Both teams have developed a special type of quantum computer known as a quantum simulator. The Harvard design used 51 uncharged and super-cooled rubidium atoms captured with an array of lasers, while the JQI team used 53 individual and charged ytterbium ions trapped in place by gold-coated and razor-sharp electrodes.
The Harvard system, according to the team, could be used to shed new light on a host of complex quantum processes, from the connection between quantum mechanics and material properties to investigating new phases of matter and solving complex real-world optimization problems.
The combination of the system’s large size and high degree of quantum coherence make it a particularly important achievement, the researchers say. With over 50 coherent qubits, this is one of the largest quantum systems ever created with individual assembly and measurement.
“Everything happens in a small vacuum chamber where we have a very dilute vapor of atoms which are cooled close to absolute zero,” says Mikhail Lukin, a professor at Harvard and one of the team’s leaders. “When we focus about 100 laser beams through this cloud, each of them acts like a trap. The beams are so tightly focused they can either grab one atom or zero; they can’t grab two. And that’s when the fun starts.”
Using a microscope, researchers can image the captured atoms in real time and then arrange them into arbitrary patterns to make up the system’s input. “We assemble them in a way that’s very controlled,” says Ahmed Omran, a post-doctoral fellow working in Lukin’s lab and a co-author of the paper. “Starting with a random pattern we decide which trap needs to go where to arrange them into desired clusters.”
As the researchers began feeding energy into the system, the atoms started to interact with each other, and it’s those interactions, Lukin says, that give the system its quantum nature.
“We make the atoms interact, and that’s really what’s performing the computation,”Omran says. “In essence, as we excite the system with laser light, it self-organizes. It’s not that we say this atom has to be a one or a zero—we could do that easily just by throwing light on the atoms—but what we do is allow the atoms to perform the computation for us and then we measure the results.”
Those results, Lukin says, could shed light on complex quantum mechanical phenomena that are all but impossible to model using conventional computers. “It is important that we can start by simulating small systems using our machine. So we are able to show those results are correct…until we get to the larger systems, because there is no simple comparison we can make.”
All the atoms in the experiment began in a classical state, creating a string of classical bits, zeros and ones, during the experiment. “But in order to get from the start to the end, they have to go through the complex quantum mechanical state,” says Hannes Bernien, a post-doctoral fellow in Lukin’s lab and a co-author of the study. “If you have a substantial error rate, the quantum mechanical state will collapse.”
It’s that coherent quantum state, Bernien says, that allows the system to work as a simulator, and also makes the machine a potentially valuable tool for gaining new insight into complex quantum phenomena and eventually performing useful calculations. The system already allows researchers to obtain unique insights into transformations between different types of quantum phases, called quantum phase transitions.
It may also help shed light on new and exotic forms of matter, according to Lukin.“Normally, when you talk about phases of matter, you talk about matter being in equilibrium,” he says. “But some very interesting new states of matter may occur far away from equilibrium…and there are many possibilities for that in the quantum domain. This is a completely new frontier.”
The researchers have already seen evidence of such states. In one of the first experiments conducted with the new system, the team discovered a new coherent non-equilibrium state that remained stable for a surprisingly long time.
“Quantum computers will be used to realize and study such non-equilibrium states of matter in the coming years,” Lukin says. “Another intriguing direction involves solving complex optimization problems. It turns out one can encode some very complicated problems by programming atom locations and interactions between them.”
In such systems, some proposed quantum algorithms could potentially outperform classical machines. “It’s not yet clear whether they will or not, because we just can’t test them classically,” Lukin says. “But we are on the verge of entering the regime where we can test them on the fully quantum machines containing over a hundred controlled qubits. Scientifically, this is really exciting.”
That’s a sentiment shared by the research team at the University of Maryland. Its research uses interacting atomic qubits to mimic magnetic quantum matter. “Each ion qubit is a stable atomic clock that can be perfectly replicated,” says Christopher Monroe, the UMD team leader. “They are effectively wired together with external laser beams. This means that the same device can be reprogrammed and reconfigured, from the outside, to adapt to any type of quantum simulation or future quantum computer application that comes up.”
