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Megan Taylor Tillman

Publications and source records attributed to Megan Taylor Tillman.

8 recordsLinked to original sources

Early Exploration of the Scientific Discovery Space for the Habitable Worlds Observatory

The Habitable Worlds Observatory (HWO) is a future NASA flagship mission concept identified by the Astro2020 Decadal Survey as the highest priority for large space missions. HWO should conduct "transformative astrophysics" and search for biosignatures in the atmospheres of approximately 25 potentially Earth-like planets. To further the early-stage development of HWO, NASA formed the Science, Technology, Architecture Review Team (START). In turn, START invited the scientific community to join working groups to explore the potential discovery space. In this paper, we present 70 science cases that resulted from this process. The cases address four scientific pillars: growth of galaxies (15 cases), evolution of the elements (13 cases), solar systems in context (32 cases), and living worlds (10 cases). Combined, they would address 27 of the 30 science questions and discovery areas identified by Astro2020. The 140 observing programs needed for the 70 investigations encompass a rich variety of spectroscopic (for 87% of science cases) and photometric (for 30%) observations extending from the UV to the NIR. Additionally, high-contrast and polarimetric capabilities would be needed for 34% and 27% of science cases, respectively. Access to UV wavelengths is critical: 83% of science cases need data at wavelengths <400 nm, and 26% extend to <100 nm. In the NIR, 26% of science cases need observations at wavelengths >=2000 nm. Pursuing the full portfolio of science would also necessitate precise astrometry for planet mass measurement, rapid response capabilities, a large instantaneous field of regard, non-sidereal tracking, saturation mitigation strategies, and high dynamic range.

astro-ph.IM↗

Learning the Universe with the 2nd Generation of CAMELS: Varying 35 parameters of the IllustrisTNG model in (50Mpc/h)^3 boxes

We present a new set of 1,192 cosmological simulations as part of the CAMELS project, in which a space of 35 cosmological, astrophysical, and numerical parameters is explored around the fiducial IllustrisTNG model. The volume of each of these simulations is (50Mpc/h)^3, eight times larger than that of previous CAMELS simulations. This provides lower sample variance as well as access to more massive halos and more diverse environments. We focus this work on exploring the advantages these differences provide for parameter inference powered by neural networks. We generate training sets based on the matter power spectra, projected maps of the volumes, graphs representing galaxy spatial distributions, and thermodynamical properties of massive halos. We employ multilayer perceptrons, convolutional neural networks, graph neural networks, and Gaussian processes, respectively, to extract information on the simulation parameters from these inputs while comparing systematically to analogous results from our previous generation of (25Mpc/h)^3 simulations. We generally find that the new, larger volumes produce tighter marginal constraints on the parameters, to degrees that vary between the different inputs. The improvements, however, scale more weakly than with the square root of the increase in the amount of data (i.e., physical volume). We interpret this as originating either from information loss due to mode coupling or from complex degeneracies in parameter space. We also discuss the effects on statistics of the intergalactic medium temperature from four new parameters that are varied in these simulations, which control the amplitude and timing of the ionizing background radiation. We publicly release the simulation outputs and ancillary data at https://camels.readthedocs.io.

astro-ph.CO↗

Implications of the nanoHertz Gravitational-Wave Background for Galactic Feedback and Massive Black Hole Growth

