Tag: quantum algorithms

Running Jupyter notebooks as Hybrid Jobs on Amazon Braket, you get performance and convenience of jobs, without modifying code. In this post, we show how you can scale up from exploratory notebook to repeatable and reliable experiments on different quantum hardware.

Introduction Quantum computers hold the promise of driving novel approaches to solving complex problems across multiple fields, including optimization, machine learning, and the simulation of physical systems. Researchers are already using quantum computers to explore computational chemistry problems, however the scale and capabilities of quantum devices available today is limited by noise and other factors. […]

Research scientists and quantum algorithm developers are often new to cloud computing. Their main focus during quantum algorithm development should center on writing algorithm code; however, they often spend time setting up and maintaining interactive development environments, estimating costs to run their code on classical or quantum hardware, and stitching together common subroutines. Today, we […]

When experimenting on a quantum computer, customers often need to program at the lower-level language of the device. Today, we are launching Braket Pulse, a feature that provides pulse-level access to quantum processing units (QPUs) from two hardware providers on Amazon Braket, Rigetti Computing and Oxford Quantum Circuits (OQC). In this blog, we present an […]

As of 05/17/2023, the ARN of the IonQ Harmony device changed to arn:aws:braket:us-east-1::device/qpu/ionq/Harmony. Therefore, information on this page may be outdated. Learn more. Previously, when customers submitted a circuit to the IonQ device on Amazon Braket, the circuit was automatically compiled to native instructions. Today, we are extending the verbatim compilation feature to IonQ’s 11-qubit […]

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 […]

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 […]

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 […]

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 […]

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, […]