Chempy\mathit{Chempy}: A flexible chemical evolution model for abundance fitting - Do the Sun's abundances alone constrain chemical evolution models?

Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history, the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova type Ia (SN Ia). Unlike established approaches, Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets. We extend Chempy to a multi-zone scheme. As an illustrative application, we show that interesting parameter constraints result from only the ages and elemental abundances of Sun, Arcturus and the present-day interstellar medium (ISM). For the first time, we use such information to infer IMF parameter via GCE modeling, where we properly marginalize over nuisance parameters and account for different yield sets. We find that of the IMF $11.6_{-1.6}^{+2.1}$ % explodes as core-collapse SN, compatible with Salpeter 1955. We also constrain the incidence of SN Ia per 10^3 Msun to 0.5-1.4. At the same time, this Chempy application shows persistent discrepancies between predicted and observed abundances for some elements, irrespective of the chosen yield set. These cannot be remedied by any variations of Chempy's parameters and could be an indication for missing nucleosynthetic channels. Chempy should be a powerful tool to confront predictions from stellar nucleosynthesis with far more complex abundance data sets.Comment: 19 pages, 17 figures, accepted for publication in A&A, python code: https://github.com/jan-rybizki/Chemp

New stellar encounters discovered in the second Gaia data release

Passing stars may play an important role in the evolution of our solar system. We search for close stellar encounters to the Sun among all 7.2 million stars in Gaia-DR2 that have six-dimensional phase space data. We characterize encounters by integrating their orbits through a Galactic potential and propagating the correlated uncertainties via a Monte Carlo resampling. After filtering to remove spurious data, we find 694 stars that have median (over uncertainties) closest encounter distances within 5 pc, all occurring within 15 Myr from now. 26 of these have at least a 50% chance of coming closer than 1 pc (and 7 within 0.5 pc), all but one of which are newly discovered here. We further confirm some and refute several other previously-identified encounters, confirming suspicions about their data. The closest encounter in the sample is Gl 710, which has a 95% probability of coming closer than 0.08 pc (17 000 AU). Taking mass estimates from Gaia astrometry and multiband photometry for essentially all encounters, we find that Gl 710 also has the largest impulse on the Oort cloud. Using a Galaxy model, we compute the completeness of the Gaia-DR2 encountering sample as a function of perihelion time and distance. Only 15% of encounters within 5 pc occurring within +/- 5 Myr of now have been identified, mostly due to the lack of radial velocities for faint and/or cool stars. Accounting for the incompleteness, we infer the present rate of encounters within 1 pc to be 19.7 +/- 2.2 per Myr, a quantity expected to scale quadratically with the encounter distance out to at least several pc. Spuriously large parallaxes in our sample from imperfect filtering would tend to inflate both the number of encounters found and this inferred rate. The magnitude of this effect is hard to quantify.Comment: 12 pages. Accepted to A&A. Added to this version: section 3.2 and Fig. 8 (CMD) with discussion of astrometric quality metrics; full versions of tables 2 and 3 as ancillary dat

TESS exoplanet candidates validated with HARPS archival data. A massive Neptune around GJ143 and two Neptunes around HD23472

We aim at the discovery of new planetary systems by exploiting the transit light curve results from TESS orbital observatory's Sector 1 and 2 observations and validating them with precise Doppler measurements obtained from archival HARPS data. Taking advantage of the reported TESS transit events around GJ143 (TOI 186) and HD23472 (TOI 174) we model their HARPS precise Doppler measurements and derive orbital parameters for these two systems. For the GJ143 system TESS has reported only a single transit, and thus its period is unconstrained from photometry. Our RV analysis of GJ143 reveal the full Keplerian solution of the system, which is consistent with an eccentric planet with a mass almost twice that of Neptune and a period of $P_{\rm b}$ = $35.59_{-0.01}^{+0.01}$ days. Our estimates of the GJ143 b planet are fully consistent with the transit timing from TESS. We confirm the two-planet system around HD23472, which according to our analysis is composed of two Neptune mass planets in a possible 5:3 MMR.Comment: Submitted to A&A on 10th December 2018, Accepted on 14 January 2019, Published online on 30 January 201

Inference from modelling the chemodynamical evolution of the Milky Way disc

In this thesis, the field star Initial Mass Function (IMF) and chemical evolution parameters for the Milky Way (MW) are derived using a forward modelling technique in combination with Bayesian statistics. Starting from a local MM disc model, observations of stellar samples in the Solar Neighbourhood are synthesised and compared to the corresponding volume-complete observational samples of Hipparcos stars. The resulting IMF, derived from observations in the range from 0.5 to 8Msun, is a two-slope broken power law with powers of -1.49 +- 0.08 and -3.02 +- 0.06 for the low-mass slope and the high-mass slope, respectively, with a break at 1.39 +- 0.05Msun. In order to constrain the IMF for stars more massive than 8Msun, a fast and flexible chemical enrichment code, Chempy, was developed, which is also able to reproduce spatial and stellar population selections of observational samples. The inferred high-mass slope for stellar masses above 6Msun is -2.28 +- 0.09, accounting for the systematic effects of different yield sets from the literature. This shows that constraints from chemical modelling, similarly to hydrodynamical simulations of the Galaxy, demand a Salpeter high-mass index. This is hard to recover from star count analysis given the rareness of high-mass stars

A Gaia DR2 Mock Stellar Catalog

We present a mock catalog of Milky Way stars, matching in volume and depth the content of the Gaia data release 2 (GDR2). We generated our catalog using Galaxia, a tool to sample stars from a Besancon Galactic model, together with a realistic 3D dust extinction map. The catalog mimicks the complete GDR2 data model and contains most of the entries in the Gaia source catalog: 5-parameter astrometry, 3-band photometry, radial velocities, stellar parameters, and associated scaled nominal uncertainty estimates. In addition, we supplemented the catalog with extinctions and photometry for non-Gaia bands. This catalog can be used to prepare GDR2 queries in a realistic runtime environment, and it can serve as a Galactic model against which to compare the actual GDR2 data in the space of observables. The catalog is hosted through the virtual observatory GAVO's Heidelberg data center service and thus can be queried using ADQL as for GDR2 data.Comment: 8 pages, 7 figures, 9 queries, accepted by PASP, catalog is available from http://dc.g-vo.org/tableinfo/gdr2mock.main and topcat queriabl