Simulated Galaxies Research Articles

From particles to pixels: How many particles do I really need to construct stellar kinematic mock observational measurements?

Abstract This work considers the impact of resolution in the construction of mock observations of simulated galaxies. In particular, when building mock integral field spectroscopic observations from galaxy formation models in cosmological simulations, we investigate the possible systematics that may arise given the assumption that all galaxies above some stellar mass limit will provide unbiased and meaningful observable stellar kinematics. We build a catalogue of N-body simulations to sample the range of stellar particle resolutions within the Eagle Ref0050N0752 simulation box and examine how their observable kinematics vary relative to a higher-resolution N-body control. We use these models to compile a table of the minimum number of particles-per-pixel to reach a given uncertainty in the fitted line-of-sight velocity distribution parameters. Further, we introduce a Voronoi-binning module to the mock observation code, SimSpin, in order to meet these minimum numbers. Using Eagle, we show the impact of this shot noise on the observed spin-ellipticity plane and the recovery of this space when observations are binned with increasing numbers of particles. In conclusion, we advise binning mock images to meet at least 200 particles-per-pixel to avoid systematically under-estimating the velocity dispersion along a given line-of-sight. We demonstrate that this is important for comparing galaxies extracted from the same simulation, as well as between simulations of varying mass resolution and observations of real galaxies.

Cold Gas Subgrid Model (CGSM): A two-fluid framework for modeling unresolved cold gas in galaxy simulations

Abstract The cold (∼104 K) component of the circumgalactic medium (CGM) accounts for a significant fraction of all galactic baryons. However, using current galaxy-scale simulations to determine the origin and evolution of cold CGM gas poses a significant challenge, since it is computationally infeasible to directly simulate a galactic halo alongside the sub-pc scales that are crucial for understanding the interactions between cold CGM gas and the surrounding ‘hot’ medium. In this work, we introduce a new approach: the Cold Gas Subgrid Model (CGSM), which models unresolved cold gas as a second fluid in addition to the standard ‘normal’ gas fluid. The CGSM tracks the total mass density and bulk momentum of unresolved cold gas, deriving the properties of its unresolved cloudlets from the resolved gas phase. The interactions between the subgrid cold fluid and the resolved fluid are modeled by prescriptions from high-resolution simulations of ‘cloud crushing’ and thermal instability. Through a series of idealized tests, we demonstrate the CGSM’s ability to overcome the resolution limitations of traditional hydrodynamics simulations, successfully capturing the correct cold gas mass, its spatial distribution, and the timescales for cloud destruction and growth. We discuss the implications of using this model in cosmological simulations to more accurately represent the microphysics that govern the galactic baryon cycle.

Stellar stripping efficiencies of satellites in numerical simulations: the effect of resolution, satellite properties and numerical disruption

Abstract The stellar stripping of satellites in cluster haloes is understood to play an important role in the production of intracluster light. Increasingly, cosmological simulations have been utilised to investigate its origin and assembly. However, such simulations typically model individual galaxies at relatively coarse resolutions, raising concerns about their accuracy. Although there is a growing literature on the importance of numerical resolution for the accurate recovery of the mass loss rates of dark matter (DM) haloes, there has been no comparable investigation into the numerical resolution required to accurately recover stellar mass loss rates in galaxy clusters. Using N-body simulations of satellite galaxies orbiting in a cluster halo represented by a static external potential, we conduct a set of convergence tests in order to explore the role of numerical resolution and force softening length on stellar stripping efficiency. We consider a number of orbital configurations, satellite masses and satellite morphologies. We find that stellar mass resolution is of minor importance relative to DM resolution. Resolving the central regions of satellite DM halos is critical to accurately recover stellar mass loss rates. Poorly resolved DM haloes develop cored inner profiles and, if this core is of comparable size to the stellar component of the satellite galaxy, this leads to significant over-stripping. To prevent this, relatively high DM mass resolutions of around MDM ∼ 106 M⊙, better than those achieved by many contemporary cosmological simulations, are necessary.

