The spring school, scheduled on May 16-17 2022 (online, 13:00 - 16:00 and 17:00 - 20:00 CEST), is dedicated to PhD students but the lectures are also open to other colleagues. 


An introduction to quantum algorithms for optimization


Short description: In this short PhD-level course we introduce the model of computation for quantum computers, and several basic subroutines that are at the heart of quantum algorithms. We also give an overview of recent research in the area of quantum optimization algorithms, in particular highlighting the sources of quantum speedup as well as the limitations of the resulting algorithms. The course is complemented by guided reading and homework.



Lecturer: Giacomo Nannicini, Thomas J. Watson Research Center, Yorktown Heights, NY USA

Bio: Giacomo Nannicini is a Research Staff Member in the Quantum Algorithms group at the IBM T. J. Watson Research Center. Before joining IBM, he was an assistant professor in the Engineering Systems and Design pillar at the Singapore University of Technology and Design. His main research interest is optimization broadly defined and its applications. Giacomo received several awards, including the 2021 Beale--Orchard-Hays prize, the 2015 Robert Faure prize, the 2012 Glover-Klingman prize.  



Technical informations:

  • The students are encouraged to be able to run Python on their computers.
  • Some coding tasks and recommended readings will be given as exercises during the Spring School.
  • We hope that all participants have at least a basic familiarity with computational complexity (what is a Turing machine, the classes P and NP), and linear algebra in complex vector spaces. In particular, if you have not worked with complex numbers in some time, please read a refresher about basic operations on them!
  • We will propose a nice visio tool for students to discuss and work in groups during the breaks and to do their exercices together.

Detailed lecture notes:

Online user: 2