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Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on ~Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy-galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called S8 tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect--weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear., Comment: 20 pages, 10 figures, submitted to MNRAS

The intrinsic alignment of galaxies is a key factor in modeling weak-lensing observations and can serve as a valuable signal for both cosmological and astrophysical studies. Modelling this signal requires understanding how galaxy shapes form, and their relations to the large-scale gravitational field -- typically encoded in the value of large-scale shape-bias parameters. In this article we contribute to this topic in three ways: (i) developing new estimators of Lagrangian shape-biases (ii) applying them to measure the shape-biases of dark-matter halos (iii) interpreting these measurements to gain insight on the process of halo-shape formation. We show that our estimators produce results consistent with previous literature, and that they possess advantages with respect to previous methods, namely that the measurement of each bias parameter is completely independent from the others, and that bias parameters can be defined for each individual object. We measure universal relations between shape-bias parameters and peak-significance, $\nu$. This relation for the first-order shape-bias parameter is linear at high $\nu$, and converges to zero at low $\nu$, which we interpret as strong evidence against the proposed scenario according to which galaxy shapes arise due to post-formation interaction with the large-scale tidal-field. We anticipate our estimators to be very useful in analyzing hydrodynamical simulations to extract physical understandings of galaxy shape formation, as well as establishing priors on the values of intrinsic-alignment biases., Comment: Comments are welcome

We present a catalog of stellar parameters (effective temperature $T_{\rm eff}$, surface gravity $\log g$, age, and metallicity [Fe/H]) and elemental-abundance ratios ([C/Fe], [Mg/Fe], and [$\alpha$/Fe]) for some five million stars (4.5 million dwarfs and 0.5 million giants stars) in the Milky Way, based on stellar colors from the Javalambre Photometric Local Universe Survey (J-PLUS) DR3 and \textit{Gaia} EDR3. These estimates are obtained through the construction of a large spectroscopic training set with parameters and abundances adjusted to uniform scales, and trained with a Kernel Principal Component Analysis. Owing to the seven narrow/medium-band filters employed by J-PLUS, we obtain precisions in the abundance estimates that are as good or better than derived from medium-resolution spectroscopy for stars covering a wide range of the parameter space: 0.10-0.20 dex for [Fe/H] and [C/Fe], and 0.05 dex for [Mg/Fe] and [$\alpha$/Fe]. Moreover, systematic errors due to the influence of molecular carbon bands on previous photometric-metallicity estimates (which only included two narrow/medium-band blue filters) have now been removed, resulting in photometric-metallicity estimates down to [Fe/H] $\sim -4.0$, with typical uncertainties of 0.25 dex and 0.40 dex for dwarfs and giants, respectively. This large photometric sample should prove useful for the exploration of the assembly and chemical-evolution history of our Galaxy., Comment: 31 pages, 20 figures, 3 tables, accepeted by ApJ

Context. Mock galaxy catalogues are essential for correctly interpreting current and future generations of galaxy surveys. Despite their significance in galaxy formation and cosmology, little to no work has been done to validate the predictions of these mocks for high-order clustering statistics. Aims. We compare the predicting power of the latest generation of empirical models used in the creation of mock galaxy catalogues: a 13-parameter Halo Occupation Distribution (HOD) and an extension of the SubHalo Abundance Matching technique (SHAMe). Methods. We build GalaxyEmu-Planck, an emulator that makes precise predictions for the two-point correlation function, galaxy-galaxy lensing (restricted to distances greater than 1 $h^{-1} {\rm Mpc}$ to avoid baryonic effects), and other high-order statistics resulting from the evaluation of SHAMe and HOD models. Results. We evaluate the precision of GalaxyEmu-Planck using two galaxy samples extracted from the FLAMINGO hydrodynamical simulation that mimic the properties of DESI-BGS and BOSS galaxies, finding that the emulator reproduces all the predicted statistics precisely. The HOD showed comparable performance when fitting galaxy clustering and galaxy-galaxy lensing. In contrast, the SHAMe model showed better predictions for higher-order statistics, especially regarding the galaxy assembly bias. We also tested the performance of the models after removing some of their extensions, finding that we can withdraw two of the HOD parameters without a loss of performance. Conclusions. The results of this paper validate the current generation of empirical models as a way to reproduce galaxy clustering, galaxy-galaxy lensing and other high-order statistics. The excellent performance of the SHAMe model with a small number of free parameters suggests that it is a valid method to extract cosmological constraints from galaxy clustering., Comment: 22 pages, 12 figures, submitted to A&A. Comments welcomed!

We present a novel analysis of the redshift-space power spectrum of galaxies in the SDSS-III BOSS survey. Our methodology improves upon previous analyses by using a theoretical model based on cosmological simulations coupled with a perturbative description of the galaxy-matter connection and a phenomenological prescription of Fingers of God. This enables a very robust analysis down to mildly non-linear scales, $k\sim 0.4\,h\,{\rm Mpc}^{-1}$. We carried out a number of tests on mock data, different subsets of BOSS, and using model variations, all of which support the robustness of our analysis. Our results provide constraints on $\sigma_8$, $\Omega_m$, $h$, and $S_8 \equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$. Specifically, we measure $\Omega_m=0.301\pm 0.011$, $\sigma_8=0.745^{+0.028}_{-0.035}$, $h=0.705\pm 0.015$, and $ S_8 = 0.747^{+0.032}_{-0.039}$ when all the nuisance parameters of our model are left free. By adopting relationships among bias parameters measured in galaxy formation simulations, the value of $S_8$ remains consistent whereas uncertainties are reduced by $\sim20\%$. Our cosmological constraints are some of the strongest obtained with the BOSS power spectrum alone: they exhibit a $2.5-3.5\sigma$ tension with the results of the {\it Planck\/} satellite, agreeing with the lower values of $S_8$ derived from gravitational lensing. However, the cosmological model preferred by {\it Planck\/} is still a good fit to the BOSS data, assuming small departures from physical bias priors and, therefore, cannot be excluded at high significance. We conclude that, at the present, the BOSS data alone does not show strong evidence for a tension between the predictions of $\Lambda$CDM for the high- and low-redshift Universe., Comment: 17 pages, 12 figures

Baryonification algorithms model the impact of galaxy formation and feedback on the matter field in gravity-only simulations by adopting physically motivated parametric prescriptions. In this paper, we extend these models to describe gas temperature and pressure, allowing for a self-consistent modelling of the thermal Sunyaev-Zeldovich effect, weak gravitational lensing, and their cross-correlation, down to small scales. We validate our approach by showing that it can simultaneously reproduce the electron pressure, gas, stellar, and dark matter power spectra as measured in all BAHAMAS hydrodynamical simulations. Specifically, with only two additional free parameters, we can fit the electron pressure auto- and cross-power spectra at 10% while reproducing the suppression in the matter power spectrum induced by baryons at the per cent level, for different AGN feedback strengths in BAHAMAS. Furthermore, we reproduce BAHAMAS convergence and thermal Sunyaev Zeldovich angular power spectra within 1% and 10% accuracy, respectively, down to l = 5000. When used jointly with cosmological rescaling algorithms, the baryonification presented here will allow a fast and accurate exploration of cosmological and astrophysical scenarios. Therefore, it can be employed to create mock catalogues, lightcones, and large training sets for emulators aimed at interpreting forthcoming multi-wavelength observations of the large-scale structure of the Universe., Comment: 10 pages, 6 figures, to be submitted to A&A. Comments are welcome!

