Ruining Tian | Searcharxiv

arXiv2026

The Intermediate-Mass Black Hole Reverberation Mapping Project: Scientific Overview and Sample Characteristics

Recent discoveries with the James Webb Space Telescope of massive black holes at high redshift have highlighted fundamental questions about black hole seed formation and the coevolution of black holes with their host galaxies. Because the initial seed population cannot yet be observed directly, nearby intermediate-mass black holes provide a complementary fossil record of black hole formation and early growth. Motivated by this opportunity, we present the Intermediate-Mass Black Hole Reverberation Mapping (IMBH-RM) project and construct a homogeneous Sloan Digital Sky Survey sample of active broad-line IMBHs by uniformly reanalyzing literature candidates with consistent spectral decomposition and black hole mass estimation. Our sample contains 192 reliable IMBH candidates at $z\lesssim0.3$ with $\log(M_{\rm BH}/M_\odot)<6$, including four particularly compelling sources with $\log(M_{\rm BH}/M_\odot)<5$. The primary goal of IMBH-RM is to obtain reliable black hole masses from direct measurements and characteristic sizes of the broad-line region and accretion disk for a carefully selected subsample. These measurements will provide robust low-mass anchors for calibrating single-epoch black hole mass estimates and extending black hole--galaxy scaling relations into the IMBH regime. By building a statistically meaningful reverberation-mapped sample spanning $10^4-10^6\,M_\odot$, we aim to constrain the local IMBH mass distribution and place observational constraints on competing black hole seed formation scenarios. The future Multi-Channel Imager aboard the Chinese Space-station Survey Telescope provides a particularly promising platform for achieving these goals.

astro-ph.GA↗

arXiv2025

SHAPE. I. A SOM-SED hybrid approach for efficient galaxy parameter estimation leveraging JWST

With the launch and application of next-generation ground- and space-based telescopes, astronomy has entered the era of big data, necessitating more efficient and robust data analysis methods. Most traditional parameter estimation methods are unable to reconcile differences between photometric systems. Ideally, we would like to optimally rely on high-quality observation data provided by, e.g., JWST, for calibrating and improving upcoming wide-field surveys such as the China Space Station Telescope (CSST) and Euclid. To this end, we introduce a new approach (SHAPE, SOM-SED Hybrid Approach for efficient Parameter Estimation) that can bridge different photometric systems and efficiently estimate key galaxy parameters, such as stellar mass ($M_\star$) and star formation rate (SFR), leveraging data from a large and deep JWST/NIRCam and MIRI survey (PRIMER). As a test of the methodology, we focus on galaxies at $z\sim 1.5-2.5$. To mitigate discrepancies between input colors and the training set, we replace the default SOM weights with stacked SEDs from each cell, extending the applicability of our model to other photometric catalogs (e.g., COSMOS2020). By incorporating a SED library (SED Lib), we apply this JWST-calibrated model to the COSMOS2020 catalog. Despite the limited sample size and potential template-related uncertainties, SOM-derived parameters exhibit a good agreement with results from SED-fitting using extended photometry. Under identical photometric constraints from CSST and Euclid bands, our method outperforms traditional SED-fitting techniques in SFR estimation, exhibiting both a reduced bias (-0.01 vs. 0.18) and a smaller $\sigma_{\rm NMAD}$ (0.25 vs. 0.35). With its computational efficiency capable of processing $10^6$ sources per CPU per hour during the estimation phase, this JWST-calibrated estimator holds significant promise for next-generation wide-field surveys.

astro-ph.GA↗