Advanced Quantum Algorithms for Scientific Computing - Lecture 2
Centre International de Rencontres Mathématiques via YouTube
-
41
-
- Write review
The Investment Banker Certification
AI Engineer - Learn how to integrate AI into software applications
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore advanced quantum algorithms designed for scientific computing applications in this comprehensive 90-minute lecture from the CEMRACS Summer School on Quantum Computing. Begin with fundamental quantum computing concepts including quantum states, unitary operators, the no-cloning theorem, and measurement principles. Delve into essential techniques such as block-encoding and linear combination of unitaries (LCU) before examining specialized quantum algorithms for scientific applications. Master the Quantum Linear System Problem (QLSP), Quantum Singular Value Transformation (QSVT), and Quantum Eigenvalue Transformation methods. Understand Hamiltonian Simulation and Trotterization techniques, explore Adiabatic Quantum Computation (AQC) and Variational Quantum Eigensolver (VQE) approaches, and investigate Quantum Krylov Algorithms alongside quantum differential equation solvers for both linear and nonlinear systems. Discover how these quantum algorithms address large-scale numerical linear algebra problems and high-dimensional differential equations, positioning quantum computing as a transformative tool for tackling complex scientific computing challenges across diverse research fields.
Syllabus
Agnieszka Międlar: Advanced quantum algorithms for scientific computing -Lecture 2
Taught by
Centre International de Rencontres Mathématiques