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Christopher C. Lovell

Publications and source records attributed to Christopher C. Lovell.

79 records · Page 5Linked to original sources

Powderday: Dust Radiative Transfer for Galaxy Simulations

We present Powderday, a flexible, fast, open-source dust radiative transfer package designed to interface with galaxy formation simulations. Powderday builds on FSPS population synthesis models, Hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, which allows for significant run-time flexibility in the assumed stellar physics. We include a model for nebular line emission that can employ either precomputed Cloudy lookup tables (for efficiency), or direct photoionization calculations for all young stars (for flexibility). The dust content follows either observationally-motivated prescriptions, direct modeling from galaxy formation simulations, or a novel approach that includes the dust content via learning-based algorithms from the SIMBA cosmological galaxy formation simulation. AGN can additionally be included via a range of prescriptions. The output of these models are broadband SEDs, as well as filter-convolved images. Powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models, and seamlessly interfaces with GIZMO, AREPO, GASOLINE, CHANGA, and ENZO. We demonstrate the capabilities of the code via three applications: a model for the star formation rate (SFR) - infrared luminosity relation in galaxies (including the impact of AGN); the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs; and the impact of galaxy inclination angle on dust attenuation laws.

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Nebular Line Emission During the Epoch of Reionization

Nebular emission lines associated with galactic HII regions carry information about both physical properties of the ionised gas and the source of ionising photons as well as providing the opportunity of measuring accurate redshifts and thus distances once a cosmological model is assumed. While nebular line emission has been extensively studied at lower redshift there are currently only few constraints within the epoch of reionisation (EoR, $z>6$), chiefly due to the lack of sensitive near-IR spectrographs. However, this will soon change with the arrival of the Webb Telescope providing sensitive near-IR spectroscopy covering the rest-frame UV and optical emission of galaxies in the EoR. In anticipation of Webb we combine the large cosmological hydrodynamical simulation Bluetides with photoionisation modelling to predict the nebular emission line properties of galaxies at $z=8\to 13$. We find good agreement with the, albeit limited, existing direct and indirect observational constraints on equivalent widths though poorer agreement with luminosity function constraints.

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Recalibrating the Cosmic Star Formation History

The calibrations linking observed luminosities to the star formation rate depend on the assumed stellar population synthesis model, initial mass function, star formation and metal enrichment history, and whether reprocessing by dust and gas is included. Consequently the shape and normalisation of the inferred cosmic star formation history is sensitive to these assumptions. Using v2.2.1 of the Binary Population and Spectral Synthesis (\bpass) model we determine a new set of calibration coefficients for the ultraviolet, thermal-infrared, and, hydrogen recombination lines. These ultraviolet and thermal infrared coefficients are 0.15-0.2 dex higher than those widely utilised in the literature while the H$α$ coefficient is $\sim 0.35$ dex larger. These differences arise in part due to the inclusion binary evolution pathways but predominantly reflect an extension in the IMF to 300 $M_{\odot}$ and a change in the choice of reference metallicity. We use these new coefficients to recalibrate the cosmic star formation history, and find improved agreement between the integrated cosmic star formation history and the in-situ measured stellar mass density as a function of redshift. However, these coefficients produce new tension between star formation rate densities inferred from the ultraviolet and thermal-infrared and those from H$α$.

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Learning the Relationship between Galaxies Spectra and their Star Formation Histories using Convolutional Neural Networks and Cosmological Simulations

We present a new method for inferring galaxy star formation histories (SFH) using machine learning methods coupled with two cosmological hydrodynamic simulations. We train Convolutional Neural Networks to learn the relationship between synthetic galaxy spectra and high resolution SFHs from the EAGLE and Illustris models. To evaluate our SFH reconstruction we use Symmetric Mean Absolute Percentage Error (SMAPE), which acts as a true percentage error in the low-error regime. On dust-attenuated spectra we achieve high test accuracy (median SMAPE $= 10.5\%$). Including the effects of simulated observational noise increases the error ($12.5\%$), however this is alleviated by including multiple realisations of the noise, which increases the training set size and reduces overfitting ($10.9\%$). We also make estimates for the observational and modelling errors. To further evaluate the generalisation properties we apply models trained on one simulation to spectra from the other, which leads to only a small increase in the error (median SMAPE $\sim 15\%$). We apply each trained model to SDSS DR7 spectra, and find smoother histories than in the VESPA catalogue. This new approach complements the results of existing SED fitting techniques, providing star formation histories directly motivated by the results of the latest cosmological simulations.

