Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Abstract We present the [OIII]88μm spectral scan results from the ALMA Large Program REBELS (Reionization Era Bright Emission Line Survey). The generally high luminosity of [OIII]88μm and ALMA’s Band 7 efficiency motivated its use for line scans of REBELS targets at z > 8. Spectral scans of four sources covered 326.4-373.0 GHz (z = 8.10-9.39), reaching [OIII]88μm luminosities of ∼7.6 × 108 L⊙ (5σ) for a FWHM of 400 km s−1. No credible lines are detected for the four targets. For REBELS-04, the non-detection is unexpected given the ≥92% coverage of the redshift likelihood distribution and its estimated SFR of 40 M⊙ yr−1. Possible explanations for the faint [OIII]88μm emission (assuming a FWHM of 100 km s−1) include high ISM densities (>ncrit ≈ 510 cm−3) and low ionization parameters (log10 Uion ≲ −2.5). For REBELS-37, a subsequent detection of [CII]158μm (z = 7.643) confirmed it lay outside our scan range. For REBELS-11 and REBELS-13, it remains unclear if the non-detection is due to the depth of the line scan or redshift coverage. REBELS-04 and REBELS-37 show significant (≥3.8σ) dust continuum emission in Band 7. If the photometric redshift of REBELS-04 is accurate, i.e., $z_{\mathrm{phot}}=8.57^{+0.10}_{-0.09}$ or $z_{\mathrm{phot}}=8.43^{+0.10}_{-0.10}$ accounting for additional neutral hydrogen in the circumgalactic medium, REBELS-04 would constitute the most distant dust-detected galaxy identified with ALMA to date. Additional Band 6 dust observations of REBELS-37 constrain the shape of the far-IR SED, ruling out cold dust temperatures (≲ 28 K) at 3σ. Further insight into these galaxies will require spectroscopic redshifts and deeper multi-band dust observations.

Abstract:

We show, using the pseudo-Cl technique, how to estimate cosmic shear and galaxy–galaxy lensing power spectra that are insensitive to the effects of multiple sources of lensing bias including source-lens clustering, magnification bias, and obscuration effects. All of these effects are of significant concern for ongoing and near-future Stage-IV cosmic shear surveys. Their common attribute is that they all introduce a cosmological dependence into the selection of the galaxy shear sample. Here, we show how a simple adaptation of the pseudo-Cl method can help to suppress these biases to negligible levels in a model-independent way. Our approach is based on making pixelized maps of the shear field and then using a uniform weighting of those shear maps when extracting power spectra. To produce unbiased measurements, the weighting scheme must be independent of the cosmological signal, which makes the commonly used inverse-variance weighting scheme unsuitable for cosmic shear measurements. We demonstrate this explicitly. A frequently cited motivation for using inverse-variance weights is to minimize the errors on the resultant power spectra. We find that, for a Stage-IV-like survey configuration, this motivation is not compelling: the precision of power spectra recovered from uniform-weighted maps is only very slightly degraded compared to those recovered from an inverse-variance analysis, and we predict no degradation in cosmological parameter constraints. We suggest that other 2-point statistics, such as real-space correlation functions, can be rendered equally robust to these lensing biases by applying those estimators to pixelized shear maps using a uniform weighting scheme.

Abstract:

Redshift-independent distances underpin much of astrophysics, and there exists a plethora of methods to estimate them. However, the extent to which the distances they imply are consistent, while crucial for the integrity of the distance ladder, has been little explored. We construct a statistical framework to assess both internal (between measurements with the same method) and external (between method) consistency by comparing differences between distances to their quoted statistical uncertainties in the National Aeronautics and Space Administration/Infrared Processing and Analysis Center (NASA/IPAC) Extragalactic Data base of Distances (NED-D). 66 of the 76 indicators in NED-D are amenable to a consistency test by having at least two measurements to the same galaxy or at least one measurement to a galaxy also measured by another method. We find that only 12 of these methods produce self-consistent distances across literature determinations, of which seven are also consistent with distances to the same galaxies measured by all other methods. The most consistent six methods (M-stars luminosity, Novae, Masers, Globular Cluster Fundamental Plane, O- and B-type Supergiants, and BL Lac Luminosity) also give similar average distances to the mean of all indicators, while the 7th (Proper Motion) underestimates distances relative to the mean by 17.1 per cent. We also investigate consistency of Cepheid distances in the SH0ES 2022 catalogue, finding no evidence for unaccounted-for systematics. Our NED-D results imply that considerable work remains to obtain reliable distances by a multitude of methods, a crucial endeavour for constructing a multiply cross-checked and fully robust distance ladder.

Abstract:

The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20–30 million H α -emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k -d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission’s timeline, highlighting the software’s capability to handle large datasets efficiently.