Nav: Home

Artificial intelligence techniques reconstruct mysteries of quantum systems

February 26, 2018

The same techniques used to train self-driving cars and chess-playing computers are now helping physicists explore the complexities of the quantum world.

For the first time, physicists have demonstrated that machine learning can reconstruct a quantum system based on relatively few experimental measurements. This method will allow scientists to thoroughly probe systems of particles exponentially faster than conventional, brute-force techniques. Complex systems that would require thousands of years to reconstruct with previous methods could be wholly analyzed in a matter of hours.

The research will benefit the development of quantum computers and other applications of quantum mechanics, the researchers report February 26 in Nature Physics.

"We have shown that machine intelligence can capture the essence of a quantum system in a compact way," says study co-author Giuseppe Carleo, an associate research scientist at the Center for Computational Quantum Physics at the Flatiron Institute in New York City. "We can now effectively extend the capabilities of experiments."

Carleo, who conducted the research while a lecturer at ETH Zurich, was inspired by AlphaGo. This computer program used machine learning to outplay the world champion of the Chinese board game Go in 2016. "AlphaGo was really impressive," he says, "so we started asking ourselves how we could use those ideas in quantum physics."

Systems of particles such as electrons can exist in lots of different configurations, each with a particular probability of occurring. Each electron, for instance, can have either an upward or downward spin, similar to Schrödinger's cat being either dead or alive in the famous thought experiment. In the quantum realm, unobserved systems don't exist as any one of these arrangements. Instead, the system may be thought of as being is in all possible configurations simultaneously.

When measured, the system collapses into one configuration, just like Schrödinger's cat is either dead or alive once you open its box. This quirk of quantum mechanics means that you can never observe the entire complexity of a system in a single experiment. Instead, experimentalists conduct the same measurements over and over until they can determine the state of the whole system.

That method works well for simple systems containing only a few particles. But "things get nasty with a lot of particles," Carleo says. As the number of particles increases, the complexity skyrockets. If only considering that each electron can have either spin up or down, a system of five electrons has 32 possible configurations. A system of 100 electrons has more than 1 million trillion trillion.

The entanglement of particles further complicates matters. Through quantum entanglement, independent particles become intertwined and can no longer be treated as purely separate entities even when physically separated. This entanglement alters the probability of different configurations.

Conventional methods, therefore, just aren't feasible for complex quantum systems.

Giacomo Torlai of the University of Waterloo and the Perimeter Institute in Canada, Carleo and colleagues circumvented these limitations by tapping machine learning techniques. The researchers fed experimental measurements of a quantum system to a software tool based on artificial neural networks. The software learns over time and attempts to mimic the system's behavior. Once the software ingests enough data, it can accurately reconstruct the complete quantum system.

The researchers tested the software using mock experimental datasets based on different sample quantum systems. In these tests, the software far surpassed conventional methods. For eight electrons, each with spin up or down, the software could accurately reconstruct the system with only around 100 measurements. For comparison, a conventional brute-force method required almost 1 million measurements to reach the same level of accuracy. The new technique can also handle much larger systems. In turn, this ability can help scientists validate that a quantum computer is correctly set up and that any quantum software would run as intended, the researchers suggest.

Capturing the essence of complex quantum systems with compact artificial neural networks has other far-reaching consequences. Center for Computational Quantum Physics co-director Andrew Millis notes that the ideas provide an important new approach to the center's ongoing development of novel methods for understanding the behavior of interacting quantum systems, and connect with work on other quantum physics-inspired machine learning approaches.

Besides applications to fundamental research, Carleo says that the lessons the team learned as they blended machine learning with ideas from quantum physics could improve general-purpose applications of artificial intelligence as well. "We could use the methods we developed here in other contexts," he says. "Someday we might have a self-driving car inspired by quantum mechanics, who knows."
-end-
ABOUT THE FLATIRON INSTITUTE

The Flatiron Institute is the research division of the Simons Foundation. Its mission is to advance scientific research through computational methods, including data analysis, modeling and simulation. The institute's Center for Computational Quantum Physics aims to develop the concepts, theories, algorithms and codes needed to solve the quantum many-body problem and to use the solutions to predict the behavior of materials and molecules of scientific and technological interest.

