The macroscopic realm, which consists of everything from falling balls to orbiting planets, can be explained by the laws of classical mechanics. When nature reaches the smallest scales, however, stranger, quantum rules kick in. Here, particles begin to exhibit bizarre properties: They do not have definite positions, and they can remain connected across vast distances and be altered by observation alone. To truly comprehend how the universe works, scientists need to be able to tap into this quantum realm.
One of the first to propose this idea was physicist Richard Feynman, who, in a now-famous 1981 lecture, stated that to understand the universe, scientists would need to use a quantum simulator. “Nature isn’t classical—and if you want to make a simulation of nature, you'd better make it quantum mechanical,” Feynman said. “And by golly it's a wonderful problem, because it doesn’t look so easy.”
The problem has, indeed, proven to be difficult: A quantum computer capable of simulating high-energy physics phenomena has yet to be developed. But over the last few decades, scientists have managed to build simulators that can touch on physics problems of the quantum realm.
“It’s quite an exciting field at the moment,” says Zohreh Davoudi, a theoretical physicist at the University of Maryland. “Several groups are pushing to reach the milestones that we have set in enabling truly quantum simulations of nature.”
From classical to quantum
The weirdness of quantum phenomena makes them challenging to study. Consider Schrödinger’s cat: In this well-known thought experiment, a theoretical cat in a sealed box whose fate is linked to a random quantum event is considered simultaneously dead and alive until the container is opened.
This demonstrates one of the fundamental properties of quantum mechanics—it is probabilistic, rather than deterministic, explains Dorota Grabowska, a theoretical physicist at the University of Washington. “You can determine the probabilities perfectly, but you can’t determine what will actually happen perfectly.”
Physicists currently tackle quantum problems on classical computers using something called the path integral formulation, a method that sums all possible paths that, say, a particle might take to get from point A to point B. Although an infinite number of paths exists, because some are more important than others, researchers can sample a finite set of those paths to predict a process’s end state.
However, the path integral formulation falls short when it comes to studying how quantum processes unfold over time. The dynamics of the early universe or the aftermath of particle collisions in high-energy accelerators, for instance, cannot be explored using the path integral formulation. “Classically, we cannot address these problems because we run into an exponentially large problem size,” Davoudi says.
The path integral formulation treats a particle along each path as something concrete, which exists in one place and state at a time, then sums up contributions from all the paths the particle takes. To understand a process with many possibilities, scientists find it helpful to treat the particle as a wave, which can represent myriad possible places and states at once.
To do that, scientists apply something called Schrödinger’s equation, also known as the Hamiltonian formulation, which can describe how the probability of a given result changes with time. But there’s a catch: You can’t run Schrödinger’s equation on a classical computer, at least not without memory and processing times that are exponentially larger than existing machines can provide; you must run it on a quantum one.
Quantum simulations
Classical computers run on bits, which can have a value of either 0 or 1. In a similar way, quantum computers run on “qubits,” which can have the value of 0, 1, or be in a superposition of both states at once.
This property allows quantum computers to rapidly process massive quantities of data, but also makes them fragile. Interacting with a quantum system can change its properties and ultimately lead to it collapsing into a classical, deterministic system. “The difficulty with quantum computers is you have to interact with them,” Grabowska says. “But you can’t interact with them too much, or else they stop being quantum.”
On top of that, the quantum computers that have been developed to date are small, typically containing a couple hundred qubits. Much larger machines are needed for most of the quantum mechanics problems physicists hope to solve.
“We are still quite limited in what we can do on quantum machines,” Grabowska says. “But we’re on the cusp of looking at the real-time properties of quantum systems that weren’t accessible previously.”
For example, over the last year or so, several groups have published studies of real-time string breaking, a name for what happens when pulling apart subatomic particles bound by the strong force releases a new particle-antiparticle pair.
The studies used two types of quantum computers—analog and digital—to simulate the string-breaking process in simplified models. “Qualitatively, the string-breaking mechanisms were the same between all three experiments,” says Davoudi, who took part in one of the studies. “It is great to have different quantum platforms to address the same problem, which eventually will be a way of verifying large-scale quantum simulations.”
Researchers have also been working on using quantum computers to analyze experimental data linked with quantum phenomena, such as particle collisions. While such processes are inherently quantum mechanical, the data themselves—because they are gathered using classical detectors—are not.
The question, according to Sofia Vallecorsa, the coordinator of the Quantum Technology Initiative at CERN, is: Can we use quantum computers to recover the original quantum mechanical laws?
At this stage, Vallecorsa says, scientists are looking at problems that can be solved using classical machines to determine whether quantum computers can solve them as well. “The good news is that they can, and for the different tasks that we have tried quantum algorithms on so far, we prove that they actually have good performance.”
Speaking quantum
Studying quantum systems with quantum computers comes with a whole host of challenges, such as learning how to translate classical codes that are based on the path integral formulation into quantum ones, which are rooted in Schrödinger’s equation.
“To me it feels like a completely different way of thinking, which is exciting” Grabowska says. “It means that you’re having to think about the same problems in completely different ways—and that is sometimes when breakthroughs happen.”
Ultimately, the goal is to create a quantum supercomputer, a so-called “fault-tolerant” machine that will be free of the limitations that exist in current simulators.
“No matter how far we take classical computing resources, we know that some physics problems cannot be addressed,” Davoudi says. “Therefore, we need to be patient. Our best bet is to wait for this technology, and in the meantime, take advantage of the technology we have today.”
Davoudi is optimistic. “The progress we’ve seen in hardware over the past five to 10 years has been really breathtaking,” she says. “I’m very hopeful that in 10 years, we’ll be in a place that we could not predict today.”
