Ph.D. Thesis - Physics
Ph.D. Thesis - Physics
Ph.D. Thesis - Physics
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us whether the target system obeys a given Hamiltonian at all!<br />
The concept of quantum simulation was first conjectured by Feynman in 1982 [Fey82],<br />
and subsequently rigorously proven by Lloyd in 1996 [Llo96]. Following this, a number of<br />
significant papers presented in detail methods for simulating a variety of physical systems.<br />
Abrams and Lloyd discovered algorithms for calculating the eigenvalues and eigenvectors of<br />
a Hamiltonian on a quantum computer [AL97] and for simulating the dynamics of fermionic<br />
many-body systems [AL99]. Following this, a 2001 paper presented a method for efficiently<br />
simulating quantum chaos and localization [GS01]. In 2002, a paper of great importance to<br />
our work was published by Wu et al., which proposed a method for simulating pairing models<br />
on an NMR-type quantum computer [WBL02]. Jumping ahead a bit, in 2005 an interesting<br />
report was published, detailing classical simulations of a quantum computer calculating<br />
molecular energies [AGDLHG05]. This paper suggested that, using only tens of qubits,<br />
a quantum computer might indeed be able to solve certain problems in chemistry more<br />
efficiently than a classical computer can. This paper was followed-up by an article detailing<br />
a general polynomial-time algorithm for the simulation of chemical dynamics [KJL + 08].<br />
The above partial listing of the important literature is meant to illustrate the breadth<br />
of interest in quantum simulations, but also an important caveat: it is not trivial to de-<br />
sign a quantum simulation algorithm for a given quantum system. There is no “general<br />
purpose” quantum algorithm that can solve any problem in quantum mechanics efficiently.<br />
Although it may be efficient to implement a given simulated Hamiltonian, it is not, in gen-<br />
eral, straightforward to design an efficient measurement. It is fairly easy to see why: the<br />
length of the state vector for n qubits is of length 2 n . Even if the state could be measured<br />
without collapse, inquiring as to the state of the whole system is intractable. Part of the<br />
art of designing quantum simulations is asking the right questions.<br />
We would like to note a common theme throughout this thesis and a dominant one in<br />
the current effort of researchers worldwide. Some of the most interesting and classically-<br />
intractable models occur within the realm of solid-state physics, especially with regard to<br />
superconductivity. The BCS Hamiltonian is a model for which some good approximate<br />
methods (such as the density matrix renormalization group) exist, but which eludes a full<br />
quantum-mechanical description on a classical computer. The paper of Wu et al. [WBL02]<br />
provides a way for a quantum simulator to calculate the low-lying spectrum of this Hamil-<br />
tonian in polynomial time.<br />
This is only the beginning, though. BCS theory works well for Type-I superconductors,<br />
and the main advantage of quantum simulation of this model would be in calculating the<br />
spectra to greater precision. However, the mechanism behind Type-II superconductivity is<br />
still poorly understood. It has been conjectured that the phenomenon of spin frustration<br />
in a 2-D lattice of antiferromagnetically interacting spins may hold some insight into the<br />
dynamics of high-temperature superconductors [GP00, NGB92, BDZ08]. Research is active<br />
into using both neutral atoms and trapped ions to realize such spin Hamiltonians [DDL03,<br />
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