arXiv subjects

Daisuke Nagai

Publications and source records attributed to Daisuke Nagai.

At least 91 records · Page 5Linked to original sources

arXiv2022

R2-D2: Roman and Rubin -- From Data to Discovery

The NASA Nancy Grace Roman Space Telescope (Roman) and the Vera C. Rubin Observatory Legacy Survey of Space and Time (Rubin), will transform our view of the wide-field sky, with similar sensitivities, but complementary in wavelength, spatial resolution, and time domain coverage. Here we present findings from the AURA Roman+Rubin Synergy Working group, charged by the STScI and NOIRLab Directors to identify frontier science questions in General Astrophysics, beyond the well-covered areas of Dark Energy and Cosmology, that can be uniquely addressed with Roman and Rubin synergies in observing strategy, data products and archiving, joint analysis, and community engagement. This analysis was conducted with input from the community in the form of brief (1-2 paragraph) "science pitches" (see Appendix), and testimony from "outside experts" (included as co-authors). We identify a rich and broad landscape of potential discoveries catalyzed by the combination of exceptional quality and quantity of Roman and Rubin data, and summarize implementation requirements that would facilitate this bounty of additional science with coordination of survey fields, joint coverage of the Galactic plane, bulge, and ecliptic, expansion of General Investigator and Target of Opportunity observing modes, co-location of Roman and Rubin data, and timely distribution of data, transient alerts, catalogs, value-added joint analysis products, and simulations to the broad astronomical community.

astro-ph.IM↗

arXiv2022

Emulating Sunyaev-Zeldovich Images of Galaxy Clusters using Auto-Encoders

We develop a machine learning algorithm that generates high-resolution thermal Sunyaev-Zeldovich (SZ) maps of novel galaxy clusters given only halo mass and mass accretion rate. The algorithm uses a conditional variational autoencoder (CVAE) in the form of a convolutional neural network and is trained with SZ maps generated from the IllustrisTNG simulation. Our method can reproduce many of the details of galaxy clusters that analytical models usually lack, such as internal structure and aspherical distribution of gas created by mergers, while achieving the same computational feasibility, allowing us to generate mock SZ maps for over $10^5$ clusters in 30 seconds on a laptop. We show that the model is capable of generating novel clusters (i.e. not found in the training set) and that the model accurately reproduces the effects of mass and mass accretion rate on the SZ images, such as scatter, asymmetry, and concentration, in addition to modeling merging sub-clusters. This work demonstrates the viability of machine-learning--based methods for producing the number of realistic, high-resolution maps of galaxy clusters necessary to achieve statistical constraints from future SZ surveys.

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arXiv2022

Breaking baryon-cosmology degeneracy with the electron density power spectrum

Uncertain feedback processes in galaxies affect the distribution of matter, currently limiting the power of weak lensing surveys. If we can identify cosmological statistics that are robust against these uncertainties, or constrain these effects by other means, then we can enhance the power of current and upcoming observations from weak lensing surveys such as DES, Euclid, the Rubin Observatory, and the Roman Space Telescope. In this work, we investigate the potential of the electron density auto-power spectrum as a robust probe of cosmology and baryonic feedback. We use a suite of (magneto-)hydrodynamic simulations from the CAMELS project and perform an idealized analysis to forecast statistical uncertainties on a limited set of cosmological and physically-motivated astrophysical parameters. We find that the electron number density auto-correlation, measurable through either kinematic Sunyaev-Zel'dovich observations or through Fast Radio Burst dispersion measures, provides tight constraints on $Ω_{m}$ and the mean baryon fraction in intermediate-mass halos, $\bar{f}_{\mathrm{bar}}$. By obtaining an empirical measure for the associated systematic uncertainties, we find these constraints to be largely robust to differences in baryonic feedback models implemented in hydrodynamic simulations. We further discuss the main caveats associated with our analysis, and point out possible directions for future work.

