AI designs quantum physics experiments beyond any human imagination

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AI designs quantum physics experiments beyond any human imagination. Originally created to speed up computing, a machine learning system is now making amazing advances at the frontiers of experimental quantum physics and AI quantum physics experiment design beyond anything any human ever imagined.

AI designs quantum physics

Quantum physicist Mario Crain recalls sitting in a Vienna cafe in early 2016, examining computer printouts, trying to decipher what Melvin had found. Melvin was a machine learning algorithm created by Crain, a type of artificial intelligence. His job was to combine the building blocks of standard quantum experiments and find solutions to new problems. And he made many interesting discoveries. But there was one that didn’t make any sense.

“My first thought was, ‘There is a bug in my program, because the solution may not exist,'” says Crain. Melvin solved the problem of creating highly complex entangled states involving multiple photons (entangled states are what Albert Einstein once called the specter of “spooky action at a distance”).

Keren, Anton Zeilinger of the University of Vienna, and their colleagues did not explicitly provide Melvin with the rules necessary to generate such complex states, but they found a way. Eventually, he realized that the algorithm had discovered a kind of experimental arrangement that had been devised in the early 1990s. But those experiments were very easy. Melvin had solved a much more complex puzzle.

“When we understood what was going on, we were able to generalize [the solution] right away,” says Crain, who now works at the University of Toronto. Since then, other teams have begun conducting the experiments identified by MELVIN, allowing them to test the conceptual basis of quantum mechanics in new ways.

Meanwhile, Crane, working with colleagues in Toronto, has perfected his machine learning algorithm. His latest effort, an AI named THESEUS, has gone further: It’s orders of magnitude faster than MELVIN, and humans can easily analyze its output. While it will take KERNEN and his colleagues days or even weeks to understand Melvin’s words, they can almost immediately understand what THESEUS is saying.

“This is amazing work,” says theoretical quantum physicist Renato Rainer of the Institute for Theoretical Physics at the Swiss Federal Institute of Technology in Zurich, who reviewed the 2020 study on THESEUS but was not directly involved in these efforts.

Crane stumbled upon this entire research program somewhat by accident when he and his colleagues were trying to figure out how to experimentally create the quantum states of photons in a particular way: when two photons interact, then they become entangled, and both can only be described. mathematically using a single shared quantum state. If you measure the position of one photon, the measurement immediately fixes the position of the other, even if the two are miles apart (hence Einstein’s sarcastic comment that entanglement is “creepy”).

In 1989, three physicists — Daniel Greenberger, the late Michael Horn, and Zeilinger — described an entangled state that became known as “GHz” (from its initials). It consisted of four photons, each of which could be in a two-state quantum superposition, 0 and 1 (called quantum). In his paper, the GHZ state entangled four qubits so that the whole system was in a two-dimensional quantum superposition of states 0000 and 1111. If you measure one of the photons and find it in state 0, the superposition will collapse and the other photons They will also be in state 0. The same was true of state 1. In the late 1990s, Zeilinger and his colleagues first observed GHZ states experimentally using three qubits.

Quantum physics

Krenn and his colleagues were targeting higher dimensional GHZ states. They wanted to work with three photons, where each photon had a dimensionality of three, which means that it could be in a superposition of three states: 0, 1, and 2. This quantum state is called a qutrit. The entanglement the team was looking for was a three-dimensional GHZ state that was a superposition of states 000, 111, and 222.

These states are important elements for secure quantum communication and fast quantum computing. In late 2013, researchers spent weeks at the blackboard designing experiments and performing calculations to see if their configuration could produce the required quantum state. But each time they failed. “I thought, ‘This is absolutely crazy. Why can’t we come up with a setup?'” Says Crain.

Krenn and his colleagues were aiming for higher dimensional GHZ states. They wanted to work with three photons, where each photon had a dimensionality of three, which means that it could be in a superposition of three states: 0, 1, and 2. This quantum state is called a qutrit. The entanglement the team was looking for was a three-dimensional GHZ state that was a superposition of states 000, 111, and 222.

These states are important elements for secure quantum communication and fast quantum computing. In late 2013, researchers spent weeks at the blackboard designing experiments and performing calculations to see if their configuration could produce the required quantum state. But each time they failed. “I thought, ‘This is absolutely crazy. Why can’t we come up with a setup?'” Says Crain.

To speed up the process, Krenn first wrote a computer program that took an experimental setup and calculated the result. He then updated the program to include in their calculations the same building blocks that experimenters use to create and manipulate photons on the optical bench: lasers, non-linear crystals, beam splitters, phase shifters, holograms, etc.

The program searched a large space of configurations, calculated, and produced results by randomly mixing and matching the building blocks. Melvin was born. “In a few hours, the program found a solution that the scientists, three experimenters and a theorist, could not find for months,” says Crain. “That was a crazy day. I can’t believe it happened.”

He then gave Melvin more intelligence. Whenever he found a configuration that did something useful, MELVIN would add that configuration to his toolbox. “The algorithm remembers this and tries to reuse it for more complex solutions,” says Crain. It was the more developed Melvin who left Crain scratching his head at the Viennese cafe. He configured it to work with an experimental toolbox consisting of two crystals, each capable of generating a pair of entangled photons in three dimensions.

