Quantum computing, first discussed abstractly in the 1980s by physicists Paul Benioff and Richard Feynman, is gaining momentum, and significant advancements in this strange frontier are coming out of Los Alamos’ Theoretical (T) Division. In 2015, Los Alamos acquired a quantum computer (and updated it in 2019), and a number of theoretical physicists are working to find ways to unleash the potential of this strange machine.

“Quantum simulation is expected to exponentially transform our ability to predict quantum phenomena.”- Andrew Sornborger

Quantum computers use the properties of quantum physics to find shortcuts in computing by taking unconventional routes to perform operations. The individual operations are not faster than those of classical computers—they might, in fact, be slower. But, for some types of problems, a quantum computer can reach a result with many fewer operations than a classical computer.

In classical computers, binary code—a language of ones and zeroes—tells the computer what operations to perform by turning transistors (electronic signals) on and off. But what could a computer do if the transistors could be on and off and in between, all at the same time?

Physicist Erwin Schrödinger posited in his classic quantum mechanics paradox that a cat that may or may not have been poisoned after being placed inside a closed box is, until the box is opened, both dead and alive. Schrödinger’s famous cat illustrates a concept called quantum superposition—the ability of two states to exist together. Superposition is one of the things that gives quantum computing the potential to be much faster than classical computing for specific types of problems. Instead of the traditional ones and zeroes of classical computers, qubits (quantum bits, made of subatomic particles) are able to be the equivalent of one, zero, and everything in between.

Another way quantum computers are able to produce extremely fast operations is through entanglement. Entanglement describes two quantum particles that are so intrinsically connected that their states, and changes in those states, are correlated. How and why entanglement exists is still a mystery, but the phenomenon is very useful when utilized for quantum computing.

Superposition and entanglement can lead to interesting and powerful computing properties that are not possible with classical computers. Quantum computers won’t be useful for most things—they aren’t going to make websites load faster or help us with most calculations—but, for a very specific subset of problems, they have the potential to move from the beginning to the end of operations at almost unbelievable speeds—millions of times faster than their classical counterparts. Because of this, quantum computers cannot replace classical computers, but they do have exciting potential for some specific problems, especially large mathematical calculations.

Cryptography (the computerized encoding and decoding of information) is one of the most promising fields for quantum computing, as it involves patterns in numerical systems. The race to develop superior quantum computing capabilities in codebreaking is of particular importance for national security. If another country gains the ability to use quantum computers to break codes, and the United States does not yet possess that ability, all of our digital security measures could be rendered useless in the blink of an eye. The type of codebreaking that takes classical computers a very long time could be much faster on a quantum computer.

Advancement in quantum computing is tricky and arduous. Right now, most quantum computers struggle to add two plus two. Some of the most significant obstacles to quantum computing are in the infrastructure required to run the machines. Many require extreme cooling (temperatures near absolute zero), they are incredibly expensive (at least tens of millions of dollars per system), and they aren’t particularly useful—yet. So quantum computers and the scientists who work on them are rare.

There are also myriad problems inherent in machines that use subatomic particles and physical processes that are difficult to understand, much less control. Qubits are prone to decoherence, a decaying and falling-apart that prevents them from finishing their jobs. One of the biggest causes of decoherence is noise. This means not that the computers are loud, but that they produce a great deal of energy—noise—that interferes with the qubits, preventing operations from being correctly performed. A team at Los Alamos led by physicist Patrick Coles has recently developed a method to make theoretical earplugs for qubits. “Our method is analogous to how a vaccine makes you immune to a virus,” Coles says, “in that we produce circuits that are immune to a given device’s noise.”

Challenges aside, Los Alamos “is one of the strongest national labs when it comes to quantum computing theory,” says Rolando Somma, a physicist in T Division, who is active in the Laboratory’s quantum computing summer school. The participants, a combination of graduate students and upper-level undergraduates, come to Los Alamos each summer to be mentored by scientists working on quantum computing theory. In 2020, the school was conducted virtually but with the same number of lectures and projects as previous years. The school “typically results in new collaborations and papers,” Somma says.

And while the Laboratory is busy collaborating with students, it’s also collaborating with other research institutions. In August, Los Alamos joined the Quantum Science Center (QSC), a new Department of Energy initiative based at Oak Ridge National Laboratory to develop research in quantum computing. Los Alamos will lead one of the QSC’s three major research thrusts—quantum simulations and algorithms—and will contribute to the other two (quantum materials discovery and design, and quantum devices and sensors for discovery science).

“Quantum simulation is expected to exponentially transform our ability to predict quantum phenomena,” says Andrew Sornborger, a scientist in the Computer, Computational, and Statistical Sciences Division who will lead Los Alamos’ quantum algorithm efforts in QSC. “Being at the front of this research will extend our scientific computing capabilities well beyond the state of the art.”