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Finding Space for Semiconductor Quantum Computers

 


A false-colored scanning electron micrograph of a qubit structure, featuring a “wiggle well” developed by UWMadison researchers to improve the accuracy of quantum computers. The imaged area is approximately 1,500 nanometers wide. For comparison, a human hair is between 50,000 and 100,000 nanometers wide.University of Wisconsin-Madison

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.

Mark Friesen

“In traditional computers, all sides of a transistor are very uniform,” says Mark Friesen, UWMadison Distinguished Scientist. “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 at the University of Wisconsin-Madison, the University of New South Wales, and Delft University of Technology fine-tuned the physical structure of qubits known as silicon quantum dots. We have shown that sufficient valley splitting occurs to reduce computational error. The discovery flips 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 joint

Bob Joynt, Professor of Physics at UWMadison, 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 Mark Eriksson, professor of physics at UWMadison.

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 is clear that small changes in concentration were not the only factor affecting valley splitting, individual atoms were also important.

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, germanium in the wells is a really good idea. Sprinkling the germanium completely randomly without concentration oscillations would work pretty well. Sprinkling concentration oscillations would do better.” “

Both qubit structures have been filed for patent protection by WARF, and the UWMadison 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 UWMadison, 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 were funded by the Army Research Service, Directorate of the United States Army Combat Capability Development Command Army Research Laboratory (W911NF-17-1-0274).

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