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Seminar Series


​07 October 2022

Controlling enhanced ionisation with machine learning

Héloise Chomet
PhD student at University College London, UK

heloise.chomet.12@ucl.ac.uk


Strong-field enhanced ionization consists of an increase in the ionization rate of an extended molecule. Studies looking at enhanced ionization in H2+ have shown that nonclassical pathways and quantum interference provide a ‘bridge’ which facilitates intramolecular population transfer. The frequency of such bridge is intrinsic to the system and depends on several factors. Here we will use the t-SNE, an unsupervised machine learning dimensionality reduction technique, to investigate the effect of multiple parameters simultaneously in enhanced ionisation. We will then finally use semiclassical phase-space arguments as well as Wigner quasi-probability distributions to determine the physical cause of such ionisation pattern [1].

[1] H Chomet, S Plesnik, C D Nicolae, J Dunham, L Gover, T Weaving, C Figueira de Morisson Faria "Controlling quantum effects in enhanced strong-field ionisation with machine-learning techniques" arXiv:2205.03176 (2022)

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  • Workshop 2023
    • Register
      • Registration
      • Abstract submission
    • Attendees
      • Invited Speakers
      • Combatants
      • List of attendees
    • Programme
      • Structure
      • Scientific Programme
      • Code of Conduct
    • Practicalities
      • Fees & Expenses
      • Deadlines
    • Venue
      • Local information
      • Getting here
      • Accommodation
      • Visas
  • Social Media
  • Atto Fridays Seminar Series
    • Atto Fridays 2021/22
    • Programme
    • Speakers' Gallery
    • Hot Topics
    • FAQ