AWS Quantum Technologies Blog
Category: Amazon Quantum Solutions Lab
Australian Red Cross Lifeblood collaborates with AWS to optimize rostering
Using AWS advanced computing, the Australian Red Cross Lifeblood achieved theoretical cost reductions of up to 46% by optimizing nurse scheduling – key to meeting rising blood donation demand affordably.
Delivering quantum information – a field-deployed quantum network
Researchers made breakthroughs in distributing, storing, & processing quantum data across a network in Boston. Discover the tech that might power a future secure quantum internet.
JPMorgan Chase and AWS study the prospects for quantum speedups with near-term Rydberg atom arrays
Want the details on using quantum optimization for finance? New research from Amazon QSL and JPMorgan Chase maps out pathways to quantum advantage. Their post analyzes problem classes inspired by real-world use cases, setting the stage for impactful future experiments.
Hyperparameter optimization for quantum machine learning with Amazon Braket
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.
Exploring quantum-informed recursive optimization algorithms on Amazon Braket
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.
Explainable AI using expressive Boolean formulas
ML models driving high-stakes decisions need interpretability. See how the Amazon QSL and Fidelity FCAT developed interpretable models based on Boolean logic.
Exploring industrial use cases in the Airbus-BMW Group Quantum Computing Challenge
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.
A detailed, end-to-end assessment of a quantum algorithm for portfolio optimization, released by Goldman Sachs and AWS
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.
Designing hybrid algorithms for neutral-atom quantum hardware using Bayesian 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.
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.