Lectures & Seminars

This school will be organized in a relatively short set of long lectures supplemented by more specialized lectures and seminars, presentations by participants, and a poster session. The lectures will introduce the theoretical background focusing on computational and methodological aspects of the research, and the lecturers will also propose hands-on exercises and practical work on laptop, most likely using Python notebooks or similar. Students are invited to practice during the afternoons.

A poster session open to all participants will also be organized.  

Main lecture topics will cover:

• Entanglement dynamics in closed quantum systems
• Dynamics of open, driven-dissipative systems
• Matrix-Product-states/tensor-network-states methods : DMRG/TEBD/PEPS, from one-dimensional to two-dimensional systems
• Quantum Monte Carlo methods in and out-of equilibrium: variational Monte Carlo (VMC), time-dependent VMC, highly entangled variational Ansätze
• Variational quantum methods applied to small quantum processors: variational quantum eigensolvers
• Semiclassical approaches to quantum dynamics (truncated-Wigner approximation)
• Machine learning, neural quantum states

Specialized topics will cover: quantum computing, frustrated magnetism, topological phases, etc.

List of lecturers:

• Thomas Ayral:
  What to expect from variational algorithms on quantum computers?
• Mari-Carmen Bañuls:
  Tensor Network Applications: dynamics and more
• Frederico Becca:
  Variational wave functions for strongly correlated models on the lattice
• Natalia Chepiga:
  Constrained tensor networks
• Markus Heyl:
  Neural quantum states: Time dependence
• Anna Keselman:
  Numerical signatures of frustrated magnets
• Herviou Loïc:
  Matrix Product States for Quantum Hall systems
• Julien Leonard:
  Quantum matter under the microscope
• Manon Michel:
  Monte Carlo methods
• Frank Pollmann:
  Tensor networks methods
• Johannes Schachenmayer:
  The quantum many-body non-equilibrium problem in phase space
• Marco Schiro:
  Non-unitary quantum dynamics: methods and applications
• Filippo Vicentini:
  Machine Learning quantum neural states 
• Xavier Waintal:
  Machine learning tensor trains: an alternative to Monte-Carlo sampling.
  Application to diagrammatic calculations.