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ABSTRACT Recent works have suggested that energy balance spectral energy distribution (SED) fitting codes may be of limited use for studying high-redshift galaxies for which the observed ultraviolet and far-infrared emission are offset (spatially ‘decoupled’). It has been proposed that such offsets could lead energy balance codes to miscalculate the overall energetics, preventing them from recovering such galaxies’ true properties. In this work, we test how well the SED fitting code magphys can recover the stellar mass, star formation rate (SFR), specific SFR, dust mass, and luminosity by fitting 6706 synthetic SEDs generated from four zoom-in simulations of dusty, high-redshift galaxies from the FIRE project via dust continuum radiative transfer. Comparing our panchromatic results (using wavelengths 0.4–500 μm, and spanning 1 < z < 8) with fits based on either the starlight ($\lambda _\mathrm{eff} \le 2.2\, \mu$m) or dust ($\ge 100\, \mu$m) alone, we highlight the power of considering the full range of multiwavelength data alongside an energy balance criterion. Overall, we obtain acceptable fits for 83 per cent of the synthetic SEDs, though the success rate falls rapidly beyond z ≈ 4, in part due to the sparser sampling of the priors at earlier times since SFHs must be physically plausible (i.e. shorter than the age of the universe). We use the ground truth from the simulations to show that when the quality of fit is acceptable, the fidelity of magphys estimates is independent of the degree of UV/FIR offset, with performance very similar to that previously reported for local galaxies. 

Single flux density measurements at observed-frame submillimeter and millimeter wavelengths are commonly used to probe dust and gas masses in galaxies. In this Letter, we explore the robustness of this method to infer dust mass, focusing on quiescent galaxies, using a series of controlled experiments on four massive halos from the Feedback in Realistic Environments project. Our starting point is four star-forming central galaxies at seven redshifts betweenz= 1.5 andz= 4.5. We generate modified quiescent galaxies that have been quenched for 100 Myr, 500 Myr, or 1 Gyr prior to each of the studied redshifts by reassigning stellar ages. We derive spectral energy distributions for each fiducial and modified galaxy using radiative transfer. We demonstrate that the dust mass inferred is highly dependent on the assumed dust temperature,T_dust, which is often unconstrained observationally. Motivated by recent work on quiescent galaxies that assumedT_dust∼ 25 K, we show that the ratio between dust mass and 1.3 mm flux density can be higher than inferred by up to an order of magnitude, due to the considerably lower dust temperatures seen in non-star-forming galaxies. This can lead to an underestimation of dust mass (and, when submillimeter flux density is used as a proxy for molecular gas content and gas mass). This underestimation is most severe at higher redshifts, where the observed-frame 1.3 mm flux density probes rest-frame wavelengths far from the Rayleigh–Jeans regime, and hence depends superlinearly on dust temperature. We fit relations between ratios of rest-frame far-infrared flux densities and mass-weighted dust temperature that can be used to constrain dust temperatures from observations and hence derive more reliable dust and molecular gas masses.

 

Recent years have seen growing interest in post-processing cosmological simulations with radiative transfer codes to predict observable fluxes for simulated galaxies. However, this can be slow, and requires a number of assumptions in cases where simulations do not resolve the interstellar medium (ISM). Zoom-in simulations better resolve the detailed structure of the ISM and the geometry of stars and gas; however, statistics are limited due to the computational cost of simulating even a single halo. In this paper, we make use of a set of high-resolution, cosmological zoom-in simulations of massive ($M_{\star }\gtrsim 10^{10.5}\, \rm {M_{\odot }}$ at z = 2), star-forming galaxies from the FIRE suite. We run the skirt radiative transfer code on hundreds of snapshots in the redshift range 1.5 < z < 5 and calibrate a power-law scaling relation between dust mass, star formation rate, and $870\, \mu \rm {m}$ flux density. The derived scaling relation shows encouraging consistency with observational results from the sub-millimetre-selected AS2UDS sample. We extend this to other wavelengths, deriving scaling relations between dust mass, stellar mass, star formation rate, and redshift and sub-millimetre flux density at observed-frame wavelengths between $\sim \! 340$ and $\sim \! 870\, \mu \rm {m}$. We then apply the scaling relations to galaxies drawn from EAGLE, a large box cosmological simulation. We show that the scaling relations predict EAGLE sub-millimetre number counts that agree well with previous results that were derived using far more computationally expensive radiative transfer techniques. Our scaling relations can be applied to other simulations and semi-analytical or semi-empirical models to generate robust and fast predictions for sub-millimetre number counts.

 

