Tag: quantum algorithms

This post shows how quantum reservoir computing (QRC) can tackle machine learning challenges using Rydberg-atom quantum computers. Readers will learn how QRC works, see its performance on image classification and time series prediction tasks, and understand when it outperforms classical methods—particularly for small datasets in pharmaceutical research. After decades of progress, machine learning (ML) has […]

AWS re:Invent 2025 returns to Las Vegas from December 1 to 5, bringing together builders, researchers, and business leaders who are exploring what is next in advanced computing on AWS. Quantum computing is moving from research labs into early real-world use. With Amazon Braket , AWS gives you managed access to multiple quantum hardware providers, […]

This post was contributed by Ernesto Palidda and Marco Paini from Rigetti Computing, Cristopher Salvi and Antoine Jacquier from Imperial College London, Samuel Crew from National Tsing Hua University and Shaun Geaney from Standard Chartered along with Sebastian Stern and Michael Brett from Amazon Web Services (AWS). Empirical evidence suggests that well-chosen quantum feature maps […]

This post was contributed by Jiaqi Leng, Joseph Li, Xiaodi Wu Scientists and engineers face numerous computational challenges in fields like fluid dynamics [1], modeling heat and sound propagation [2], and aircraft design [3]. Simulating partial differential equations (PDEs) in high dimensions offers a powerful approach to addressing these challenges. However, solving these high-dimensional differential […]

Given a three-dimensional model of a drug’s potential target (the binding site), what is the orientation of the drug candidate molecule that best “fits” (docks onto) this binding site? Structure-based drug design involves the use of computational tools to answer this very question! Chugai Pharmaceutical Co., Ltd., a leading Japanese pharmaceutical company, specializes in the […]

Introduction In this post, we explore the mathematical foundations and practical implementations of quantum measurement techniques using Amazon Braket. We examine this subject through multiple perspectives: action of gates as basis transformation, projection as inner product, projector formalism, and observable formalism. A key insight that we’ll develop is understanding basis transformations as tools for converting […]

Quantum Key Distribution (QKD) is a method of exchanging encryption keys that complements traditional and post-quantum cryptography by offering a different kind of security guarantee: the ability to reveal whether a key exchange has been observed or disrupted. This blog explores BB84[i] —the first and most well-known QKD protocol—to illustrate how quantum principles can be […]

Quantum computers promise to revolutionize computation for problems across many industrial sectors, though understanding exactly how useful this technology will be remains an open question. In this blog post, the team from Strangeworks, an AWS Partner, evaluates different implementations of the Quantum Approximate Optimization Algorithm (QAOA) against an aircraft cargo loading problem posed by Airbus […]

When running quantum computing workloads with multiple circuits, such as simulating molecular systems, building classical shadows, and training quantum machine learning models, submitting each circuit individually creates substantial delays between executions due to task setup and processing time. This overhead adds hours to the total run time of the experiments and makes the results sensitive […]

Available today, quantum computing developers, educators, and enthusiasts can learn the foundations of quantum computing on Amazon Web Services (AWS) with the Amazon Braket Digital Learning Plan and earn their own Digital badge – at no additional cost. You earn the badge after completing a series of learning courses and scoring at least 80% on an […]