Halo assembly bias in the early Universe: a clustering probe of the origin of the Little Red Dots

Zihao Wang, Fangzhou Jiang, Haonan Zheng, Xuejian Shen, Zixiang Jia, Luis C. Ho, Kohei Inayoshi, Linhua Jiang

First listed 2026-03-16 | Last updated 2026-03-16

Abstract

The clustering of galaxies encodes key information about the structure and assembly history of their host dark matter (DM) haloes, providing a powerful probe of the origin of extreme high-redshift systems. While halo assembly bias has been extensively studied at low redshift, its behavior in the early Universe remains poorly explored. Using the large-volume, high-resolution Shin-Uchuu cosmological $N$-body simulation, we characterize halo assembly bias associated with formation time, concentration, and angular momentum across a wide range of halo masses and redshifts. We find that the sign and amplitude of assembly bias depend on halo mass for both concentration and spin. High-concentration and low-spin haloes are more strongly clustered below characteristic peak heights of $ν\sim 1.5$ and $\sim 0.75$, respectively, while the trends weaken or reverse at higher masses. Halo age bias persists at all redshifts but decreases toward higher masses and earlier cosmic times. We apply these results to assess whether clustering can distinguish competing formation scenarios for the Little Red Dots (LRDs). We find that the direct-collapse-black-hole (DCBH) scenario predicts the strongest large-scale bias and enhanced pair fractions, the self-interacting-dark-matter (SIDM) core-collapse scenario and low-spin compact-galaxy scenarios yield weaker clustering due to lower characteristic halo masses and spin-related secondary bias, and a primordial-black-hole (PBH) scenario predicts unbiased clustering. Our results demonstrate that halo assembly bias and characteristic host masses provide powerful diagnostics for constraining the physical origin of LRDs, offering testable predictions for upcoming clustering measurements with JWST and future deep surveys.

Short digest

Using the large-volume, high-resolution Shin-Uchuu N-body simulation, this paper maps halo assembly bias at early times across formation time, concentration, and spin, and tracks its mass and redshift dependence. The authors find mass-dependent sign and amplitude: high-concentration and low-spin haloes are more strongly clustered below ν≈1.5 and ≈0.75, respectively, while trends weaken or flip at higher masses; halo age bias persists at all redshifts but fades toward higher mass and earlier epochs. They then translate these trends into clustering predictions for Little Red Dots: a DCBH origin yields the strongest large-scale bias and elevated pair fractions, SIDM core-collapse and low-spin compact-galaxy channels predict weaker clustering due to lower host masses and spin-related bias, and a PBH scenario is effectively unbiased. The result is a clear, testable clustering roadmap for distinguishing LRD formation pathways with forthcoming JWST-era surveys.

Key figures to inspect

• Figure 1: Check where the Shin-Uchuu halo mass function matches Sheth–Tormen and where the UniverseMachine galaxy mass function falls below recent JWST counts at the massive end—this sets expectations for the abundance and host-mass scale relevant to LRD clustering tests.
• Figure 2: Inspect the joint distributions of concentration, spin, and formation redshift versus halo mass at high z to see the near mass-independence of c and λ and the earlier assembly of low-mass haloes; note the relaxed-halo subset’s effect on the concentration tail used for percentile splits.
• Figure 3: Compare ACFs across the low/intermediate/high-mass bins to see (i) the concentration-driven sign reversal at high mass, (ii) the mass-robust trend that low-spin haloes cluster more strongly, and (iii) the weakening of “oldest halo” bias with increasing mass—these are the secondary-bias patterns later mapped…
• Figure 4: Follow the redshift evolution of secondary bias for upper/lower quartiles to identify the mass–z windows where signals peak and where the concentration/spin trends flip; also check consistency with z≈0 benchmarks (Sato-Polito 2019) to validate the high-z extrapolation used for LRD predictions.