Three new capabilities launched today for Aquila on Amazon Braket let you customize lattice geometry and detuning. Learn how increased flexibility empowers your research. Read the Post on the AWS Blog Channel
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Check out our latest blog to learn how we implemented a cost-effective development cycle for training a hybrid quantum-classical algorithm using Amazon Braket and hyperparameter optimization. Read the Post on the AWS Blog Channel
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In this new post you’ll learn how Arm-based AWS Graviton processors can accelerate Simulated Quantum Annealing for nonlinear optimization problems in quantum computing. Read the Post on the AWS Blog Channel
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Combinatorial optimization problems got you stumped? Check out our new blog exploring a hybrid algorithm that taps into quantum computing to recursively reduce complexity while ensuring feasible solutions. Read the Post on the AWS Blog …
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Quantum error correction is key to building useful quantum computers. New research by Amazon & Caltech demonstrates a strategy that cuts the overhead of error correction. A lot. Read the Post on the AWS Blog Channel
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The story of how Qedma used Amazon Braket Direct for dedicated access to IonQ hardware to execute milestone VQE circuits. This post details leveraging reservations and collaborating directly with experts. An exciting look at accelerating …
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ML models driving high-stakes decisions need interpretability. See how the Amazon QSL and Fidelity FCAT developed interpretable models based on Boolean logic. Read the Post on the AWS Blog Channel
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Today we look at how Citi Innovation Labs is exploring quantum computing for portfolio optimization in partnership with Classiq and AWS. Their research examines how adjustments to the QAOA algorithm’s penalty factor impact performance. Read …
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