arXiv subjects

Sidney Lower

Publications and source records attributed to Sidney Lower.

12 recordsLinked to original sources

arXiv2023

TEMPLATES: Characterization of a Merger in the Dusty Lensing SPT0418-47 System

We present JWST and ALMA results for the lensing system SPT0418-47, which includes a strongly-lensed, dusty star-forming galaxy at redshift z=4.225 and an associated multiply-imaged companion. JWST NIRCam and MIRI imaging observations presented in this paper were acquired as part of the Early Release Science program Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star Formation (TEMPLATES). This data set provides robust, mutiwavelength detection of stellar light in both the main (SPT0418A) and companion (SPT0418B) galaxies, while the ALMA detection of [C II] emission confirms that SPT0418B lies at the same redshift as SPT0418A. From a source plane reconstruction, we infer that the projected physical separation of the two galaxies is $4.42\pm 0.05$ kpc. We derive total magnifications of $\mu=29.5\pm1.2$ and $\mu=4.2\pm 0.9$ for SPT0418A and SPT0418B, respectively. We use both CIGALE and PROSPECTOR to derive stellar masses. The stellar mass ratio of SPT0418A and SPT0418B is approximately 4 to 1 ($4.5\pm 1.0$ for CIGALE and $4.2^{+1.9}_{-1.6}$ for PROSPECTOR). We also see evidence of extended structure associated with SPT0418A in the lensing reconstruction that is suggestive of a tidal feature. Interestingly, the star formation rates and stellar masses of both galaxies are consistent with the main sequence of star-forming galaxies at this epoch, indicating that this ongoing interaction has not noticeably elevated the star formation levels.

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arXiv2023

Outshining by Recent Star Formation Prevents the Accurate Measurement of High-z Galaxy Stellar Masses

In this paper, we demonstrate that the inference of galaxy stellar masses via spectral energy distribution (SED) fitting techniques for galaxies formed in the first billion years after the Big Bang carries fundamental uncertainties owing to the loss of star formation history (SFH) information from the very first episodes of star formation in the integrated spectra of galaxies. While this early star formation can contribute substantially to the total stellar mass of high-redshift systems, ongoing star formation at the time of detection outshines the residual light from earlier bursts, hampering the determination of accurate stellar masses. As a result, order of magnitude uncertainties in stellar masses can be expected. We demonstrate this potential problem via direct numerical simulation of galaxy formation in a cosmological context. In detail, we carry out two cosmological simulations with significantly different stellar feedback models which span a significant range in star formation history burstiness. We compute the mock SEDs for these model galaxies at z=7 via 3D dust radiative transfer calculations, and then backwards fit these SEDs with Prospector SED fitting software. The uncertainties in derived stellar masses that we find for z>7 galaxies motivate the development of new techniques and/or star formation history priors to model early Universe star formation.

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arXiv2023

Cosmic Sands II: Challenges in Predicting and Measuring High-z Dust Temperatures

In the current era of high-z galaxy discovery with JWST and ALMA, our ability to study the stellar populations and ISM conditions in a diverse range of galaxies at Cosmic Dawn has rapidly improved. At the same time, the need to understand the current limitations in modeling galaxy formation processes and physical properties in order to interpret these observations is critical. Here, we study the challenges in modeling galaxy dust temperatures, both in the context of forward modeling galaxy spectral properties from a hydrodynamical simulation and via backwards modeling galaxy physical properties from mock observations of far-infrared dust emission. Using the Simba model for galaxy formation combined with Powderday radiative transfer, we can accurately predict the evolution of dust at high redshift, though several aspects of the model are essentially free parameters (dust composition, sub-resolution dust in star-forming regions) that dull the predictive power of the model dust temperature distributions. We also highlight the uncertainties in the backwards modeling methods, where we find the commonly used models and assumptions to fit FIR SEDs and infer dust temperatures (e.g., single temperature, optically thin modified blackbody) largely fail to capture the complexity of high-z dusty galaxies. We caution that conclusions inferred from both simulations -- limited by resolution and post-processing techniques -- and observations -- limited by sparse data and simplistic model parameterizations -- are susceptible to unique and nuanced uncertainties that can limit the usefulness of current high-z dust measurements.

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arXiv2022

Cosmic Sands: The Origin of Dusty, Star-forming Galaxies in the Epoch of Reionization

We present the Cosmic Sands suite of cosmological zoom-in simulations based on the Simba galaxy formation model in order to study the build up of the first massive and dusty galaxies in the early Universe. Residing in the most massive halos, we find that the compact proto-massive galaxies undergo nearly continuous mergers with smaller subhalos, boosting star formation rates (SFRs) and the build up of stellar mass. The galaxies are already appreciably chemically evolved by z=10, with modeled dust masses comparable to those inferred from observations in the same epoch. We track gas accretion onto the galaxies to understand how extreme SFRs can be sustained by these early systems. We find that smooth gas accretion can maintain SFRs above 250 M$_{\odot}$ / yr but to achieve SFRs that boost galaxies well above the main sequence, a larger perturbation like a gas-rich major merger is necessary to trigger a starburst episode. Post-processing the Cosmic Sands simulations with dust radiative transfer, we find that while the infrared luminosities of the most dust rich galaxies are comparable to local ULIRGs, they are substantially dimmer than classical z=2 sub-millimeter galaxies. We end with a discussion on the possible reasons for this discrepancy at the highest masses and the future work we intend to carry out to study the chemical enrichment of the earliest dusty galaxies.