Testing the Accuracy of Spectral Energy Distribution Modeling Techniques Using the NIHAO-SKIRT-Catalog

We use simulated galaxy observations from the NIHAO-SKIRT-Catalog to test the accuracy of spectral energy distribution (SED) modeling techniques. SED modeling is an essential tool for inferring star formation histories from nearby galaxy observations but is fraught with difficulty due to our incomplete understanding of stellar populations, chemical enrichment processes, and the nonlinear, geometry-dependent effects of dust. The NIHAO-SKIRT-Catalog uses hydrodynamic simulations and radiative transfer to produce SEDs from the ultraviolet (UV) through the infrared (IR), accounting for dust. We use the commonly used Prospector software to perform inference on these SEDs and compare the inferred stellar masses and star formation rates (SFRs) to the known values in the simulation. We match the stellar population models to isolate the effects of differences in the star formation history, the chemical evolution history, and the dust. For the high-mass NIHAO galaxies (>109.5 M ⊙), we find that model mismatches lead to inferred SFRs that are on average underestimated by a factor of 2 when fit to UV through IR photometry, and a factor of 3 when fit to UV through optical photometry. These biases lead to significant inaccuracies in the resulting specific SFR–mass relations, with UV through optical fits showing particularly strong deviations from the true relation of the simulated galaxies. In the context of massive existing and upcoming photometric surveys, these results highlight that star formation history inference from photometry may remain imprecise and inaccurate and that there is a pressing need for more realistic testing of existing techniques.

Bursty Star Formation in Dwarfs is Sensitive to Numerical Choices in Supernova Feedback Models

Simulations of galaxy formation are mostly unable to resolve the energy-conserving phase of individual supernova events, having to resort to subgrid models to distribute the energy and momentum resulting from stellar feedback. However, the properties of these simulated galaxies, including the morphology, stellar mass formed, and the burstiness of the star formation history, are highly sensitive to the numerical choices adopted in these subgrid models. Using the SMUGGLE stellar feedback model, we carry out idealized simulations of an M vir ∼ 1010 M ⊙ dwarf galaxy, a regime where most simulation codes predict significant burstiness in star formation, resulting in strong gas flows that lead to the formation of dark matter cores. We find that by varying only the directional distribution of momentum imparted from supernovae to the surrounding gas, while holding the total momentum per supernova constant, bursty star formation may be amplified or completely suppressed, and the total stellar mass formed can vary by as much as a factor of ∼3. In particular, when momentum is primarily directed perpendicular to the gas disk, less bursty and lower overall star formation rates result, yielding less gas turbulence, more disky morphologies, and a retention of cuspy dark matter density profiles. An improved understanding of the nonlinear coupling of stellar feedback into inhomogeneous gaseous media is thus needed to make robust predictions for stellar morphologies and dark matter core formation in dwarfs independent of uncertain numerical choices in the baryonic treatment.

Mass modeling and kinematics of galaxy clusters in modified gravity

The chameleon screening mechanism has been constrained many a time using dynamic and kinematic galaxy cluster observables. Current constraints are, however, insensitive to different mass components within galaxy clusters and have been mainly focused on a single mass density profile, the Navarro-Frenk-White mass density model. In this work, we extend the study of the Chameleon screening mechanism in galaxy clusters by considering a series of mass density models, namely: generalized-Navarro-Frenk-While, b-Navarro-Frenk-While, Burket, Isothermal and Einasto. The coupling strength (β) and asymptotic value of the chameleon field (ϕ ∞) are constrained by using kinematics analyses of simulated galaxy clusters, generated both assuming General Relativity and a strong chameleon scenario. By implementing a Bayesian analysis we comprehensively show that the biases introduced due to an incorrect assumption of the mass model are minimal. Similarly, we also demonstrate that a spurious detection of evidence for modifications to gravity is highly unlikely when utilizing the kinematics of galaxy clusters.

A Merger-driven Scenario for Clumpy Galaxy Formation in the Epoch of Reionization: Physical Properties of Clumps in the FirstLight Simulation

