*Tai-Danae Bradley* @math3ma

My PhD thesis “At the Interface of Algebra and Statistics” is now on the 
arXiv!  It uses basic tools in quantum physics to explore mathematical 
structure that's both algebraic & statistical. Curious? See my new 10m 
video on YouTube!! 

https://www.youtube.com/watch?v=wiadG3ywJIs
https://www.math3ma.com/blog/at-the-interface-of-algebra-and-statistics

http://arxiv.org/abs/2004.05631


At the Interface of Algebra and Statistics
Tai-Danae Bradley 
<https://arxiv.org/search/quant-ph?searchtype=author&query=Bradley%2C+T>
(Submitted on 12 Apr 2020)

This thesis takes inspiration from quantum physics to investigate 
mathematical structure that lies at the interface of algebra and 
statistics. The starting point is a passage from classical probability 
theory to quantum probability theory. The quantum version of a probability 
distribution is a density operator, the quantum version of marginalizing is 
an operation called the partial trace, and the quantum version of a 
marginal probability distribution is a reduced density operator. Every 
joint probability distribution on a finite set can be modeled as a rank one 
density operator. By applying the partial trace, we obtain reduced density 
operators whose diagonals recover classical marginal probabilities. In 
general, these reduced densities will have rank higher than one, and their 
eigenvalues and eigenvectors will contain extra information that encodes 
subsystem interactions governed by statistics. We decode this information, 
and show it is akin to conditional probability, and then investigate the 
extent to which the eigenvectors capture "concepts" inherent in the 
original joint distribution. The theory is then illustrated with an 
experiment that exploits these ideas. Turning to a more theoretical 
application, we also discuss a preliminary framework for modeling 
entailment and concept hierarchy in natural language, namely, by 
representing expressions in the language as densities. Finally, initial 
inspiration for this thesis comes from formal concept analysis, which finds 
many striking parallels with the linear algebra. The parallels are not 
coincidental, and a common blueprint is found in category theory. We close 
with an exposition on free (co)completions and how the free-forgetful 
adjunctions in which they arise strongly suggest that in certain 
categorical contexts, the "fixed points" of a morphism with its adjoint 
encode interesting information.


@philipthrift

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