Quantum technology (QT) applies quantum mechanical properties such as quantum entanglement, quantum superposition, and No-cloning theorem to quantum systems such as atoms, ions, electrons, photons, or molecules.
Quantum bit is the basic unit of quantum information. Whereas in a classical system, a bit is either in one state or the another. However, quantum qubits can exist in large number of states simultaneously, property called Superposition.
Quantum entanglement is a phenomenon where entangled particles can stay connected in the sense that the actions performed on one of the particles affects the other no matter what’s the distance between them. No-cloning theorem tells us that quantum information (qubit) cannot be copied.
Quantum computers shall bring power of massive parallel processing, equivalent of supercomputer to a single chip. They can consider different possible solutions to a problem simultaneously, quickly converge on the correct solution without check each possibility individually. This dramatically speed up certain calculations, such as number factoring.
A working quantum computer has the potential to transform the information economy and create the industries of the future, solving in hours or minutes problems that would take conventional computers – even supercomputers – centuries, and tackling otherwise intractable problems that even supercomputers could not solve. Applications include for software design, machine learning, scheduling and logistical planning, financial analysis, stock market modelling, software and hardware verification, climate modelling, rapid drug design and testing, and early disease detection and prevention.
Quantum bits, or qubits, are the basic building blocks of quantum computers, just as bits are that of modern computers. The power of quantum computers depends on the number of qubits and their quality measured by coherence, and gate fidelity. Qubit is very fragile, can be disrupted by things like tiny changes in temperature or very slight vibrations. Coherence measures the time during which quantum information is preserved. The gate fidelity uses distance from ideal gate to decide how noisy a quantum gate is.
Researchers around the world have been exploring a range of different physical systems to act as qubits, including Superconducting quantum computing (qubit implemented by the state of small superconducting circuits (Josephson junctions)); Trapped ion quantum computer (qubit implemented by the internal state of trapped ions); Optical lattices (qubit implemented by internal states of neutral atoms trapped in an optical lattice); Quantum dot computer, spin-based (e.g. the Loss-DiVincenzo quantum computer) (qubit given by the spin states of trapped electrons), and Quantum dot computer, spatial-based (qubit given by electron position in double quantum dot.) . Qubits hold great promise, but unlike bits in traditional computing, they are error prone. This means millions are required for complex calculations to allow for error correction.
Recently, however, experimental breakthroughs in silicon-based nanodevices have brought a another option, to manufacture quantum processors in the same way as conventional microprocessors, by leveraging widely deployed industrial complementary metal-oxide-semiconductor (CMOS) technology. Spin qubits highly resemble the semiconductor electronics and transistors as we know them today. They deliver their quantum power by leveraging the spin of a single electron on a silicon device and controlling the movement with tiny, microwave pulses. Electron spins in silicon quantum dots are attractive systems for quantum computing owing to their long coherence times and the promise of rapid scaling of the number of dots in a system using semiconductor fabrication techniques.
The idea of silicon quantum computing was first proposed in 1998 by Bruce Kane, a physicist at the University of Maryland, in College Park. Quantum computers based on familiar silicon could theoretically be manufactured in conjunction with the conventional semiconductor techniques found in today’s computer industry. A silicon approach to quantum computing also offers the advantage of strong stability and high coherence times for qubits. (High coherence times mean the qubits can continue holding their information for long enough to complete calculations.) Kane proposed using the quantum characteristic of spin in the nucleus of the phosphorus donor atom as the qubit.
Feasibility of Quantum computer in Silicon
Historically, silicon qubits have been shunned for two reasons: It’s difficult to control qubits manufactured on silicon, and it’s never been clear if silicon qubits could scale as well as other solutions. However, as seen with small-scale demonstrations of quantum computers using other types of qubit, combining these elements leads to challenges related to qubit crosstalk, state leakage, calibration and control hardware.
Three breakthrough papers have confirmed that silicon is neck-and-neck with competing technology for quantum computing, including those under active research by corporate giants Google, Microsoft and IBM. The first, published in the journal Nature Electronics, showed silicon reaching an accuracy (or fidelity) for one-qubit logic of 99.96%. “This puts it on an even par with all other competing qubit technologies”, explains Dzurak, “since all qubits have errors, and these must be kept very low if we want to do useful computations, otherwise the final answers to calculations will be unreliable.”
