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The Department of Physics & Astronomy Colloquium Speaker Series presents: "Strings of Data: Aspects of String Phenomenology through the lens of Machine Learning" with Damián Kaloni Mayorga Peña, University of the Witwatersrand, Johannesburg, Gauteng, South Africa.
Thursday, March 25, from 9AM to 10:15AM
Join us on Zoom: uleth.zoom.us/j/99069795964
String theory is a leading candidate for a theory of quantum gravity. Instead of providing a single model with all the desired features of the real world, it provides a landscape of valid models. Deriving the standard model of particle physics from string theory amounts to looking for a needle in a haystack. In the first part of the talk, I discuss human efforts to obtain phenomenologically realistic models from various branches of string theory. As large datasets are inherent to string models (compactifications), In the second part I discuss various Machine Learning efforts to analyze and identify relevant features in concrete examples: (a) Obtaining the metric of Calabi-Yau compactifications, (b) Testing swampland conjectures in toroidal compactifications.
Contact:
Catherine Drenth | catherine.drenth@uleth.ca | (403) 329-2280 | uleth.ca/artsci/physics-astronomy