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Much of the excitement about quantum computers stems from the ability to use quantum algorithms to solve problems unsolvable with standard or “classic” computers. Several notable examples of quantum accelerations have been discovered, notably with applications to cryptography and chemistry.
Despite these exciting applications, quantum computers are not a panacea for computation; for some problems, quantum algorithms offer no or only a minor 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 are out of sync, a process known as decoherence.
Q-Ctrl Error Removal for Better Quantum Algorithms
To provide a means to support quantum technology development, Sydney-based Q-Ctrl offers quantum control infrastructure software, dubbed Fire Opal, for quantum computing R&D professionals and end users. . Fire Opal connects intermediate representations, such as QASM, to hardware-specific instructions with built-in deterministic error suppression techniques designed to minimize noise and decoherence and maximize algorithmic success when executed on hardware. This foundational technology also applies to a new generation of quantum sensors and enables Q-Ctrl to shape and support every application of quantum technology.
Since 2018, Q-Ctrl has been an inaugural member of 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 and Ridgeline Partners.
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Automate and simplify quantum algorithms with Classiq
Most recently, Q-Ctrl announced a partnership with Classiq, a Tel Aviv-based quantum algorithm development software startup, to provide an end-to-end platform for design, execution and analysis. of quantum algorithms. The Classiq platform automatically creates optimized quantum circuits in an intermediate representation from high-level functional models. Specifically, the Classiq solution enables any algorithm developer to work with high-level functional descriptions of algorithms and produce 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 will provide a single interface where developers can use both solutions to build algorithms and run them with high-performance error reduction techniques, simplifying the end-to-end process of getting useful insights from them. quantum computers. The technologies developed by the two companies aim to reduce the need for users to have deep expertise in quantum computing, allowing developers to focus on the domain-specific applications that matter most to them.
“The goal of this integration is to provide the utility and benefits of quantum computing to a broader base of algorithm developers in businesses and universities. Classiq will be responsible for relevant integration with its software tools, leveraging support from Q-Ctrl,” Aravind Ratnam, chief strategy officer at Q-Ctrl, told VentureBeat.
Bringing it all together to help developers without quantum expertise
Users will be able to develop in Classiq’s platform while incorporating Q-Ctrl’s hardware enhancement tools “under the hood”. Classiq’s quantum algorithm design platform can take high-level functional models and turn them into quantum circuits, which will be automatically optimized by Q-Ctrl’s framework software. Both of these tools are hardware-independent, meaning they can run on a wide range of quantum hardware vendors.
An additional component of the Q-Ctrl offering is its education technology platform, dubbed Black Opal. As an optional extension of the solution integration, Black Opal will be offered to customers for their own education and training through the Classiq portal. Future expansions may include the co-development of an explicitly educationally focused Black Opal Skills Pathway for the Classiq platform.
“Classiq and Q-Ctrl provided a natural fit as we immediately saw how our solutions handled different parts of a developer’s workflow,” Ratnam said. “Many developers see algorithm design as a major barrier to using our tools, so our combined toolset makes this more accessible and easy to get started. Putting our solutions together made natural sense.
In the current state of things, the integrated offer will be accessible to customers directly via the Classiq platform. Initially, Classiq and Q-Ctrl will jointly engage with enterprise customers (regardless of which party brings the customer in), to learn more about use cases and get feedback. Classiq and Q-Ctrl will price their solution components (IP, time, and hardware) based on the nature of the use case, the complexity of the integration, and the customer context.
Customers can use these out-of-the-box tools to get the most out of today’s hardware and create quantum algorithms to solve some of the world’s toughest computational problems, such as finance, quantum machine learning for discovery drugs and optimization problems for logistics. .
“Classiq’s algorithm design tools reduce barriers for developers who want to build quantum circuits and Q-Ctrl’s error correction tools will help them improve the algorithm performance of quantum hardware, which is often prone to noise and error,” Ratnam said. “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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