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Gravitational Lensing Analysis for Data Intensive Upcoming Surveys

Objective

Gravitational lensing is one of the major tools to address the long-standing problems in astrophysics and cosmology, such as dark energy, dark matter, and black hole physics. Progress has so far been limited by the small number of known lensed systems and the intricate nature of the phenomenon, requiring painstaking handcrafted modelling approaches, hard-to-procure high-quality data, and lengthy computations. Upcoming all-sky surveys will revolutionize the field by discovering orders-of-magnitude more lenses and providing adequate information to understand them in depth. Mining these massive troves of data for the new astrophysical discoveries they hold requires a paradigm shift in our analysis approaches, providing high flexibility, automation, and adaptability to a much larger parameter space, in order to determine critical lensing and physical parameters. GLADIUS has the potential to spearhead gravitational lensing science with the next generation of observations by: i) increasing the accuracy and flexibility of the time delay method to measure cosmic expansion ii) disentangling baryonic and dark matter in galaxies through lensing self-consistently and iii) providing accurate predictions of those rare microlensing events, rich in information on quasar structure and black hole environments. To this end, existing state-of-the-art traditional modelling approaches and simulations will be fused with the groundbreaking machine learning framework of Deep Learning and extended through powerful methodologies, like supervised and generative learning, dramatically increasing the scope of gravitational lensing studies. The resulting data-intensive framework will be directly applicable to the high-resolution imaging and monitoring data products of the upcoming Euclid and LSST surveys. GLADIUS is perfectly aligned with the MSCA scope, allowing me to combine my lens modelling expertise with the leading role of EPFL in major global observational and modelling projects.

Fields of science (EuroSciVoc)

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Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2019

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Coordinator

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 191 149,44
Address
BATIMENT CE 3316 STATION 1
1015 LAUSANNE
Switzerland

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Region
Schweiz/Suisse/Svizzera Région lémanique Vaud
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 191 149,44
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