arXiv subjects

Tobias Buck

Publications and source records attributed to Tobias Buck.

At least 55 records · Page 3Linked to original sources

arXiv2024

There is No Place Like Home -- Finding Birth Radii of Stars in the Milky Way

Stars move away from their birthplaces over time via a process known as radial migration, which blurs chemo-kinematic relations used for reconstructing the Milky Way (MW) formation history. To understand the true time evolution of the MW, one needs to take into account the effects of this process. We show that stellar birth radii can be derived directly from the data with minimum prior assumptions on the Galactic enrichment history. This is done by first recovering the time evolution of the stellar birth metallicity gradient, $d\mathrm{[Fe/H]}(R, τ)/dR$, through its inverse relation to the metallicity range as a function of age today, allowing us to place any star with age and metallicity measurements back to its birthplace, $R_b$. Applying our method to a large, high-precision data set of MW disk subgiant stars, we find a steepening of the birth metallicity gradient from 11 to 8 Gyr ago, which coincides with the time of the last massive merger, Gaia-Sausage-Enceladus (GSE). This transition appears to play a major role in shaping both the age-metallicity relation and the bimodality in the [$α$/Fe]-[Fe/H] plane. By dissecting the disk into mono-$R_b$ populations, clumps in the low-[$α$/Fe] sequence appear, which are not seen in the total sample and coincide in time with known star-formation bursts, possibly associated with the Sagittarius Dwarf Galaxy. We estimated that the Sun was born at $4.5\pm 0.4$~kpc from the Galactic center. Our $R_b$ estimates provide the missing piece needed to recover the Milky Way formation history.

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arXiv2024

Finding accreted stars in the Milky Way: clues from NIHAO simulations

Exploring the marks left by galactic accretion in the Milky Way helps us understand how our Galaxy was formed. However, finding and studying accreted stars and the galaxies they came from has been challenging. This study uses a simulation from the NIHAO project, which now includes a wider range of chemical compositions, to find better ways to spot these accreted stars. By comparing our findings with data from the GALAH spectroscopic survey, we confirm that the observationally established diagnostics of [Al/Fe] vs. [Mg/Mn] also show a separation of in-situ and accreted stars in the simulation, but stars from different accretion events tend to overlap in this plane even without observational uncertainties. Looking at the relationship between stellar age and linear or logarithmic abundances, such as [Fe/H], we can clearly separate different groups of these stars if the uncertainties in their chemical makeup are less than 0.15 dex and less than 20% for their ages. This method shows promise for studying the history of the Milky Way and other galaxies. Our work highlights how important it is to have accurate measurements of stellar ages and chemical content. It also shows how simulations can help us understand the complex process of galaxies merging and suggest how these events might relate to the differences we see between our Galaxy's thin and thick disk stars. This study provides a way to compare theoretical models with real observations, opening new paths for research in both our own Galaxy and beyond.

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arXiv2024

The Hierarchical Structure of Galactic Haloes: Differentiating Clusters from Stochastic Clumping with AstroLink

We present AstroLink, an efficient and versatile clustering algorithm designed to hierarchically classify astrophysically-relevant structures from both synthetic and observational data sets. We build upon CluSTAR-ND, a hierarchical galaxy/(sub)halo finder, so that AstroLink now generates a two-dimensional representation of the implicit clustering structure as well as ensuring that clusters are statistically distinct from the noisy density fluctuations implicit within the $n$-dimensional input data. This redesign replaces the three cluster extraction parameters from CluSTAR-ND with a single parameter, $S$ -- the lower statistical significance threshold of clusters, which can be automatically and reliably estimated via a dynamical model-fitting process. We demonstrate the robustness of this approach compared to AstroLink's predecessors by applying each algorithm to a suite of simulated galaxies defined over various feature spaces. We find that AstroLink delivers a more powerful clustering performance while being $\sim27\%$ faster and using less memory than CluSTAR-ND. With these improvements, AstroLink is ideally suited to extracting a meaningful set of hierarchical and arbitrarily-shaped astrophysical clusters from both synthetic and observational data sets -- lending itself as a great tool for morphological decomposition within the context of hierarchical structure formation.