Simons Foundation

Related Quantum Physics Articles:

Quantum physics: On the way to quantum networks
Physicists at Ludwig-Maximilians-Universitaet (LMU) in Munich, together with colleagues at Saarland University, have successfully demonstrated the transport of an entangled state between an atom and a photon via an optic fiber over a distance of up to 20 km -- thus setting a new record.
Quantum physics: Controlled experiment observes self-organized criticality
Researchers from Cologne, Heidelberg, Strasbourg and California have observed important characteristics of complex systems in a lab experiment.
A platform for stable quantum computing, a playground for exotic physics
Harvard University researchers have demonstrated the first material that can have both strongly correlated electron interactions and topological properties, which not only paves the way for more stable quantum computing but also an entirely new platform to explore the wild world of exotic physics.
A new quantum data classification protocol brings us nearer to a future 'quantum internet'
A new protocol created by researchers at the Universitat Autònoma de Barcelona sorts and classifies quantum data by the state in which they were prepared, with more efficiency than the equivalent classical algorithm.
Quantum physics: Ménage à trois photon-style
When two photons become entangled, the quantum state of the first will correlate perfectly with the quantum state of the second.
Quantum physics -- Simulating fundamental interactions with ultracold atoms
An international team of physicists succeeded in precisely engineering key ingredients to simulate a specific lattice gauge theory using ultracold atoms in optical lattices.
A key piece to understanding how quantum gravity affects low-energy physics
In a new study, led by researchers from SISSA (Scuola Internazionale Superiore di Studi Avanzati), the Complutense University of Madrid and the University of Waterloo, a solid theoretical framework is provided to discuss modifications to the Unruh effect caused by the microstructure of space-time.
Helping physics teachers who don't know physics
A shortage of high school physics teachers has led to teachers with little-to-no training taking over physics classrooms, reports show.
Quantum physics and origami for the ultimate get-well card
The bizarre optical properties of tiny metal particles -- smaller than light waves -- can be captured on paper to detect even a single target molecule in a test sample.
Can artificial intelligence solve the mysteries of quantum physics?
A new study published in Physical Review Letters by Prof.
More Quantum Physics News and Quantum Physics Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Listen Again: Reinvention
Change is hard, but it's also an opportunity to discover and reimagine what you thought you knew. From our economy, to music, to even ourselves–this hour TED speakers explore the power of reinvention. Guests include OK Go lead singer Damian Kulash Jr., former college gymnastics coach Valorie Kondos Field, Stockton Mayor Michael Tubbs, and entrepreneur Nick Hanauer.
Now Playing: Science for the People

#562 Superbug to Bedside
By now we're all good and scared about antibiotic resistance, one of the many things coming to get us all. But there's good news, sort of. News antibiotics are coming out! How do they get tested? What does that kind of a trial look like and how does it happen? Host Bethany Brookeshire talks with Matt McCarthy, author of "Superbugs: The Race to Stop an Epidemic", about the ins and outs of testing a new antibiotic in the hospital.
Now Playing: Radiolab

Dispatch 6: Strange Times
Covid has disrupted the most basic routines of our days and nights. But in the middle of a conversation about how to fight the virus, we find a place impervious to the stalled plans and frenetic demands of the outside world. It's a very different kind of front line, where urgent work means moving slow, and time is marked out in tiny pre-planned steps. Then, on a walk through the woods, we consider how the tempo of our lives affects our minds and discover how the beats of biology shape our bodies. This episode was produced with help from Molly Webster and Tracie Hunte. Support Radiolab today at Radiolab.org/donate.