Machine Learning for Quantum Matter

Europe/Stockholm
132:028 (Nordita, Stockholm)

132:028

Nordita, Stockholm

Alexander Balatsky (Nordita), Bart Olsthoorn (Nordita), Jens H. Bardarson (KTH), Matthias Geilhufe (Nordita)
Description

Venue

Nordita, Stockholm, Sweden

Deadline for application extended to: 15 July 2019

Scope

Over the past decades we have witnessed an enormous increase of computational power and a rapid development of experimental techniques. Both developments, together with the great advancements of data storage capacities have initiated the application of methods taken from computer and data science into the research of functional quantum materials and quantum many-body physics. For example, interpretable and computationally-efficient machine learning models are able to capture the structure-property relationship in materials science opening the path towards an efficient computer based materials design. In the case of supervised learning, large datasets, e.g., of ab initio calculations, provide the necessary training examples. The trained models facilitate high-throughput screening of materials by reducing the search space. Additionally, the models enable dynamic simulation on longer timescales than traditionally feasible. Unsupervised clustering approaches using structural similarity metrics allow for a new way of exploring the large chemical space. In case of the many body problem, machine learning architectures provide versatile wavefunctions that lead to accurate results and prove to be more flexible than traditional methods. Conversely, quantum has also influenced the development of machine learning methods in the case of tensor networks and stimulated the research on developments of machine learning algorithms for potential quantum computers.

To assist the community in developing a coherent and consistent view we hold a three day focus workshop at Nordita titled "Machine Learning for Quantum Matter". We envision a set of leading experts talks combined with the talks of younger participants to present a broad picture of the activities and best ideas on the use of ML methods in quantum matter.

  • State-of-the art and method development
  • Scientific data and materials databases
  • Quantum materials design
  • Machine Learning applied to quantum phases and phase transitions
  • Machine learning applied to many-body quantum physics
  • Tensor network states
  • Quantum machine learning
  • Machine learning algorithms for quantum computers

[Timetable - available from start of the workshop]

Invited Speakers (tentative)

  • Alexandre Tkatchenko (University of Luxembourg)
  • Anatole von Lilienfeld (University of Basel)
  • Artem Oganov (Skolkovo Institute of Science and Technology)
  • Jacob Biamonte (Skolkovo Institute of Science and Technology)
  • Kristof Schütt (TU Berlin)
  • Valentin Stanev (University of Maryland)
  • Tess Smidt (Lawrence Berkeley National Laboratory)
  • Johan Mentink (Radboud University)
  • Ryo Tamura (National Institute for Materials Science - NIMS)
  • Matthias Geilhufe (Nordita)
  • Johan Hellsvik (Nordita)

Application

If you want to apply for participation in the workshop, please fill in the application form. You will be informed by the organizers shortly after the application deadline whether your application has been approved. Due to space restrictions, the total number of participants is strictly limited. (Invited speakers are of course automatically approved, but need to register anyway.)

Application deadline: 15 July 2019

There is no registration fee.

Accommodation

Nordita provides a limited number of rooms in the Stockholm apartment hotel BizApartments free of charge for accepted participants.

Please be aware that unfortunately, scammers sometimes approach participants claiming to be able to provide accommodation and asking for credit card details. Please do not give this information to them. For successful applicants, Nordita will be in touch via email regarding accommodation. If you are in any doubt about the legitimacy of an approach, please get in contact with the organisers.

Sponsored by:

Nordita KTH - Royal Institute of Technology Stockholm University

    • 09:30 09:45
      Introduction 15m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Alexander Balatsky
    • 09:45 10:45
      Quantum Machine Learning for Quantum Simulation 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Jacob Biamonte
    • 10:45 11:00
      Coffee break 15m 132:028

      132:028

      Nordita, Stockholm

    • 11:00 12:00
      Quantum error correction for the toric code using deep reinforcement learning 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Mats Granath
    • 12:00 14:00
      Lunch 2h Albanova Restaurant Entré

      Albanova Restaurant Entré

      Nordita, Stockholm

    • 14:00 15:00
      Organic Quantum Matter and the Organic Materials Database 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Matthias Geilhufe
    • 15:00 16:00
      Machine learning modeling of superconducting critical 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Valentin Stanev
    • 16:00 16:30
      Coffee break 30m 132:028

      132:028

      Nordita, Stockholm

    • 16:30 17:00
      Unsupervised detection of topological quantum state equivalences 30m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Oleksandr Balabanov
    • 17:00 17:30
      Deriving descriptors from fundamental physical models for targeted material property prediction using machine learning 30m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Ali Mazhar
    • 18:30 21:00
      Reception 2h 30m Albanova Entrance (Albanova Main Building)

      Albanova Entrance

      Albanova Main Building

    • 09:00 10:00
      Towards Universal Machine-Learning/Physics Model of Molecular Properties in Chemical Space 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Alexandre Tkachenko
    • 10:00 10:15
      Coffee break 15m 132:028

      132:028

      Nordita, Stockholm

    • 10:15 11:15
      Navigating chemical space with quantum machine learning 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Anatole von Lilienfeld
    • 11:15 12:15
      Artificial intelligence methods for discovering novel materials and exotic compounds 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Artem Oganov
    • 12:15 14:00
      Lunch 1h 45m Albanova Restaurant Entré (Albanova Main Building)

      Albanova Restaurant Entré

      Albanova Main Building

    • 14:00 15:00
      Effective model estimation for magnetic materials by machine learning 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Rio Tamura
    • 15:00 16:00
      Spin wave excitations of magnetic metal organic materials 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Johan Hellsvik
    • 16:00 16:30
      Coffee break 30m 132:028

      132:028

      Nordita, Stockholm

    • 16:30 17:30
      New horizons for the fastest, densest and least dissipative brain-inspired computing 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Johan Mentink
    • 09:00 10:00
      SchNet - An interpretable atomistic neural network 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Kristof Schütt
    • 10:00 10:15
      Coffee break 15m 132:028

      132:028

      Nordita, Stockholm

    • 10:15 11:15
      Euclidean Neural Networks for Emulating Ab Initio Calculations and Generating Atomic Geometries 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Tess Smidt
    • 11:15 11:45
      Phylogenetic operads in machine learning 30m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Caroline Brembilla
    • 11:45 12:15
      Microsoft’s Azure ML and AI modeling portfolio 30m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Joana Olivia
    • 12:15 14:00
      Lunch 1h 45m Albanova Restaurant Entré (Albanova Main Building)

      Albanova Restaurant Entré

      Albanova Main Building

    • 14:00 15:00
      Dirac Materials and Informatics 1h 132:028

      132:028

      Nordita, Stockholm

      Speaker: Alexander Balatsky
    • 15:00 15:30
      Determining spectrum-structure relation with machine learning techniques 30m 132:028

      132:028

      Nordita, Stockholm

      Speaker: Prof. Yi Luo
    • 15:30 16:30
      Coffee and round table discussion 1h 132:028

      132:028

      Nordita, Stockholm