Search

Superclusters are the most massive structures in the universe. To what degree they are actually bound against an accelerating expansion of the background is of significant cosmological and astrophysical interest. In this study, we introduce a cross matched set of superclusters from the SLOW constrained simulations of the local (z<0.05) universe. Identifying the superclusters provides estimates on the efficacy of the constraints in reproducing the local large-scale structure accurately. The simulated counterparts can help identifying possible future observational targets containing interesting features such as bridges between pre-merging and merging galaxy clusters and collapsing filaments and provide comparisons for current observations. By determining the collapse volumes for the superclusters we further elucidate the dynamics of cluster-cluster interactions in those regions. Using catalogs of local superclusters and the most massive simulated clusters, we search for counterparts of supercluster members of six regions. We evaluate the significance of these detections by comparing their geometries to supercluster regions in random simulations. We then run an N-body version of the simulation into the far future and determine which of the member clusters are gravitationally bound to the host superclusters. Furthermore we compute masses and density contrasts for the collapse regions. We demonstrate the SLOW simulation of the local universe to accurately reproduce local supercluster regions in mass of their members and three-dimensional geometrical arrangement. We furthermore find the bound regions of the local superclusters consistent in size and density contrast with previous theoretical studies. This will allow to connect future numerical zoom-in studies of the clusters to the large scale environments and specifically the supercluster environments these local galaxy clusters evolve in., Comment: 18 pages, 20 figures, submitted to A&A

We present a study on the inference of cosmological and astrophysical parameters using stacked galaxy cluster profiles. Utilizing the CAMELS-zoomGZ simulations, we explore how various cluster properties--such as X-ray surface brightness, gas density, temperature, metallicity, and Compton-y profiles--can be used to predict parameters within the 28-dimensional parameter space of the IllustrisTNG model. Through neural networks, we achieve a high correlation coefficient of 0.97 or above for all cosmological parameters, including $\Omega_{\rm m}$, $H_0$, and $\sigma_8$, and over 0.90 for the remaining astrophysical parameters, showcasing the effectiveness of these profiles for parameter inference. We investigate the impact of different radial cuts, with bins ranging from $0.1R_{200c}$ to $0.7R_{200c}$, to simulate current observational constraints. Additionally, we perform a noise sensitivity analysis, adding up to 40\% Gaussian noise (corresponding to signal-to-noise ratios as low as 2.5), revealing that key parameters such as $\Omega_{\rm m}$, $H_0$, and the IMF slope remain robust even under extreme noise conditions. We also compare the performance of full radial profiles against integrated quantities, finding that profiles generally lead to more accurate parameter inferences. Our results demonstrate that stacked galaxy cluster profiles contain crucial information on both astrophysical processes within groups and clusters and the underlying cosmology of the universe. This underscores their significance for interpreting the complex data expected from next-generation surveys and reveals, for the first time, their potential as a powerful tool for parameter inference., Comment: Submitted to ApJ

(abridged) We analyze 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 $31.7 \times 10^{14} \,M_\odot$, along with 11 cross-identified galaxy clusters from observations. We investigate dark matter-baryonic matter interactions in galaxy clusters in their present stage at redshift $z=0$ by assuming all dark matter consists of axion quark nuggets. The resulting electromagnetic signatures are compared to thermal Bremsstrahlung and non-thermal cosmic ray synchrotron emission in each galaxy cluster. We further investigate 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. We propose that the Fornax and Virgo clusters represent the most promising candidates to search for axion quark nugget emission signatures., Comment: 22 pages, 14 figures

