arXiv subjects

Rui Lan Jun

Publications and source records attributed to Rui Lan Jun.

4 recordsLinked to original sources

arXiv2026

The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective

We present a model for the power spectrum of the density field of galaxies weighted by their star formation rate. This weighting is relevant in line-intensity mapping (LIM) when the observed line luminosity is strongly correlated with star formation, as is the case for the H$α$ line. Our model reproduces the measured power spectrum in the IllustrisTNG simulation to within a few per cent across all scales, with fitting parameters that have clear physical interpretations. On scales of tens of megaparsecs, the model accounts for the weighted non-linear bias of galaxies as well as halo exclusion (2-halo term). On smaller scales, it incorporates the weighted distribution of satellite galaxies within haloes (1-halo term). The random sampling of satellite galaxies introduces a galaxy shot noise term to the power spectrum on small scales, and their confinement to haloes introduces a halo shot noise term on large scales. Omitting satellite galaxies from the analysis results in an underestimation of both the large-scale bias and the mean intensity by approximately 30 per cent each at redshift 1.5. Assigning the intensity of satellites to the centre of their respective haloes affects the power spectrum on scales $k > 0.3$ h Mpc$^{-1}$. Our fitting function provides a well-motivated parametrisation that can be used to interpret data from upcoming LIM surveys.

astro-ph.GA↗

arXiv2026

Signatures of Accreting Black Holes in Line Intensity Mapping

Line-intensity mapping (LIM) has attracted growing attention as a powerful technique for probing the large-scale distribution of galaxies and the cosmic history of star formation through unresolved line emission. Existing LIM models for galaxy-associated lines, such as H$α$, often assume that the dominant contribution to observed emission arises from star-forming activity, while the role of accreting black holes (BHs) remains largely unexplored. In this study, we use the IllustrisTNG cosmological hydrodynamical simulation to construct mock intensity maps of H$α$ and He II, including contributions from both star formation and BH accretion. We show that the BH contribution to the mean intensity is significant, reaching $\sim$40--60 per cent for H$α$ and $\sim$60--80 per cent for He II around cosmic noon. Owing to the large luminosity weight of rare, bright sources, BH-powered emission dominates the shot-noise component of the power spectrum and significantly boosts the small-scale clustering amplitude, particularly for He II. We assess the implications for forthcoming LIM surveys and show that SPHEREx can probe the BH-influenced bright end of the H$α$ voxel intensity distribution (VID) at $z\lesssim4$, and a CDIM-like experiment can further access the BH-dominated regime of He II. Our results demonstrate that accreting BHs represent an essential component of LIM signals, which was previously underappreciated. We thus conclude that accurately modeling the BH contribution is crucial for a physically complete interpretation of future LIM observations.

astro-ph.GA↗

arXiv2025

CosmoGLINT: Cosmological Generative Model for Line Intensity Mapping with Transformer

Modelling star-forming galaxies is crucial for upcoming observations of large-scale matter and galaxy distributions with galaxy redshift surveys and line intensity mapping (LIM). We introduce CosmoGLINT (Cosmological Generative model for Line INtensity mapping with Transformer), a Transformer-based generative framework designed to create realistic galaxy populations from dark matter (DM)-only simulations. CosmoGLINT auto-regressively generates sequences of galaxy properties -- including star formation rate (SFR), distance to the halo centre, and radial and tangential velocities relative to the halo -- conditioned on halo mass. Trained on the IllustrisTNG hydrodynamic simulation, the model reproduces key statistical properties of the original data, including the voxel intensity distribution and the power spectrum both in real and redshift space. It can efficiently generate a number of different realisations of the designated galaxy populations, enabling the creation of mock LIM/redshift survey catalogues from large halo catalogues produced by fast DM-only simulations. We show that our model trained at multiple redshifts can be applied to DM halo lightcone data to generate a realistic mock galaxy lightcone with incorporating the redshift evolution of the galaxy population. The mock catalogues can be readily used to derive statistical quantities and to develop data analysis pipelines for ongoing and future wide-field surveys.

astro-ph.CO↗

arXiv2025

Scatter in the star formation rate-halo mass relation: secondary bias and its impact on line-intensity mapping

We use the IllustrisTNG cosmological hydrodynamical simulations to study the impact of secondary bias -- specifically, the correlation between star formation rate (SFR) and halo bias at fixed halo mass -- on the line-intensity mapping (LIM) power spectrum. In LIM, the galaxy contributions are flux-weighted, and therefore depend on the luminosity of emission line. We show that the (ensemble-averaged) large-scale two-halo term of the power spectrum depends only on the mean luminosity-halo mass relation if the scatter is uncorrelated with halo bias. However, when luminosity correlates with halo bias at fixed mass, this assumption breaks down. For many emission lines (e.g. H$α$), luminosity is strongly correlated with SFR, making the SFR-weighted power spectrum important to study. In IllustrisTNG, secondary bias increases the two-halo term of the SFR-weighted power spectrum by 5 per cent at $z \sim 1.5$ compared to a model with random scatter. We also find that SFRs of central and satellite galaxies are correlated, enhancing the one-halo term -- which depends on the distribution of SFR inside the halo -- by 10 per cent relative to random pairings. To mitigate secondary bias in the two-halo term, we identify halo concentration (for haloes with mass $\log M_h \lesssim 12$) and satellite mass (for $\log M_h \gtrsim 12$) as effective secondary parameters. These results highlight the need to account for secondary bias when building mock catalogues and interpreting LIM observations.

astro-ph.GA↗