Quantum computing is building momentum after scientists at the University of Southern California (USC), US, put the first, so-called quantum processor through its paces. Lockheed Martin purchased the D-Wave 128 qubit processor almost two years ago and housed it at USC’s Viterbi Information Sciences Institute (ISI).
“Using a specific test problem involving eight qubits, we’ve verified that the D-Wave processor performs optimization calculations – finds lowest energy solutions – using a procedure that is consistent with quantum annealing," said Daniel Lidar, the lead scientist on the project and director of the USC-Lockheed Martin Quantum Computing Center (QCC), in Marina del Ray, CA, US.
Sergio Boixo, first author of the June 2013 Nature Communicationspaper on the research, echoed Lidar: From a purely physical point of view, quantum effects definitely play a functional role in information processing in the D-Wave processor.
Quantum annealing is a method of solving optimization problems using quantum mechanics. The superposition principle of quantum mechanics holds that any physical system – imagine a coffee mug or computer mouse – exists in more than one state at exactly the same time. In fact, your mug or mouse could exist in all possible theoretical states or locations at the same time. Mind-blowingly, your mug or mouse is everywhere at every moment.
What does this have to do with quantum computing? In an everyday computer, a transistor stores a single ‘bit’ of information, which can either be 1 or 0 but not both at the same time. In quantum computing, the qubit can store 1 and 0 simultaneously. This means two qubits can store four values (00, 01, 10, and 11), and these values increase as you add even more qubits. Ultimately, you could use quantum computing to create an exponentially more powerful machine.
If you follow the observations of Moore’s law, there is a limit to the number of transistors you can fit on a single chip. The cost of the energy required to power massive supercomputers is also an issue. There are also optimization problems that scientists cannot unravel with existing technology.
“For example, it would take many times the age of the universe to try to identify the folded state of a protein. And yet nature can do this in seconds, or maybe minutes. It’s had billions of years to think about it,” Lidar explains.
Quantum computing offers an alternative. If you can simulate 20 years of evolution in 10 nanoseconds, then you can quickly close in on key developments in the lifecycles of the systems you’re researching. This could lead to problem solving in energy, healthcare, transportation, and climate domains, just to name a few – in other words, to doing more than we ever thought possible.
The research findings came out shortly after QCC upgraded the original D-Wave processor to a new 512 qubit chip. The “Vesuvius” chip and computer are protected by a magnetically shielded box, which is kept at a temperature near absolute zero to prevent decoherence. A second Vesuvius chip owned by Google and housed at NASA’s Ames Research Center in Moffet Field, CA, US, is expected to be operational later this year. Google will use the system to help advance machine learning – and they just hired Boixo to help them gain traction in quantum computing.