Disaster, infrastructure and participatory knowledge: the Planetary Response Network

Citizen Science: Theory and Practice Ubiquity Press 7:1 (2022) 21-21

Authors:

Brooke D Simmons, Chris Lintott, Steven Reece, Campbell Allen, Grant RM Miller, Rebekah Yore, David Jones, Sascha T Ishikawa, Tom Jardine-McNamara, Amy R Boyer, James E O’Donnell, Lucy Fortson, Danil Kuzin, Adam McMaster, Laura Trouille, Zach Wolfenbarger

Abstract:

There are many challenges involved in online participatory humanitarian response. We evaluate the Planetary Response Network (PRN), a collaboration between researchers, humanitarian organizations, and the online citizen science platform Zooniverse. The PRN uses satellite and aerial image analysis to provide stakeholders with high-level situational awareness during and after humanitarian crises. During past deployments, thousands of online volunteers have compared pre- and post-event satellite images to identify damage to infrastructure and buildings, access blockages, and signs of people in distress. In addition to collectively producing aggregated “heat maps” of features that are shared with responders and decision makers, individual volunteers may also flag novel features directly using integrated community discussion software. The online infrastructure facilitates worldwide participation even for geographically focused disasters; this widespread public participation means that high-value information can be delivered rapidly and uniformly even for large-scale crises. We discuss lessons learned from deployments, place the PRN’s distributed online approach in the context of more localized efforts, and identify future needs for the PRN and similar online crisis-mapping projects. The successes of the PRN demonstrate that effective online crisis mapping is possible on a generalized citizen science platform such as the Zooniverse.

Looking at the distant universe with the MeerKAT array: discovery of a luminous OH megamaser at z > 0.5

Astrophysical Journal Letters IOP Science 931:1 (2022) L7

Authors:

Marcin Glowacki, Jordan D Collier, Amir Kazemi-Moridani, Bradley Frank, Hayley Roberts, Jeremy Darling, Hans-Rainer Kloeckner, Nathan Adams, Andrew J Baker, Matthew Bershady, Tariq Blecher, Sarah-Louise Blyth, Rebecca Bowler, Barbara Catinella, Laurent Chemin, Steven M Crawford, Catherine Cress, Romeel Dave, Roger Deane, Erwin de Blok, Jacinta Delhaize, Kenneth Duncan, Ed Elson, Sean February, Eric Gawiser, Peter Hatfield, Julia Healy, Patricia Henning, Kelley M Hess, Ian Heywood, Benne W Holwerda, Munira Hoosain, John P Hughes, Zackary L Hutchens, Matt Jarvis, Sheila Kannappan, Neal Katz, Dusan Keres, Marie Korsaga, Renee C Kraan-Korteweg, Philip Lah, Michelle Lochner, Natasha Maddox, Sphesihle Makhathini, Gerhardt R Meurer, Martin Meyer, Danail Obreschkow, Se-Heon Oh, Tom Oosterloo

Abstract:

In the local universe, OH megamasers (OHMs) are detected almost exclusively in infrared-luminous galaxies, with a prevalence that increases with IR luminosity, suggesting that they trace gas-rich galaxy mergers. Given the proximity of the rest frequencies of OH and the hyperfine transition of neutral atomic hydrogen (H i), radio surveys to probe the cosmic evolution of H i in galaxies also offer exciting prospects for exploiting OHMs to probe the cosmic history of gas-rich mergers. Using observations for the Looking At the Distant Universe with the MeerKAT Array (LADUMA) deep H i survey, we report the first untargeted detection of an OHM at z > 0.5, LADUMA J033046.20-275518.1 (nicknamed "Nkalakatha"). The host system, WISEA J033046.26-275518.3, is an infrared-luminous radio galaxy whose optical redshift z ≈ 0.52 confirms the MeerKAT emission-line detection as OH at a redshift z OH = 0.5225 ± 0.0001 rather than H i at lower redshift. The detected spectral line has 18.4σ peak significance, a width of 459 ± 59 km s-1, and an integrated luminosity of (6.31 ± 0.18 [statistical] ± 0.31 [systematic]) × 103 L ⊙, placing it among the most luminous OHMs known. The galaxy's far-infrared luminosity L FIR = (1.576 ±0.013) × 1012 L ⊙ marks it as an ultraluminous infrared galaxy; its ratio of OH and infrared luminosities is similar to those for lower-redshift OHMs. A comparison between optical and OH redshifts offers a slight indication of an OH outflow. This detection represents the first step toward a systematic exploitation of OHMs as a tracer of galaxy growth at high redshifts.