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arXiv2024

Quantitatively rating galaxy simulations against real observations with anomaly detection

Cosmological galaxy formation simulations are powerful tools to understand the complex processes that govern the formation and evolution of galaxies. However, evaluating the realism of these simulations remains a challenge. The two common approaches for evaluating galaxy simulations is either through scaling relations based on a few key physical galaxy properties, or through a set of pre-defined morphological parameters based on galaxy images. This paper proposes a novel image-based method for evaluating the quality of galaxy simulations using unsupervised deep learning anomaly detection techniques. By comparing full galaxy images, our approach can identify and quantify discrepancies between simulated and observed galaxies. As a demonstration, we apply this method to SDSS imaging and NIHAO simulations with different physics models, parameters, and resolution. We further compare the metric of our method to scaling relations as well as morphological parameters. We show that anomaly detection is able to capture similarities and differences between real and simulated objects that scaling relations and morphological parameters are unable to cover, thus indeed providing a new point of view to validate and calibrate cosmological simulations against observed data.

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arXiv2023

LMC Stars and Where to Find Them: Inferring Birth Radii for External Galaxies

It is well known that stars move away from their birth location over time via radial migration. This dynamical process makes computing the correct chemical evolution, e.g., metallicity gradients, of galaxies very difficult. This dynamical process makes inferring the chemical evolution of observed galaxies from their measured abundance gradients very difficult. One way to account for radial migration is to infer stellar birth radii for individual stars. Many attempts to do so have been performed over the last years, but are limited to the Milky Way as computing the birth position of stars requires precise measurements of stellar metallicity and age for individual stars that cover large Galactic radii. Fortunately, recent and future surveys will provide numerous opportunities for inferring birth radii for external galaxies such as the Large Magellanic Cloud (LMC). In this paper, we investigate the possibility of doing so using the NIHAO cosmological zoom-in simulations. We find that it is theoretically possible to infer birth radii with a ~ 25% median uncertainty for individual stars in galaxies with i) orderliness of the orbits, $\langle v_ϕ\rangle/σ_{v} >$ 2, ii) a dark matter halo mass greater or equal to approximately the LMC mass (~ 2 x 10$^{11} M_\odot$), and iii) after the average azimuthal velocity of the stellar disk reaches ~70% of its maximum. From our analysis, we conclude that it is possible and useful to infer birth radii for the LMC and other external galaxies that satisfy the above criteria.

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arXiv2023

Speeding up astrochemical reaction networks with autoencoders and neural ODEs

In astrophysics, solving complex chemical reaction networks is essential but computationally demanding due to the high dimensionality and stiffness of the ODE systems. Traditional approaches for reducing computational load are often specialized to specific chemical networks and require expert knowledge. This paper introduces a machine learning-based solution employing autoencoders for dimensionality reduction and a latent space neural ODE solver to accelerate astrochemical reaction network computations. Additionally, we propose a cost-effective latent space linear function solver as an alternative to neural ODEs. These methods are assessed on a dataset comprising 29 chemical species and 224 reactions. Our findings demonstrate that the neural ODE achieves a 55x speedup over the baseline model while maintaining significantly higher accuracy by up to two orders of magnitude reduction in relative error. Furthermore, the linear latent model enhances accuracy and achieves a speedup of up to 4000x compared to standard methods.

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arXiv2023

GAMMA: Galactic Attributes of Mass, Metallicity, and Age Dataset

We introduce the GAMMA (Galactic Attributes of Mass, Metallicity, and Age) dataset, a comprehensive collection of galaxy data tailored for Machine Learning applications. This dataset offers detailed 2D maps and 3D cubes of 11 727 galaxies, capturing essential attributes: stellar age, metallicity, and mass. Together with the dataset, we publish our code to extract any other stellar or gaseous property from the raw simulation suite to extend the dataset beyond these initial properties, ensuring versatility for various computational tasks. Ideal for feature extraction, clustering, and regression tasks, GAMMA offers a unique lens to explore galactic structures using computational methods and is a bridge between astrophysical simulations and the field of scientific machine learning (ML). As a first benchmark, we applied Principal Component Analysis (PCA) to this dataset. We find that PCA effectively captures the key morphological features of galaxies with a small number of components. We achieve a dimensionality reduction by a factor of approximately 200 (3650) for 2D images (3D cubes) with a reconstruction accuracy below 5%.