Monroe has been one of the early pioneers in quantum computing and his research group’s quantum simulator is part of a blueprint for a general-purpose quantum computer. While modern, transistor-driven computers are great for crunching their way through many problems, they can screech to a halt when dealing with more than 20 interacting quantum objects. That’s certainly the case for quantum magnetism, in which the interactions can lead to magnetic alignment or to a jumble of competing interests at the quantum scale.
“What makes this problem hard is that each magnet interacts with all the other magnets,” says Zhexuan Gong, a UMD research scientist, lead theorist and co-author on the study. “With the 53 interacting quantum magnets in this experiment, there are over a quadrillion possible magnet configurations, and this number doubles with each additional magnet. Simulating this large-scale problem on a conventional computer is extremely challenging, if at all possible.”
When these calculations hit a wall, a quantum simulator may help scientists push the envelope on difficult problems. This is a restricted type of quantum computer that uses qubits to mimic complex quantum matter. Qubits are isolated and well-controlled quantum systems that can be in a combination of two or more states at once. Qubits come in different forms, and atoms—the versatile building blocks of everything—are one of the leading choices for making qubits. In recent years, scientists have controlled 10 to 20 atomic qubits in small-scale quantum simulations.
Currently, tech industry behemoths, startups and university researchers are in a fierce race to build prototype quantum computers that can control even more qubits. But qubits are delicate and must stay isolated from the environment to protect the device’s quantum nature. With each added qubit this protection becomes more difficult, especially if qubits are not identical from the start, as is the case with fabricated circuits. This is one reason that atoms are an attractive choice—they can dramatically simplify the process of scaling up to large-scale quantum machinery, according to the UMD team.
Unlike the integrated circuitry of modern computers, the atomic qubits at UMD reside inside a vacuum chamber that maintains a pressure similar to outer space. This isolation is necessary to keep the destructive environment at bay, and it allows the scientists to precisely control the atomic qubits with a highly engineered network of lasers, lenses, mirrors, optical fibers and electrical circuitry. “The principles of quantum computing differ radically from those of conventional computing, so there’s no reason to expect that these two technologies will look anything alike,” says Monroe.
In the 53-qubit simulator, the ion qubits are made from atoms that all have the same electrical charge and therefore repel one another. But as they push each other away, an electric field generated by a trap forces them back together. The two effects balance each other, and the ions line up single file. The UMD team leveraged the inherent repulsion to create deliberate ion-to-ion interactions that are necessary for simulating of interacting quantum matter.
The quantum simulation begins with a laser pulse that commands all the qubits into the same state. Then, a second set of laser beams interacts with the ion qubits, forcing them to act like tiny magnets, each having a north and south pole. The team does this second step suddenly, which jars the qubits into action. The researchers say the qubits feel torn between two choices, or phases, of quantum matter.
As magnets, they can either align their poles with their neighbors to form a ferromagnet or point in random directions yielding no magnetization, according to the team. The researchers can change the relative strengths of the laser beams and observe which phase wins out under different laser conditions.
The entire simulation takes only a few milliseconds. By repeating the process many times and measuring the resulting states at different points during the simulation, the team can see the process as it unfolds from start to finish. The researchers observe how the qubit magnets organize as different phases form, dynamics that the team says are nearly impossible to calculate using conventional means when there are so many interactions.
This quantum simulator is suitable for probing magnetic matter and related problems, according to the team, but other kinds of calculations may need a more general quantum computer with arbitrarily programmable interactions in order to get a boost.
“Quantum simulations are widely believed to be one of the first useful applications of quantum computers,” says Alexey Gorshkov, a NIST theoretical physicist and co-author of the study. “After perfecting these quantum simulators, we can then implement quantum circuits and eventually quantum-connect many such ion chains together to build a full-scale quantum computer with a much wider domain of applications.”
As the team looks to add even more qubits, it believes that its simulator will embark on more computationally challenging terrain, beyond magnetism. “We are continuing to refine our system, and we think that soon, we will be able to control 100 ion qubits or more,” says Jiehang Zhang, the study’s lead author and UMD postdoctoral researcher. “At that point, we can potentially explore difficult problems in quantum chemistry or materials design.”