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arXiv2022

The Circumgalactic Medium from the CAMELS Simulations: Forecasting Constraints on Feedback Processes from Future Sunyaev-Zeldovich Observations

The cycle of baryons through the circumgalactic medium (CGM) is important to understand in the context of galaxy formation and evolution. In this study we forecast constraints on the feedback processes heating the CGM with current and future Sunyaev-Zeldovich (SZ) observations. To constrain these processes, we use a suite of cosmological simulations, the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS), that varies four different feedback parameters of two previously existing hydrodynamical simulations, IllustrisTNG and SIMBA. We capture the dependencies of SZ radial profiles on these feedback parameters with an emulator, calculate their derivatives, and forecast future constraints on these feedback parameters from upcoming experiments. We find that for a DESI-like (Dark Energy Spectroscopic Instrument) galaxy sample observed by the Simons Observatory all four feedback parameters are able to be constrained (some within the $10\%$ level), indicating that future observations will be able to further restrict the parameter space for these sub-grid models. Given the modeled galaxy sample and forecasted errors in this work, we find that the inner SZ profiles contribute more to the constraining power than the outer profiles. Finally, we find that, despite the wide range of AGN feedback parameter variation in the CAMELS simulation suite, we cannot reproduce the tSZ signal of galaxies selected by the Baryon Oscillation Spectroscopic Survey as measured by the Atacama Cosmology Telescope.

astro-ph.CO↗

arXiv2022

Cosmology with one galaxy?

Galaxies can be characterized by many internal properties such as stellar mass, gas metallicity, and star-formation rate. We quantify the amount of cosmological and astrophysical information that the internal properties of individual galaxies and their host dark matter halos contain. We train neural networks using hundreds of thousands of galaxies from 2,000 state-of-the-art hydrodynamic simulations with different cosmologies and astrophysical models of the CAMELS project to perform likelihood-free inference on the value of the cosmological and astrophysical parameters. We find that knowing the internal properties of a single galaxy allow our models to infer the value of $Ω_{\rm m}$, at fixed $Ω_{\rm b}$, with a $\sim10\%$ precision, while no constraint can be placed on $σ_8$. Our results hold for any type of galaxy, central or satellite, massive or dwarf, at all considered redshifts, $z\leq3$, and they incorporate uncertainties in astrophysics as modeled in CAMELS. However, our models are not robust to changes in subgrid physics due to the large intrinsic differences the two considered models imprint on galaxy properties. We find that the stellar mass, stellar metallicity, and maximum circular velocity are among the most important galaxy properties to determine the value of $Ω_{\rm m}$. We believe that our results can be explained taking into account that changes in the value of $Ω_{\rm m}$, or potentially $Ω_{\rm b}/Ω_{\rm m}$, affect the dark matter content of galaxies. That effect leaves a distinct signature in galaxy properties to the one induced by galactic processes. Our results suggest that the low-dimensional manifold hosting galaxy properties provides a tight direct link between cosmology and astrophysics.

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arXiv2022

The CAMELS project: public data release

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogues, power spectra, bispectra, Lyman-$α$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic Model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies and summary statistics. We provide further technical details on how to access, download, read, and process the data at \url{https://camels.readthedocs.io}.

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arXiv2021

Constraining Cluster Virialization Mechanism and Cosmology using Thermal-SZ-selected clusters from Future CMB Surveys

We forecast the number of galaxy clusters that can be detected via the thermal Sunyaev-Zeldovich (tSZ) signals by future cosmic microwave background (CMB) experiments, primarily the wide area survey of the CMB-S4 experiment but also CMB-S4's smaller delensing survey and the proposed CMB-HD experiment. We predict that CMB-S4 will detect 75,000 clusters with its wide survey of $f_{\rm sky}$ = 50% and 14,000 clusters with its deep survey of $f_{\rm sky}$ = 3%. Of these, approximately 1350 clusters will be at $z \ge 2$, a regime that is difficult to probe by optical or X-ray surveys. We assume CMB-HD will survey the same sky as the S4-Wide{}, and find that CMB-HD will detect $\times3$ more overall and an order of magnitude more $z \ge 2$ clusters than CMB-S4. These results include galactic and extragalactic foregrounds along with atmospheric and instrumental noise. Using CMB-cluster lensing to calibrate cluster tSZ-mass scaling relation, we combine cluster counts with primary CMB to obtain cosmological constraints for a two parameter extension of the standard model ($ΛCDM+\sum m_ν+w_{0}$). Besides constraining $σ(w_{0})$ to $\lesssim 1\%$, we find that both surveys can enable a $\sim 2.5-4.5σ$ detection of $\sum m_ν$, substantially strengthening CMB-only constraints. We also study the evolution of intracluster medium by modelling the cluster virialization ${\rm v}(z)$ and find tight constraints from CMB-S4, with further factors of 3-4 improvement for CMB-HD. The binned cluster counts, Fisher matrices, and other associated products can be downloaded from https://github.com/sriniraghunathan/tSZ_cluster_forecasts.

