Keysight buys Quantum Benchmark

Keysight Technologies has picked up a software company that focuses on identifying and reducing errors in quantum computing, for an undisclosed sum.

Privately-held, venture-backed Canadian company Quantum Benchmark specializes in performance validation, error diagnostics and error suppression software for quantum computing. Its investors including VanEdge Capital and Quantonation. The company, which was spun off from the Institute of Quantum Computing at Canada’s University of Waterloo in 2017, has worked with companies including Google, IBM and Fujitsu Laboratories to support various quantum computing initiatives.

This is Keysight’s third quantum computing acquisition in the past few years, and Keysight says that the buy supports its goal to “deliver a comprehensive quantum portfolio addressing customer needs across the physical, protocol and application layers.” Keysight’s previous quantum-related purchases include Signadyne in 2016 and Labber Quantum — another university-associated start-up, born out of a quantum group at the Massachusetts Institute of Technology — in 2019.

Joseph Emerson, who is Quantum Benchmark’s CEO, founder and chief scientist, said that that acquisition is a “strategic and timely opportunity to accelerate the development and delivery” of Quantum’s solutions and will “bring the world closer to achieving the break-through applications of quantum computing including the design of energy-efficient materials, the acceleration of drug discovery, the promise of quantum machine learning, and so much more.”

As Keysight explained in a release on the acquisition, quantum systems use quantum bits, or qubits, to process data — but performance-limiting errors in qubit hardware “present the key challenge to large-scale quantum computing,” the company says. Quantum Benchmark’s technology improves the quality of the qubits across quantum hardware platforms helps quantum hardware makers design better qubits, the test company says, while also supporting quantum end-users stabilize the performance of qubits for their specific use-cases.

Comments are closed.