Hands-on training on Quantum Computation for Quantum Chemistry

Context: The second quantum revolution has started quite recently, making quantum computing a very active and rapidly growing field of research. Indeed, quantum computers are promising tools that could theoretically provide considerable advantages by exploiting quantum phenomena such as superposition and entanglement. The development of quantum computers is at the heart of academic and industrial research, although still in its infancy. One challenge is to develop powerful and predictive quantum algorithms dedicated to electronic structure of molecules and materials with both short- and long-term prospects. Objectives: Many scientific communities are now including (or thinking of including) quantum computing to there research, using recently developed python libraries (openfermion, cirq, qiskit, myQLM, to cite only a few). Quantum algorithms such as the variational quantum eigensolver (VQE) are often used as a black-box, without a clear understanding on how quantum circuits are constructed and the different sources of errors that may be hidden in the final result. The objectives of this hands-on training is to fill this gap by (i) teaching the basics of quantum computing and the building blocks of any quantum algorithms, (ii) showing how to solve the electronic structure problem using quantum algorithms, (iii) making hands-on training to design and implement a personalized quantum circuit from scratch (on any of the existing python libraries). Targeted audience: This hands-on training is dedicated to PhD students, postdoc and researchers that are either just interested about learning quantum computing, or who wants to potentially use it in their own research. Requirements: The applicants should have a minimal knowledge in Python programming.