The main goal of quantum computing is to design novel methods, founded on the laws of quantum mechanics, for faster problem solving. Quantum computing is the area of study focused on developing computer technology based on the principles of quantum theory, which explains the nature and behavior of energy and matter on the quantum (atomic and subatomic) level. Development of a quantum computer, if practical, would mark a leap forward in computing capability far greater than that of the modern day supercomputer, with performance gains in the billion-fold realm and beyond. The quantum computer, following the laws of quantum physics, would gain enormous processing power through the ability to be in multiple states, and to perform tasks using all possible permutations simultaneously.
Alternative Models of Quantum Computing for Optimization and Simulation of Quantum Systems
Rolando Somma, NMC Affiliate Researcher, LANL Staff Scientist
Nga Nguyen, UNM Student
Hao-Tien Chiang, UNM Student
The research project pursues the design of new and fast quantum algorithms for optimization and simulation of quantum systems, as well as a rigorous analysis of their algorithmic complexity. Quantum computers may solve some important problems much more efficiently than their classical counterparts. However, to be able to gain insight into the power and speed of quantum information processing, it is imperative to design new tools for quantum computation that take advantage of the surprising essence of quantum mechanics. The objective of this research project is to consider alternative techniques to design new and fast quantum algorithms for optimization and simulation of quantum systems. In addition to obtaining faster computing power over other known conventional methods, new quantum algorithms will shed more light on the power of quantum computation, providing an understanding of why so few useful quantum algorithms have been found in the past. Faster and novel methods for optimization and simulation of quantum systems will have important applications in several fields, including computational biology, material science, and condensed matter. Funding for this project comes from the National Science Foundation.