In the race to create quantum computing hardware, silicon is starting to shine

A silicon-based device is in development for use in quantum computers. The gate electrodes, shown in blue, red, and green, are used to determine the potentials of the quantum dots, and the micromagnet at the top provides a gradient of the magnetic field. The image was taken by scanning electron microscopy, and colors were applied for clarity. Author: Adam Mills, Princeton University

Research by physicists at Princeton University is paving the way for the use of silicon technology in quantum computing, especially as quantum bits, the basic building blocks of quantum computers. This study promises to accelerate the use of silicon technology as a viable alternative to other quantum computing technologies such as superconductors or trapped ions.

In a study published in the journal Advances in science, Princeton physicists used a two-qubit silicon quantum instrument to achieve an unprecedented level of accuracy. Above 99 percent, this is the highest accuracy ever achieved for a two-cubic-meter semiconductor shutter, and on par with the best results achieved by competing technologies. Loyalty, which is a measure of a qubit’s ability to perform error-free operations, is a key feature in the search to develop practical and efficient quantum computations.

Researchers from around the world are trying to figure out which technologies – such as superconducting qubits, trapped ions or spin qubits of silicon – are best used as the basic blocks of quantum computing. And last but not least, researchers are studying which technologies will be able to scale most efficiently for commercial use.

“Silicon spin qubits are gaining momentum [in the field]”said Adam Mills, a graduate student at Princeton University’s physics department and lead author of a recently published study.” It looks like a big year for silicon as a whole. “

Using a silicon device called a double quantum dot, Princeton researchers were able to capture two electrons and make them interact. The spin state of each electron can be used as a qubit, and the interaction between the electrons can confuse these qubits. This operation is critical to quantum computing, and a research team led by Jason Pett, a physics professor at Eugene Higgins at Princeton, was able to perform this confusing operation with an accuracy level in excess of 99.8 percent.

Qubit, simply put, is a quantum version of the computer bit, which is the smallest unit of data in a computer. Like its classic counterpart, the qubit is encoded with information that can have a value of one or zero. But unlike bits, qubits are capable of using the concepts of quantum mechanics so that it can perform tasks that classical bits cannot perform.

“In the qubit you can encode zeros and ones, but you can also have superpositions of those zeros and ones,” Mills said. This means that each qubit can be both zero and one. This concept, called superposition, is a fundamental quality of quantum mechanics and allows qubits to perform operations that seem strange and otherworldly. In practical terms, this allows quantum computers to gain a great advantage over conventional computers, for example, relying on multipliers of very large numbers or highlighting the most optimal solution to the problem.

The “spin” in spin qubits is the angular momentum of an electron. This is a quantum property that manifests itself in the form of a tiny magnetic dipole that can be used to encode information. A classic analogue is the compass needle, which has north and south poles and rotates according to the Earth’s magnetic field. The quantum-mechanical spin of an electron can be consistent with a magnetic field created in a laboratory (spinning), or be oriented antiparallel to the field (spin down), or located in a quantum superposition of spin up and spin down. Spin is a property of the electron used in silicon-based quantum devices; conventional computers, by contrast, work by manipulating the negative charge of an electron.

Mills argued that in general silicon spin qubits have advantages over other types of qubits. “The idea is that each system will have to scale to many qubits,” he said. “And right now other qubit systems have real physical limitations on scalability. Size can be a real problem for these systems. There’s just so much space where you can squeeze these things.”

For comparison, silicon spin qubits are made of single electrons and are extremely small.

“Our devices are about 100 nanometers in diameter, while a conventional superconducting qubit is more like 300 microns in diameter, so if you want to do a lot on a chip, it will be difficult to use a superconducting approach,” Petta said.

Another advantage of silicon spin-qubits, Pete added, is that conventional electronics today are based on silicon technology. “We believe that if you really want to make a million or ten million qubits that will be needed for something practical, it will only happen in a solid-state system that can be scaled using the standard semiconductor industry. “

However, the control of spin qubits, like other types of qubits, with high accuracy has been a challenge for researchers.

“One of the bottlenecks for spin-qubit technology is that the loyalty of double-qubit gates has not been so high until recently,” Petta said. “In most experiments, it was well below 90 percent.”

But this was a problem that Petta, Mills and the research team believed could be achieved.

To conduct the experiment, the researchers first had to capture one electron – a difficult task.

“We capture one electron, a very small particle, and we need to bring it into a certain area of ​​space and then make it dance,” Petta said.

To do this, Mills, Petta and their colleagues needed to build a “cage”. It took the form of a semiconductor-thin plate made mostly of silicon. At the top of this team blew up small electrodes that create the electrostatic potential used to drive the electron. The two of these cells combined, separated by a barrier or gate, formed a double quantum dot.

“We have two backs sitting on adjacent sites side by side,” Petta said. “By adjusting the voltage at this gate, we can momentarily shift the electrons together and cause them to interact. It’s called a double-barreled gate. “

The interaction causes each spin qubit to evolve according to the state of the neighboring spin qubits, leading to entanglement in quantum systems. The researchers were able to carry out this two-qubit interaction with an accuracy of more than 99 percent. To date, this is the highest accuracy for double-qubit gates that has so far been achieved in spin-qubits.

Petta said the results of this experiment put this technology – silicon qubits spin – on an equal footing with the best results achieved by other major competing technologies. “This technology is growing rapidly,” he said, “and I think it’s only a matter of time before it overtakes superconducting systems.”

“Another important aspect of this article,” Peta added, “is that it’s not just a demonstration of a high-precision double-quad gate, but this device does it all. It’s the first demonstration of a spin-quad semiconductor system where we have integrated system-wide performance.” – state preparation, reading, control with one qubit, control with two qubits – all with performance indicators exceeding the threshold required for a larger system.

In addition to Mills and Patty, the work also included the efforts of Princeton graduate students Charles Ginn and Mayer Feldman, as well as Associate Professor of Electrical Engineering at the University of Pennsylvania Anthony Sigilita. Also contributing to the article and research were Michael Gulans of Princeton University School of Physics and the Center for Quantum Information and Computer Science at NIST / University of Maryland and Eric Nielsen of Sandia National Laboratory, Albuquerque, New Mexico.

The triangular tangled state was implemented in a fully controlled array of spin qubits in silicon

Additional information:
Adam R. Mills and others, a dual-quasi-silicon quantum processor with an accuracy of more than 99% Advances in science (2022). DOI: 10.1126 / sciadv.abn5130

Provided by Princeton University

Citation: In the race to create hardware for quantum computing silicon begins to shine (2022, April 6), obtained April 7, 2022 from

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