The result was followed up by a second paper, in the journal Nature, which demonstrated that two-qubit computations had reached 98% accuracy, an important step because linking qubits together is how quantum computations are undertaken. These two sets of findings are key to constructing more feasible quantum computers, because greater accuracy means fewer redundant qubits are required for error correction.
A third paper, published in the journal Nature Nanotechnology in May 2019, took the team’s work to an all-new practical level. “It shows it is possible to read out the state of a quantum bit in a silicon device using only a single wire (in this case a nanoscale electrode), vastly simplifying the on-chip electronics needed for a full-scale quantum processor chip,” explains Dzurak. The fewer qubits required for processing problems, combined with reducing the size of read-outs required for each qubit enough, dramatically reduces the size and complexity of a quantum computer, thus bringing it that much closer to reality
Scientists and engineers from the Australian Research Council Centre of Excellence for Quantum Computation and Communication Technology (CQC2T), are developing a scalable quantum computer in silicon. They found that a single atom of phosphorus could be used to tightly hold an electron, which also carries a “spin” (like a tiny magnet) that could be used as a quantum bit.
In August 2021, scientists from Japan reported having discovered a stable quantum entangled state of two protons on a silicon surface, opening doors to an organic union of classical and quantum computing platforms and potentially strengthening the future of quantum technology. By looking at the surface spin states, the scientists discovered an entangled pair of protons on the surface of a silicon nanocrystal.
The scientists studied the spin states using a technique known as “inelastic neutron scattering spectroscopy” to determine the nature of surface vibrations. By modeling these surface atoms as “harmonic oscillators,” they showed anti-symmetry of protons. Since the protons were identical (or indistinguishable), the oscillator model restricted their possible spin states, resulting in strong entanglement. Compared to the proton entanglement in molecular hydrogen, the entanglement harbored a massive energy difference between its states, ensuring its longevity and stability. Additionally, the scientists theoretically demonstrated a cascade transition of terahertz entangled photon pairs using the proton entanglement.
The confluence of proton qubits with contemporary silicon technology could result in an organic union of classical and quantum computing platforms, enabling a much larger number of qubits (106) than currently available (102), and ultra-fast processing for new supercomputing applications.
Prof. Matsumoto, the lead scientist, outlines the significance of their study: “Proton entanglement has been previously observed in molecular hydrogen and plays an important role in a variety of scientific disciplines. However, the entangled state was found in gas or liquid phases only. Now, we have detected quantum entanglement on a solid surface, which can lay the groundwork for future quantum technologies.” Their pioneering study was published in a recent issue of Physical Review B.
Advantages of Silicon qubits, in comparison to their superconducting counterparts
Morello and Dzurak were among the physicists impressed by Kane’s proposal, but they chose to investigate electron spins instead, because electron spins in silicon have very long coherence times—that is, it takes a relatively long time for such a qubit to lose its information. So far, the UNSW team has demonstrated a system with quantum bits, or qubits, only in a single atom. Australian teams demonstrated mastery of single qubits based on electron spin in 2012 and control of nuclear spin qubits in 2013. Useful computations will require linking qubits in multiple atoms.
But the team’s silicon qubits hold their quantum state nearly a million times longer than do systems made from superconducting circuits, a leading alternative, said UNSW physicist Guilherme Tosi reported by Nature. This helps the silicon qubits to perform operations with one-sixth of the errors of superconducting circuits.
The scheme showcased at the innovation forum by Tosi and fellow physicist Vivien Schmitt uses qubits that are the spins of the electrons and nuclei in phosphorus atoms embedded in a silicon lattice, and are controlled using a special system of electric fields. Because the spins respond only to very specific, tuneable frequencies, they are robust to electrical noise. That allows the qubits to keep their quantum states for one minute and to operate perfectly 99.9% of the time, said Tosi.
Moreover, the electrically controlled qubits can communicate with each other at larger distances than can the qubits in other silicon designs. That bodes well for scaling up because the qubits can be far enough apart to allow room for control and read-out instruments to be placed between them. The atoms also do not need to be placed precisely, so they would fit with existing microprocessor-fabrication techniques, added Tosi.
