Abstract
We determine the thermal evolution of the intergalactic medium (IGM) over 3 Gyr of cosmic time
by comparing measurements of the Ly
α
forest power spectrum to a suite of ∼70 hydrodynamical ...simulations. We conduct Bayesian inference of IGM thermal parameters using an end-to-end forward modeling framework whereby mock spectra generated from our simulation grid are used to build a custom emulator that interpolates the power spectrum between thermal grid points. The temperature at mean density
T
0
rises steadily from
at
z
= 5.4, peaks at 14,000 K for
z
∼ 3.4, and decreases at lower redshift, reaching
T
0
∼ 7000 K by
z
∼ 1.8. This evolution provides conclusive evidence for photoionization heating resulting from the reionization of
, as well as the subsequent cooling of the IGM due to the expansion of the universe after all reionization events are complete. Our results are broadly consistent with previous measurements of thermal evolution based on a variety of approaches, but the sensitivity of the power spectrum, the combination of high-precision measurements of large-scale modes (
) from the Baryon Oscillation Spectroscopic Survey with our recent determination of the small-scale power, our large grid of models, and our careful statistical analysis allow us to break the well-known degeneracy between the temperature at mean density
T
0
and the slope of the temperature–density relation
γ
that has plagued previous analyses. At the highest redshifts,
z
≥ 5, we infer lower temperatures than expected from the standard picture of IGM thermal evolution leaving little room for additional smoothing of the Ly
α
forest by free streaming of warm dark matter.
Abstract
Hydrodynamical cosmological simulations are a powerful tool for accurately predicting the properties of the intergalactic medium (IGM) and for producing mock skies that can be compared ...against observational data. However, the need to resolve density fluctuation in the IGM puts a stringent requirement on the resolution of such simulations, which in turn limits the volumes that can be modeled, even on the most powerful supercomputers. In this work, we present a novel modeling method that combines physics-driven simulations with data-driven generative neural networks to produce outputs that are qualitatively and statistically close to the outputs of hydrodynamical simulations employing eight times higher resolution. We show that the Ly
α
flux field, as well as the underlying hydrodynamic fields, have greatly improved statistical fidelity over a low-resolution simulation. Importantly, the design of our neural network allows for sampling multiple realizations from a given input, enabling us to quantify the model uncertainty. Using test data, we demonstrate that this model uncertainty correlates well with the true error of the Ly
α
flux prediction. Ultimately, our approach allows for training on small simulation volumes and applying it to much larger ones, opening the door to producing accurate Ly
α
mock skies in volumes of Hubble size, as will be probed with DESI and future spectroscopic sky surveys.
Abstract
Generating large-volume hydrodynamical simulations for cosmological observables is a computationally demanding task necessary for next-generation observations. In this work, we construct a ...novel fully convolutional variational autoencoder (VAE) to synthesize hydrodynamic fields conditioned on dark matter fields from
N
-body simulations. After training the model on a single hydrodynamical simulation, we are able to probabilistically map new dark-matter-only simulations to corresponding full hydrodynamical outputs. By sampling over the latent space of our VAE, we can generate posterior samples and study the variance of the mapping. We find that our reconstructed field provides an accurate representation of the target hydrodynamical fields as well as reasonable variance estimates. This approach has promise for the rapid generation of mocks as well as for implementation in a full inverse model of observed data.
A study of imaging the Fukushima Daiichi reactors with cosmic-ray muons to assess the damage to the reactors is presented. Muon scattering imaging has high sensitivity for detecting uranium fuel and ...debris even through thick concrete walls and a reactor pressure vessel. Technical demonstrations using a reactor mockup, detector radiation test at Fukushima Daiichi, and simulation studies have been carried out. These studies establish feasibility for the reactor imaging. A few months of measurement will reveal the spatial distribution of the reactor fuel. The muon scattering technique would be the best and probably the only way for Fukushima Daiichi to make this determination in the near future.
