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Jan Rybizki

Publications and source records attributed to Jan Rybizki.

At least 19 recordsLinked to original sources
arXiv2024

Astronomy's climate emissions: Global travel to scientific meetings in 2019

Travel to academic conferences -- where international flights are the norm -- is responsible for a sizeable fraction of the greenhouse gas (GHG) emissions associated with academic work. In order to provide a benchmark for comparison with other fields, as well as for future reduction strategies and assessments, we estimate the CO2-equivalent emissions for conference travel in the field of astronomy for the prepandemic year 2019. The GHG emission of the international astronomical community's 362 conferences and schools in 2019 amounted to 42,500 tCO2e, assuming a radiative-forcing index factor of 1.95 for air travel. This equates to an average of 1.0 $\pm$ 0.6 tCO2e per participant per meeting. The total travel distance adds up to roughly 1.5 Astronomical Units, that is, 1.5 times the distance between the Earth and the Sun. We present scenarios for the reduction of this value, for instance with virtual conferencing or hub models, while still prioritizing the benefits conferences bring to the scientific community.

physics.soc-ph↗
arXiv2022

A new third planet and the dynamical architecture of the HD33142 planetary system

Based on recently-taken and archival HARPS, FEROS and HIRES radial velocities (RVs), we present evidence for a new planet orbiting the first ascent red giant star HD33142 (with an improved mass estimate of 1.52$\pm$0.03 M$_\odot$), already known to host two planets. We confirm the Jovian mass planets HD33142 b and c with periods of $P_{\rm b}$ = 330.0$_{-0.4}^{+0.4}$ d and $P_{\rm c}$ = 810.2$_{-4.2}^{+3.8}$ d and minimum dynamical masses of $m_{\rm b}\sin{i}$ = 1.26$_{-0.05}^{+0.05}$ M$_{\rm Jup}$ and $m_{\rm c}\sin{i}$ = 0.89$_{-0.05}^{+0.06}$ M$_{\rm Jup}$. Furthermore, our periodogram analysis of the precise RVs shows strong evidence for a short-period Doppler signal in the residuals of a two-planet Keplerian fit, which we interpret as a third, Saturn-mass planet with $m_\mathrm{d}\sin{i}$ = 0.20$_{-0.03}^{+0.02}$ M$_{\rm Jup}$ on a close-in orbit with an orbital period of $P_{\rm d}$ =89.9$_{-0.1}^{+0.1}$ d. We study the dynamical behavior of the three-planet system configurations with an N-body integration scheme, finding it long-term stable with the planets alternating between low and moderate eccentricities episodes. We also performed N-body simulations, including stellar evolution and second-order dynamical effects such as planet-stellar tides and stellar mass-loss on the way to the white dwarf phase. We find that planets HD33142 b, c and d are likely to be engulfed near the tip of the red giant branch phase due to tidal migration. These results make the HD33142 system an essential benchmark for the planet population statistics of the multiple-planet systems found around evolved stars.

astro-ph.EP↗
arXiv2022

Neutron-capture elements record the ordered chemical evolution of the disc over time

An ensemble of chemical abundances probing different nucleosynthetic channels can be leveraged to build a comprehensive understanding of the chemical and structural evolution of the Galaxy. Using GALAH DR3 data, we seek to trace the enrichment by the supernovae Ia, supernovae II, asymptotic giant branch stars, and neutron-star mergers and/or collapsars nucleosynthetic sources by studying the [Fe/H], [$α$/Fe], [Ba/Fe], and [Eu/Fe] chemical compositions of $\sim$50,000 red giant stars, respectively. Employing small [Fe/H]-[$α$/Fe] cells, which serve as an effective reference-frame of supernovae contributions, we characterise the abundance-age profiles for [Ba/Fe] and [Eu/Fe]. Our results disclose that these age-abundance relations vary across the [Fe/H]-[$α$/Fe] plane. Within cells, we find negative age-[Ba/Fe] relations and flat age-[Eu/Fe] relations. Across cells, we see the slope of the age-[Ba/Fe] relations evolve smoothly and the [Eu/Fe] relations vary in amplitude. We subsequently model our empirical findings in a theoretical setting using the flexible Chempy Galactic chemical evolution (GCE) code, using the mean [Fe/H], [Mg/Fe], [Ba/Fe], and age values for stellar populations binned in [Fe/H], [Mg/Fe], and age space. We find that within a one-zone framework, an ensemble of GCE model parameters vary to explain the data. Using present day orbits from \textit{Gaia} EDR3 measurements we infer that the GCE model parameters, which set the observed chemical abundance distributions, vary systematically across mean orbital radii. Under our modelling assumptions, the observed chemical abundances are consistent with a small gradient in the high mass end of the initial mass function (IMF) across the disc, where the IMF is more top heavy towards the inner disc and more bottom heavy in the outer disc.

