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

Abstract

We predict the effective clustering bias parameter, $b_{\mathrm{eff}}$, at $z\sim 5$ for Little Red Dots (LRDs) seeded by Ultra-Strongly Self-Interacting Dark Matter (uSIDM). From our model, we find that $b_{\mathrm{eff}}\sim 4.5$, thus we infer that LRDs seeded by uSIDM would populate halos of typical masses $\sim 8\times 10^{10}{M}_{\odot }$; 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.

Comments: 5 pages, 3 figures