AWS Quantum Computing Blog

Tag: quantum algorithms

Combinatorial Optimization with Physics-Inspired Graph Neural Networks

Combinatorial optimization problems, such as the traveling salesman problem where we are looking for an optimal path with a discrete number of variables, are pervasive across science and industry. Practical (and yet notoriously challenging) applications can be found in virtually every industry, such as transportation and logistics, telecommunications, and finance. For example, optimization algorithms help […]

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Quantum computing research in Poland with Amazon Braket

With a host of vibrant research centers, scientists and engineers in Poland have made valuable contributions to quantum information science over the past 40 years. Today, as a large number of quantum hardware technologies are becoming available for experimentation, Polish researchers are turning to Amazon Braket – the AWS quantum computing service to test new […]

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Improving analysis of the computational cost of quantum simulations for chemistry and material science

This post summarizes a recent research paper from the AWS Center for Quantum Computing. The paper provides an improved analysis of quantum simulation of chemical and material systems. This research shows that such simulations can be implemented using fewer elementary quantum operations than previously thought. Computer simulations enable scientists to test their intuition about the […]

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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 […]

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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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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 […]

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