In brief

As we approach a quantum revolution, A*STAR scientists are harnessing the technology for super sensors, advanced algorithms and more.

© A*STAR Research

Delving into a spectrum of quantum capabilities

24 Sep 2021

From advanced materials to atomic super sensors, A*STAR scientists are harnessing the power of quantum to the fullest, ushering in the next generation of trailblazing technologies.

In late 2019, Google lit the quantum community abuzz. For the first time, they achieved quantum research’s elusive milestone: quantum supremacy. Up against the best of classical computing, the tech giant’s Sycamore quantum computer finally leapfrogged the competition—carrying out a calculation that would have taken supercomputers 10,000 years to solve.

In another case of doing the impossible, researchers using Sycamore demonstrated a time crystal in early August this year. Sounding like something straight out of a Marvel movie, time crystals are veritable paradoxes—constantly changing yet stable, undergoing repeated cycles of change without burning energy. These milestones not only belie the excitement around quantum but also showcase the bizarre, law-defying ways of quantum phenomena.

High-speed computing is just one area where quantum systems are expected to outperform current systems. After all, units of quantum information called qubits can exist as multiple states simultaneously until they are measured, unlike traditional computer bits that only exist as zero or one. While these properties sound futuristic, the particles exhibiting these quantum effects are already all around us.

For example, charges that power electronic devices can exist in both spin up or spin down states when placed in a magnetic field. Meanwhile, photons or light particles are frequently entangled in optical networks and imaging applications. These linked units mirror each other’s properties, allowing measurements from a distance without ever directly observing the pair’s opposite component. As intriguing as these phenomena may be, bringing quantum from abstract thoughts and experimental observations to mainstream relevance poses another mountain to climb. The key to next-generation quantum technologies lies in inducing these quantum effects in a well-controlled and scalable way.

In the race to exploit quantum properties for practical applications, A*STAR’s researchers are part of a global community driving the quantum revolution across domains like telecommunications and bioimaging.

Cracking the quantum code

While quantum computing promises supremacy over high-performance classical models, this advantage remains limited to the research and development stage. As full-scale quantum computers have yet to be realized, many opt for hybrid models combining quantum with classical algorithms. This allows developers to run simulations and explore the frontiers of quantum, executing the algorithms on noisy intermediate-scale quantum (NISQ) devices—so-called because they are still error-prone.

However, hybrid algorithms often demand a high number of measurements, driving up costs and slowing down performance. Meanwhile, current fixes to reduce these costs have yet to make a dent in solving larger problems that typically require adding more qubits as well as better fault tolerance. Given the limits of NISQ in correcting errors, these algorithms are often rendered unusable for commercially relevant applications.

To realize the quantum advantage, researchers from A*STAR’s Institute of High Performance Computing (IHPC) like Dax Koh are devising novel techniques to scale up quantum algorithms and solve practical problems.

Supported by A*STAR’s National Science Scholarship, Koh previously worked on an algorithm called the variational quantum eigensolver, alongside collaborators at Zapata Computing1. Like many other quantum models, this algorithm involves sampling and estimation, running through numerous possible outputs to find the best answer for a given problem.

The larger the problem, however, the longer the runtime needed to determine the solution—time that quantum systems may not be able to provide. Due to their fragility, a system can only maintain its quantum states for so long before collapsing, a phenomenon called quantum decoherence.

To speed up the algorithm, Koh's team developed a framework called the engineered likelihood functions (ELF) that carries out statistical calculations known as the Bayesian inference. During the inference phase, several possibilities are checked to determine the relationship between variables or estimate the value of a certain parameter. By maximizing the information gained per run-through of this algorithm, ELF allowed the model to find the solution faster while reducing measurement costs.

“The ELF framework takes into account the depth and coherence of the quantum device implementing the quantum algorithm,” Koh explained. Besides crucially running on NISQ devices, ELF is also adaptable, adjusting the algorithms’ parameters when transitioning to more fault-tolerant machinery.

At IHPC, Koh continues to refine quantum algorithms to make them friendlier for NISQ devices, establishing in-depth insights into the power and limitations of quantum computers. For example, he and his team have studied how various factors like qubit counts and noise affect the computational power of machine learning (ML) models, a subfield of artificial intelligence that emulates the human brain and makes predictions about new datasets based on training inputs.

With a keen understanding of quantum’s limitations, scientists can devise innovative ways to overcome these barriers to create quantum-enhanced ML, further advancing the field.

Case in point: a quantum advantage could supercharge disciplines like materials design. As Koh optimizes quantum algorithms, his colleague Jun Ye—a Senior Scientist at IHPC—sees quantum-enhanced ML as a gateway to enhancing polymer innovation.