Understanding $\textit{galaxy bias}$ -- that is the statistical relation between matter and galaxies -- is of key importance for extracting cosmological information from galaxy surveys. While the bias function $f$ -- that is the probability of forming galaxy in a region with a given density field -- is usually approximated through a parametric expansion, we show here, that it can also be measured directly from simulations in a non-parameteric way. Our measurements show that the Lagrangian bias function is very close to a Gaussian for halo selections of any mass. Therefore, we newly introduce a Gaussian bias model with several intriguing properties: (1) It predicts only strictly positive probabilities $f > 0$ (unlike expansion models), (2) It has a simple analytic renormalized form and (3) It behaves gracefully in many scenarios where the classical expansion converges poorly. We show that the Gaussian bias model describes the galaxy environment distribution $p(\delta | \mathrm{g})$, the scale dependent bias function $f$ and the renormalized bias function $F$ of haloes and galaxies generally equally well or significantly better than a second order expansion with the same number of parameters. We suggest that a Gaussian bias approach may enhance the range of validity of bias schemes where the canonical expansion converges poorly and further, that it may make new applications possible, since it guarantees the positivity of predicted galaxy densities., Comment: 21 pages, 12 figures, submitted to A&A

The spatial distribution of galaxies is a highly complex phenomenon currently impossible to predict deterministically. However, by using a statistical $\textit{bias}$ relation, it becomes possible to robustly model the average abundance of galaxies as a function of the underlying matter density field. Understanding the properties and parametric description of the bias relation is key to extract cosmological information from future galaxy surveys. Here, we contribute to this topic primarily in two ways: (1) We develop a new set of probabilistic estimators for bias parameters using the moments of the Lagrangian galaxy environment distribution. These estimators include spatial corrections at different orders to measure bias parameters independently of the damping scale. We report robust measurements of a variety of bias parameters for haloes, including the tidal bias and its dependence with spin at a fixed mass. (2) We propose an alternative formulation of the bias expansion in terms of "cumulant bias parameters" that describe the response of the logarithmic galaxy density to large-scale perturbations. We find that cumulant biases of haloes are consistent with zero at orders $n > 2$. This suggests that: (i) previously reported bias relations at order $n > 2$ are an artefact of the entangled basis of the canonical bias expansion; (ii) the convergence of the bias expansion may be improved by phrasing it in terms of cumulants; (iii) the bias function is very well approximated by a Gaussian -- an avenue which we explore in a companion paper., Comment: 26 pages, 16 figures, submitted to A&A

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $\Lambda$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented., Comment: New submissions welcome! Challenge data available at https://github.com/ANSalcedo/Beyond2ptMock

We present a cosmological analysis of the combination of the DES-Y3, KiDS-1000 and HSC-DR1 weak lensing samples under a joint harmonic-space pipeline making use of angular scales down to $\ell_{\rm max}=4500$, corresponding to significantly smaller scales ($\delta\theta\sim2.4'$) than those commonly used in cosmological weak lensing studies. We are able to do so by accurately modelling non-linearities and the impact of baryonic effects using Baccoemu. We find $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}=0.795^{+0.015}_{-0.017}$, in relatively good agreement with CMB constraints from Planck (less than $\sim1.8\sigma$ tension), although we obtain a low value of $\Omega_{\rm m}=0.212^{+0.017}_{-0.032}$, in tension with Planck at the $\sim3\sigma$ level. We show that this can be recast as an $H_0$ tension if one parametrises the amplitude of fluctuations and matter abundance in terms of variables without hidden dependence on $H_0$. Furthermore, we find that this tension reduces significantly after including a prior on the distance-redshift relationship from BAO data, without worsening the fit. In terms of baryonic effects, we show that failing to model and marginalise over them on scales $\ell\lesssim2000$ does not significantly affect the posterior constraints for DES-Y3 and KiDS-1000, but has a mild effect on deeper samples, such as HSC-DR1. This is in agreement with our ability to only mildly constrain the parameters of the Baryon Correction Model with these data, Comment: v1: 57 pages, 24 figures, comments welcome. v2: accepted version in JCAP

We study the local environmental properties of 418 supernovae (SNe) of all types using data from the Javalambre Photometric Local Universe Survey (J-PLUS), which includes 5 broad- and 7 narrow-band imaging filters, using two independent analyses: 1) the Normalized Cumulative Rank (NCR) method, utilizing all 12 single bands along with five continuum-subtracted narrow-band emission and absorption bands, and 2) simple stellar population (SSP) synthesis, where we build spectral energy distributions (SED) of the surrounding SN environment using the 12 filters. Improvements over previous works include: (i) the extension of the NCR technique to other filters using a set of homogeneous data; (ii) a correction for extinction to all bands based on the relation between the g-i color and the color excess; and (iii) a correction for the [NII] line contamination that falls within the H$\alpha$ filter. All NCR distributions in the broad-band filters, tracing the overall light distribution in each galaxy, are similar to each other, being type Ia, II and IIb SNe are preferably located in redder environments than the other SN types. The radial distribution of the SNe shows that type IIb SNe seem to have a preference for occurring in the inner regions of galaxies. All core-collapse SN (CC) types are strongly correlated to the [OII] emission, which traces SFR. The NCR distributions of the Ca II triplet show a clear division between II/IIb/Ia and Ib/Ic/IIn subtypes, which is interpreted as a difference in the environmental metallicity. Regarding the SSP synthesis, we found that including the 7 J-PLUS narrow filters in the fitting process has a more significant effect for the CC SN environmental parameters than for SNe Ia, shifting their values towards more extinct, younger, and more star-forming environments, due to the presence of strong emission-lines and stellar absorptions in those narrow-bands., Comment: 18 pages, 12 figures, 8 tables. A&A accepted

Dark matter haloes form from small perturbations to the almost homogeneous density field of the early universe. Although it is known how large these initial perturbations must be to form haloes, it is rather poorly understood how to predict which particles will end up belonging to which halo. However, it is this process that determines the Lagrangian shape of protohaloes and is therefore essential to understand their mass, spin and formation history. Here, we present a machine-learning framework to learn how the protohalo regions of different haloes emerge from the initial density field. This involves one neural network to distinguish semantically which particles become part of any halo and a second neural network that groups these particles by halo membership into different instances. This instance segmentation is done through the Weinberger method, in which the network maps particles into a pseudo-space representation where different instances can be distinguished easily through a simple clustering algorithm. Our model reliably predicts the masses and Lagrangian shapes of haloes object-by-object, as well as summary statistics like the halo-mass function. We find that our model extracts information close to optimal by comparing it to the degree of agreement between two N-body simulations with slight differences in their initial conditions. We publish our model open-source and suggest that it can be used to inform analytical methods of structure formation by studying the effect of systematic manipulations of the initial conditions., Comment: 19 pages, 18 figures. Comments are welcome. Public code: https://github.com/daniellopezcano/instance_halos. Typos corrected, references added

The first generation of haloes forms from the collapse of the smallest peaks in the initial density field. $N$-body simulations of this process suggest a prompt formation of a steep power-law cusp, but these calculations are plagued by numerical artifacts which casts some doubt on this result. Here, we develop new simulation methods based on the dark matter phase-space sheet approach and present results which are entirely free of artificial clumps. We find that a cusp with density $\rho\propto r^{-1.5}$ is indeed formed promptly, subsequently accreting a more extended halo and participating in the hierarchical growth of later halo generations. However, our simulations also suggest that the presence of artificial clumps just before peak collapse can significantly shallow the inner profiles of the cusps. We use $N$-body simulations with controlled amounts of small-scale power to place a conservative upper limit on the scales affected by artificial clumps. Finally, we used these results to simulate the collapse of the first generation of peaks of various types and in different cosmologies, finding prompt cusps to form in all cases. We conclude that prompt cusps are a generic feature of the collapse of peaks on the free-streaming scale of the initial density field, and their structure can safely be studied using $N$-body simulations provided care is taken to excise the region potentially affected by artificial clumps., Comment: 20 pages, 18 figures