They’re small and strong: Spin qubits are much smaller in physical size and their coherence time is expected to be longer – an advantage as researchers aim to scale the system to the millions of qubits that will be required for a commercial system. Superconducting qubits are quite large and they operate in systems the size of 55-gallon drums, which makes it hard to scale up the design of the quantum system to the millions of qubits necessary to create a truly useful commercial system.
They can function at higher temperatures: Silicon spin qubits can operate at higher temperatures than superconducting qubits (1 kelvin as opposed to 20 millikelvin). This could drastically reduce the complexity of the system required to operate the chips by allowing the integration of control electronics much closer to the processor. Intel and academic research partner QuTech* are exploring higher temperature operation of spin qubits with interesting results up to 1K (or 50x warmer) than superconducting qubits. The team is planning to share the results at the American Physical Society (APS) meeting in March.
Silicon qubit advances
In 2017, two groups reached a milestone when they designed the first fully controllable two-qubit devices in silicon. Petta and his collaborators achieved that feat, as did a separate team led by Lieven Vandersypen at Delft. Intel, which is investing US$50 million over 10 years at Delft, is now manufacturing multiple-qubit electron-spin devices for Vandersypen, in the same type of factory where it develops microprocessor-fabrication techniques. Industrial partners can help by providing reliably identical devices, he says.
In a paper published in Nature, researchers at Delft University of Technology in the Netherlands and the University of Wisconsin–Madison say they were able to program a two-qubit machine based on spin qubits to execute a couple of algorithms that are typically employed to test the effectiveness of quantum machines, including one that could be used for searching a database. “Here we overcome these challenges by using carefully designed control techniques to demonstrate a programmable two-qubit quantum processor in a silicon device that can perform the Deutsch–Josza algorithm and the Grover search algorithm—canonical examples of quantum algorithms that outperform their classical analogues.”
Thomas Watson, one of the researchers, says the team’s advance was based on things such as finding better ways to calibrate the “gates” in the machine, or the basic quantum circuits. He thinks that silicon-based systems could ultimately allow qubits to be packed more densely together than other approaches. The closer qubits are to one another, the easier it is to get them to influence neighbors, which boosts machines’ computational power.
Two teams from Australia are experimenting with two different types of Qbits, one team is using natural atom made of Phosphorous which contains two quantum bits electron and nuclear spin and on which they have achiever 99.99% accuracy that leads to 1 error in every 10,000 operations.
The second team is working with artificial atom that harness silicon to build a quantum processor with advantage of it being compatible with the microelectronics of existing computers. The spin of an electron or a nucleus in a semiconductor naturally implements the unit of quantum information – the qubit – while providing a technological link to the established electronics industry. However naturally occurring silicon contains about 92% 28Si, and other isotopes including 29Si at about 4.7%, which is a dominant factor for decoherence. For silicon then, coherence time can be drastically improved through the isotopic enrichment of the spin-zero nuclear species 28Si.
So far, the UNSW team has demonstrated a system with quantum bits, or qubits, only in a single atom. Useful computations will require linking qubits in multiple atoms. But the team’s silicon qubits hold their quantum state nearly a million times longer than do systems made from superconducting circuits, a leading alternative, UNSW physicist Guilherme Tosi told participants at the event. This helps the silicon qubits to perform operations with one-sixth of the errors of superconducting circuits. A second group from the UNSW has a less robust silicon design that has already demonstrated calculations that link up two qubits, a building block that paves the way for creating more-complex devices.
Systems will need to be scaled up to a large number of qubits to execute nontrivial quantum algorithms so that these quantum devices can simulate quantum systems efficiently, crack modern encryption codes, search through huge databases, as well as solve a wide range of optimization problems.
Australian engineers have created a new ultra stable quantum bit
Researchers at the University of New South Wales in Australia have designed a new type of quantum bit (qubit), which they say will enable large-scale quantum computing at a lower cost. The new ‘flip-flop qubits’ are able to communicate over distances of more than 150nm, which researcher leader Andrea Morello said might actually leave room to “cram other things between qubits.” What the team have invented is a new way to define a ‘spin qubit’ that uses both the electron and the nucleus of the atom. Crucially, this new qubit can be controlled using electric signals, instead of magnetic ones,” said Prof Morello.
