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Category: computing – Page 868

A University of Oklahoma-led team of physicists believes chip-based atomic physics holds promise to make the second quantum revolution—the engineering of quantum matter with arbitrary precision—a reality. With recent technological advances in fabrication and trapping, hybrid quantum systems are emerging as ideal platforms for a diverse range of studies in quantum control, quantum simulation and computing.

James P. Shaffer, professor in the Homer L. Dodge Department of Physics and Astronomy, OU College of Arts and Sciences; Jon Sedlacek, OU graduate student; and a team from the University of Nevada, Western Washington University, The United States Naval Academy, Sandia National Laboratories and Harvard-Smithsonian Center for Astrophysics, have published research important for integrating Rydberg atoms into hybrid quantum systems and the fundamental study of atom– interactions, as well as applications for electrons bound to a 2D surface.

“A convenient surface for application in hybrid quantum systems is quartz because of its extensive use in the semiconductor and optics industries,” Sedlacek said. “The surface has been the subject of recent interest as a result of it stability and low surface energy. Mitigating electric fields near ‘trapping’ surfaces is the holy grail for realizing hybrid ,” added Hossein Sadeghpour, director of the Institute for Theoretical Atomic Molecular and Optical Physics, Harvard-Smithsonian Center for Astrophysics.

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(Phys.org)—One promising approach for scalable quantum computing is to use an all-optical architecture, in which the qubits are represented by photons and manipulated by mirrors and beam splitters. So far, researchers have demonstrated this method, called Linear Optical Quantum Computing, on a very small scale by performing operations using just a few photons. In an attempt to scale up this method to larger numbers of photons, researchers in a new study have developed a way to fully integrate single-photon sources inside optical circuits, creating integrated quantum circuits that may allow for scalable optical quantum computation.

The researchers, Iman Esmaeil Zadeh, Ali W. Elshaari, and coauthors, have published a paper on the integrated quantum circuits in a recent issue of Nano Letters.

As the researchers explain, one of the biggest challenges facing the realization of an efficient Linear Optical Quantum Computing system is integrating several components that are usually incompatible with each other onto a single platform. These components include a single-photon source such as quantum dots; routing devices such as waveguides; devices for manipulating such as cavities, filters, and quantum gates; and single-photon detectors.

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Synthetic biology involves creating or re-engineering microbes or other organisms to perform specific tasks, like fighting obesity, monitoring chemical threats or creating biofuels. Essentially, biologists program single-celled organisms like bacteria and yeast much the same way one would program and control a robot.

But 10 years ago, it was extremely challenging to take a DNA sequence designed on a computer and turn it into a polymer that could implement its task in a specific host, say a mouse or human cell. Now, thanks to a multitude of innovations across computing, engineering, biology and other fields, researchers can type out any DNA sequence they want, email it to a synthesis company, and receive their completed DNA construct in a week. You can build entire chromosomes and entire genomes of bacteria in this way.

“Biology is the most powerful substrate for engineering that we know of,” said Christopher Voigt, Professor of Biological Engineering at MIT. “It’s more powerful than electrical engineering, mechanical engineering, materials science and others. Unlike all the other fields, we can look at what biology is already able to do. When we look at the natural world, we see things like the brain. That’s a complex place computing, electrical engineering and computer science can’t reach. The brain even constructs nanostructures very deliberately, something materials science has not accomplished.”

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To solve some of the world’s toughest computing problems, Lawrence Livermore National Laboratory is getting a boost from the human brain.

The U.S. government lab will begin testing on Thursday a $1 million computer, the first of its kind, packed with 16 microprocessors that are designed to mimic the way the brain works.

The chip called TrueNorth, introduced by International Business Machines Corp. in 2014, is radically…

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