DESIGNS FOR A UNIVERSAL QUANTUM COMPUTER
SILICON SPIN QUBITS
LONGEVITY 0.03 – 30 seconds LOGIC SUCCESS RATE ~99% NUMBER ENTANGLED 2
LONGEVITY 0.00005 seconds LOGIC SUCCESS RATE 99.4% NUMBER ENTANGLED 9
LONGEVITY 1,000 seconds LOGIC SUCCESS RATE 99.9% NUMBER ENTANGLED 14
A number of options exist. Dopant atoms such as phosphorus or arsenic, can be added to a silicon crystal; either the spin of the dopant atom’s nucleus, or that of the electrons in orbit around it, are used to create qubits. The nuclear spin approach holds the record in the solid state for a longevity of 30 seconds. Similar spin qubits can also be made artificially, using electrodes and semiconductor structures to trap electrons inside quantum dots. Silicon, purified of all its isotopes except for one, helps boost the stability of qubits; it also has the advantage of using the tools and infrastructure of the existing global computer industry. The small size of quantum dots and attendant systems makes interconnects challenging, but also allows a small footprint even when integrating a huge number of qubits. While scalable architectures exist on paper, they have yet to be demonstrated.
Qubits are created from a loop of superconducting material, such as aluminium, paired with thin insulating barriers through which pairs of electrons can tunnel. One approach is to use the direction of current running around the loop to make a ‘flux qubit’; when the qubit is in a superposition, current flows in both directions at the same time. Stability has been an issue, but has improved dramatically, and flux qubits can be entangled with one another with good fidelity in superconducting buses. The space required is very large: a qubit can measure in the millimetres when a resonator to control it is included. Extremely low temperatures, in the thousandths of a degree above absolute zero (or -273˚C), are also needed.
The outermost electron of an ion (eg. calcium) is used to create a qubit in two states, defined either by the electron’s orbital state or its interaction with the atom’s nucleus. Among the first designs investigated, ion traps have since been miniaturised and can now be implemented on a chip with electrodes, used to suspend ions in mid-air and move them around. Some traps can hold more than 10 qubits at a time. Since the ions are made to hover, qubits can be well isolated from stray fields and are extremely stable. Disadvantages are that qubits must be made in ultra-high vacuum to prevent interactions with other atoms, and ion qubits must be pushed together to entangle – difficult to do with high precision because of electrical noise.
COMPANIES Intel, HRL
COMPANIES Google, IBM, Intel, Quantum Circuits, DWave, Rigetti RESEARCH LEADERS UC Santa Barbara, ETH Zurich, TU Delft, Yale, UC Berkeley, MIT/Lincoln Labs
RESEARCH LEADERS UNSW, University of Wisconsin-Madison, TU Delft, Princeton, Sandia National Labs, RIKEN
COMPANIES ionQ RESEARCH LEADERS University of Innsbruck, US National Institute of Standards and Technology, University of Oxford, University of Maryland, MIT, University of Sussex
UNSW’S THREE WAYS OF MAKING
A SILICON QUBIT
Simmons’s team creates precision atomic-scale transistors where each atom naturally hosts the spin qubit and can be uniquely engineered to form large arrays for error-corrected quantum computing processors.
Morello’s team encodes quantum data into the spin of phosphorus atoms, inserted into the silicon chip in an industry-standard process. They then build electrodes and transistors around the atoms to control their quantum state.
Dzurak’s team modifies silicon transistors to make quantum dots, or ‘artificial atoms’. A metal electrode attracts one electron underneath it, and its spin encodes the qubit. These can be strung together to create entangled qubit arrays.
state ‘collapse’ into one of its many possible states, giving you the answer to your calculation problem. If software algorithms can be designed to make use of superposition and entanglement to arrive at an answer in a much smaller number of steps, the ability of a quantum computer to work in parallel would make it, in many cases, millions of times faster than any conventional computer. How fast is that? One way to measure the processing speed of computers is to calculate their number of ‘flops’, or FLoating-point OPerations per Second. Today’s typical desktop computers run at gigaflops (billions of flops, or 109). By comparison, the world’s fastest supercomputer, China’s Sunway
Published on Jun 1, 2017
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