Jupyter notebooks and scientifique presentations .pdf files

QC4QC 2024 is over, but you may still have access to jupyter notebooks and .pdf files of this hands-on training!
 
Jupyter notebooks:
All jupyter notebooks used for this hands-on training are available on Github: https://github.com/kmaussang/QC4QC
 
Lectures .pdf files:
 
General introduction to the Quantum Computing landscape
Kenneth Maussang
 
Lecture 1 - Quantum Computing
Bruno Senjean
 
 
Lecture 2 - Quantum circuits and quantum algorithms
Saad Yalouz
 
Scientific presentation .pdf files:
 
Denis Lacroix
Quantum computing description of strongly interacting atomic nuclei: challenges and opportunities
 
César Féniou
Refining building blocks of quantum algorithms for electronic structure computation
 
 
Audrey Bienfait
Addressing a spin ensemble via superconducting circuits to implement a quantum memory
 

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.

Python library
This hands-on training will use the myQLM Python library (https://myqlm.github.io/) for quantum circuit implementation.

 

!!! Be careful that this training is only available on-site in Montpellier, and NOT remotely !!!

 

Requirements

The applicants should have a minimal knowledge in Python programming, and are expected to bring their own laptop.

 

Registration fees

Registration fees consist in a small contribution of 100 euros HT, 110 euros TTC, comprising all the coffee breaks and lunches as well as one dinner.

Please note that full registration is in two step :
1) registration on this website in this section
2) payment of the fees on a dedicated website : https://dr13.azur-colloque.fr/inscription/fr/320/inscription

Please note that following your registration your will receive an e-mail with a link to pay your registration fees. Your registration is only validated once the fees are paid.

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