Calcul Quantique

Quantum Computing and Error Correction

Description: This course provides an in-depth introduction to quantum information processing, with a focus on the theoretical foundations and practical challenges of quantum computing and quantum communication. It begins with a review of the fundamental concepts of quantum computation, including quantum circuits, basic algorithms, and the impact of noise through the framework of open quantum systems.

A central part of the course is devoted to understanding and mitigating noise in quantum devices. Students will explore noise modeling in quantum circuits and will be introduced to the key principles of quantum error correction, from simple encoding schemes to more advanced concepts such as fault-tolerant quantum computation and surface codes. The course also addresses the specific constraints and opportunities offered by current noisy intermediate-scale quantum (NISQ) architectures.

In parallel, the course introduces quantum simulation as a major application of quantum technologies, covering both digital and analog approaches, Hamiltonian simulation techniques, and selected applications in physics. Elements of quantum complexity theory will also be discussed, providing insights into the potential advantages and fundamental limits of quantum computing.

The course is complemented by problem-solving sessions focused on the analysis of quantum communication protocols, as well as hands-on laboratory sessions where students implement and experimentally study such protocols. These activities aim to strengthen both conceptual understanding and practical skills in quantum information science.

Learning outcomes: AA1: Knowledge of the main quantum resources for the implementation of hardware solutions – AA2: Numerical and experimental implementation of quantum communication protocols – AA3: Mastery of the different architectures of quantum computers and their limitations – AA4: Mastery of existing techniques in quantum metrology

Evaluated skills:

  • Physical Engineering Design
  • Physical Modeling
  • Data Processing
  • Systems Analysis

Course supervisor: Damien Rontani

Geode ID: SPM-PHY-026