A population of ultraviolet-dim protoclusters detected in absorption.

Galaxy protoclusters, which will eventually grow into the massive clusters we see in the local Universe, are usually traced by locating overdensities of galaxies1. Large spectroscopic surveys of distant galaxies now exist, but their sensitivity depends mainly on a galaxy's star-formation activity and dust content rather than its mass. Tracers of massive protoclusters that do not rely on their galaxy constituents are therefore needed. Here we report observations of Lyman-α absorption in the spectra of a dense grid of background galaxies2,3, which we use to locate a substantial number of candidate protoclusters at redshifts 2.2 to 2.8 through their intergalactic gas. We find that the structures producing the most absorption, most of which were previously unknown, contain surprisingly few galaxies compared with the dark-matter content of their analogues in cosmological simulations4,5. Nearly all of the structures are expected to be protoclusters, and we infer that half of their expected galaxy members are missing from our survey because they are unusually dim at rest-frame ultraviolet wavelengths. We attribute this to an unexpectedly strong and early influence of the protocluster environment6,7 on the evolution of these galaxies that reduced their star formation or increased their dust content.

Forecast Cosmological Constraints with the 1D Wavelet Scattering Transform and the Lyman-α Forest.

We make forecasts for the constraining power of the 1D wavelet scattering transform when used with a Lyman-α forest cosmology survey. Using mock simulations and a Fisher matrix, we show that there is considerable cosmological information in the scattering transform coefficients not captured by the flux power spectrum. We estimate mock covariance matrices assuming uncorrelated Gaussian pixel noise for each quasar at a level drawn from a simple log-normal model. The extra information comes from a smaller estimated covariance in the first-order wavelet power and from second-order wavelet coefficients that probe non-Gaussian information in the forest. Forecast constraints on cosmological parameters from the wavelet scattering transform are more than an order of magnitude tighter than for the power spectrum, shrinking a 4D parameter space by a factor of 10^{6}. Should these improvements be realized with the Dark Energy Spectroscopic Instrument, inflationary running would be constrained to test common inflationary models predicting α_{s}=-6×10^{-4} and neutrino mass constraints would be improved enough for a 5-σ detection of the minimal neutrino mass.

AI-assisted superresolution cosmological simulations.

Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in artificial intelligence (AI; specifically deep learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data and then make accurate superresolution (SR) versions of different low-resolution (LR) images. We apply such techniques to LR cosmological N-body simulations, generating SR versions. Specifically, we are able to enhance the simulation resolution by generating 512 times more particles and predicting their displacements from the initial positions. Therefore, our results can be viewed as simulation realizations themselves, rather than projections, e.g., to their density fields. Furthermore, the generation process is stochastic, enabling us to sample the small-scale modes conditioning on the large-scale environment. Our model learns from only 16 pairs of small-volume LR-HR simulations and is then able to generate SR simulations that successfully reproduce the HR matter power spectrum to percent level up to [Formula: see text] and the HR halo mass function to within [Formula: see text] down to [Formula: see text] We successfully deploy the model in a box 1,000 times larger than the training simulation box, showing that high-resolution mock surveys can be generated rapidly. We conclude that AI assistance has the potential to revolutionize modeling of small-scale galaxy-formation physics in large cosmological volumes.

Stochastic Gravitational-Wave Background due to Primordial Binary Black Hole Mergers.

Recent Advanced LIGO detections of binary black hole mergers have prompted multiple studies investigating the possibility that the heavy GW150914 binary system was of primordial origin, and hence could be evidence for dark matter in the form of black holes. We compute the stochastic background arising from the incoherent superposition of such primordial binary black hole systems in the Universe and compare it to the similar background spectrum due to binary black hole systems of stellar origin. We investigate the possibility of detecting this background with future gravitational-wave detectors, and conclude that constraining the dark matter component in the form of black holes using stochastic gravitational-wave background measurements will be very challenging.

Did LIGO Detect Dark Matter?

We consider the possibility that the black-hole (BH) binary detected by LIGO may be a signature of dark matter. Interestingly enough, there remains a window for masses 20M_{⊙}≲M_{bh}≲100M_{⊙} where primordial black holes (PBHs) may constitute the dark matter. If two BHs in a galactic halo pass sufficiently close, they radiate enough energy in gravitational waves to become gravitationally bound. The bound BHs will rapidly spiral inward due to the emission of gravitational radiation and ultimately will merge. Uncertainties in the rate for such events arise from our imprecise knowledge of the phase-space structure of galactic halos on the smallest scales. Still, reasonable estimates span a range that overlaps the 2-53 Gpc^{-3} yr^{-1} rate estimated from GW150914, thus raising the possibility that LIGO has detected PBH dark matter. PBH mergers are likely to be distributed spatially more like dark matter than luminous matter and have neither optical nor neutrino counterparts. They may be distinguished from mergers of BHs from more traditional astrophysical sources through the observed mass spectrum, their high ellipticities, or their stochastic gravitational wave background. Next-generation experiments will be invaluable in performing these tests.