Scientists from the University of Virginia School of Engineering and Applied Science (UVA) are pioneering the use of optical multiplexing to develop a scalable quantum computing platform for real-world applications.
Both scientists and investors are interested in the lucrative opportunities offered by quantum computing, such as its potential applications for complex problem-solving. The quantum computing market is, therefore, set to reach $65bn by 2030.
Quantum computing and drug discovery
One of the most promising future applications for quantum computing is its potential for drug discovery. In order to fully comprehend drug interactions, a pharmaceutical company may wish to simulate the interaction between two molecules.
Currently, the difficulty posed by this is that every molecule is formed of hundreds of atoms and researchers would need to model every way in which the atoms could array themselves when their respective molecules are introduced. The number of possible configurations is staggering — more than the number of atoms in the Universe. Therefore, only a quantum computer can represent, let alone solve, such an extensive, dynamic data problem.
The ability to apply quantum computing to such societal uses is, unfortunately, decades away, but scientists in universities and private industry across the globe are working on different dimensions of the technology.
Photonic chip with quantum applications
A group of researchers led by Xu Yi, who is an assistant professor of electrical and computer engineering at the University of Virginia School of Engineering and Applied Science, has found a niche in the physics and applications of photonic devices, which distinguish and shape light for a variety of uses such as communications and computing. The team has developed a scalable quantum computing platform, which significantly decreases the quantity of devices necessary to achieve quantum speed on a photonic chip the size of a penny.
This research has been supported by a grant from the National Science Foundation’s Engineering Quantum Integrated Platforms for Quantum Communication, and the group’s findings have recently been published in Nature Communications.
Olivier Pfister, professor of quantum optics and quantum information at UVA, and Hansuek Lee, assistant professor at the Korean Advanced Institute of Science and Technology, contributed to the success of the research.
Quantum computers offer a completely novel method of information processing; they process information in parallel, meaning they don’t have to wait for one sequence of information to be processed before they can compute more. Their unit of information is called a qubit, a hybrid that can be one and zero at the same time. A quantum mode, or qumode, spans the full spectrum of variables between one and zero.
Scientists are working on various methods to effectively generate the immense amount of qumodes required to attain quantum speeds. Yi’s photonics-based method is appealing as a field of light is also full spectrum; each light wave in the spectrum has the capability to become a quantum unit. Yi hypothesised that by entangling fields of light, the light would reach a quantum state.
The UVA researchers are pioneering the utilisation of optical multiplexing to develop a scalable quantum computing platform. In 2014, Pfister’s group were successful in generating over 3,000 quantum modes in a bulk optical system. However, employing this number of quantum modes necessitates a large footprint to contain the thousands of mirrors, lenses and other components that would be required to run an algorithm and perform other operations.
“The future of the field is integrated quantum optics,” Pfister explained. “Only by transferring quantum optics experiments from protected optics labs to field-compatible photonic chips will bona fide quantum technology be able to see the light of day. We are extremely fortunate to have been able to attract to UVA a world expert in quantum photonics such as Xu Yi, and I’m very excited by the perspectives these new results open to us.”
The research team led by Yi have been successful in developing a quantum source in an optical microresonator, a ring-shaped, millimetre-sized structure that covers the photons and produces a microcomb, a device that effectively transforms photons from single to multiple wavelengths. Light circulates around the ring to build up optical power, and this power build-up improves the possibilities for photons to interact, which generates quantum entanglement between fields of light in the microcomb.
With the use of multiplexing, the researchers were able to authenticate the generation of 40 qumodes from one microresonator on a chip, demonstrating that multiplexing of quantum modes can work in integrated photonic platforms.
“We estimate that when we optimise the system, we can generate thousands of qumodes from a single device,” Yi commented.
Yi’s multiplexing method commences a route towards quantum computing applications in real-world conditions, where inaccuracies are unavoidable. The quantity of qubits necessary to offset the potential for inaccuracies could surpass one million, with an equivalent increase in the number of devices. Multiplexing decreases the quantity of devices required by two or three orders of magnitude.
This novel photonics-based system presents two further benefits in the pursuit of real-world quantum computing. Quantum computing platforms that use superconducting electronic circuits need cooling to cryogenic temperatures. As the photon has no mass, quantum computers with photonic integrated chips are able to run or sleep at room temperature. Furthermore, Lee fabricated the microresonator on a silicon chip by applying standard lithography methods. This is significant because it indicates that the resonator or quantum source could be mass-produced.
“We are proud to push the frontiers of engineering in quantum computing and accelerate the transition from bulk optics to integrated photonics,” Yi concluded. “We will continue to explore ways to integrate devices and circuits in a photonics-based quantum computing platform and optimise its performance.”