LyMAS reloaded: improving the predictions of the large-scale Lyman-α forest statistics from dark matter density and velocity fields

Monthly Notices of the Royal Astronomical Society Oxford University Press 514:3 (2022) 3222-3245

Authors:

S Peirani, S Prunet, S Colombi, C Pichon, Dh Weinberg, C Laigle, G Lavaux, Y Dubois, J Devriendt

Abstract:

We present LyMAS2, an improved version of the ‘Lyman-α Mass Association Scheme’ aiming at predicting the large-scale 3D clustering statistics of the Lyman-α forest (Ly α) from moderate-resolution simulations of the dark matter (DM) distribution, with prior calibrations from high-resolution hydrodynamical simulations of smaller volumes. In this study, calibrations are derived from the HORIZON-AGN suite simulations, (100 Mpc h)−3 comoving volume, using Wiener filtering, combining information from DM density and velocity fields (i.e. velocity dispersion, vorticity, line-of-sight 1D-divergence and 3D-divergence). All new predictions have been done at z = 2.5 in redshift space, while considering the spectral resolution of the SDSS-III BOSS Survey and different DM smoothing (0.3, 0.5, and 1.0 Mpc h−1 comoving). We have tried different combinations of DM fields and found that LyMAS2, applied to the HORIZON-NOAGN DM fields, significantly improves the predictions of the Ly α 3D clustering statistics, especially when the DM overdensity is associated with the velocity dispersion or the vorticity fields. Compared to the hydrodynamical simulation trends, the two-point correlation functions of pseudo-spectra generated with LyMAS2 can be recovered with relative differences of ∼5 per cent even for high angles, the flux 1D power spectrum (along the light of sight) with ∼2 per cent and the flux 1D probability distribution function exactly. Finally, we have produced several large mock BOSS spectra (1.0 and 1.5 Gpc h−1) expected to lead to much more reliable and accurate theoretical predictions.

The ALMA REBELS Survey: cosmic dust temperature evolution out to z ∼ 7

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 513:3 (2022) 3122-3135

Authors:

L Sommovigo, A Ferrara, A Pallottini, P Dayal, RJ Bouwens, R Smit, E da Cunha, I De Looze, RAA Bowler, J Hodge, H Inami, P Oesch, R Endsley, V Gonzalez, S Schouws, D Stark, M Stefanon, M Aravena, L Graziani, D Riechers, R Schneider, P van der Werf, H Algera, L Barrufet, Y Fudamoto, APS Hygate, I Labbé, Y Li, T Nanayakkara, M Topping

A fast and reliable method for the comparison of covariance matrices

Monthly Notices of the Royal Astronomical Society Oxford University Press 513:4 (2022) 5438-5445

Authors:

Tassia Ferreira, Valerio Marra

Abstract:

Covariance matrices are important tools for obtaining reliable parameter constraints. Advancements in cosmological surveys lead to larger data vectors and, consequently, increasingly complex covariance matrices, whose number of elements grows as the square of the size of the data vector. The most straightforward way of comparing these matrices, in terms of their ability to produce parameter constraints, involves a full cosmological analysis, which can be very computationally expensive. Using the concept and construction of compression schemes, which have become increasingly popular, we propose a fast and reliable way of comparing covariance matrices. The basic idea is to focus only on the portion of the covariance matrix that is relevant for the parameter constraints and quantify, via a fast Monte Carlo simulation, the difference of a second candidate matrix from the baseline one. To test this method, we apply it to two covariance matrices that were used to analyse the cosmic shear measurements for the Dark Energy Survey Year 1. We found that the uncertainties on the parameters change by 2.6 per cent, a figure in agreement with the full cosmological analysis. While our approximate method cannot replace a full analysis, it may be useful during the development and validation of codes that estimate covariance matrices. Our method takes roughly 100 times less CPUh than a full cosmological analysis.