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Ph.D. Thesis - Physics

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Chapter 4<br />

Theory and history of quantum<br />

simulation using trapped ions<br />

In the previous part, we explored how NMR systems can be used to perform quantum<br />

simulations. However, we also saw some drawbacks to the scalability of these systems, as<br />

well as to the precision with which results can be calculated. In this chapter, we present<br />

an alternative approach based on trapped ions. Trapped ions have a long coherence time<br />

(potentially O(10 s) or longer), which exceeds that of nuclear spins in solution, and offer a<br />

potentially scalable system in the sense that the number of ions that can be used is unlimited<br />

if proper controls are available and decoherence is sufficiently small (or error correction is<br />

used). Networking between ions may be accomplished by moving ions or by linking them<br />

with photonic or electronic quantum communication, as discussed in Ch. 1.<br />

We also noted in Ch. 1 that the analog approach to quantum simulation is promising for<br />

quantum simulations of systems that do not require error correction, or systems which are<br />

fundamentally not amenable to error correction, such as systems with continuous Hilbert<br />

spaces. In particular, analog simulations of spin physics may be able to solve problems that<br />

classical simulation cannot for as few as 36 interacting particles [RMR + 07]. Here, we turn<br />

to such analog systems. Our main effort is to design and experimentally characterize an<br />

ion trap in which such a simulation could be done, focusing on the problem of simulating a<br />

2-D lattice of interacting spins using trapped ions.<br />

In Sec. 4.1, we present the basic ion trap Hamiltonian and demonstrate how it permits<br />

quantum control of the internal and external degrees of freedom of trapped ions using laser<br />

radiation. Then, in Sec. 4.2, we outline the method proposed in Ref. [PC04b] for simulating<br />

quantum spin models in an ion trap. Sec. 4.3 enumerates the challenges involved with<br />

designing ion traps for such quantum simulations, framing the questions explored in the<br />

remainder of Part II. We summarize in Sec. 4.4.<br />

83

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