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We analyse the properties of strongly barred disc galaxies using the TNG100 simulation, a cosmological hydrodynamical realization of the IllustrisTNG suite. We identify 270 disc galaxies at z = 0 in the stellar mass range M+ = 1010.4-11 M⊙, of which 40 percent are barred. Of the detected bars, more than half are strong. We find that the fraction of barred galaxies increases with stellar mass, in agreement with observational results. Strongly barred galaxies exhibit, overall, lower gas-to-stellar mass ratios compared to unbarred galaxies. The majority of barred galaxies are quenched (sSFR ∼ 10-11.7 yr-1), whereas unbarred galaxies continue to be active (sSFR ∼ 10-103 yr-1) on the main sequence of star-forming galaxies. We explore the evolution of strongly barred and unbarred galaxies to investigate their formation and quenching histories. We find that strong bars form between 0.5 < z < 1.5, with more massive galaxies hosting older bars. Strong bars form in galaxies with an early-established prominent disc component, undergoing periods of enhanced star formation and black hole accretion, possibly assisted by cosmological inflows. Unbarred galaxies, on the other hand, assemble most of their mass and disc component at late times. The nuclear region of strongly barred galaxies quenches shortly after bar formation, while unbarred galaxies remain active across time. Our findings are indicative of bar quenching, possibly assisted by nuclear feedback processes. We conclude that the cosmological environment, together with small-scale feedback processes, determine the chances of a galaxy to form a bar and to rapidly quench its central region.

ABSTRACT We introduce the thesan project, a suite of large volume ($L_\mathrm{box} = 95.5 \, \mathrm{cMpc}$) radiation-magnetohydrodynamic simulations that simultaneously model the large-scale statistical properties of the intergalactic medium during reionization and the resolved characteristics of the galaxies responsible for it. The flagship simulation has dark matter and baryonic mass resolutions of $3.1 \times 10^6\, {\rm M_\odot }$ and $5.8 \times 10^5\, {\rm M_\odot }$, respectively. The gravitational forces are softened on scales of 2.2 ckpc with the smallest cell sizes reaching 10 pc at z = 5.5, enabling predictions down to the atomic cooling limit. The simulations use an efficient radiation hydrodynamics solver (arepo-rt) that precisely captures the interaction between ionizing photons and gas, coupled to well-tested galaxy formation (IllustrisTNG) and dust models to accurately predict the properties of galaxies. Through a complementary set of medium resolution simulations we investigate the changes to reionization introduced by different assumptions for ionizing escape fractions, varying dark matter models, and numerical convergence. The fiducial simulation and model variations are calibrated to produce realistic reionization histories that match the observed evolution of the global neutral hydrogen fraction and electron scattering optical depth to reionization. They also match a wealth of high-redshift observationally inferred data, including the stellar-to-halo-mass relation, galaxy stellar mass function, star formation rate density, and the mass–metallicity relation, despite the galaxy formation model being mainly calibrated at z = 0. We demonstrate that different reionization models give rise to varied bubble size distributions that imprint unique signatures on the 21 cm emission, especially on the slope of the power spectrum at large spatial scales, enabling current and upcoming 21 cm experiments to accurately characte

© 2019. The American Astronomical Society. All rights reserved. We present a machine-learning (ML) approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep ML tool commonly used in image recognition tasks. The CNN is trained and tested on our sample of 7896 Chandra X-ray mock observations, which are based on 329 massive clusters from the simulation. Our CNN learns from a low resolution spatial distribution of photon counts and does not use spectral information. Despite our simplifying assumption to neglect spectral information, the resulting mass values estimated by the CNN exhibit small bias in comparison to the true masses of the simulated clusters (-0.02 dex) and reproduce the cluster masses with low intrinsic scatter, 8% in our best fold and 12% averaging over all. In contrast, a more standard core-excised luminosity method achieves 15%-18% scatter. We interpret the results with an approach inspired by Google DeepDream and find that the CNN ignores the central regions of clusters, which are known to have high scatter with mass.

