Research interests

  • Quantum dynamics of spin systems
  • Fundamental theory of NMR and ESR spectroscopy
  • Quantum mechanical calculation of magnetic properties
  • Artificial intelligence processing of NMR and ESR data
  • Chemical and biological effects of weak magnetic fields
  • Optimal control of large quantum systems

Current research projects

  • High-performance quantum dynamics simulation methods: we are developing numerically efficient algorithms for spin dynamics simulations. The largest previously accessible spin systems contained about fifteen spins. The current version of our Spinach library can handle thousands of spins and simulate virtually anything within modern magnetic resonance.
  • Machine learning and artificial intelligence data processing: we are developing artificial neural networks for processing the types of magnetic resonance data that previously relied on human judgement and Tikhonov regularised reconstructions.
  • Automated processing of quantum decoherence equations: we have created analytical and numerical tools that greatly simplify relaxation theory treatment of large quantum systems and automatically identify decoherence-free subspaces.
  • Quantum mechanical modelling of biological effects of weak magnetic fields: we are working on theoretical and computational tools for modelling and analysis of spin-selective chemical reactions that are responsible for the magnetic field sense of migratory birds.
  • Optimal control of quantum systems: we are developing new algorithms for the design of time- and energy-efficient quantum control sequences. The results are applied to NMR/ESR spectroscopy and quantum dynamics in general.

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