Thesis
Quantum information scrambling in tunable range spin models
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2025
- Thesis identifier
- T17186
- Person Identifier (Local)
- 202170785
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- Quantum information scrambling refers to the spreading of initially localised information across a system’s many degrees of freedom, generating many-body entangled states. The fastest known scramblers achieve this at a timescale that grows logarithmically with the system size N and black holes are conjectured to saturate this bound. Such fast scramblers are also potentially useful for generating resource states within the system’s coherence time. This thesis investigates efficient entanglement generation using models with tunable-range interactions, allowing interpolation between different geometries with varying notions of locality. We show that this crossing between the geometries leads to a dynamical phase transition, marking the onset of fast scrambling in quantum circuits with different levels of long-range connectivity. This enables the identification of regimes where resource states can be generated on timescales of O(logN), allowing the relevant system sizes to grow exponentially with coherence time. We further demonstrate the utility of states generated from sparse coupling graphs in quantum-enhanced metrology. We show both analytically and numerically that in certain regimes, sparse graphs can emulate dynamics associated with dense all-to-all coupling, with example applications including generating states with Heisenberg scaling for quantum metrology. We also propose models to implement both the dynamical transition and generation of metrologically relevant states in neutral atom arrays with the aid of tweezer-assisted shuffling operations. With these results, we provide a solid foundation for further exploration of the rich physics and applications that sparse coupling graphs with tunable-range interactions have to offer.
- Advisor / supervisor
- Daley, Andrew
- Resource Type
- DOI
Relations
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PDF of Thesis T17186 | 2025-02-10 | Public | Download |