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arXiv2021

Galaxy Velocity Bias in Cosmological Simulations: Towards Percent-level Calibration

Galaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, b_v -- defined as the ratio of galaxy and DM velocity dispersions -- as a function of redshift, host halo mass, and galaxy stellar mass threshold (Mstarsat), for massive halos (M200c > 1e13.5 msun) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of b_v increasing with M200c and decreasing with redshift and Mstarsat. The ensemble-estimated theoretical uncertainty in b_v is 2-3% but becomes percent-level when considering only the three highest resolution simulations. We update the mass-richness normalization previously estimated by Farahi et al. (2016) for an SDSS redMaPPer cluster sample. The improved accuracy of our b_v estimates reduces the mass normalization uncertainty from 22% to 8%, demonstrating that dynamical estimation techniques can be competitive with weak lensing in calibrating population mean masses. We discuss necessary steps for further improving this precision. Our estimates for b_v(M200c, Mstarsat, z) are made publicly available.

astro-ph.CO↗

arXiv2021

Shock and Splash: Gas and Dark Matter Halo Boundaries around LambdaCDM Galaxy Clusters

Recent advances in simulations and observations of galaxy clusters suggest that there exists a physical outer boundary of massive cluster-size dark matter haloes. In this work, we investigate the locations of the outer boundaries of dark matter and gas around cluster-size dark matter haloes, by analyzing a sample of 65 massive dark matter halos extracted from the Omega500 zoom-in hydrodynamical cosmological simulations. We show that the location of accretion shock is offset from that of the dark matter splashback radius, contrary to the prediction of the self-similar models. The accretion shock radius is larger than all definitions of the splashback radius in the literature by 20-100%. The accretion shock radius defined using the steepest drop in the entropy pressure profiles is approximately 2 times larger than the splashback radius defined by the steepest slope in the dark matter density profile, and it is ~1.2 times larger than the edge of the dark matter phase-space structure. We discuss implications of our results for multi-wavelength studies of galaxy clusters.

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arXiv2021

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from 2,000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span $\sim$100 million light years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine learning models, CMD is the largest dataset of its kind containing more than 70 Terabytes of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.

cs.LG↗

arXiv2021

Constraining Merging Galaxy Clusters with X-ray and Lensing Simulations and Observations: The case of Abell 2146

Galaxy cluster mergers are a powerful laboratory for testing cosmological and astrophysical models. However, interpreting individual merging clusters depends crucially on their merger configuration, defined by the masses, velocities, impact parameters, and orientation of the merger axis with respect to the plane of the sky. In this work, we investigate the impact of merger parameters on the X-ray emitting intracluster medium and gravitational lensing maps using a suite of idealised simulations of binary cluster mergers performed using the GAMER-2 code. As a test case, we focus on modeling the Bullet Cluster-like merging system Abell 2146, in which deep \textit{Chandra} X-ray and lensing observations revealed prominent merger shocks as well as the mass distribution and substructures associated with this merging cluster. We identify the most interesting parameter combinations, and evaluate the effects of various parameters on the properties of merger shocks observed by deep \textit{Chandra} and lensing observations. We show that due gravitational compression of the cluster halos during the merger, previous mass estimates from weak lensing are too high. The plane of the merger is tilted further from the plane of the sky than estimated previously, up to $30^\circ$ from the plane of the sky. We discuss the applicability of our results to multi-wavelength observations of merging galaxy clusters and their use as probes of cosmology and plasma physics.

astro-ph.HE↗

arXiv2021

SHAPing the Gas: Understanding Gas Shapes in Dark Matter Haloes with Interpretable Machine Learning

