1967 Publications

8 in 10 Stars in the Milky Way Bulge Experience Stellar Encounters Within 1000 AU in a Gigayear

Moiya McTier, David Kipping, K. Johnston

The Galactic bulge is a tumultuous dense region of space, packed with stars separated by far smaller distances than those in the Solar neighborhood. A quantification of the frequency and proximity of close stellar encounters in this environment dictates the exchange of material, disruption of planetary orbits, and threat of sterilizing energetic events. We present estimated encounter rates for stars in the Milky Way bulge found using a combination of numerical and analytical methods. By integrating the orbits of bulge stars with varying orbital energy and angular momentum to find their positions over time, we were able to estimate how many close stellar encounters the stars should experience as a function of orbit shape. We determined that ~80% of bulge stars have encounters within 1000 AU and that half of bulge stars will have >35 such encounters, both over a gigayear. Our work has interesting implications for the long-term survivability of planets in the Galactic bulge.

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Better together: Elements of successful scientific software development in a distributed collaborative community

J. Koehler, B Weitzner, D. Renfrew, S Lewis, R Moretti, A Watkins, V. Mulligan, S Lyskov, J Adolf-Bryfogle, J Labonte, J Krys, Rosetta Commons Consortium, W Schief, D Gront, O Schueler-Furman, D Baker, J Gray, R Dunbrack, T Kortemme, A Leaver-Fay, C Strauss, J Meiler, B Kuhlman, J Gray , R. Bonneau

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.

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Observing photo-induced chiral edge states of graphene nanoribbons in pump-probe spectroscopies

Y. Chen, Y. Wang, M. Claassen, B. Moritz, T. P. Devereaux

Photo-induced edge states in low dimensional materials have attracted considerable attention due to the tunability of topological properties and dispersion. Specifically, graphene nanoribbons have been predicted to host chiral edge modes upon irradiation with circularly polarized light. Here, we present numerical calculations of time-resolved angle resolved photoemission spectroscopy (trARPES) and time-resolved resonant inelastic x-ray scattering (trRIXS) of a graphene nanoribbon. We characterize pump-probe spectroscopic signatures of photo-induced edge states, illustrate the origin of distinct spectral features that arise from Floquet topological edge modes, and investigate the roles of incoming photon energies and finite core-hole lifetime in RIXS. With momentum, energy, and time resolution, pump-probe spectroscopies can play an important role in understanding the behavior of photo-induced topological states of matter.

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A Population-Informed Mass Estimate for Pulsar J0740+6620

Galactic double neutron star systems have a tight mass distribution around ∼1.35M⊙, but the mass distribution of all known pulsars is broader. Here we reconstruct the Alsing, et al. (2018) bimodal mass distribution of pulsars observed in binary systems, incorporating data from observations of J0740+6620 which were not available at the time of that work. Because J0740+6620 is an outlier in the mass distribution with non-negligible uncertainty in its mass measurement, its mass receives a large correction from the population, becoming mJ0740+6620=2.03+0.10−0.08M⊙ (median and 68\% CI). Stochastic samples from our population model, including population-informed pulsar mass estimates, are available \href{https://github.com/farr/AlsingNSMassReplication}{at this https URL}.

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Electron ratchets: State of the field and future challenges

Bryan T. G. Lau, Ofer Kedem
Electron ratchets are non-equilibrium electronic devices that break inversion symmetry to produce currents from non-directional and random perturbations, without an applied net bias. They are characterized by strong parameter dependence, where small changes in operating conditions lead to large changes in the magnitude and even direction of the resulting current. This high sensitivity makes electron ratchets attractive research subjects, but leads to formidable challenges in their deeper study, and particularly to their useful application. This perspective reviews the progress that was made in the field starting from the first experimental electron ratchets in the late 1990s, and how the field spawned multiple designs with very different properties. We discuss the possible uses of electron ratchets in sensing and energy harvesting, and the specific issues encountered when idealized behavior meets complex reality. We promote an application-driven approach where complexity is not necessarily detrimental and argue that a system level perspective would be beneficial over reductionism. We highlight several promising research directions, which revolve around the intentional study of complex effects, and the modeling of realistic devices.
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Chemodynamics of barred galaxies in cosmological simulations: On the Milky Way’s quiescent merger history and in-situ bulge

