Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Quantum Algorithms for Optimization - Quantum Colloquium

Simons Institute via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore quantum algorithms for optimization in this comprehensive lecture from the Quantum Colloquium series. Delve into the potential applications of quantum computers for solving optimization problems, including recent advancements in gradient descent and linear and semidefinite program solving. Examine both discrete and continuous optimization, discussing quantum speed-ups and their limitations. Investigate issues such as the requirement for large instance sizes to achieve quadratic quantum speedups and the need for quantum random-access memory (QRAM). Cover topics including graph sparsification, NP-hard optimization, and linear programs while gaining insights from Ronald de Wolf of QuSoft, CWI, and the University of Amsterdam.

Syllabus

Introduction
What is optimization
Types of optimization
Limitations
Quantum RAM
Discrete Optimization
Graph Sparsification
Quantum Algorithm
NPHard Optimization
Gradient Descent
Linear Programs

Taught by

Simons Institute

Reviews

Start your review of Quantum Algorithms for Optimization - Quantum Colloquium

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.