Computing for the Next Generation
ORNL scientists provide the building blocks for quantum information science
Just the name of ORNL's Cyberspace Science and Information Intelligence Research (CSIIR) group conjures images of enigmatic, cutting-edge science. As it turns out, this impression is pretty accurate—at least for the computing research being done by quantum information scientist Phil Evans and his colleagues.
Researchers are recreating the capabilities of a half-million-dollar laser table on a silicon chip the size of a fingernail. The silicon wafer above will be cut into 20 to 25 individual chips. (Photo: Jason Richards)
Evans' efforts are concentrated on applying principles of quantum physics and optics to developing the building blocks needed to realize the goal of quantum information processing. He notes that, because QIP is so new, there are a variety of approaches to the problem. "Programs at other laboratories and universities work with trapped ions or groups of electrons traveling in superconducting loops," he says. "However, at ORNL our research is focused on doing QIP with photons."
The advantage of QIP over traditional data processing can be roughly illustrated by looking at the basic units of information used by the two approaches. "Classical" digital information is based on the binary digit, or "bit." A bit can have a value of 0 or 1. The basic unit of information in QIP is the quantum bit, or "qubit." Its value can be 0, 1 or a superimposition of the two, meaning both 0 and 1—as well as all the values in between. While the concept is a little hard to get one's head around, the ability of a qubit to simultaneously represent a theoretically unlimited number of values points to the potential of devices utilizing QIP to become orders of magnitude more powerful than today's technology.
The path forward
Evans sees the ongoing evolution of quantum information science as a four-step progression that he expects will lead to the development of quantum-enhanced devices and applications.
The first generation, he says, was focused on an information security technique called "quantum key distribution." Technology companies have already begun to apply quantum principles to the problem of encoding and decoding communications such as email. QKD is an attractive option because it not only enables users to swap secret "keys" used to encrypt and decrypt messages, but it also tells them when someone is eavesdropping on the exchange.
Evans notes that the security of these exchanges is guaranteed by quantum physics—to a point. A well-publicized weak point in existing QKD implementations is the single-photon detector used in every QKD system. QKD systems manufacturers are constantly looking for ways to reduce the detectors' tolerance for noise—errors introduced by irregularities in the system's physical or network environment. Error tolerance is necessary to ensure that exchanges can take place under less-than-ideal conditions. However, tolerance for mistakes in transmission also provides an opening that can be exploited by hackers, so, while the physics behind QKD is unassailable, the technology used to implement it needs to be airtight to ensure its security.
The second generation of quantum apps includes a range of projects such as those spearheaded by Evans' colleague, quantum scientist Raphael Pooser. Pooser's research into quantum noise reduction and quantum sensors reboots traditional optical technologies by applying quantum principles to make them smaller, more sensitive and more precise. Evans cites Pooser's work with atomic force microscopes as an example of this quantum refinement. Traditionally, AFMs have gathered data by shining a laser onto a cantilever and measuring its movement as it is pulled across the surface of a material. "There is always a certain amount of quantum noise, or uncertainty, associated with laser-based measurements," Evans says. "However, replacing the laser beam with a beam of light that has been engineered to have less quantum noise improves the resolution and sensitivity of the microscope."
Quantum chips and Q-STILLs
One of the roadblocks to faster development of QIP technologies is the cost of the highly specialized optical equipment required to conduct quantum information research. "We tell our sponsors about the gains that can be made using this technology," Evans says, "but we can't expect them to pay for the half million dollars' worth of equipment it takes to support each laser table." It's also not practical to develop a quantum sensor package that requires a table-sized collection of equipment with substantial power if its ultimate application is going to be on a submarine or aircraft or anywhere else space and power may be limited.
Fortunately, Evans has an alternative in mind. He and his colleagues are working on a process that places the capabilities of a half-million-dollar laser table on a silicon chip the size of a fingernail. A downsizing challenge of this magnitude might seem a bit daunting, but Evans reasons that this is no different than the trend toward smaller, more powerful microprocessors that drove the personal computing revolution. "I guess you could say that we're trying to do the same thing with quantum technologies," he says. "One of the big challenges is to make the current technology scalable."
