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Prof. Eluned A Smith
Assistant Professor of Physics
Primary DLC
Department of Physics
MIT Room:
24-417
(617) 253-4800
eluned@mit.edu
https://physics-mit-edu.ezproxyberklee.flo.org/faculty/eluned-smith/
Areas of Interest and Expertise
Particle Physics Experiment
Research Summary
Professor Smith’s research uses rare beauty decays, measured with the LHCb detector at CERN, to search for new fundamental particles at mass scales above the collision energy of the LHC.
The Standard Model of particle physics describes all known fundamental particles and their interactions. However, there are many aspects of our universe that the Standard Model fails to explain, pointing to the existence of physics Beyond the Standard Model (BSM).
Heavy BSM particles can mediate known Standard Model decays, altering their properties. Comparing the decay properties of these known particles to their predictions therefore provides sensitivity to BSM effects. This approach probes very heavy BSM energy scales, which would otherwise be inaccessible at the LHC.
Professor Smith’s research uses rare decays of particles containing beauty quarks (B hadrons). These decays are referred to as electroweak penguin decays, named after their dominant Feynman diagram.
Over the last decade, significant tensions with the SM have been seen in rare electroweak penguin decays, in a phenomena referred to as the Flavour-Anomalies. However, these decays are also sensitive to poorly described QCD effects, which could mimic BSM signatures. Prof. Smith and her group specialize in using novel high-dimensional fits to data to both constrain the properties of the potential BSM signatures behind these anomalies and to isolate and constrain the magnitude of possible QCD contributions. In doing so, her work aims to resolve whether the Flavour-Anomalies are misunderstood QCD or the first sign of BSM physics at the LHC.
Her group will also contribute to R&D for the next upgrade of the LHCb detector, due to start data-taking in around 10 years time. Her group will focus on developing fast Machine Learning algorithms to reduce data throughput to more manageable levels in real time
Recent Work
Related Faculty
Prof. Max Erik Tegmark
Professor of Physics
Prof. June L Matthews
Professor of Physics, Emerita
Prof. Samuel C C Ting
Thomas D Cabot Institute Professor of Physics