Embedded Files
This presentation was prepared in collaboration with Simon, as part of a research project focused on the topic of simulating quantum computing.
Our goal is to provide a structured and accessible overview of the key concepts and techniques involved in simulating quantum algorithms, as well as the practical challenges and methods currently used in this field.
The work presented here combines theoretical foundations with practical aspects, aiming to contribute to ongoing research efforts and provide useful insights for students and researchers interested in quantum technologies.
We hope this presentation will serve as a valuable resource for those seeking to understand or develop simulation techniques for quantum computing systems.
This document is intended for students who wish to build solid foundations in quantum information.
It outlines the essential prerequisites needed to approach this field effectively.
To benefit from this material, students should ideally have:
A solid understanding of linear algebra (vector spaces, inner products, operators, eigenvalues/eigenvectors, tensor products).
Familiarity with complex numbers and Hilbert spaces.
Basic knowledge of probability theory and statistics.
Some exposure to classical information theory (optional but useful).
For practical work: basic proficiency in Python programming (libraries such as NumPy can help with matrix manipulations).
This document focuses on concepts at the intersection of quantum mechanics and information theory, aiming to provide clear and accessible foundations without assuming prior expertise in advanced physics
dm_quantique_mpri-2.pdfPage updated
Google Sites
Report abuse