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arXiv2022

Star Formation Suppresion by Tidal Removal of Cold Molecular Gas from an Intermediate-Redshift Massive Post-Starburst Galaxy

Observations and simulations have demonstrated that star formation in galaxies must be actively suppressed to prevent the formation of over-massive galaxies. Galactic outflows driven by stellar feedback or supermassive black hole accretion are often invoked to regulate the amount of cold molecular gas available for future star formation, but may not be the only relevant quenching processes in all galaxies. We present the discovery of vast molecular tidal features extending up to 64 kpc outside of a massive z=0.646 post-starburst galaxy that recently concluded its primary star-forming episode. The tidal tails contain (1.2 +/- 0.1)x10^10 Msun of molecular gas, 47 +/- 5 % of the total cold gas reservoir of the system. Both the scale and magnitude of the molecular tidal features are unprecedented compared to all known nearby or high-redshift merging systems. We infer that the cold gas was stripped from the host galaxies during the merger, which is most likely responsible for triggering the initial burst phase and the subsequent suppression of star formation. While only a single example, this result shows that galaxy mergers can regulate the cold gas contents in distant galaxies by directly removing a large fraction of the molecular gas fuel, and plausibly suppress star formation directly, a qualitatively different physical mechanism than feedback-driven outflows.

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arXiv2022

Recovering the star formation histories of recently-quenched galaxies: the impact of model and prior choices

Accurate models of the star formation histories (SFHs) of recently-quenched galaxies can provide constraints on when and how galaxies shut down their star formation. The recent development of "non-parametric" SFH models promises the flexibility required to make these measurements. However, model and prior choices significantly affect derived SFHs, particularly for post-starburst galaxies (PSBs) which have sharp changes in their recent SFH. In this paper, we create mock PSBs, then use the Prospector SED fitting software to test how well four different SFH models recover key properties. We find that a two-component parametric model performs well for our simple mock galaxies, but is sensitive to model mismatches. The fixed- and flexible-bin non-parametric models included in Prospector are able to rapidly quench a major burst of star formation, but systematically underestimate the post-burst age by up to 200 Myr. We develop a custom SFH model that allows for additional flexibility in the recent SFH. Our flexible non-parametric model is able to constrain post-burst ages with no significant offset and just ~90 Myr of scatter. Our results suggest that while standard non-parametric models are able to recover first-order quantities of the SFH (mass, SFR, average age), accurately recovering higher-order quantities (burst fraction, quenching time) requires careful consideration of model flexibility. These mock recovery tests are a critical part of future SFH studies. Finally, we show that our new, public SFH model is able to accurately recover the properties of mock star-forming and quiescent galaxies and is suitable for broader use in the SED fitting community.

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arXiv2022

How Well Can We Measure Galaxy Dust Attenuation Curves? The Impact of the Assumed Star-Dust Geometry Model in SED Fitting

One of the most common methods for inferring galaxy attenuation curves is via spectral energy distribution (SED) modeling, where the dust attenuation properties are modeled simultaneously with other galaxy physical properties. In this paper, we assess the ability of SED modeling to infer these dust attenuation curves from broadband photometry, and suggest a new flexible model that greatly improves the accuracy of attenuation curve derivations. To do this, we fit mock SEDs generated from the Simba cosmological simulation with the Prospector SED fitting code. We consider the impact of the commonly-assumed uniform screen model and introduce a new non-uniform screen model parameterized by the fraction of unobscured stellar light. This non-uniform screen model allows for a non-zero fraction of stellar light to remain unattenuated, resulting in a more flexible attenuation curve shape by decoupling the shape of the UV attenuation curve from the optical attenuation curve. The ability to constrain the dust attenuation curve is significantly improved with the use of a non-uniform screen model, with the median offset in UV attenuation decreasing from $-0.30$ dex with a uniform screen model to $-0.17$ dex with the non-uniform screen model. With this increase in dust attenuation modeling accuracy, we also improve the star formation rates (SFRs) inferred with the non-uniform screen model, decreasing the SFR offset on average by $0.12$ dex. We discuss the efficacy of this new model, focusing on caveats with modeling star-dust geometries and the constraining power of available SED observations.

