Subordinate Average Structures on Random Walks
DOI:
https://doi.org/10.29020/nybg.ejpam.v18i1.5761Keywords:
Superaverage functions, Subordinate Structure, Parahperbolic, Bounded HyperbolicAbstract
In a random walk {N, p(x, y)} where N is an infinite graph and {p(x, y)} is a set of transition probabilities, if {p′(x, y)} is another set subordinate to the set {p(x, y)} such that p′(x, y) ≤ p(x, y) for all pairs (x, y) and p′(x, y) < p(x, y) for atleast one pair (x, y), then {N, p′(x, y)} can be identified as a Schr¨odinger network. In general, we consider the random walk {N, P ′} which is subordinate to {N, P} and discuss the relation between the classes of super-average functions defined by the transition probabilities sets {p(x, y)} and {p′(x, y)}. Moreover, we define {N, P ′} as parahyperbolic if 0 is the only bounded P ′-average function on N and study various potential-theoretic properties of parahyperbolic networks. We also give equivalent conditions for a random walk to be parahyperbolic. Finally, we discuss the relation between bounded P ′and P -average functions. average functions.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 M. Surya Priya, N. Nathiya
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Upon acceptance of an article by the European Journal of Pure and Applied Mathematics, the author(s) retain the copyright to the article. However, by submitting your work, you agree that the article will be published under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This license allows others to copy, distribute, and adapt your work, provided proper attribution is given to the original author(s) and source. However, the work cannot be used for commercial purposes.
By agreeing to this statement, you acknowledge that:
- You retain full copyright over your work.
- The European Journal of Pure and Applied Mathematics will publish your work under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
- This license allows others to use and share your work for non-commercial purposes, provided they give appropriate credit to the original author(s) and source.