Recent JWST observations with superb angular resolution have revealed the existence of clumpy galaxies at high redshift through the detection of rest-frame optical emission lines. We use the FirstLight simulation to study the properties of (sub)galactic clumps that are bright in the [O III] λ5007 line with flux greater than ∼10−18 erg s−1 cm−2, to be detected by JWST. For 62 simulated galaxies that have stellar masses of (0.5–6) × 1010 M ⊙ at z = 5, we find clumps in 1828 snapshots in the redshift range z = 9.5–5.5. The clumps are identified by the surface density of the star formation rate (SFR). About one-tenth of the snapshots show the existence of clumpy systems with two or more components. Most of the clumps are formed by mergers and can be characterized by their ages: central clumps dominated by stellar populations older than 50 Myr, and off-centered clumps dominated by younger stellar populations with specific SFRs of ∼50 Gyr−1. The latter type of young clumps is formed from gas debris in the tidal tails of major mergers with baryonic mass ratios of 1 ≤ q < 4. The merger-induced clumps are short-lived and merge within a dynamical time of several tens of million years. The number density of the clumpy systems is estimated to be ∼10−5 cMpc−3, which is large enough to be detected in recent JWST surveys.

Simba-EoR: early galaxy formation in the simba simulation including a new sub-grid interstellar medium model

ABSTRACT We update the dust model present within the simba galaxy simulations with a self-consistent framework for the co-evolution of dust and molecular hydrogen populations in the interstellar medium, and use this to explore $z \ge 6$ galaxy evolution. In addition to tracking the evolution of dust and molecular hydrogen abundances, our model fully integrates these species into the simba simulation, explicitly modelling their impact on physical processes such as star formation and cooling through the inclusion of a novel two-phase sub-grid model for interstellar gas. Running two cosmological simulations down to $z \sim 6$ we find that our simba-EoR model displays a generally tighter concordance with observational data than fiducial simba. Additionally we observe that our simba-EoR models increase star formation activity at early epochs, producing larger dust-to-gas ratios consequently. Finally, we discover a significant population of hot dust at $\sim 100$ K, aligning with contemporaneous observations of high-redshift dusty galaxies, alongside the large $\sim 20$ K population typically identified.

Untangling stellar components of galaxies: Evaluation of dynamical decomposition methods in simulated galaxies with GalaxyChop

Galaxy formation is intrinsically connected to the distinct evolutionary processes of disk and spheroidal systems, which are the fundamental stellar components of galaxies. Understanding the mutual, dynamical interplay and co-evolution of these components requires a detailed dynamical analysis to allow for disentanglement of these systems. We introduce JEHistogram, a new method for the dynamical decomposition of simulated galaxies into disk and spheroidal stellar components that utilizes the angular momentum and energy of star particles. We evaluate its performance against five previously established methods using a sample of equilibrium galaxies with stellar masses in the range $10^ M_ gal /M_ $. Our assessment involves several metrics, including the completeness and purity of stellar particle classification, scale lengths, mass density profiles, velocity dispersion, and rotational velocity profiles. While all methods approximate the properties of the original components, such as mass fractions and density or velocity profiles, JEHistogram demonstrates a better accuracy, particularly in the inner regions of galaxies where component overlap complicates separation. Additionally, we apply JEHistogram to a Milky Way-like galaxy from the IllustrisTNG cosmological simulations, showcasing its capability to derive properties such as the size, mass, velocity, color, and age of dynamically defined disk and spheroidal components. All the dynamical decomposition methods we analyzed are publicly accessible through the Python package GalaxyChop

On the Corotation of Milky Way Satellites: LMC-mass Satellites Induce Apparent Motions in Outer Halo Tracers

Abstract Understanding the physical mechanism behind the formation of a corotating thin plane of satellite galaxies, like the one observed around the Milky Way (MW), has been challenging. The perturbations induced by a massive satellite galaxy, like the Large Magellanic Cloud (LMC), provide valuable insight into this problem. The LMC induces an apparent corotating motion in the outer halo by displacing the inner regions of the halo with respect to the outer halo. Using the Latte suite of Feedback In Realistic Environments cosmological simulations of MW-mass galaxies, we confirm that the apparent motion of the outer halo induced by the infall of a massive satellite changes the observed distribution of orbital poles of outer-halo tracers, including satellites. We quantify the changes in the distribution of orbital poles using the two-point angular correlation function and find that all satellites induce changes. However, the most massive satellites with pericentric passages between ≈30 and 100 kpc induce the largest changes. The best LMC-like satellite analog shows the largest change in orbital pole distribution. The dispersion of orbital poles decreases by 20° during the first two pericentric passages. Even when excluding the satellites brought in with the LMC-like satellite, there is clustering of orbital poles. These results suggest that in the MW, the recent pericentric passage of the LMC should have changed the observed distribution of orbital poles of all other satellites. Therefore, studies of kinematically coherent planes of satellites that seek to place the MW in a cosmological context should account for the existence of a massive satellite like the LMC.

