891 research outputs found
Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field
No full textR. Pearce-Casey et al. -- This paper is published on behalf of the Euclid Consortium.The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. As a result, machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates, such that the usage of CNNs in lens identification has increased. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate, thus producing a pure and complete sample of strong lens candidates from Euclid with a limited need for visual inspection. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. This work is vital in preparing our CNN-based detection pipelines to be able to produce a pure sample of the >100 000 strong gravitational lensing systems widely predicted for Euclid. We select all sources with VIS IE < 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just ∼11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artifacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected ∼105 lensing systems in Euclid, this implies 106 objects for human classification, which while very large is not in principle intractable and not without precedent.This work has made use of the Early Release Observations (ERO) data from the Euclid mission of the European Space Agency (ESA), 2024, https://doi.org/10.57780/esa-qmocze3. R. Pearce-Casey thanks the Science and Technology Facilities Council (STFC) for support under grant ST/W006839/1. V.B. and C.T. acknowledge the INAF grant 2022 LEMON. A.M.G. acknowledges the support of project PID2022-141915NB-C22 funded by MCIU/AEI/10.13039/501100011033 and FEDER/UE. M.W. is a Dunlap Fellow. The Dunlap Institute is funded through an endowment established by the David Dunlap family and the University of Toronto. SHS thanks the Max Planck Society for support through the Max Planck Fellowship. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (LENSNOVA: grant agreement No 771776). This research is supported in part by the Excellence Cluster ORIGINS which is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC2094 – 390783311. L.M. acknowledges financial support from the South African Department of Science and Innovation’s National Research Foundation under the ISARP RADIOMAP Joint Research Scheme (DSI-NRF Grant Number 150551) and the CPRR Projects (DSI-NRF Grant Number SRUG2204254729) This work made use of Astropy: a community-developed core Python package and an ecosystem of tools and resources for astronomy (Astropy Collaboration 2013, 2018, 2022), NumPy (Harris et al. 2020) and Matplotlib (Hunter 2007). The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Agenzia Spaziale Italiana, the Austrian Forschungsförderungsgesellschaft funded through BMK, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum für Luftund Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d’Etudes Spatiales, the Fundação para a Ciência e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovación y Universidades, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Research Council of Finland, the Romanian Space Agency, the State Secretariat for Education, Research, and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid web site (http://www.euclid-ec.org).Peer reviewe
Letter From Ruby Doris Smith to her Mother, circa 1964
No full textCorrespondence from Ruby Doris Smith to her mother about being in Conakry, Guinea in West Africa. 4 pages
Letter to Mother From Ruby D. Smith, June 21, 1961
No full textLetter from Ruby Doris Smith in Hinds County Jail, Jackson, Mississippi, to her mother. Smith was in jail for taking part in the Freedom Rides. 1 page
[Prisoner medical records describing the condition of Jack Ruby]
No full textPartially illegible prisoner medical records by an unknown author, on photocopied index cards. The records describe the condition of Jack Ruby upon his arrest
[Prisoner medical records describing the condition of Jack Ruby]
No full textPartially illegible prisoner medical records by an unknown author, on photocopied index cards. The records describe the condition of Jack Ruby upon his arrest and a letter requesting examination by the Dallas Police Department and the Federal Bureau of Investigation
[Prisoner medical records describing the condition of Jack Ruby]
No full textPartially illegible prisoner medical records by an unknown author, on photocopied index cards. The records describe the condition of Jack Ruby upon his arrest
[Prisoner medical records describing the condition of Jack Ruby]
No full textPartially illegible prisoner medical records by an unknown author, on photocopied index cards. The records describe the condition of Jack Ruby upon his arrest
[Prisoner medical records describing the condition of Jack Ruby]
No full textPartially illegible prisoner medical records by an unknown author, on photocopied index cards. The records describe the condition of Jack Ruby upon his arrest
Letter to Mother From Ruby D. Smith, June 10, 1961
No full textTo her mother, the letter is from Ruby Doris Smith in Hinds County Jail, Jackson, Mississippi. Smith was in jail for taking part in the Freedom Rides. 2 pages
Mary Ann Smith Wilson, Ruby Doris Smith Robinson Collection on Student Activism
No full textThe Mary Ann Smith Wilson - Ruby Doris Smith Robinson Collection on Student Activism spans the dates 1948-2008 with the bulk of the material dated 1960-1967. The collection documents both Ruby Doris Smith Robinson's and Mary Ann Smith Wilson's participation in the civil rights movement and the organizations with which they were affiliated. Although the collection documents both sisters' activities, the bulk of the collection reflects Ruby Doris Smith Robinson’s activism activities in the civil rights movement. Also included in the collection are photographs, correspondences, news articles, programs, reports, and flyers.
At the AUC Robert W. Woodruff Library, we are always striving to improve our digital collections. We welcome additional information about people, places, or events depicted in any of the works in this collection. To submit information, please contact us at [email protected]
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