Zapata Computing Earns New Patent for Technique to Unlock Value from Early Fault-Tolerant Quantum Computers

Robust Amplitude Estimation (RAE) speeds up a key component of many industrially relevant quantum algorithms, shortening the path to practical quantum advantage.

Zapata Computing, a leading developer of Quantum AI software for enterprises, announced that the company has earned a patent for Robust Amplitude Estimation (RAE). RAE reduces the runtime and resources required for the estimation subroutine, currently a bottleneck in many industrially relevant quantum algorithms. It is the latest patent granted in Zapata’s industry-leading portfolio of 49 patent families, including proprietary techniques in optimization, generative modeling, and post-quantum cybersecurity.

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“RAE not only speeds up computations on today’s quantum devices, it accelerates the path to quantum advantage as devices mature.”

“At Zapata, we’re focused on building a bridge to the quantum future for our customers, and everything in our patent portfolio reflects that,” said CEO and Co-founder Christopher Savoie. “This includes near-term quantum-inspired techniques, for example in generative AI, that can deliver value on today’s classical devices, while being compatible with the quantum devices of the future. It also includes techniques like RAE that bring that quantum future closer and position our customers to gain an advantage with quantum hardware as it matures.”

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Quantum algorithms such as the Variational Quantum Eigensolver (VQE), which Zapata Co-founder Alán Aspuru-Guzik co-invented, are currently not practical due to a prohibitive number of measurements required for the estimation subroutine, making them too slow to outperform classical supercomputers. In contrast, RAE reduces the measurement number and runtime compared to the standard sampling method for the estimation subroutine, with enterprise applications in chemistry, materials, finance, and beyond.

“When we first published research on RAE in 2019, it was a breakthrough that bridged near-term and far-term quantum computing,” said Peter Johnson, Zapata’s Lead Research Scientist and Co-Founder, who was an author of the initial paper. Subsequent research published with bp that found that RAE could reduce the runtime for VQE — a key algorithm for quantum chemistry — by one to two orders of magnitude. “RAE not only speeds up computations on today’s quantum devices, it accelerates the path to quantum advantage as devices mature.”

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