AWS Quantum Technologies Blog

Tag: quantum algorithms

Introducing the Amazon Braket Learning Plan and Digital Badge

Introducing the Amazon Braket Learning Plan and Digital Badge

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 […]

A detailed, end-to-end assessment of a quantum algorithm for portfolio optimization, released by Goldman Sachs and AWS

A detailed, end-to-end assessment of a quantum algorithm for portfolio optimization, released by Goldman Sachs and AWS

In this post we’ll walk you through some key takeaways from a paper published today by scientists from Goldman Sachs and AWS describing a quantum algorithm for portfolio optimization.

Towards practical molecular electronic structure simulations on NISQ devices with Amazon Braket and Kvantify’s FAST-VQE algorithm

Towards practical molecular electronic structure simulations on NISQ devices with Amazon Braket and Kvantify’s FAST-VQE algorithm

Quantum computing’s potential for computational chemistry is immense, but there are practical limitations. We show how Kvantify’s FAST-VQE algorithm can deliver great accuracy, performance, superior cost-effectiveness, driving us closer to transformative applications in drug discovery.

Constructing an “end-to-end” quantum algorithm: a comprehensive technical resource for algorithms designers

Constructing an “end-to-end” quantum algorithm: a comprehensive technical resource for algorithms designers

Today we’re introducing Quantum algorithms: A survey of applications and end-to-end complexities. This is a comprehensive resource, designed for quantum computing researchers and customers who are looking to explore how quantum algorithms will apply to their use cases.

Designing hybrid algorithms for neutral-atom quantum hardware using Bayesian optimization

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.