Morello and his team proposed a method of using both the electron and nucleus of a single phosphorous atom, to create a qubit inside a layer of silicon. ‘Pulling’ the electron away from the nucleus would extend the electric field that qubits use for entanglement. As well as leaving more space, the new chip designs would also overcome the need for atoms to be very precisely placed.
Even more important, though, is the fact that the new chips could be produced using existing manufacturing technology, which opens up the possibility of mass production. Morello said that this “makes the building of a quantum computer much more feasible.” “This new idea allows us to fabricate multi-qubit processes with current technology,” says Guilherme Tosi, the lead scientist.
Australian engineers team from Australia’s University of New South Wales (UNSW) had earlier reported to have created a new quantum bit which remains in a stable superposition for 10 times longer than previously achieved, dramatically expanding the time during which calculations could be performed in a future silicon quantum computer. “We have created a new quantum bit where the spin of a single electron is merged together with a strong electromagnetic field,” said Arne Laucht, a Research Fellow at the School of Electrical Engineering & Telecommunications at UNSW, and lead author of the paper. “This quantum bit is more versatile and more long-lived than the electron alone, and will allow us to build more reliable quantum computers.”
“The greatest hurdle in using quantum objects for computing is to preserve their delicate superpositions long enough to allow us to perform useful calculations,” said Andrea Morello, leader of the research team and a Program Manager in the Centre for Quantum Computation & Communication Technology (CQC2T) at UNSW.
“Our decade-long research program had already established the most long-lived quantum bit in the solid state, by encoding quantum information in the spin of a single phosphorus atom inside a silicon chip, placed in a static magnetic field,” said Andrea Morello. The results are striking: since the electromagnetic field steadily oscillates at a very high frequency, any noise or disturbance at a different frequency results in a zero net effect. The researchers achieved an improvement by a factor of 10 in the time span during which a quantum superposition can be preserved.
Specifically, they measured a dephasing time of T2*=2.4 milliseconds – a result that is 10-fold better than the standard qubit, allowing many more operations to be performed within the time span during which the delicate quantum information is safely preserved. “This new ‘dressed qubit’ can be controlled in a variety of ways that would be impractical with an ‘undressed qubit’,”, added Morello. “For example, it can be controlled by simply modulating the frequency of the microwave field, just like in an FM radio. The ‘undressed qubit’ instead requires turning the amplitude of the control fields on and off, like an AM radio.
“In some sense, this is why the dressed qubit is more immune to noise: the quantum information is controlled by the frequency, which is rock-solid, whereas the amplitude can be more easily affected by external noise”. Since the device is built upon standard silicon technology, this result paves the way to the construction of powerful and reliable quantum processors based upon the same fabrication process already used for today’s computers. What Laucht and colleagues did was push this further: “We have now implemented a new way to encode the information: we have subjected the atom to a very strong, continuously oscillating electromagnetic field at microwave frequencies, and thus we have ‘redefined’ the quantum bit as the orientation of the spin with respect to the microwave field.”
Australia’s first quantum computing company, Silicon Quantum Computing Pty Ltd, has been launched to advance the development and commercialisation of the University of New South Wales (UNSW Sydney)’s world-leading quantum computing technology. It will drive the development and commercialisation of a 10-qubit quantum integrated circuit prototype in silicon by 2022 as the forerunner to a silicon based quantum computer.
CQC2T is home to an incredibly strong team of silicon quantum computing researchers being the only group in the world that can make atomically precise devices in silicon. Led by UNSW Scientia Professor Michelle Simmons, the Centre’s teams have produced the longest coherence time qubits in the solid state, the ability to optically address single dopant atoms in silicon, the lowest noise silicon devices and the first two qubit gate in silicon.
Researchers at the University of New South Wales (UNSW) built a two-qubit logic gate in silicon
A second group from the UNSW led by physicist Andrew Dzurak, uses as its qubits the spins of electrons in a set-up that is based on modified electrical transistors. Although the qubits are less robust than those in the Morello design, Dzurak’s team demonstrated two-qubit calculations last October.