astro-ph.GA↗
arXiv2021

A classifier for spurious astrometric solutions in Gaia EDR3

The Gaia early Data Release 3 has delivered exquisite astrometric data for 1.47 billion sources, which is revolutionizing many fields in astronomy. For a small fraction of these sources, the astrometric solutions are poor, and the reported values and uncertainties may not apply. Before any analysis, it is important to recognize and excise these spurious results - this is commonly done by means of quality flags in the Gaia catalog. Here, we devise a means of separating 'good' from 'bad' astrometric solutions that is an order of magnitude cleaner than any single flag: 99.3% pure and 97.3% complete, as validated on our test data. We devise an extensive sample of manifestly bad astrometric solutions, with parallax that is negative at > 4.5 sigma; and a corresponding sample of presumably good solutions, including sources in HEALPix pixels on the sky that do not contain such negative parallaxes, and sources that fall on the main sequence in a color-absolute magnitude diagram. We then train a neural network that uses 17 pertinent Gaia catalog entries and information about nearby sources to discriminate between these two samples, captured in a single 'astrometric fidelity' parameter. A diverse set of verification tests shows that our approach works very cleanly, including for sources with positive parallaxes. The main limitations of our approach are in the very low-SNR and the crowded regime. Our astrometric fidelities for all of eDR3 can be queried via the Virtual Observatory, our code and data are public.

astro-ph.IM↗
arXiv2021

Data-Driven Stellar Models

We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way. The model uses a neural network to learn the (de-reddened) absolute magnitude in one band and colors across many bands, given stellar parameters from spectroscopic surveys and parallax constraints from Gaia. To demonstrate the effectiveness of this approach, we train our model on a dataset with spectroscopic parameters from LAMOST, APOGEE and GALAH, Gaia parallaxes, and optical and near-infrared photometry from Gaia, Pan-STARRS~1, 2MASS and WISE. Testing the model on these datasets leads to an excellent fit and a precise - and by construction accurate - prediction of the color-magnitude diagrams in many bands. This flexible approach rigorously links spectroscopic and photometric surveys, and also results in an improved, stellar-temperature-dependent reddening vector. As such, it provides a simple and accurate method for predicting photometry in stellar evolutionary models. Our model will form a basis to infer stellar properties, distances and dust extinction from photometric data, which should be of great use in 3D mapping of the Milky Way. Our trained model may be obtained at https://doi.org/10.5281/zenodo.3902382.

astro-ph.GA↗
arXiv2021

The challenge of simultaneously matching the observed diversity of chemical abundance patterns in cosmological hydrodynamical simulations

With the advent of large spectroscopic surveys the amount of high quality chemo-dynamical data in the Milky Way (MW) increased tremendously. Accurately and correctly capturing and explaining the detailed features in the high-quality observational data is notoriously difficult for state-of-the-art numerical models. In order to keep up with the quantity and quality of observational datasets, improved prescriptions for galactic chemical evolution need to be incorporated into the simulations. Here we present a new, flexible, time resolved chemical enrichment model for cosmological simulations. Our model allows to easily change a number of stellar physics parameters such as the shape of the initial mass function (IMF), stellar lifetimes, chemical yields or SN Ia delay times. We implement our model into the Gasoline2 code and perform a series of cosmological simulations varying a number of key parameters, foremost evaluating different stellar yield sets for massive stars from the literature. We find that total metallicity, total iron abundance and gas phase oxygen abundance are robust predictions from different yield sets and in agreement with observational relations. On the other hand, individual element abundances, especially $α$-elements show significant differences across different yield sets and none of our models can simultaneously match constraints on the dwarf and MW mass scale. This offers a unique way of observationally constraining model parameters. For MW mass galaxies we find for most yield tables tested in this work a bimodality in the $[α$/Fe] vs. [Fe/H] plane of rather low intrinsic scatter potentially in tension with the observed abundance scatter.