F. Fragkoudi, R. J. J. Grand, R. Pakmor, ..., M. Ness, et. al.

We explore the chemodynamical properties of a sample of barred galaxies in the Auriga magneto-hydrodynamical cosmological zoom-in simulations, which form boxy/peanut (b/p) bulges, and compare these to the Milky Way (MW). We show that the Auriga galaxies which best reproduce the chemodynamical properties of stellar populations in the MW bulge have quiescent merger histories since redshift z∼3.5: their last major merger occurs at tlookback>12Gyrs, while subsequent mergers have a stellar mass ratio of ≤1:20, suggesting an upper limit of a few percent for the mass ratio of the recently proposed Gaia Sausage/Enceladus merger. These Auriga MW-analogues have a negligible fraction of ex-situ stars in the b/p region (30%) and exhibit X-shaped age and abundance distributions. Examining the discs in our sample, we find that in some cases a star-forming ring forms around the bar, which alters the metallicity of the inner regions of the galaxy. Further out in the disc, bar-induced resonances lead to metal-rich ridges in the Vϕ−r plane -- the longest of which is due to the Outer Lindblad Resonance. Our results suggest the Milky Way has an uncommonly quiet merger history, which leads to an essentially in-situ bulge, and highlight the significant effects the bar can have on the surrounding disc.

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DeepArk: modeling cis-regulatory codes of model species with deep learning

E Cofer, J Raimundo, A Tadych, Y Yamazaki, A. Wong, C Theesfeld, M Levine, O. Troyanskaya

To enable large-scale analyses of regulatory logic in model species, we developed DeepArk (https://DeepArk.princeton.edu), a set of deep learning models of the cis-regulatory codes of four widelystudied species: Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, and Mus musculus. DeepArk accurately predicts the presence of thousands of different context-specific regulatory features, including chromatin states, histone marks, and transcription factors. In vivo studies show that DeepArk can predict the regulatory impact of any genomic variant (including rare or not previously observed), and enables the regulatory annotation of understudied model species.

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April 28, 2020

Spatial Transcriptional Mapping of the Human Nephrogenic Program

N Lindström, R. Sealfon, X. Chen, R Parvez, A Ransick, G De Sena Brandine, J Guo, B Hill, T Tran, A Kim, J Zhou, A Tadych, A. Watters, A. Wong, E. Lovero, B Grubbs, M Thornton, J McMahon, A Smith, S Ruffins , C Armit, O. Troyanskaya, A McMahon

defects affecting 3% of newborns. The human kidney develops over a 30-week period in which a nephron progenitor pool gives rise to around a million nephrons. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlagen, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single cell RNA sequencing identified novel progenitor states which were spatially mapped to the nephron anatomy enabling the generation of functional gene-networks predicting interactions within and between nephron cell-types. Network mining identified known developmental disease genes and predicts new targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease, and enhance efforts to generate new kidney structures.

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April 28, 2020

Visualizing ’omic feature rankings and log-ratios using Qurro

M. Fedarko, C. Martino, J. Morton, A. González, G. Rahman, C. Marotz, J. Minich, E. Allen, R. Knight

Many tools for dealing with compositional ‘ ’omics’ data produce feature-wise values that can be ranked in order to describe features’ associations with some sort of variation. These values include differentials (which describe features’ associations with specified covariates) and feature loadings (which describe features’ associations with variation along a given axis in a biplot). Although prior work has discussed the use of these ‘rankings’ as a starting point for exploring the log-ratios of particularly high- or low-ranked features, such exploratory analyses have previously been done using custom code to visualize feature rankings and the log-ratios of interest. This approach is laborious, prone to errors and raises questions about reproducibility. To address these problems we introduce Qurro, a tool that interactively visualizes a plot of feature rankings (a ‘rank plot’) alongside a plot of selected features’ log-ratios within samples (a ‘sample plot’). Qurro’s interface includes various controls that allow users to select features from along the rank plot to compute a log-ratio; this action updates both the rank plot (through highlighting selected features) and the sample plot (through displaying the current log-ratios of samples). Here, we demonstrate how this unique interface helps users explore feature rankings and log-ratios simply and effectively.

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Sr2MoO4 and Sr2RuO4: Disentangling the Roles of Hund’s and van Hove Physics

Jonathan Karp, Max Bramberger, Martin Grunder, Ulrich Schollwöck, A. Millis, M. Zingl

Sr2MoO4 is isostructural to the unconventional superconductor Sr2RuO4 but with two electrons instead of two holes in the Mo/Ru-t2g orbitals. Both materials are Hund's metals, but while Sr2RuO4 has a van Hove singularity in close proximity to the Fermi surface, the van Hove singularity of Sr2MoO4 is far from the Fermi surface. By using density functional plus dynamical mean-field theory we determine the relative influence of van Hove and Hund's metal physics on the correlation properties. We show that theoretically predicted signatures of Hund's metal physics occur on the occupied side of the electronic spectrum of Sr2MoO4, identifying Sr2MoO4 as an ideal candidate system for a direct experimental confirmation of the theoretical concept of Hund's metals via photoemission spectroscopy.

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