Virginia Tech researchers are on a mission to bring quantum computing closer to real-world application.
With a $5m grant from the U.S. Department of Energy, the team aims to overcome the current limitations of quantum computers and make them more practical for solving complex problems. This grant will fund their research over the next five years.
The promise of quantum computers
Quantum computers operate using the strange, counterintuitive properties of quantum physics, allowing them to perform certain computations exponentially faster than traditional computers.
Unlike classical computers that process data in bits (0s and 1s), quantum computers utilise qubits, which can exist in multiple states simultaneously.
This enables them to solve complex problems that would take classical computers an impractical amount of time to compute.
However, quantum computing technology is still in its early stages. While small-scale quantum processors can execute various tasks, they are not yet advanced enough to tackle significant real-world problems like drug design or energy optimisation.
The challenge: Diverse quantum machines and algorithms
One of the biggest obstacles in quantum computing today is the inefficiency of current algorithms. These algorithms are often designed for a universal quantum machine, which isn’t ideal because quantum computers come in different types and architectures.
Virginia Tech’s approach focuses on this diversity, recognising that different quantum computers –whether based on superconducting circuits, silicon nanostructures, or trapped atoms – may be better suited for specific problems.
Physics professor Ed Barnes, leading the research team, believes that matching the right algorithm to the right quantum machine is key to improving performance.
Tailoring algorithms
The research team, consisting of experts from Virginia Tech, North Carolina State University, and the University of California, Santa Barbara, is developing adaptive algorithms.
These algorithms will account for the unique hardware of various quantum computers, optimising them for specific tasks in fields like chemistry, machine learning, and materials physics. This tailored approach is expected to speed up problem-solving on quantum platforms significantly.
By refining these algorithms to fit different quantum systems, the team hopes to advance quantum computing towards practical, high-impact applications, bringing the next major breakthrough in computing closer.
With this interdisciplinary collaboration, Virginia Tech is at the forefront of making quantum computing useful in everyday problem-solving.
As the technology matures, it has the potential to revolutionise industries, solving problems that are currently out of reach for classical computers. The development of adaptable algorithms is a crucial step toward unlocking this future.