Without active galactic nucleus (AGN) feedback, simulated massive, star-forming galaxies become too compact relative to observed galaxies at z ≲ 2. In this paper, we perform high-resolution re-simulations of a massive ($M_{\star }\sim 10^{11}\, \rm {{\rm M}_{\odot }}$) galaxy at z ∼ 2.3, drawn from the Feedback in Realistic Environments (FIRE) project. In the simulation without AGN feedback, the galaxy experiences a rapid starburst and shrinking of its half-mass radius. We experiment with driving mechanical AGN winds, using a state-of-the-art hyper-Lagrangian refinement technique to increase particle resolution. These winds reduce the gas surface density in the inner regions of the galaxy, suppressing the compact starburst and maintaining an approximately constant half-mass radius. Using radiative transfer, we study the impact of AGN feedback on the magnitude and extent of the multiwavelength continuum emission. When AGN winds are included, the suppression of the compact, dusty starburst results in lowered flux at FIR wavelengths (due to decreased star formation) but increased flux at optical-to-near-IR wavelengths (due to decreased dust attenuation, in spite of the lowered star formation rate), relative to the case without AGN winds. The FIR half-light radius decreases from ∼1 to $\sim 0.1\, \rm {kpc}$ in $\lesssim 40\, \rm {Myr}$ when AGN winds are not included, but increases to $\sim 2\, \rm {kpc}$ when they are. Interestingly, the half-light radius at optical-NIR wavelengths remains approximately constant over $35\, \rm {Myr}$, for simulations with and without AGN winds. In the case without winds, this occurs despite the rapid compaction, and is due to heavy dust obscuration in the inner regions of the galaxy. This work highlights the importance of forward-modelling when comparing simulated and observed galaxy populations.

 

ABSTRACT Hydrodynamic simulations provide a powerful, but computationally expensive, approach to study the interplay of dark matter and baryons in cosmological structure formation. Here, we introduce the EMulating Baryonic EnRichment (EMBER) Deep Learning framework to predict baryon fields based on dark matter-only simulations thereby reducing computational cost. EMBER comprises two network architectures, U-Net and Wasserstein Generative Adversarial Networks (WGANs), to predict 2D gas and H i densities from dark matter fields. We design the conditional WGANs as stochastic emulators, such that multiple target fields can be sampled from the same dark matter input. For training we combine cosmological volume and zoom-in hydrodynamical simulations from the Feedback in Realistic Environments (FIRE) project to represent a large range of scales. Our fiducial WGAN model reproduces the gas and H i power spectra within 10 per cent accuracy down to ∼10 kpc scales. Furthermore, we investigate the capability of EMBER to predict high resolution baryon fields from low resolution dark matter inputs through upsampling techniques. As a practical application, we use this methodology to emulate high-resolution H i maps for a dark matter simulation of a $L=100\, \text{Mpc}\, h^{ -1}$ comoving cosmological box. The gas content of dark matter haloes and the H i column density distributions predicted by EMBER agree well with results of large volume cosmological simulations and abundance matching models. Our method provides a computationally efficient, stochastic emulator for augmenting dark matter only simulations with physically consistent maps of baryon fields. 

ABSTRACT The galaxy size–stellar mass and central surface density–stellar mass relationships are fundamental observational constraints on galaxy formation models. However, inferring the physical size of a galaxy from observed stellar emission is non-trivial due to various observational effects, such as the mass-to-light ratio variations that can be caused by non-uniform stellar ages, metallicities, and dust attenuation. Consequently, forward-modelling light-based sizes from simulations is desirable. In this work, we use the skirt  dust radiative transfer code to generate synthetic observations of massive galaxies ($M_{*}\sim 10^{11}\, \rm {M_{\odot }}$ at z = 2, hosted by haloes of mass $M_{\rm {halo}}\sim 10^{12.5}\, \rm {M_{\odot }}$) from high-resolution cosmological zoom-in simulations that form part of the Feedback In Realistic Environments project. The simulations used in this paper include explicit stellar feedback but no active galactic nucleus (AGN) feedback. From each mock observation, we infer the effective radius (Re), as well as the stellar mass surface density within this radius and within $1\, \rm {kpc}$ (Σe and Σ1, respectively). We first investigate how well the intrinsic half-mass radius and stellar mass surface density can be inferred from observables. The majority of predicted sizes and surface densities are within a factor of 2 of the intrinsic values. We then compare our predictions to the observed size–mass relationship and the Σ1−M⋆ and Σe−M⋆ relationships. At z ≳ 2, the simulated massive galaxies are in general agreement with observational scaling relations. At z ≲ 2, they evolve to become too compact but still star forming, in the stellar mass and redshift regime where many of them should be quenched. Our results suggest that some additional source of feedback, such as AGN-driven outflows, is necessary in order to decrease the central densities of the simulated massive galaxies to bring them into agreement with observations at z ≲ 2. 

ABSTRACT We present the first detailed study of the spatially resolved dust continuum emission of simulated galaxies at 1 < z < 5. We run the radiative transfer code skirt on a sample of submillimetre-bright galaxies drawn from the Feedback In Realistic Environments (FIRE) project. These simulated galaxies reach Milky Way masses by z = 2. Our modelling provides predictions for the full rest-frame far-ultraviolet-to-far-infrared spectral energy distributions of these simulated galaxies, as well as 25-pc resolution maps of their emission across the wavelength spectrum. The derived morphologies are notably different in different wavebands, with the same galaxy often appearing clumpy and extended in the far-ultraviolet yet an ordered spiral at far-infrared wavelengths. The observed-frame 870-$\mu$m half-light radii of our FIRE-2 galaxies are ${\sim} 0.5\rm {-}4\, \rm {kpc}$, consistent with existing ALMA observations of galaxies with similarly high redshifts and stellar masses. In both simulated and observed galaxies, the dust continuum emission is generally more compact than the cold gas and the dust mass, but more extended than the stellar component. The most extreme cases of compact dust emission seem to be driven by particularly compact recent star formation, which generates steep dust temperature gradients. Our results confirm that the spatial extent of the dust continuum emission is sensitive to both the dust mass and star formation rate distributions.