The intrinsic alignment of galaxies is an important ingredient for modelling weak-lensing measurements, and a potentially valuable cosmological and astrophysical signal. In this paper, we present HYMALAIA: a new model to predict the intrinsic alignments of biased tracers. HYMALAIA is based on a perturbative expansion of the statistics of the Lagrangian shapes of objects, which is then advected to Eulerian space using the fully non-linear displacement field obtained from $N$-body simulations. We demonstrate that HYMALAIA is capable of consistently describing monopole and quadrupole of halo shape-shape and matter-shape correlators, and that, without increasing the number of free parameters, it does so more accurately than other perturbatively inspired models such as the non-linear alignment (NLA) model and the tidal-alignment-tidal-torquing (TATT) model., Comment: 17 pages, 9 figures. Accepted version published in MNRAS

Recently, hybrid bias expansions have emerged as a powerful approach to modelling the way in which galaxies are distributed in the Universe. Similarly, field-level emulators have recently become possible thanks to advances in machine learning and $N$-body simulations. In this paper we explore whether both techniques can be combined to provide a field-level model for the clustering of galaxies in real and redshift space. Specifically, here we will demonstrate that field-level emulators are able to accurately predict all the operators of a $2^{\rm nd}$-order hybrid bias expansion. The precision achieved in real and redshift space is similar to that obtained for the nonlinear matter power spectrum. This translates to roughly 1-2\% precision for the power spectrum of a BOSS and a Euclid-like galaxy sample up to $k\sim 0.6 h^{-1}$Mpc. Remarkably, this combined approach also delivers precise predictions for field-level galaxy statistics. Despite all these promising results, we detect several areas where further improvements are required. Therefore, this work serves as a road-map for the developments required for a more complete exploitation of upcoming large-scale structure surveys., Comment: 15 pages, 9 figures

Several analyses have shown that LCDM-based models cannot jointly describe the clustering (GC) and galaxy-galaxy lensing (GGL) of galaxies in the SDSS-III BOSS survey, which is commonly known as the 'lensing-is-low problem'. In this work, we show that an extension of Subhalo Abundance Matching, dubbed SHAMe, successfully solves this problem. First, we show that this model accurately reproduces the GC and GGL of a mock galaxy sample in the TNG300 hydrodynamic simulation with analogous properties to BOSS galaxies. Then, we switch our attention to observed BOSS galaxies at z=0.31-0.43, and we attempt to reproduce their GC and GGL by evaluating SHAMe on two different simulations: one adopting best-fitting cosmological parameters from Planck and the other from weak gravitational lensing surveys (Low S8), where the amplitude of matter fluctuations is lower for the latter. We find excellent agreement between SHAMe predictions and observations for both cosmologies, indicating that the lensing-is-low problem originates from approximations in previous theoretical descriptions of the data. The main difference between SHAMe results in these cosmologies is the level of galaxy assembly bias, which is approximately 20 and 10% for Planck and Low S8, respectively. These results highlight the dangers of employing oversimplified models to analyse current large-scale structure datasets, and the need for realistic yet flexible descriptions of the galaxy-halo connection., Comment: 13 pages, 9 figures. Accepted by MNRAS

We present the first analysis of cosmic shear measured in DES Y3 that employs the entire range of angular scales in the data. To achieve this, we build upon recent advances in the theoretical modelling of weak lensing provided by a combination of $N$-body simulations, physical models of baryonic processes, and neural networks. Specifically, we use BACCOemu to model the linear and nonlinear matter power spectrum including baryonic physics, allowing us to robustly exploit scales smaller than those used by the DES Collaboration. We show that the additional data produce cosmological parameters that are tighter but consistent with those obtained from larger scales, while also constraining the distribution of baryons. In particular, we measure the mass scale at which haloes have lost half of their gas, $\log\,M_{\rm c}=14.38^{+0.60}_{-0.56}\log(h^{-1}{\rm M_{ \odot}})$, and a parameter that quantifies the weighted amplitudes of the present-day matter inhomogeneities, $S_8=0.799^{+0.023}_{-0.015}$. Our constraint on $S_8$ is statistically compatible with that inferred from the Planck satellite's data at the $0.9\sigma$ level. We find instead a $1.4\sigma$ shift in comparison to that from the official DES Y3 cosmic shear, because of different choices in the modelling of intrinsic alignment, non-linearities, baryons, and lensing shear ratios. We conclude that small scales in cosmic shear data contain valuable astrophysical and cosmological information and thus should be included in standard analyses., Comment: Accepted for publication on A&A

Prompt cusps are the densest quasi-equilibrium dark matter objects; one forms at the instant of collapse within every isolated peak of the initial cosmological density field. They have power-law density profiles, $\rho \propto r^{-1.5}$ with central phase-space density set by the primordial velocity dispersion of the dark matter. At late times they account for $\sim 1\%$ of the dark matter mass but for $>90\%$ of its annihilation luminosity in all but the densest regions, where they are tidally disrupted. Here we demonstrate that individual stellar encounters, rather than the mean galactic tide, are the dominant disruptors of prompt cusps within galaxies. Their cumulative effect is fully (though stochastically) characterised by an impulsive shock strength $B_* = 2\pi G\int\rho_*({\bf x}(t))\, \mathrm{d}t$ where $\rho_*$, the total mass density in stars, is integrated over a cusp's entire post-formation trajectory. Stellar encounters and mean tides have only a small effect on the halo annihilation luminosity seen by distant observers, but this is not true for the Galactic halo because of the Sun's position. For a 100 GeV WIMP, Earth-mass prompt cusps are predicted, and stellar encounters suppress their mean annihilation luminosity by a factor of two already at 20 kpc, so that their annihilation emission is predicted to appear almost uniform over the sky. The Galactic Center $\gamma$-ray Excess is thus unaffected by cusps. If it is indeed dark matter annihilation radiation, then prompt cusps in the outer Galactic halo and beyond must account for 20-80% of the observed isotropic $\gamma$-ray background in the 1 to 10 GeV range., Comment: 22 pages, 23 figures, for a video and code see https://github.com/jstuecker/cusp-encounters

The spatial distribution of galaxies and their gravitational lensing signal offer complementary tests of galaxy formation physics and cosmology. However, their synergy can only be fully exploited if both probes are modelled accurately and consistently. In this paper, we demonstrate that this can be achieved using an extension of Subhalo Abundance Matching, dubbed SHAMe. Specifically, we use mock catalogues built from the TNG300 hydrodynamical simulation to show that SHAMe can simultaneously model the multipoles of the redshift-space galaxy correlation function and galaxy-galaxy lensing, without noticeable bias within the statistical sampling uncertainties of a SDSS volume and on scales r = [0.6-30] Mpc/h. Modelling the baryonic processes in galaxy-galaxy lensing with a baryonification scheme allows SHAMe's range of validity to be extended to r = [0.1-30] Mpc/h. Remarkably, our model achieves this level of precision with just five free parameters beyond those describing the baryonification model. At fixed cosmology, we find that galaxy-galaxy lensing provides a general consistency test but little additional information on galaxy modelling parameters beyond that encoded in the redshift-space multipoles. It does, however, improve constraints if only the projected correlation function is available, as in surveys with only photometric redshifts. We expect SHAMe to have a higher fidelity across a wider range of scales than more traditional methods such as Halo Occupation Distribution modelling. Thus it should provide a significantly more powerful and more robust tool for analysing next-generation large-scale surveys., Comment: 14 pages, 7 figures. Accepted by MNRAS

