arXiv subjects

Tobias Buck

Publications and source records attributed to Tobias Buck.

At least 37 records · Page 2Linked to original sources

arXiv2025

Disentangling Metallicity Effects in Hot Jupiter Occurrence Across Galactic Birth Radius and Phase-Space Density

We explore how the correlation between host star metallicity and giant planets shapes hot Jupiter occurrence as a function of Galactic birth radius (\rbirth) and phase-space density in the Milky Way disk. Using the GALAH and APOGEE surveys and a galaxy from the NIHAO simulation suite, we inject hot Jupiters around stars based on metallicity power laws, reflecting the trend that giant planets preferentially form around metal-rich stars. For \rbirth\ $\geq 5$ kpc, hot Jupiter occurrence decreases with \rbirth\ by $\sim -0.1%$ per kpc; this is driven by the Galaxy's chemical evolution, where the inner regions of the disk are more metal-rich. Differences in GALAH occurrence rates versus APOGEE's and the simulation's at \rbirth\ $< 5$ kpc arise from survey selection effects. APOGEE and the NIHAO simulation have more high-$α$ sequence stars than GALAH, resulting in average differences in metallicity (0.2--0.4 dex), $α$-process element enrichment (0.2 dex), and vertical velocities (7--14 km/s) at each \rbirth\ bin. Additionally, we replicate the result of \cite{Winter20}, which showed that over 92% of hot Jupiters are associated with stars in phase-space overdensities, or "clustered environments." However, our findings suggest that this clustering effect is primarily driven by chemical and kinematic differences between low and high-$α$ sequence star properties. Our results support stellar characteristics, particularly metallicity, being the primary drivers of hot Jupiter formation, which serves as the "null hypothesis" for interpreting planet demographics. This underscores the need to disentangle planetary and stellar properties from Galactic-scale effects in future planet demographics studies.

astro-ph.EP↗

arXiv2025

Local variations of the radial metallicity gradient in a simulated NIHAO-UHD Milky Way analogue and their implications for (extra-)galactic studies

Radial metallicity gradients are fundamental to understanding galaxy formation and evolution. In our high-resolution simulation of a NIHAO-UHD Milky Way analogue, we analyze the linearity, scatter, spatial coherence, and age-related variations of metallicity gradients using young stars and gas. While a global linear model generally captures the gradient, it ever so slightly overestimates metallicity in the inner galaxy and underestimates it in the outer regions of our simulated galaxy. Both a quadratic model, showing an initially steeper gradient that smoothly flattens outward, and a piecewise linear model with a break radius around 9.3-11.5~kpc (2.4-3.0 effective radii) fit the data equally better. The spread of [Fe/H] of young stars in the simulation increases by tenfold from the innermost to the outer galaxy at a radius of 20~kpc. We find that stars born at similar times along radial spirals drive this spread in the outer galaxy, with a chemical under- and over-enhancement of up to 0.1 dex at leading and trailing regions of such spirals, respectively. This localised chemical variance highlights the need to examine radial and azimuthal selection effects for both Galactic and extragalactic observational studies. The arguably idealised but volume-complete simulations suggest that future studies should not only test linear and piecewise linear gradients, but also non-linear functions such as quadratic ones to test for a smooth gradient rather than one with a break radius. Either finding would help to determine the importance of different enrichment or mixing pathways and thus our understanding of galaxy formation and evolution scenarios.

astro-ph.GA↗

arXiv2025

Potential Impact of the Sagittarius Dwarf Galaxy on the Formation of Young O-rich Stars

The Milky Way underwent significant transformations in its early history, characterised by violent mergers and satellite galaxy accretion. However, recent observations reveal notable star formation events over the past 4 Gyr, likely triggered by perturbations from the Sagittarius dwarf galaxy. Here, we present chemical signatures of this accretion event, using the [Fe/H] (metallicity) and [O/Fe] (oxygen abundance) ratios of thin-disc stars. In the normalised age-metallicity plane, we identify a discontinuous V-shape structure at z$_{\rm max}$ (maximum vertical distance from the disc plane) $<$ 0.4 kpc in the local disc, interrupted by a star formation burst between 4 and 2 Gyr ago. This event is characterised by a significant increase in oxygen abundance, resulting in a distinct [O/Fe] gradient and the formation of young O-rich stars. These stars have larger birth radii, indicating formation in the outer disc followed by radial migration to the Solar neighbourhood. Simulations of late satellite infall suggest that the passage of the Sagittarius dwarf galaxy may have contributed to the observed increase in oxygen abundance in the local disc.

