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arXiv · 2512.18000

The Clustering of Little Red Dots from Ultra-Strongly Self-Interacting Dark Matter

Abstract

We predict the effective clustering bias parameter, $b_{\rm{eff}}$, at $z\sim5$ for Little Red Dots (LRDs) seeded by Ultra-Strongly Self-Interacting Dark Matter (uSIDM). From our model, we find that $b_{\rm{eff}}\sim4.5$, thus we infer that LRDs seeded by uSIDM would populate halos of typical masses $\sim 8\times10^{10}~M_{\odot}$; this bias factor is consistent with LRDs being a distinct population from high redshift quasars. To the extent that we are aware, this is the first formation-based theoretical prediction of LRD clustering from a model consistent with the LRD mass function. We find that this bias and clustering is insensitive to a wide range of the underlying uSIDM microphysics parameters, including the uSIDM cross-section $\sigma/m$ and uSIDM fraction $f$. This is therefore a robust prediction from the uSIDM model, and will allow for direct probes of the uSIDM paradigm as the origin of LRDs in the next few years. Upcoming \texttt{JWST} observations will constrain the population of LRDs, including directly measuring their clustering.

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M. Grant Roberts, Aarna Garg, Tesla Jeltema, Stefano Profumo. 2025-12-19. The Clustering of Little Red Dots from Ultra-Strongly Self-Interacting Dark Matter. https://arxiv.org/abs/2512.18000

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