AWS Quantum Computing Blog

Tag: Amazon Braket

Using quantum annealing on Amazon Braket for price optimization

Combinatorial Optimization is one of the most popular fields in applied optimization, and it has various practical applications in almost every industry, including both private and public sectors. Examples include supply chain optimization, workforce and production planning, manufacturing layout design, facility planning, vehicle scheduling and routing, financial engineering, capital budgeting, retail seasonal planning, telecommunication network […]

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Updates from re:Invent 2021

With so much happening at the annual re:Invent conference, it would be easy to miss some of the updates in AWS Quantum Technologies. In this post we summarize four recent announcements: a new feature that helps customers run hybrid quantum-classical algorithms more easily and with better performance, two new quantum processing units (QPUs) coming to […]

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Realizing quantum spin liquid phase on an analog Hamiltonian Rydberg simulator

This week at re:Invent, we announced the future availability of a Rydberg-atom based quantum computer from QuEra Computing. Launching in 2022, it will introduce a new quantum computing paradigm to Amazon Braket, Analog Hamiltonian Simulation (AHS). AHS uses programmable quantum devices to emulate the behavior of other quantum mechanical systems. Already today, researchers in academia […]

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Community Detection using Hybrid Quantum Annealing on Amazon Braket – Part 1

Many customers are facing the challenge of efficiently extracting information hidden within complex network structures. For example, a healthcare insurance company needs to identify fraudulent claims through detecting abnormal relationships between patients and providers, a finance company needs an anti-money laundering tool that can detect abnormal transactions between different entities, or a marketing company needs […]

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ConnectWise

Implementing a Recommendation Engine with Amazon Braket

In this blog post, we detail an approach to solving a feature selection problem that implements a recommendation engine using Amazon Braket – the quantum computing service by Amazon Web Services. Our approach tackles the “cold-start” problem that recommendation systems face, produces a solution comparable with traditional approaches, and reaches the required levels of accuracy […]

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CINECA Center in Italy

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. […]

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Mitiq Overview

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 […]

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Amazon Braket

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 […]

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a diagram of 2 independent quantum processing units combined with a classical extractor to generate fully random bits

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, […]

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Amazon Braket

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 […]

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