arXiv subjects

Ian G. McCarthy

Publications and source records attributed to Ian G. McCarthy.

At least 37 records · Page 2Linked to original sources

arXiv2024

ARTEMIS emulator: exploring the effect of cosmology and galaxy formation physics on Milky Way-mass haloes and their satellites

We present the new ARTEMIS Emulator suite of high resolution (baryon mass of $2.23 \times 10^{4}$ $h^{-1}$M$_{\odot}$) zoom-in simulations of Milky Way mass systems. Here, three haloes from the original ARTEMIS sample have been rerun multiple times, systematically varying parameters for the stellar feedback model, the density threshold for star formation, the reionisation redshift and the assumed warm dark matter (WDM) particle mass (assuming a thermal relic). From these simulations emulators are trained for a wide range of statistics that allow for fast predictions at combinations of parameters not originally sampled, running in $\sim 1$ms (a factor of $\sim 10^{11}$ faster than the simulations). In this paper we explore the dependence of the central haloes' stellar mass on the varied parameters, finding the stellar feedback parameters to be the most important. When constraining the parameters to match the present-day stellar mass halo mass relation inferred from abundance matching we find that there is a strong degeneracy in the stellar feedback parameters, corresponding to a freedom in formation time of the stellar component for a fixed halo assembly history. We additionally explore the dependence of the satellite stellar mass function, where it is found that variations in stellar feedback, the reionisation redshift and the WDM mass all have a significant effect. The presented emulators are a powerful tool which allows for fundamentally new ways of analysing and interpreting cosmological hydrodynamic simulations. Crucially, allowing their free (subgrid) parameters to be varied and marginalised, leading to more robust constraints and predictions.

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arXiv2024

Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?

We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These models, which include examples from artificial neural networks, decision trees and dimensionality reduction techniques, are trained on a sample of disc-like, Milky Way-mass galaxies drawn from the ARTEMIS cosmological hydrodynamical zoom-in simulations. We find that the input parameters which provide an optimal performance for these models consist of a combination of stellar positions, kinematics, chemical abundances ([Fe/H] and [$α$/Fe]) and photometric properties. Models from all categories perform similarly well, with area under the precision-recall curve (PR-AUC) scores of $\simeq 0.6$. Beyond a galactocentric radius of $5$~kpc, models retrieve $>90\%$ of accreted stars, with a sample purity close to $60\%$, however the purity can be increased by adjusting the classification threshold. For one model, we also include host galaxy-specific properties in the training, to account for the variability of accretion histories of the hosts, however this does not lead to an improvement in performance. The ML models can identify accreted stars even in regions heavily dominated by the in-situ component (e.g., in the disc), and perform well on an unseen suite of simulations (the Auriga simulations). The general applicability bodes well for application of such methods on observational data to identify accreted substructures in the Milky Way without the need to resort to selection cuts for minimising the contamination from in-situ stars.

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arXiv2024

The FLAMINGO Project: Galaxy clusters in comparison to X-ray observations

Galaxy clusters are important probes for both cosmology and galaxy formation physics. We test the cosmological, hydrodynamical FLAMINGO simulations by comparing to observations of the gaseous properties of clusters measured from X-ray observations. FLAMINGO contains unprecedented numbers of massive galaxy groups ($>10^6$) and clusters ($>10^5$) and includes variations in both cosmology and galaxy formation physics. We predict the evolution of cluster scaling relations as well as radial profiles of the temperature, density, pressure, entropy, and metallicity for different masses and redshifts. We show that the differences between volume-, and X-ray-weighting of particles in the simulations, and between cool-core non cool-core samples, are similar in size as the differences between simulations for which the stellar and AGN feedback has been calibrated to produce significantly different gas fractions. Compared to thermally-driven AGN feedback, kinetic jet feedback calibrated to produce the same gas fraction at $R_{\rm 500c}$ yields a hotter core with higher entropies and lower densities, which translates into a smaller fraction of cool-core clusters. Stronger feedback, calibrated to produce lower gas fractions and hence lower gas densities, results in higher temperatures, entropies, and metallicities, but lower pressures. The scaling relations and thermodynamic profiles show almost no evolution with respect to self-similar expectations, except for the metallicity decreasing with redshift. We find that the temperature, density, pressure, and entropy profiles of clusters in the fiducial FLAMINGO simulation are in excellent agreement with observations, while the metallicities in the core are too high.

