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The element abundance pattern found in Milky Way disk stars is close to two-dimensional, dominated by production from one prompt process and one delayed process. This simplicity is remarkable, since the elements are produced by a multitude of nucleosynthesis mechanisms operating in stars with a wide range of progenitor masses. We fit the abundances of 14 elements for 48,659 red-giant stars from APOGEE Data Release 17 using a flexible, data-drivenK-process model—dubbedKPM. In our fiducial model, withK= 2, each abundance in each star is described as the sum of a prompt and a delayed process contribution. We find thatKPMwithK= 2 is able to explain the abundances well, recover the observed abundance bimodality, and detect the bimodality over a greater range in metallicity than has previously been possible. We compare to prior work by Weinberg et al., finding thatKPMproduces similar results, but thatKPMbetter predicts stellar abundances, especially for the elements C+N and Mn and for stars at supersolar metallicities. The model fixes the relative contribution of the prompt and delayed processes to two elements to break degeneracies and improve interpretability; we find that some of the nucleosynthetic implications are dependent upon these detailed choices. We find that moving to four processes adds flexibility and improves the model’s ability to predict the stellar abundances, but does not qualitatively change the story. The results ofKPMwill help us to interpret and constrain the formation of the Galaxy disk, the relationship between abundances and ages, and the physics of nucleosynthesis.

 

Abstract Discoveries of gaps in data have been important in astrophysics. For example, there are kinematic gaps opened by resonances in dynamical systems, or exoplanets of a certain radius that are empirically rare. A gap in a data set is a kind of anomaly, but in an unusual sense: instead of being a single outlier data point, situated far from other data points, it is a region of the space, or a set of points, that is anomalous compared to its surroundings. Gaps are both interesting and hard to find and characterize, especially when they have nontrivial shapes. We present in this paper a statistic that can be used to estimate the (local) “gappiness” of a point in the data space. It uses the gradient and Hessian of the density estimate (and thus requires a twice-differentiable density estimator). This statistic can be computed at (almost) any point in the space and does not rely on optimization; it allows us to highlight underdense regions of any dimensionality and shape in a general and efficient way. We illustrate our method on the velocity distribution of nearby stars in the Milky Way disk plane, which exhibits gaps that could originate from different processes. Identifying and characterizing those gaps could help determine their origins. We provide in an appendix implementation notes and additional considerations for finding underdensities in data, using critical points and the properties of the Hessian of the density. 7 7 A Python implementation of t methods presented here is available at https://github.com/contardog/FindTheGap . 

Abstract In the coming decade, thousands of stellar streams will be observed in the halos of external galaxies. What fundamental discoveries will we make about dark matter from these streams? As a first attempt to look at these questions, we model Magellan/Megacam imaging of the Centaurus A (Cen A) disrupting dwarf companion Dwarf 3 (Dw3) and its associated stellar stream, to find out what can be learned about the Cen A dark matter halo. We develop a novel external galaxy stream-fitting technique and generate model stellar streams that reproduce the stream morphology visible in the imaging. We find that there are many viable stream models that fit the data well, with reasonable parameters, provided that Cen A has a halo mass larger than M 200 > 4.70 × 10 12 M ⊙ . There is a second stream in Cen A’s halo that is also reproduced within the context of this same dynamical model. However, stream morphology in the imaging alone does not uniquely determine the mass or mass distribution for the Cen A halo. In particular, the stream models with high likelihood show covariances between the inferred Cen A mass distribution, the inferred Dw3 progenitor mass, the Dw3 velocity, and the Dw3 line-of-sight position. We show that these degeneracies can be broken with radial-velocity measurements along the stream, and that a single radial velocity measurement puts a substantial lower limit on the halo mass. These results suggest that targeted radial-velocity measurements will be critical if we want to learn about dark matter from extragalactic stellar streams. 