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arXiv2023

GalacticFlow: Learning a Generalized Representation of Galaxies with Normalizing Flows

State-of-the-art galaxy formation simulations generate data within weeks or months. Their results consist of a random sub-sample of possible galaxies with a fixed number of stars. We propose a ML based method, GalacticFlow, that generalizes such results. We use normalizing flows to learn the extended distribution function of galaxies conditioned on global galactic parameters. GalacticFlow then provides a continuized and condensed representation of the ensemble of galaxies in the data. Thus, essentially compressing large amounts of explicit simulation data into a small implicit generative model. Our model is able to evaluate any galaxy eDF given by a set of global parameters and allows generating arbitrarily many stars from it. We show that we can learn such a representation, embodying the entire mass range from dwarf to Milky Way mass, from only 90 galaxies in $\sim18$ hours on a single RTX 2080Ti and generate a new galaxy of one million stars within a few seconds.

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arXiv2023

The Prince and the Pauper: Evidence for the early high-redshift formation of the Galactic $α$-poor disc population

Context. The presence of [$α$/Fe]-[Fe/H] bi-modality in the Milky Way disc has animated the Galactic archaeology community since more than two decades. Aims. Our goal is to investigate the chemical, temporal, and kinematical structure of the Galactic discs using abundances, kinematics, and ages derived self-consistently with the new Bayesian framework SAPP. Methods. We employ the public Gaia-ESO spectra, as well as Gaia EDR3 astrometry and photometry. Stellar parameters and chemical abundances are determined for 13 426 stars using NLTE models of synthetic spectra. Ages are derived for a sub-sample of 2 898 stars, including subgiants and main-sequence stars. The sample probes a large range of Galactocentric radii, $\sim$ 3 to 12 kpc, and extends out of the disc plane to $\pm$ 2 kpc. Results. Our new data confirm the known bi-modality in the [Fe/H] - [$α$/Fe] space, which is often viewed as the manifestation of the chemical thin and thick discs. The over-densities significantly overlap in metallicity, age, and kinematics, and none of these is a sufficient criterion for distinguishing between the two disc populations. Different from previous studies, we find that the $α$-poor disc population has a very extended [Fe/H] distribution and contains $\sim$ 20$\%$ old stars with ages of up to $\sim$ 11 Gyr. Conclusions. Our results suggest that the Galactic thin disc was in place early, at look-back times corresponding to redshifts z $\sim$ 2 or more. At ages $\sim$ 9 to 11 Gyr, the two disc structures shared a period of co-evolution. Our data can be understood within the clumpy disc formation scenario that does not require a pre-existing thick disc to initiate a formation of the thin disc. We anticipate that a similar evolution can be realised in cosmological simulations of galaxy formation.

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arXiv2023

AGN radiation imprints on the circumgalactic medium of massive galaxies

Active Galactic Nuclei (AGN) in cosmological simulations generate explosive feedback that regulates star formation in massive galaxies, modifying the gas phase structure out to large distances. Here, we explore the direct effects that AGN radiation has on gas heating and cooling within one high-resolution $z=3$ dark matter halo as massive as a quasar host ($M_{\rm h}=$10$^{\rm 12.5}$M$_{\rm\odot}$), run without AGN feedback. We assume AGN radiation to impact the circumgalactic medium (CGM) anisotropically, within a bi-cone of angle $α$. We find that even a relatively weak AGN (black hole mass $M_{\rm\bullet}=10^{\rm 8}$M$_{\rm\odot}$ with an Eddington ratio $λ=0.1$) can significantly lower the fraction of halo gas that is catastrophically cooling compared to the case of gas photoionized only by the ultraviolet background (UVB). Varying $M_{\rm\bullet}$, $λ$ and $α$, we study their effects on observables. A 10$^{\rm 9}$M$_{\rm\odot}$ AGN with $λ=0.1$ and $α\approxeq60^{^{\rm o}}$ reproduces the average surface brightness (SB) profiles of Ly$α$, HeII and CIV, and results in a covering fraction of optically thick absorbers within observational estimates. The simulated SB$_{\rm CIV}$ profile is steeper than observed, indicating that not enough metals are pushed beyond the very inner CGM. For this combination of parameters, the CGM mass catastrophically cooling is reduced by half with respect to the UVB-only case, with roughly same mass out of hydrostatic equilibrium heating up and cooling down, hinting to the importance of self-regulation around AGNs. This study showcases how CGM observations can constrain not only the properties of the CGM itself, but also those of the AGN engine.