ABSTRACT We introduce the thesan project, a suite of large volume ($L_\mathrm{box} = 95.5 \, \mathrm{cMpc}$) radiation-magnetohydrodynamic simulations that simultaneously model the large-scale statistical properties of the intergalactic medium during reionization and the resolved characteristics of the galaxies responsible for it. The flagship simulation has dark matter and baryonic mass resolutions of $3.1 \times 10^6\, {\rm M_\odot }$ and $5.8 \times 10^5\, {\rm M_\odot }$, respectively. The gravitational forces are softened on scales of 2.2 ckpc with the smallest cell sizes reaching 10 pc at z = 5.5, enabling predictions down to the atomic cooling limit. The simulations use an efficient radiation hydrodynamics solver (arepo-rt) that precisely captures the interaction between ionizing photons and gas, coupled to well-tested galaxy formation (IllustrisTNG) and dust models to accurately predict the properties of galaxies. Through a complementary set of medium resolution simulations we investigate the changes to reionization introduced by different assumptions for ionizing escape fractions, varying dark matter models, and numerical convergence. The fiducial simulation and model variations are calibrated to produce realistic reionization histories that match the observed evolution of the global neutral hydrogen fraction and electron scattering optical depth to reionization. They also match a wealth of high-redshift observationally inferred data, including the stellar-to-halo-mass relation, galaxy stellar mass function, star formation rate density, and the mass–metallicity relation, despite the galaxy formation model being mainly calibrated at z = 0. We demonstrate that different reionization models give rise to varied bubble size distributions that imprint unique signatures on the 21 cm emission, especially on the slope of the power spectrum at large spatial scales, enabling current and upcoming 21 cm experiments to accurately characte

Massive black hole (MBH) binaries, which are expected to form following the merger of their parent galaxies, produce gravitational waves that will be detectable by pulsar timing arrays at nanohertz frequencies (year periods). While no confirmed, compact MBH binary systems have been seen in electromagnetic observations, a large number of candidates have recently been identified in optical surveys of active galactic nucleus (AGN) variability. Using a combination of cosmological, hydrodynamic simulations; comprehensive, semi-analytic binary merger models; and analytic AGN spectra and variability prescriptions; we calculate the expected electromagnetic detection rates of MBH binaries as periodically variable AGN. In particular, we consider two independent variability models: (i) Doppler boosting due to large orbital velocities and (ii) hydrodynamic variability in which the fuelling of MBH accretion discs is periodically modulated by the companion. Our models predict that numerous MBH binaries should be present and distinguishable in the existing data. In particular, our fiducial models produce an expectation value of 0.2 (Doppler) and 5 (hydrodynamic) binaries to be identifiable in the Catalina survey (CRTS), while 20 and 100 are expected after 5 yr of LSST observations. The brightness variations in most systems are too small to be distinguishable, but almost 1 per cent of AGN at redshifts z 0.6 could be in massive binaries. We analyse the predicted binary parameters of observable systems and their selection biases, and include an extensive discussion of our model parameters and uncertainties.

During the next decade, gravitational waves will be observed from hundreds of binary inspiral events. When the redshifts of the host galaxies are known, these events can be used as “standard sirens”, sensitive to the expansion rate of the Universe. Measurements of the Hubble constant H0 from standard sirens can be done independently of other cosmological probes, and events occurring at z < 0.1 will allow us to infer H0 independentently of cosmological models. The next generation of spectroscopic galaxy surveys will play a crucial role in reducing systematic uncertainties in H0 from standard sirens, particularly for the numerous “dark sirens” which do not have an electromagnetic counterpart. In combination with large spectroscopic data sets, standard sirens with an EM counterpart are expected to constrain H0 to ∼ 1 − 2% precision within the next decade. This is competitive with the best estimates of H0 obtained to date and will help illuminate the current tension between existing measurements.

© 2019. The American Astronomical Society. All rights reserved. We present a machine-learning (ML) approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep ML tool commonly used in image recognition tasks. The CNN is trained and tested on our sample of 7896 Chandra X-ray mock observations, which are based on 329 massive clusters from the simulation. Our CNN learns from a low resolution spatial distribution of photon counts and does not use spectral information. Despite our simplifying assumption to neglect spectral information, the resulting mass values estimated by the CNN exhibit small bias in comparison to the true masses of the simulated clusters (-0.02 dex) and reproduce the cluster masses with low intrinsic scatter, 8% in our best fold and 12% averaging over all. In contrast, a more standard core-excised luminosity method achieves 15%-18% scatter. We interpret the results with an approach inspired by Google DeepDream and find that the CNN ignores the central regions of clusters, which are known to have high scatter with mass.