The glow of axion quark nugget dark matter

Context. The existence of axion quark nuggets is a potential consequence of the axion field, which provides a possible solution to the charge-conjugation parity violation in quantum chromodynamics. In addition to explaining the cosmological discrepancy of matter-antimatter asymmetry and a visible-to-dark-matter ratio of Ωdark/Ωvisible ≃ 5, these composite compact objects are expected to represent a potentially ubiquitous electromagnetic background radiation by interacting with ordinary baryonic matter. We conducted an in-depth analysis of axion quark nugget-baryonic matter interactions in the environment of the intracluster medium in the constrained cosmological Simulation of the LOcal Web (SLOW). Aims. Here, we aim to provide upper limit predictions on electromagnetic counterparts of axion quark nuggets in the environment of galaxy clusters by inferring their thermal and non-thermal emission spectrum originating from axion quark nugget-cluster gas interactions. Methods. We analyzed the emission of axion quark nuggets in a large sample of 161 simulated galaxy clusters using the SLOW simulation. These clusters are divided into a sub-sample of 150 galaxy clusters, ordered in five mass bins ranging from 0.8 to 31.7 × 1014 M⊙, along with 11 cross-identified galaxy clusters from observations. We investigated dark matter-baryonic matter interactions in galaxy clusters in their present stage at the redshift of z = 0 by assuming all dark matter consists of axion quark nuggets. The resulting electromagnetic signatures were compared to thermal Bremsstrahlung and non-thermal cosmic ray (CR) synchrotron emission in each galaxy cluster. We further investigated individual frequency bands imitating the observable range of the WMAP, Planck, Euclid, and XRISM telescopes for the most promising cross-identified galaxy clusters hosting detectable signatures of axion quark nugget emission. Results. We observed a positive excess in the low- and high-energy frequency windows, where thermal and non-thermal axion quark nugget emission can significantly contribute to (or even outshine) the emission of the intracluster medium (ICM) in frequencies up to νT ≲ 3842.19 GHz and νT ϵ [3.97, 10.99] × 1010GHz, respectively. Emission signatures of axion quark nuggets are found to be observable if CR synchrotron emission of individual clusters is sufficiently low. The degeneracy in the parameters contributing to an emission excess makes it challenging to offer predictions with respect to pinpointing specific regions of a positive axion quark nugget excess; however, a general increase in the total galaxy cluster emission is expected based on this dark matter model. Axion quark nuggets constitute an increment of 4.80% of the total galaxy cluster emission in the low-energy regime of νT ≲ 3842.19 GHz for a selection of cross-identified galaxy clusters. We propose that the Fornax and Virgo clusters represent the most promising candidates in the search for axion quark nugget emission signatures. Conclusions. The results from our simulations point towards the possibility of detecting an axion quark nugget excess in galaxy clusters in observations if their signatures can be sufficiently disentangled from the ICM radiation. While this model proposes a promising explanation for the composition of dark matter, with the potential to have this outcome verified by observations, we propose further changes that are aimed at refining our methods. Our ultimate goal is to identify the extracted electromagnetic counterparts of axion quark nuggets with even greater precision in the near future.

The disc origin of the Milky Way bulg. The high velocity dispersion of metal-rich stars at low latitudes

