Dynex is the world’s only accessible neuromorphic quantum computing cloud for solving real-world problems, at scale

Taking advantage of a biological approach, neuromorphic quantum computing emulates the parallel processing capabilities of the human brain.

Neuromorphic quantum computing is a special type of computing that combines ideas from brain-like computing with quantum technology to solve problems. It works differently from regular quantum computing by using a network of connected components that can quickly react to changes, helping the system to swiftly find the best solutions.

This setup mimics natural processes like those seen in the human brain and can also simulate aspects of quantum physics like tunneling but uses everyday electrical behavior instead. This means it can be simulated on current computers and built with usual electrical parts, making it more practical for real-world problems.

This technology is exciting because it leads to computer systems that are faster and capable of handling complex tasks more efficiently than traditional computers.

Dynex SDK

The Dynex SDK is a collection of open-source Python tools designed to tackle difficult problems using n.quantum computing. It helps adapt your application's challenges for resolution on the Dynex platform and manages the communication between your application code and the n.quantum system seamlessly.

Easy to use and access through seamless integration with the Python development environment, and support for a large number of commonly used libraries.

Programmers already using tools like the Dimod framework, PyQUBO, or any other Qubo framework, will find it straightforward to run computations on the Dynex neuromorphic computing platform: Simply using the Dynex Sampler object in place of the usual sampler object typically used with systems like D-Wave, but without the typical constraints of regular quantum machines.

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