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arXiv2024

The FLAMINGO project: Baryonic impact on weak gravitational lensing convergence peak counts

Weak gravitational lensing convergence peaks, the local maxima in weak lensing convergence maps, have been shown to contain valuable cosmological information complementary to commonly used two-point statistics. To exploit the full power of weak lensing for cosmology, we must model baryonic feedback processes because these reshape the matter distribution on non-linear and mildly non-linear scales. We study the impact of baryonic physics on the number density of weak lensing peaks using the FLAMINGO cosmological hydrodynamical simulation suite. We generate ray-traced full-sky convergence maps mimicking the characteristics of a Stage IV weak lensing survey. We compare the number densities of peaks in simulations that have been calibrated to reproduce the observed galaxy mass function and cluster gas fraction or to match a shifted version of these, and that use either thermally driven or jet AGN feedback. We show that the differences induced by realistic baryonic feedback prescriptions (typically $5 - 30\%$ for $κ= 0.1 - 0.4$) are smaller than those induced by reasonable variations in cosmological parameters ($20 - 60\%$ for $κ= 0.1 - 0.4$) but must be modeled carefully to obtain unbiased results. The reasons behind these differences can be understood by considering the impact of feedback on halo masses, or by considering the impact of different cosmological parameters on the halo mass function. Our analysis demonstrates that, for the range of models we investigated, the baryonic suppression is insensitive to changes in cosmology up to $κ\approx 0.4$ and that the higher $κ$ regime is dominated by Poisson noise and cosmic variance.

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arXiv2024

GODMAX: Modeling gas thermodynamics and matter distribution using JAX

We introduce GODMAX (Gas thermODynamics and Matter distribution using jAX), a novel code designed to calculate correlations between the cosmological matter distribution and various gas thermodynamic quantities. Utilizing the extensive ANTILLES suite of 200 hydrodynamical simulations with a diverse range of baryonic feedback strengths, we jointly fit the 3D profiles of total matter distribution, electron density, and electron pressure across various halo masses and redshifts. By accommodating significant variations in gas profiles expected due to baryonic feedback, solving exact hydrostatic equilibrium equation and offering flexible modeling of non-thermal pressure support, GODMAX has the capability to jointly fit all these profiles within the measurement uncertainties. This advancement enables, for the first time, robust joint analyses of multiple cosmic probes, including the kinetic and thermal Sunyaev-Zel'dovich effect, weak lensing, and X-ray observations. Furthermore, the model accurately captures correlations between the total matter power suppression due to baryonic feedback and local average thermodynamic quantities, such as the baryon fraction and integrated tSZ effect, in high-mass halos, aligning with observations from hydrodynamical simulations. Looking ahead, we forecast the expected constraints on cosmological and baryonic parameters from upcoming weak lensing catalogs from the LSST and tSZ maps from the Simons Observatory. This analysis underscores the importance of cross-correlations between weak lensing and tSZ in enhancing parameter constraints by resolving major systematic uncertainties due to baryonic physics. The GODMAX code leverages the JAX library, resulting in a fully differentiable halo model with native GPU compilation support.

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arXiv2023

Cosmic-Enu: An emulator for the non-linear neutrino power spectrum

Cosmology is poised to measure the neutrino mass sum $M_ν$ and has identified several smaller-scale observables sensitive to neutrinos, necessitating accurate predictions of neutrino clustering over a wide range of length scales. The FlowsForTheMasses non-linear perturbation theory for the massive neutrino power spectrum, $Δ^2_ν(k)$, agrees with its companion N-body simulation at the $10\%-15\%$ level for $k \leq 1~h/$Mpc. Building upon the Mira-Titan IV emulator for the cold matter, we use FlowsForTheMasses to construct an emulator for $Δ^2_ν(k)$ covering a large range of cosmological parameters and neutrino fractions $Ω_{ν,0} h^2 \leq 0.01$, which corresponds to $M_ν\leq 0.93$~eV. Consistent with FlowsForTheMasses at the $3.5\%$ level, it returns a power spectrum in milliseconds. Ranking the neutrinos by initial momenta, we also emulate the power spectra of momentum deciles, providing information about their perturbed distribution function. Comparing a $M_ν=0.15$~eV model to a wide range of N-body simulation methods, we find agreement to $3\%$ for $k \leq 3 k_\mathrm{FS} = 0.17~h/$Mpc and to $19\%$ for $k \leq 0.4~h/$Mpc. We find that the enhancement factor, the ratio of $Δ^2_ν(k)$ to its linear-response equivalent, is most strongly correlated with $Ω_{ν,0} h^2$, and also with the clustering amplitude $σ_8$. Furthermore, non-linearities enhance the free-streaming-limit scaling $\partial \log(Δ^2_ν/ Δ^2_{\rm m}) / \partial \log(M_ν)$ beyond its linear value of 4, increasing the $M_ν$-sensitivity of the small-scale neutrino density.

