New Protocol Helps Classify Topological Matter

Topological materials have captured the interest of many scientists and may provide the basis for a new era in materials development. On April 10, 2020 in the journal Science Advances, physicists working with Andreas Elben, Jinlong Yu, Peter Zoller and Benoit Vermersch, including Associate Professor Mohammad Hafezi and former Joint Quantum Institute (JQI) postdoctoral researcher Guanyu Zhu (currently a research staff member at IBM T. J. Watson Research Center), presented a new method for identifying and characterizing topological invariants on various experimental platforms, testing their protocol in a quantum simulator made of neutral atoms.

Quantum simulators are an emerging tool for preparing and investigating complex quantum states. They can be realized in a variety of different physical systems—such as ultracold atoms in optical lattices, Rydberg atoms, trapped ions or superconducting quantum bits—and they promise to enhancemany body topological invariants from randomized measurements finalTopological phases of matter are a particularly fascinating class of quantum states. (Credit: Harald Ritsch/IQOQI Innsbruck) the study of exotic states of matter.

In particular, this new breed of simulator may be able to prepare topological states of matter, which researchers find particularly fascinating. In 2016, David Thouless, Duncan Haldane and Michael Kosterlitz were awarded the Nobel Prize in Physics for their theoretical discoveries about topological states. Scientists now know that these states of matter are characterized by nonlocal quantum correlations, making them particularly robust against local distortions that inevitably occur in experiments.

But it’s often hard to know if a material sample in the lab is in a topological phase. "Identifying and characterizing such topological phases in experiments is a great challenge," say Vermersch, Yu and Elben from the Center for Quantum Physics at the University of Innsbruck and the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences. "Topological phases cannot be identified by local measurements because of their special properties. We are therefore developing new measurement protocols that will enable experimental physicists to characterize these states in the laboratory".

In recent years this identification has been achieved for systems without any interactions. However, for interacting systems, which in the future could also be used as topological quantum computers, this has not been possible so far.

In the new work, the research team proposed and experimentally tested protocols that might enable other experimenters to measure topological invariants. These mathematical expressions distinguish different topological phases, making it possible to classify interacting topological states in a wide variety of systems.

"The idea of our method is to first prepare such a topological state in a quantum simulator,” explains Elben. “Now so-called random measurements are performed, and topological invariants are extracted from statistical correlations of these random measurements.”

The key to the method is that although the topological invariants are highly complex, non-local correlation functions, they can still be extracted from statistical correlations of simple and local random measurements. “The many-body invariants characterizing different types of topological orders are path-integrals in topological quantum field theory, corresponding to various types of space-time manifolds, such as the real-projective plane,” says Zhu. “It is kind of a miracle that we eventually realized that these highly abstract quantities in theory can actually be measured in relatively simple experiments.”

And as some members of the research group have recently shown, such random measurements are possible in experiments today. "Our protocols for measuring the topological invariants can therefore be directly applied in the existing experimental platforms," says Vermersch.

In addition to Elben, Yu, Zoller, Vermersch, Zhu and Hafezi, the co-authors included Frank Pollmann from the Technical University of Munich. The research was financially supported by the European Research Council and the EU flagship for quantum technologies, as well as the Army Research Office MURI program and the NSF Physics Frontier Center at JQI.

This story was originally published by the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences in Innsbruck. It was adapted with permission by the JQI:

Research Contact: Mohammad Hafezi, This email address is being protected from spambots. You need JavaScript enabled to view it.


Understanding and Exploring Network Epidemiology in the Time of Coronavirus

In response to the COVID-19 pandemic, Michelle Girvan, Daniel Serrano, Juniper Lovato, Anshuman Swain, and Nick Mennona launched Understanding and Exploring Network Epidemiology in the Time of Coronavirus (#Net_COVID), an online workshop series in network biology developed and presented by the University of Maryland’s COMBINE partnership with Vermont’s Complex Systems Center.

The series includes tutorials and seminars to contextualize and understand the current COVID-19 global pandemic using network science. Activities include introduction to network epidemiology, review of recent research on coronavirus, and exploration of various modeling and data analysis approaches. 

The intended audience for the series includes STEM graduate students, postdocs, faculty, and other researchers who are interested in network epidemiology. A prior background in network science is not necessary, but may be helpful for some optional discussion group activities.

The tutorials and seminars can be viewed on the COMBINE YouTube Channel.

The response to the series has been considerable with approximately 250 participating in the seminars and 150 actively engaging in small working groups. Participants are drawn from around the world, with many from UMD taking part in research projects. 

For more information, visit the website or contact the organizers at This email address is being protected from spambots. You need JavaScript enabled to view it.


