Year: 2019
Type: dissertation
Abstract: Exact simulation of quantum systems is intractable on current classical computers due to the time required to calculate the exponential number of amplitudes which represent a quantum state.This thesis explores how highly tuned quantum devices, such as quantum simulators and digital quantum computers, can be utilized to gain a deeper understanding of nature.In Chapter 1 we begin by reviewing some of the basics of quantum information.Chapter 2 highlights the advantages of using entangled states in metrology and how quantum simulators can be realized on a system of trapped ions.Chapter 3 develops the gate model of quantum computing and reviews many of the foundational algorithms needed to simulate many-body systems.Chapter 4 originates from the paper "Verification of a many-ion simulator of the Dicke model through slow quenches across a phase transition."[1].This chapter examines how a system of trapped ions can be engineered to emulate a famous model known as the Dicke model, which involves coupling many spins to a single bosonic mode.After confirming that the Dicke model indeed has been realized, we show in Chapter 5 how simple protocols can be used to prepare highly entangled states.This chapter originates from the paper, "Bang-bang shortcut to adiabaticity in the Dicke model as realized in a Penning trap experiment" [2].These states have the potential to provide giant gains in making precision measurements.Finally, with the use of universal quantum computers on the horizon, we develop a framework, in Chapter 6, for extracting thermal properties of many-body systems on these machines.This chapter eminates Many thanks are in order for the people who helped me get to where I am in my career.First, my parents, Robert and Maureen Cohn, who have always been there to support me.In this respect I am also grateful for the support provided by my grandparents Alien and Joeseph
Author: Jeffrey Cohn
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2973491337