We investigate how pulsar timing array (PTA) measurements of the nanoHertz gravitational-wave background (GWB) can constrain models for the growth history of supermassive black holes (SMBHs) and how active galactic nucleus (AGN) and stellar feedback models can affect GWB predictions. Feedback regulates supermassive black hole (SMBH) growth, altering the black hole mass function (BHMF). Using BHMFs drawn from multiple cosmological simulation suites including IllustrisTNG, MillenniumTNG, Simba, and CAMELS, and combining these with a quasar-based SMBH binary population framework, we predict the resulting GWB amplitude under a range of different stellar and AGN feedback prescriptions. We find that the choice of both stellar and AGN feedback models alters the high-mass end of the BHMF and changes the predicted GWB amplitude by up to a factor of 2 for the fiducial simulations and a factor 10 for extreme feedback variations in CAMELS. Models with inefficient or absent AGN feedback produce abundant SMBHs and yield GWB amplitudes consistent with PTA data, yet fail in producing realistic galaxies. Fiducial models of AGN and stellar feedback suppress SMBH growth too much and under-predict the expected signal, an effect which could possibly be mitigated by more realistic black hole seeding and growth prescriptions. The mismatch between the GWB amplitudes predicted by cosmological simulations and that inferred by PTA measurements suggests that SMBH growth is more efficient or occurs earlier than captured by current models. This demonstrates that PTA measurements provide a powerful new probe of not only the SMBH population but also feedback physics.

astro-ph.GA↗

Exploring the impact of AGN feedback model variations on the Lyman-$α$ Forest Flux Power Spectrum

We study the effects of varying different Active Galactic Nuclei (AGN) feedback parameters on the Lyman-$α$ (Ly$α$) forest 1D transmitted flux power spectrum (P1D). We use the Cosmological and Astrophysics with Machine Learning Simulations (CAMELS) suite to explore variations on the Simba simulation AGN feedback model. The parameters explored include AGN momentum flux, AGN jet speed, supermassive black hole (SMBH) radiative efficiency, jet velocity threshold, and minimum SMBH mass needed to produce jet feedback. Although all parameters affect the P1D, this work explores the radiative efficiency, jet velocity threshold, and minimum SMBH mass in this context for the first time and finds the following results: Primarily, the most massive SMBHs impact the Ly$α$ forest through the jet feedback mode. While heating AGN jets to the virial temperature at injection aids in the removal of neutral hydrogen from the Ly$α$ forest, this heating also inhibits further jet feedback. Similar behaviors are seen when varying the SMBH radiative efficiency, with higher values resulting in a suppression of SMBH growth and thus a later reduction in AGN feedback and lower values directly reducing the impact of AGN feedback on the Ly$α$ forest P1D. These results imply that increasing the AGN feedback strength in the Simba simulation model suppresses the Ly$α$ forest P1D, but only if the feedback does not impact the number of massive jet producing BHs. Future studies of AGN feedback models will require careful exploration of the unique aspects of the specific subgrid model, and how they interact with one another, for a complete understanding of the potential astrophysical impacts of SMBH feedback.

astro-ph.GA↗

The Effects of AGN Feedback on the Lyman-$α$ Forest Flux Power Spectrum

We study the effects of AGN feedback on the Lyman-$α$ forest 1D flux power spectrum (P1D). Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba, the impact of AGN feedback is most dramatic at lower redshifts ($z<1$) and that AGN jet feedback plays the most significant role in altering the P1D. The effects of AGN feedback can be seen across a large range of wavenumbers ($1.5\times10^{-3} 2.0$), AGN feedback has a $2\%$ effect on the P1D for $k<5\times10^{-2}$ s/km and an $8\%$ effect for $k>5\times10^{-2}$ s/km. We show that the small scale effect is reduced when normalizing the simulation to the observed mean flux. On large scales, the effect of AGN feedback appears via a change in the IGM temperature and is thus unlikely to bias cosmological parameters. The strong AGN jets in the Simba simulation can reproduce the $z>2$ Lyman-$α$ forest. We stress that analyses comparing different AGN feedback models to future higher precision data will be necessary to determine the full extent of this effect.

astro-ph.CO↗

An Exploration of AGN and Stellar Feedback Effects in the Intergalactic Medium via the Low Redshift Lyman-$α$ Forest