Recent analyses show that $\Lambda$CDM-based models optimised to reproduce the clustering of massive galaxies overestimate their gravitational lensing by about 30\%, the so-called lensing is low problem. Using a state-of-the-art hydrodynamical simulation, we show that this discrepancy reflects shortcomings in standard galaxy-halo connection models rather than tensions within the $\Lambda$CDM paradigm itself. Specifically, this problem results from ignoring a variety of galaxy formation effects, including assembly bias, segregation of satellite galaxies relative to dark matter, and baryonic effects on the matter distribution. All these effects contribute towards overestimating gravitational lensing and, when combined, explain the amplitude and scale dependence of the lensing is low problem. We conclude that simplistic galaxy-halo connection models are inadequate to interpret clustering and lensing simultaneously, and that it is crucial to employ more sophisticated models for the upcoming generation of large-scale surveys., Comment: 16 pages, 12 figures, accepted by MNRAS

We introduce a novel technique for constraining cosmological parameters and galaxy assembly bias using non-linear redshift-space clustering of galaxies. We scale cosmological N-body simulations and insert galaxies with the SubHalo Abundance Matching extended (SHAMe) empirical model to generate over 175,000 clustering measurements spanning all relevant cosmological and SHAMe parameter values. We then build an emulator capable of reproducing the projected galaxy correlation function at the monopole, quadrupole and hexadecapole level for separations between $0.1\,h^{-1}{\rm Mpc}$ and $25\,h^{-1}{\rm Mpc}$. We test this approach by using the emulator and Monte Carlo Markov Chain (MCMC) inference to jointly estimate cosmology and assembly bias parameters both for the MTNG740 hydrodynamic simulation and for a semi-analytical galaxy formation model (SAM) built on the MTNG740-DM dark matter-only simulation, obtaining unbiased results for all cosmological parameters. For instance, for MTNG740 and a galaxy number density of $n\sim 0.01 h^{3}{\rm Mpc}^{-3}$, we obtain $\sigma_{8}=0.799^{+0.039}_{-0.044}$ ($\sigma_{8,{\rm MTNG}} =$ 0.8159), and $\Omega_\mathrm{M}h^2= 0.138^{+ 0.025}_{- 0.018}$ ($\Omega_{\mathrm{M}} h^2_{\rm MTNG} =$ 0.142). For fixed Hubble parameter ($h$), the constraint becomes $\Omega_\mathrm{M}h^2= 0.137^{+ 0.011}_{- 0.012}$. Our method performs similarly well for the SAM and for other tested sample densities. We almost always recover the true amount of galaxy assembly bias within one sigma. The best constraints are obtained when scales smaller than $2\,h^{-1}{\rm Mpc}$ are included, as well as when at least the projected correlation function and the monopole are incorporated. These methods offer a powerful way to constrain cosmological parameters using galaxy surveys., Comment: 18 pages, 12 figures, accepted by MNRAS

Current best limits on the 21-cm signal during reionization are provided at large scales ($\gtrsim$100 Mpc). To model these scales, enormous simulation volumes are required which are computationally expensive. We find that the primary source of uncertainty at these large scales is sample variance, which decides the minimum size of simulations required to analyse current and upcoming observations. In large-scale structure simulations, the method of `fixing' the initial conditions (ICs) to exactly follow the initial power spectrum and `pairing' two simulations with exactly out-of-phase ICs has been shown to significantly reduce sample variance. Here we apply this `fixing and pairing' (F\&P) approach to reionization simulations whose clustering signal originates from both density fluctuations and reionization bubbles. Using a semi-numerical code, we show that with the traditional method, simulation boxes of $L\simeq 500$ (300) Mpc are required to model the large-scale clustering signal at $k$=0.1 Mpc$^{-1}$ with a precision of 5 (10) per cent. Using F\&P, the simulation boxes can be reduced by a factor of 2 to obtain the same precision level. We conclude that the computing costs can be reduced by at least a factor of 4 when using the F\&P approach., Comment: 5 pages, 4 figures, accepted for publication in A&A

The concentrations of dark matter haloes provide crucial information about their internal structure and how it depends on mass and redshift -- the so-called concentration-mass-redshift relation, denoted $c(M,z)$. We present here an extensive study of the cosmology-dependence of $c(M,z)$ that is based on a suite of 72 gravity-only, full N-body simulations in which the following cosmological parameters were varied: $\sigma_{8}$, $\Omega_{\mathrm{M}}$, $\Omega_{\mathrm{b}}$, $n_{\mathrm{s}}$, $h$, $M_{\nu}$, $w_{0}$ and $w_{\mathrm{a}}$. We characterize the impact of these parameters on concentrations for different halo masses and redshifts. In agreement with previous works, and for all cosmologies studied, we find that there exists a tight correlation between the characteristic densities of dark matter haloes within their scale radii, $r_{-2}$, and the critical density of the Universe at a suitably defined formation time. This finding, when combined with excursion set modelling of halo formation histories, allows us to accurately predict the concentrations of dark matter haloes as a function of mass, redshift, and cosmology. We use our simulations to test the reliability of a number of published models for predicting halo concentration and highlight when they succeed or fail to reproduce the cosmological $c(M,z)$ relation., Comment: 11 pages, 9 figures

In this work, we carry out a suite of specially-designed numerical simulations to shed further light on dark matter (DM) subhalo survival at mass scales relevant for gamma-ray DM searches, a topic subject to intense debate nowadays. Specifically, we have developed and employed an improved version of DASH, a GPU $N$-body code, to study the evolution of low-mass subhaloes inside a Milky Way-like halo with unprecedented accuracy, reaching solar-mass and sub-parsec resolution in our simulations. We simulate subhaloes with varying mass, concentration, and orbital properties, and consider the effect of the gravitational potential of the Milky Way galaxy itself. More specifically, we analyze the evolution of both the bound mass fraction and annihilation luminosity of subhaloes, finding that most subhaloes survive until present time, even though in some cases they lose more than 99% of their mass at accretion. Baryons in the host induce a much more severe mass loss, especially when the subhalo orbit is more parallel to the galactic disk. Many of these subhaloes cross the solar galactocentric radius, thus making it easier to detect their annihilation fluxes from Earth. We find subhaloes orbiting a DM-only halo with a pericentre in the solar vicinity to lose 70-90% of their initial annihilation luminosity at redshift zero, which increases up to 99% when baryons are also included in the host. We find a strong relation between subhalo's mass loss and the effective tidal field at pericentre. Indeed, much of the dependence on concentration, orbital parameters, host potential and baryonic components can be explained through this single parameter. In addition to shedding light on the survival of low-mass galactic subhaloes, our results can provide detailed predictions that will aid current and future quests for the nature of DM., Comment: 19 pages, 16 figures. Submitted to MNRAS, comments welcome!

