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Quantum dots: Nanocrystals packed with potential

Caption: Artistic rendition of a spherical quantum dot (fluorescing ensemble of spheres) embedded in a semiconductor surface (blue, green, and yellow spheres). Credit S. Kelley/JQI

Quantum dots (QD) can be made from tiny crystals of semiconductor material, around 10 nanometers in size. The electron-hole pairs in this structure are confined, resulting in a quantization of energy levels analogous to those of an atom – hence quantum dots are often dubbed ‘artificial atoms.’  Like an atom, a QD’s energy levels can be manipulated using lasers and magnetic fields. The fluorescing wavelengths can be tuned by altering the crystal size. Semiconductor quantum dots are attractive for quantum information processing because the technology for integration with modern electronics already exists. 

Read more to learn more about these artificial atoms

Fluorescence occurs when an excited electron relaxes back to the ground state, and the color of the emitted light is a function of how far in energy the electron travels. In this type of quantum dot, the spacing between the conduction and valence band is inversely related to the size if the crystal. The smaller the dot, the more energy is needed to create excitations, and accordingly higher energy (bluer) light is emitted. During manufacturing, quantum dots can be tuned to fluoresce at specific wavelengths of light. Unlike atoms, where you would need to swap in a new element to achieve a different spectrum of emitted light, quantum dots of a particular material can emit a wide range of colors simply by adjusting the size. Their fluorescence range neatly corresponds with the visible spectrum, and thus there is also interest in manufacturing light-emitting diodes from quantum dots. 

In 1997, Daniel Loss and David P. DiVincenzo proposed a quantum dot-based spin-qubit quantum computer. Single electron spins can be isolated inside a fabricated quantum dot architecture. Here, the quantum dots are fabricated between layers of semiconductor. At low temperatures, the electrons in this system move in a flatland, constrained to just two dimensions. The quantum dot provides further confinement, localizing these electrons in space. Scientists can apply electric fields to the quantum dot leads, allowing a single electron to leave the two-dimensional gas and effectively become trapped in a well. Here the electron spin functions as a qubit. However, the coherence time is limited in the single dot case because the quantum system is disturbed by the surrounding bath of semiconductor nuclei. This has lead to research in double and triple quantum dot structures, wherein the decoherence processes can be circumvented.

Recent JQI work includes a theoretical proposal for a double quantum dot qubit that contains up to six electrons, rather than the usual one or two. Another research group has proposed what is known as the resonant exchange qubit in a double quantum dot. In yet another avenue of research, JQI experimentalists embed quantum dots in photonic crystals and perform quantum logic operations.

Quantum dots also have uses in bio-medical research. Their small size means they can pass unimpeded through the body, and their tunable florescence can be employed as a biomarker for medical imaging. 

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:

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