astro-ph.GA↗
arXiv2020

Characterising the Gaia Radial Velocity sample selection function in its native photometry

The Gaia DR2 radial velocity sample (GDR2RVS), which provides six-dimensional phase-space information on 7.2 million stars, is of great value for inferring properties of the Milky Way. Yet a quantitative and accurate modelling of this sample is hindered without knowledge and inclusion of a well-characterized selection function. Here we derive the selection function through estimates of the internal completeness, i.e. the ratio of GDR2RVS sources compared to all Gaia DR2 sources (GDR2all). We show that this selection function or "completeness" depends on basic observables, in particular the apparent magnitude GRVS and colour G-GRP, but also on the surrounding source density and on sky position, where the completeness exhibits distinct small-scale structure. We identify a region of magnitude and colour that has high completeness, providing an approximate but simple way of implementing the selection function. For a more rigorous and detailed description we provide python code to query our selection function, as well as tools and ADQL queries that produce custom selection functions with additional quality cuts.

astro-ph.IM↗
arXiv2020

From birth associations to field stars: mapping the small-scale orbit distribution in the Galactic disc

Stars born at the same time in the same place should have formed from gas of the same element composition. But most stars subsequently disperse from their birth siblings, in orbit and orbital phase, becoming 'field stars'. Here we explore and provide direct observational evidence for this process in the Milky Way disc, by quantifying the probability that orbit-similarity among stars implies indistinguishable metallicity. We define the orbit similarity among stars through their distance in action-angle space, $Δ(J,θ)$, and their abundance similarity simply by $Δ$[Fe/H]. Analyzing a sample of main sequence stars from Gaia DR2 and LAMOST, we find an excess of pairs with the same metallicity ($Δ\mathrm{[Fe/H]}<0.1$) that extends to remarkably large separations in $Δ(J,θ)$ that correspond to nearly 1 kpc distances. We assess the significance of this effect through a mock sample, drawn from a smooth and phase-mixed orbit distribution. Through grouping such star pairs into associations with a friend-of-friends algorithm linked by $Δ(J,θ)$, we find 100s of mono-abundance groups with $\ge 3$ (to $\gtrsim 20$) members; these groups -- some clusters, some spread across the sky -- are over an order-of-magnitude more abundant than expected for a smooth phase-space distribution, suggesting that we are witnessing the 'dissolution' of stellar birth associations into the field.

astro-ph.GA↗
arXiv2020

A Gaia early DR3 mock stellar catalog: Galactic prior and selection function

We present a mock stellar catalog, matching in volume, depth and data model the content of the planned Gaia early data release 3 (Gaia EDR3). We have generated our catalog (GeDR3mock) using galaxia, a tool to sample stars from an underlying Milky Way (MW) model or from N-body data. We used an updated Besançon Galactic model together with the latest PARSEC stellar evolutionary tracks, now also including white dwarfs. We added the Magellanic clouds and realistic open clusters with internal rotation. We empirically modelled uncertainties based on Gaia DR2 (GDR2) and scaled them according to the longer baseline in Gaia EDR3. The apparent magnitudes were reddened according to a new selection of 3D extinction maps. To help with the Gaia selection function we provide all-sky magnitude limit maps in G and BP for a few relevant GDR2 subsets together with the routines to produce these maps for user-defined subsets. We supplement the catalog with photometry and extinctions in non-Gaia bands. The catalog is available in the Virtual Observatory and can be queried just like the actual Gaia EDR3 will be. We highlight a few capabilities of the Astronomy Data Query Language (ADQL) with educative catalog queries. We use the data extracted from those queries to compare GeDR3mock to GDR2, which emphasises the importance of adding observational noise to the mock data. Since the underlying truth, e.g. stellar parameters, is know in GeDR3mock, it can be used to construct priors as well as mock data tests for parameter estimation. All code, models and data used to produce GeDR3mock are linked and contained in galaxia_wrap, a python package, representing a fast galactic forward model, able to project MW models and N-body data into realistic Gaia observables.

