Variational MBQC Hamiltonian Ground State Learning

Contract type : Internship agreement

Level of qualifications required : Graduate degree or equivalent

Fonction : Internship Research

Assignment

Variational quantum algorithms have been proposed to discover the ground state of physically motivated Hamiltonians. This is usually proposed in the circuit model using an hardware efficient Ansatz. That is the circuit is made of parametrized native gates assembled in shallow way. This is aimed to provide enough expressivity to approach the desired ground state, while at the same time be short enough to avoid adverse effects of decoherence.
 
More recently, the same approach has been proposed in the Measruement  Based Quantum Computation (MBQC) model. Yet, most of the work is still to be developed. The main questions are:
- How to construct Ansatze?
- How to perform the optimization?
- What loss function to use?
- How differently it behaves compared to circuit VQAs?
  
We have developed in the past months an approach to generate valid computational graphs that can serve as Ansatz. We are looking for a suitable problem to experiment the full variational MBQC approach to
guide the development of theoretical tools.

Main activities

  • Litterature review
  • Selection of suitable Hamiltonians
  • Simulations
  • Refinement of the technique

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage