The Romulus Cosmological Simulations: A Physical Approach to the Formation, Dynamics and Accretion Models of SMBHs

We present a novel implementation of supermassive black hole (SMBH) formation, dynamics, and accretion in the massively parallel tree+SPH code, ChaNGa. This approach improves the modeling of SMBHs in fully cosmological simulations, allowing for a more de- tailed analysis of SMBH-galaxy co-evolution throughout cosmic time. Our scheme includes novel, physically motivated models for SMBH formation, dynamics and sinking timescales within galaxies, and SMBH accretion of rotationally supported gas. The sub-grid parameters that regulate star formation (SF) and feedback from SMBHs and SNe are optimized against a comprehensive set of z = 0 galaxy scaling relations using a novel, multi-dimensional parameter search. We have incorporated our new SMBH implementation and parameter optimization into a new set of high resolution, large-scale cosmological simulations called Romulus. We present initial results from our flagship simulation, Romulus25, showing that our SMBH model results in SF efficiency, SMBH masses, and global SF and SMBH accretion histories at high redshift that are consistent with observations. We discuss the importance of SMBH physics in shaping the evolution of massive galaxies and show how SMBH feedback is much more effective at regulating star formation compared to SNe feedback in this regime. Further, we show how each aspect of our SMBH model impacts this evolution compared to more common approaches. Finally, we present a science application of this scheme studying the properties and time evolution of an example dual AGN system, highlighting how our approach allows simulations to better study galaxy interactions and SMBH mergers in the context of galaxy-BH co-evolution.Comment: 21 pages, 17 figures, Accepted to MNRAS, in press. Updated reference

The Little Galaxies that Could (Reionize the Universe): Predicting Faint End Slopes & Escape Fractions at z > 4

The sources that reionized the universe are still unknown, but likely candidates are faint but numerous galaxies. In this paper we present results from running a high resolution, uniform volume simulation, the Vulcan, to predict the number densities of undetectable, faint galaxies and their escape fractions of ionizing radiation, $f_\mathrm{esc}$, during reionization. Our approach combines a high spatial resolution, a realistic treatment of feedback and hydro processes, a strict threshold for minimum number of resolution elements per galaxy, and a converged measurement of $f_\mathrm{esc}$. We calibrate our physical model using a novel approach to create realistic galaxies at z=0, so the simulation is predictive at high redshifts. With this approach we can (1) robustly predict the evolution of the galaxy UV luminosity function at faint magnitudes down to $M_\mathrm{UV}$~-15, two magnitudes fainter than observations, and (2) estimate $f_\mathrm{esc}$ over a large range of galaxy masses based on the detailed stellar and gas distributions in resolved galaxies. We find steep faint end slopes, implying high number densities of faint galaxies, and the dependence of $f_\mathrm{esc}$ on the UV magnitude of a galaxy, given by the power-law: log $f_\mathrm{esc} = (0.51 \pm 0.04)M_\mathrm{UV} + 7.3 \pm 0.8$, with the faint population having $f_\mathrm{esc}$~35%. Convolving the UV luminosity function with $f_\mathrm{esc}$($M_\mathrm{UV}$), we find an ionizing emissivity that is (1) dominated by the faintest galaxies and (2) reionizes the universe at the appropriate rate, consistent with observational constraints of the ionizing emissivity and the optical depth to the decoupling surface tau_es, without the need for additional sources of ionizing radiation.Comment: 16 pages, 12 Figures, Accepted for publication to MNRA

An Efficient Bayesian Inference Framework for Coalescent-Based Nonparametric Phylodynamics

Phylodynamics focuses on the problem of reconstructing past population size dynamics from current genetic samples taken from the population of interest. This technique has been extensively used in many areas of biology, but is particularly useful for studying the spread of quickly evolving infectious diseases agents, e.g.,\ influenza virus. Phylodynamics inference uses a coalescent model that defines a probability density for the genealogy of randomly sampled individuals from the population. When we assume that such a genealogy is known, the coalescent model, equipped with a Gaussian process prior on population size trajectory, allows for nonparametric Bayesian estimation of population size dynamics. While this approach is quite powerful, large data sets collected during infectious disease surveillance challenge the state-of-the-art of Bayesian phylodynamics and demand computationally more efficient inference framework. To satisfy this demand, we provide a computationally efficient Bayesian inference framework based on Hamiltonian Monte Carlo for coalescent process models. Moreover, we show that by splitting the Hamiltonian function we can further improve the efficiency of this approach. Using several simulated and real datasets, we show that our method provides accurate estimates of population size dynamics and is substantially faster than alternative methods based on elliptical slice sampler and Metropolis-adjusted Langevin algorithm

Examining the histories of Bisa Butler's quilted portrait I know why the caged bird sings

Bisa Butler, a contemporary fiber artist, roots her practice in the processes of craft and the histories of Black women. By creating large-scale quilted portraits that express the layered histories of Black Americans, she investigates stories that are often buried under false accounts that perpetuate a Euro-centric interpretation of history. In this thesis, I explore three histories represented in Butler's 2019 quilted portrait, I Know Why the Caged Bird Sings, through the research methods of biography and intersectional feminism. First, I underscore the ways that Butler's fine art contributes to the inclusion of fiber art in the high art space. Second, using the subjects of her quilt as a guide, I examine the histories of middle class, educated Black women in the early 20th century, which offers insight into the intersections of race, gender, and class embedded in this work. Finally, I investigate the work and identities of Black artists (not Black art history) by placing Butler and her quilted portraits in conversation with artists like Faith Ringgold and the artists of the AfriCOBRA movement. I use my exploration into these three to offer a thorough reading of I Know Why the Caged Bird Sings, identifying how the histories intersect and overlap to inform the narrative of quilt scholarship. The layered histories in Butler's work demonstrate the need to integrate fiber art, specifically quilts, into the mainstream of art history.Includes bibliographical references