1.Yang-Mills, 2.Job Postings 3.Calabi-Yau 4.EconoPhysics, Divergent Recovery, TopologyGAN, Ricci Flow, Hodge theory

Hi Readers,

Yang Mills - First of all, lot of people must have seen my old orchestration on Yang Mills & Social Collider - Kdnuggets (and Neural Networks & Ricci Flow my old blog) - Here comes the absolutely brilliant paper on Yang Mills almost depicting the same - Emergent Attention on Yang-Mills Space of Connections - https://lukepereira.github.io/notebooks/documents/2021-moduli-attention/main.pdf (from Universidade Federal Fluminense .... Brazil & India is where so much of mathematical innovation is happening right ) Btw, you should watch my Ricci Flow video on Community detection & clustering to before reading this paper - https://www.youtube.com/watch?v=z_pjsJisdHQ 

Job Postings - This is an absolutely brilliant paper by Pratik Kothari on
Job Postings and Aggregate Stock Returns A much needed paper in today's time especially when CNBC announced Stock futures bounce as investors assess start of new quarter, bond market recession ( https://www.cnbc.com/2022/03/31/stock-market-futures-open-to-close-news.html ) 
- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3223141

Calabi Yau - While I am impressed with the Inception Neural Network for Complete Intersection Calabi-Yau 3-folds - inspired by Google’s Inception model to compute the Hodge number I am still waiting for application on DeepSwarm in Calabi Yau. 

EconoPhysics - Dr. Gita Gopinath mentions Divergent Recovery in her IMF blog. How to make it optimum can be a very cool question to solve through EconoPhysics?

Most of you might have read my previous blog on Ricci Curvature & Market Failure ( https://researchcircle.blogspot.com/2022/02/job-posting-paper-ricci-flow-economics.html ). And some of you might have seen my recent tweet on Hodge Theory & Trading Networks in the evening. ( https://twitter.com/Prasad_Kothari/status/1509634908125335559 )

The following figure is from Sandhu's paper (w.r.t. Average Ricci curvature over a 15-year span of the S&P 500 - Choosing a window of T = 22 days )

I have mentioned portrait divergence in the following orchestration to compare sub-topologies between the economic & trade networks.  

Reference - 

1. Symmetry perception with spiking neural networks -  https://www.nature.com/articles/s41598-021-85232-3

2. Comparing methods for comparing networks -  https://www.nature.com/articles/s41598-019-53708-y

3. Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network - https://ui.adsabs.harvard.edu/abs/2021Entrp..23..292W/abstract

4. Controlling Entropy via Discrete Ricci Flow Over Networks - https://arxiv.org/abs/1910.04560

The most interesting thing which I have not mentioned in this solution (apart from the code) is Thermodynamic Entropy in Quantum Statistics for Stock Market Networks from Shanghai University which talks about - Asian Financial Crisis (what could have been cool is use of HodgeNet (Graph Neural Networks for Edge Data) in it - https://ieeexplore.ieee.org/document/9049000

Edge entropy distribution of network structure before, during, and after the 1997 Asian financial crisis. (a)-(e) Bose-Einstein statistics. (d)-(f) Fermi-Dirac statistics.