AWS Quantum Technologies Blog

Tag: quantum algorithms

The active space is localised on the oxygen atoms and two neighbouring platinum atoms

Exploring computational chemistry using Quantinuum’s InQuanto on AWS

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. […]

Introducing the Amazon Braket Algorithm Library

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 […]

Amazon Braket launches Braket Pulse to develop quantum programs at the pulse level

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 […]

Amazon Braket now supports verbatim compilation and native gates with IonQ

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 Therefore, information on this page may be outdated.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 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 […]