We present an emulator that accurately predicts the power spectrum of galaxies in redshift space as a function of cosmological parameters. Our emulator is based on a 2nd-order Lagrangian bias expansion that is displaced to Eulerian space using cosmological $N$-body simulations. Redshift space distortions are then imprinted using the non-linear velocity field of simulated particles and haloes. We build the emulator using a forward neural network trained with the simulations of the BACCO project, which covers an 8-dimensional parameter space including massive neutrinos and dynamical dark energy. We show that our emulator provides unbiased cosmological constraints from the monopole, quadrupole, and hexadecapole of a mock galaxy catalogue that mimics the BOSS-CMASS sample down to nonlinear scales ($k\sim0.6$[$h/$Mpc]$^{3}$). This work opens up the possibility of robustly extracting cosmological information from small scales using observations of the large-scale structure of the Universe., Comment: 16 pages, 9 figures

We present a model for the remnants of haloes that have gone through an adiabatic tidal stripping process. We show that this model exactly reproduces the remnant of an NFW halo that is exposed to a slowly increasing isotropic tidal field and approximately for an anisotropic tidal field. The model can be used to predict the asymptotic mass loss limit for orbiting subhaloes, solely as a function of the initial structure of the subhalo and the value of the tidal field at pericentre. Predictions can easily be made for differently concentrated host-haloes with and without baryonic components, which differ most notably in their relation between pericentre radius and tidal field. The model correctly predicts several empirically measured relations such as the `tidal track' and the `orbital frequency relation' that was reported by Errani & Navarro (2021) for the case of an isothermal sphere. Further, we propose applications of the `structure-tide' degeneracy which implies that increasing the concentration of a subhalo has exactly the same impact on tidal stripping as reducing the amplitude of the tidal field. Beyond this, we find that simple relations hold for the bound mass, truncation radius, WIMP annihilation luminosity and tidal ratio of tidally stripped NFW haloes in relation to quantities measured at the radius of maximum circular velocity. Finally, we note that NFW haloes cannot be completely disrupted when exposed adiabatically to tidal fields of arbitrary magnitudes. We provide an open-source implementation of our model and suggest that it can be used to improve predictions of dark matter annihilation., Comment: 31 pages, 19 figures, submitted to MNRAS, comments welcome, code publicly available under https://github.com/jstuecker/adiabatic-tides

Cosmological simulations play an increasingly important role in analysing the observed large-scale structure of the Universe. Recently, they have been particularly important in building hybrid models that combine a perturbative bias expansion with displacement fields extracted from N-body simulations to describe the clustering of biased tracers. Here, we show that simulations that employ a technique referred to as "Fixing-and-pairing" (F&P) can dramatically improve the statistical precision of such hybrid models. Specifically, by numerical and analytic means, we show that F&P simulations provide unbiased estimates for all statistics employed by hybrid models while reducing, by up to two orders of magnitude, their uncertainty on large scales. This roughly implies that an EUCLID-like survey could be analysed using simulations of 2Gpc a side -- a 20% of the survey volume. Our work establishes the robustness of F&P for current hybrid theoretical models for galaxy clustering, an important step towards achieving an optimal exploitation of large-scale structure measurements., Comment: 23 pages, 8 figures

Globular clusters (GCs) are proxies of the formation assemblies of their host galaxies. However, few studies exist targeting GC systems of spiral galaxies up to several effective radii. Through 12-band Javalambre Photometric Local Universe Survey (J-PLUS) imaging, we study the point sources around the M81/M82/NGC3077 triplet in search of new GC candidates. We develop a tailored classification scheme to search for GC candidates based on their similarity to known GCs via a principal components analysis (PCA) projection. Our method accounts for missing data and photometric errors. We report 642 new GC candidates in a region of 3.5 deg$^2$ around the triplet, ranked according to their Gaia astrometric proper motions when available. We find tantalising evidence for an overdensity of GC candidate sources forming a bridge connecting M81 and M82. Finally, the spatial distribution of the GC candidates $(g-i)$ colours is consistent with halo/intra-cluster GCs, i.e. it gets bluer as they get further from the closest galaxy in the field. We further employ a regression-tree based model to estimate the metallicity distribution of the GC candidates based on their J-PLUS bands. The metallicity distribution of the sample candidates is broad and displays a bump towards the metal-rich end. Our list increases the population of GC candidates around the triplet by 3-fold, stresses the usefulness of multi-band surveys in finding these objects, and provides a testbed for further studies analysing their spatial distribution around nearby (spirals) galaxies., Comment: 20 pages, 18 figures, MNRAS accepted

Context. The Javalambre Photometric Local Universe Survey (J-PLUS) has obtained precise photometry in twelve specially designed filters for large numbers of Galactic stars. Deriving their precise stellar atmospheric parameters and individual elemental abundances is crucial for studies of Galactic structure, and the assembly history and chemical evolution of our Galaxy. Aims. Our goal is to estimate not only stellar parameters (effective temperature, Teff, surface gravity, log g, and metallicity, [Fe/H]), but also [{\alpha}/Fe] and four elemental abundances ([C/Fe], [N/Fe], [Mg/Fe], and [Ca/Fe]) using data from J-PLUS DR1. Methods. By combining recalibrated photometric data from J-PLUS DR1, Gaia DR2, and spectroscopic labels from LAMOST, we design and train a set of cost-sensitive neural networks, the CSNet, to learn the non-linear mapping from stellar colors to their labels. Results. We have achieved precisions of {\delta}Teff {\sim}55K, {\delta}logg{\sim}0.15dex, and {\delta}[Fe/H]{\sim}0.07dex, respectively, over a wide range of temperature, surface gravity, and metallicity. The uncertainties of the abundance estimates for [{\alpha}/Fe] and the four individual elements are in the range 0.04-0.08 dex. We compare our parameter and abundance estimates with those from other spectroscopic catalogs such as APOGEE and GALAH, and find an overall good agreement. Conclusions. Our results demonstrate the potential of well-designed, high-quality photometric data for determinations of stellar parameters as well as individual elemental abundances. Applying the method to J-PLUS DR1, we have obtained the aforementioned parameters for about two million stars, providing an outstanding data set for chemo-dynamic analyses of the Milky Way. The catalog of the estimated parameters is publicly accessible., Comment: 30 pages, 26 figures, 3 tables, accepted by A&A

We review the field of collisionless numerical simulations for the large-scale structure of the Universe. We start by providing the main set of equations solved by these simulations and their connection with General Relativity. We then recap the relevant numerical approaches: discretization of the phase-space distribution (focusing on N-body but including alternatives, e.g., Lagrangian submanifold and Schr\"odinger-Poisson) and the respective techniques for their time evolution and force calculation (Direct summation, mesh techniques, and hierarchical tree methods). We pay attention to the creation of initial conditions and the connection with Lagrangian Perturbation Theory. We then discuss the possible alternatives in terms of the micro-physical properties of dark matter (e.g., neutralinos, warm dark matter, QCD axions, Bose-Einstein condensates, and primordial black holes), and extensions to account for multiple fluids (baryons and neutrinos), primordial non-Gaussianity and modified gravity. We continue by discussing challenges involved in achieving highly accurate predictions. A key aspect of cosmological simulations is the connection to cosmological observables, we discuss various techniques in this regard: structure finding, galaxy formation and baryonic modelling, the creation of emulators and light-cones, and the role of machine learning. We finalise with a recount of state-of-the-art large-scale simulations and conclude with an outlook for the next decade., Comment: 171 pages, 30 figures, 1018 references. Review article (in press) for 'Living Reviews in Computational Astrophysics'. The article will be updated regularly, thus, comments and suggestions will be very welcome

We study the relations among the parameters of the hybrid Lagrangian bias expansion model, fitting biased auto and cross power spectra up to $k_{\rm max} = 0.7 \, h \, \mathrm{Mpc}^{-1}$. We consider $\sim 8000$ halo and galaxy samples, with different halo masses, redshifts, galaxy number densities, and varying the parameters of the galaxy formation model. Galaxy samples are obtained through state-of-the-art extended subhalo abundance matching techniques and include both stellar-mass and star-formation-rate selected galaxies. All of these synthetic galaxies samples are publicly available at https://bacco.dipc.org/galpk.html. We find that the hybrid Lagrangian bias model provides accurate fits to all of our halo and galaxy samples. The coevolution relations between galaxy bias parameters, although roughly compatible with those obtained for haloes, show systematic shifts and larger scatter. We explore possible sources of this difference in terms of dependence on halo occupation and assembly bias of each sample. The bias parameter relations displayed in this work can be used as a prior for future Bayesian analyses employing the hybrid Lagrangian bias expansion model., Comment: 14 pages, 12 figures, galaxy power spectra available at https://bacco.dipc.org/galpk.html