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arXiv2023

The individual abundance distributions of disc stars across birth radii in GALAH

Individual abundances in the Milky Way disc record stellar birth properties (e.g. age, birth radius ($R_{\rm birth}$)) and capture the diversity of the star-forming environments over time. Assuming an analytical relationship between ([Fe/H], [$α$/Fe]) and $R_{\rm birth}$, we examine the distributions of individual abundances [X/Fe] of elements C, O, Mg, Si, Ca ($α$), Al (odd-z), Mn (iron-peak), Y, and Ba (neutron-capture) for stars in the Milky Way. We want to understand how these elements might differentiate environments across the disc. We assign tracks of $R_{\rm birth}$ in the [$α$/Fe] vs. [Fe/H] plane as informed by expectations from simulations for $\sim 59,000$ GALAH stars in the solar neighborhood ($R\sim7-9$ kpc) which also have inferred ages. Our formalism for $R_{\rm birth}$ shows that older stars ($\sim$10 Gyrs) have a $R_{\rm birth}$ distribution with smaller mean values (i.e., $\bar{R}_{\mbox{birth}}$$\sim5\pm0.8$ kpc) compared to younger stars ($\sim6$ Gyrs; $\bar{R}_{\mbox{birth}}$$\sim10\pm1.5$ kpc), for a given [Fe/H], consistent with inside-out growth. The $α$-, odd-z, and iron-peak element abundances decrease as a function of $R_{\rm birth}$, whereas the neutron-capture abundances increase. The $R_{\rm birth}$-[Fe/H] gradient we measure is steeper compared to the present-day gradient (-0.067 dex/kpc vs -0.058 dex/kpc), which we also find true for $R_{\rm birth}$-[X/Fe] gradients. These results (i) showcase the feasibility of relating the birth radius of stars to their element abundances, (ii) the abundance gradients across $R_{\rm birth}$ are steeper than those over current radius, and (iii) offer an observational comparison to expectations on element abundance distributions from hydrodynamical simulations.

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arXiv2023

The impact of early massive mergers on the chemical evolution of Milky Way-like galaxies: insights from NIHAO-UHD simulations

Recent observations of the Milky Way (MW) found an unexpected steepening of the star-forming gas metallicity gradient around the time of the Gaia-Sausage-Enceladus (GSE) merger event. Here we investigate the influence of early ($t_{\mathrm{merger}}\lesssim5$ Gyr) massive ($M_{\mathrm{gas}}^{\mathrm{merger}}/M_{\mathrm{gas}}^{\mathrm{main}}(t_{\mathrm{merger}})\gtrsim10\%$) merger events such as the Gaia-Sausage Enceladus merger in the MW on the evolution of the cold gas metallicity gradient. We use the NIHAO-UHD suite of cosmological hydrodynamical simulations of MW-mass galaxies to study the frequency of massive early mergers and their detailed impact on the morphology and chemistry of the gaseous disks. We find a strong steepening of the metallicity gradient at early times for all four galaxies in our sample which is caused by a sudden increase in the cold gas disk size (up to a factor of 2) in combination with the supply of un-enriched gas ($\sim0.75$ dex lower compared to the main galaxy) by the merging dwarf galaxies. The mergers mostly affect the galaxy outskirts and lead to an increase in cold gas surface density of up to 200% outside of $\sim8$ kpc. The addition of un-enriched gas breaks the self-similar enrichment of the inter-stellar-medium and causes a dilution of the cold gas in the outskirts of the galaxies. The accreted stars and the ones formed later out of the accreted gas inhabit distinct tracks offset to lower [$α$/Fe] and [Fe/H] values compared to the main galaxy's stars. We find that such mergers can contribute significantly to the formation of a second, low-$α$ sequence as is observed in the MW.