This story was originally published here:

Donuts, Donut Holes and Topological Superconductors

Topology—the mathematical study of shapes that describes how a donut differs from a donut hole—has turned out to be remarkably relevant to understanding our physical world. For decades, it’s captured the hearts and minds of physicists, who have spent that time uncovering just how deep the connection between topology and physics runs. Among many other things, they’ve unearthed a prediction, born of topology, for a new particle with promising applications to quantum computing.topology shapes1a color scheme 6E. Edwards, IQUIST

In this episode of the Joint Quantum Institute's Relatively Certain podcast, Dina Genkina sits down with Associate Professor Jay Sau and Professor Johnpierre Paglione, the director of the Quantum Materials Center. They take a trip back to the 1980s, when the story of topology in physics began, and arrive at a recent discovery by Paglione and his collaborators of a (possible) topological superconductor.

This episode of Relatively Certain was produced by Dina Genkina, Chris Cesare, and Emily Edwards. It features music by Dave Depper, Frequency Decree, Chad Crouch and Scott Holmes.

Relatively Certain is a production of the Joint Quantum Institute, a research partnership between the University of Maryland and the National Institute of Standards and Technology, and you can find it on iTunesGoogle PlaySoundcloud or Spotify.


Charting a Course Toward Quantum Simulations of Nuclear Physics

In nuclear physics, like much of science, detailed theories alone aren’t always enough to unlock solid predictions. There are often too many pieces, interacting in complex ways, for researchers to follow the logic of a theory through to its end. It’s one reason there are still so many mysteries in nature, including how the universe’s basic building blocks coalesce and form stars and galaxies. The same is true in high-energy experiments, in which particles like protons smash together at incredible speeds to create extreme conditions similar to those just after the Big Bang.for jqi article v.1.1 gallary copyTrapped ion quantum simulators may soon offer new means to explore the properties of matter emerging from complex interactions among quarks, gluons and the other fundamental building blocks of nature. (Credit: A. Shaw and Z. Davoudi/University of Maryland)

Fortunately, scientists can often wield simulations to cut through the intricacies. A simulation represents the important aspects of one system—such as a plane, a town’s traffic flow or an atom—as part of another, more accessible system (like a computer program or a scale model). Researchers have used their creativity to make simulations cheaper, quicker or easier to work with than the formidable subjects they investigate—like proton collisions or black holes.

Simulations go beyond a matter of convenience; they are essential for tackling cases that are both too difficult to directly observe in experiments and too complex for scientists to tease out every logical conclusion from basic principles. Diverse research breakthroughs—from modeling the complex interactions of the molecules behind life to predicting the experimental signatures that ultimately allowed the identification of the Higgs boson—have resulted from the ingenious use of simulations.

But conventional simulations only get you so far. In many cases, a simulation requires so many computations that the best computers ever built can’t make meaningful progress—not even if you are willing to wait your entire life.

Now, quantum simulators (which exploit quantum effects like superposition and entanglement) promise to bring their power to bear on many problems that have refused to yield to simulations built atop classical computers—including problems in nuclear physics. But to run any simulation, quantum or otherwise, scientists must first determine how to faithfully represent their system of interest in their simulator. They must create a map between the two.

Assistant professor Zohreh Davoudi, a computational nuclear physicist, is collaborating with researchers at the Joint Quantum Institute to explore how quantum simulations might aid nuclear physicists. They are working to create some of the first maps between the theories that describe the underpinnings of nuclear physics and the early quantum simulators and quantum computers being put together in labs.

“It seems like we are at the verge of going into the next phase of computing that takes advantage of quantum mechanics,” says Davoudi. “And if nuclear scientists don't get into this field now—if we don't start to move our problems into such quantum hardware, we might not be able to catch up later because quantum computing is evolving very fast.”

Davoudi and several colleagues, including Chris Monroe and Mohammad Hafezi, designed their approach to making maps with an eye toward compatibility with the quantum technologies on the horizon. In a new paper published April 8, 2020 in the journal Physical Review Research, they describe their new method and how it creates new simulation opportunities for researchers to explore.

“It is not yet clear exactly where quantum computers will be usefully applied,” says Monroe, who is also a professor of physics at UMD and co-founder of the quantum computing startup IonQ. “One strategy is to deploy them on problems that are based in quantum physics. There are many approaches in electronic structure and nuclear physics that are so taxing to normal computers that quantum computers may be a way forward.”

Patterns and Control

As a first target, the team set their sights on lattice gauge theories. Gauge theories describe a wide variety of physics, including the intricate dance of quarks and gluons—the fundamental particles in nuclear physics. Lattice versions of gauge theories simplify calculations by restricting all the particles and their interactions to an orderly grid, like pieces on a chessboard.

