AWS Quantum Technologies Blog

Amazon Braket Pulse lets you control the low-level analog instructions for quantum computers, to optimize performance or develop new analog protocols, like error suppression and mitigation. Today we show you how and describe some best practices.

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.

In this post, we’ll explore the Wolfram Quantum Framework and show you how to connect it with Amazon Braket to run quantum algorithms.

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.

Earlier this year, QuEra and AWS sponsored the first-ever hackathon on a neutral-atom computer. In 24 hrs the teams solved hard problems using real quantum computers. It was a rush. We asked the winning team to tell us their story.

Amazon Braket is now included in the latest @awscloud SOC-2 report. You need to have confidence in the security, confidentiality + privacy of all services you use. Quantum computing may be experimental but it’s no different to us: security is job zero.

Everyone needs effective cost management. In this post, we’ll introduce you to an Amazon Braket cost-control solution, which we’ve open-sourced on GitHub under an MIT license.

In this post, you’ll learn about IonQ’s latest trapped-ion quantum computer, IonQ Aria, which is now available on Amazon Braket, and is also the first QPU in AWS to feature error mitigation.

In this post, we show how tools from our partner Good Chemistry can help you further explore the potential of quantum computing for non-trivial molecular systems, and design experiments that you can run on Amazon Braket.

In this blog post, we show how you can track and manage hybrid quantum-classical experiments with the Hybrid Jobs feature in Amazon Braket and Amazon SageMaker Experiments, used by ML developers on AWS to organize their experiments and trials.