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arXiv2023

Unveiling the time evolution of chemical abundances across the Milky Way disk with APOGEE

Chemical abundances are an essential tool in untangling the Milky Way's enrichment history. However, the evolution of the interstellar medium abundance gradient with cosmic time is lost as a result of radial mixing processes. For the first time, we quantify the evolution of many observational abundances across the Galactic disk as a function of lookback time and birth radius, $R_\text{birth}$. Using an empirical approach, we derive $R_\text{birth}$ estimates for 145,447 APOGEE DR17 red giant disk stars, based solely on their ages and [Fe/H]. We explore the detailed evolution of 6 abundances (Mg, Ca ($α$), Mn (iron-peak), Al, C (light), Ce (s-process)) across the Milky Way disk using 87,426 APOGEE DR17 red giant stars. We discover that the interstellar medium had three fluctuations in the metallicity gradient $\sim 9$, $\sim 6$, and $\sim4$ Gyr ago. The first coincides with the end of high-$α$ sequence formation around the time of the Gaia-Sausage-Enceladus disruption, while the others are likely related to passages of the Sagittarius dwarf galaxy. A clear distinction is found between present-day observed radial gradients with age and the evolution with lookback time for both [X/Fe] and [X/H], resulting from the significant flattening and inversion in old populations due to radial migration. We find the [Fe/H]--[$α$/Fe] bimodality is also seen as a separation in the $R_\text{birth}$--[X/Fe] plane for the light and $α$-elements. Our results recover the chemical enrichment of the Galactic disk over the past 12 Gyr, providing tight constraints on Galactic disk chemical evolution models.

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arXiv2022

Reliability and limitations of inferring birth radii in the Milky Way disk

Recovering the birth radii of observed stars in the Milky Way is one of the ultimate goals of Galactic Archaeology. One method to infer the birth radius and the evolution of the ISM metallicity assumes a linear relation between the ISM metallicity with radius at any given look-back time. Here we test the reliability of this assumption by using 4 zoom-in cosmological hydrodynamic simulations from the NIHAO-UHD project. We find that one can infer precise birth radii only when the stellar disk starts to form, which for our modeled galaxies happens ~ 10 Gyr ago, in agreement with recent estimates for the Milky Way. At later times the linear correlation between the ISM metallicity and radius increases, as stellar motions become more ordered and the azimuthal variations of the ISM metallicity start to drop. The formation of a central bar and perturbations from mergers can increase this uncertainty in the inner and outer disk, respectively.

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arXiv2022

NIHAO-LG: The uniqueness of Local Group dwarf galaxies

Recent observational and theoretical studies of the Local Group (LG) dwarf galaxies have highlighted their unique star-formation history, stellar metallicity, gas content, and kinematics. We investigate the commonality of these features by comparing constrained LG and field central dwarf halo simulations in the Numerical Investigation of a Hundred Astrophysical Objects (NIHAO) project. Our simulations, performed with NIHAO-like hydrodynamics which track the evolution of the Milky Way (MW) and M31 along with ~100 dwarfs in the LG, reveal the total gas mass and stellar properties (velocity dispersion, evolution history, etc.) of present-day LG dwarfs to be similar to field systems. However, relative to field galaxies, LG dwarfs have more cold gas in their central parts and more metal-rich gas in the halo stemming from interactions with other dwarfs living in a high-density environment like the LG. Interestingly, the direct impact of massive MW/M31 analogues on the metallicity evolution of LG dwarfs is minimal; LG dwarfs accrete high-metallicity gas mostly from other dwarfs at late times. We have also tested for the impact of metal diffusion on the chemical evolution of LG dwarfs, and found that it does not affect the stellar or gaseous content of LG dwarfs. Our simulations suggest that the stellar components of LG dwarfs offer a unique and unbiased local laboratory for galaxy-formation tests and comparisons, especially against the overall dwarf population in the Universe.