Researchers reported in the journal Nature that they have built a two-qubit logic gate containing two entangled qubits, based on spins of trapped electrons in silicon for the first time and thereby clearing the hurdle to making silicon-based quantum computer processors a reality.
Such trapped electrons can be integrated with existing CMOS technology, to create quantum computer chips that could store thousands, even millions of qubits on a single silicon processor chip. UNSW scientists have patented a design for a full-scale quantum chip that would hold millions of silicon qubits.
The UNSW researchers then simulated fundamental gate: the controlled NOT or CNOT operation through their two-qubit logic gate. Depending on the state of the control qubit, the CNOT gate changes an “up” spin into a “down” spin, and the other way around. The CNOT is the fundamental gate that can be combined to form complex quantum computations just as NAND gate is fundamental gate in conventional computers.
“For the creation of the two-qubit gate the researchers modified the design of a CMOS transistor. Two gates are placed next to each other on an insulating layer of silicon dioxide that separates them from a layer of almost pure silicon-28 isotope, writes Alexander Hellemans,” in IEEE spectrum.
Controlling the voltage of the gates allows the trapping of a single electron in the region under the gate. The quantum states of both electrons can be controlled by gigahertz-frequency pulses transmitted by the “electron spin resonance” (ESR) line, in combination with a 1.4 Tesla magnetic field.
The ESR line allows the spin state for each electron to be set independently for “one-qubit” operations. Voltage pulses entangle the two qubits, allowing them to operate as a CNOT gate; changing the spin of one electron results in changing the spin of the other electron. The authors write in Nature, “Here we present a two-qubit logic gate, which uses single spins in isotopically enriched silicon and is realized by performing single- and two-qubit operations in a quantum dot system using the exchange interaction, as envisaged in the Loss–DiVincenzo proposal.
“We realize CNOT gates via controlled-phase operations combined with single-qubit operations. Direct gate-voltage control provides single-qubit addressability, together with a switchable exchange interaction that is used in the two-qubit controlled-phase gate. By independently reading out both qubits, we measure clear anticorrelations in the two-spin probabilities of the CNOT gate.”
Australian scientists design a full-scale architecture for a quantum computer in silicon
“Our Australian team has developed the world’s best qubits in silicon,” says University of Melbourne Professor Lloyd Hollenberg, Deputy Director of the CQC2T who led the work with colleague Dr Charles Hill. “However, to scale up to a full operational quantum computer we need more than just many of these qubits – we need to be able to control and arrange them in such a way that we can correct errors quantum mechanically.”
Australian scientists have designed a 3D silicon chip architecture based on single atom quantum bits, one of the final hurdles to scaling up to an operational quantum computer many thousands of qubits. Researchers detailed an architecture that sandwiches a 2-D layer of nuclear spin qubits between an upper and lower layer of control lines. Such triple-layer architecture enables a smaller number of control lines to activate and control many qubits all at the the same time.
By applying voltages to a sub-set of these wires, multiple qubits can be controlled in parallel, performing a series of operations using far fewer controls. Importantly, with their design, they can perform the 2D surface code error correction protocols in which any computational errors that creep into the calculation can be corrected faster than they occur.
“This architecture gives us the dense packing and parallel operation essential for scaling up the size of the quantum processor,” says Scientia Professor Sven Rogge, Head of the UNSW School of Physics. “Ultimately, the structure is scalable to millions of qubits, required for a full-scale quantum processor.”
In theory, the new architecture could pack about 25 million physical qubits within an array that’s 150 micrometers by 150 µm. But those millions of qubits would require just 10,000 control lines. By comparison, an architecture that tried to control each individual qubit would have required over 1000 times more control lines.
“We have demonstrated we can build devices in silicon at the atomic-scale and have been working towards a full-scale architecture where we can perform error correction protocols – providing a practical system that can be scaled up to larger numbers of qubits,” says UNSW Scientia Professor Michelle Simmons, study co-author and Director of the CQC2T.