Crain’s naive expectation was that Melvin would discover configurations that combine these pairs of photons to form entangled states of up to nine dimensions. But “actually he found a solution, an extremely rare case, in which there is much more mess than in the rest of the states,” says Keren.

Eventually, they learned that Melvin had used a technique that various teams had developed nearly three decades earlier. One method was devised in 1991 by Shin Yu Zhu, Lee Jun Wang, and Leonard Mandel at the University of Rochester. And in 1994 Zeilinger, then at the University of Innsbruck in Austria, and his colleagues devised another. conceptually.

These experiments attempted something similar, but the setup that Zeilinger and his colleagues produced is easier to understand. It starts with a crystal that generates a pair of photons (A and B). The path of these photons passes through another crystal, which can also generate two photons (C and D).

The paths of photon A from the first crystal and photon C from the second crystal overlap exactly and lead to the same detector. If that detector clicks, it is impossible to tell if the photon originated from the first or second crystal. The same is true for photons b and d.

AI designs quantum physics

A phase shifter is a device that effectively increases the path traveled by a photon as a fraction of its wavelength. If you introduce a phase shifter in one of the paths between the crystals and keep changing the amount of the phase change, it can cause constructive and destructive interference to the detectors.

For example, each crystal can generate 1,000 pairs of photons per second. With constructive interference, the detectors would register 4,000 pairs of photons per second. And with destructive interference, they won’t detect any – the entire system won’t create photons, even though individual crystals are generating 1,000 pairs per second. “It’s actually pretty crazy, when you think about it,” says Crain.

Melvin’s original solution included overlapping paths. One of the things that Crain winced was that there were only two crystals in the algorithm’s toolbox. And instead of using those crystals at the beginning of the experimental setup, he mounted them inside an interferometer (a device that divides the path of a photon in two and then recombines them). After much effort, he realized that the configuration Melvin had found was equivalent to one containing more than two crystals, each of which generated pairs of photons.

So that their paths to the detectors overlapped. The configuration can be used to generate high-dimensional interlaced states. Quantum physicist Nora Tishler, who has a Ph.D. A student working with Zeilinger on an unrelated topic, while Melvin was going through his rhythm, was noticing these events. “It was clear from the beginning [that] such an experiment would not exist if it had not been discovered by an algorithm,” she says.

In addition to generating complex entangled states, configurations using more than two crystals with overlapping trajectories can be used to perform the generalized form of the 1994 Zeilinger quantum interference experiments with two crystals. Ephraim Steinberg, an experimentalist at the University of Toronto.

Whoever is Crane’s contributor, but hasn’t worked on these projects, is impressed by what he found the AI. “It’s a generalization that (to my knowledge) no human could and never would have dreamed of for decades to come,” he says. “This is a great first example of the kind of new explorations that these thinking machines can advance us.”

In such a generalized configuration with four crystals, each generating a pair of photons and overlapping paths leading to all four detectors, quantum interference can cause a situation where all four detectors click (creative interference) or none at all. of them does (destructive interference). ).

But until recently, conducting such an experiment remained a distant dream. Then, in a March prepress article, a team led by Lan-Tian Feng of the China University of Science and Technology, in collaboration with Crane, reports that they had manufactured and experimented with the entire setup on a single photonic chip.

The researchers collected the data over more than 16 hours – a feat made possible by the incredible optical stability of the photonic chip, something that would have been impossible to achieve in a large-scale tabletop experiment. To get started, the setup will require a square meter of optics lined up correctly on an optical bench, Steinberg says. Furthermore, “an optical element that moves or flows through one thousandth of the diameter of a human hair during those 16 hours could be enough to eliminate the effect,” he says.

Quantum Physics

During their early attempts to simplify and generalize what Melvin found, Crain and his colleagues realized that the solutions resembled abstract mathematical shapes called graphs, which contain vertices and edges and represent pairwise relationships between objects. For these quantum experiments, each path the photon takes is represented by a vertex.

And a crystal, for example, is represented by an edge that connects two vertices. Melvin first prepared such a graph and then performed mathematical operations on it. The operation, called “perfect match”, involves creating a uniform graph in which each vertex is associated with a single edge. This process makes it very easy to calculate the final quantum state, although it is still difficult for humans to understand.

This changed with Melvin’s successor, which first generates much simpler graphs by representing the complex graph with a solution that reduces it to the absolute minimum number of edges and vertices (so no further eliminations are required to generate the desired quantum states) . The charts are simpler than Melvin’s perfect match charts, so any AI-generated solution is even easier to understand.

Rainer is particularly impressed by THESEUS ‘human acting output. “The solution is designed to minimize the number of connections on the graph,” he says. “And that’s naturally a solution that we could understand better if you had a very complex graph.” Eric Cavalcanti from Griffith University in Australia is impressed and attentive to the work. “These machine learning techniques represent an interesting development. For a human scientist looking at and interpreting the data, some solutions may seem like new ‘creative’ solutions.

But at this stage, these algorithms are still far from the level where you can tell they are actually coming up with new ideas or creating new concepts, “he says. “On the other hand, I think one day they will get there. So these are small steps, but we have to start somewhere.” Steinberg agrees. “For now, they are amazing tools,” he says. “And like all great tools, they already allow us to do some things that we probably wouldn’t have been able to do without them.”

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