Extragalactic globular clusters (GCs) are key objects for studying the history of galaxies. The arrival of wide-field surveys such as the Javalambre Photometric Local Universe Survey (J-PLUS) offers new possibilities for the study of these systems. We perform the first study of GCs in J-PLUS to recover information about the history of NGC 1023 taking advantage of wide-field images and 12 filters. We develop the semiautomatic pipeline GCFinder that detects GC candidates in J-PLUS images and can also be adapted to similar surveys. We study the stellar population properties of a sub-sample of GC candidates using spectral energy distribution (SED) fitting. We find 523 GC candidates in NGC 1023, of which $\sim$300 are new. We identify subpopulations of GC candidates, where age and metallicity distributions have multiple peaks. By comparing our results with simulations, we report a possible broad age-metallicity relation, evidence that NGC 1023 experienced accretion events in the past. The dominating age peak is at $10^{10}$ yr. We report a correlation between masses and ages that suggests that massive GC candidates are more likely to survive the turbulent history of the host galaxy. Modeling the light of NGC 1023, we find two spiral-like arms and detect a displacement of the galaxy's photometric center with respect to the outer isophotes and center of GC distribution ($\sim$700 pc and $\sim$1600 pc, respectively), which could be the result of ongoing interaction between NGC 1023 and NGC 1023A. By studying the GC system of NGC 1023 with J-PLUS we showcase the power of multi-band surveys for this kind of study and find evidence of a complex accretion history of the host galaxy., Comment: Published in A&A, 2022

We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1<[Fe/H]<+0.5$. The performance of the pipeline has been tested with a sample of stars observed by the LAMOST survey within the same parameter range. The average differences between the parameters of a sample of stars observed with SEGUE and J-PLUS, which were obtained with the SEGUE Stellar Parameter Pipeline and SPEEM, respectively, are $\Delta Teff\sim 41$ K, $\Delta \log g\sim 0.11$ dex, and $\Delta [Fe/H]\sim 0.09$ dex. A sample of 177 stars have been identified as new candidates with $[Fe/H]<-2.5$ and 11 of them have been observed with the ISIS spectrograph at the William Herschel Telescope. The spectroscopic analysis confirms that $64\%$ of stars have $[Fe/H]<-2.5$, including one new star with $[Fe/H]<-3.0$. SPEEM in combination with the J-PLUS filter system has shown the potential to estimate the stellar atmospheric parameters (Teff, $\log g$, and [Fe/H]). The spectroscopic validation of the candidates shows that SPEEM yields a success rate of $64\%$ on the identification of very metal-poor star candidates with $[Fe/H]<-2.5$., Comment: Accepted for publication in the Astronomy & Astrophysics Journal

We present "sheet+release" simulations that reliably follow the evolution of dark matter structure at and below the dark matter free-streaming scale, where instabilities in traditional N-body simulations create a large population of spurious artificial haloes. Our simulations sample a large range of power-spectrum cutoff functions, parameterized through the half-mode scale $k_{\rm{hm}}$ and a slope parameter $\beta$. This parameter space can represent many non-cold dark matter models, including thermal relic warm dark matter, sterile-neutrinos, fuzzy dark matter, and a significant fraction of ETHOS models. Combining these simulations with additional N-body simulations, we find the following results. (1) Even after eliminating spurious haloes, the halo mass function in the strongly suppressed regime ($n_{\rm{X}}/n_{\rm{CDM}} < 5\%$) remains uncertain because it depends strongly on the definition of a halo. At these mass scales traditional halo finders primarily identify overdensities that are unbound, highly elongated, dominated by tidal fields, or far from virialized. (2) The regime where the suppression is smaller than a factor of 20 is quite robust to these uncertainties, however, and can be inferred reliably from suitable N-body simulations. (3) Parameterizing the suppression in the halo- and subhalo mass functions through the scales where the suppression reaches $20\%$, $50\%$ and $80\%$, we provide simple formulae which enable predictions for many non-cold dark matter models. (4) The halo mass-concentration relations in our sheet+release simulations agree well with previous results based on N-body simulations. (5) In general, we confirm the validity of previous N-body studies of warm dark matter models, largely eliminating concerns about the effects of artificial haloes., Comment: 17 pages, 15 figures, submitted to MNRAS, for extra material see https://bacco.dipc.org/ncdm.html

Improving the theoretical description of galaxy clustering on small scales is an important challenge in cosmology, as it can considerably increase the scientific return of forthcoming galaxy surveys -- e.g. tightening the bounds on neutrino masses and deviations from general relativity. In this paper, we propose and test a new model for the clustering of galaxies that is able to accurately describe redshift-space distortions even down to small scales. This model corresponds to a second-order perturbative Lagrangian bias expansion which is advected to Eulerian space employing a displacement field extracted from $N$-body simulations. Eulerian coordinates are then transformed into redshift space by directly employing simulated velocity fields augmented with nuisance parameters capturing various possible satellite fractions and intra-halo small-scale velocities. We quantify the accuracy of our approach against samples of physically-motivated mock galaxies selected according to either Stellar Mass (SM) or Star Formation Rate (SFR) at multiple abundances and at $z=0$ and $1$. We find our model describes the monopole, quadrupole, and hexadecapole of the galaxy-power spectra down to scales of $k\approx 0.6 [h/$Mpc] within the accuracy of our simulations. This approach could pave the way to significantly increase the amount of cosmological information to be extracted from future galaxy surveys., Comment: 15 pages, 8 figures

The global gravitational potential, $\phi$, is not commonly employed in the analysis of cosmological simulations, since its level sets do not show any clear correspondence to the underlying density field and its persistent structures. Here, we show that the potential becomes a locally meaningful quantity when considered from a boosted frame of reference, defined by subtracting a uniform gradient term $\phi_{\rm{boost}}(\boldsymbol{x}) = \phi(\boldsymbol{x}) + \boldsymbol{x} \cdot \boldsymbol{a}_0$ with acceleration $\boldsymbol{a}_0$. We study this "boosted potential" in a variety of scenarios and propose several applications: (1) The boosted potential can be used to define a binding criterion that naturally incorporates the effect of tidal fields. This solves several problems of commonly-used self-potential binding checks: i) it defines a tidal boundary for each halo, ii) it is much less likely to misidentify caustics as haloes (specially in the context of warm dark matter cosmologies), and iii) performs better at identifying virialized regions of haloes -- yielding to the expected value of 2 for the virial ratio. (2) This binding check can be generalized to filaments and other cosmic structures. (3) The boosted potential facilitates the understanding of the disruption of satellite subhaloes. We propose a picture where most mass loss is explained through a lowering of the escape energy through the tidal field. (4) We discuss the possibility of understanding the topology of the potential field in a way that is independent of constant offsets in the first derivative $\boldsymbol{a}_0$. We foresee that this novel perspective on the potential can help to develop more accurate models and improve our understanding of structure formation., Comment: 22 pages, 14 figures. Submitted to MNRAS. Comments welcome!