If the team can pull off this low error rate in a larger system, it would be “quite amazing”, said Hartmut Neven, director of engineering at Google and a member of the panel. But he cautioned that in terms of performance, the system is far behind others. The team is aiming for ten qubits in five years, but both Google and IBM are already approaching this with superconducting systems. And in five years, Google plans to have ramped up to hundreds of qubits.
New silicon-based quantum bits produce photons that may provide the basis for quantum internet and Quantum computers, reported in June 2022
Researchers at Canada’s Simon Fraser University have taken a new look at silicon – an element already at the centre of modern computer chips – to make quantum bits, or “qubits”. One approach, published in Nature, is to use the “photon-spin” produced by defects in silicon as a transistor. Spin is an intrinsic property of particles like photons, which is a type of angular momentum. Particles can be thought of as spinning like a top – the particles are either spinning up or down (like turning the top upside down). Up and down can therefore be translated into ones and zeroes.
Their research, published in Nature , describes their observations of over 150,000 silicon ‘T centre’ photon-spin qubits, an important milestone that unlocks immediate opportunities to construct massively scalable quantum computers and the quantum internet that will connect them.
Past research has indicated that silicon can produce some of the most stable and long-lived qubits in the industry. Now the research published by Daniel Higginbottom, Alex Kurkjian, and co-authors provides proof of principle that T centres, a specific luminescent defect in silicon, can provide a ‘photonic link’ between qubits. This comes out of the SFU Silicon Quantum Technology Lab in SFU’s Physics Department, co-led by Stephanie Simmons, Canada Research Chair in Silicon Quantum Technologies and Michael Thewalt, Professor Emeritus.
“This work is the first measurement of single T centresin isolation, and actually, the first measurement of any single spin in silicon to be performed with only optical measurements,” says Stephanie Simmons.
“An emitter like the T centre that combines high-performance spin qubits and optical photon generation is ideal to make scalable, distributed, quantum computers, because they can handle the processing and the communications together, rather than needing to interface two different quantum technologies, one for processing and one for communications,” Simmons says.
In addition, T centres have the advantage of emitting light at the same wavelength that today’s metropolitan fibre communications and telecom networking equipment use.
“With T centres, you can build quantum processors that inherently communicate with other processors,” Simmons says. “When your silicon qubit can communicate by emitting photons (light) in the same band used in data centres and fiber networks, you get these same benefits for connecting the millions of qubits needed for quantum computing.”
Arrival of Silicon based quantum integrated circuits
Proponents of the silicon technique see major advantages in using a semiconductor to code qubits. They can be manipulated much more simply using microscopic electric leads etched right onto the chip. And if the same large-scale manufacturing techniques for making chips could be transferred to the quantum realm, it could become easier to turn the technology into commercial products.
However, integrating CMOS electronics and silicon-based qubits into a single, monolithic chip throw many challenges. In some respects, VLSI technology, thanks to its focus on minimizing the impact of process variation, guarantees a level of reproducibility that no other industry can provide. However, in the quantum realm, variability acquires a much higher degree of importance. Even a single atomic-level defect (for example in the quality of the interfaces or the purity and crystallinity of the material) may lead quantum devices to perform very differently.
Although both technologies can be manufactured using existing silicon industrial processes, these processes currently involve different technological nodes; that is, they employ slightly different processing standards and protocols at the manufacturing stage. A common “classical-quantum” node will have to be developed and consolidated to produce hybrid quantum circuits at scale.
Full integration also implies that both technologies will have to operate at the same temperature. This problem is non-trivial given that qubits operate better at deep cryogenic temperatures (a few millikelvin), while the current models for integrated-circuit design are rarely accurate for temperatures below 20 K. Understanding the behaviour of silicon transistors (either as digital or as analogue circuit elements) at millikelvin temperatures will require a development effort of its own. To support that effort, researchers will need to develop precise models that can be imported into existing electronic computer-aided design tools.
Intel Bets It Can Turn Everyday Silicon into Quantum Computing’s Wonder Material
Intel’s silicon qubits represent data in a quantum property called the “spin” of a single electron trapped inside a modified version of the transistors in its existing commercial chips. “The hope is that if we make the best transistors, then with a few material and design changes we can make the best qubits,” says Clarke. The design of the spin qubit processors highly resembles the traditional silicon transistor technologies. While there are key scientific and engineering challenges remaining to scale this technology, Intel has the equipment and infrastructure from decades of fabricating transistors at scale.