astro-ph.GA↗

arXiv2025

Inferring Galactic Parameters from Chemical Abundances with Simulation-Based Inference

Galactic chemical abundances provide crucial insights into fundamental galactic parameters, such as the high-mass slope of the initial mass function (IMF) and the normalization of Type Ia supernova (SN Ia) rates. Constraining these parameters is essential for advancing our understanding of stellar feedback, metal enrichment, and galaxy formation processes. However, traditional Bayesian inference techniques, such as Hamiltonian Monte Carlo (HMC), are computationally prohibitive when applied to large datasets of modern stellar surveys. We leverage simulation-based-inference (SBI) as a scalable, robust, and efficient method for constraining galactic parameters from stellar chemical abundances and demonstrate its the advantages over HMC in terms of speed, scalability, and robustness against model misspecifications. We combine a Galactic Chemical Evolution (GCE) model, CHEMPY, with a neural network emulator and a Neural Posterior Estimator (NPE) to train our SBI pipeline. Mock datasets are generated using CHEMPY, including scenarios with mismatched nucleosynthetic yields, with additional tests conducted on data from a simulated Milky Way-like galaxy. SBI results are benchmarked against HMC-based inference, focusing on computational performance, accuracy, and resilience to systematic discrepancies. SBI achieves a $\sim75,600\times$ speed-up compared to HMC, reducing inference runtime from $\gtrsim42$ hours to mere seconds for thousands of stars. Inference on $1,000$ stars yields precise estimates for the IMF slope ($α_{\rm IMF} = -2.298 \pm 0.002$) and SN Ia normalization ($\log_{10}(N_{\rm Ia}) = -2.885 \pm 0.003$), deviating less than 0.05% from the ground truth. SBI also demonstrates similar robustness to model misspecification than HMC, recovering accurate parameters even with alternate yield tables or data from a cosmological simulation. (shortened...)

astro-ph.GA↗

arXiv2025

Bar-spiral interaction produces radial migration and star formation bursts

Central bars and spirals are known to strongly impact the evolution of their host galaxies, both in terms of dynamics and star formation. Their typically different pattern speeds cause them to regularly overlap, which induces fluctuations in bar parameters. In this paper, we analyze both numerical simulations of disk galaxies and observational data to study the effect of bar-spiral physical overlap on stellar radial migration and star formation in the bar vicinity, as a function of time and galactic azimuth. We study three different numerical models, two of which are in a cosmological context, as well as APOGEE DR17 data and the WISE catalog of Galactic HII regions. We find that periodic boosts in stellar radial migration occur when the bar and spiral structure overlap. This mechanism causes net inward migration along the bar leading side, while stars along the bar trailling side and minor axis are shifted outward. The signature of bar-spiral induced migration is seen between the bar's inner Lindbald resonance and well outside its corotation, beyond which other drivers take over. We also find that, in agreement with simulations, APOGEE DR17 stars born at the bar vicinity (mostly metal-rich) can migrate out to the solar radius while remaining on cold orbits. For the Milky Way, 13% of stars in the solar vicinity were born inside the bar, compared to 5-20% in the simulations. Bar-spiral reconnections also result in periodic starbursts at the bar ends with an enhancement of up to a factor of 4, depending on the strength of the spiral structure. Similarly to the migration bursts, these do not always happen simultaneously at the two sides of the bar, hinting at the importance of odd spiral modes. Data from the WISE catalog suggest this phhenomenon is also relevant in our own Galaxy.