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Characterising and Identifying Galaxy Protoclusters

We study the characteristics of galaxy protoclusters using the latest L-galaxies semi-analytic model. Searching for protoclusters on a scale of $\sim 10 \, \mathrm{cMpc}$ gives an excellent compromise between the completeness and purity of their galaxy populations, leads to high distinction from the field in overdensity space, and allows accurate determination of the descendant cluster mass. This scale is valid over a range of redshifts and selection criteria. We present a procedure for estimating, given a measured galaxy overdensity, the protocluster probability and its descendant cluster mass for a range of modelling assumptions, particularly taking into account the shape of the measurement aperture. This procedure produces lower protocluster probabilities compared to previous estimates using fixed size apertures. The relationship between AGN and protoclusters is also investigated, and shows significant evolution with redshift; at $z \sim 2$ the fraction of protoclusters traced by AGN is high, but the fraction of all AGN in protoclusters is low, whereas at $z \geqslant 5$ the fraction of protoclusters containing AGN is low, but most AGN are in protoclusters. We also find indirect evidence for the emergence of a passive sequence in protoclusters at $z \sim 2$, and note that a significant fraction of all galaxies reside in protoclusters at $z \geqslant 2$, particularly the most massive.

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Dust Obscured Star Forming Galaxies in the Early Universe

Motivated by recent observational constraints on dust reprocessed emission in star forming galaxies at $z\sim 6$ and above we use the very-large cosmological hydrodynamical simulation \bluetides\ to explore predictions for the amount of dust obscured star formation in the early Universe ($z>8$). \bluetides\ matches current observational constraints on both the UV luminosity function and galaxy stellar mass function and predicts that approximately $90\%$ of the star formation in high-mass ($M_{*}>10^{10}\,{\rm M_{\odot}}$) galaxies at $z=8$ is already obscured by dust. The relationship between dust attenuation and stellar mass predicted by \bluetides\ is consistent with that observed at lower redshift. However, observations of several individual objects at $z>6$ are discrepant with the predictions, though it is possible their uncertainties may have been underestimated. We find that the predicted surface density of $z\ge 8$ sub-mm sources is below that accessible to current {\em Herschel}, SCUBA-2, and ALMA sub-mm surveys. However, as ALMA continues to accrue additional surface area the population of $z>8$ dust-obscured galaxies may become accessible in the near future.

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The properties of the first galaxies in the BLUETIDES simulation

We employ the very large cosmological hydrodynamical simulation BLUETIDES to investigate the predicted properties of the galaxy population during the epoch of reionisation ($z>8$). BLUETIDES has a resolution and volume ($(400/h\approx 577)^{3}\,{\rm cMpc^3}$) providing a population of galaxies which is well matched to depth and area of current observational surveys targeting the high-redshift Universe. At $z=8$ BLUETIDES includes almost 160,000 galaxies with stellar masses $>10^{8}\,{\rm M_{\odot}}$. The population of galaxies predicted by BLUETIDES closely matches observational constraints on both the galaxy stellar mass function and far-UV ($150\,{\rm nm}$) luminosity function. Galaxies in BLUETIDES are characterised by rapidly increasing star formation histories. Specific star formation rates decrease with redshift though remain largely insensitive to stellar mass. As a result of the enhanced surface density of metals more massive galaxies are predicted to have higher dust attenuation resulting in a significant steepening of the observed far-UV luminosity function at high luminosities. The contribution of active SMBHs to the UV luminosities of galaxies with stellar masses $10^{9-10}\,{\rm M_{\odot}}$ is around $3\%$ on average. Approximately $25\%$ of galaxies with $M_{*}\approx 10^{10}\,{\rm M_{\odot}}$ are predicted to have active SMBH which contribute $>10\%$ of the total UV luminosity.

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