of Active Galactic Nucleus Light Curves. I. A Case Study with ZTF Observations in the EGS Field.”

Variability is a typical observational characteristic of AGNs. Analyzing their light curves is a key diagnostic tool for investigating the accretion physics of the central supermassive black holes. However, for low-luminosity AGNs and high-redshift AGNs, the limited depth of single-epoch observations leads to issues such as large photometric errors, sparse sampling, or even undetectable variability in their light curves, limiting the variability study of these objects.

To overcome these observational challenge, the research team proposed an innovative forward-modeling data-processing strategy. Rather than post-processing existing light curves, the approach begins with the raw imaging data: single-epoch exposures are binned and stacked following the temporal sequence of observations (Figure 1). This procedure effectively integrates multiple short exposures, improving the detection limit by approximately 2.0–2.5 magnitudes. While sacrificing short-timescale variability, the method robustly preserves long-term variability on month-to-year scales, making it particularly suitable for AGN variability study.

Figure 1. Data processing workflow.

Applying this method to the ZTF observations in the Extended Groth Strip (EGS) field (Figure 2), the team successfully constructed high-quality light curves for 73 AGNs. Compared with traditional ZTF data products, the improvements of the new method are mainly reflected in: (1) For AGNs with strong variability, the method substantially enhances photometric precision while retaining the original long-term trends; (2) for AGNs with faint signals, the technique suppresses noise contamination and clearly reveals variability features that were previously indistinguishable; (3) for objects with brightness near or below the single-exposure detection threshold, the method recovers meaningful variability signals, extending the accessible AGN sample to fainter regimes (Figure 3).

Based on these improved light curves, the team further analyzed color evolution and found that 56 of the 73 AGNs (77 percent) exhibit a significant “bluer-when-brighter” trend, consistent with thermal fluctuations in the inner accretion disk as the dominant mechanism of long-term optical variability.

Corresponding author Zhen-Ya Zheng noted: "In optical variability studies of supermassive black holes and binary black hole systems, light-curve quality is often the main bottleneck in extracting reliable physical parameters. By co-adding multiple short-exposure images, we significantly improve detection depth and SNR, enabling systematic acquisition of high-quality light curves for low-luminosity AGNs that were previously beyond reach. This provides a solid data foundation for studying accretion processes and long-term evolutionary behaviors of AGN central engines."

Corresponding author Bin Ma added: “Our next step is to develop automated data reduction pipelines to extend this method across other ZTF fields and to systematically build a high-precision optical light-curve dataset for low-luminosity AGNs. This will offer essential observational support for understanding black hole growth and evolution in the early universe. The technical framework is also highly scalable and will serve as a methodological reference for processing deep-field observations from the Multi-Channel Imager (MCI) onboard the China Space Station Telescope (CSST), thereby enhancing the scientific returns of CSST-MCI in time-domain astronomy.”

The first author of the paper is Jiaqi Lin, a PhD candidate jointly supported by SYSU and SHAO. The corresponding authors are Zhen-Ya Zheng and Bin Ma. This work is supported by the National Key R&D Program of China, the China-Chile Joint Research Fund, the China Manned Space Program, and other projects.

Figure 2. Schematic diagram of the overlapping region between ZTF and the EGS field. Left panel: Coverage of the EGS field by three ZTF CCD-quadrants and statistics of observation counts per band (2018-2024). Right panel: Overlap region between the selected CCD-quadrant (blue area) and the EGS field (red outlined area, approx. 10.2' × 37.5'). Yellow "×" marks represent the 73 AGN sample extracted in this study.

Figure 3. Comparison of light curves from the stacking method and traditional ZTF data, highlighting the performance advantages of the new method in three typical scenarios.

Paper link:https://doi.org/10.3847/1538-4365/ae1a88

Scientific Contacts:
Jiaqi Lin, Sun Yat-sen University, linjq63@mail2.sysu.edu.cn
Zhen-Ya Zheng, Shanghai Astronomical Observatory, CAS, zhengzy@shao.ac.cn
Bin Ma, Sun Yat-sen University, mabin3@mail.sysu.edu.cn