The connection between galaxies and their host dark matter (DM) halos is critical to our understanding of cosmology, galaxy formation, and DM physics. To maximize the return of upcoming cosmological surveys, we need an accurate way to model this complex relationship. Many techniques have been developed to model this connection, from Halo Occupation Distribution (HOD) to empirical and semi-analytic models to hydrodynamic. Hydrodynamic simulations can incorporate more detailed astrophysical processes but are computationally expensive; HODs, on the other hand, are computationally cheap but have limited accuracy. In this work, we present NeHOD, a generative framework based on variational diffusion model and Transformer, for painting galaxies/subhalos on top of DM with an accuracy of hydrodynamic simulations but at a computational cost similar to HOD. By modeling galaxies/subhalos as point clouds, instead of binning or voxelization, we can resolve small spatial scales down to the resolution of the simulations. For each halo, NeHOD predicts the positions, velocities, masses, and concentrations of its central and satellite galaxies. We train NeHOD on the TNG-Warm DM suite of the DREAMS project, which consists of 1024 high-resolution zoom-in hydrodynamic simulations of Milky Way-mass halos with varying warm DM mass and astrophysical parameters. We show that our model captures the complex relationships between subhalo properties as a function of the simulation parameters, including the mass functions, stellar-halo mass relations, concentration-mass relations, and spatial clustering. Our method can be used for a large variety of downstream applications, from galaxy clustering to strong lensing studies.
Disks of gas accreting onto supermassive black holes may host numerous stellar-mass objects, formed within the disk or captured from a nuclear star cluster. We present a simplified model of stellar evolution applicable to these dense environments; our model exhibits exquisite agreement with full stellar evolution calculations at a minuscule fraction of the cost. Although the model presented here is limited to stars burning hydrogen in their cores, it is sufficient to determine the evolutionary fate of disk-embedded stars: whether they proceed to later stages of nuclear burning and leave behind a compact remnant, reach a quasi-steady state where mass loss and accretion balance one another, or whether accretion proceeds faster than stellar structure can adjust, causing a runaway. We provide numerous examples, highlighting how various disk parameters, and effects such as gap opening, affect stellar evolution outcomes. We also highlight how our model can accommodate time-varying conditions, such as those experienced by a star on an eccentric orbit, and can couple to N-body integrations. This model will enable more detailed studies of stellar populations and their interaction with accretion disks than have previously been possible.
The cold interstellar medium (ISM) as the raw material for star formation is critical to understanding galaxy evolution. It is generally understood that galaxies stop making stars when, in one way or another, they run out of gas. However, here we provide evidence that central spiral galaxies remain rich in atomic gas even if their star formation rate and molecular gas fraction have dropped significantly compared to "normal" star-forming galaxies of the same mass. Since HI is sensitive to external processes, here we investigate central spiral galaxies using a combined sample from SDSS, ALFALFA, and xGASS surveys. After proper incompleteness corrections, we find that the key HI scaling relations for central spirals show significant but regular systematic dependence on stellar mass. At any given stellar mass, the HI gas mass fraction is about constant with changing specific star formation rate (sSFR), which suggests that HI reservoir is ubiquitous in central spirals with any star formation status down to M* ~ 10^9 Msun. Together with the tight correlation between the molecular gas mass fraction and sSFR for galaxies across a wide range of different properties, it suggests that the decline of SFR of all central spirals in the local universe is due to the halt of H2 supply, though there is plenty of HI gas around. These hence provide critical observations of the dramatically different behavior of the cold multi-phase ISM, and a key to understand the star formation process and quenching mechanism.
Dense cores inherit turbulent motions from the interstellar medium in which they form. As a tool for comparison to both simulations and observations, it is valuable to construct theoretical core models that can relate their internal density and velocity structure while predicting their stability to gravitational collapse. To this end, we solve the angle-averaged equations of hydrodynamics under two assumptions: 1) the system is in a quasi-steady equilibrium; 2) the velocity field consists of radial bulk motion plus isotropic turbulence, with turbulent dispersion increasing as a power-law in the radius. The resulting turbulent equilibrium sphere (TES) solutions form a two-parameter family, characterized by the sonic radius $r_s$ and the power-law index $p$. The TES is equivalent to the Bonnor-Ebert (BE) sphere when $r_s\to \infty$. The density profile in outer regions of the TES is slightly shallower than the BE sphere, but is steeper than the logotropic model. Stability analysis shows that the TESs with size exceeding a certain critical radius are unstable to radial perturbations. The center-to-edge density contrast, mass, and radius of the marginally stable TES all increase with increasing average velocity dispersion. The FWHM of the column density profile is always smaller than the critical radius, by a larger factor at higher velocity dispersion, suggesting that observations need to probe beyond the FWHM to capture the full extent of turbulent cores. When applied to the highly turbulent regime typical of cluster-forming clumps, the critical mass and radius of the TES intriguingly resembles the typical mass and radius of observed star clusters.
This is an index of the contributions by the Giant Radio Array for Neutrino Detection (GRAND) Collaboration to the 10th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities (ARENA 2024, University of Chicago, June 11-14, 2024). The contributions include an overview of GRAND in its present and future incarnations, methods of radio-detection that are being developed for them, and ongoing joint work between the GRAND and BEACON experiments.
To constrain models beyond $\Lambda$CDM, the development of the Euclid analysis pipeline requires simulations that capture the nonlinear phenomenology of such models. We present an overview of numerical methods and $N$-body simulation codes developed to study the nonlinear regime of structure formation in alternative dark energy and modified gravity theories. We review a variety of numerical techniques and approximations employed in cosmological $N$-body simulations to model the complex phenomenology of scenarios beyond $\Lambda$CDM. This includes discussions on solving nonlinear field equations, accounting for fifth forces, and implementing screening mechanisms. Furthermore, we conduct a code comparison exercise to assess the reliability and convergence of different simulation codes across a range of models. Our analysis demonstrates a high degree of agreement among the outputs of different simulation codes, providing confidence in current numerical methods for modelling cosmic structure formation beyond $\Lambda$CDM. We highlight recent advances made in simulating the nonlinear scales of structure formation, which are essential for leveraging the full scientific potential of the forthcoming observational data from the Euclid mission.
The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard $\Lambda$-cold-dark-matter ($\Lambda$CDM) paradigm and in many non-standard models beyond $\Lambda$CDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard $\Lambda$CDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid.
We study the constraint on $f(R)$ gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu-Sawicki $f(R)$ gravity model, we consider four different predictions for the ratio between the power spectrum in $f(R)$ and that in $\Lambda$CDM: a fitting formula, the halo model reaction approach, ReACT and two emulators based on dark matter only $N$-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering and their cross-correlation. By running Markov Chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered $f(R)$ parameter if the data are created by a different model. For the pessimistic setting of WL, one dimensional bias for the $f(R)$ parameter, $\log_{10}|f_{R0}|$, is found to be $0.5 \sigma$ when FORGE is used to create the synthetic data with $\log_{10}|f_{R0}| =-5.301$ and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator BCemu. For the optimistic setting, the $f(R)$ parameter and two main baryon parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated by the adjustment of baryon parameters, and the one-dimensional marginalised constraint on $\log_{10}|f_{R0}|$ is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the $\Lambda$CDM synthetic data for WL, we obtain the prior-independent upper limit of $\log_{10}|f_{R0}|< -5.6$. Finally, we implement a method to include theoretical errors to avoid the bias.