{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/162097"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/162097","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Energy Flow in Particle Collisions","abstract":"In this thesis, I introduce a new bottom-up approach to quantum field theory and collider physics, beginning from the observable energy flow: the energy distribution produced by particle collisions. First, I establish a metric space for collision events by comparing their energy flows. I unify many ideas spanning multiple decades, such as observables and jets, as simple geometric objects in this new space. Second, I develop a basis of observables by systematically expanding in particle energies and angles, encompassing many existing observables and uncovering new analytic structures. I highlight how the traditional criteria for theoretical calculability emerge as consistency conditions, due to the redundancy of describing an event using particles rather than its energy flow. Finally, I propose a definition of particle type, or flavor, which makes use of only observable information. This definition requires refining the notion of flavor from a per-event label to a statistical category, and I showcase its direct experimental applicability at colliders. Throughout, I synthesize concepts from particle physics with ideas from statistics and computer science to expand the theoretical understanding of particle interactions and enhance the experimental capabilities of collider data analysis techniques.","abstract_html":"In this thesis, I introduce a new bottom-up approach to quantum field theory and collider physics, beginning from the observable energy flow: the energy distribution produced by particle collisions. First, I establish a metric space for collision events by comparing their energy flows. I unify many ideas spanning multiple decades, such as observables and jets, as simple geometric objects in this new space. Second, I develop a basis of observables by systematically expanding in particle energies and angles, encompassing many existing observables and uncovering new analytic structures. I highlight how the traditional criteria for theoretical calculability emerge as consistency conditions, due to the redundancy of describing an event using particles rather than its energy flow. Finally, I propose a definition of particle type, or flavor, which makes use of only observable information. This definition requires refining the notion of flavor from a per-event label to a statistical category, and I showcase its direct experimental applicability at colliders. Throughout, I synthesize concepts from particle physics with ideas from statistics and computer science to expand the theoretical understanding of particle interactions and enhance the experimental capabilities of collider data analysis techniques.","abstract_has_math":false,"creators":["Metodiev, Eric Mario"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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First, I establish a metric space for collision events by comparing their energy flows. I unify many ideas spanning multiple decades, such as observables and jets, as simple geometric objects in this new space. Second, I develop a basis of observables by systematically expanding in particle energies and angles, encompassing many existing observables and uncovering new analytic structures. I highlight how the traditional criteria for theoretical calculability emerge as consistency conditions, due to the redundancy of describing an event using particles rather than its energy flow. Finally, I propose a definition of particle type, or flavor, which makes use of only observable information. This definition requires refining the notion of flavor from a per-event label to a statistical category, and I showcase its direct experimental applicability at colliders. Throughout, I synthesize concepts from particle physics with ideas from statistics and computer science to expand the theoretical understanding of particle interactions and enhance the experimental capabilities of collider data analysis techniques."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Energy Flow in Particle Collisions"]}]}],"canonical_facts":{"dc:contributor.advisor":["Thaler, Jesse"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Physics"],"dc:creator":["Metodiev, Eric Mario"],"dc:date.accessioned":["2025-07-29T17:17:39Z"],"dc:date.available":["2025-07-29T17:17:39Z"],"dc:date.issued":["2020-09"],"dc:description.abstract":["In this thesis, I introduce a new bottom-up approach to quantum field theory and collider physics, beginning from the observable energy flow: the energy distribution produced by particle collisions. First, I establish a metric space for collision events by comparing their energy flows. I unify many ideas spanning multiple decades, such as observables and jets, as simple geometric objects in this new space. Second, I develop a basis of observables by systematically expanding in particle energies and angles, encompassing many existing observables and uncovering new analytic structures. I highlight how the traditional criteria for theoretical calculability emerge as consistency conditions, due to the redundancy of describing an event using particles rather than its energy flow. Finally, I propose a definition of particle type, or flavor, which makes use of only observable information. This definition requires refining the notion of flavor from a per-event label to a statistical category, and I showcase its direct experimental applicability at colliders. 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