Dwave systems will make 128 quantum computing chips on each Cypress Semiconductor Wafer

Cypress Semiconductor Corp. and D-Wave Systems Inc., the world’s first commercial quantum computing company, today announced that D-Wave has successfully transferred its proprietary process technology for building quantum computing microprocessors to Cypress’s Wafer Foundry. D-Wave selected Cypress as its foundry and started the site change in January of 2013, and Cypress delivered first silicon on June 26. Results from this lot indicate better yields than D-Wave has achieved in the past, validating the quality of Cypress’s production-scale environment.

NASA Ames, Lockheed and Google have both bought D-Wave Quantum computing machines.

“We can make 120 quantum chips at a time, on an eight-inch wafer,” Colin Williams director of partnerships at D-Wave told TechWeekEurope. Williams joined D-Wave from NASA’s Jet Propulsion Laboratory (JPL) which built earlier chips for D-Wave. The newer generations are now built by Cypress Semiconductor’s silicon fab in Minnesota.

“The site change to Cypress will enable D-Wave to continue to scale its technology to meet its objective of delivering quantum processors that radically outperform conventional computing platforms,” said Eric Ladizinsky, D-Wave co-founder and Chief Scientist. “We selected Cypress as a foundry for their ability to support our unique materials and processing flow, while allowing us to leverage the consistency and yield of a production-scale wafer fab. The yield results we saw on first silicon exceeded our expectations and validate that Cypress was the right foundry choice for our technology development and processor production.

“While academics get about two designs of quantum computer a year, we can manage six to eight,” he said. “That is what differentiates us from the academic approach.”

D-Wave also uses a distinctive approach to quantum computing – quantum “annealing” – which has caused some controversy. The machine is designed to solve optimisation problems where the user wants to find the best solution out of many millions of possibilities. The D-Wave machine solves a particular one of these “NP-hard” problems, in the following way. It is designed so that the solution to the problem will have the lowest energy state: it starts in a coherent state in which the possible solutions exist simultaneously and then settles until only one state exists – the solution.

It’s called annealing because of the similarity with metallic solids which can gradually settle to a lower energy state as their crystalline structure re-aligns. “If you can solve one NP-hard problem well, you can transform others onto it,” said Williams. This means that quantum computers could potentially be used for jobs like financial modelling and analysing the structures of proteins.

From the start, D-Wave has faced controversy. At first, academics expressed doubts that its systems were actually exhibiting quantum computing at all – but a USC research team led by Sergio Boxio found in July that it appears to be real quantum computing (paper published at Arxiv). However, sceptics still argue over whether the system actually produces real benefits over classical computer systems that could be run on ordinary laptops.

DWave’s Colin Williams says that NASA found the system to be 10,000 times faster than a state-of-the-art algorithm running on an off-the-shelf 2.4GHz Intel chip. “The system is also tunable,” he said, “so we have got up to 35,000 times faster.”

He also made two other claims.

1) that quantum computers can scale up faster (exponentially) than conventional computers, with each qubit added: “As the number of qubits goes up, the search space gets exponentially bigger”.

2) he claimed that while the classical approach brings back correct solutions, the quantum computer brings back the best correct solution. “You can use it in conjunction with a high performance computer to get better results,” he said.

There is some overhead in mapping other NP-hard problems to the D-Wave system, but D-Wave is working on other possible architectures that solve problems with easier mappings to real-world problems.

Dwave expects to have 2000 qubits by 2015.

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