Ouroboros Functionals, Families of Ouroboros Functions, and Their Relationship to Partial Differential Equations and Probability Theory

TL;DR

This paper introduces Ouroboros functionals and their spaces, linking them to PDEs and probability theory, and demonstrates their utility in solving linear PDEs and reinterpreting expected values.

Contribution

It extends the Ouroboros function theory by defining functionals and spaces, and connects these concepts to PDEs and probabilistic measure theory.

Findings

Ouroboros functions solve certain linear PDEs.

Reframing expected value as an Ouroboros functional offers new insights.

Introduction of Ouroboros functionals and their spaces expands the theoretical framework.

Abstract

Previously, we have introduced a very small number of examples of what we call Ouroboros functions. Using our already established theory of Ouroboros spaces and their functions, we will provide a set of families of Ouroboros functions that bolster our overall understanding of the Ouroboros spaces. From here, we extend the theory of Ouroboros functions by introducing Ouroboros functionals and Ouroboros functional spaces. Furthermore, we re-frame the expected value of a random variable as an Ouroboros functional, which proves to be more intuitive in view of probabilistic measure theory. We then show that these Ouroboros functions have additional applications, as they are general solutions to certain elementary linear first order partial differential equations (PDEs). We conclude by elaborating upon this connection and discussing future endeavors, which will be centered on answering a given hypothesis.