13th December 2017: Cambridge Quantum Computing are delighted to confirm that they are participating with the Quantum Communications Hub on a 2-year partnership research programme, to build on an existing collaboration between CQC and the University of Cambridge for the commercialisation of a specialist quantum technology.
Cambridge Quantum Computing (CQC) and Oxford Quantum Circuits (OQC) are delighted to confirm that they have been granted an Innovate UK award as part of the UK Quantum Computing Initiative.
Pursuant to the award, CQC will lead the development of a compiler of quantum algorithms onto OQC’s quantum computing architecture. Additionally, CQC and OQC will jointly research applications best suited to the OQC architecture. As a result of the development of a quantum compiler and suitable quantum algorithms, OQC will develop and assess prototypes of different circuit layouts, working jointly with Oxford University. These strands will lead to a demonstration by the end of the project period that will last 1 year, of a well-chosen algorithm, compiled using the CQC compiler, and run on an optimal OQC circuit. It is expected that blueprints will be generated for quickly scaling up to a level at which device performance outstrips classical computers.
We are very pleased to report that we are participating in the Google Cloud Startup Program that provides CQC with cloud credits, access to architecture reviews and technical mentors, 24/7 support, and more. The programme is designed to help startups build and scale on Google Cloud Platform.
Google Cloud Platform has specific strengths in big data and machine learning, which is a core technology of CQC’s project Arrow that has been designed, built and now delivered through the AI Team here at CQC. At present, one of the tools we currently use to really enhance and scale our development plan is the Cloud Machine Learning Engine. As a result of Google’s generous support, during the next year CQC will have flexible access to a professionally maintained computing cluster that can scale up to a size of hundreds of GPUs and even thousands of CPUs. This enables us to develop deep learning models at a far greater pace, and facilitates the pace of our in house R&D activities to adapt to those of our commercial partners.
On a broader horizon, the computational capabilities now at hand are comparable to university research groups. These resources are now readily available to the CQC scientific team to be employed towards one of the founding missions of CQC: the simulation of quantum hardware and the prototyping of quantum algorithms.
A team of 4 from Cambridge Quantum Computing are proud to be swimming to support London City Swim in aid of research into Motor Neurone Disease. The team is made up of scientists, directors and shareholders.
CQC has open-sourced a cross-platform trading interface for financial securities. TA> was developed wholly in-house to facilitate the testing and production implementation of our AI driven trading algorithms known as ARROW>
As well as aiming for flexibility, TA> is designed to be lightweight. For extra speed and efficiency developers and users are recommended to wrap trading logic classes around C++ classes using a popular cross-language wrapper such as SWIG or Cython where possible.
The GitHub repository is copied in the link below. By publishing TA> we have provided a vital resource with flexibility and customisable modules for both development and back-testing as well as live trading and sub-millisecond reporting, and ease of use for a wide variety of Direct Market Access (“DMA”) trading platforms. With AI driven algorithms improving in speed and effectiveness we believe that the relatively mundane but critical “last mile” should not hold up the far more valuable work of bringing actual strategies to market.
Cambridge Quantum Computing are very pleased to have won a prestigious EPSRC grant to develop a compiler module for the UK’s flagship quantum computing hub in Oxford, NQIT.
Building a quantum computer as a network of smaller devices is central to the NQIT idea. However, quantum algorithms are typically given in a high level mathematical language, and are usually not designed with a granular network in mind. CQC’s compiler project, that is built on groundbreaking work completed last year, will address this problem by exploring the challenges and potential gains of compiling quantum algorithms (or quantum programs) onto a network quantum computer such as NQIT.
CQC’s compiler module will be able to evaluate alternative physically realistic network graphs allowing us to understand how much connectivity is useful for NQIT and inform us how one of the first large scale quantum computers can be made to operate at maximum efficiency.