Q-Ctrl and Classiq partner to help developers build faster, more efficient quantum algorithms
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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 to standard or “classical” computers. Several notable examples of quantum acceleration have been discovered, particularly with applications to cryptography and chemistry.
Despite these exciting applications, quantum computers are not a panacea for computations; For some problems, quantum algorithms offer no advantage or only a minor advantage. In its current state of development, quantum computing is extremely sensitive to noise and disruptive factors in the environment. This makes quantum computing “noisy,” as quantum bits (or qubits) lose information when they become out of sync, a process known as decoherence.
Error suppression by Q-Ctrl for better quantum algorithms
To provide a means to enhance the development of quantum technology, Sydney-based Q-Ctrl is offering its quantum control infrastructure software, called Fire Opal, to quantum computing R&D professionals and end users. Fire Opal links intermediate representations, such as QASM, to hardware-specific instructions with built-in deterministic error prevention techniques designed to reduce noise and decoherence and increase algorithm success when implemented on hardware. This underlying technology is also applicable to a new generation of quantum sensors, and Q-Ctrl enables shaping and supporting every application of quantum technology.
Since 2018, Q-Ctrl has been an inaugural member of the IBM Quantum Startup and is currently backed by Square Peg Capital, Sierra Ventures, Sequoia Capital China, Data Collective, Horizons Ventures, Main Sequence Ventures, In-Q-Tel, Airbus Ventures, Ridgeline Partners.
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Automate and simplify quantum algorithms with Classic
Recently, Q-Ctrl announced a partnership with Tel Aviv-based quantum algorithm development software startup Classiq to provide a comprehensive platform for the design, implementation, and analysis of quantum algorithms. The Classiq platform automatically generates quantum-optimized circuits in an average representation from high-level functional models. Specifically, the Classiq solution enables any algorithm developer to work with high-level functional descriptions of the algorithms and pull out complete quantum circuits, automating and simplifying the difficult process of creating quantum algorithms.
The new partnership will combine Classic’s quantum algorithm design platform with Q-Ctrl’s quantum control technologies designed to boost hardware performance. The integration will provide a single interface where developers can use both solutions to build and run algorithms with high-performance error-reducing techniques, simplifying the overall process of obtaining useful insights from quantum computers. The technologies developed by the two companies aim to reduce the need for users to have deep quantum computing expertise, allowing developers to focus on the domain-specific applications that matter most to them.
The goal of this integration is to bring the usefulness and benefits of quantum computing to an expanding base of algorithm developers in institutions and academia. Classic will be responsible for related integration with its software tools, leveraging support from Q-Ctrl, Aravind Ratnam, Q-Ctrl Chief Strategy Officer told VentureBeat.
Put it together to help developers without quantitative experience
Users will be able to develop in the Classiq platform with hardware optimization tools integrated into Q-Ctrl “under the hood”. Classiq’s quantum algorithm design platform can take high-level functional models and convert them into quantum circuits, which will be automatically optimized by Q-Ctrl infrastructure software. These tools are hardware agnostic, which means they can run on a wide range of quantum hardware providers.
An additional component of Q-Ctrl’s offering is its education technology platform, dubbed Black Opal. As an optional extension of solution integration, Black Opal will be offered to customers for their education and training via the Classiq portal. Future additions may include the co-development of a Black Opal skills track with a clear focus on education for the Classic platform.
“Classic and Q-Ctrl provided a natural fit as we immediately saw how our solutions handled different parts of the developer workflow,” said Ratnam. “There are many developers who see algorithm design as a major barrier to using our tools, so our built-in toolkit makes that easier and easier to get started with. Bringing our solutions together makes a natural sense.”
As it stands, the integrated offering will be available to customers directly through the Classic platform. Initially, Classiq and Q-Ctrl will jointly engage enterprise customers (regardless of which party brings the customer), to learn about use cases and get feedback. Classic and Q-Ctrl will price the components of the solution (IP, time, materials) based on the nature of the use case, integration complexity and customer context.
Customers can use these out-of-the-box tools to get the most out of today’s hardware and build quantum algorithms to solve some of the world’s most challenging computational problems, such as finance, quantum machine learning for drug discovery, and logistics optimization problems.
“Classiq algorithm design tools lower barriers for developers to build quantum circuits, and Q-Ctrl debugging tools will help them achieve improved algorithm performance from quantum devices, which are often prone to noise and errors,” said Ratnam. “Together, we aim to extend access to quantum algorithm design and debugging and optimization tools to a broader base of developers, with or without deep quantum expertise.”
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