Advances in Many-Body Theories: from First Principle Methods to Quantum Computing and Machine Learning

Europe/Rome
Online
David Jarvis Dean (Oak Ridge National Laboratory), Gaute Hagen (Oak Ridge National Laboratory/The University of Tennessee), Jason Holt (TRIUMF - Vancouver), Martin Savage (INT & University of Washington), Morten Hjorth-Jensen (Michigan State University (USA)), Stefano Gandolfi (Los Alamos National Laboratory), Thomas Papenbrock (University of Tennessee & Oak Ridge National Laboratory)
Description

Advances in Many-Body Theories: from First Principle Methods to Quantum Computing and Machine Learning

Quantum computing and machine learning are two of the most promising approaches for studying complex physical systems where several length and energy scales are involved. Traditional many-particle methods, either quantum mechanical or classical ones, face huge dimensionality problems when applied to studies of systems with many interacting particles. By bringing together experts from these fields, this workshop will explore the links between these exciting new approaches and traditional many-particle methods in order to map out future research paths.

The workshop will be held through the Zoom Platform. Only who has registered in Eventbrite can participate in the workshop

The recording will be uploaded on the ECT* YouTube Channel.

    • 5
      Machine Learning for Lattice Field Theory
      Speaker: Phiala Shanahan (MIT)
    • 6
      Nuclear Physics Entering a Quantum-simulation Era: Lessons from the Past, Vision for the Future
      Speaker: Zohreh Davoudi (University of Maryland)
    • 7
      Variational Methods in the Era of Machine Learning: Classical and Quantum Computing Applications
      Speaker: Giuseppe Carleo (EPFL Lausanne)
    • 8
      Neural Network Quantum States for Atomic Nuclei
      Speaker: Alessandro Lovato (Argonne National Laboratory and UniTn)
    • 9
      Towards a Machine Learning Description of Nuclei
      Speaker: James Keeble (University of Surrey)
    • 10
      Phys-NN -A Machine Learning Approach to Invert Nuclear Responses
      Speaker: Krishnan Raghavan (Argonne National Laboratory)
    • 11
      Quantum Simulating Lattice Gauge Theories – High-energy Physics at Ultra-cold Temperatures
      Speaker: Philipp Hauke (UniTn)
    • 12
      Prospects for Near Term Quantum Simulations through Optimal Control
      Speaker: Kyle Wendt ( Lawrence Livermore National Lab)
    • 13
      The European Quantum Flagship and the ECT*
      Speakers: Daniele Binosi (ECT*), Tommaso Calarco (Juelich)
    • 14
      Nuclear Dynamics on Current Generation Quantum Devices
      Speaker: Alessandro Roggero (UW)
    • 15
      Quantum Technologies for High Energy Physics: the CERN Quantum Technology Initiative

      CERN, the European Organisation for Nuclear Research, operates the largest particle accelerator in the world and has a long tradition of collaboration and excellence in fundamental physics research. Quantum Technologies have seen an incredible development over just the last few years in all their aspects, computing, sensing, communications and theory. After a few years of pilot investigations, CERN has announced the creation of its Quantum Technology Initiative to understand the potential of these technologies for High Energy Physics, but also to contribute to their future development. This talk highlights the main objectives and current activities of the CERN Quantum Technology Initiative. A special emphasis will be placed on the Quantum Computing aspect and the activities carried out by CERN openlab, outlining the initial investigations that use quantum machine learning in High Energy Physics.

      Speaker: Sofia Vallecorsa (CERN)
    • 16
      Quantum and the Future
      Speaker: David Dean (ORNL)