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The Oxford 750MHz NMR Spectrometer

The Oxford 750MHz NMR Spectrometer

Prof Jonathan Jones

Professor of Physics

Research theme

  • Quantum information and computation

Sub department

  • Atomic and Laser Physics

Research groups

  • NMR quantum computing
jonathan.jones@physics.ox.ac.uk
  • About
  • Publications

Temporal Entanglement and Witnesses of Non-Classicality

(2025)

Authors:

Giuseppe Di Pietra, Gaurav Bhole, James Eaton, Andrew J Baldwin, Jonathan A Jones, Vlatko Vedral, Chiara Marletto

Controlling NMR spin systems for quantum computation

Progress in Nuclear Magnetic Resonance Spectroscopy Elsevier 140-141 (2024) 49-85

Abstract:

Nuclear magnetic resonance is arguably both the best available quantum technology for implementing simple quantum computing experiments and the worst technology for building large scale quantum computers that has ever been seriously put forward. After a few years of rapid growth, leading to an implementation of Shor's quantum factoring algorithm in a seven-spin system, the field started to reach its natural limits and further progress became challenging. Rather than pursuing more complex algorithms on larger systems, interest has now largely moved into developing techniques for the precise and efficient manipulation of spin states with the aim of developing methods that can be applied in other more scalable technologies and within conventional NMR. However, the user friendliness of NMR implementations means that they remain popular for proof-of-principle demonstrations of simple quantum information protocols.
More details from the publisher
Details from ORA
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Controlling NMR spin systems for quantum computation

ArXiv 2402.01308 (2024)
Details from ArXiV

Efficiently computing the Uhlmann fidelity for density matrices

Physical Review A American Physical Society 107 (2023) 012427

Authors:

Andrew Baldwin, Jonathan Jones

Abstract:

We consider the problem of efficiently computing the Uhlmann fidelity in the case when explicit density matrix descriptions are available. We derive an alternative formula which is simpler to evaluate numerically, saving a factor of 10 in time for large matrices.
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Details from ORA
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Efficiently computing the Uhlmann fidelity for density matrices

ArXiv 2211.02623 (2022)

Authors:

Andrew J Baldwin, Jonathan A Jones
Details from ArXiV

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