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Quantum computing replaces the binary digits (bits) of classical computing with quantum bits (qubits), which can exist in a superposition of both one and zero, on and off, and can become entangled. This means the state of one atom is determined by the state of its partner regardless of the distance between them.
Through manipulation of these phenomena – which only occur on the atomic, or quantum (smallest possible interacting) scale of matter – the processing ability of classical electric computers can be exponentially improved.
One of the barriers to quantum supremacy – the theoretical period in time in the future in which a quantum computer can be shown to complete any task better than a classical computer – is the minute complexity and precision required in the manufacture of quantum technology.
Prototype Quantum Computers
University researchers use prototype quantum computers to perform their experiments, but these typically need almost absolute zero ambient temperatures and a laboratory-controlled atmospheric environment to run properly. These prototype computers encode qubits either by trapping single ions or oscillating currents in superconducting loops.
Both methods rely on extreme precision to control the qubits they encode, either with complicated systems of lasers (in the trapped ion method) or with a radio wave device (in the oscillating currents method).
Research recently pioneered by the global information technology company, Intel, has produced a quantum computer using a third method, which is already well-known in the world of classical computing: using a semiconductor (silicon) to encode units of information.
If quantum technology can be reliably built using the semiconductor method of classical electric computing, then the manufacture of quantum computers would be much simpler, and large-scale manufacturing processes employed in the semiconductor chip industry could be transferred to quantum technology.
Silicon for Quantum Computers
Experimental physicist Bruce Kane was the first to propose silicon as a building block for quantum computers. He suggested that magnetic orientation (spin) in the nucleus of a phosphorous material’s atom could be embedded in silicon (Kane, 1998). In the same year, David DiVincenzo, working for IBM, and Daniel Loss of the University of Basel put a method for information storage in electron spin states within semiconductors forward (Loss and DiVincenzo, 1998).
However, in the decades since then, progress had been slow, due to the quality of available materials.
Producing Qubits
Recently, researchers at the University of New South Wales, Australia, embedded electrons and nuclei from the atoms of phosphorus matter in a silicon lattice to produce qubits from their spin states (clockwise or counterclockwise, giving one and zero states). This method, developed by Guilherme Tosi and Vivien Schmitt in the laboratory directed by Andrea Morello at UNSW, makes the spins more robust to interference from electrical noise, allowing a much longer lifetime of the fragile quantum state required for quantum computing (Gibney, 2016).
The first usable 2-qubit quantum computers created in silicon were designed in 2017, an important milestone reached by two teams of collaborators: Jason Pretta and colleagues at Princeton University (Zajac et al., 2017), and a team led by Lieven Vandersypen at the Delft University of Technology in the Netherlands (Watson et al., 2018).
Intel is investing $50 million over ten years in Vandersypen’s team at Delft. The company is producing multiple-qubit spin-based quantum computers with semiconductors in their cutting-edge microprocessor fabrication facility in Hillsboro, Oregon, for the Delft researchers to use.
Conclusion
While semiconductor-based quantum technology is still behind the more established approaches, Intel’s quantum technology chief, James Clarke, is optimistic about semiconductors’ role in quantum computing. “We hope that we can accelerate [research into] spin qubits to compete,” he says, and Intel’s investment in the Delft team signifies that his optimism is being supported (Castelvecchi, 2018).
Sources
- Castelvecchi, D. (2018). Silicon gains ground in quantum-computing race. Nature, 553(7687), pp.136–137.
- Gibney, E. (2016). Silicon quantum computers take shape in Australia. Nature, 533(7604), pp.448–449.
- Kane, B.E. (1998). A silicon-based nuclear spin quantum computer. Nature, 393(6681), pp.133–137.
- Loss, D. and DiVincenzo, D.P. (1998). Quantum computation with quantum dots. Physical Review A, 57(1), pp.120–126.
- Watson, T.F., Philips, S.G.J., Kawakami, E., Ward, D.R., Scarlino, P., Veldhorst, M., Savage, D.E., Lagally, M.G., Friesen, M., Coppersmith, S.N., Eriksson, M.A. and Vandersypen, L.M.K. (2018). A programmable two-qubit quantum processor in silicon. Nature, 555(7698), pp.633–637.
- Zajac, D.M., Sigillito, A.J., Russ, M., Borjans, F., Taylor, J.M., Burkard, G. and Petta, J.R. (2017). Resonantly driven CNOT gate for electron spins. Science, 359(6374), pp.439–442.
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