This is the second paper in a series presenting the results from a 500 $h^{-1}$Mpc large constrained hydro-dynamical simulation of the local Universe (SLOW). The initial conditions are based on peculiar velocities derived from the CosmicFlows-2 catalogue. The inclusion of galaxy formation treatment, allows to directly predict observable properties of the Intra-Cluster Medium (ICM) within galaxy clusters. Comparing the properties of observed galaxy clusters within the local Universe with the properties of their simulated counterparts, enables us to assess the effectiveness of the initial condition constraints in accurately replicating the non-linear properties of the largest, collapsed objects within the simulation. Based on the combination of several, publicly available surveys, we identified 45 local Universe galaxy clusters in SLOW, including the 13 most massive from the Planck SZ catalog and 70% of those with $M_{500} > 2\times 10^{14}$ M$_{\odot}$. We then derived the probability of the cross identification based on mass, X-ray luminosity, temperature and Compton-y by comparing it to a random selection. In relation to previous constrained simulations of the local volume, we found in SLOW a much larger amount of replicated galaxy clusters, where their simulation based mass prediction falls within the uncertainties of the observational mass estimates. Comparing the median observed and simulated masses of our cross identified sample allows to independently deduce a hydrostatic mass bias of $(1-b)\approx0.87$. The SLOW constrained simulation of the local Universe faithfully reproduces numerous fundamental characteristics of the galaxy clusters within our local neighbourhood, opening a new avenue for studying the formation and evolution of a large set of individual galaxy clusters as well as testing our understanding of physical processes governing the ICM., Comment: Submitted to Astronomy & Astrophysics

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. (2023) developed models that could accurately infer the value of $\Omega_{\rm m}$ from catalogs that only contain the positions and radial velocities of galaxies that are robust to uncertainties in astrophysics and subgrid models. However, observations are affected by many effects, including 1) masking, 2) uncertainties in peculiar velocities and radial distances, and 3) different galaxy selections. Moreover, observations only allow us to measure redshift, intertwining galaxies' radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that, although the presence of these effects degrades the precision and accuracy of the models, and increases the fraction of catalogs where the model breaks down, the fraction of galaxy catalogs where the model performs well is over 90 %, demonstrating the potential of these models to constrain cosmological parameters even when applied to real data., Comment: 39 pages, 25 figures. For the reference in the abstract (de Santi et al. 2023) see arXiv:2302.14101

Aims: Detecting diffuse synchrotron emission from the cosmic web is still a challenge for current radio telescopes. We aim to make predictions about the detectability of cosmic web filaments from simulations. Methods: We present the first cosmological magnetohydrodynamic simulation of a 500 $h^{-1} c$Mpc volume with an on-the-fly spectral cosmic ray (CR) model. This allows us to follow the evolution of populations of CR electrons and protons within every resolution element of the simulation. We modeled CR injection at shocks, while accounting for adiabatic changes to the CR population and high-energy-loss processes of electrons. The synchrotron emission was then calculated from the aged electron population, using the simulated magnetic field, as well as different models for the origin and amplification of magnetic fields. We used constrained initial conditions, which closely resemble the local Universe, and compared the results of the cosmological volume to a zoom-in simulation of the Coma cluster, to study the impact of resolution and turbulent reacceleration of CRs on the results. Results: We find a consistent injection of CRs at accretion shocks onto cosmic web filaments and galaxy clusters. This leads to diffuse emission from filaments of the order $S_\nu \approx 0.1 \: \mu$Jy beam$^{-1}$ for a potential LOFAR observation at 144~MHz, when assuming the most optimistic magnetic field model. The flux can be increased by up to two orders of magnitude for different choices of CR injection parameters. This can bring the flux within a factor of ten of the current limits for direct detection. We find a spectral index of the simulated synchrotron emission from filaments of $\alpha \approx$ -1.0 -- -1.5 in the LOFAR band., Comment: 26 pages, 18 figures, accepted for publication in A&A

When measuring the observed pressure, density or temperature profiles of the intracluster gas, and hence the mass of clusters of galaxies, projection effects or departures from the spherical symmetry hypothesis may induce biases. In order to estimate how strongly the cluster observed properties depend on the direction of observation, we use a constrained hydrodynamical simulation of Virgo cluster that replicates the actual cluster of galaxies. In this case study, we analyse Virgo properties when they are projected along different directions including along the Milky Way-Virgo axis which mimics our observation direction. We compare the hydrostatic mass and the hydrostatic mass bias from the projection along the different observation directions to that derived from the 3D simulation. We show that projection effects impact the determination of Virgo mass. We particularly demonstrate that the mass and pressure along the line of sight correlates with the 2D and 3D-deprojected electron density and pressure profiles intensity and thus impacts the derived hydrostatic mass. We also show that the deviations to the hydrostatic equilibrium induced by pressure discontinuities within the cluster are emphasized by the deprojection process and thus makes the hydrostatic mass estimation invalid at these radii., Comment: Published in A&A, proofs version, 18 pages, 10 figures and 3 tables