The company recently revealed its tiniest quantum chip yet–it’s so small that it can sit comfortably on a pencil eraser. The chip is powered by qubits that are each more than a thousand times smaller than a single strand of hair. In a typical superconducting quantum computer, qubits live in small loops of superconducting wire cooled to very low temperatures. Intel’s transistor-free chip relies on a more manageable, readily available, and quintessentially traditional component: silicon. Some researchers say the retro element that inspired an industry (and a metaphor, a competitive housing market, and a television show) might be key for the next phase of quantum computing.
Intel has invented a spin qubit fabrication flow on its 300 mm process technology using isotopically pure wafers sourced specifically for the production of spin-qubit test chips. Fabricated in the same facility as Intel’s advanced transistor technologies, Intel is now testing the initial wafers. Within a couple of months, Intel expects to be producing many wafers per week, each with thousands of small qubit arrays.
The new process that helps Intel experiment with silicon qubits on standard chip wafers, developed with the materials companies Urenco and Air Liquide, should help speed up its research, says Andrew Dzurak, who works on silicon qubits at the University of New South Wales in Australia. Companies developing superconducting qubits also make them using existing chip fabrication methods. But the resulting devices are larger than transistors, and there is no template for how to manufacture and package them up in large numbers, says Dzurak.
Another key limitation, Petta emphasizes, is “material, material, material.” Spin qubits require exceptionally clean silicon, in terms of chemical purity and isotopic enrichment.
Intel’s group has reported that they can now layer the ultra-pure silicon needed for a quantum computer onto the standard wafers used in chip factories. A quantum computer would need to have thousands or millions of qubits to be broadly useful, and to get to hundreds of thousands of qubits, we will need incredible engineering reliability, and that is the hallmark of the semiconductor industry, according to Andrew Dzurak, who works on silicon qubits at the University of New South Wales in Australia says. Another reason to work on silicon qubits is that they should be more reliable than the superconducting equivalents.
Silicon Quantum Computing Pty. Ltd. (SQC) is working to create and commercialize a quantum computer based on world-leading intellectual property acquired from the Australian Centre of Excellence for Quantum Computation and Communication Technology (CQC2T). We have set ourselves a bold ambition: to develop a 10-qubit quantum integrated circuit prototype in silicon by 2022.
Quantum Motion unveils 9-second silicon qubit
Quantum Motion, a four-year-old UK-based startup is announced in March 2021 a quantum computing breakthrough, demonstrating that a stable qubit can be created on a standard silicon chip, similar to those used in smartphones. By cooling the chip down to a temperature just above absolute zero (−273°C), and by using tiny transistors, the Quantum Motion team were able to isolate a single electron and measure its quantum state for an astounding nine seconds. The discovery has been peer-reviewed in the scientific journal PRX Quantum.
John Morton, professor of nanoelectronics at UCL and cofounder of Quantum Motion said the Quantum Motion technique could be “a blueprint to shortcut our way to industrial-scale quantum chip production” tapping into the already existing silicon chip industry. Of course, Quantum Motion has demonstrated just one qubit, which may not seem very impressive compared to the 50+ qubits that have been achieved by Google and IBM.
“Both 1 qubit and 50 qubits are almost equally far away from 1m. Some technologies may be quicker in getting to 10 or even 50 qubits but would struggle after that. The key is to find something that is truly scalable,” he told Sifted. Some of the quantum computing technologies may also be quite bulky when you scale up to multiple thousands of qubits. But in theory, a million of Quantum Motion’s electron-spin qubits could be packed onto a 1cm square chip. You would still need the elaborate chandelier-like refrigerator to keep the chips at a fraction of a kelvin above absolute zero, but just one such refrigerator — similar in size to a server rack — can hold many chips.
Quantum Motion is one of a number of quantum computer companies that are trying to create quantum computing components out of more readily-available materials. UK-based ORCA, for example, is using standard optical cable used in the telecoms industry to isolate single photons for use as qubits. Such an approach, if successful, would dramatically decrease the cost of building a quantum computer, from tens of millions of dollars to less than $1m.