Can tidal disruption event models reliably measure black hole masses?

TL;DR

This work tests the reliability of TDE-based black hole mass measurements by analyzing three spectroscopically confirmed repeating partial TDEs (rpTDEs). It applies multiple modelling frameworks—MOSFiT fallback, TDEmass luminosity–color scaling, UV plateau scaling, and a cooling-envelope model—to independently fit each flare and compare inferred $M_{ m BH}$ values against host-galaxy proxies. Results show that $M_{ m BH}$ is generally recovered consistently across flares and approaches host-based estimates within $ abla \,0.3$–$0.5$ dex when accounting for model systematics, while $M_{ m star}$ and disruption depth are poorly constrained due to degeneracies and partial-disruption physics. The study also highlights the critical role of near-UV data for constraining temperatures and bolometric corrections, and demonstrates that LSST-like sampling can bias $M_{ m BH}$ low unless complemented by targeted follow-up and multi-wavelength coverage. Overall, rpTDEs provide a robust testbed for TDE mass inference and underscore the need for improved partial-disruption stellar models to enable reliable population-level inferences in the LSST era.

Abstract

Tidal disruption event (TDE) light curves are increasingly used to infer the masses of quiescent supermassive black holes ($M_{\rm{BH}}$), offering a powerful probe of low-mass black hole demographics independent of host-galaxy scaling relations. However, the reliability of most semi-analytic TDE models assume full stellar disruption, despite theoretical expectations that partial disruptions dominate the TDE population. In this work we test the robustness of current TDE models using three repeating partial TDEs (rpTDEs), in which the multiple flares produced by the same surviving stellar core must yield consistent black hole masses. We present spectroscopic observations establishing AT 2023adr as a rpTDE, making it the third such spectroscopically confirmed event. We independently model the flares of the three rpTDEs; 2020vdq, 2022dbl, and 2023adr, applying fallback-accretion fits, stream-stream collision scaling relations, luminosity-based empirical relations, and cooling-envelope fits. After accounting for statistical and model-specific systematics, we find that all TDE models generally return self-consistent $M_{\rm{BH}}$ values between flares, and are broadly consistent with host-galaxy $M_{\rm{BH}}$ proxies, recovering $M_{\rm{BH}}$ to within 0.3-0.5 dex. However, the convergence of fallback models towards unphysical stellar masses and impact parameters reveals limitations in the existing fallback model grids. We also show that light curve coverage, particularly in the near-UV, is critical for constraining model parameters. This has direct implications for interpreting the thousands of TDE light curves expected from upcoming surveys such as the Rubin Observatory's Legacy Survey of Space and Time, where from simulations, we find that $M_{\rm{BH}}$ may be underestimated on average by 0.5 dex without additional follow-up.

Figures (10)

• Figure 1: Top:Spectroscopic evolution of TDE 2023adr. Low resolution spectra during the first peak show a strong blue contiuum with some broad balmer emission, whilst the second peak exhibits broaded, blended helium and nitrogen emission. Bottom: Comparison of spectrum during the second peak with the well observed TDE, ASASSN-15oi holoien_asassn-15oi_2016.
• Figure 2: UV-Optical light curves of the first (left) and second (right) flares of the confirmed rpTDEs, with survey data from ZTF, ATLAS, PanSTARRS, alongside targeted follow-up observations from Swift and Liverpool Telescope. All magnitudes are host subtracted, corrected for galactic reddening and presented in the AB system. Phases are given in the rest frame of the TDE with respect to each flare.
• Figure 3: Resulting distributions of key parameters ($M_{\rm BH}$, $M_{\star}$ and scaled impact parameter, $b$) from MOSFiT fallback modelling of the rpTDEs 2020vdq (top), 2022dbl (middle), and 2023adr (bottom). Results from independently fitting the first peak are shown in red, and in blue for the second peak.
• Figure 4: Comparison of MOSFiT parameter distributions when modelling with constrained priors on scaled impact parameter, $b$ for TDE 2022dbl.
• Figure 5: Comparison of $M_{\rm BH}$ 1$\sigma$ posterior distributions from fitting the individual peaks of the rpTDEs (top: TDE 2020vdq, middle: TDE 2022dbl, bottom TDE 2023adr) with the MOSFiT fallback model, TDEmass stream collision model, the cooling envelope model implimented in Redback, plateau- and peak-luminosity scaling relations, and from host galaxy $M_{\rm BH}$ approximations (stellar mass, velocity dispersion, bulge mass fitting). For MOSFiT, we show fallback posterior distributions with (dashed lines) and without (solid lines) systematics uncertainties mockler_weighing_2019.