Recent work has pointed out the potential existence of a tight relation between the cosmological parameter $\Omega_{\rm m}$, at fixed $\Omega_{\rm b}$, and the properties of individual galaxies in state-of-the-art cosmological hydrodynamic simulations. In this paper, we investigate whether such a relation also holds for galaxies from simulations run with a different code that made use of a distinct subgrid physics: Astrid. We find that also in this case, neural networks are able to infer the value of $\Omega_{\rm m}$ with a $\sim10\%$ precision from the properties of individual galaxies while accounting for astrophysics uncertainties as modeled in CAMELS. This tight relationship is present at all considered redshifts, $z\leq3$, and the stellar mass, the stellar metallicity, and the maximum circular velocity are among the most important galaxy properties behind the relation. In order to use this method with real galaxies, one needs to quantify its robustness: the accuracy of the model when tested on galaxies generated by codes different from the one used for training. We quantify the robustness of the models by testing them on galaxies from four different codes: IllustrisTNG, SIMBA, Astrid, and Magneticum. We show that the models perform well on a large fraction of the galaxies, but fail dramatically on a small fraction of them. Removing these outliers significantly improves the accuracy of the models across simulation codes., Comment: 16 pages, 12 figures

We discover analytic equations that can infer the value of $\Omega_{\rm m}$ from the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining a tailored graph neural network (GNN) architecture with symbolic regression. We first train the GNN on dark matter halos from Gadget N-body simulations to perform field-level likelihood-free inference, and show that our model can infer $\Omega_{\rm m}$ with $\sim6\%$ accuracy from halo catalogues of thousands of N-body simulations run with six different codes: Abacus, CUBEP$^3$M, Gadget, Enzo, PKDGrav3, and Ramses. By applying symbolic regression to the different parts comprising the GNN, we derive equations that can predict $\Omega_{\rm m}$ from halo catalogues of simulations run with all of the above codes with accuracies similar to those of the GNN. We show that by tuning a single free parameter, our equations can also infer the value of $\Omega_{\rm m}$ from galaxy catalogues of thousands of state-of-the-art hydrodynamic simulations of the CAMELS project, each with a different astrophysics model, run with five distinct codes that employ different subgrid physics: IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE. Furthermore, the equations also perform well when tested on galaxy catalogues from simulations covering a vast region in parameter space that samples variations in 5 cosmological and 23 astrophysical parameters. We speculate that the equations may reflect the existence of a fundamental physics relation between the phase-space distribution of generic tracers and $\Omega_{\rm m}$, one that is not affected by galaxy formation physics down to scales as small as $10~h^{-1}{\rm kpc}$., Comment: 32 pages, 13 figures, summary video: https://youtu.be/STZHvDHkVgo

We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant and do not impose any cut on scale. From galaxy catalogs that only contain $3$D positions and radial velocities of $\sim 1, 000$ galaxies in tiny $(25~h^{-1}{\rm Mpc})^3$ volumes our models can infer the value of $\Omega_{\rm m}$ with approximately $12$ % precision. More importantly, by testing the models on galaxy catalogs from thousands of hydrodynamic simulations, each having a different efficiency of supernova and AGN feedback, run with five different codes and subgrid models - IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE -, we find that our models are robust to changes in astrophysics, subgrid physics, and subhalo/galaxy finder. Furthermore, we test our models on $1,024$ simulations that cover a vast region in parameter space - variations in $5$ cosmological and $23$ astrophysical parameters - finding that the model extrapolates really well. Our results indicate that the key to building a robust model is the use of both galaxy positions and velocities, suggesting that the network have likely learned an underlying physical relation that does not depend on galaxy formation and is valid on scales larger than $\sim10~h^{-1}{\rm kpc}$., Comment: 34 pages, 12 figures. For a video summarizing the results, see https://youtu.be/b59ep7cyPOs