The non-spherical shapes of dark matter and gas distributions introduce systematic uncertainties that affect observable-mass relations and selection functions of galaxy groups and clusters. However, the triaxial gas distributions depend on the non-linear physical processes of halo formation histories and baryonic physics, which are challenging to model accurately. In this study we explore a machine learning approach for modelling the dependence of gas shapes on dark matter and baryonic properties. With data from the IllustrisTNG hydrodynamical cosmological simulations, we develop a machine learning pipeline that applies \pkg{XGBoost}, an implementation of gradient boosted decision trees, to predict radial profiles of gas shapes from halo properties. We show that \pkg{XGBoost} models can accurately predict gas shape profiles in dark matter haloes. We also explore model interpretability with \pkg{SHAP}, a method that identifies the most predictive properties at different halo radii. We find that baryonic properties best predict gas shapes in halo cores, whereas dark matter shapes are the main predictors in the halo outskirts. This work demonstrates the power of interpretable machine learning in modelling observable properties of dark matter haloes in the era of multi-wavelength cosmological surveys.

astro-ph.CO↗

arXiv2021

Thermal Instabilities and Shattering in the High-Redshift WHIM: Convergence Criteria and Implications for Low-Metallicity Strong HI Absorbers

Using a novel suite of cosmological simulations zooming in on a Mpc-scale intergalactic sheet or "pancake" at z~3-5, we conduct an in-depth study of the thermal properties and HI content of the warm-hot intergalactic medium (WHIM) at those redshifts. The simulations span nearly three orders of magnitude in gas-cell mass, from ~(7.7x10^6-1.5x10^4)Msun, one of the highest resolution simulations of such a large patch of the inter-galactic medium (IGM) to date. At z~5, a strong accretion shock develops around the main pancake following a collision between two smaller sheets. Gas in the post-shock region proceeds to cool rapidly, triggering thermal instabilities and the formation of a multiphase medium. We find neither the mass, nor the morphology, nor the distribution of HI in the WHIM to be converged at our highest resolution. Interestingly, the lack of convergence is more severe for the less dense, more metal-poor, intra-pancake medium (IPM) in between filaments and far from any star-forming galaxies. As the resolution increases, the IPM develops a shattered structure, with ~kpc scale clouds containing most of the HI. From our lowest to highest resolution, the covering fraction of metal-poor (Z<10^{-3}Zsun) Lyman-limit systems (NHI>10^{17.2}/cm^2) in the IPM at z~4 increases from (3-15)%, while that of Damped Lyman-alpha Absorbers (NHI>10^{20}/cm^2) with similar metallicity increases threefold, from (0.2-0.6)%, with no sign of convergence. We find that a necessary condition for the formation of a multiphase, shattered structure is resolving the cooling length, lcool=cs*tcool, at T~10^5K. If this scale is unresolved, gas "piles up" at these temperatures and cooling to lower temperatures becomes very inefficient. We conclude that state-of-the-art cosmological simulations are still unable to resolve the multi-phase structure of the low-density IGM, with potentially far-reaching implications.

astro-ph.CO↗

arXiv2021

Fountains and storms: The role of AGN and mergers in disrupting the cool-core in the RomulusC simulation

The intracluster medium (ICM) is a multi-phase environment, dynamically regulated by Active Galactic Nuclei (AGN), the motions of galaxies through it, and mergers with other clusters. AGN as a central heating source are key to preventing runaway cooling flows, but their role in heating cores in a cosmological context is still poorly understood. The activity of the AGN is strongly linked to star formation, especially in the Brightest Cluster Galaxy (BCG), likely because both rely on cold phase gas. A self-consistent model for AGN and star formation in galaxy clusters thus requires cosmological context, higher resolution, and a careful modeling of cooling and heating balance. In this paper, we use the high-resolution hydrodynamical cosmological simulation of the RomulusC galaxy cluster to study in detail the role of AGN and a major, head-on merger in shaping the cluster core. The unprecedented resolution of the RomulusC simulation captures the multiphase structure of the ICM. The realistic large-scale outflows launched by very small-scale thermal injections, the improved modeling of turbulent diffusion and mixing, and the particle nature of the simulation allow us to carefully separate different heating channels. We show that AGN activity, while efficient at regulating star formation, is incapable of destroying a CC. Instead, that process is facilitated by a head-on, 1:8 mass ratio merger. The merger generates bulk and turbulent motions, which in turn mix high entropy gas generated by AGN and merger driven shocks, turbulent dissipation and sloshing of the ICM by infalling substructures. While central cooling times remain shorter than the Hubble time, restoring a CC is made more difficult by the reduced precipitation rates at larger radii, emphasizing that the AGN-ICM connection is truly a multi-scale problem.

