Category: Amazon Quantum Solutions Lab

Check out our latest blog to learn how we implemented a cost-effective development cycle for training a hybrid quantum-classical algorithm using Amazon Braket and hyperparameter optimization.

Combinatorial optimization problems got you stumped? Check out our new blog exploring a hybrid algorithm that taps into quantum computing to recursively reduce complexity while ensuring feasible solutions.

ML models driving high-stakes decisions need interpretability. See how the Amazon QSL and Fidelity FCAT developed interpretable models based on Boolean logic.

Discover how Airbus and BMW Group are harnessing quantum computing to tackle industry challenges. Join the Airbus-BMW Group Quantum Mobility Quest and help shape the future of transportation.

In this post we’ll walk you through some key takeaways from a paper published today by scientists from Goldman Sachs and AWS describing a quantum algorithm for portfolio optimization.

BMW sponsors PhD students to research novel approaches to computational challenges. Today we’ll show you how they bridge the gap between academia and industry, to solve some of the hardest problems in industry using Bayesian protocols for quantum optimization problems.

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.

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 […]

Suppose you are trying to solve a problem of interest (e.g., portfolio optimization or machine learning), and you are given some classical data, neatly arranged into a matrix A. Your plan is to solve this problem using a quantum algorithm to process the data. For example, you may be trying to solve a linear system […]

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 […]