Project description
Extending the applicability of bootstrap methods
Understanding interacting emergent phenomena has been challenging, but new approaches suggest that studying symmetries and consistency conditions can yield remarkable results, as demonstrated by successes in conformal and amplitude bootstrap methods. With the support of the Marie Skłodowska-Curie Actions programme, the HeI project aims to extend and improve the applicability of bootstrap methods by combining it with other techniques. It also seeks to explore the conformal window of quantum chromodynamics (QCD)-like theories and enhance our understanding of QCD physics by refining partonic distribution functions of quarks and gluons in nuclear matter. Additionally, the project will integrate AI and machine learning techniques with innovative research in theoretical physics.
Objective
Understanding the basic building blocks of Nature has led to the Standard Model, a non abelian quantum field theory with particles and glue that explains within a single framework the forces between the basic constituents of matter. However, the description of strongly coupled emergent phenomena has remained a hard problem to solve, especially with traditional methods. In recent years, new techniques have challenged this difficulty by showing that an optimized knowledge of symmetries and consistency conditions actually leads to unprecedented quantitative results. Both the conformal and the amplitude bootstrap have proven this idea to be successful. A first objective of the High-energy Intelligence -HeI- project is to extend the horizon of applicability of bootstrap methods by finding better constraints and more rigorous predictions, eg. as path towards quantum chromodynamics (QCD) study the conformal window of QCD-like theories, study integrable and supersymmetric theories, and for quantum gravity, study those theories that have a gravitational dual within string theory. A second objective of the HeI project, specific and original, is to push the boundaries of our understanding of QCD physics, by obtaining the most refined partonic distribution functions of quarks and gluons in nuclear matter. A third objective, timely and novel in the proposed approach, is to combine an Artificial Intelligence and Machine Learning training with cutting-edge research in theoretical physics, having in mind neural networks designs that can be trained on partial data sets, and at the same time, solve the non-perturbative constraint equations coming from theory.
The HeI project, for the first time, brings together many scientists working on related aspects of high-energy physics but with different areas of specializations, to make a collaborative scientific breakthrough, through secondments to leading research institutes in Brazil, Canada, Switzerland, and the Jefferson Laboratories.
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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencestheoretical physicsparticle physicsgluons
- natural sciencesphysical sciencestheoretical physicsparticle physicsquarks
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff ExchangesCoordinator
4099-002 Porto
Portugal