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arXiv2023

FLAMINGO: Calibrating large cosmological hydrodynamical simulations with machine learning

To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller-volume simulations, we model how the galaxy stellar mass function and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the stellar mass function. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters.

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arXiv2023

The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys

We introduce the Virgo Consortium's FLAMINGO suite of hydrodynamical simulations for cosmology and galaxy cluster physics. To ensure the simulations are sufficiently realistic for studies of large-scale structure, the subgrid prescriptions for stellar and AGN feedback are calibrated to the observed low-redshift galaxy stellar mass function and cluster gas fractions. The calibration is performed using machine learning, separately for three resolutions. This approach enables specification of the model by the observables to which they are calibrated. The calibration accounts for a number of potential observational biases and for random errors in the observed stellar masses. The two most demanding simulations have box sizes of 1.0 and 2.8 Gpc and baryonic particle masses of $1\times10^8$ and $1\times10^9 \text{M}_\odot$, respectively. For the latter resolution the suite includes 12 model variations in a 1 Gpc box. There are 8 variations at fixed cosmology, including shifts in the stellar mass function and/or the cluster gas fractions to which we calibrate, and two alternative implementations of AGN feedback (thermal or jets). The remaining 4 variations use the unmodified calibration data but different cosmologies, including different neutrino masses. The 2.8 Gpc simulation follows $3\times10^{11}$ particles, making it the largest ever hydrodynamical simulation run to $z=0$. Lightcone output is produced on-the-fly for up to 8 different observers. We investigate numerical convergence, show that the simulations reproduce the calibration data, and compare with a number of galaxy, cluster, and large-scale structure observations, finding very good agreement with the data for converged predictions. Finally, by comparing hydrodynamical and `dark-matter-only' simulations, we confirm that baryonic effects can suppress the halo mass function and the matter power spectrum by up to $\approx20$ per cent.

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arXiv2023

The FLAMINGO project: revisiting the $S_8$ tension and the role of baryonic physics

A number of recent studies have found evidence for a tension between observations of large-scale structure (LSS) and the predictions of the standard model of cosmology with the cosmological parameters fit to the cosmic microwave background (CMB). The origin of this '$S_8$ tension' remains unclear, but possibilities include new physics beyond the standard model, unaccounted for systematic errors in the observational measurements and/or uncertainties in the role that baryons play. Here we carefully examine the latter possibility using the new FLAMINGO suite of large-volume cosmological hydrodynamical simulations. We project the simulations onto observable harmonic space and compare with observational measurements of the power and cross-power spectra of cosmic shear, CMB lensing, and the thermal Sunyaev-Zel'dovich (tSZ) effect. We explore the dependence of the predictions on box size and resolution, cosmological parameters including the neutrino mass, and the efficiency and nature of baryonic 'feedback'. Despite the wide range of astrophysical behaviours simulated, we find that baryonic effects are not sufficiently large to remove the $S_8$ tension. Consistent with recent studies, we find the CMB lensing power spectrum is in excellent agreement with the standard model, whilst the cosmic shear power spectrum, tSZ effect power spectrum, and the cross-spectra between shear, CMB lensing, and the tSZ effect are all in varying degrees of tension with the CMB-specified standard model. These results suggest that some mechanism is required to slow the growth of fluctuations at late times and/or on non-linear scales, but that it is unlikely that baryon physics is driving this modification.