astro-ph.GA↗

arXiv2024

NIHAO-RiNG: A Comparison of Simulated Disc Galaxies from GASOLINE and GIZMO

We utilize the public GIZMO code to simulate twelve disc galaxies from the NIHAO suite simulated with the GASOLINE code, then compare the corresponding galaxies in the two simulations. We find that while both codes with the same initial conditions and large-scale environments can successfully produce similar disc galaxies, significant differences are still seen in many properties of the galaxies, particularly in the circumgalactic medium (CGM) environment they reside. Specifically, the thermal feedback recipe used in GASOLINE results in ubiquitous long-lasting collimated outflows, primarily driven by high-density hot interstellar medium (ISM) from the galaxy center, and inflows of gas not aligned with the outflow cools rapidly and flows towards the galactic center. In contrast, galaxies from GIZMO code do not exhibit large-scale outflows at low redshifts, but instead display quasi-virialized hot gaseous halos that arise from the strong interaction between inflow of gas and feedback driven outflow. Therefore, the origins of mass and angular momentum of the cold disc in the two simulations are quite different, even though the final morphologies of corresponding galaxies are similar at $z\sim0$. The differences in the distribution of CGM gas are mainly due to different feedback models implemented in the two codes, thus future observations of CGM provide valuable insight into the physics governing the baryon cycle in disc galaxies.

astro-ph.GA↗

arXiv2024

Fast GPU-Powered and Auto-Differentiable Forward Modeling of IFU Data Cubes

We present RUBIX, a fully tested, well-documented, and modular Open Source tool developed in JAX, designed to forward model IFU cubes of galaxies from cosmological hydrodynamical simulations. The code automatically parallelizes computations across multiple GPUs, demonstrating performance improvements over state-of-the-art codes by a factor of 600. This optimization reduces compute times from hours to only seconds. RUBIX leverages JAX's auto-differentiation capabilities to enable not only forward modeling but also gradient computations through the entire pipeline paving the way for new methodological approaches such as e.g. gradient-based optimization of astrophysics model parameters. RUBIX is open-source and available on GitHub: https://github.com/ufuk-cakir/rubix.

astro-ph.IM↗

arXiv2024

CASBI -- Chemical Abundance Simulation-Based Inference for Galactic Archeology

Galaxies evolve hierarchically through merging with lower-mass systems and the remnants of destroyed galaxies are a key indicator of the past assembly history of our Galaxy. However, accurately measuring the properties of the accreted galaxies and hence unraveling the Milky Way's (MW) formation history is a challenging task. Here we introduce CASBI (Chemical Abundance Simulation Based Inference), a novel inference pipeline for Galactic Archeology based on Simulation-based Inference methods. CASBI leverages on the fact that there is a well defined mass-metallicity relation for galaxies and performs inference of key galaxy properties based on multi-dimensional chemical abundances of stars in the stellar halo. Hence, we recast the problem of unraveling the merger history of the MW into a SBI problem to recover the properties of the building blocks (e.g. total stellar mass and infall time) using the multi-dimensional chemical abundances of stars in the stellar halo as observable. With CASBI we are able to recover the full posterior probability of properties of building blocks of Milky Way like galaxies. We highlight CASBI's potential by inferring posteriors for the stellar masses of completely phase mixed dwarf galaxies solely from the 2d-distributions of stellar abundance in the iron vs. oxygen plane and find accurate and precise inference results.

astro-ph.GA↗

arXiv2024

CODES: Benchmarking Coupled ODE Surrogates

We introduce CODES, a benchmark for comprehensive evaluation of surrogate architectures for coupled ODE systems. Besides standard metrics like mean squared error (MSE) and inference time, CODES provides insights into surrogate behaviour across multiple dimensions like interpolation, extrapolation, sparse data, uncertainty quantification and gradient correlation. The benchmark emphasizes usability through features such as integrated parallel training, a web-based configuration generator, and pre-implemented baseline models and datasets. Extensive documentation ensures sustainability and provides the foundation for collaborative improvement. By offering a fair and multi-faceted comparison, CODES helps researchers select the most suitable surrogate for their specific dataset and application while deepening our understanding of surrogate learning behaviour.