We explore the role of galactic feedback on the low redshift Lyman-$α$ (Ly$α$)~forest ($z \lesssim 2$) statistics and its potential to alter the thermal state of the intergalactic medium. Using the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) suite, we explore variations of the AGN and stellar feedback models in the IllustrisTNG and Simba sub-grid models. We find that both AGN and stellar feedback in Simba play a role in setting the Ly$α$ forest column density distribution function (CDD) and the Doppler width ($b$-value) distribution. The Simba AGN jet feedback mode is able to efficiently transport energy out to the diffuse IGM causing changes in the shape and normalization of the CDD and a broadening of the $b$-value distribution. We find that stellar feedback plays a prominent role in regulating supermassive black hole growth and feedback, highlighting the importance of constraining stellar and AGN feedback simultaneously. In IllustrisTNG, the AGN feedback variations explored in CAMELS do not affect the Ly$α$ forest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low-$z$ Ly$α$ forest can be sensitive to changes in the ultraviolet background (UVB), stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM.

astro-ph.GA↗

Efficient long-range AGN feedback affects the low redshift Lyman-$α$ forest

Active galactic nuclei (AGN) feedback models are generally calibrated to reproduce galaxy observables such as the stellar mass function and the bimodality in galaxy colors. We use variations of the AGN feedback implementations in the IllustrisTNG (TNG) and Simba cosmological hydrodynamic simulations to show that the low redshift Lyman-$α$ forest can provide constraints on the impact of AGN feedback. We show that TNG over-predicts the number density of absorbers at column densities $N_{\rm HI} < 10^{14}$ cm$^{-2}$ compared to data from the Cosmic Origins Spectrograph (in agreement with previous work), and we demonstrate explicitly that its kinetic feedback mode, which is primarily responsible for galaxy quenching, has a negligible impact on the column density distribution (CDD) of absorbers. In contrast, we show that the fiducial Simba model which includes AGN jet feedback is the preferred fit to the observed CDD of the $z = 0.1$ Lyman-$α$ forest across five orders of magnitude in column density. We show that the Simba results with jets produce a quantitatively better fit to the observational data than the Simba results without jets, even when the UVB is left as a free parameter. AGN jets in Simba are high speed, collimated, weakly-interacting with the interstellar medium (via brief hydrodynamic decoupling) and heated to the halo virial temperature. Collectively these properties result in stronger long-range impacts on the IGM when compared to TNG's kinetic feedback mode, which drives isotropic winds with lower velocities at the galactic radius. Our results suggest that the low redshift Lyman-$α$ forest provides plausible evidence for long-range AGN jet feedback.

astro-ph.GA↗

Running Late: Testing Delayed Supermassive Black Hole Growth Models Against the Quasar Luminosity Function

Observations of massive galaxies at low redshift have revealed approximately linear scaling relations between the mass of a supermassive black hole (SMBH) and properties of its host galaxy. How these scaling relations evolve with redshift and whether they extend to lower-mass galaxies however remain open questions. Recent galaxy formation simulations predict a delayed, or "two-phase", growth of SMBHs: slow, highly intermittent BH growth due to repeated gas ejection by stellar feedback in low-mass galaxies, followed by more sustained gas accretion that eventually brings BHs onto the local scaling relations. The predicted two-phase growth implies a steep increase, or "kink", in BH-galaxy scaling relations at a stellar mass $M_{*}\sim5\times10^{10} M_{\odot}$. We develop a parametric, semi-analytic model to compare different SMBH growth models against observations of the quasar luminosity function (QLF) at $z\sim0.5-4$. We compare models in which the relation between SMBH mass and galaxy mass is purely linear versus two-phase models. The models are anchored to the observed galaxy stellar mass function, and the BH mass functions at different redshifts are consistently connected by the accretion rates contributing to the QLF. The best fits suggest that two-phase evolution is significantly preferred by the QLF data over a purely linear scaling relation. Moreover, when the model parameters are left free, the two-phase model fits imply a transition mass consistent with that predicted by simulations. Our analysis motivates further observational tests, including measurements of BH masses and AGN activity at the low-mass end, which could more directly test two-phase SMBH growth.

astro-ph.GA↗