AWS Quantum Technologies Blog
Low-overhead quantum computing with Gottesman-Kitaev-Preskill qubits
Introduction This post summarizes a research paper from the AWS Center for Quantum Computing that proposes a direction to implement fault-tolerant quantum computers with minimal hardware overhead. This research shows that by concatenating the surface code with Gottesman, Kitaev, and Preskill (GKP) qubits, it is theoretically possible to achieve a logical error rate of 10-8 […]
Quantum Machine Learning on QC Ware Forge built on Amazon Braket
By Fabio Sanches, Quantum Computing Services Lead, QC Ware In this post, I introduce you to QC Ware Forge, which is built on Amazon Braket. It provides turnkey quantum algorithms, so you can speed up research into applying quantum computing to hard data science problems. I also walk you through an example of using Forge […]
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 […]
Designing a fault-tolerant quantum computer based on Schrödinger-cat qubits
At the AWS Center for Quantum Computing, we are doing scientific research and development on quantum computing algorithms and hardware. This post summarizes findings from our first architecture paper that describes a theoretical blueprint for a fault-tolerant quantum computer that features a novel approach to quantum error correction (QEC). Fair warning, this post dives somewhat […]
Supporting quantum computing research at Israeli universities
While quantum computing continues to advance through scientific discovery and engineering innovation, the field still faces formidable challenges. Collaboration between industry and academia for quantum computing research is important. Expertise from multiple domains is needed to solve specific problems facing technology firms, and the collaboration fosters a richer environment for education. In this post, I […]
Working with PennyLane for variational quantum algorithms and quantum machine learning
The field of quantum computing today resembles the state of machine learning a few decades ago – in many ways. Near-term quantum algorithms for optimization, computational chemistry, and other applications are based on the very same principles that are used to train a neural network. In machine learning, there was no theoretical proof that a […]
〈 Hello | World 〉!
Welcome to the new AWS Quantum Computing blog channel. Quantum computing is hardly the most common topic in dinner conversations, unless you’re a physics geek, but it is becoming more and more talked about, particularly in the business and technology media. In my opinion, quantum computing is an interdisciplinary area with two equally important goals: […]