Quantum Speedup for Graph Sparsification, Cut Approximation and Laplacian Solving
Offered By: IEEE via YouTube
Course Description
Overview
Explore quantum algorithms for graph sparsification, cut approximation, and Laplacian solving in this 25-minute IEEE conference talk. Delve into the contributions of Simon Apers and Ronald de Wolf as they present their research on quantum speedup for these graph-related problems. Learn about classical sparsification algorithms, quantum spanner algorithms, and quantum sparsification algorithms. Discover the innovative bootstrapping trick and matching quantum lower bound. Gain insights into cut approximation and Laplacian solving techniques, and understand how quantum computing can potentially accelerate these graph algorithms.
Syllabus
Intro
Graph Sparsification
Spectral Sparsification
Our Contribution
Classical Sparsification Algorithm
Quantum Spanner Algorithm
Quantum Sparsification Algorithm
A Bootstrapping Trick
Matching Quantum Lower Bound
Cut Approximation
Laplacian Solving
Taught by
IEEE FOCS: Foundations of Computer Science
Tags
Related Courses
An Improved Exponential-Time Approximation Algorithm for Fully-Alternating Games Against NatureIEEE via YouTube Computation in the Brain Tutorial - Part 2
IEEE via YouTube Computation in the Brain - Part 1
IEEE via YouTube Spectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model
IEEE via YouTube Cookbook Lower Bounds for Statistical Inference in Distributed and Constrained Settings - Part 1
IEEE via YouTube