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arXiv2021

SQuIGGLE: Studying Quenching in Intermediate-z Galaxies -- Gas, AnguLar Momentum, and Evolution

We describe the SQuIGGLE survey of intermediate-redshift post-starburst galaxies. We leverage the large sky coverage of the SDSS to select ~1300 recently-quenched galaxies at 0.5 75% of SQuIGGLE galaxies formed at least a quarter of their total stellar mass in the recent burst, which ended just ~200Myr before observation. We find that SQuIGGLE galaxies are on average younger and more burst-dominated than most other z<~1 post-starburst samples. This large sample of bright post-starburst galaxies at intermediate redshift opens a wide range of studies into the quenching process. In particular, the full SQuIGGLE survey will investigate the molecular gas reservoirs, morphologies, kinematics, resolved stellar populations, AGN incidence, and infrared properties of this unique sample of galaxies in order to place definitive constraints on the quenching process.

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arXiv2021

Quenching and the UVJ diagram in the SIMBA cosmological simulation

Over the past decade, rest-frame color-color diagrams have become popular tools for selecting quiescent galaxies at high redshift, breaking the color degeneracy between quiescent and dust-reddened star-forming galaxies. In this work, we study one such color-color selection tool -- the rest-frame $U-V$ vs. $V-J$ diagram -- by employing mock observations of cosmological galaxy formation simulations. In particular, we conduct numerical experiments assessing both trends in galaxy properties in UVJ space and the color-color evolution of massive galaxies as they quench at redshifts $z\sim 1$--$2$. We find that our models broadly reproduce the observed UVJ diagram at $z=1$--$2$, including (for the first time in a cosmological simulation) reproducing the population of extremely dust-reddened galaxies in the top right of the UVJ diagram. However, our models primarily populate this region with low-mass galaxies and do not produce as clear a bimodality between star-forming and quiescent galaxies as is seen in observations. The former issue is due to an excess of dust in low-mass galaxies and relatively gray attenuation curves in high-mass galaxies, while the latter is due to the overpopulation of the green valley in SIMBA. When investigating the time evolution of galaxies on the UVJ diagram, we find that the quenching pathway on the UVJ diagram is independent of the quenching timescale, and instead dependent primarily on the average specific star formation rate in the 1 Gyr prior to the onset of quenching. Our results support the interpretation of different quenching pathways as corresponding to the divergent evolution of post-starburst and green valley galaxies.

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arXiv2021

{\sc mirkwood:} Fast and Accurate SED Modeling Using Machine Learning

Traditional spectral energy distribution (SED) fitting codes used to derive galaxy physical properties are often uncertain at the factor of a few level owing to uncertainties in galaxy star formation histories and dust attenuation curves. Beyond this, Bayesian fitting (which is typically used in SED fitting software) is an intrinsically compute-intensive task, often requiring access to expensive hardware for long periods of time. To overcome these shortcomings, we have developed {\sc mirkwood}: a user-friendly tool comprising of an ensemble of supervised machine learning-based models capable of non-linearly mapping galaxy fluxes to their properties. By stacking multiple models, we marginalize against any individual model's poor performance in a given region of the parameter space. We demonstrate \textsc{mirkwood}'s significantly improved performance over traditional techniques by training it on a combined data set of mock photometry of z=0 galaxies from the \textsc{Simba}, \textsc{EAGLE} and \textsc{IllustrisTNG} cosmological simulations, and comparing the derived results with those obtained from traditional SED fitting techniques. \textsc{mirkwood} is also able to account for uncertainties arising both from intrinsic noise in observations, and from finite training data and incorrect modeling assumptions. To increase the added value to the observational community, we use Shapley value explanations (SHAP) to fairly evaluate the relative importance of different bands to understand why particular predictions were reached. We envisage \textsc{mirkwood} to be an evolving, open-source framework that will provide highly accurate physical properties from observations of galaxies as compared to traditional SED fitting.

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arXiv2020

How Well Can We Measure the Stellar Mass of a Galaxy: The Impact of the Assumed Star Formation History Model in SED Fitting

The primary method for inferring the stellar mass ($M_*$) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history and dust attenuation law that can severely impact the accuracy of derived physical properties from SED modeling. Here, we examine the effect that the assumed star formation history (SFH) has on the stellar properties inferred from SED fitting by ground truthing them against mock observations of high-resolution cosmological hydrodynamic galaxy formation simulations. Classically, SFHs are modeled with simplified parameterized functional forms, but these forms are unlikely to capture the true diversity of galaxy SFHs and may impose systematic biases with under-reported uncertainties on results. We demonstrate that flexible nonparametric star formation histories outperform traditional parametric forms in capturing variations in galaxy star formation histories, and as a result, lead to significantly improved stellar masses in SED fitting. We find a decrease in the average bias of 0.4 dex with a delayed-$τ$ model to a bias of just under 0.05 dex for the nonparametric model. Similarly, using nonparametric star formation histories in SED fitting result in increased accuracy in recovered galaxy star formation rates (SFRs) and stellar ages.

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arXiv2020

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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