QuantumAtlas

Quantum Algorithms Database

Quantum Algorithms for Optimal Transport

Quantum approaches to the optimal transport problem — finding the most efficient way to move or transform one distribution of resources into another — relevant to logistics and machine learning.

Year

2019 onward

Inventor(s)

Multiple contributors

Speedup Type

Polynomial Speedup

Difficulty

★★★★★

The Problem

Determining the most efficient way to redistribute resources, mass, or probability from one configuration to a target configuration, minimizing total movement cost.

How It Works

Reformulates the classical optimal transport linear program using quantum optimization or quantum linear algebra subroutines, aiming to reduce the computational cost of large-scale transport problems.

Real-World Impact

An emerging research area connecting quantum computing to a mathematical framework already widely used in classical machine learning, economics, and logistics planning.

← Back to Algorithms Database