分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Measurements of The Hubble-Lemaitre constant from early- and local-universe observations show a significant discrepancy. In an attempt to understand the origin of this mismatch, independent techniques to measure H0 are required. One such technique, strong lensing time delays, is set to become a leading contender amongst the myriad methods due to forthcoming large strong lens samples. It is therefore critical to understand the systematic effects inherent in this method. In this paper, we quantify the influence of additional structures along the line-of-sight by adopting realistic light cones derived from the CosmoDC2 semi-analytical extra-galactic catalogue. Using multiple lens plane ray-tracing to create a set of simulated strong lensing systems, we have investigated the impact of line-of-sight structures on time-delay measurements and in turn, on the inferred value of H0. We have also tested the reliability of existing procedures for correcting for line-of-sight effects. We find that if the integrated contribution of the line-of-sight structures is close to a uniform mass sheet, the bias in H0 can be adequately corrected by including a constant external convergence $\kappa_{ext}$ in the lens model. However, for realistic line-of-sight structures comprising many galaxies at different redshifts, this simple correction overestimates the bias by an amount that depends linearly on the median external convergence. We, therefore, conclude that lens modelling must incorporate multiple lens planes to account for line-of-sight structures for accurate and precise inference of H0.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure $H_0$, such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24,440,816 candidate QSOs contained in the 9th data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours of a group's members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identify 620 new candidate multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI. The catalogues and images of the candidates in this work are available online (https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure $H_0$, such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24,440,816 candidate QSOs contained in the 9th data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours of a group's members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identify 620 new candidate multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI. The catalogues and images of the candidates in this work are available online (https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Karina Rojas
Thomas E. Collett
Daniel Ballard
Mark R. Magee
Simon Birrer
Elizabeth Buckley-Geer.
James H. H. Chan
Benjamin Clément
José M. Diego
Fabrizio Gentile
Jimena González
Rémy Joseph
Jorge Mastache
Stefan Schuldt
Crescenzo Tortora
Tomás Verdugo
Aprajita Verma
Tansu Daylan
Martin Millon
Neal Jackson
摘要： We investigate the ability of human 'expert' classifiers to identify strong gravitational lens candidates in Dark Energy Survey like imaging. We recruited a total of 55 people that completed more than 25$\%$ of the project. During the classification task, we present to the participants 1489 images. The sample contains a variety of data including lens simulations, real lenses, non-lens examples, and unlabeled data. We find that experts are extremely good at finding bright, well-resolved Einstein rings, whilst arcs with $g$-band signal-to-noise less than $\sim$25 or Einstein radii less than $\sim$1.2 times the seeing are rarely recovered. Very few non-lenses are scored highly. There is substantial variation in the performance of individual classifiers, but they do not appear to depend on the classifier's experience, confidence or academic position. These variations can be mitigated with a team of 6 or more independent classifiers. Our results give confidence that humans are a reliable pruning step for lens candidates, providing pure and quantifiably complete samples for follow-up studies.
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