Physics gets weird on the atomic scale. Scientists are using quantum analog simulators—laboratory experiments involving cooling many atoms to low temperatures and examining them with precisely calibrated lasers and magnets—to uncover, exploit, and control these unusual quantum effects. Scientists hope that any new insights from quantum simulations will provide blueprints for the development of new exotic materials, smarter and more efficient electronics, and practical quantum computers. But to extract information from quantum simulators, scientists must first trust them.

That is, they must ensure that their quantum device is “highly sensitive” and accurately reflects quantum behavior. For example, if an atomic system is easily affected by external noise, researchers might assume the existence of a quantum effect where nothing happens. But until now, there was no reliable way to characterize the accuracy of quantum analog simulators.

In a recently published study NaturePhysicists at MIT and Caltech have reported a new quantum phenomenon: They discovered that there is some randomness in the quantum fluctuations of atoms, and that this random behavior exhibits a universal, predictable pattern. Behavior that is both random and predictable may sound contradictory. However, the team confirmed that certain random fluctuations may indeed follow a predictable statistical pattern.

At most, the researchers used this quantum randomness as a tool to characterize the accuracy of the quantum analog simulator. Using theory and experimentation, they showed they could determine the accuracy of a quantum simulator by analyzing its random fluctuations.

The team developed a new benchmarking protocol that can be applied to existing quantum analog simulators to evaluate their accuracy based on quantum fluctuation models. The protocol could help accelerate the development of new exotic materials and quantum computing systems.

“This work will enable very high precision characterization of many existing quantum devices,” said co-author Sunwon Choi, professor of physics at MIT. “It also shows that there are deeper theoretical structures behind randomness in chaotic quantum systems than we previously thought.”

The study’s authors include MIT graduate student Daniel Mark and colleagues from the California Institute of Technology, the University of Illinois at Urbana-Champaign, Harvard University, and the University of California, Berkeley.

random evolution

The new work stems from the progress Google made in 2019 when researchers developed a digital quantum computer called “Çınar” that could do certain calculations faster than a classical computer.

The computational units in a classical computer are “bits” that exist as 0 or 1, while the units in a quantum computer known as “qubits” can exist in the superposition of multiple states. When several qubits interact, they can theoretically run special algorithms that solve complex problems in much less time than any classical computer.

Google researchers have developed a system of superconducting loops that act like 53 qubits and have shown that the “computer” can perform certain calculations that are normally very difficult for even the world’s fastest supercomputer.

Google has also demonstrated that it can measure the accuracy of the system. By randomly changing the state of individual qubits and comparing the resulting states of all 53 qubits with those predicted by the principles of quantum mechanics, they were able to measure the accuracy of the system.

Choi and colleagues wondered if they could use a similar random approach to measure the accuracy of quantum analog simulators. But they had one hurdle to overcome: Unlike Google’s digital quantum system, it is incredibly difficult to manipulate and therefore randomly control individual atoms and other qubits in analog simulators.

But with some theoretical modeling, Choi realized that the collective effect of individual manipulation of qubits in Google’s system could be reproduced in an analog quantum simulator by allowing the qubits to evolve naturally.

“We realized we didn’t need to create this kind of random behavior,” Choi says. “Without tweaking, we can allow the natural dynamics of quantum simulators to evolve, and the result will be a similar pattern of randomness through chaos.”

build trust

As an extremely simplified example, imagine a system of five qubits. Each qubit can exist simultaneously as a 0 or a 1 until a measurement is made, at which point the qubits enter one state or the other. In any given measure, qubits can take one of 32 different combinations: 0-0-0-0-0, 0-0-0-0-1, etc.

“These 32 configurations will occur with a certain probability distribution that people think should be similar to the predictions of statistical physics,” explains Choi. “We show that they match on average, but there are biases and fluctuations that reveal a universal randomness that we didn’t know existed. And that randomness looks like you’re executing the random operations that Google does.”

The researchers hypothesized that if they could develop a numerical simulation that accurately represented the dynamics and universal random fluctuations of the quantum simulator, they could compare the predicted results with the actual simulation results. The closer they are, the more accurate the quantum simulator should be.

To test this idea, Choi teamed up with experimenters at the California Institute of Technology, who are developing a quantum analog simulator made up of 25 atoms. In the experiment, the physicists used a laser to co-excite atoms and then let the qubits naturally interact and evolve over time. They measured the state of each qubit several times and collected a total of 10,000 measurements.

Choi and colleagues also developed a numerical model representing the quantum dynamics of the experiment and combined an equation they derived to predict the universal random fluctuations that should occur. The researchers then compared their experimental measurements with the model’s predicted results and observed a very close match; strong evidence that this particular simulation represents purely quantum-mechanical behavior.

More generally, the results show a new way to characterize nearly all existing quantum analog simulators.

“The ability to characterize quantum devices makes it an essential engineering tool for building larger, more precise and more complex quantum systems,” says Choi. “With our tool, people can tell if they’re working with a reliable system.”