Quantum cloud computing platform opens in public beta
Introduced last September as the only quantum-first cloud computing platform, Quantum Cloud Services (QCS) is offered as a new access model for quantum programming that is centered on an integrated cloud architecture. With QCS, says the company, quantum processors are tightly integrated with classical computing infrastructure to deliver performance gains that enable programs to run as much as 30x faster than on web API models.
Once registered with QCS, users have access to their own dedicated Quantum Machine Image – a virtual development and execution environment for quantum programming. It comes preloaded with all the tools necessary to get started building quantum programs, including pyQuil – a Python library for quantum programming using Quil – and the company’s quantum simulator.
The company says that it is also deploying two Aspen QPUs to the QCS platform, which users can book with an online reservation system available on the new QCS web dashboard. Beta users will receive $5,000 in credits to use toward running programs on the QPU during their first month.
The company also announced that it is distributing the first set of applications built by its Developer Partners:
- QCompress – an application from Zapata Computing that provides a tool for compressing quantum data to boost the optimization of variational quantum algorithms.
- QClassify – another tool from Zapata that uses quantum states to facilitate classification, which allows users to train a variational quantum circuit for classification of data points using a labeled set of training data.
- QuantumFreeze – a game where users can navigate a penguin across a frozen lake while avoiding hidden holes. Users can make classical moves from one square to the next, or make a quantum move by splitting a penguin into a superposition of states.
- Quantum Feature Detector – a Python library from QxBranch that provides a configurable class of quantum machine learning functions. It has a simple interface for using quantum transformations, or circuits, to detect features in data as part of a machine learning application stack.
The company says that more than 30 leading scientists from around the world have signed on as QCS Research Partners, with their work ranging from characterizing and benchmarking quantum hardware to computational research across biology, chemistry, and machine learning. The research partners are encouraged to publish their results and to share their data and code and open-source the tools and libraries they create on the QCS platform.
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