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Much of the excitement surrounding quantum computers stems from the possibility of using quantum algorithms to solve problems that are intractable with standard or “classical” computers. Several notable examples of quantum acceleration have been discovered, particularly with applications in cryptography and chemistry.
Despite these exciting applications, quantum computers are not a panacea for computation; for some problems, quantum algorithms offer little or no advantage. In its current state of development, quantum computing is extremely sensitive to noise and environmental disturbances. This makes quantum computing “noisy,” because quantum bits (or qubits) lose information when they go out of sync, a process called decoherence.
Q-Ctrl error suppression for better quantum algorithms
To provide a medium to support the development of quantum technology, based in Sydney Q-Ctrl provides quantum control infrastructure software called Fire Opal for R&D professionals and quantum computing end users. Fire Opal connects intermediate representations, such as QASM, to hardware-specific instructions with embedded deterministic error suppression techniques designed to minimize noise and decoherence and maximize algorithmic success when executed on hardware. This fundamental technology also applies to a new generation of quantum sensors and enables Q-Ctrl to shape and support any application of quantum technology.
As of 2018, Q-Ctrl is an inaugural member of the IBM Quantum Startupand is currently backed by Square Peg Capital, Sierra Ventures, Sequoia Capital China, Data Collective, Horizons Ventures, Main Sequence Ventures, In-Q-Tel, Airbus Ventures and Ridgeline Partners.
Automate and simplify quantum algorithms with Classiq
Recently Q-Ctrl has a partnership launching software for the development of quantum algorithms in Tel Aviv Class provide an end-to-end platform for designing, running and analyzing quantum algorithms. The Classiq platform automatically creates optimized quantum circuits in an intermediate representation of high-level functional models. In particular, the Classiq solution enables any algorithm developer to work with high-level functional descriptions of algorithms and run complete quantum circuits, automating and simplifying the difficult process of creating quantum algorithms.
The new partnership will integrate Classiq’s Quantum Algorithm Design platform with Q-Ctrl’s quantum control techniques designed to improve hardware performance. The integration provides a single interface where developers can use both solutions to create algorithms and run them with high-performance error reduction techniques, simplifying the end-to-end process of extracting actionable insights from quantum computing. The technologies developed by both companies aim to reduce the need for users to have deep quantum computing expertise, allowing developers to focus on domain-specific applications that matter most to them.
“The purpose of this integration is to deliver the utility and benefits of quantum computing to an extensive base of algorithm developers in enterprise and academia. Classiq will be responsible for the relevant integration with its software tools, leveraging the support of Q-Ctrl,” Aravind Ratnam, chief strategy officer at Q-Ctrl, told VentureBeat.
Bringing everything together to help developers without quantum expertise
Users can develop in the Classiq platform while integrating Q-Ctrl’s hardware enhancement tools “under the hood”. Classiq’s Quantum Algorithm Design platform can convert high-level functional models into quantum circuits, which are automatically optimized by Q-Ctrl’s infrastructure software. These tools are both hardware agnostic, meaning they can run on a wide variety of quantum hardware vendors.
An additional part of the Q-Ctrl offering is the education technology platform, called Black Opal. As an optional extension to the solution integration, Black Opal is offered to customers for their own education and training through the Classiq portal. Future expansions may include the co-development of a Black Opal skills track explicitly focused on education for the Classiq platform.
“Classiq and Q-Ctrl were a natural fit because we immediately saw how our solutions addressed different parts of a developer’s workflow,” said Ratnam. “There are many developers who see algorithm design as a major barrier to using our tools, so our combined toolset makes that more accessible and easier to get started. It made sense to tie our solutions together.”
As things stand, the integrated offering will be available directly to customers through the Classiq platform. Initially, Classiq and Q-Ctrl will jointly engage with enterprise customers (regardless of which party the customer brings in) to learn more about use cases and get feedback. Classiq and Q-Ctrl will price their solution components (IP, time and material) based on the nature of the use case, integration complexity and customer context.
Customers can use these out-of-the-box tools to get more out of today’s hardware and build quantum algorithms to solve some of the world’s toughest computing problems, such as finance, quantum machine learning for drug discovery, and optimization problems for logistics.
“Classiq algorithm design tools lower the barriers for developers to build quantum circuits, and Q-Ctrl’s error correction tools will help them achieve the improved algorithm performance of quantum hardware, which is often prone to noise and error,” said Ratnam. “Together, we aim to expand access to quantum algorithm design and error correction and optimization tools to a broader base of developers, with or without deep quantum expertise.”
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