AWS Quantum Technologies Blog
Tag: Amazon Quantum Solutions Lab
Running quantum chemistry calculations using AWS ParallelCluster
This blog post is an introduction to HPC on AWS for quantum computing researchers who are seeking to compare their quantum or hybrid algorithms against classical calculations.
Graph coloring with physics-inspired graph neural networks
In this post we show how physics-inspired graph neural networks can be used to solve the notoriously hard graph-coloring problem, at scale. This can help in an huge number of familiar resource-allocation problems from sports to rental cars.
Optimization of robot trajectory planning with nature-inspired and hybrid quantum algorithms
Introduction The problem of robot motion planning is pervasive across many industry verticals, including (for example) automotive, manufacturing, and logistics. In the automotive industry, robotic path optimization problems can be found across the value chain in body shops, paint shops, assembly, and logistics, among others [1]. Typically, hundreds of robots operate in a single plant […]
Noise in Quantum Computing
Customers looking to solve their hardest computational problems often wonder about the production-readiness of quantum computing. They want to know when a full-scale, fault-tolerant quantum computer will be available, and what the obstacles are to achieving this ambitious goal. Current generation quantum computers are not fault-tolerant and have limited utility, but customers are experimenting with […]
A guide to BMW’s Quantum Computing for Automotive Challenges
Post Event Update We had a great time in Munich with the BMW Group at the Quantum Computing for Automotive Challenges event on July 20-21. Dr. Helmut Katzgraber, Sr. Practice Manager for the AWS Quantum Solutions Lab, reported: “To date, the application scope of quantum computers for real-world problems remains narrow. This is why identifying […]
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
Combinatorial optimization problems, such as the traveling salesman problem where we are looking for an optimal path with a discrete number of variables, are pervasive across science and industry. Practical (and yet notoriously challenging) applications can be found in virtually every industry, such as transportation and logistics, telecommunications, and finance. For example, optimization algorithms help […]
Community Detection using Hybrid Quantum Annealing on Amazon Braket – Part 2
As of 11/17/2022, D-Wave is no longer available on Amazon Braket and has transitioned to the AWS Marketplace. Therefore, information on this page may be outdated. Learn more. Many customers are facing the challenge of efficiently extracting information hidden within complex network structures. For example, a healthcare insurance company needs to identify fraudulent claims through […]
Using quantum annealing on Amazon Braket for price optimization
Combinatorial Optimization is one of the most popular fields in applied optimization, and it has various practical applications in almost every industry, including both private and public sectors. Examples include supply chain optimization, workforce and production planning, manufacturing layout design, facility planning, vehicle scheduling and routing, financial engineering, capital budgeting, retail seasonal planning, telecommunication network […]
Winners announced in the BMW Group Quantum Computing Challenge
The four winning teams of the BMW Quantum Computing Challenge were announced this morning at the annual Q2B conference in Santa Clara, California. The challenge, focused on discovering potential quantum computing solutions for real-world use cases, was a collaboration between the BMW Group and the Amazon Quantum Solutions Lab Professional Services team. “We at the […]
Community Detection using Hybrid Quantum Annealing on Amazon Braket – Part 1
As of 11/17/2022, D-Wave is no longer available on Amazon Braket and has transitioned to the AWS Marketplace. Therefore, information on this page may be outdated. Learn more. Many customers are facing the challenge of efficiently extracting information hidden within complex network structures. For example, a healthcare insurance company needs to identify fraudulent claims through […]