Previous studies of the chemo-kinematic properties of stars in the Galactic bulge have revealed a puzzling trend. Along the bulge minor axis, and close to the Galactic plane, metal-rich stars display a higher line-of-sight velocity dispersion compared to metal-poor stars, while at higher latitudes metal-rich stars have lower velocity dispersions than metal-poor stars, similar to what is found in the Galactic disc. In this work, we re-examine this issue, by studying the dependence of line-of-sight velocity dispersions on metallicity and latitude in APOGEE Data Release 17, confirming the results of previous works. We then analyse an $N$-body simulation of a Milky Way-like galaxy, also taking into account observational biases introduced by the APOGEE selection function. We show that the inversion in the line-of-sight velocity dispersion-latitude relation observed in the Galactic bulge -- where the velocity dispersion of metal-rich stars becomes greater than that of metal-poor stars as latitude decreases -- can be reproduced by our model. We show that this inversion is a natural consequence of a scenario in which the bulge is a boxy or peanut-shaped structure, whose metal-rich and metal-poor stars mainly originate from the thin and thick disc of the Milky Way, respectively. Due to their cold kinematics, metal-rich, thin disc stars are efficiently trapped in the boxy, peanut-shaped bulge, and at low latitudes show a strong barred morphology, which -- given the bar orientation with respect to the Sun-Galactic centre direction -- results in high velocity dispersions that are larger than those attained by the metal-poor populations. Extremely metal-rich stars in the Galactic bulge, which have received renewed attention in the literature, do follow the same trends as those of the metal-rich populations. The line-of-sight velocity-latitude relation observed in the Galactic bulge for metal-poor and metal-rich stars are thus both an effect of the intrinsic nature of the Galactic bulge (i.e. mostly secular) and of the angle at which we observe it from the Sun.

Assessing the robustness of the Galactic rotation curve inferred from the Jeans equations using Gaia DR3 and cosmological simulations

Several authors have recently applied Jeans modelling to -based datasets to infer the circular velocity curve for the Milky Way. These works have consistently found evidence for a continuous decline in the rotation curve beyond $ kpc $, which may indicate the existence of a light dark matter (DM) halo. Using a large sample of Gaia DR3 data, we aim to derive the rotation curve of the Milky Way using the Jeans equations, and to quantify the role of systematic effects, both in the data and those inherent to the Jeans methodology under the assumptions of axisymmetry and time independence. We used data from the Gaia DR3 radial velocity spectrometer sample, supplemented with distances inferred through Bayesian frameworks, to determine the radial variation of the second moments of the velocity distribution for stars close to the Galactic plane. We used these profiles to determine the rotation curve using the Jeans equations under the assumption of axisymmetry and explored how they vary with azimuth and position above and below the plane of the Galactic disc. We applied the same methodology to an N-body simulation of a Milky Way-like galaxy impacted by a satellite akin the Sagittarius dwarf, and to the Auriga suite of cosmological simulations. The circular velocity curve we infer for the Milky Way is consistent with previous findings out to $ 15$ kpc, where our statistics are robust. Due to the larger number of stars in our sample, we are able to reveal evidence of disequilibrium and deviations from axisymmetry closer in. For example, we find that the second moment of $V_R$ flattens out at $R kpc, and that the second moment of $V_ is different above and below the plane for $R kpc. Our exploration of the simulations indicates that these features are typical of galaxies that have been perturbed by external satellites. From the simulations, we also estimate that the difference between the true circular velocity curve and that inferred from Jeans equations can be as high as $15&lt;!PCT!&gt;$, but that it is likely of the order of $10&lt;!PCT!&gt;$ for the Milky Way. This is higher than the systematic uncertainties associated with the observations or those linked to most modelling assumptions when using the Jeans equations. However, if the density of the tracer population were truncated at large radii instead of being exponential as often assumed, this could lead to the erroneous conclusion of a steeply declining rotation curve. We find that steady-state axisymmetric Jeans modelling becomes less robust at large radii, indicating that particular caution must be exercised when interpreting the rotation curve inferred in those regions. A more careful and sophisticated approach may be necessary for precision measurements of the DM content of our Galaxy.

Reconciling concentration to virial mass relations

The concentration--virial mass (c-M) relation is a fundamental scaling relation within the standard cold dark matter (Lambda CDM) framework well established in numerical simulations. However, observational constraints of this relation are hampered by the difficulty of characterising the properties of dark matter haloes. Recent comparisons between simulations and observations have suggested a systematic difference of the c-M relation, with higher concentrations in the latter. In this work, we undertake detailed comparisons between simulated galaxies and observations of a sample of strong-lensing galaxies. We explore several factors of the comparison with strong gravitational lensing constraints, including the choice of the generic dark matter density profile, the effect of radial resolution, the reconstruction limits of observed versus simulated mass profiles, and the role of the initial mass function in the derivation of the dark matter parameters. Furthermore, we show the dependence of the c-M relation on reconstruction and model errors through a detailed comparison of real and simulated gravitational lensing systems. An effective reconciliation of simulated and observed c-M relations can be achieved if one considers less strict assumptions on the dark matter profile, for example, by changing the slope of a generic NFW profile or focusing on rather extreme combinations of stellar-to-dark matter distributions. A minor effect is inherent to the applied method: fits to the NFW profile on a less well-constrained inner mass profile yield slightly higher concentrations and lower virial masses.

