AWS Quantum Computing Blog

Category: Technical How-to

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 […]

Read More

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 […]

Read More

Quantum Chemistry with Qu&Co’s QUBEC on Amazon Braket

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 Amazon Braket. Finally, we show how you can register for the […]

Read More
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 […]

Read More
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 […]

Read More
A tensor network representation of a GHZ circuit and the corresponding circuit diagram

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 […]

Read More
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, […]

Read More

Quantum Machine Learning on QC Ware Forge built on Amazon Braket

By Fabio Sanches, Quantum Computing Services Lead, QC Ware In this post, I introduce you to QC Ware Forge, which is built on Amazon Braket. It provides turnkey quantum algorithms, so you can speed up research into applying quantum computing to hard data science problems. I also walk you through an example of using Forge […]

Read More
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 […]

Read More