Tag: quantum research

In this post, we’ll explore quantum computing using Amazon Braket. We’ll take an educational approach for this by using a well-known quantum algorithm, Grover’s algorithm. We’ll first explain how Grover’s algorithm works, then we’ll introduce the dinner party problem which involves identifying a set of friends that can be invited together to a party satisfying […]

Quantum encryption promises unbreakable security, but managing the infrastructure can be challenging. Read how LuxQuanta leveraged AWS to centralize control and gain insights.

Exciting news for the quantum computing community! Amazon Braket has just onboarded Rigetti’s newest 84-qubit superconducting quantum processor, Ankaa-2. This device offers faster gate times, improved fidelities, and 24/7 availability. Learn more about how you can access Ankaa-2 and start running algorithms today in this new blog post.

Amazon Braket brings quantum computing to more users with a new 20-qubit processor from IQM in the EU. See how this tech could shape the future in our blog post.

Researchers made breakthroughs in distributing, storing, & processing quantum data across a network in Boston. Discover the tech that might power a future secure quantum internet.

Want the details on using quantum optimization for finance? New research from Amazon QSL and JPMorgan Chase maps out pathways to quantum advantage. Their post analyzes problem classes inspired by real-world use cases, setting the stage for impactful future experiments.

Three new capabilities launched today for Aquila on Amazon Braket let you customize lattice geometry and detuning. Learn how increased flexibility empowers your research.

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.

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.

ML models driving high-stakes decisions need interpretability. See how the Amazon QSL and Fidelity FCAT developed interpretable models based on Boolean logic.