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arXiv2023

Testing the Collisionless Nature of Dark Matter with the Radial Acceleration Relation in Galaxy Clusters

The radial acceleration relation (RAR) represents a tight empirical relation between the inferred total and baryonic centripetal accelerations, $g_{\rm{tot}}=GM_{\rm{tot}}(<r)/r^2$ and $g_{\rm{bar}}=GM_{\rm{bar}}(<r)/r^2$, observed in galaxies and galaxy clusters. The tight correlation between these two quantities can provide insight into the nature of dark matter. Here we use BAHAMAS, a state-of-the-art suite of cosmological hydrodynamical simulations, to characterize the RAR in cluster-scale halos for both cold and collisionless dark matter (CDM) and self-interacting dark matter (SIDM) models. SIDM halos generally have reduced central dark matter densities, which reduces the total acceleration in the central region when compared with CDM. We compare the RARs in galaxy clusters simulated with different dark matter models to the RAR inferred from CLASH observations. Our comparison shows that the cluster-scale RAR in the CDM model provides an excellent match to the CLASH RAR obtained by Tian et al. including the high-acceleration regime probed by the brightest cluster galaxies (BCGs). By contrast, models with a larger SIDM cross-section yield increasingly poorer matches to the CLASH RAR. Excluding the BCG regions results in a weaker but still competitive constraint on the SIDM cross-section. Using the RAR data outside the central $r<100$kpc region, an SIDM model with $σ/m=0.3$cm$^{2}$g$^{-1}$ is disfavored at the $3.8σ$ level with respect to the CDM model. This study demonstrates the power of the cluster-scale RAR for testing the collisionless nature of dark matter.

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arXiv2023

Non-linear CMB lensing with neutrinos and baryons: FLAMINGO simulations vs. fast approximations

Weak lensing of the cosmic microwave background is rapidly emerging as a powerful probe of neutrinos, dark energy, and new physics. We present a fast computation of the non-linear CMB lensing power spectrum which combines non-linear perturbation theory at early times with power spectrum emulation using cosmological simulations at late times. Comparing our calculation with lightcones from the FLAMINGO 5.6 Gpc cube dark-matter-only simulation, we confirm its accuracy to 1% (2%) up to multipoles L = 3000 (L = 5000) for a nuLambdaCDM cosmology consistent with current data. Clustering suppression due to small-scale baryonic phenomena such as feedback from active galactic nuclei can reduce the lensing power by of order 10%. To our perturbation theory and emulator-based calculation we add SP(k), a new fitting function for this suppression, and confirm its accuracy compared to the FLAMINGO hydrodynamic simulations to 4% at L = 5000, with similar accuracy for massive neutrino models. We further demonstrate that scale-dependent suppression due to neutrinos and baryons approximately factorize, implying that a careful treatment of baryonic feedback can limit biasing neutrino mass constraints.

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arXiv2023

SP(k) -- A hydrodynamical simulation-based model for the impact of baryon physics on the non-linear matter power spectrum

Upcoming large-scale structure surveys will measure the matter power spectrum to approximately percent level accuracy with the aim of searching for evidence for new physics beyond the standard model of cosmology. In order to avoid biasing our conclusions, the theoretical predictions need to be at least as accurate as the measurements for a given choice of cosmological parameters. However, recent theoretical work has shown that complex physical processes associated with galaxy formation (particularly energetic feedback processes associated with stars and especially supermassive black holes) can alter the predictions by many times larger than the required accuracy. Here we present $\texttt{SP(k)}$, a model for the effects of baryon physics on the non-linear matter power spectrum based on a new large suite of hydrodynamical simulations. Specifically, the ANTILLES suite consists of 400 simulations spanning a very wide range of the "feedback landscape" and show that the effects of baryons on the matter power spectrum can be understood at approaching the percent level in terms of the mean baryon fraction of haloes, at scales of up to $k \lesssim 10 \, h \, $Mpc$^{-1}$ and redshifts up to $z=3$. For the range of scales and redshifts that will be probed by forthcoming cosmic shear measurements, most of the effects are driven by galaxy group-mass haloes ($M \sim 10^{13-14}$ M$_\odot$). We present a simple Python implementation of our model, available at $\href{https://github.com/jemme07/pyspk}{\mathrm{https{:}//github.com/jemme07/pyspk}}$, which can be used to incorporate baryon effects in standard gravity-only predictions, allowing for marginalisation over baryon physics within cosmological pipelines.

