64 citations · 150 across the 8 of their papers we have counts for
11 papers
Machine Learned Calabi-Yau Metrics and Curvature
Per Berglund, Giorgi Butbaia, Tristan Hübsch +4
Finding Ricci-flat (Calabi-Yau) metrics is a long standing problem in geometry with deep implications for string theory and phenomenology. A new attack on this problem uses neural…
Neural Network Approximations for Calabi-Yau Metrics
Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra
Ricci flat metrics for Calabi-Yau threefolds are not known analytically. In this work, we employ techniques from machine learning to deduce numerical flat metrics for the Fermat qu…
Time-dependent and time-independent SIR models applied to the COVID-19 outbreak in Argentina, Brazil, Colombia, Mexico and South Africa
Nana Geraldine Cabo Bizet, Damián Kaloni Mayorga Peña
We consider the SIR epidemiological model applied to the evolution of COVID-19 with two approaches. In the first place we fit a global SIR model, with time delay, and constant para…
Baryons from Mesons: A Machine Learning Perspective
Yarin Gal, Vishnu Jejjala, Damian Kaloni Mayorga Pena +1
Quantum chromodynamics (QCD) is the theory of the strong interaction. The fundamental particles of QCD, quarks and gluons, carry colour charge and form colourless bound states at l…
Leaving the Swampland: Non-geometric fluxes and the Distance Conjecture
Nana Cabo Bizet, Cesar Damian, Oscar Loaiza-Brito +1
We study a Type IIB isotropic toroidal compactification with non-geometric fluxes. Under the assumption of a hierarchy on the moduli, an effective scalar potential is constructed s…
Three-Family Particle Physics Models from Global F-theory Compactifications
Mirjam Cvetic, Denis Klevers, Damián Kaloni Mayorga Peña +2
We construct four-dimensional, globally consistent F-theory models with three chiral generations, whose gauge group and matter representations coincide with those of the Minimal Su…