Even with this simplification, modern computers can still choke when simulating dense clumps of matter or when tracking how matter changes over time. The team believes that quantum computers might overcome these limitations and eventually simulate more challenging types of gauge theories—such as quantum chromodynamics, which describes the strong interactions that bind quarks and gluons into protons and neutrons and hold them together as atomic nuclei.

Davoudi and her colleagues chose trapped atomic ions—the specialty of Monroe—as the physical system for performing their simulation. In these systems, ions, which are electrically charged atoms, hover, each trapped by a surrounding electric or magnetic field. Scientists can design these fields to arrange the ions in various patterns that can be used to store and transfer information. For this proposal, the team focused on ions organized into a straight line.

Researchers use lasers to control each ion and its interactions with neighbors—an essential ability when creating a useful simulation. The ions are much more accessible than the smaller particles that intrigue Davoudi. Nuclear physicists can only dream of achieving the same level of control over the interactions at the hearts of atoms.

“Take a problem at the femtometer scale and expand it to micron scale—that dramatically increases our level of control,” says Hafezi, who is also an associate professor in the Department of Electrical and Computer Engineering and the Department of Physics at UMD. “Imagine you were supposed to dissect an ant. Now the ant is stretched to the distance between Boston and Los Angeles.”

While designing their map-making method, the team looked at what can be done with off-the-shelf lasers. They realized that current technology allows ion trappers to set up lasers in a new, efficient way that allows for simultaneous control of three different spin interactions for each ion.

“Trapped-ion systems come with a toolbox to simulate these problems,” says Hafezi. “Their amazing feature is that sometimes you can go back and design more tools and add it to the box.”

With this opportunity in mind, the researchers developed a procedure for producing maps with two desirable features. First, the maps maximize how faithfully the ion-trap simulation matches a desired lattice gauge theory. Second, they minimize the errors that occur during the simulation.

In the paper, the researchers describe how this approach might allow a one-dimensional string of ions to simulate a few simple lattice gauge theories, not only in one dimension but also higher dimensions. With this approach, the behavior of ion spins can be tailored and mapped to a variety of phenomena that can be described by lattice gauge theories, such as the generation of matter and antimatter out of a vacuum.

“As a nuclear theorist, I am excited to work further with theorists and experimentalists with expertise in atomic, molecular, and optical physics and in ion-trap technology to solve more complex problems,” says Davoudi. “I explained the uniqueness of my problem and my system, and they explained the features and capabilities of their system, then we brainstormed ideas on how we can do this mapping.”

Monroe points out that “this is exactly what is needed for the future of quantum computing. This ‘co-design’ of devices tailored for specific applications is what makes the field fresh and exciting.”

Analog vs. Digital

The simulations proposed by Davoudi and her colleagues are examples of analog simulations, since they directly represent elements and interactions in one system with those of another system. Generally, analog simulators must be designed for a particular problem or set of problems. This makes them less versatile than digital simulators, which have an established set of discrete building blocks that can be put together to simulate nearly anything given enough time and resources.

The versatility of digital simulations has been world-altering, but a well-designed analog system is often less complex than its digital counterpart. Carefully designed quantum analog simulations might deliver results for certain problems before quantum computers can reliably perform digital simulations. This is similar to just using a wind tunnel instead of programming a computer to model the way the wind buffets everything from a goose to an experimental fighter plane.

Monroe’s team, in collaboration with coauthor Guido Pagano, a former JQI postdoctoral researcher who is now an assistant professor at Rice University, is working to implement the new analog approach within the next couple of years. The completed system should be able to simulate a variety of lattice gauge theories.

The authors say that this research is only the beginning of a longer road. Since lattice gauge theories are described in mathematically similar ways to other quantum systems, the researchers are optimistic that their proposal will find uses beyond nuclear physics, such as in condensed matter physics and materials science. Davoudi is also working to develop digital quantum simulation proposals with Monroe and Norbert Linke, another JQI Fellow. She hopes that the two projects will reveal the advantages and disadvantages of each approach and provide insight into how researchers can tackle nuclear physics problems with the full might of quantum computing.

“We want to eventually simulate theories of a more complex nature and in particular quantum chromodynamics that is responsible for the strong force in nature,” says Davoudi. “But that might require thinking even more outside the box.”

Original story by Bailey Bedford

In addition to Davoudi, Hafezi and Monroe, co-authors of the paper include former JQI postdoctoral researcher and current assistant professor at Rice University Guido Pagano; JQI graduate student Alireza Seif, and UMD Physics graduate student Andrew Shaw.

Research Contact: Zohreh DavoudiThis email address is being protected from spambots. You need JavaScript enabled to view it.
Media Contact: Bailey Bedford This email address is being protected from spambots. You need JavaScript enabled to view it.