astro-ph.IM↗
arXiv2019

Inferring Galactic Parameters from Chemical Abundances: A Multi-Star Approach

Constraining parameters such as the initial mass function high-mass slope and the frequency of type Ia supernovae is of critical importance in the ongoing quest to understand galactic physics and create realistic hydrodynamical simulations. In this paper, we demonstrate a method to precisely determine these using individual chemical abundances from a large set of stars, coupled with some estimate of their ages. Inference is performed via the simple chemical evolution model Chempy in a Bayesian framework, marginalizing over each star's specific interstellar medium parameters, including an element-specific `model error' parameter to account for inadequacies in our model. Hamiltonian Monte Carlo (HMC) methods are used to sample the posterior function, made possible by replacing Chempy with a trained neural network at negligible error. The approach is tested using data from both Chempy and the IllustrisTNG simulation, showing sub-percent agreement between inferred and true parameters using data from up to 1600 individual stellar abundances. For IllustrisTNG, strongest constraints are obtained from metal ratios, competitive with those from other methods including star counts. Analysis using a different set of nucleosynthetic yields shows that incorrectly assumed yield models can give non-negligible bias in the derived parameters; this is reduced by our model errors, which further show how well the yield tables match data. We also find a significant bias from analyzing only a small set of stars, as is often done in current analyses. The method can be easily applied to observational data, giving tight bounds on key galactic parameters from chemical abundances alone.

astro-ph.GA↗
arXiv2019

Variations in $α$-element ratios trace the chemical evolution of the disk

It is well established that the chemical structure of the Milky Way exhibits a bimodality with respect to the $α$-enhancement of stars at a given [Fe/H]. This has been studied largely based on a bulk $α$ abundance, computed as a summary of several individual $α$-elements. Inspired by the expected subtle differences in their nucleosynthetic origins, here we probe the higher level of granularity encoded in the inter-family [Mg/Si] abundance ratio. Using a large sample of stars with APOGEE abundance measurements, we first demonstrate that there is additional information in this ratio beyond what is already apparent in [$α$/Fe] and [Fe/H] alone. We then consider Gaia astrometry and stellar age estimates to empirically characterize the relationships between [Mg/Si] and various stellar properties. We find small but significant trends between this ratio and $α$-enhancement, age, [Fe/H], location in the Galaxy, and orbital actions. To connect these observed [Mg/Si] variations to a physical origin, we attempt to predict the Mg and Si abundances of stars with the galactic chemical evolution model Chempy. We find that we are unable to reproduce abundances for the stars that we fit, which highlights tensions between the yield tables, the chemical evolution model, and the data. We conclude that a more data-driven approach to nucleosynthetic yield tables and chemical evolution modeling is necessary to maximize insights from large spectroscopic surveys.

astro-ph.GA↗
arXiv2019

Voyage 2050 White Paper: All-Sky Visible and Near Infrared Space Astrometry

A new all-sky visible and Near-InfraRed (NIR) space astrometry mission with a wavelength cutoff in the K-band is not just focused on a single or small number of key science cases. Instead, it is extremely broad, answering key science questions in nearly every branch of astronomy while also providing a dense and accurate visible-NIR reference frame needed for future astronomy facilities. For almost 2 billion common stars the combination of Gaia and a new all-sky NIR astrometry mission would provide much improved proper motions, answering key science questions -- from the solar system and stellar systems, including exoplanet systems, to compact galaxies, quasars, neutron stars, binaries and dark matter substructures. The addition of NIR will result in up to 8 billion newly measured stars in some of the most obscured parts of our Galaxy, and crucially reveal the very heart of the Galactic bulge region. In this white paper we argue that rather than improving on the accuracy, a greater overall science return can be achieved by going deeper than Gaia and by expanding the wavelength range to the NIR.

astro-ph.IM↗
arXiv2019

Stellar Astrophysics and Exoplanet Science with the Maunakea Spectroscopic Explorer (MSE)