Given the potential to perform massive parallel sampling, quantum computing can accelerate materials design—predicting polymer properties and identifying tweaks to the structure and interactions of their subparts. Since electronic devices are made of numerous interacting particles, characterizing the quantum dynamics of these many-body systems is key to achieving desired properties like charge transport.

This vision draws from Ye’s experience in designing semiconductors with enhanced electrical transport, for instance2. As an electron is itself a quantum object, quantum mechanics govern properties such as the movement of charge carriers from one molecule to another and coupling interactions between neighboring molecules.

While quantum dynamics has clear implications for manufacturing electronic devices, Ye explained that these fundamental laws are similarly applicable to quantum computing itself.

“Quantum computer operations and quantum circuit executions can be viewed as the time-evolution of a many-body quantum system composed of coupled qubits,” he said. “One key area of research is to understand the role of various noises in affecting the dynamics of a quantum system.”

By determining how to mitigate the effects of noise, Ye seeks to improve error correction in these machines, overcoming a critical stumbling block for scalable quantum computing.

Materializing breakthroughs in quantum devices

In the computing arena, the significance of scalability is nothing new. From the first computers using vacuum tubes, classical technologies have advanced leaps and bounds by packing more power into tinier circuits on silicon chips. Behind these historic changes are material breakthroughs, spurring widespread adoption for real-world applications.

To catalyze a similar revolution in quantum devices, highly stable platforms are needed to support an increasing number of qubits while maintaining low error rates. After all, the uniquely high sensitivity of qubits to external changes makes them prone to errors As these particles are susceptible to environmental conditions like heat, quantum computers generally need to be maintained and operated at sub-zero temperatures.

Facing this dilemma, the Quantum Materials and Devices group at A*STAR’s Institute of Materials Research and Engineering (IMRE) is developing high-quality materials to build a scalable architecture for quantum devices.

Transition metal chalcogenides (TMDC), for example, are attracting interest as ultrathin semiconductors to support spin-based qubits. Carrying two different metal atoms in their crystal structure, these 2D TMDCs have unique inversion asymmetry and time-reversal symmetry properties—resulting in the coupling of the spin and valley components of electrons3.

“Spin-valley coupling provides a more stable type of quantum state which requires two keys to unlock, akin to two-factor authentication, via the ‘spin-key’ and ‘valley-key,’” explained Johnson Goh, Principal Scientist and Head of the Quantum Technologies for Engineering Department at IMRE. This stability could make qubits more robust and potentially operable as quantum processor chips.

While faster qubit operation has usually come at the cost of faster decoherence, IMRE Scientist Aaron Lau explained that the unique spin-valley coupling in 2D semiconductors can protect against decoherence. By enabling both fast operations and long coherence lifetimes, such material could already meet some of the major needs for scalable quantum devices.

Still, the viability of these semiconductors relies on their ability to withstand the cryogenic temperatures needed to preserve the fragile quantum states.

“Even if we can create the most exceptional quantum materials, without contacts that can work at extremely low temperatures, there will be no way to electrically probe and study their exotic properties,” Lau said.

Typically, contact engineering approaches like physical vapor deposition tend to damage 2D materials. According to Lau, the process is akin to throwing darts. Traveling from a source, metallic atoms of the contacts land on conventional bulk semiconductors where they may cause some surface damage with minimal impact on device performance. But in ultrathin atomically thick 2D TMDCs, such surface defects can be catastrophic. It’s the difference between throwing darts at a concrete wall (bulk semiconductors) vs tissue paper (2D TMDCs).

Goh, Lau and collaborators found that using indium alloy could limit the damage sustained by tungsten disulfide (WS2) TMDCs at cryogenic temperatures4. By carefully depositing indium alloy, the team reduced contact resistance in these materials, enabling more efficient charge transport.

But scientists also recognize that completely defect-free materials are practically impossible to manufacture over larger scales. “Instead of seeing this as a problem, we investigated whether different densities of defects called S-vacancies could provide an interesting range of electrical properties,” said Goh, adding that S-vacancies are widely present defects in sulfur-based TMDCs.

S-vacancies, they found, hindered the mobility of negative charges, becoming more severe as defects accumulated5. However, S-vacancies did not significantly limit transport in hole-based TMDCs, injecting positive charges across the material. By showing that low-resistance contacts may be more promising for hole-based TMDCs, the study revealed valuable insights for developing electronic devices using 2D semiconductors.

