RSS icon
Twitter icon
Facebook icon
Vimeo icon
YouTube icon

An ultracold landscape for atomtronics

Artistic impression of a spinning, ring-shaped BEC. The vortex “motion” was created to visualize the motion of the condensate when stirred. The reflections here depict the hysteresis in this atomtronic system- where there are bistable states with opposite rotations (image credit: E. Edwards/JQI). See more on this research at

Atomtronics is an emerging technology whereby physicists use ensembles of atoms to build analogs to electronic circuit elements. Modern electronics relies on utilizing the charge properties of the electron. Using lasers and magnetic fields, atomic systems can be engineered to have behavior analogous to that of electrons, making them an exciting platform for studying and generating alternatives to charge-based electronics. 

Read more to learn more about recent atomtronics research 

Initially inspired by atoms trapped in optical lattices of light, wherein the atoms play the role of electrons and the light plays the role of a solid state lattice, other atom-laser systems based on designer optical traps have emerged as leaders in atomtronics. For example, as described in today's issue of Nature, JQI physicists, led by Gretchen Campbell, have demonstrated a tool that is critical to electronics: hysteresis. This is the first time that hysteresis has been observed in an ultracold atomic gas. The cover of this issue features an artistic impression of the superfluid ring system.

Other recent JQI atomtronic work includes atomic analogs of both a transistor and an RF SQuID (Superconducting Quantum Interference Device). SQuIDs work because of a fundamental property of superconductors: When exposed to an applied magnetic field, a ring of superconductor generates currents which produce magnetic flux exactly canceling the external field. When the current reaches a critical value (determined by a junction or weak link in the ring), it “jumps” by a discrete amount, allowing a quantized amount of flux to penetrate the ring. Measuring the effect of that action on the current across a junction allows one to measure the strength of the applied field, and SQUIDs are routinely employed to detect very weak fields such as those produced by brain waves or nerve impulses in muscle tissue. Read about how an atomtronic SQuID can be used as a rotation sensor.


Recent Quantum Bits

October 17, 2016

Check out the second half of our feature story on Weyl semimetals and Weyl fermions, new materials and particles that have become a major focus for condensed matter researchers around the world. Part two looks at some of the theoretical work going on at JQI and CMTC. If you missed part one, it's not too late to catch up on the series. And if you missed our roundup of the research that led to last week's Nobel Prize in Physicsresearch that is closely related to Weyl materialswe encourage you to take a look.

JQI is also happy to congratulate Karina Jiménez-García on receiving a 2016 L'Oréal-UNESCO For Women in Science fellowship. "This is a recognition that I owe to all those that have guided and inspired me and those who have supported me throughout my professional career, especially my family," Jiménez-García said. We wrote a short story on how she plans to use the fellowship funds. It links to stories about the research she worked on while visiting JQI.

October 6, 2016

This year's Nobel Prize in Physics was awarded to three researchers who helped bring topology into physics. It's an innovation that has propelled condensed matter physics for the past three decades, leading recently to the discovery of several exotic materials.

We put together a roundup ( of the research that led to the prize and offered our take on topology. (Yes, we resorted to pastries.)

This year's prize is timely, too, as today we published part one ( of a two-part series on Weyl semimetals, topological materials with a long history. That history is due, in part, to this year's laureates: David Thouless, Duncan Haldane and Michael Kosterlitz.

Part one focuses on the history and basic physics of Weyl materials. Part two, which will appear next week, focuses on some of the research being explored by physicists at JQI and the Condensed Matter Theory Center at the University of Maryland.

September 15, 2016

From self-driving cars and IBM’s Watson to chess engines and AlphaGo, there is no shortage of news about machine learning, the field of artificial intelligence that studies how to make computers that can learn. Recently, parallel to these advances, scientists have started to ask how quantum devices and techniques might aid machine learning in the future.

To date, much research in the emerging field of quantum machine learning has attacked choke points in ordinary machine learning tasks, focusing, for example, on how to use quantum computers to speed up image recognition. But Vedran Dunjko and Hans Briegel at the University of Innsbruck, along with JQI Fellow Jake Taylor, have taken a broader view. Rather than focusing on speeding up subroutines for specific tasks, the researchers have introduced an approach to quantum machine learning that unifies much of the prior work and extends it to problems that received little attention before. They also showed how to increase learning performance for a large group of problems. The research has been accepted for publication in Physical Review Letters.

Quantum-enhanced machine learning. V. Dunjko, J. M. Taylor and H. J. Briegel, Physical Review Letters, to appear. arXiv:

Subscribe to A Quantum Bit 

Quantum physics began with revolutionary discoveries in the early twentieth century and continues to be central in today’s physics research. Learn about quantum physics, bit by bit. From definitions to the latest research, this is your portal. Subscribe to receive regular emails from the quantum world. Previous Issues...

Sign Up Now

Sign up to receive A Quantum Bit in your email!

 Have an idea for A Quantum Bit? Submit your suggestions to