Ricci Flow, Markov Chain, Torus GAN, Yang Mills..

Hi guys,

It is 3 AM Friday Night. Few hints on Yang Mills & Calibi Yau since I have been writing a lot on these topics apart from 

1. CERN project to analyze Calabi Yau data 

2. Google project on Inception Neural Networks to analyze Calabi Yau 

3. A Julia Code on Machine learning of Vector Bundles (TBR)

4. Sobolev training of Neural Networks from Deepmind

My vision for Yang Mills was Mathematical Analogy which I developed working in the nights through 

1. Twitter and Social Collider, 

2. Use of Quantum Neural Nets - (recently published paper - Neural quantum states for supersymmetric quantum gauge theories sponsored by NTT  - https://arxiv.org/pdf/2112.05333.pdf

3. Projected Spaces, 

4. Ricci Flow and Markov chain, 

5. Vector Bundles (Gang Tian has published some awesome work in Vector Bundles and Ricci Flow in 2014), 

6. Random Vector - Salt vector (Salt vector was available in the encryption system of the banking software I was working on along with Convolutional Neural Networks etc. in 2011)... 

7. and  along with Twitter Cortex for Graph Neural Networks to analyze it Further..

.. part of which was later on published in Kdnuggets in 2013 in a very simplified format and visual way...  - https://www.kdnuggets.com/2013/11/yang-mills-million-dollar-connection-twitter-quantum-physics.html

What is yet to be seen is - 

1. Use of GraphGANs, TopologyGANs, Vector Bundles and CurvGANs for analyzing social Networks 

2. Ricci Flow to Analyze Social Networks - Available in my animation video on Ricci Flow (used to prove $1 million Poincare Conjecture) & its application in  Community detection in social networks which was an entry in Field Prize Math video Contest with your friends and colleagues 

3. Ricci Curvature and Markov Chain to Analyze social Networks along with HodgeNet for Link Prediction  

4. TorusGANs to analyze clusters in social networks further after running Ricci Flow Surgery as shown in my video of "PK - me - Prasad Kothari - giving answers to Grigori Perelman" - https://www.youtube.com/watch?v=z_pjsJisdHQ