Physics
Physics Colloquium: Exploring the string landscape with machine learning

Speaker: Dr. Nana Geraldine Cabo Bizet of the University of Guanajuato

Abstract: String theory is a successful candidate for quantum gravity unified with the other fundamental forces of nature: electro-weak and strong interactions. The richness of string theory arises from the extra hidden dimensions and could describe the physics of our universe, as well as a great variety of different consistent physical realities. The coupling of any quantum field theory to gravity poses severe restrictions. Theories which pass them, belong to the landscape, and the much larger set that doesn’t, belongs to the swampland. In recent years there have been ingenious conjectures that attempt to settle the criteria for the landscape. I will present an exploration of physical realities determined by extrema of a scalar potential V (vacua), with an artificial neural network coupled to a genetic algorithm. The physical setup is type IIB string theory with extra dimensions on a torus and fluxes. We find thousands of flux configurations yielding extrema, outperforming standard programming searches. We checked the Refined de Sitter Conjecture which restricts the theory description of current cosmological observations, such that unstable dS extrema (V>0) with small tachyonic mass and large energy are absent. I will mention other explorations where neural networks should play a crucial role in testing string theory as a fundamental description of particle physics and cosmology.

https://northeastern.zoom.us/j/93449472685?pwd=U0RLSnBwZE1DZU92SDZOMDJveUNGUT09
Physics Colloquium: Exploring the string landscape with machine learning