Strong Gravitational Lensing in the Era of Big Data (Iau S381)

During recent decades, strong gravitational lensing has become a powerful tool to study astronomical objects with widely different physical scales. It has also proven to be a promising diagnostic that can solve outstanding problems in cosmology. Now is a critical time for strong lensing research, as forthcoming large surveys (Euclid, Roman Space Telescope, Rubin Observatory and CSST) will map the entire sky and increase the number of known lenses from a few hundred to around 100,000. Concurrently, observations of lenses with current and forthcoming instruments (ALMA, JWST, E-ELT) will spatially resolve scales that are beyond the reach of telescopes for objects in the distant Universe. These new data will revolutionise our understanding of galaxy and structure formation, and offer unprecedented cosmological applications. In IAU Symposium 381, members of observational and theoretical communities review our preparedness for this new era, to discuss advanced statistical techniques, and to foster new collaborations.

Summary

Strong gravitational lensing has become a powerful tool to study astronomical objects with widely different physical scales and to probe outstanding problems in cosmology. IAU S381 reviews our preparedness for this new era, as forthcoming large surveys and instruments will revolutionise our understanding of diverse areas of astrophysics.

Product details

• Assisted by: Hannah (Max Planck Institute for Astrophysics Stacey (Editor), Alessandro (Shanghai Jiao Tong University Sonnenfeld (Editor), Claudio (Universita degli Studi di Milano) Grillo (Editor), Alessandro Sonnenfeld (Editor), Claudio Grillo (Editor), Hannah Stacey (Editor)
• Authors: Hannah (Max Planck Institute for Astrophys Stacey
• Publisher: Cambridge University Press ELT
• Content: Book
• Product form: Hardback
• Publication date: 30.04.2024
• Subject: Natural sciences, medicine, IT, technology > Physics, astronomy > Astronomy
• EAN: 9781009398992
• ISBN: 978-1-0-0939899-2
• Pages: 170
• Series: Proceedings of the International Astronomical Union Symposia and Colloquia
• Subjects: machine learning, Astrophysics, Gravity, SCIENCE / Physics / Astrophysics, pattern recognition, Astronomical observation: observatories, equipment & methods