AWS Quantum Technologies Blog
Category: Customer Solutions
Thermodynamic sampling of disordered materials with an analog Hamiltonian Rydberg simulator
This post was contributed by Mao Lin, Bruno Camino, John Buckeridge and Scott M. Woodley Many advanced materials — from battery electrodes to semiconductor alloys — owe their useful properties to atomic-scale disorder. But predicting how atoms arrange themselves at a given temperature is hard: the number of possible configurations explodes combinatorially and sampling them […]
A framework for quantum-classical integration decisions
This post was contributed by Dimitar Trenev, Sebastian Stern, Tyler Takeshita, Cedric Lin, Peter Komar, Pooja Rao, Jerome Gonthier, and Elica Kyoseva. As quantum computing matures toward fault tolerance, a pressing question faces the high-performance computing (HPC) community: why is tightly integrating quantum processors to classical supercomputing infrastructure important? Today, algorithm researchers from Amazon Web […]
Classiq and AWS Power Quantum-Classical Chemistry Innovation in Singapore with Hatch
Introduction In biochemical processes development and analysis, binding energy, the energy released when a small molecule docks into a protein’s active site, determines how strongly a compound, such as a ligand, interacts with its protein target. Early-stage computational prediction of this quantity helps research teams prioritize candidates before committing to resource-intensive laboratory testing. Conventional methods […]
Designing hybrid algorithms for neutral-atom quantum hardware using Bayesian optimization
BMW sponsors PhD students to research novel approaches to computational challenges. Today we’ll show you how they bridge the gap between academia and industry, to solve some of the hardest problems in industry using Bayesian protocols for quantum optimization problems.
Optimization with OpenQAOA on Amazon Braket
In this blog post, we introduce OpenQAOA, Entropica Labs’ open-source SDK for the QAOA, and OpenQAOA-Braket, a plugin specifically designed to expand OpenQAOA’s capabilities by leveraging Amazon Braket.
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. […]
Setting up a cross-Region private environment in Amazon Braket
As of 11/17/2022, D-Wave is no longer available on Amazon Braket and has transitioned to the AWS Marketplace. Therefore, information on this page may be outdated. Learn more. 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. At AWS we say […]
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 […]
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 […]