astro-ph.GA↗

arXiv2021

The Phase Space Structure of Dark Matter Halos

The phase space structure of dark matter halos can be used to measure the mass of the halo, infer mass accretion rates, and probe the effects of modified gravity. Previous studies showed that the splashback radius can be measured in position space using the slope of the density profile. Using N-body simulations, we show that the phase space structure of the dark matter halo does not end at this splashback radius. Instead, there exists a region where infalling, splashback, and virialized halos are mixed spatially. We model the distribution of the three kinematically distinct populations and show that there exists an "edge radius" beyond which a dark matter halo has no orbiting substructures. This radius is a fixed multiple of the splashback radius as defined in previous works, and can be interpreted as a radius which contains a fixed fraction of the apocenters of dark matter particles. Our results provide a firm theoretical foundation to the satellite galaxy model adopted in the companion paper by Tomooka et al., where we analyzed the phase space distribution of SDSS redMaPPer clusters.

astro-ph.CO↗

arXiv2021

The Role of Machine Learning in the Next Decade of Cosmology

In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.

astro-ph.IM↗

arXiv2021

The Formation of Isolated Ultra-Diffuse Galaxies in Romulus25

We use the \textsc{Romulus25} cosmological simulation volume to identify the largest-ever simulated sample of {\it field} ultra-diffuse galaxies (UDGs). At $z=0$, we find that isolated UDGs have average star formation rates, colors, and virial masses for their stellar masses and environment. UDGs have moderately elevated HI masses, being 70\% (300\%) more HI-rich than typical isolated dwarf galaxies at luminosities brighter (fainter) than M$_\mathrm{B}$=-14. However, UDGs are consistent with the general isolated dwarf galaxy population and make up $\sim$20\% of all field galaxies with 10$^7$<M$_\star$/M$_\odot$<10$^{9}$. The HI masses, effective radii, and overall appearances of our UDGs are consistent with existing observations of field UDGs, but we predict that many isolated UDGs have been missed by current surveys. Despite their isolation at $z=0$, the UDGs in our sample are the products of major mergers. Mergers are no more common in UDG than non-UDG progenitors, but mergers that create UDGs tend to happen earlier - almost never occurring after $z=1$, produce a temporary boost in spin, and cause star formation to be redistributed to the outskirts of galaxies, resulting in lower central star formation rates. The centers of the galaxies fade as their central stellar populations age, but their global star formation rates are maintained through bursts of star formation at larger radii, producing steeper negative g-r color gradients. This formation channel is unique relative to other proposals for UDG formation in isolated galaxies, demonstrating that UDGs can potentially be formed through multiple mechanisms.

astro-ph.GA↗

arXiv2020

Full-sky photon simulation of clusters and active galactic nuclei in the soft X-rays for eROSITA

The eROSITA X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) mission will measure the position and properties of about 100,000 clusters of galaxies and 3 million active galactic nuclei over the full sky. To study the statistical properties of this ongoing survey, it is key to estimate the selection function accurately. We create a set of full sky light-cones using the MultiDark and UNIT dark matter only N-body simulations. We present a novel method to predict the X-ray emission of galaxy clusters. Given a set of dark matter halo properties (mass, redshift, ellipticity, offset parameter), we construct an X-ray emissivity profile and image for each halo in the light-cone. We follow the eROSITA scanning strategy to produce a list of X-ray photons on the full sky. We predict scaling relations for the model clusters, which are in good agreement with the literature. The predicted number density of clusters as a function of flux also agrees with previous measurements. Finally, we obtain a scatter of 0.21 (0.07, 0.25) for the X-ray luminosity -- mass (temperature -- mass, luminosity -- temperature) model scaling relations. We provide catalogues with the model photons emitted by clusters and active galactic nuclei. These catalogues will aid the eROSITA end to end simulation flow analysis and in particular the source detection process and cataloguing methods.

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