Radial properties of dust in galaxies: Comparison between observations and isolated galaxy simulations

We study the importance of several processes that influence the evolution of dust and its grain size distribution on spatially resolved scales in nearby galaxies. Here, we compiled several multi-wavelength observations for the nearby galaxies NGC\,628 (M74), NGC\,5457 (M101), NGC\,598 (M33), and NGC 300. We applied spatially resolved spectral energy distribution (SED) fitting to the latest iteration of infrared data to get constraints on the galaxy dust masses and the small-to-large grain abundance ratio (SLR). We separated each galaxy into radial rings and obtained the radial profiles of the properties mentioned above. For comparison, we took the radial profiles of the stellar mass and gas mass surface density for NGC\,628 combined with its metallicity gradient in the literature to calibrate a single-galaxy simulation using the GADGET4-OSAKA code. The simulations include a parametrization to separate the dense and diffuse phases of the ISM where different dust-evolution mechanisms are in action. We find that our simulation can reproduce the radial profile of dust mass surface density but overestimates the SLR in NGC\,628. Changing the dust-accretion timescale has little impact on the dust mass or SLR, as most of the available metals are accreted onto dust grains at early times ($&lt;3$\,Gyr), except in the outer regions of the galaxy where the metallicity is below $2 $. This suggests we can only constrain the accretion timescale of galaxies at extremely low metallicities where accretion still competes with other mechanisms controlling the dust budget. The overestimation of the SLR likely results from (i) overly efficient shattering processes in the diffuse interstellar medium (ISM), which were calibrated to reproduce Milky Way-type galaxies and/or (ii) our use of a diffuse and dense gas density subgrid model that does not entirely capture the intricacies of the small-scale structure present in NGC\,628. We conclude that future modeling efforts will need to focus on improving the subgrid recipes to mimic the multi-phase gas distribution in galaxies before the efficiency of dust evolution processes can be calibrated for galaxies other than the Milky Way.

N exus: a framework for controlled simulations of idealized galaxies

ABSTRACT Motivated by the need for realistic, dynamically self-consistent, evolving galaxy models that avoid the complexity of full, and zoom-in, cosmological simulations, we have developed Nexus, an integral framework to create and evolve synthetic galaxies made of collisionless and gaseous components. Nexus leverages the power of publicly available, tried-and-tested packages: the stellar-dynamics, action-based library Action-based Galaxy Modelling Architecture (AGAMA); and the adaptive mesh refinement, N-body/hydrodynamical code Ramses, modified to meet our needs. In addition, we make use of a proprietary module to account for galaxy formation physics, including gas cooling and heating, star formation, stellar feedback, and chemical enrichment. Nexus’ basic functionality consists in the generation of bespoke initial conditions (ICs) for a diversity of galaxy models, which are advanced in time to simulate the galaxy’s evolution. The fully self-consistent ICs are generated with a distribution-function-based approach, as implemented in the galaxy modelling module of AGAMA – up to now restricted to collisionless components, extended in this work to treat two types of gaseous configurations: hot haloes and gas discs. Nexus allows constructing equilibrium models with disc gas fractions $0~\le ~f_{\rm {\rm gas}}~\le ~1$, appropriate to model both low- and high-redshift galaxies. Similarly, the framework is ideally suited to the study of galactic ecology, i.e. the dynamical interplay between stars and gas over billions of years. As a validation and illustration of our framework, we reproduce several isolated galaxy model setups reported in earlier studies, and present a new, ‘nested bar’ galaxy simulation. Future upgrades of Nexus will include magnetohydrodynamics and highly energetic particle (‘cosmic ray’) heating.

MEGS: Morphological Evaluation of Galactic Structur. Principal component analysis as a galaxy morphology model

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 $ for 2D images and $ 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 downstreaming tasks such as galaxy classification and analysis.

