# States in generalized probabilistic models: an approach based in algebraic geometry

## TL;DR

This paper introduces a novel algebraic geometric approach to characterize states in generalized probabilistic models, enabling natural incorporation of invariant states within a non-commutative geometric probability framework.

## Contribution

It develops a non-commutative algebraic geometric framework for states in probabilistic models, advancing the theoretical understanding of invariant states.

## Key findings

- Provides a new algebraic geometric characterization of states
- Incorporates invariant states naturally into the framework
- Advances the theoretical foundation of probabilistic models

## Abstract

We present a characterization of states in generalized probabilistic models by appealing to a non-commutative version of geometric probability theory based on algebraic geometry techniques. Our theoretical framework allows for incorporation of invariant states in a natural way.