cs.LG↗

arXiv2024

Differentiable Conservative Radially Symmetric Fluid Simulations and Stellar Winds -- jf1uids

We present jf1uids, a one-dimensional fluid solver that can, by virtue of a geometric formulation of the Euler equations, model radially symmetric fluid problems in a conservative manner, i.e., without losing mass or energy. For spherical problems, such as ideal supernova explosions or stellar wind-blown bubble expansions, simulating only along a radial dimension drastically reduces compute and memory demands compared to a full three-dimensional method. This simplification also alleviates constraints on backpropagation through the solver. Written in JAX, jf1uids is a GPU-compatible and fully differentiable simulator. We demonstrate the advantages of this differentiable physics simulator by retrieving the wind's parameters for an adiabatic stellar wind expansion from the final fluid state using gradient descent. As part of a larger "stellar winds, cosmic rays and machine learning" research track, jf1uids serves as a solid foundation to be extended with additional physics modules, foremost cosmic rays and a neural-net powered gas-cooling surrogate and improved by higher order and more accurate numerical schemes. All code is available under https://github.com/leo1200/jf1uids/.

physics.flu-dyn↗

arXiv2024

Deep Multimodal Representation Learning for Stellar Spectra

Recently, contrastive learning (CL), a technique most prominently used in natural language and computer vision, has been used to train informative representation spaces for galaxy spectra and images in a self-supervised manner. Following this idea, we implement CL for stars in the Milky Way, for which recent astronomical surveys have produced a huge amount of heterogeneous data. Specifically, we investigate Gaia XP coefficients and RVS spectra. Thus, the methods presented in this work lay the foundation for aggregating the knowledge implicitly contained in the multimodal data to enable downstream tasks like cross-modal generation or fused stellar parameter estimation. We find that CL results in a highly structured representation space that exhibits explicit physical meaning. Using this representation space to perform cross-modal generation and stellar label regression results in excellent performance with high-quality generated samples as well as accurate and precise label predictions.

astro-ph.SR↗

arXiv2024

Learning Locally Adaptive Metrics that Enhance Structural Representation with $\texttt{LAMINAR}$

We present $\texttt{LAMINAR}$, a novel unsupervised machine learning pipeline designed to enhance the representation of structure within data via producing a more-informative distance metric. Analysis methods in the physical sciences often rely on standard metrics to define geometric relationships in data, which may fail to capture the underlying structure of complex data sets. $\texttt{LAMINAR}$ addresses this by using a continuous-normalising-flow and inverse-transform-sampling to define a Riemannian manifold in the data space without the need for the user to specify a metric over the data a-priori. The result is a locally-adaptive-metric that produces structurally-informative density-based distances. We demonstrate the utility of $\texttt{LAMINAR}$ by comparing its output to the Euclidean metric for structured data sets.

cs.LG↗

arXiv2024

Galaxy Formation and Evolution via Phase-temporal Clustering with FuzzyCat $\circ$ AstroLink

We demonstrate how the composition of two unsupervised clustering algorithms, $\texttt{AstroLink}$ and $\texttt{FuzzyCat}$, makes for a powerful tool when studying galaxy formation and evolution. $\texttt{AstroLink}$ is a general-purpose astrophysical clustering algorithm built for extracting meaningful hierarchical structure from point-cloud data defined over any feature space, while $\texttt{FuzzyCat}$ is a generalised soft-clustering algorithm that propagates the dynamical effects of underlying data processes into a fuzzy hierarchy of stable fuzzy clusters. Their composition, $\texttt{FuzzyCat}$ $\circ$ $\texttt{AstroLink}$, can therefore identify a fuzzy hierarchy of astrophysically- and statistically-significant fuzzy clusters within any point-based data set whose representation is subject to changes caused by some underlying process. Furthermore, the pipeline achieves this without relying upon strong assumptions about the data, the change process, the number/importance of specific structure types, or much user input -- thereby making itself applicable to a wide range of fields in the physical sciences. We find that for the task of structurally decomposing simulated galaxies into their constituents, our context-agnostic approach has a substantial impact on the diversity and completeness of the structures extracted as well as on their relationship within the broader galactic structural hierarchy -- revealing dwarf galaxies, infalling groups, stellar streams (and their progenitors), stellar shells, galactic bulges, and star-forming regions.

