The TDE Population from First-Principles Models of Stellar Disruption and Debris Dynamics
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| Formato: | Preprint |
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2026
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| author | Piran, Tsvi Krolik, Julian Ryu, Taeho |
| author_facet | Piran, Tsvi Krolik, Julian Ryu, Taeho |
| contents | We present a physically-grounded population model for optical tidal disruption events (TDEs) that combines first-principles hydrodynamic simulations of stellar disruption with statistical inference of the underlying stellar and black hole populations. The model's prediction of peak luminosity is based directly on recent global simulations that follow the disruption self-consistently and contains no tunable parameters related to the emission physics. We construct the predicted joint distribution of peak luminosity and black hole mass, including both full and partial disruptions, and compare it to a sample of observed TDEs using Bayesian inference and Markov chain Monte Carlo sampling. We find that the model reproduces the distribution in the ($M_{BH},L_{peak}$) plane for the bulk of the observed TDE population with good statistical consistency. The data strongly favor an old stellar population, with a sharp suppression of stars above $M_* \simeq 1.5 - 2 M_\odot$. They also indicate that, at fixed stellar mass, the volumetric TDE rate is nearly independent of black hole mass. Partial disruptions contribute a substantial fraction ($\sim 30\%$) of detected events in flux-limited samples and are essential for reproducing the observed distribution. The inferred population properties are robust to different approximations to the stellar mass-radius relation, although the event rate at high luminosity is sensitive to the form of this relation for massive stars. We predict a large population of difficult to detect low luminosity TDEs, implying that the true volumetric TDE rate may exceed that inferred from present samples by up to an order of magnitude. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2601_20110 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The TDE Population from First-Principles Models of Stellar Disruption and Debris Dynamics Piran, Tsvi Krolik, Julian Ryu, Taeho High Energy Astrophysical Phenomena We present a physically-grounded population model for optical tidal disruption events (TDEs) that combines first-principles hydrodynamic simulations of stellar disruption with statistical inference of the underlying stellar and black hole populations. The model's prediction of peak luminosity is based directly on recent global simulations that follow the disruption self-consistently and contains no tunable parameters related to the emission physics. We construct the predicted joint distribution of peak luminosity and black hole mass, including both full and partial disruptions, and compare it to a sample of observed TDEs using Bayesian inference and Markov chain Monte Carlo sampling. We find that the model reproduces the distribution in the ($M_{BH},L_{peak}$) plane for the bulk of the observed TDE population with good statistical consistency. The data strongly favor an old stellar population, with a sharp suppression of stars above $M_* \simeq 1.5 - 2 M_\odot$. They also indicate that, at fixed stellar mass, the volumetric TDE rate is nearly independent of black hole mass. Partial disruptions contribute a substantial fraction ($\sim 30\%$) of detected events in flux-limited samples and are essential for reproducing the observed distribution. The inferred population properties are robust to different approximations to the stellar mass-radius relation, although the event rate at high luminosity is sensitive to the form of this relation for massive stars. We predict a large population of difficult to detect low luminosity TDEs, implying that the true volumetric TDE rate may exceed that inferred from present samples by up to an order of magnitude. |
| title | The TDE Population from First-Principles Models of Stellar Disruption and Debris Dynamics |
| topic | High Energy Astrophysical Phenomena |
| url | https://arxiv.org/abs/2601.20110 |