The Maunakea Spectroscopic Explorer (MSE) is a planned 11.25-m aperture facility with a 1.5 square degree field of view that will be fully dedicated to multi-object spectroscopy. A rebirth of the 3.6m Canada-France-Hawaii Telescope on Maunakea, MSE will use 4332 fibers operating at three different resolving powers (R ~ 2500, 6000, 40000) across a wavelength range of 0.36-1.8mum, with dynamical fiber positioning that allows fibers to match the exposure times of individual objects. MSE will enable spectroscopic surveys with unprecedented scale and sensitivity by collecting millions of spectra per year down to limiting magnitudes of g ~ 20-24 mag, with a nominal velocity precision of ~100 m/s in high-resolution mode. This white paper describes science cases for stellar astrophysics and exoplanet science using MSE, including the discovery and atmospheric characterization of exoplanets and substellar objects, stellar physics with star clusters, asteroseismology of solar-like oscillators and opacity-driven pulsators, studies of stellar rotation, activity, and multiplicity, as well as the chemical characterization of AGB and extremely metal-poor stars.

astro-ph.SR↗
arXiv2019

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.

astro-ph.EP↗
arXiv2018

On the Optimal Choice of Nucleosynthetic Yields, IMF and Number of SNe Ia for Chemical Evolution Modelling

To fully harvest the rich library of stellar elemental abundance data available, we require reliable models that facilitate our interpretation of them. Galactic chemical evolution (GCE) models are one such set, and a key part of which are the selection of chemical yields from different nucleosynthetic enrichment channels, predominantly asymptotic giant branch (AGB) stars, Type Ia supernovae (SNe Ia), and core-collapse supernovae (CC-SNe). Here, we present a scoring system for yield tables based on their ability to reproduce proto-solar abundances within a simple parametrisation of the GCE modelling software Chempy, which marginalises over galactic parameters describing simple stellar populations (SSPs) and interstellar medium physics. Two statistical scoring methods are presented, based on Bayesian evidence and leave-one-out cross-validation and are applied to five CC-SN tables, (a) for all mutually available elements and (b) for a subset of the 9 most abundant elements. We find that the yields of Prantzos et al. (P18, including stellar rotation) and Chieffi & Limongi (C04) best reproduce proto-solar abundances for the two cases, respectively. The inferred best-fit SSP parameters for (b) are $α_\mathrm{IMF}=-2.45^{+0.15}_{-0.11}$ for the initial mass function high-mass slope and $\mathrm{N}_\mathrm{Ia}=1.29^{+0.45}_{-0.31}\times10^{-3}$ M$_\odot^{-1}$ for the SN Ia normalisation, which are broadly consistent across tested yield tables. Additionally, we demonstrate how Chempy can be used to dramatically improve elemental abundance predictions of hydrodynamical simulations by plugging tailored best-fit SSP parameters into a Milky Way analogue from Gutcke & Springel. Our code, including a comprehensive tutorial, is freely available and can additionally provide SSP enrichment tables for any combination of parameters and yield tables.

astro-ph.GA↗
arXiv2018

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.

astro-ph.GA↗
arXiv2018

Age-resolved chemistry of red giants in the solar neighbourhood

In the age of high-resolution spectroscopic stellar surveys of the Milky Way, the number of stars with detailed abundances of multiple elements is rapidly increasing. These elemental abundances are directly influenced by the evolutionary history of the Galaxy, but this can be difficult to interpret without an absolute timeline of the abundance enrichment. We present age-abundance trends for [M/H], [α/M], and 17 individual elements using a sample of 721 solar neighbourhood Hipparcos red giant stars observed by APOGEE. These age trends are determined through a Bayesian hierarchical modelling method presented by Feuillet et al. (2016). We confirm that the [α/M]- age relation in the solar neighbourhood is steep and relatively narrow (0.20 dex age dispersion), as are the [O/M]- and [Mg/M]-age relations. The age trend of [C/N] is steep and smooth, consistent with stellar evolution. The [M/H]-age relation has a mean age dispersion of 0.28 dex and a complex overall structure. The oldest stars in our sample are those with the lowest and highest metallicities, while the youngest stars are those with solar metallicity. These results provide strong constraints on theoretical models of Galactic chemical evolution (GCE). We compare them to the predictions of one-zone GCE mod- els and multi-zone mixtures, both analytic and numerical. These comparisons support the hypothesis that the solar neighbourhood is composed of stars born at a range of Galactocentric radii, and that the most metal-rich stars likely migrated from a region with earlier and more rapid star formation such as the inner Galaxy.

astro-ph.GA↗