Meanwhile, Goh, Lau and colleagues recently delved into a technique called chemical vapor deposition (CVD) that allows the scalable large-area synthesis of TMDCs. In an engineering feat, theirs was the first CVD device to show quantum confinement, where electrostatic fields spatially confine and alter the carriers in the material.

“Understanding low-temperature transport mechanisms is key to designing increasingly complex 2D semiconductor-based quantum devices,” Lau said.

From basic research into TMDC properties to devising novel manufacturing methods, these efforts all contribute to a grand vision of mastering materials development for producing quantum devices at scale.

Super-sensors on compact platforms

Besides manufacturing materials, translating fundamental knowledge into application-oriented research is a common vision across A*STAR, including the fields of optics and sensing. For instance, light particles or photons can travel far and fast—making them ideal information carriers. By using photons as ‘flying qubits,’ as Jason Png, Director of the Electronics and Photonics Department at IHPC calls them, information transfer could be accelerated even further.

According to Png’s IHPC colleague Lin Wu, photons can act as qubits even at room temperature, potentially paving the way for large-scale quantum computers. In particular, Wu’s team studies cavity quantum electrodynamics, or the interaction between light confined in a reflective cavity and atoms or other particles under conditions where the quantum nature of photons is significant.

Through these cavities, the atoms or other particles can be manipulated in a scalable manner. One area where their work has since been applied is quantum sensing. Together with Png, Wu and her colleagues are exploring energized particles called plasmons in detecting antigens as markers of infection—giving biosensing a quantum twist6,7. By confining electromagnetic fields into tiny spatial regions, plasmonic nanocavities enable strong light-matter interactions even at the single-molecule level, measuring weak analyte signals that otherwise might have been mistaken as background noise.

“Conventional plasmonic sensors detect biological molecules in the weak coupling regime, with the detected molecules appearing as a shift in the spectral peak,” said Wu. “In our quantum plasmonic immunoassay, detection appears as a split in the spectral peak due to the strong coupling between the quantum-emitter label attached to the target molecule and the plasmonic cavity. This makes our sensor much more sensitive.”

“The plasmonic systems also bring the strong light-matter coupling from cryogenic temperature to room temperature, which largely relaxes the experimental requirements for practical implementation and miniaturization of the sensors,” Png explained.

In a collaborative effort between IHPC’s Electronics and Photonics department and IMRE’s Quantum Technologies for Engineering group, Png and IMRE Principal Scientist Leonid Krivitsky led the development of the first-ever integrated avalanche photodetector (APD) for the visible light range8, making it more energy- and cost-efficient than detectors operating at infrared wavelengths.

The team’s device uses a doped silicon waveguide coupled to a silicon nitride waveguide for highly efficient detection, restricting the area for light transmission while packing the system on a compact chip. Png shared that they are now exploring design variations to stabilize the device, reducing noise and further optimizing detection performance.

Already considered a mature technology, APDs operate at near-room temperature and on-chip designs are a promising frontier for scalability, Krivitsky noted. While still in the research stages, these devices could potentially be integrated with various sensing systems, including light detection and ranging (LIDAR) for remote, high-resolution environmental mapping.

While APDs detect light, quantum sensors can also measure a host of other properties such as magnetic fields, poised to enhance applications like magnetic resonance imaging for brain scans.

IMRE Scientist Junyi Lee is leading the development of alkali atomic magnetometers, exploiting quantum effects to forgo the use of large and expensive magnets. “By directly measuring the energy shifts of alkali atoms with a laser, they can measure magnetic fields to better than a part per billion,” Lee highlighted.

This means that not only would measuring instruments become more compact, but the environmental footprint of quantum-powered innovations would also shrink significantly. As alkali magnetometers function even without cryogenic cooling, they require much less power to operate than other quantum sensors, providing significant cost savings.

Besides biomedical imaging, these sensors could pave the way for precise chemical analysis in food safety testing and geomagnetic surveys to scope out the planet’s underground structure and tectonic activity.

Igniting a quantum revolution

Today, scientists are gearing up for a new wave of technological transformations ushered by quantum. For the field to prosper, scalability is the key to transforming basic research into real-world applications. To reach this pivotal point, researchers around the world are pushing to establish quantum’s computational supremacy as well as uncovering the best ways to control quantum properties for electronics and metrology.

A*STAR researchers are among those pursuing such endeavors, whether by integrating quantum phenomena into existing systems or building new devices to support quantum effects. These efforts are just the tip of the iceberg as the agency strives to not only create a smarter nation with tech-enabled applications, creating impact in areas like healthcare and sustainability.

While no quantum computer is yet ready to deliver useful work, quantum tech’s range of potential benefits is growing longer each day. As quantum capabilities are built up across sectors, quantum can advance from nascency to the technology of the moment.

