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Thesis

Engineering quantum states of fermionic many-body systems

Abstract:

Controlling and stabilising collective phases of many-body quantum systems is a problem of deep fundamental and technological interest. In this thesis, we perform a theoretical investigation on how useful quantum phases may be engineered in strongly correlated fermionic lattice systems, especially through periodic driving.

We first compute the phase diagram of the one-dimensional t–J model with the addition of non-standard pair hopping terms. We show that at dilute fillings these terms enhance superconductivity while, counter- intuitively, suppressing it at large fillings. We argue that this is due to dynamical constraints originating from the fact that local pairs cannot overlap. We conjecture that these constraints may play a more significant role in the physics of two-dimensional systems where the t–J model is studied as a candidate model of high-Tc superconductivity. We begin to investigate these dynamical constraints on a ladder geometry.

We then study the fermionic Hubbard model under periodic driving. We show that the driving induces a strong and robust singlet-pairing effect consistent with a superconducting state. This could provide a new mechanism for light-induced superconductivity in some classes of strongly cor- related materials. We show using Floquet theory that the dynamics of the driven Hubbard model are described precisely by the t–J model studied in the previous section. As the driven Hubbard model is also implementable with ultracold fermions in an optical lattice, our results could lead to their use as a quantum simulator for a broad class of candidate models for high-Tc superconductivity.

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Institution:
University of Oxford
Oxford college:
Worcester College
Role:
Author

Contributors

Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
UUID:
uuid:c2ad8834-7202-45cf-8348-4f9b07e942d1
Deposit date:
2019-10-01
ARK identifier:

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