We calculate the properties, occurrence rates and detection prospects of individually resolvable 'single sources' in the low-frequency gravitational wave (GW) spectrum. Our simulations use the population of galaxies and massive black hole binaries from the Illustris cosmological hydrodynamic simulations, coupled to comprehensive semi-analytic models of the binary merger process. Using mock pulsar timing arrays (PTA) with, for the first time, varying red-noise models, we calculate plausible detection prospects for GW single sources and the stochasticGWbackground (GWB). Contrary to previous results,we find that single sources are at least as detectable as theGWbackground. Using mock PTA, we find that these 'foreground' sources (also 'deterministic'/'continuous') are likely to be detected with~20 yr total observing baselines. Detection prospects, and indeed the overall properties of single sources, are only moderately sensitive to binary evolution parameters - namely eccentricity and environmental coupling, which can lead to differences of ~5 yr in times to detection. Red noise has a stronger effect, roughly doubling the time to detection of the foreground between a white-noise only model (~10-15 yr) and severe red noise (~20-30 yr). The effect of red noise on the GWB is even stronger, suggesting that single source detections may be more robust. We find that typical signal-to-noise ratios for the foreground peak near f = 0.1 yr-1, and are much less sensitive to the continued addition of new pulsars to PTA.

Pulsar timing arrays (PTAs) around the world are using the incredible consistency of millisecond pulsars to measure low-frequency gravitational waves from (super)massive black hole (MBH) binaries. We use comprehensive MBH merger models based on cosmological hydrodynamic simulations to predict the spectrum of the stochastic gravitational wave background (GWB). We use real time-of-arrival specifications from the European, NANOGrav, Parkes, and International PTA (IPTA) to calculate realistic times to detection of the GWB across a wide range of model parameters. In addition to exploring the parameter space of environmental hardening processes (in particular: stellar scattering efficiencies), we have expanded our models to include eccentric binary evolution which can have a strong effect on the GWB spectrum. Our models show that strong stellar scattering and high characteristic eccentricities enhance the GWB strain amplitude near the PTA-sensitive 'sweet-spot' (near the frequency f = 1 yr-1), slightly improving detection prospects in these cases. While the GWB amplitude is degenerate between cosmological and environmental parameters, the location of a spectral turnover at low frequencies (f ≲ 0.1 yr-1) is strongly indicative of environmental coupling. At high frequencies (f ≳ 1 yr-1), the GWB spectral index can be used to infer the number density of sources and possibly their eccentricity distribution. Even with merger models that use pessimistic environmental and eccentricity parameters, if the current rate of PTA expansion continues, we find that the IPTA is highly likely to make a detection within about 10 yr.

Observations at low redshifts thus far fail to account for all of the baryons expected in the Universe according to cosmological constraints. A large fraction of the baryons presumably resides in a thin and warm–hot medium between the galaxies, where they are difficult to observe due to their low densities and high temperatures. Cosmological simulations of structure formation can be used to verify this picture and provide quantitative predictions for the distribution of mass in different large-scale structure components. Here we study the distribution of baryons and dark matter at different epochs using data from the Illustris simulation. We identify regions of different dark matter density with the primary constituents of large-scale structure, allowing us to measure mass and volume of haloes, filaments and voids. At redshift zero, we find that 49 per cent of the dark matter and 23 per cent of the baryons are within haloes more massive than the resolution limit of 2 × 10⁸ M⊙. The filaments of the cosmic web host a further 45 per cent of the dark matter and 46 per cent of the baryons. The remaining 31 per cent of the baryons reside in voids. The majority of these baryons have been transported there through active galactic nuclei feedback. We note that the feedback model of Illustris is too strong for heavy haloes, therefore it is likely that we are overestimating this amount. Categorizing the baryons according to their density and temperature, we find that 17.8 per cent of them are in a condensed state, 21.6 per cent are present as cold, diffuse gas, and 53.9 per cent are found in the state of a warm–hot intergalactic medium.

