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ABSTRACT We combine the isothermal Jeans model and the model of adiabatic halo contraction into a semi-analytic procedure for computing the density profile of self-interacting dark-matter (SIDM) haloes with the gravitational influence from the inhabitant galaxies. The model agrees well with cosmological SIDM simulations over the entire core-forming stage up to the onset of gravothermal core-collapse. Using this model, we show that the halo response to baryons is more diverse in SIDM than in CDM and depends sensitively on galaxy size, a desirable feature in the context of the structural diversity of bright dwarfs. The fast speed of the method facilitates analyses that would be challenging for numerical simulations – notably, we quantify the SIDM halo response as functions of the baryonic properties, on a fine mesh grid spanned by the baryon-to-total-mass ratio, Mb/Mvir, and galaxy compactness, r1/2/Rvir; we show with high statistical precision that for typical Milky-Way-like systems, the SIDM profiles are similar to their CDM counterparts; and we delineate the regime of core-collapse in the Mb/Mvir − r1/2/Rvir space, for a given cross section and concentration. Finally, we compare the isothermal Jeans model with the more sophisticated gravothermal fluid model, and show that the former yields faster core formation and agrees better with cosmological simulations. We attribute the difference to whether the target CDM halo is used as a boundary condition or as the initial condition for the gravothermal evolution, and thus comment on possible improvements of the fluid model. We have made our model publicly available at https://github.com/JiangFangzhou/SIDM. 

Abstract Submillimeter emission lines produced by the interstellar medium (ISM) are strong tracers of star formation and are some of the main targets of line intensity mapping (LIM) surveys. In this work we present an empirical multiline emission model that simultaneously covers the mean, scatter, and correlations of [C ii ], CO J = 1–0 to J = 5–4, and [C i ] lines in the redshift range 1 ≤ z ≤ 9. We assume that the galaxy ISM line emission luminosity versus halo mass relations can be described by double power laws with redshift-dependent lognormal scatter. The model parameters are then derived by fitting to the state-of-the-art semianalytic simulation results that have successfully reproduced multiple submillimeter line observations at 0 ≤ z ≲ 6. We cross-check the line emission statistics predicted by the semianalytic simulation and our empirical model, finding that at z ≥ 1 our model reproduces the simulated line intensities with fractional error less than about 10%. The fractional difference is less than 25% for the power spectra. Grounded on physically motivated and self-consistent galaxy simulations, this computationally efficient model will be helpful in forecasting ISM emission-line statistics for upcoming LIM surveys. 

Abstract The Millimeter-wave Intensity Mapping Experiment (mmIME) recently reported a detection of excess spatial fluctuations at a wavelength of 3 mm, which can be attributed to unresolved emission of several CO rotational transitions between z ∼ 1 and 5. We study the implications of these data for the high-redshift interstellar medium using a suite of state-of-the-art semianalytic simulations that have successfully reproduced many other submillimeter line observations across the relevant redshift range. We find that the semianalytic predictions are mildly in tension with the mmIME result, with a predicted CO power ∼3.5 σ below what was observed. We explore some simple modifications to the models that could resolve this tension. Increasing the molecular gas abundance at the relevant redshifts to ∼10 8 M ⊙ Mpc −3 , a value well above that obtained from directly imaged sources, would resolve the discrepancy, as would assuming a CO–H 2 conversion factor α CO of ∼1.5 M ⊙ K −1 (km s −1 ) −1 pc 2 , a value somewhat lower than is commonly assumed. We go on to demonstrate that these conclusions are quite sensitive to the detailed assumptions of our simulations, highlighting the need for more careful modeling efforts as more intensity mapping data become available.