Lifeboat Foundation

(Phys.org)—Inspired by natural selection and the concept of “survival of the fittest,” genetic algorithms are flexible optimization techniques that can find the best solution to a problem by repeatedly selecting for and breeding ever “fitter” generations of solutions.

Now for the first time, researchers Urtzi Las Heras et al. at the University of the Basque Country in Bilbao, Spain, have applied genetic algorithms to digital quantum simulations and shown that genetic algorithms can reduce quantum errors, and may even outperform existing optimization techniques. The research, which is published in a recent issue of Physical Review Letters, was led by Ikerbasque Prof. Enrique Solano and Dr. Mikel Sanz in the QUTIS group.

In general, quantum simulations can provide a clearer picture of the dynamics of systems that are impossible to understand using conventional computers due to their high degree of complexity. Whereas computers calculate the behavior of these systems, quantum simulations approximate or “simulate” the behavior.

Continue reading “Genetic algorithms can improve quantum simulations” »

Forget pitching a tent when camping; soon (at this rate) we can have the 3D Printer print us a cabin.

A tiny house was built using Vesta, the 3D concrete printer. It took 24 hours to build the structure. The developer aims to shorten the construction time with the third version of the device.

Vesta, the 3D concrete printer, was just used to print a house. Though the word “house” may be a little suspect. Admittedly, given its size, the structure is more of a tool shed than a home, but one could theoretically live inside of it.

Continue reading “A Tiny House Was Built in 24 Hours, Thanks to A 3D Concrete Printer” »

Cool beans.

The technique would help address problems that classical computers can’t handle.

Excellent story and highlights how Quantum computers may provide a way to overcome the obstacles around particle physics because QC can simulate certain aspects of elementary particle physics in a well-controlled quantum system.

Physicists in Innsbruck have realized the first quantum simulation of lattice gauge theories, building a bridge between high-energy theory and atomic physics. In the journal Nature, Rainer Blatt’s and Peter Zoller’s research teams describe how they simulated the creation of elementary particle pairs out of the vacuum by using a quantum computer.

Entanglement purification, a vital enabler for practical quantum networks, has been shown to be feasible with secluded nuclear memories in diamond.

Quantum devices can team up to perform a task collectively, but only if they share that most “spooky” of all quantum phenomena: entanglement. Remote devices have been successfully entangled in order to investigate entanglement itself [1], but the entanglement’s quality is too low for practical applications. The solution, known as entanglement purification [2], has seemed daunting to implement in a real device. Now new research [3] shows that even quite simple quantum components—nanostructures in diamond—have the potential to store and upgrade entanglement. The result relies on hiding information in almost-inaccessible nuclear memories, and may be a key step toward the era of practical quantum networks.

The concept of an interlinked network is absolutely fundamental to conventional technologies. It applies not only to distributed systems like the internet, but also to individual devices like laptops, which contain a hierarchy of interlinked components. For quantum technologies to fulfill their potential, we will want them to have the flexibility and scalability that come from embracing the network paradigm.

Northwestern University’s Ken Forbus is closing the gap between humans and machines.

Using cognitive science theories, Forbus and his collaborators have developed a model that could give computers the ability to reason more like humans and even make moral decisions. Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve moral dilemmas.

“In terms of thinking like humans, analogies are where it’s at,” said Forbus, Walter P. Murphy Professor of Electrical Engineering and Computer Science in Northwestern’s McCormick School of Engineering. “Humans use relational statements fluidly to describe things, solve problems, indicate causality, and weigh moral dilemmas.”

Continue reading “Structure-mapping engine enables computers to reason and learn like humans, including solving moral dilemmas” »

Robert Dunleavy had just started his sophomore year at Lehigh University when he decided he wanted to take part in a research project. He sent an email to Bryan Berger, an assistant professor of chemical and biomolecular engineering, who invited Dunleavy to his lab.

Berger and his colleagues were conducting experiments on tiny semiconductor particles called quantum dots. The optical and electronic properties of QDs make them useful in lasers, light-emitting diodes (LEDs), medical imaging, solar cells, and other applications.

Dunleavy joined Berger’s group and began working with cadmium sulfide (CdS), one of the compounds from which QDs are fabricated. The group’s goal was to find a better way of producing CdS quantum dots, which are currently made with toxic chemicals in an expensive process that requires high pressure and temperature.

Continue reading “Using Enzymes to Enhance LEDs” »

Whether referred to as AI, machine learning, or cognitive systems, such as IBM Watson, a growing cadre of business leaders is embracing this opportunity head on.

That’s because their consumers are using cognitive applications on a daily basis — through their phones, in their cars, with their doctors, banks, schools, and more. All of this consumer engagement is creating 2.5 quintillion bytes of data every day. And thanks to IT infrastructures designed for cognitive workloads — that can understand, reason, and learn from all this data — organizations and entire industries are transforming and reaping the benefits.

What’s important to remember is that this sci-fi-turned-reality-show of cognitive computing cannot happen without the underlying systems on which the APIs, software, and services run. For this very reason, today’s leading CIOs are thinking differently about their IT infrastructure.

Continue reading “Voice: How To Architect A Cognitive Future For Business” »

Nice.

Richard Feynman suggested that it takes a quantum computer to simulate large quantum systems, but a new study shows that a classical computer can work when the system has loss and noise.

The field of quantum computing originated with a question posed by Richard Feynman. He asked whether or not it was feasible to simulate the behavior of quantum systems using a classical computer, suggesting that a quantum computer would be required instead [1]. Saleh Rahimi-Keshari from the University of Queensland, Australia, and colleagues [2] have now demonstrated that a quantum process that was believed to require an exponentially large number of steps to simulate on a classical computer could in fact be simulated in an efficient way if the system in which the process occurs has sufficiently large loss and noise.

Continue reading “Viewpoint: Classical Simulation of Quantum Systems?” »