We present the full public release of all data from the Illustris simulation project. Illustris is a suite of large volume, cosmological hydrodynamical simulations run with the moving-mesh code Arepo and including a comprehensive set of physical models critical for following the formation and evolution of galaxies across cosmic time. Each simulates a volume of (106.5 Mpc)³ and self-consistently evolves five different types of resolution elements from a starting redshift of z=127 to the present day, z=0. These components are: dark matter particles, gas cells, passive gas tracers, stars and stellar wind particles, and supermassive black holes. This data release includes the snapshots at all 136 available redshifts, halo and subhalo catalogs at each snapshot, and two distinct merger trees. Six primary realizations of the Illustris volume are released, including the flagship Illustris-1 run. These include three resolution levels with the fiducial “full” baryonic physics model, and a dark matter only analog for each. In addition, we provide four distinct, high time resolution, smaller volume “subboxes”. The total data volume is ∼∼265 TB, including ∼∼800 full volume snapshots and ∼30,000 subbox snapshots. We describe the released data products as well as tools we have developed for their analysis. All data may be directly downloaded in its native HDF5 format. Additionally, we release a comprehensive, web-based API which allows programmatic access to search and data processing tasks. In both cases we provide example scripts and a getting-started guide in several languages: currently, IDL, Python, and Matlab. This paper addresses scientific issues relevant for the interpretation of the simulations, serves as a pointer to published and on-line documentation of the project, describes planned future additional data releases, and discusses technical aspects of the release

The separation of the faint cosmological background signal from bright astrophysical foregrounds remains one of the most daunting challenges of mapping the high-redshift intergalactic medium with the redshifted 21 cm line of neutral hydrogen. Advances in mapping and modeling of diffuse and point source foregrounds have improved subtraction accuracy, but no subtraction scheme is perfect. Precisely quantifying the errors and error correlations due to missubtracted foregrounds allows for both the rigorous analysis of the 21 cm power spectrum and for the maximal isolation of the "EoR window" from foreground contamination. We present a method to infer the covariance of foreground residuals from the data itself in contrast to previous attempts at a priori modeling. We demonstrate our method by setting limits on the power spectrum using a 3 h integration from the 128-tile Murchison Widefield Array. Observing between 167 and 198 MHz, we find at 95% confidence a best limit of Delta^2(k) < 3.7 x 10^4 mK^2 at comoving scale k = 0.18 hMpc^-1 and at z = 6.8, consistent with existing limits.

We confirm our recent prediction of the "pitchfork" foreground signature in power spectra of high-redshift 21 cm measurements where the interferometer is sensitive to large-scale structure on all baselines. This is due to the inherent response of a wide-field instrument and is characterized by enhanced power from foreground emission in Fourier modes adjacent to those considered to be the most sensitive to the cosmological H I signal. In our recent paper, many signatures from the simulation that predicted this feature were validated against Murchison Widefield Array (MWA) data, but this key pitchfork signature was close to the noise level. In this paper, we improve the data sensitivity through the coherent averaging of 12 independent snapshots with identical instrument settings and provide the first confirmation of the prediction with a signal-to-noise ratio > 10. This wide-field effect can be mitigated by careful antenna designs that suppress sensitivity near the horizon. Simple models for antenna apertures that have been proposed for future instruments such as the Hydrogen Epoch of Reionization Array and the Square Kilometre Array indicate they should suppress foreground leakage from the pitchfork by ~40 dB relative to the MWA and significantly increase the likelihood of cosmological signal detection in these critical Fourier modes in the three-dimensional power spectrum.

Magnetic fields play an important role in many astrophysical systems and a detailed understanding of their impact on the gas dynamics requires robust numerical simulations. Here we present a new method to evolve the ideal magnetohydrodynamic (MHD) equations on unstructured static and moving meshes that preserves the magnetic field divergence-free constraint to machine precision. The method overcomes the major problems of using a cleaning scheme on the magnetic fields instead, which is non-conservative, not fully Galilean invariant, does not eliminate divergence errors completely, and may produce incorrect jumps across shocks. Our new method is a generalization of the constrained transport (CT) algorithm used to enforce the ∇ · B = 0 condition on fixed Cartesian grids. Preserving ∇ · B = 0 at the discretized level is necessary to maintain the orthogonality between the Lorentz force and B. The possibility of performing CT on a moving mesh provides several advantages over static mesh methods due to the quasi-Lagrangian nature of the former (i.e. the mesh generating points move with the flow), such as making the simulation automatically adaptive and significantly reducing advection errors. Our method preserves magnetic fields and fluid quantities in pure advection exactly., National Science Foundation (U.S.). Graduate Research Fellowship (Grant DGE-1144152)