This is the second part of a thorough investigation of the redshift-space effects that affect void properties and the impact they have on cosmological tests. Here, we focus on the void-galaxy cross-correlation function, specifically, on the projected versions that we developed in a previous work. The pillar of the analysis is the one-to-one relationship between real and redshift-space voids above the shot-noise level identified with a spherical void finder. Under this mapping, void properties are affected by three effects: (i) a systematic expansion as a consequence of the distortions induced by galaxy dynamics, (ii) the Alcock-Paczynski volume effect, which manifests as an overall expansion or contraction depending on the fiducial cosmology, and (iii) a systematic off-centring along the line of sight as a consequence of the distortions induced by void dynamics. We found that correlations are also affected by an additional source of distortions: the ellipticity of voids. This is the first time that distortions due to the off-centring and ellipticity effects are detected and quantified. With a simplified test, we verified that the Gaussian streaming model is still robust provided all these effects are taken into account, laying the foundations for improvements in current models in order to obtain unbiased cosmological constraints from spectroscopic surveys. Besides this practical importance, this analysis also encodes key information about the structure and dynamics of the Universe at the largest scales. Furthermore, some of the effects constitute cosmological probes by themselves, as is the case of the void ellipticity., Comment: 14 pages, 9 figures, published in MNRAS, accepted after minor comments

Context: The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 ultraviolet-visible filters (0.3-1 {\mu}m) of approximately 8 500 deg{^2} of the sky observable from Javalambre (Teruel, Spain). Due to its characteristics and strategy of observation, this survey will let us analyze a great number of Solar System small bodies, with improved spectrophotometric resolution with respect to previous large-area photometric surveys in optical wavelengths. Aims: The main goal of this work is to present here the first catalog of magnitudes and colors of minor bodies of the Solar System compiled using the first data release (DR1) of the J-PLUS observational campaign: the Moving Objects Observed from Javalambre (MOOJa) catalog. Methods: Using the compiled photometric data we obtained very-low-resolution reflectance (photospectra) spectra of the asteroids. We first used a {\sigma}-clipping algorithm in order to remove outliers and clean the data. We then devised a method to select the optimal solar colors in the J-PLUS photometric system. These solar colors were computed using two different approaches: on one hand, we used different spectra of the Sun, convolved with the filter transmissions of the J-PLUS system, and on the other, we selected a group of solar-type stars in the J-PLUS DR1, according to their computed stellar parameters. Finally, we used the solar colors to obtain the reflectance spectra of the asteroids. Results: We present photometric data in the J-PLUS filters for a total of 3 122 minor bodies (3 666 before outlier removal), and we discuss the main issues of the data, as well as some guidelines to solve them

One of the main predictions of excursion set theory is that the clustering of dark matter haloes only depends on halo mass. However, it has been long established that the clustering of haloes also depends on other properties, including formation time, concentration, and spin; this effect is commonly known as halo assembly bias. We use a suite of gravity-only simulations to study the dependence of halo assembly bias on cosmology; these simulations cover cosmological parameters spanning 10$\sigma$ around state-of-the-art best-fitting values, including standard extensions of the $\Lambda$CDM paradigm such as neutrino mass and dynamical dark energy. We find that the strength of halo assembly bias presents variations smaller than 0.05 dex across all cosmologies studied for concentration and spin selected haloes, letting us conclude that the dependence of halo assembly bias upon cosmology is negligible. We then study the dependence of galaxy assembly bias (i.e. the manifestation of halo assembly bias in galaxy clustering) on cosmology using subhalo abundance matching. We find that galaxy assembly bias also presents very small dependence upon cosmology ($\sim$ 2$\%$-4$\%$ of the total clustering); on the other hand, we find that the dependence of this signal on the galaxy formation parameters of our galaxy model is much stronger. Taken together, these results let us conclude that the dependence of halo and galaxy assembly bias on cosmology is practically negligible., Comment: 11 pages, 8 figures. Submitted to MNRAS, comments welcome

The linear matter power spectrum is an essential ingredient in all theoretical models for interpreting large-scale-structure observables. Although Boltzmann codes such as CLASS or CAMB are very efficient at computing the linear spectrum, the analysis of data usually requires $10^4$-$10^6$ evaluations, which means this task can be the most computationally expensive aspect of data analysis. Here, we address this problem by building a neural network emulator that provides the linear theory (total and cold) matter power spectrum in about one millisecond with 0.2% (0.5%) accuracy over redshifts $z \le 3$ ($z \le 9$), and scales $10^{-4} \le k \, [h {\rm Mpc^{-1}}] < 50$. We train this emulator with more than 200,000 measurements, spanning a broad cosmological parameter space that includes massive neutrinos and dynamical dark energy. We show that the parameter range and accuracy of our emulator is enough to get unbiased cosmological constraints in the analysis of a Euclid-like weak lensing survey. Complementing this emulator, we train 15 other emulators for the cross-spectra of various linear fields in Eulerian space, as predicted by 2nd-order Lagrangian Perturbation theory, which can be used to accelerate perturbative bias descriptions of galaxy clustering. Our emulators are specially designed to be used in combination with emulators for the nonlinear matter power spectrum and for baryonic effects, all of which are publicly available at http://www.dipc.org/bacco., Comment: 15 pages, 7 figures. Published in Open Research Europe

The abundance of dark matter haloes is one of the key probes of the growth of structure and expansion history of the Universe. Theoretical predictions for this quantity usually assume that, when expressed in a certain form, it depends only on the mass variance of the linear density field. However, cosmological simulations have revealed that this assumption breaks, leading to 10-20% systematic effects. In this paper we employ a specially-designed suite of simulations to further investigate this problem. Specifically, we carry out cosmological N-body simulations where we systematically vary growth history at a fixed linear density field, or vary the power spectrum shape at a fixed growth history. We show that the halo mass function generically depends on these quantities, thus showing a clear signal of non-universality. Most of this effect can be traced back to the way in which the same linear fluctuation grows differently into the nonlinear regime depending on details of its assembly history. With these results, we propose a parameterization with explicit dependence on the linear growth rate and power spectrum shape. Using an independent suite of simulations, we show that this fitting function accurately captures the mass function of haloes over cosmologies spanning a vast parameter space, including massive neutrinos and dynamical dark energy. Finally, we employ this tool to improve the accuracy of so-called cosmology-rescaling methods and show they can deliver 2% accurate predictions for the halo mass function over the whole range of currently viable cosmologies.

We present an emulator for the two-point clustering of biased tracers in real space. We construct this emulator using neural networks calibrated with more than $400$ cosmological models in a 8-dimensional cosmological parameter space that includes massive neutrinos an dynamical dark energy. The properties of biased tracers are described via a Lagrangian perturbative bias expansion which is advected to Eulerian space using the displacement field of numerical simulations. The cosmology-dependence is captured thanks to a cosmology-rescaling algorithm. We show that our emulator is capable of describing the power spectrum of galaxy formation simulations for a sample mimicking that of a typical Emission-Line survey at $z \sim 1$ with an accuracy of $1-2\%$ up to nonlinear scales $k \sim 0.7 h \mathrm{Mpc}^{-1}$., Comment: 14 pages, 8 figures

We present a neural-network emulator for baryonic effects in the non-linear matter power spectrum. We calibrate this emulator using more than 50,000 measurements in a 15-dimensional parameters space, varying cosmology and baryonic physics. Baryonic physics is described through a baryonification algorithm, that has been shown to accurately capture the relevant effects on the power spectrum and bispectrum in state-of-the-art hydrodynamical simulations. Cosmological parameters are sampled using a cosmology-rescaling approach including massive neutrinos and dynamical dark energy. The specific quantity we emulate is the ratio between matter power spectrum with baryons and gravity-only, and we estimate the overall precision of the emulator to be 1-2%, at all scales 0.01 < k < 5 h/Mpc, and redshifts 0 < z < 1.5. We also obtain an accuracy of 1-2%, when testing the emulator against a collection of 74 different cosmological hydrodynamical simulations and their respective gravity-only counterparts. We show also that only one baryonic parameter, namely Mc, which set the gas fraction retained per halo mass, is enough to have accurate and realistic predictions of the baryonic feedback at a given epoch. Our emulator will become publicly available in http://www.dipc.org/bacco., Comment: 13 pages, 11 figures. Comments are welcome