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters that characterize the underlying ...physical system-our universe, from these observations and theoretical forward-modeling. The only way to accurately forward-model physical behavior on small scales is via expensive numerical simulations, which are further "emulated" due to their high cost. Emulators are commonly built with a set of simulations covering the parameter space with Latin hypercube sampling and an interpolation procedure; the aim is to establish an approximately constant prediction error across the hypercube. In this paper, we provide a description of a novel statistical framework for obtaining accurate parameter constraints. The proposed framework uses multi-output Gaussian process emulators that are adaptively constructed using Bayesian optimization methods with the goal of maintaining a low emulation error in the region of the hypercube preferred by the observational data. In this paper, we compare several approaches for constructing multi-output emulators that enable us to take possible inter-output correlations into account while maintaining the efficiency needed for inference. Using a Ly forest flux power spectrum, we demonstrate that our adaptive approach requires considerably fewer-by a factor of a few in the Ly P(k) case considered here-simulations compared to the emulation based on Latin hypercube sampling, and that the method is more robust in reconstructing parameters and their Bayesian credible intervals.
Abstract
We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys’ Data Release 9. ...Targeting the identification of new strong gravitational lens candidates, we first create a rapid similarity search tool to discover new strong lenses given only a single labeled example. We then show how training a simple linear classifier on the self-supervised representations, requiring only a few minutes on a CPU, can automatically classify strong lenses with great efficiency. We present 1192 new strong lens candidates that we identified through a brief visual identification campaign and release an interactive web-based similarity search tool and the top network predictions to facilitate crowd-sourcing rapid discovery of additional strong gravitational lenses and other rare objects:
github.com/georgestein/ssl-legacysurvey
.
We study the statistics of the Ly alpha forest in a flat ... cold dark matter cosmology with the N-body + Eulerian hydrodynamics code nyx. We produce a suite of simulations, covering the ...observationally relevant redshift range 2 less than or equal to z less than or equal to 4. We find that a grid resolution of 20 h... kpc is required to produce 1 per cent convergence of Ly alpha forest flux statistics, up to k = 10 h... Mpc. In addition to establishing resolution requirements, we study the effects of missing modes in these simulations, and find that box sizes of L > 40h... Mpc are needed to suppress numerical errors to a sub-per cent level. Our optically thin simulations with the ionizing background prescription of Haardt & Madau reproduce an intergalactic medium density-temperature relation with T... 10... K and ... 1.55 at z = 2, with a mean transmitted flux close to the observed values. When using the ionizing background prescription of Faucher-Giguere et al., the mean flux is 10-15 per cent below observed values at z = 2, and a factor of 2 too small at z = 4. We show the effects of the common practice of rescaling optical depths to the observed mean flux and how it affects convergence rates. We also investigate the practice of 'splicing' results from a number of different simulations to estimate the 1D flux power spectrum and show it is accurate at the 10 per cent level. Finally, we find that collisional heating of the gas from dark matter particles is negligible in modern cosmological simulations. (ProQuest: ... denotes formulae/symbols omitted.)
Abstract
Galaxy formation depends critically on the physical state of gas in the circumgalactic medium (CGM) and its interface with the intergalactic medium (IGM), determined by the complex interplay ...between inflow from the IGM and outflows from supernovae and/or AGN feedback. The average Ly
α
absorption profile around galactic halos represents a powerful tool to probe their gaseous environments. We compare predictions from Illustris and Nyx hydrodynamical simulations with the observed absorption around foreground quasars, damped Ly
α
systems, and Lyman-break galaxies. We show how large-scale BOSS and small-scale quasar pair measurements can be combined to precisely constrain the absorption profile over three decades in transverse distance
. Far from galaxies,
, the simulations converge to the same profile and provide a reasonable match to the observations. This asymptotic agreement arises because the ΛCDM model successfully describes the ambient IGM and represents a critical advantage of studying the mean absorption profile. However, significant differences between the simulations, and between simulations and observations, are present on scales
, illustrating the challenges of accurately modeling and resolving galaxy formation physics. It is noteworthy that these differences are observed as far out as
, indicating that the “sphere of influence” of galaxies could extend to approximately ∼7 times the halo virial radius. Current observations are very precise on these scales and can thus strongly discriminate between different galaxy formation models. We demonstrate that the Ly
α
absorption profile is primarily sensitive to the underlying temperature–density relationship of diffuse gas around galaxies, and argue that it thus provides a fundamental test of galaxy formation models.
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