Physicists and engineers have found a way to identify and address imperfections in materials for one of the most promising technologies in commercial quantum computing. The University of Queensland team was able to develop treatments and optimise fabrication protocols in common techniques for building superconducting circuits on silicon chips. Dr Peter Jacobson, who co-led the research, said the team had identified that imperfections introduced during fabrication reduced the effectiveness of the circuits. He noted that superconducting quantum circuits are attracting interest from industry giants, but the widespread application is hindered by ‘decoherence’, a phenomenon that causes information to be lost.
Decoherence is primarily due to interactions between the superconducting circuit and the silicon chip – a physics problem – and to material imperfections introduced during fabrication – an engineering problem. Thus, there is a need for input from physicists and engineers to find a solution. The team used a method called terahertz scanning near-field optical microscopy (THz SNOM) – an atomic force microscope combined with a THz light source and detector. This provided a combination of high spatial resolution – seeing down to the size of viruses – and local spectroscopic measurements.
Professor Aleksandar Rakić said the technique enabled probing at the nanoscale rather than the macroscale by focusing light onto a metallic tip. This provides new access for the team to understand where imperfections are located so we can reduce decoherence and help reduce losses in superconducting quantum devices. The team found that commonly used fabrication recipes unintentionally introduce imperfections into the silicon chips, which contribute to decoherence. And they also showed that surface treatments reduce these imperfections, which in turn reduces losses in the superconducting quantum circuits.
Associate Professor Arkady Fedorov said this allowed the team to determine where the process defects were introduced and optimise fabrication protocols to address them. Their method allows the same device to be probed multiple times, in contrast to other methods that often require the devices to be cut up before being probed. The team’s results provide a path towards improving superconducting devices for use in quantum computing applications. In future, THz SNOM could be used to define new ways to improve the operation of quantum devices and their integration into a viable quantum computer.
The Quantum Computing Software market size is projected to grow from US$0.11 billion in 2021 to US$0.43 billion in 2026, at a Compound Annual Growth Rate (CAGR) of 30.5% during the forecast period. The major factors driving the growth of the Quantum Computing Software market include the growing adoption of quantum computing software in the BFSI vertical, government support for the development and deployment of the technology, and the increasing number of strategic alliances for research and development.
Quantum computing technology was witnessing increasing global demand during the pre-COVID-19 period, as companies were making strategic partnerships and collaborations and undertaking patent registrations to enhance their position in the market. During the pre-COVID-19 era, the key factor driving the growth of the quantum computing market was the rising investments by governments of different countries in the development of quantum computing technology.
The growth of the quantum computing market is primarily driven by technological advancements in quantum computing technology. The demand for quantum computing systems and services post-COVID-19 is expected to increase owing to the rise in the adoption of quantum computing technology in drug discovery. However, the stability and error correction issues in quantum computing technology are expected to restrain the market growth.
Quantum computers provide powerful tools for studying complex systems such as human physiology and the impact of drugs on biological systems and living organisms. These computers are expected to be used in several applications in pharmaceutical research and development, especially during the early phases of drug discovery and development.