Story of 3 papers - Yang Mills, Social Collider, Machine Learning, Vector Bundles, Calabi–Yau Manifolds

Hey Readers,

Thanks to 50,000 views of my last blog. Lot of my readers might remember me writing about Yang Mills, Social Collider, Social Networks and Neural Networks as well 12 years back (Remember SuperSymmetric Yang Mills N= 4 -> N= 6 and generalized solution through network sciences & neural networks??) Also, my hint in kdnuggets on Yang Mills & Social Collider - https://www.kdnuggets.com/2013/11/yang-mills-million-dollar-connection-twitter-quantum-physics.html

Here are 4 important papers which have come out of it -

1. Quantum Walk Model for Idea Propagation in Social Network and Group Decision Making - https://www.researchgate.net/publication/351631537_A_Quantum_Walk_Model_for_Idea_Propagation_in_Social_Network_and_Group_Decision_Making

2. Emergent Attention on Yang-Mills Space of Connections - https://lukepereira.github.io/notebooks/documents/2021-moduli-attention/main.pdf

3. Machine learning line bundle connections - machine learning for finding numerical hermitian Yang–Mills connections on line bundles over Calabi–Yau manifolds. Defining an appropriate loss function and focusing on the examples of an elliptic curve, a K3 surface and a quintic threefold, we show that neural networks can be trained to give a close approximation to hermitian Yang–Mills connections - https://www.sciencedirect.com/science/article/pii/S037026932200106X

4. Convergence of Hermitian-Yang-Mills Connections on Kähler Surfaces and mirror symmetry - https://arxiv.org/pdf/math/0301324.pdf

 

Also Remember my last month's Orchestration on CNNs & Swarm on Calabi–Yau & Super-Symmetric Yang Mills -