Unique Presentation Identifier:
35
Program Type
Honors
Faculty Advisor
Dr. Hamed Shojaei
Document Type
Poster
Location
Face-to-face
Start Date
9-4-2026 1:00 PM
End Date
9-4-2026 3:00 PM
Abstract
Cosmological models are a tool used to understand the mysterious nature of dark energy and dark matter by predicting how these dark sector components have shaped the expansion of the universe. The cosmic coincidence problem stems from the present day densities of dark energy and matter sharing very similar magnitudes when previously we expect a much larger difference in orders of magnitude. The current best-fit model, ΛCDM , assumes dark energy is non-interacting; however, assuming that dark energy instead does interact could serve to alleviate this cosmic tension. We define an interaction where we relate the density of dark energy to the Hubble parameter by the Holographic principle. The predictions of theorized interactions are modeled and compared against different parameter values to determine the behavior of the system.
Recommended Citation
Hodges, Gunner W., "Interacting Dark Energy Models and the Cosmic Coincidence Problem" (2026). ATU Scholars Symposium. 55.
https://orc.library.atu.edu/atu_rs/2026/2026/55
Included in
Interacting Dark Energy Models and the Cosmic Coincidence Problem
Face-to-face
Cosmological models are a tool used to understand the mysterious nature of dark energy and dark matter by predicting how these dark sector components have shaped the expansion of the universe. The cosmic coincidence problem stems from the present day densities of dark energy and matter sharing very similar magnitudes when previously we expect a much larger difference in orders of magnitude. The current best-fit model, ΛCDM , assumes dark energy is non-interacting; however, assuming that dark energy instead does interact could serve to alleviate this cosmic tension. We define an interaction where we relate the density of dark energy to the Hubble parameter by the Holographic principle. The predictions of theorized interactions are modeled and compared against different parameter values to determine the behavior of the system.
Comments
A complete data analysis is planned to better determine best-fit parameter values.