AWS Quantum Technologies Blog
Tag: Amazon Braket
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. […]
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 […]
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, […]
Using Quantum Machine Learning with Amazon Braket to Create a Binary Classifier
By Michael Fischer, Chief of Innovation at Aioi Insurance Services USA, Daniel Brooks, Research Data Scientist formerly of Aioi Insurance Services USA, with AWS quantum solution architects Pavel Lougovski and Tyler Takeshita. This post details an approach taken by Aioi Insurance Services USA to research an exploratory quantum machine learning application using the Amazon Braket […]
Working with PennyLane for variational quantum algorithms and quantum machine learning
The field of quantum computing today resembles the state of machine learning a few decades ago – in many ways. Near-term quantum algorithms for optimization, computational chemistry, and other applications are based on the very same principles that are used to train a neural network. In machine learning, there was no theoretical proof that a […]