Scientific Background:

The second quantum revolution has only recently begun, making quantum computing a very active and rapidly expanding field of research. Unlike classical computing, which relies on bits taking the values 0 or 1, quantum computing exploits qubits, which can exist in a superposition of states thanks to the fundamental principles of quantum mechanics. This property, combined with quantum entanglement and interference, enables the possibility of exponential speed-ups for certain types of calculations, thus opening the way to groundbreaking applications in many areas, notably in chemistry and materials science. This could lead to significant advances in the development of new drugs, the design of innovative materials, and the optimization of complex chemical reactions.

Currently, although still in its early stages, the development of quantum computers is at the core of both academic and industrial research. Many technology companies and specialized startups are investing heavily in the development of quantum hardware and increasingly powerful algorithms. Furthermore, governments and research institutions around the world are funding major programs to accelerate progress in this field. Today, quantum computers are indeed a reality. Some prototypes are commercially available and accessible via the cloud, allowing researchers and companies to test their algorithms on real quantum platforms. Quantum algorithms have already been successfully tested on these machines, although they are still limited by the quality and stability of the qubits. Indeed, we are still in an era where quantum computers are unstable and highly susceptible to quantum decoherence, a phenomenon that leads to the rapid loss of information stored in qubits due to their interaction with the external environment. This fragility makes quantum computations extremely sensitive to errors and remains one of the main obstacles to overcome before these machines can truly outperform classical computers in practical applications.
To achieve quantum advantage or utility, it is necessary to constantly improve both our algorithms and the performance of quantum hardware. The scientific and industrial communities are actively working to overcome the technical and theoretical challenges to make this technology viable on a large scale. If these challenges are successfully addressed, quantum computers could one day revolutionize how we solve complex problems and open up unprecedented scientific and technological horizons.

Motivations:

Today, many scientific communities are integrating (or considering integrating) quantum computing into their research, using newly developed Python libraries (such as OpenFermion, Cirq, Qiskit, myQLM, to name just a few). Quantum algorithms designed for the Noisy-Intermediate Scale Quantum (NISQ) era, such as variational quantum eigensolver (VQE) [1], or for the Fault-Tolerant era, such as block encoding or quantum phase estimation (QPE) [2,3] are often used as a "black box," without a real understanding of how quantum circuits are constructed or the different sources of error that can affect the final result. Furthermore, accessing quantum computing resources, whether through classical simulators or actual quantum machines, remains a challenge for many researchers, due to the complexity of the tools and a lack of appropriate training.
The aim of this autumn school is thus to provide comprehensive and practical training, enabling participants to develop an in-depth understanding of the principles and tools of quantum computing, with a particular focus on applications in quantum chemistry and materials science. It will be useful for all types of participants, whether they are already experienced researchers, early-career researchers such as PhD students or postdocs, or even industry professionals.
This autumn school will be extremely valuable for participants seeking to understand how quantum computers work and how to develop quantum algorithms. We will also address the issues of noise and error correction (including error mitigation techniques [4] and quantum error correction codes [5]), to pave the way toward the era of fault-tolerant quantum computers. Mathematical aspect will also be considered, with lectures on quantum computational complexity.
It is important to note that there is currently massive investment in quantum computing by companies, specialized industries, and startups. However, the demand in this field far exceeds the number of available experts, making this kind of training all the more essential to help address the shortage.