Context: Several observations of the local Universe (LU) point towards the existence of very prominent structures. The presence of massive galaxy clusters and local super clusters on the one hand, but also large local voids and under-densities on the other hand. However, it is highly non trivial to connect such different observational selected tracers to the underlying dark matter (DM) distribution. Methods (abridged): We used a 500 Mpc/h large constrained simulation of the LU with initial conditions based on peculiar velocities derived from the CosmicFlows-2 catalogue and follow galaxy formation physics directly in the hydro-dynamical simulations to base the comparison on stellar masses of galaxies or X-ray luminosity of clusters. We also used the 2668 Mpc/h large cosmological box from the Magneticum simulations to evaluate the frequency of finding such anomalies in random patches within simulations. Results: We demonstrate that haloes and galaxies in our constrained simulation trace the local DM density field very differently. Thereby, this simulation reproduces the observed 50% under-density of galaxy clusters and groups within the sphere of ~100 Mpc when applying the same mass or X-ray luminosity limit used in the observed cluster sample (CLASSIX), which is consistent with a ~1.5$\sigma$ feature. At the same time, the simulation reproduces the observed over-density of massive galaxy clusters within the same sphere, which on its own also corresponds to a ~1.5$\sigma$ feature. Interestingly, we find that only 44 out of 15635 random realizations (i.e. 0.28%) are matching both anomalies, making the LU to be a ~3$\sigma$ environment. We finally compared a mock galaxy catalogue with the observed distribution of galaxies in the LU, finding also a match to the observed factor of two over-density at ~16 Mpc as well as the observed 15% under-density at ~40 Mpc distance., Comment: 16 pages, 12 figure, accepted for publication in A&A

We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain $\lesssim$5,000 halos with masses $\gtrsim 10^{10}~h^{-1}M_\odot$ in a periodic volume of $(25~h^{-1}{\rm Mpc})^3$; every halo in the catalogue is characterized by several properties such as position, mass, velocity, concentration, and maximum circular velocity. Our models, built to be permutationally, translationally, and rotationally invariant, do not impose a minimum scale on which to extract information and are able to infer the values of $\Omega_{\rm m}$ and $\sigma_8$ with a mean relative error of $\sim6\%$, when using positions plus velocities and positions plus masses, respectively. More importantly, we find that our models are very robust: they can infer the value of $\Omega_{\rm m}$ and $\sigma_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses. Surprisingly, the model trained to infer $\Omega_{\rm m}$ also works when tested on thousands of state-of-the-art CAMELS hydrodynamic simulations run with four different codes and subgrid physics implementations. Using halo properties such as concentration and maximum circular velocity allow our models to extract more information, at the expense of breaking the robustness of the models. This may happen because the different N-body codes are not converged on the relevant scales corresponding to these parameters., Comment: 25 pages, 11 figures, summary video: https://youtu.be/qkw92Z6owJU

We present results from models of galactic winds driven by energy injected from nuclear (at the galactic center) and non-nuclear starbursts. The total energy of the starburst is provided by very massive young stellar clusters,which can push the galactic interstellar medium and produce an important outflow. Such outflow can be a well, or partially mixed wind, or a highly metallic wind. We have performed adiabatic 3D N-Body/Smooth Particle Hydrodynamics simulations of galactic winds using the GADGET-2 code. The numerical models cover a wide range of parameters, varying the galaxy concentration index, gas fraction of the galactic disk, and radial distance of the starburst. We show that an off-center starburst in dwarf galaxies is the most effective mechanism to produce a significant loss of metals (material from the starburst itself). At the same time a non-nuclear starburst produce a high efficiency of metal loss, in spite of having a moderate to low mass loss rate., Comment: 13 pages, 7 figures, accepted for publication in ApJ

