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Riverlane publishes new research testing quantum algorithm on real quantum processor

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Riverlane publishes new research testing quantum algorithm on real quantum processor
19 December, 2023

Today, Riverlane announces a step forward in its work on quantum error correction with the publication of a new research paper in PRX Quantum. The paper, titled "Statistical Phase Estimation and Error Mitigation on a Superconducting Quantum Processor," explores a practical implementation of the Quantum Phase Estimation (QPE) algorithm, known as "statistical phase estimation," on Rigettiā€™s quantum processors.

The research focuses on Quantum Phase Estimation (QPE), a key algorithm with potential applications in chemistry and solid-state calculations on future quantum computers. By modifying QPE on a real-world quantum processor, Riverlane's team explores the algorithm's adaptability for early fault-tolerant devices.

The paper investigates "statistical phase estimation" as a potential improvement over QPE, demonstrating its natural resilience to noise and high accuracy in real-world applications. The research essentially showcases the development of a chemistry compiler that utilises error mitigation techniques.

This work is an important step as we move towards quantum error correction. Not only has it highlighted the suitability of statistical phase estimation for future fault-tolerant devices, but it also combines error mitigation and chemical embedding methods in a novel way, allowing us to reduce circuit depth and unlock exciting, new applications, sooner.

The work tests this algorithm with error mitigation on Rigetti's quantum processors. The molecules investigated include examples motivated by pharmaceutical applications, in collaboration with Astex Pharmaceuticals, using chemical embedding techniques to make this task tractable on current quantum devices.

For further details, read our blog post here.

The complete research paper "Statistical Phase Estimation and Error Mitigation on a Superconducting Quantum Processor," can be accessed here.


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