A multi-point bootstrap approach to quantum field theory

Project funded by Fundação para a Ciência e a Tecnologia, I.P. (FCT), grant 2024.04788.BD. Runs 2024-09-01 to 2028-08-31. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-06-25); national funding data, not CORDIS. Abstract given by the source: Quantum field theory (QFT) is essential in describing several physical phenomena, ranging from condensed-matter systems to high-energy particle collisions. Unfortunately, a considerable portion of physical systems exhibit a strongly coupled nature, eluding many conventional theoretical methods. A way to tackle these systems is grounded on the old idea of deriving constraints from imposing consistency conditions based on the symmetries and analytical properties of the underlying theory. This is the essence of the conformal and S-matrix bootstrap programs. An important problem which only recently has been able to be explored by bootstrap methods is the study of higher-point functions in CFTs. These are complex quantities worth analyzing since in principle they encode more information than a finite number of four-point correlators and have a non-trivial structure. This project seeks to explore these multi-point objects and extract additional information which may be relevant for CFTs and QFTs in general.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Fundação para a Ciência e a Tecnologia, I.P. (FCT). Retrieved 2026-10-28. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: The project "A multi-point bootstrap approach to quantum field theory" is funded by FCT with grant 2024.04788.BD, running from September 1, 2024, to August 31, 2028. It aims to explore higher-point functions in conformal field theories using bootstrap methods. Suggested technology pillar: simulation. Generated by AI from the public source text; it may contain errors and the original source is authoritative.