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1. Wang, G., Koh, D.E., Johnson, P.D., and Cao, Y. Minimizing estimation runtime on noisy quantum computers. PRX Quantum 2, 010346 (2021) | article
2. Jiang, H., Hu, P., Ye, J., Chaturvedi, K., Zhang, K.K., et al. From linear to angular isomers: Achieving tunable charge transport in single-crystal indolocarbazoles through delicate synergetic CH/NH⋅⋅⋅π interactions. Angewandte Chemie International Edition 58, 8875 (2018) | article
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8. Yanikgonul, S., Leong, V., Ong, J.R., Hu, T., Siew, S.H., et al. Integrated avalanche photodetectors for visible light. Nature Communications 12, 1834 (2021) | article

About the Researchers

Dax Koh is a recipient of the National Science Scholarship and a scientist in the Computing and Intelligence department at A*STAR’s Institute of High Performance Computing (IHPC). He works on quantum algorithms, computational complexity theory, and classical simulation of quantum computation. Prior to IHPC, he was a Z-fellowship postdoctoral researcher at Zapata Computing, Inc. He received a PhD degree in Mathematics from the Massachusetts Institute of Technology under the supervision of Peter Shor.
Jun Ye is a senior research scientist at the Institute of High Performance Computing, A*STAR. He obtained his Bachelor’s degree (2007) from the Central South University, China, and PhD (2012) from Nanyang Technological University, Singapore. His research interests cover a wide range of topics related to organic materials, including quantum theory and quantum dynamics simulation of charge and excited-state energy transport, and machine learning methods for the construction of structure-properties relationships in organic molecular crystals. Besides materials research, he extends his expertise in quantum dynamics to the development of quantum computing software and algorithms for quantum chemistry and general Hamiltonian simulations.
Johnson Goh is Head of Department for Quantum Technologies for Engineering, and Principal Investigator at A*STAR’s Institute of Materials Research and Engineering (IMRE). He obtained his PhD in 2007 from the Centre of Excellence for Quantum Computer Technology in the University of New South Wales, Sydney. Joining A*STAR in 2006, he contributed to materials science and engineering research, ranging from atomic-scale 3D printing with silicon atoms, to highly conductive 3D printable thermoplastics, to 2D semiconductors and to quantum devices. He currently melds his multidisciplinary research expertise in quantum information technologies, nanoelectronics, machine learning and additive manufacturing toward disruptive quantum technologies.
Jason Png is Director of the Electronics and Photonics Department at the Institute of High Performance Computing (IHPC), A*STAR. He received his PhD degree from the University of Surrey, UK (2004), and MBA from INSEAD, France (2014) and Tsinghua University, China (2014). He joined IHPC in 2005 with research interests including quantum, high-speed photonics and plasmonics, and electromagnetics. He has received numerous awards, including the prestigious Royal Academy of Engineering Prize, Vebleo Fellow, Vebleo Scientist Award, IET Innovation Award - Software Design, Skolkovo Prize at INSEAD Venture Competition, and Spring TECS Proof-of-Value grant.
Aaron Lau is an experimental quantum scientist who engineers and studies next-generation materials and devices to understand the physics of low-dimensional systems. He graduated from the National University of Singapore in 2012 with a Bachelor of Science (Physics), first class honors, before receiving the A*STAR Graduate Scholarship to pursue his PhD at the University of Oxford. There, he frequented the Department of Materials and the Royal Oak Pub where he worked on quantum transport through single-molecule electronics. He returned to A*STAR’s Institute of Materials Research and Engineering (IMRE) in 2017, where he now works on atomically thin materials for quantum applications.
Leonid Krivitsky is the head of the quantum technologies for engineering department at A*STAR’s Institute of Materials Research and Engineering (IMRE). Krivitsky obtained his PhD in Physics from Lomonosov Moscow State University and held postdoctoral positions at the National Metrology Institute, Max Planck Institute for the Science of Light, and the Technical University of Denmark. His scientific interests include quantum metrology and sensing and quantum information processing.
Lin Wu received a degree in electrical and electronic engineering (first class honors) in 2005, and a PhD degree in microelectronics in 2009, from Nanyang Technological University, Singapore. In 2009, she joined A*STAR’s Institute of High Performance Computing (IHPC) as a computational scientist. Her research interests include nanoplasmonics and nanophotonics and their emerging applications in quantum technology and sensing. Wu has authored or co-authored two book chapters and published more than 50 refereed journal papers. She is also a co-author on three US patents.

This article was made for A*STAR Research by Wildtype Media Group