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arXiv2023

The halo bispectrum as a sensitive probe of massive neutrinos and baryon physics

The power spectrum has been a workhorse for cosmological studies of large-scale structure. However, the present-day matter distribution is highly non-Gaussian and significant cosmological information is also contained in higher-order correlation functions. Meanwhile, baryon physics (particularly AGN feedback) has previously been shown to strongly affect the two-point statistics but there has been limited exploration of its effects on higher-order functions to date. Here we use the BAHAMAS suite of cosmological hydrodynamical simulations to explore the effects of baryon physics and massive neutrinos on the halo bispectrum. In contrast to matter clustering which is suppressed by baryon physics, we find that the halo clustering is typically enhanced. The strength of the effect and the scale over which it extends depends on how haloes are selected. On small scales (k > 1 $h$ Mpc$^{-1}$, dominated by satellites of groups/clusters), we find that the bispectrum is highly sensitive to the efficiency of star formation and feedback, making it an excellent testing ground for galaxy formation models. We show that the effects of feedback and the effects of massive neutrinos are largely separable (independent of each other) and that massive neutrinos strongly suppress the halo bispectrum on virtually all scales up to the free-streaming length (apart from the smallest scales, where baryon physics dominates). The strong sensitivity of the bispectrum to neutrinos on the largest scales and galaxy formation physics on the smallest scales bodes well for upcoming precision measurements from the next generation of wide-field surveys.

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arXiv2022

GOGREEN: a critical assessment of environmental trends in cosmological hydrodynamical simulations at z ~ 1

Recent observations have shown that the environmental quenching of galaxies at z ~ 1 is qualitatively different to that in the local Universe. However, the physical origin of these differences has not yet been elucidated. In addition, while low-redshift comparisons between observed environmental trends and the predictions of cosmological hydrodynamical simulations are now routine, there have been relatively few comparisons at higher redshifts to date. Here we confront three state-of-the-art suites of simulations (BAHAMAS+MACSIS, EAGLE+Hydrangea, IllustrisTNG) with state-of-the-art observations of the field and cluster environments from the COSMOS/UltraVISTA and GOGREEN surveys, respectively, at z ~ 1 to assess the realism of the simulations and gain insight into the evolution of environmental quenching. We show that while the simulations generally reproduce the stellar content and the stellar mass functions of quiescent and star-forming galaxies in the field, all the simulations struggle to capture the observed quenching of satellites in the cluster environment, in that they are overly efficient at quenching low-mass satellites. Furthermore, two of the suites do not sufficiently quench the highest-mass galaxies in clusters, perhaps a result of insufficient feedback from AGN. The origin of the discrepancy at low stellar masses (Mstar <~ 1E10 Msun), which is present in all the simulations in spite of large differences in resolution, feedback implementations, and hydrodynamical solvers, is unclear. The next generation of simulations, which will push to significantly higher resolution and also include explicit modelling of the cold interstellar medium, may help to shed light on the low-mass tension.

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arXiv2022

Merger-induced galaxy transformations in the ARTEMIS simulations

Using the ARTEMIS set of 45 high-resolution cosmological simulations, we investigate a range of merger-induced dynamical transformations of Milky Way-like galaxies. We first identify populations of accreted stars on highly radial orbits, similar to the 'Gaia Sausage' in the Milky Way. We show that $\approx1/3$ of the ARTEMIS galaxies contain a similar feature, and confirm that they usually comprise stellar debris from the most massive accreted satellite. Selecting 15 galaxies with discs at the present-day, we study their changes around the times of the GS-like mergers. Dark matter haloes of many of these exhibit global changes in shape and orientation, with almost half becoming significantly more spherical when the mergers occur. Focusing on the galaxies themselves, we find that 4/15 have stellar discs which experience large changes in the orientation of their angular momentum (AM) axes, at rates of up to $\sim60$ degrees Gyr$^{-1}$. By calculating the orbital angular momentum axes of the satellites before they are accreted, we show that there is a tendency for the disc's AM to become more aligned with this axis after the merger. We also investigate the origin of in situ retrograde stars, analogous to the 'Splash' in the Milky Way. Tracing them back to earlier snapshots, we demonstrate that they were often disrupted onto their extreme orbits by multiple early mergers. We also find that the total mass of these stars outside the central regions positively correlates with the total accreted stellar mass.

