Mathematical Physics, Quantum Fields and ML
We can make use of unsupervised machine learning techniques to construct phase diagrams for 4-dimensional supersymmetric gauge theories related to toric Calabi-Yau 3-folds. These phase diagrams help us to study gauge theory phenomena such as Seiberg duality.
More about this work can be found here:
"Unsupervised Machine Learning Techniques for Exploring
Tropical Coamoeba, Brane Tilings and Seiberg Duality"
Rak-Kyeong Seong
Physical Review D 108, 106009 (2023)
https://doi.org/10.1103/PhysRevD.108.106009
https://arxiv.org/abs/2309.05702
Brane Brick Models are Type IIA brane configurations that encode 2d supersymmetric gauge theories corresponding to toric Calabi-Yau 4-folds. Brane Brick Models can be used to study gauge theory phenomena such as Gadde-Gukov-Putrov triality.
More about this work can be found here:
"Brane Brick Models, Toric Calabi-Yau 4-Folds and 2d (0,2) Quivers"
Sebastian Franco, Sangmin Lee, Rak-Kyeong Seong
Journal of High Energy Physics (JHEP), 1602:047, 2016
https://doi.org/10.1007/JHEP02(2016)047
http://arxiv.org/abs/1510.01744
Calabi-Yau mirror symmetry leads to a geometric unification of dualities in different spacetime dimensions. It is a powerful that helped us to discover new gauge theory phenomena in different spacetime dimensions.
More about this work can be found here:
"Brane Brick Models in the Mirror"
Sebastian Franco, Sangmin Lee, Rak-Kyeong Seong, Cumrun Vafa
Journal of High Energy Physics (JHEP), 1702:106, 2017
https://doi.org/10.1007/JHEP02(2017)106
http://arxiv.org/abs/1609.01723
By studying various geometrical quantities for non-compact toric Calabi-Yau n-folds defined as cones over Gorenstein Fano varieties, we were able to conjecture new bounds for the volume of the associated Sasaki-Einstein base manifolds.
More about this work can be found here:
"Calabi-Yau Volumes and Reflexive Polytopes"
Yang-Hui He, Rak-Kyeong Seong, Shing-Tung Yau
Communications in Mathematical Physics, 361, 155–204 (2018)
https://doi.org/10.1007/s00220-018-3128-6
https://arxiv.org/abs/1704.03462
arXiv pre-prints
Rak-Kyeong Seong
Google Scholar Profile
Rak-Kyeong Seong
https://inspirehep.net/authors/
1069262