Project description
Machine learning to answer particle physics questions
The discovery of the Higgs boson in 2012 was a pivotal moment in the history of particle physics. Nevertheless, how this elusive particle interacts with itself and other heavy bosons remains largely unknown due to measurement limitations at the Large Hadron Collider. To answer this question, the ERC-funded ARTEMIS project aims to pioneer an analytical framework for data processing. Using machine learning techniques, the project will improve detection and data precision so that researchers will be able to study the universe’s most basic building blocks. The findings will ultimately pave the way for a deeper understanding of the laws governing our physical world.
Objective
The discovery of the Higgs boson marked a milestone in particle physics, but crucial questions about how the Higgs boson interacts with itself and with heavy bosons remain unanswered. These interactions hold the key to understanding fundamental aspects of our universe, from particle mass generation to the nature of the cosmic phase transition in the early universe. Current measurements at the Large Hadron Collider (LHC) can only place weak constraints on these interactions due to significant limitations in our ability to identify and record the relevant collision events in real-time.
This project introduces a revolutionary approach to overcome these limitations by developing advanced machine learning techniques for real-time event selection in particle physics experiments. The current approach discards up 50\% of potentially valuable collision events involving hadronic decays of the Higgs boson. By implementing sophisticated neural networks that can process collision data fast, this project aims to double the detection efficiency for these crucial events. The proposed system will operate at different stages of the data-taking process, from specialized hardware (FPGAs) to traditional computing infrastructure.
The work will be carried out at the ATLAS experiment at CERN and will significantly enhance our ability to measure the Higgs boson's self-coupling, either leading to the discovery of new physics or placing stronger constraints on theories beyond the Standard Model. The PI brings extensive expertise in both Higgs physics and machine learning applications at the trigger level. An ERC Consolidator Grant will enable the formation of an independent research team with the necessary expertise to achieve these ambitious goals and advance our understanding of nature's fundamental interactions.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
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.
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.
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.
HORIZON-ERC - HORIZON ERC Grants
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-COG
See all projects funded under this callHost institution
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.
40126 Bologna
Italy
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.