astro-ph.GA↗

arXiv2024

Extragalactic Stellar Tidal Streams: Observations meet Simulation

According to the well established hierarchical framework for galaxy evolution, galaxies grow through mergers with other galaxies and the LambdaCDM cosmological model predicts that the stellar halos of massive galaxies are rich in remnants from minor mergers. The Stellar Streams Legacy Survey (SSLS) has provided a first release of a catalogue with a statistically significant sample of stellar streams in the Local Universe, detected in deep images from DESI Legacy Surveys and the Dark Energy Survey (DES). The main objective is to compare the results of the observations of stellar tidal streams with predictions from state-of-the-art cosmological simulations regarding their abundance, up to a redshift z < 0.02, according to the LambdaCDM model. We use the predictions of the cosmological simulations Copernicus Complexio, TNG50 of the IllustrisTNG project, and Auriga to generate mock-images of nearby halos and search for stellar streams. We compare the stream frequency, characteristics and photometry in these images with DES observations. We find generally good agreement between the real images and the simulated ones regarding frequency, characteristics and photometry of the streams, while the stream morphology is somewhat different between observations and simulations, and between simulations themselves. By varying the sky background of the synthetic images to emulate different surface brightness limit levels, we also obtain predictions for the detection rate of stellar tidal streams up to a surface brightness limit of 35 mag arcsec^-2. The cosmological simulations predict that with an instrument such as the one used in the DES, it would be necessary to reach a surface brightness limit of 32 mag arcsec^-2 in the r-band to achieve a frequency of up to around 70% in the detection of stellar tidal streams around galaxies in the redshift range considered here.

astro-ph.GA↗

arXiv2024

Evolution of the radial ISM metallicity gradient in the Milky Way disk since redshift $\approx 3$

Recent works identified a way to recover the time evolution of a galaxy's disk metallicity gradient from the shape of its age--metallicity relation. However, the success of the method is dependent on how the width of the star-forming region evolves over time, which in turn is dependent on a galaxy's present-day bar strength. In this paper, we account for the time variation in the width of the star-forming region when deriving the interstellar medium (ISM) metallicity gradient evolution over time ($\rm \nabla [Fe/H](τ)$), which provides more realistic birth radii estimates of Milky Way (MW) disk stars. Using MW/Andromeda analogues from the TNG50 simulation, we quantified the disk growth of newly born stars as a function of present-day bar strength to provide a correction that improves recovery of $\rm \nabla [Fe/H](τ)$. In TNG50, we find that our correction reduces the median absolute error in recovering $\rm \nabla [Fe/H] (τ)$ by over 30%. To confirm its universality, we test our correction on two galaxies from NIHAO-UHD and find the median absolute error is over 3 times smaller even in the presence of observational uncertainties for the barred, MW-like galaxy. Applying our correction to APOGEE DR17 red giant MW disk stars suggests the effects of merger events on $\rm \nabla [Fe/H](τ)$ are less significant than originally found, and the corresponding estimated birth radii expose epochs when different migration mechanisms dominated. Our correction to account for the growth of the star-forming region in the disk allows for better recovery of the evolution of the MW disk's ISM metallicity gradient and, thus, more meaningful stellar birth radii estimates. With our results, we are able to suggest the evolution of not only the ISM gradient, but also the total stellar disk radial metallicity gradient, providing key constraints to select MW analogues across redshift.