Baryons and cold dark matter (CDM) did not comove prior to recombination. This leads to differences in the local baryon and CDM densities, the so-called baryon-CDM isocurvature perturbations $\delta_{bc}$. These perturbations are usually neglected in the analysis of Large-Scale Structure data but taking them into account might become important in the era of high precision cosmology. Using gravity-only 2-fluid simulations we assess the impact of such perturbations on the dark matter halos distribution. In particular, we focus on the baryon fraction in halos as a function of mass and large-scale $\delta_{bc}$, which also allows us to study details of the nontrivial numerical setup required for such simulations. We further measure the cross-power spectrum between the halo field and $\delta_{bc}$ over a wide range of mass. This cross-correlation is nonzero and negative which shows that halo formation is impacted by $\delta_{bc}$. We measure the associated bias parameter $b_{\delta_{bc}}$ and compare it to recent results, finding good agreement. Finally we quantify the impact of such perturbations on the halo-halo power spectrum and show that this effect can be degenerate with the one of massive neutrinos for surveys like DESI., Comment: 27 pages, 11 figures, Version published in JCAP

In this work, we combine size and stellar mass measurements from the Sloan Digital Sky Server (SDSS) with the group finder algorithm of Rodriguez \& Merch\'an in order to determine the stellar and halo mass -- size relations of central and satellite galaxies separately. We show that, while central and satellite galaxies display similar stellar mass -- size relations, their halo mass -- size relations differ significantly. As expected, more massive haloes tend to host larger central galaxies. However, the size of satellite galaxies depends only slightly on halo virial mass. We show that these results are compatible with a remarkably simple model in which the size of central and satellite galaxies scales as the cubic root of their host halo mass, with the normalization for satellites being $\sim$ 30 \% smaller than that for central galaxies, which can be attributed to tidal stripping. We further check that our measurements are in excellent agreement with predictions from the IllustrisTNG hydrodynamical simulation. In the second part of this paper, we analyse how the clustering properties of central and satellite galaxies depend on their size. We demonstrate that, independently of the stellar mass threshold adopted, smaller galaxies are more tightly clustered than larger galaxies when either the entire sample or only satellites are considered. The opposite trend is observed on large scales when the size split is performed for the central galaxies alone. Our results place significant constraints for halo-galaxy connection models that link galaxy size with the properties of their hosting haloes., Comment: 15 pages, 12 figures. Accepted for publication in MNRAS

We demonstrate that baryonification algorithms, which displace particles in gravity-only simulations according to physically-motivated prescriptions, can simultaneously capture the impact of baryonic physics on the 2 and 3-point statistics of matter. Specifically, we show that our implementation of a baryonification algorithm jointly fits the changes induced by baryons on the power spectrum and equilateral bispectrum on scales up to k < 5 h/Mpc and redshifts z<2, as measured in six different cosmological hydrodynamical simulations. The accuracy of our fits are typically 1% for the power spectrum, and for the equilateral and squeezed bispectra, which somewhat degrades to 3% for simulations with extreme feedback prescriptions. Our results support the physical assumptions underlying baryonification approaches, and encourage their use in interpreting weak gravitational lensing and other cosmological observables., Comment: 14 pages, 15 figures. To be submitted to MNRAS. Comments are welcome

Inaccuracies in the initial conditions for cosmological N-body simulations could easily be the largest source of systematic error in predicting the non-linear large-scale structure. From the theory side, initial conditions are usually provided by using low-order truncations of the displacement field from Lagrangian perturbation theory, with the first and second-order approximations being the most common ones. Here we investigate the improvement brought by using initial conditions based on third-order Lagrangian perturbation theory (3LPT). We show that with 3LPT, truncation errors are vastly suppressed, thereby opening the portal to initializing simulations accurately as late as z=12 (for the resolution we consider). We analyse the competing effects of perturbative truncation and particle discreteness on various summary statistics. Discreteness errors are essentially decaying modes and thus get strongly amplified for earlier initialization times. We show that late starting times with 3LPT provide the most accurate configuration, which we find to coincide with the continuum fluid limit within 1 per cent for the power- and bispectrum at z=0 up to the particle Nyquist wave number of our simulations (k ~ 3h/Mpc). In conclusion, to suppress non-fluid artefacts, we recommend initializing simulations as late as possible with 3LPT. We make our 3LPT initial condition generator publicly available., Comment: 22 pages, 13 figures, minor revisions (matches published version), code available from https://bitbucket.org/ohahn/monofonic

In the context of next-generation spectroscopic galaxy surveys, new statistics of the distribution of matter are currently being developed. Among these, we investigated the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We tested both the standard $\mathrm{\Lambda CDM}$ model and the $\mathrm{wCDM}$ extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties by a factor of at least two on most parameters for the $\mathrm{\Lambda CDM}$ and $\mathrm{wCDM}$ models. We find that the ARF combined with angular galaxy clustering provide a great way to probe dark energy by increasing the figure of merit of the $w_0$-$w_{\rm a}$ parameter set by a factor of more than ten compared to angular galaxy clustering alone. Finally, we compared ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by $\sim 40\%$ on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing., Comment: 14 pages, 21 figures, published in A&A

Voids are promising cosmological probes. Nevertheless, every cosmological test based on voids must necessarily employ methods to identify them in redshift space. Therefore, redshift-space distortions (RSD) and the Alcock-Paczynski effect (AP) have an impact on the void identification process itself generating distortion patterns in observations. Using a spherical void finder, we developed a statistical and theoretical framework to describe physically the connection between the identification in real and redshift space. We found that redshift-space voids above the shot noise level have a unique real-space counterpart spanning the same region of space, they are systematically bigger and their centres are preferentially shifted along the line of sight. The expansion effect is a by-product of RSD induced by tracer dynamics at scales around the void radius, whereas the off-centring effect constitutes a different class of RSD induced at larger scales by the global dynamics of the whole region containing the void. The volume of voids is also altered by the fiducial cosmology assumed to measure distances, this is the AP change of volume. These three systematics have an impact on cosmological statistics. In this work, we focus on the void size function. We developed a theoretical framework to model these effects and tested it with a numerical simulation, recovering the statistical properties of the abundance of voids in real space. This description depends strongly on cosmology. Hence, we lay the foundations for improvements in current models of the abundance of voids in order to obtain unbiased cosmological constraints from redshift surveys., Comment: 16 pages, 12 figures, accepted in MNRAS

We compare predictions for galaxy-galaxy lensing profiles and clustering from the Henriques et al. (2015) public version of the Munich semi-analytical model of galaxy formation (SAM) and the IllustrisTNG suite, primarily TNG300, with observations from KiDS+GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast > 10^{11}\,M_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode AGN accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. (2017). Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only ($\chi^2 = 1.81$ compared to $\chi^2 = 7.79$ for the SAM), and locally brightest galaxies samples ($\chi^2 = 3.80$ compared to $\chi^2 = 5.01$). With added dust corrections to the colours it matches the SDSS clustering signal well for red low mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\,\%$ excessive lensing signals for intermediate mass red galaxies with $10.2 < \log_{10} M_\ast [ M_\odot ] < 11.2$ at $r \approx 0.6\,h^{-1}\,\mathrm{Mpc}$, which require further theoretical development., Comment: 30 pages, 20 figures, 10 tables, minor revisions, matches version accepted by MNRAS