Lecture Content

Principles of quantum computing

  • Quantum systems, states, evolution, and measurement
  • Quantum computing with ideal and noisy devices

Models of quantum computing

  • Gate model of quantum computation
  • Quantum annealing and Quadratic Unconstrained Binary Optimization problems
  • Elements of quantum machine learning

Quantum computers programming

  • Existing quantum hardware
  • Programming quantum computers
  • Future of quantum computing: risks and opportunities

Review of applications of quantum computing for Earth Observations

  • Quantum neural networks
  • Quantum supported neural networks
  • Combinatoric optimization


It is required that participants have basic knowledge of linear algebra, probability theory, and machine learning.



Prof. Piotr Gawron


Piotr Gawron is an applied computer scientist, leader of the Scientific Computing and Information Technology group at AstroCeNT.

He graduated in 2003 from the Faculty Of Automatic Control, Electronics and Computer Science of the Silesian University of Technology, and then obtained PhD in 2008 at the Institute of Theoretical and Applied Informatics, Polish Academy of Sciences where he was employed from 2001 to 2019 in Quantum Systems of Informatics group. His PhD thesis concerned quantum programming languages and their applications for quantum walks and quantum games. In the years 2007—2015 he intensively collaborated on restricted numerical ranges and shadows of matrices with Prof. Karol Życzkowski from the Jagiellonian University. He obtained a habilitation degree from his Alma Mater in 2014 on the basis of the dissertation “Influence of the environment on quantum information processes”. He participated in several research and development projects concerning image processing and energy usage profiling and prediction implemented with industrial partners. He is active in scientific outreach in the area of quantum computation and information. He was a supervisor of two PhD candidates.

The scientific interests of Piotr Gawron concentrate on quantum computation, quantum information theory, machine learning, tensor networks, and recently Earth observations.

Aleksandra Krawiec


Aleksandra Krawiec got her M.Sc. in mathematics from the Silesian University of Technology. In 2017, she joined the Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, where she is a Ph.D. student in the Quantum Systems of Informatics Group. Her scientific interests focus on quantum information theory, mainly quantum channels' discrimination and certification. In her free time, Aleksandra enjoys traveling, rock climbing, and dancing folk dances.