astro-ph.GA↗

arXiv2024

HELLO project: High-$z$ Evolution of Large and Luminous Objects

We present the High-$z$ Evolution of Large and Luminous Objects (HELLO) project, a set of $\sim\!30$ high-resolution cosmological simulations aimed to study Milky Way analogues ($M_\star\sim10^{10-11}$\,\Msun) at high redshift ($z\sim [2-4]$). Based on the Numerical Investigation of a Hundred Astrophysical Objects (NIHAO), HELLO features an updated scheme for chemical enrichment and the addition of local photoionization feedback. Independently of redshift and mass, our galaxies exhibit a smooth progression along the star formation main sequence until $M_\star \sim\!10^{10.5}$, around which our sample at $z \sim 4$ remains mostly unperturbed while the most massive galaxies at $z \sim 2$ reach their peak star formation rate (SFR) and its subsequent decline, due to a mix of gas consumption and stellar feedback. While AGN feedback remains subdominant with respect to stellar feedback for energy deposition, its localised nature likely adds to the physical processes leading to declining SFRs. The phase in which a galaxy in our mass range can be found at a given redshift is set by its gas reservoir and assembly history. Finally, our galaxies are in excellent agreement with various scaling relations observed with the \textit{Hubble Space Telescope} and the \textit{James Webb Space Telescope}, and hence can be used to provide the theoretical framework to interpret current and future observations from these facilities and shed light on the transition from star-forming to quiescent galaxies.

astro-ph.GA↗

arXiv2024

MEGS: Morphological Evaluation of Galactic Structure

Understanding the morphology of galaxies is a critical aspect of astrophysics research, providing insight into the formation, evolution, and physical properties of these vast cosmic structures. Various observational and computational methods have been developed to quantify galaxy morphology, and with the advent of large galaxy simulations, the need for automated and effective classification methods has become increasingly important. This paper investigates the use of Principal Component Analysis (PCA) as an interpretable dimensionality reduction algorithm for galaxy morphology using the IllustrisTNG cosmological simulation dataset with the aim of developing a generative model for galaxies. We first generate a dataset of 2D images and 3D cubes of galaxies from the IllustrisTNG simulation, focusing on the mass, metallicity, and stellar age distribution of each galaxy. PCA is then applied to this data, transforming it into a lower-dimensional image space, where closeness of data points corresponds to morphological similarity. We find that PCA can effectively capture the key morphological features of galaxies, with a significant proportion of the variance in the data being explained by a small number of components. With our method we achieve a dimensionality reduction by a factor of $\sim200$ for 2D images and $\sim3650$ for 3D cubes at a reconstruction accuracy below five percent. Our results illustrate the potential of PCA in compressing large cosmological simulations into an interpretable generative model for galaxies that can easily be used in various downstream tasks such as galaxy classification and analysis.

astro-ph.GA↗

arXiv2024

Birth of the Galactic Disk Revealed by the H3 Survey

We use chemistry ([alpha/Fe] and [Fe/H]), main sequence turnoff ages, and kinematics determined from H3 Survey spectroscopy and Gaia astrometry to identify the birth of the Galactic disk. We separate in-situ and accreted stars on the basis of angular momenta and eccentricities. The sequence of high-alpha in-situ stars persists down to at least [Fe/H]=-2.5 and shows unexpected non-monotonic behavior: with increasing metallicity the population first declines in [alpha/Fe], then increases over the range -1.3<[Fe/H]<-0.7, and then declines again at higher metallicities. The number of stars in the in-situ population rapidly increases above [Fe/H]=-1. The average kinematics of these stars are hot and independent of metallicity at [Fe/H]<-1 and then become increasingly cold and disk-like at higher metallicities. The ages of the in-situ, high-alpha stars are uniformly very old (13 Gyr) at [Fe/H]<-1.3, and span a wider range (8-12 Gyr) at higher metallicities. Interpreting the chemistry with a simple chemical evolution model suggests that the non-monotonic behavior is due to a significant increase in star formation efficiency, which began 13 Gyr ago. These results support a picture in which the first 1 Gyr of the Galaxy was characterized by a "simmering phase" in which the star formation efficiency was low and the kinematics had substantial disorder with some net rotation. The disk then underwent a dramatic transformation to a "boiling phase", in which the star formation efficiency increased substantially, the kinematics became disk-like, and the number of stars formed increased tenfold. We interpret this transformation as the birth of the Galactic disk at z~4. The physical origin of this transformation is unclear and does not seem to be reproduced in current galaxy formation models.

astro-ph.GA↗