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arXiv2022

Escaping the maze: a statistical sub-grid model for cloud-scale density structures in the interstellar medium

The interstellar medium (ISM) is a turbulent, highly structured multi-phase medium. State-of-the-art cosmological simulations of the formation of galactic discs usually lack the resolution to accurately resolve those multi-phase structures. However, small-scale density structures play an important role in the life cycle of the ISM, and determine the fraction of cold, dense gas, the amount of star formation and the amount of radiation and momentum leakage from cloud-embedded sources. Here, we derive a $statistical\, model$ to calculate the unresolved small-scale ISM density structure from coarse-grained, volume-averaged quantities such as the $gas\, clumping\, factor$, $\mathcal{C}$, and mean density $\left<ρ\right>_V$. Assuming that the large-scale ISM density is statistically isotropic, we derive a relation between the three-dimensional clumping factor, $\mathcal{C}_ρ$, and the clumping factor of the $4π$ column density distribution on the cloud surface, $\mathcal{C}_Σ$, and find $\mathcal{C}_Σ=\mathcal{C}_ρ^{2/3}$. Applying our model to calculate the covering fraction, i.e., the $4π$ sky distribution of optically thick sight-lines around sources inside interstellar gas clouds, we demonstrate that small-scale density structures lead to significant differences at fixed physical ISM density. Our model predicts that gas clumping increases the covering fraction by up to 30 per cent at low ISM densities compared to a uniform medium. On the other hand, at larger ISM densities, gas clumping suppresses the covering fraction and leads to increased scatter such that covering fractions can span a range from 20 to 100 per cent at fixed ISM density. All data and example code is publicly available at GitHub.

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arXiv2022

Using Artificial Intelligence and real galaxy images to constrain parameters in galaxy formation simulations

Cosmological galaxy formation simulations are still limited by their spatial/mass resolution and cannot model from first principles some of the processes, like star formation, that are key in driving galaxy evolution. As a consequence they still rely on a set of 'effective parameters' that try to capture the scales and the physical processes that cannot be directly resolved in the simulation. In this study we show that it is possible to use Machine Learning techniques applied to real and simulated images of galaxies to discriminate between different values of these parameters by making use of the full information content of an astronomical image instead of collapsing it into a limited set of values like size, or stellar/ gas masses. In this work we apply our method to the NIHAO simulations and the THINGS and VLA-ANGST observations of HI maps in nearby galaxies to test the ability of different values of the star formation density threshold $n$ to reproduce observed HI maps. We show that observations indicate the need for a high value of $n \gtrsim 80$ ,cm$^{-3}$ (although the exact numerical value is model-dependent), which has important consequences for the dark matter distribution in galaxies. Our study shows that with innovative methods it is possible to take full advantage of the information content of galaxy images and compare simulations and observations in an interpretable, non-parametric and quantitative manner.

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arXiv2022

The GALAH Survey: Chemical tagging and chrono-chemodynamics of accreted halo stars with GALAH+ DR3 and $Gaia$ eDR3

Since the advent of $Gaia$ astrometry, it is possible to identify massive accreted systems within the Galaxy through their unique dynamical signatures. One such system, $Gaia$-Sausage-Enceladus (GSE), appears to be an early "building block" given its virial mass $> 10^{10}\,\mathrm{M_\odot}$ at infall ($z\sim1-3$). In order to separate the progenitor population from the background stars, we investigate its chemical properties with up to 30 element abundances from the GALAH+ Survey Data Release 3 (DR3). To inform our choice of elements for purely chemically selecting accreted stars, we analyse 4164 stars with low-$α$ abundances and halo kinematics. These are most different to the Milky Way stars for abundances of Mg, Si, Na, Al, Mn, Fe, Ni, and Cu. Based on the significance of abundance differences and detection rates, we apply Gaussian mixture models to various element abundance combinations. We find the most populated and least contaminated component, which we confirm to represent GSE, contains 1049 stars selected via [Na/Fe] vs. [Mg/Mn] in GALAH+ DR3. We provide tables of our selections and report the chrono-chemodynamical properties (age, chemistry, and dynamics). Through a previously reported clean dynamical selection of GSE stars, including $30 < \sqrt{J_R~/~\mathrm{kpc\,km\,s^{-1}}} < 55$, we can characterise an unprecedented 24 abundances of this structure with GALAH+ DR3. Our chemical selection allows us to prevent circular reasoning and characterise the dynamical properties of the GSE, for example mean $\sqrt{J_R~/~\mathrm{kpc\,km\,s^{-1}}} = 26_{-14}^{+9}$. We find only $(29\pm1)\%$ of the GSE stars within the clean dynamical selection region. Our methodology will improve future studies of accreted structures and their importance for the formation of the Milky Way.

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