By measuring precise radial velocities of planetary nebulae (which belong to the intermediate age population), H II regions, and A-type supergiant stars (which are members of the young population) in NGC 6822, we aim to determine if both types of population share the kinematics of the disk of H I found in this galaxy. Spectroscopic data for four planetary nebulae were obtained with the high spectral resolution spectrograph Magellan Inamori Kyocera Echelle (MIKE) on the Magellan telescope at Las Campanas Observatory. Data for other three PNe and one H II region were obtained from the SPM Catalog of Extragalactic Planetary Nebulae which employed the Manchester Echelle Spectrometer attached to the 2.1m telescope at the Observatorio Astron\'omico Nacional, M\'exico. In the wavelength calibrated spectra, the heliocentric radial velocities were measured with a precision better than 5-6 km s$^{-1}$. Data for three additional H II regions and a couple of A-type supergiant stars were collected from the literature. The heliocentric radial velocities of the different objects were compared to the velocities of the H i disk at the same position. From the analysis of radial velocities it is found that H II regions and A-type supergiants do share the kinematics of the H I disk at the same position, as expected for these young objects. On the contrary, planetary nebula velocities differ significantly from that of the H I at the same position. The kinematics of planetary nebulae is independent from the young population kinematics and it is closer to the behavior shown by carbon stars, which are intermediate-age members of the stellar spheroid existing in this galaxy. Our results are confirming that there are at least two very different kinematical systems in NGC 6822.

[OIII]5007 on-band off-band images, obtained with the VLT and FORS2 spectrograph in two zones (center and outskirts) of the spiral galaxy NGC300, are analyzed searching for emission line objects. In particular we search for planetary nebula (PN) candidates to analyze their distribution and luminosity properties, to perform follow-up spectroscopy, and to study the planetary nebula luminosity function, PNLF. In the continuum-subtracted images, a large number of emission line objects were detected. From this sample we selected as PN candidates those objects with stellar appearance and no detectable central star. [OIII]5007 instrumental magnitudes were measured and calibrated by using spectrophotometric data from the follow-up spectroscopy. We identified more than a hundred PN candidates and a number of compact HII regions. The PN sample is the largest one reported for this galaxy so far. For all the objects we present coordinates, instrumental [OIII]5007 magnitudes and apparent nebular [OIII]5007 fluxes and magnitudes. The [OIII]5007 observed luminosity function for PNe (PNLF) was calculated for the whole sample and for the central and outskirts samples. The three PNLF are similar within uncertainties. We fit the empirical PNLF to the observed PNLF for all the samples. From our best fit for the whole sample we derived a maximum value for the apparent magnitudes of m*(5007)=22.019\pm0.022 and we obtained a tentative estimate of the distance modulus m(5007)-M(5007)= 26.29 {+0.12} {-0.22} mag, which agrees well with the recent value derived from Cepheid stars., Comment: 8 pages, 3 figures, one long table. Accepted by A&A

We aim to derive the chemical behavior of a significant sample of PNe and HII regions in the irregular galaxy NGC 6822 The selected objects are distributed in different zones of the galaxy. Due to the faintness of PNe and HII regions in NGC 6822, to gather spectroscopic data with large telescopes is necessary. We obtained a well suited sample of spectra by employing VLT-FORS 2 and Gemini-GMOS spectrographs. Ionic and total abundances are calculated for the objects where electron temperatures can be determined through the detection of [OIII] \lambda 4363 or/and [NII] \lambda 5755 lines. A "simple" chemical evolution model has been developed and the observed data are used to compute a model for NGC 6822 in order to infer a preliminary chemical history in this galaxy. Confident determinations of He, O, N, Ne, S and Ar abundances were derived for a sample of 11 PNe and one HII region. We confirm that the present ISM is chemically homogeneous, at least in the central 2 kpc of the galaxy, showing a value 12+log O/H = 8.06$\pm$0.04. From the abundance pattern of PNe, we identified two populations: a group of young PNe with abundances similar to HII regions and a group of older objects with abundances a factor of two lower. A couple of extreme Type I PNe were found. No third dredge-up O enrichement was detected in PNe of this galaxy. The abundance determinations allow us to discuss the chemical behavior of the present and past ISM in NGC 6822. Our preliminary chemical evolution model predicts that an important gas-mass lost occurred during the first 5.3 Gyr, that no star higher than 40 M$_\odot$ was formed, and that 1% of all 3-15 M$_\odot$ stars became binary systems progenitors to SNIa., Comment: 15 pages, 3 figures and 4 tables. A&A, Accepted 13/06/2009