Strong turbulence and magnetic coherent structures in the interstellar medium

Magnetic turbulence is classified as weak or strong based on the relative amplitude of the magnetic field fluctuations compared to the mean field. These two classes have different energy transport properties. The purpose of this study is to analyze turbulence in the interstellar medium (ISM) based on this classification. Specifically, we examined the ISM of simulated galaxies to detect evidence of strong magnetic turbulence and provide statistics on the associated magnetic coherent structures (MCoSs), such as current sheets, that arise in this context. We analyzed magnetohydrodynamic galaxy simulations with different initial magnetic field structures (either completely ordered or completely random) and recorded statistics on the magnetic field fluctuations ($ B/B_0$) and the MCoSs, which are defined here as regions where the current density surpasses a certain threshold. We also studied the MCoS sizes and kinematics. The magnetic field disturbances in both models follow a log-normal distribution, peaking at values close to unity; this distribution turns into a power law at large values ($ B/B_0 &gt; 1$), which is consistent with strong magnetic turbulence The current densities are widely distributed, with non-power-law deviations from a log-normal at the largest values. These deviating values of the current density define MCoSs. We find that, in both models, MCoSs are fractally distributed in space, with a typical volume-filling factor of about 10 percent, and tend to coincide with peaks of star formation density. Their fractal dimension is close to unity on sub-kiloparsec scales, and between 2 and 3 on larger scales. These values are consistent with MCoSs having a sheet-like or filament-like morphology. Our work challenges the prevailing paradigm of weak magnetic turbulence in the ISM by demonstrating that strong magnetic disturbances can occur even when the initial magnetic field is completely ordered. This strong magnetic turbulence arises self-consistently from differential rotation and supernova feedback. Our findings provide a foundation for a magnetic turbulence description of the galactic ISM that includes strong fluctuations of the magnetic field.

The redshift evolution of galactic bar pattern speed in TNG50

In this paper, the redshift evolution of the galactic bar properties, like the bar length, pattern speed, and bar fraction, has been investigated for simulated galaxies at stellar masses of $M_*&gt;10^ odot $ in the cosmological magnetohydrodynamical simulation TNG50. We focus on the redshift evolution of the bar pattern speeds and the fast bar tension. We show that the median value of the pattern speed of the bars increases as the redshift grows. On the other hand, although the median value of the bar length increases with time, the ratio between the corotation radius and the bar radius — namely, the $ R =R_ CR /R_ bar $ parameter — increases as well. In other words, the corotation radius increases with a higher rate than the bar length. This directly means that galactic bars slow down with time, or equivalently as the redshift declines. We discuss the possible mechanisms that reduce the pattern speeds in TNG50. We demonstrate that while mergers can have a significant impact on a galaxy's pattern speed, they do not play a crucial role in the overall evolution of mean pattern speed within the redshift range $z 1.0$. Furthermore, we show that the $ R $ parameter does not correlate with the gas fraction. Consequently, the existence of gas in TNG50 does not alleviate the fast bar tension. We show that the mean value of the pattern speed, computed for all the galaxies irrespective of their mass, at $z=1.0$ is $ 2.34$ km $ kpc$^ $ and reduces to $ 1.07$ km $ kpc$^ $ at $z=0.0$. This is a direct prediction by TNG50 that bars at $z=1.0$ rotate faster by a factor of $ 2$ compared to bars at $z=0.0$.

Analysis of Ring Galaxies Detected Using Deep Learning with Real and Simulated Data

Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as manual analysis takes months to accumulate an appreciable sample of rings. This paper presents a convolutional neural network (CNN) to identify ring galaxies from unclassified samples. A CNN was trained on 100,000 simulated galaxies, transfer learned onto a sample of real galaxies, and applied to a previously unclassified data set to generate a catalog of rings, which was then manually verified. Data augmentation with a generative adversarial network to simulate images of galaxies was also employed. The resulting catalog contains 1967 ring galaxies. The properties of these galaxies were then estimated from their photometry and compared to the Galaxy Zoo 2 catalog of rings. However, the model’s precision is currently limited due to a severe imbalance of rings in real data sets, leading to a significant false-positive rate of 41.1%, which poses challenges for large-scale applications in surveys imaging billions of galaxies. This study demonstrates the potential of optimizing machine learning pipelines for low training data in rare morphologies and underscores the need for further refinements to enhance precision for extensive surveys like the Vera Rubin Observatory Legacy Survey of Space and Time.