Recent high-precision proper motions from the Hubble Space Telescope suggest that the Large and Small Magellanic Clouds (LMC and SMC, respectively) are either on their first passage or on an eccentric long period (>6 Gyr) orbit about the Milky Way (MW). This differs markedly from the canonical picture in which the Clouds travel on a quasi-periodic orbit about the MW (period of ~2 Gyr). Without a short-period orbit about the MW, the origin of the Magellanic Stream, a young (1-2 Gyr old) coherent stream of H I gas that trails the Clouds ~150° across the sky, can no longer be attributed to stripping by MW tides and/or ram pressure stripping by MW halo gas. We propose an alternative formation mechanism in which material is removed by LMC tides acting on the SMC before the system is accreted by the MW. We demonstrate the feasibility and generality of this scenario using an N-body/smoothed particle hydrodynamics simulation with cosmologically motivated initial conditions constrained by the observations. Under these conditions, we demonstrate that it is possible to explain the origin of the Magellanic Stream in a first infall scenario. This picture is generically applicable to any gas-rich dwarf galaxy pair infalling toward a massive host or interacting in isolation.

We confirm our recent prediction of the "pitchfork" foreground signature in power spectra of high-redshift 21 cm measurements where the interferometer is sensitive to large-scale structure on all baselines. This is due to the inherent response of a wide-field instrument and is characterized by enhanced power from foreground emission in Fourier modes adjacent to those considered to be the most sensitive to the cosmological H i signal. In our recent paper, many signatures from the simulation that predicted this feature were validated against Murchison Widefield Array (MWA) data, but this key pitchfork signature was close to the noise level. In this paper, we improve the data sensitivity through the coherent averaging of 12 independent snapshots with identical instrument settings and provide the first confirmation of the prediction with a signal-to-noise ratio >10. This wide-field effect can be mitigated by careful antenna designs that suppress sensitivity near the horizon. Simple models for antenna apertures that have been proposed for future instruments such as the Hydrogen Epoch of Reionization Array and the Square Kilometre Array indicate they should suppress foreground leakage from the pitchfork by ~40 dB relative to the MWA and significantly increase the likelihood of cosmological signal detection in these critical Fourier modes in the three-dimensional power spectrum.

The separation of the faint cosmological background signal from bright astrophysical foregrounds remains one of the most daunting challenges of mapping the high-redshift intergalactic medium with the redshifted 21 cm line of neutral hydrogen. Advances in mapping and modeling of diffuse and point source foregrounds have improved subtraction accuracy, but no subtraction scheme is perfect. Precisely quantifying the errors and error correlations due to missubtracted foregrounds allows for both the rigorous analysis of the 21 cm power spectrum and for the maximal isolation of the "EoR window" from foreground contamination. We present a method to infer the covariance of foreground residuals from the data itself in contrast to previous attempts at a priori modeling. We demonstrate our method by setting limits on the power spectrum using a 3 h integration from the 128-tile Murchison Widefield Array. Observing between 167 and 198 MHz, we find at 95% confidence a best limit of ?2(k)<3.7×104mK2 at comoving scale k=0.18hMpc-1 and at z=6.8, consistent with existing limits.

Previous simulations of the growth of cosmic structures have broadly reproduced the ‘cosmic web’ of galaxies that we see in the Universe, but failed to create a mixed population of elliptical and spiral galaxies, because of numerical inaccuracies and incomplete physical models. Moreover, they were unable to track the small-scale evolution of gas and stars to the present epoch within a representative portion of the Universe. Here we report a simulation that starts 12 million years after the Big Bang, and traces 13 billion years of cosmic evolution with 12 billion resolution elements in a cube of 106.5 megaparsecs a side. It yields a reasonable population of ellipticals and spirals, reproduces the observed distribution of galaxies in clusters and characteristics of hydrogen on large scales, and at the same time matches the ‘metal’ and hydrogen content of galaxies on small scales.