AWS Quantum Technologies Blog
Category: Quantum Technologies
CINECA and AWS bring new quantum computing capabilities to the Italian research community
CINECA and AWS are collaborating on a series of quantum computing research initiatives to help to accelerate the next generation of computational capabilities and enable new research in Italy. CINECA is a consortium made up of 70 Italian universities and four national research institutes to form the leading high-performance computing (HPC) research center in Italy. […]
Announcing the opening of the AWS Center for Quantum Computing
What if by harnessing the properties of quantum mechanics we could model and simulate the behavior of matter at its most fundamental level, down to how molecules interact? The machine that would make that possible would be transformative, changing what we know about science and how we probe nature for answers. Quantum computers have the […]
Exploring Simon’s Algorithm with Daniel Simon
Introduction Customers exploring quantum computing often rely on existing algorithms to learn the basics or evaluate new services. Amazon Braket includes many such algorithms in its SDK and managed notebooks. In this post, we will explore one of the first quantum algorithms invented, and a new addition to our Amazon Braket examples: Simon’s algorithm. We […]
Quantum Chemistry with Qu&Co’s (now Pasqal) QUBEC on Amazon Braket
(Update: Pasqal and Qu&Co announced a merger on January 11, 2022.) In this post, we discuss the progress and limitations of chemistry simulations on current quantum computers, and introduce Qu&Co‘s QUBEC, a quantum computational platform that is specifically designed for chemistry and materials science simulations. The post describes QUBEC’s architecture and how it integrates with […]
Exploring quantum error mitigation with Mitiq and Amazon Braket
By Ryan LaRose, a researcher with Unitary Fund and Michigan State University; Nathan Shammah, CTO of Unitary Fund; Peter Karalekas, Software Engineer at the AWS Center for Quantum Computing; and Eric Kessler, Sr. Manager of Applied Science for Amazon Braket. In this blog post, we demonstrate how to use Mitiq, an open-source library for quantum […]
Setting up your local development environment in Amazon Braket
As a fully managed quantum computing service, Amazon Braket provides a development environment based on Jupyter notebooks for you to experiment with quantum algorithms, test them on quantum circuit simulators, and run them on different quantum hardware technologies. However, Amazon Braket does not restrict you to use only the managed notebooks and the AWS management […]
AWS joins the OpenQASM 3.0 Technical Steering Committee
In the early 1990s, James Gosling introduced the Java programming language. One of the key advantages to Java was that programmers could write code once and have it run on many different backends, without needing to concern themselves with the underlying hardware. This was enabled by an intermediate representation called Java bytecode. Java programs were […]
Simulating quantum circuits with Amazon Braket
Whether you want to research quantum algorithms, study the effects of noise in today’s quantum computers, or just prototype and debug your code, the ability to run large numbers of quantum circuits fast and cost effectively is critical to accelerate innovation. This post discusses the different types of quantum circuit simulators offered by Amazon Braket […]
AWS supporting the Quantum Software Research Hub led by Osaka University in Japan
Since Amazon Braket, the AWS quantum computing service, was launched, customers have said they want to learn the basics of the technology, explore quantum computing, and discuss use cases with experts in their local communities. In Japan, AWS is working with Osaka University through the Quantum Software Research Hub to educate enterprise, startup, and academic […]
Generating quantum randomness with Amazon Braket
Introduction – the need for randomness Random numbers are a crucial resource used throughout modern computer science. For example, in computation, randomized algorithms give efficient solutions for a variety of fundamental problems for which no deterministic algorithms are available. This includes Monte Carlo methods that have widespread applications in science for the simulation of physical, […]