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Qubit by Qubit: Optimizing Silicon For Quantum Computing

20 November 2023 at 10:24
silicon qubits

Insider Brief

  • Silicon qubits have long coherence times and are compatible with advanced semiconductor manufacturing techniques.
  • These qubits also face challenges, such as charge noise and valley splitting.
  • Researchers at the University of Rochester, University at Buffalo, SUNY Stony Brook, NY Creates, University of California, Los Angeles and Lawrence Livermore National Laboratory are using grant funds to find ways to overcome silicon qubit challenges.
  • Image: University of Rochester physicist John Nichol is exploring ways to overcome some shortcomings of otherwise promising silicon spin qubits. (Mark Garlick / Getty Images Science Photo Library)

PRESS RELEASE — Quantum computers harness quantum mechanics to perform computations and solve problems beyond the capabilities of classical computers. While a regular computer consists of billions of transistors, called bits, quantum computers are based on quantum bits, also known as qubits.

In the quest to build powerful quantum computers, one type of qubit has shown exceptional promise: silicon spin qubits. These qubits not only have long coherence times but are also compatible with advanced semiconductor manufacturing techniques. Despite this promise, the material used in silicon spin qubits creates recurring challenges for researchers. These include:

  • Charge noise, or erratic fluctuations in the electrostatic environment surrounding the qubits, making them unstable
  • Valley splitting, which creates quantum-dot energy levels that can get too close and cause unwanted complications
  • Spatial variations in electron g-factor, which can lead to difficulty controlling qubits

To overcome these challenges, the US Air Force Office of Scientific Research (AFOSR) has awarded more than $6.7 million to a multidisciplinary team of experts in materials characterization and modeling, silicon fabrication, and quantum experiments. Led by researchers at the University of Rochester, the team includes collaborators at the University at Buffalo; SUNY Stony Brook; NY Creates; University of California, Los Angeles; and Lawrence Livermore National Laboratory.

“We are taking a materials-first approach to discovering the underlying causes of the challenges with silicon spin qubits,” says John Nichol, an associate professor of physics at Rochester and the primary investigator on the project.

AFOSR funds high-risk basic research that has the potential to profoundly impact the nation’s technological progress, in areas including the development of stable and powerful quantum computers. The office’s funding of a partnership between academia, a national laboratory, and an innovation hub is key to making advances in quantum computing, according to Nichol.

“This team has the required expertise to investigate correlations and causation in silicon spin qubits and ultimately accelerate progress through materials development in this platform,” he says.

Study Observes Strong Noise Correlations Between Silicon Qubits

13 November 2023 at 09:50

Insider Brief

  • A team from Tokyo Institute of Technology and RIKEN has published a study in Nature Physics revealing significant noise correlations between pairs of silicon spin qubits, which could impact the development of scalable quantum processors.
  • The research focused on measuring and quantifying the correlations of noise that may impair the performance of quantum processors by increasing error rates, a crucial aspect considering the millions of qubits required for a functional quantum computer.
  • Utilizing a novel Bayesian estimation technique, the researchers confirmed strong noise correlations that persist over distance, underscoring the need for new methods to manage such noise in dense qubit arrays for future semiconductor-based quantum computing systems.

UNIVERSITY RESEARCH NEWS — TOKYO/November 3, 2023 — A research team at the Tokyo Institute of Technology and RIKEN recently set out to reliably quantify the correlations between the noise produced by pairs of semiconductor-based qubits, which are very appealing for the development of scalable quantum processors. Their paper, published in Nature Physics, unveiled strong interqubit noise correlations between a pair of neighboring silicon spin qubits.

“A useful quantum computer would practically require millions of densely packed, well-controlled qubits with errors not only small but also sufficiently uncorrelated,” Jun Yoneda, one of the researchers who carried out the study, told “We set out to address the potentially serious issue of error correlation in silicon qubits, as they have become a compelling platform for large quantum computations otherwise.”

Fabricating highly performing quantum processors based on many closely positioned silicon qubits has so far proved challenging. These systems would exhibit noise that is correlated between different qubits. This reduces the devices’ fault tolerance, increasing their error rate and thus impairing their performance.

As part of their recent study, Yoneda and his colleagues set out to explore the extent of these interqubit noise correlations, in the hope of informing the future development of semiconductor-based quantum computing systems. To do this, they analyzed and tried to quantify the correlation between the noise seen by two silicon-based qubits that were placed 100 nm away from each other.

“Errors in silicon spin qubits are dominated by fluctuations of the qubit energy, that is, the energy difference between the spin-up and -down states,” Yoneda explained. “We measured the simultaneous time evolution of qubit energies and assessed the ‘degree of similarity’ between the two time traces via a quantity called the cross power spectral density.”

The researchers subsequently used a Bayesian estimation technique they developed as part of their previous research work, which is designed to give the probability distributions of cross power spectral densities. This technique allowed them to validate the statistical relevance of the correlations they observed, confirming that the two qubits were subject to strongly correlated noise.

“We observed strong noise correlations between silicon qubits — with a correlation strength as large as 0.7 at some frequencies,” Yoneda said. “Such correlations due to electrical noise are unlikely to decay quickly with distance, so we are now keenly aware that error correlation needs to be taken seriously in dense qubit arrays in silicon. We also showed that noise correlation analysis provides novel insights into the source of qubit noise.”

The statistical methods employed by this team of researchers is unique and powerful, as contrarily to conventional approaches, it requires no prior knowledge of the auto-spectrum (e.g., 1/f) to assess and quantify qubit noise. Overall, the findings of this recent work confirm the challenges associated with noise correlation between closely situated silicon qubits, highlighting the need to devise new approaches to suppress or mitigate noise in semiconductor-based quantum computers.

“Our future research will include investigating how far the correlation will extend in a qubit array, leveraging the methods of including cross correlations in noise analysis that we pioneered here experimentally,” Yoneda added. “This is a critical question concerning fault-tolerance, as well as understanding of the noise source.”

Written by Ingrid Fadelli ,

Featured image: Characterization of qubit error correlation in a silicon qubit array. Credit: Yoneda et al