Evans leads the Quantum Lightwave Circuit project, which is supported by the Laboratory Directed Research and Development fund. The fund supports cutting-edge research across ORNL. The QLC project aims to develop a scalable framework for designing, simulating and fabricating any photon-based quantum device to perform any task. One of these circuits is called the Q-STILL (quantum states integrated with lightwave logic). Q-STILL also means "quantum still," a tongue-in-cheek reference to East Tennessee's moonshining heritage. "It's the same principle," he says. "We feed in the raw material—in this case "unentangled" photons—and interesting stuff—"entangled" photons, come out the other end."
To make a silicon chip do the work of a table full of equipment, Evans uses a process called electron-beam lithography, as well as other tools located at the laboratory's Center for Nanophase Materials Sciences, to create nano-scale waveguides—raceways for photons to follow—on a silicon wafer. The wafer is then cut into individual chips. Once a chip has been processed, researchers shine a laser through a specially designed crystal to produce pairs of entangled photons. When the photon pairs are injected into the chip, they can be split, rotated, combined, or manipulated in various other ways. "Pretty much any effect we can create on a laser table, we can duplicate on a chip—more quickly, far more cheaply and in a much smaller space," Evans says.
Because entangled photons are intimately related at a quantum level, their physical properties are precisely correlated. As a result, manipulating the photon pairs as they move through the circuits on the chip enables researchers to use these quantum correlations as the basis for calculations. Photon-based QIP may eventually use optical chips in the same way that traditional computing uses semiconductor chips—to perform various logical functions and calculations. Increasing the number and complexity of calculations that can be handled on a chip is another step toward the goal of realizing QIP. Evans suggests that classical computers, such as ORNL's Jaguar supercomputer, could eventually be used to study the production and application of these very-large-scale optical circuits.
Step by step
In the next 5 years, Evans estimates, researchers will begin to create third-generation applications, including the ability to produce optical chips that can simulate quantum objects, such as individual atoms, molecules and complex quantum processes such as photosynthesis. Because quantum chips control and manipulate photons—which are themselves quantum objects—researchers expect this type of simulation to be more accurate and in some cases faster than simulations conducted on traditional computers. "Quantum simulators are where you'll see the early stages of the marriage between classical computing and quantum computing," he says. "This is where we will be able to supplement the function of machines like ORNL's Jaguar with quantum co-processors."
Evans expects that the fourth generation of quantum applications, or true quantum computing, will require meshing several quantum technologies. He notes that, while photon-based technologies are good for transporting information, they're not likely to be useful for creating the computational core of a quantum computer. "This is more likely to be achieved using trapped ions or a gas vapor," he says. "A separate technology may be used to serve as a memory device, and all of these elements might be linked using photons. By the time we achieve quantum simulation and quantum computing, we'll start to see the number of technologies narrowed down and implemented and integrated together."
Next stop: metamaterials
To reach the third and fourth generations of quantum information science with optical chips, Evans reckons that progress will have to be made in the area of optical "metamaterials," materials engineered from the ground up to provide certain optical characteristics. "For example, Evans says, "some optical metamaterials have a negative index of refraction, providing a way to "cloak" materials hidden inside them. We're not interested in cloaking, but we would like to be able to develop optical materials that enable us to steer photons one way or the other or make them interact in one direction but not the other. It would also be useful to find a way to store photons for a short time before throwing a switch and releasing them. This is all part of the drive toward quantum simulation and quantum computing." Evans notes that quantum technology could play a key role in the development of new optical metamaterials by using QIP to leverage the laboratory's expertise in the areas of materials science, neutron science and nanotechnology.
"ORNL and CSIIR have great resources for this sort of research and a group of people with a keen interest in quantum information science," Evans says. "As a result, we have been able to build on developments made both at the lab and at other institutions and push them toward applications. Our next step will be finding out if we can build a quantum sensor that uses meta-materials for great resolution or great sensitivity. If we can do that, then we can build toward quantum simulation and quantum computing."—Jim Pearce