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arXiv2022

High-resolution synthetic UV-submm images for Milky Way-mass simulated galaxies from the ARTEMIS project

We present redshift-zero synthetic dust-aware observations for the 45 Milky Way-mass simulated galaxies of the ARTEMIS project, calculated with the SKIRT radiative transfer code. The post-processing procedure includes components for star-forming regions, stellar sources, and diffuse dust. We produce and publicly release realistic high-resolution images for 50 commonly-used broadband filters from ultraviolet to sub-millimetre wavelengths and for 18 different viewing angles. We compare the simulated ARTEMIS galaxies to observed galaxies in the DustPedia database with similar stellar mass and star formation rate, and to synthetic observations of the simulated galaxies of the Auriga project produced in previous work using a similar post-processing technique. In all cases, global galaxy properties are derived using SED fitting. We find that, similar to Auriga, the post-processed ARTEMIS galaxies generally reproduce the observed scaling relations for global fluxes and physical properties, although dust extinction at FUV/UV wavelengths is underestimated and representative dust temperatures are lower than observed. At a resolved scale, we compare multi-wavelength non-parametric morphological properties of selected disc galaxies across the data sets. We find that the ARTEMIS galaxies largely reproduce the observed morphological trends as a function of wavelength, although they appear to be more clumpy and less symmetrical than observed. We note that the ARTEMIS and Auriga galaxies occupy adjacent regions in the specific star formation versus stellar mass plane, so that the synthetic observation data sets supplement each other.

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arXiv2022

Quenching of satellite galaxies of Milky Way analogues: reconciling theory and observations

The vast majority of low-mass satellite galaxies around the Milky Way and M31 appear virtually devoid of cool gas and show no signs of recent or ongoing star formation. Cosmological simulations demonstrate that such quenching is expected and is due to the harsh environmental conditions that satellites face when joining the Local Group (LG). However, recent observations of Milky Way analogues in the SAGA survey present a very different picture, showing the majority of observed satellites to be actively forming stars, calling into question the realism of current simulations and the typicality of the LG. Here we use the ARTEMIS suite of high-resolution cosmological hydrodynamical simulations to carry out a careful comparison with observations of dwarf satellites in the LG, SAGA, and the Local Volume (LV) survey. We show that differences between SAGA and the LG and LV surveys, as well as between SAGA and the ARTEMIS simulations, can be strongly reduced by considering differences in the host mass distributions and (more importantly) observational selection effects, specifically that low-mass satellites which have only recently been accreted are more likely to be star-forming, have a higher optical surface brightness, and are therefore more likely to be included in the SAGA survey. This picture is confirmed using data from the deeper LV survey, which shows pronounced quenching at low masses, in accordance with the predictions of LCDM-based simulations.

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arXiv2022

The morphology of star-forming gas and its alignment with galaxies and dark matter haloes in the EAGLE simulations

We present measurements of the morphology of star-forming gas in galaxies from the EAGLE simulations, and its alignment relative to stars and dark matter (DM). Imaging of such gas in the radio continuum enables weak lensing experiments that complement traditional optical approaches. Star-forming gas is typically more flattened than its associated stars and DM, particularly for present-day subhaloes of total mass $\sim$$10^{ 12-12.5} \mathrm{M_{ \odot}}$, which preferentially host star-forming galaxies with rotationally-supported stellar discs. Such systems have oblate, spheroidal star-forming gas distributions, but in both less- and more-massive subhaloes the distributions tend to be prolate, and its morphology correlates positively and significantly with that of its host galaxy's stars, both in terms of sphericity and triaxiality. The minor axis of star-forming gas most commonly aligns with the minor axis of its host subhalo's DM, but often aligns more closely with one of the other two principal axes of the DM distribution in prolate subhaloes. Star-forming gas aligns with DM less strongly than is the case for stars, but its morphological minor axis aligns closely with its kinematic axis, affording a route to observational identification of the unsheared morphological axis. The projected ellipticities of star-forming gas in EAGLE are consistent with shapes inferred from high-fidelity radio continuum images, and they exhibit greater shape noise than is the case for images of the stars, owing to the greater characteristic flattening of star-forming gas with respect to stars.

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