A reliable estimate of the redshift distributionn(z) is crucial for using weak gravitational lensing and large-scale structures of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of next-generation weak-lensing surveys are expected to be unavailable, making photometric redshift (photo-z) probability density functions (PDFs) the next best alternative for comprehensively encapsulating the nontrivial systematics affecting photo-zpoint estimation. The established stacked estimator ofn(z) avoids reducing photo-zPDFs to point estimates but yields a systematically biased estimate ofn(z) that worsens with a decreasing signal-to-noise ratio, the very regime where photo-zPDFs are most necessary. We introduce Cosmological Hierarchical Inference with Probabilistic Photometric Redshifts (CHIPPR), a statistically rigorous probabilistic graphical model of redshift-dependent photometry that correctly propagates the redshift uncertainty information beyond the best-fit estimator ofn(z) produced by traditional procedures and is provably the only self-consistent way to recovern(z) from photo-zPDFs. We present thechipprprototype code, noting that the mathematically justifiable approach incurs computational cost. TheCHIPPRapproach is applicable to any one-point statistic of any random variable, provided the prior probability density used to produce the posteriors is explicitly known; if the prior is implicit, as may be the case for popular photo-ztechniques, then the resulting posterior PDFs cannot be used for scientific inference. We therefore recommend that the photo-zcommunity focus on developing methodologies that enable the recovery of photo-zlikelihoods with support over all redshifts, either directly or via a known prior probability density.

 

Signatures of vertical disequilibrium have been observed across the Milky Way’s (MW’s) disk. These signatures manifest locally as unmixed phase spirals inz–v_zspace (“snails-in-phase”), and globally as nonzero meanzandv_z, wrapping around the disk into physical spirals in thex–yplane (“snails-in-space”). We explore the connection between these local and global spirals through the example of a satellite perturbing a test-particle MW-like disk. We anticipate our results to broadly apply to any vertical perturbation. Using az–v_zasymmetry metric, we demonstrate that in test-particle simulations: (a) multiple local phase-spiral morphologies appear when stars are binned by azimuthal actionJ_ϕ, excited by a single event (in our case, a satellite disk crossing); (b) these distinct phase spirals are traced back to distinct disk locations; and (c) they are excited at distinct times. Thus, local phase spirals offer a global view of the MW’s perturbation history from multiple perspectives. Using a toy model for a Sagittarius (Sgr)–like satellite crossing the disk, we show that the full interaction takes place on timescales comparable to orbital periods of disk stars withinR≲ 10 kpc. Hence such perturbations have widespread influence, which peaks in distinct regions of the disk at different times. This leads us to examine the ongoing MW–Sgr interaction. While Sgr has not yet crossed the disk (currently,z_Sgr≈ −6 kpc,v_z,Sgr≈ 210 km s⁻¹), we demonstrate that the peak of the impact has already passed. Sgr’s pull over the past 150 Myr creates a globalv_zsignature with amplitude ∝M_Sgr, which might be detectable in future spectroscopic surveys.

 

Abstract Gaia DR2 has provided an unprecedented wealth of information about the positions and motions of stars in our Galaxy, and has highlighted the degree of disequilibria in the disc. As we collect data over a wider area of the disc it becomes increasingly appealing to start analysing stellar actions and angles, which specifically label orbit space, instead of their current phase space location. Conceptually, while $\bar{x}$ and $\bar{v}$ tell us about the potential and local interactions, grouping in action puts together stars that have similar frequencies and hence similar responses to dynamical effects occurring over several orbits. Grouping in actions and angles refines this further to isolate stars which are travelling together through space and hence have shared histories. Mixing these coordinate systems can confuse the interpretation. For example, it has been suggested that by moving stars to their guiding radius, the Milky Way spiral structure is visible as ridge-like overdensities in the Gaia data (Khoperskov et al. 2020). However, in this work, we show that these features are in fact the known kinematic moving groups, both in the Lz − φ and the vR − vφ planes. Using simulations we show how this distinction will become even more important as we move to a global view of the Milky Way. As an example, we show that the radial velocity wave seen in the Galactic disc in Gaia and APOGEE should become stronger in the action-angle frame, and that it can be reproduced by transient spiral structure.