Brookhaven National Laboratories (BNL) 2020 SULI Internship

Abstract

Dark energy is considered the main physical reason for the accelerating expansion of the universe, indirectly observed first in the 1990s through experiments such as the measurements of the luminosity distance of the type Ia supernovae (SN Ia). Different theoretical models for dark energy have been constructed through the years, all unique from the number of needed dimensions, required values of the cosmological constant λ, to the needed parameters to permit such exotic phenomena. Dark energy models simulated in this project include supercritical models as well as modified Einstein-Maxwell theories in six dimensions. Exponentially suppressed models with small values of λ, models with modified Einstein-Maxwell landscape equations and Einstein-Born-Infield flux compactification models will also be discussed, though not simulated in code. Potentials for each of the models will be used to construct the Hamiltonian and calculate their ground state energies. Python-based quantum computing software development kit Qiskit and Mathematica are the main tools used in the construction of the hamiltonians for the different models. The main quantum algorithm used throughout the experiment is the Variational Quantum Eigensolver (VQE), an algorithm developed by IBM for obtaining the minimum eigenvalue of a system. Analyses and computations of the hamiltonians and ground state energies of the models have been completed, with comparisons made between both the classical results calculated in Mathematica and the VQE results using different combinations of simulators and optimizers.