Traditional computers rarely make mistakes, thanks in large part to the digital operation of semiconductor transistors. They are either on or off, corresponding to conventional bits 1 and 0.
A qubit, or qubit, on the other hand, can be equal to zero, one, or any mixture of two, and quantum computers can solve certain computations beyond the capabilities of conventional computers. One of the complications of qubits, however, is that they can occupy energy levels other than computational 1 and 0. If these additional levels are too close to 1 or 0, errors are likely to occur.
“In a classical computer, all aspects of a transistor are very uniform,” says Mark Friesen, UW-Madison Distinguished Scientist, author of both papers. “Silicon qubits are like transistors in many ways, and we’ve reached a stage where we can control the properties of qubits very well, with one exception.”
One of its properties, known as valley splitting, is a buffer between one computational zero energy level and an additional energy level, which helps reduce errors in quantum computing.
In two papers published in December in Nature Communications, researchers from the University of Wisconsin-Madison, the University of New South Wales, and TU-Delft found that by fine-tuning the physical structure of a qubit known as a silicon quantum dot. , calculation error. This discovery turns the conventional wisdom on its head by showing that imperfect silicon quantum dots can be beneficial.
To date, the most common method of making qubits has been to embed quantum dots in a layer of pure silicon, called a silicon well, and then sandwich that layer between two layers of silicon-germanium, creating a well-defined boundary between the layers. was to do In these new studies, a semiconductor qubit is similarly made, with a layer of silicon placed between her two layers of silicon-germanium. A new feature is the addition of germanium to the silicon layer itself.
Bob Joynt, professor of physics at the University of Washington, Madison, said: “And we decided, well, let’s play around with it a bit.”
The researchers screwed up the design by intentionally adding germanium to the silicon layer in a slightly different way. Like many successes in physics, their success began with theoretical calculations. Joynt asked what would happen if the concentration of germanium “wiggled” across the well like a regularly spaced wave with peaks and valleys. His Friesen group, who also contributed to a related TU-Delft paper, noted that small amounts of germanium always spilled into the well, even when researchers tried to prevent it. They asked what would happen if low levels of germanium were randomly sprinkled throughout the well.
“Theoretical calculations clearly show that it is better with germanium in it, and it is better wiggled than not wiggled,” says UW Madison physics professor Mark Erickson.
After confirming that the Wiggle well does not significantly alter the electronic properties of the quantum dots, Eriksson’s group measured the size of the energy buffer, or valley splitting, in these new structures. For quantum dots embedded in wiggle wells, theory predicted an increase of 20 microelectronvolts. However, the largest valley splitting measured in the laboratory was nearly 250 microelectron volts. Moreover, when the QD moved to a new position within the well, the valley splitting changed, and the atoms composing the wiggle were in different positions. It was not only the concentration increments but also the individual atoms that were important in influencing the valley splitting.
This fact turned out to be important. Atoms in the wiggle well were somewhat randomly distributed. Introducing this random distribution into numerical simulations accurately accounted for the observed valley segmentation variation. In a second paper, Friesen and his TU-Delft collaborators found that even randomly distributed germanium in the wells produced, on average, greater valley splitting than in the absence of germanium. Confirmed to bring.
“Contrary to many people’s concerns, it’s a really good idea to put germanium in the well,” Eriksson says. “If you scatter completely randomly, with no concentration oscillations, you’ll do pretty well. If you scatter concentrated oscillations, you’ll do well.”
Both qubit structures have been submitted for patent protection by WARF, and the UW-Madison team is actively working on designs that further enhance the valley splitting.
“If quantum computers are made out of silicon/silicon-germanium qubits, we may need germanium in the wells,” says Joynt. “But we don’t know yet. We’re just getting started.”
At UW-Madison, Thomas McJunkin, Benjamin Harpt, Yi Feng, Merritt Losert, JP Dodson, Michael Wolfe, Don Savage, Max Lagally, and Sue Coppersmith made additional contributions to this work. Both studies army research Office, Directorate General of the U.S. Army Combat Capability Development Command Army Research Institute (W911NF-17-1-0274).