Today we’ll show you how to use a new python decorator from the Amazon Braket SDK to help algorithm researchers seamlessly execute local Python functions as an Amazon Braket Hybrid Job with just one extra line of code. Read the Post on the …
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Today, we’re announcing improvements to the task-processing speed and our support for parametric compilation on QPUs from Rigetti Computing in Amazon Braket. This enables up to 10x faster runtime performance for algorithms that use Amazon …
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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 …
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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 …
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With Hybrid Jobs, you can run algorithms that use both classical and quantum compute resources. These hybrid quantum-classical algorithms can help you optimize the performance of the quantum devices currently available. These algorithms are …
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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. Read the Post on the AWS Blog Channel
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Amazon Braket Pulse lets you control the low-level analog instructions for quantum computers, to optimize performance or develop new analog protocols, like error suppression and mitigation. Today we show you how and describe some best …
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In this post, we’ll explore the Wolfram Quantum Framework and show you how to connect it with Amazon Braket to run quantum algorithms. Read the Post on the AWS Blog Channel
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