Furthermore, they say the algorithm could be used to calculate complex measurements such as radar cross sections, an ability integral to the development of radar stealth technology, among many other applications. Their research is reported in the June 18 issue of Physical Review Letters.
The field of quantum computing is still relatively young. First proposed in the 1980s, a quantum computer harnesses the principles of quantum mechanics (the physics of very small things like electrons and photons) to process information significantly faster than traditional computers. A classical computer has a memory made up of bits (units of information), where each bit represents either a one or a zero. A quantum computer maintains a sequence of qubits. Similar to a bit, a single qubit can represent a one or a zero, but it can also represent any quantum superposition of these two states, meaning it can be both a one and a zero simultaneously.
While several few-qubit systems have been built, a full-scale quantum computer is still years away. Qubits are difficult to manipulate, since any disturbance causes them to fall out of their quantum state or “decohere,” and their behavior can no longer be explained by quantum mechanics. Other larger scale non-universal computers have been built — including the much-heralded D-Wave computer, purchased by NASA and Google last month — but none of them currently have the power to replace classical computers.
Theoretical breakthroughs in quantum algorithm design are few and far between. In 1994 Peter Shor introduced a method for finding the prime factors of large numbers — a capability that would render modern cryptography vulnerable. Fifteen years later, MIT researchers presented the Quantum Linear Systems Algorithm (QLSA), that promised to bring the same type of efficiency to systems of linear equations — whose solution is crucial to image processing, video processing, signal processing, robot control, weather modeling, genetic analysis and population analysis, to name just a few applications.
“But it didn’t quite deliver; based on their process, no one could figure out how to get a useful answer out of the computer,” explains APL’s David Clader, who along with Bryan Jacobs, and Chad Sprouse wrote, “Preconditioned Quantum Linear System Algorithm.”
As presented, the algorithm had three features that made it difﬁcult to apply to generic problem speciﬁcations and achieve the promised exponential speedup, they wrote. Technical details with setting up the problem on a quantum computer made it unclear how one would apply it to a real-world calculation. In addition, the promise of exponential speedup was only true for a very restricted set of linear systems that typically don’t exist in real-world problems. Finally, getting a useful answer from the calculation proved to be quite difficult due to intricacies with the inherently probabilistic nature of quantum measurement.
In their paper, the authors describe how they were able to solve each of these issues and extract useful information from the solution. Furthermore, they demonstrated the applicability of the algorithm by showing how to encode the problem of calculating the electromagnetic scattering cross-section, also known as radar cross section (RCS).
RCS measurements have become increasingly important to the military. It refers to the power that would be returned by an object when illuminated with radar. The power indicates how well the radar can detect or track that target, so there are ongoing efforts to reduce the RCS of such objects as missiles, ships, tanks and aircraft. With a quantum computer, APL researchers have now shown that these calculations can be done much faster and model much more complex objects than would be possible using even on the most powerful classical supercomputers.
The work was funded by the Intelligence Advanced Research Projects Activity under its Quantum Computer Science program, which explores questions relating to the computational resources required to run quantum algorithms on realistic quantum computers.
The Applied Physics Laboratory, a not-for-profit division of The Johns Hopkins University, meets critical national challenges through the innovative application of science and technology. For more information, visit www.jhuapl.edu.
Paulette Campbell | Newswise
Artificial Intelligence Helps in the Discovery of New Materials
21.09.2016 | Universität Basel
Magnetic polaron imaged for the first time
19.09.2016 | Aalto University
The Fraunhofer Institute for Organic Electronics, Electron Beam and Plasma Technology FEP has been developing various applications for OLED microdisplays based on organic semiconductors. By integrating the capabilities of an image sensor directly into the microdisplay, eye movements can be recorded by the smart glasses and utilized for guidance and control functions, as one example. The new design will be debuted at Augmented World Expo Europe (AWE) in Berlin at Booth B25, October 18th – 19th.
“Augmented-reality” and “wearables” have become terms we encounter almost daily. Both can make daily life a little simpler and provide valuable assistance for...
With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. They report on their findings in the scientific journal Physical Review Letters.
Elpasolite is a glassy, transparent, shiny and soft mineral with a cubic crystal structure. First discovered in El Paso County (Colorado, USA), it can also be...
For the first time, Fraunhofer IKTS shows additively manufactured hardmetal tools at WorldPM 2016 in Hamburg. Mechanical, chemical as well as a high heat resistance and extreme hardness are required from tools that are used in mechanical and automotive engineering or in plastics and building materials industry. Researchers at the Fraunhofer Institute for Ceramic Technologies and Systems IKTS in Dresden managed the production of complex hardmetal tools via 3D printing in a quality that are in no way inferior to conventionally produced high-performance tools.
Fraunhofer IKTS counts decades of proven expertise in the development of hardmetals. To date, reliable cutting, drilling, pressing and stamping tools made of...
At AKL’16, the International Laser Technology Congress held in May this year, interest in the topic of process control was greater than expected. Appropriately, the event was also used to launch the Industry Working Group for Process Control in Laser Material Processing. The group provides a forum for representatives from industry and research to initiate pre-competitive projects and discuss issues such as standards, potential cost savings and feasibility.
In the age of industry 4.0, laser technology is firmly established within manufacturing. A wide variety of laser techniques – from USP ablation and additive...
Every three years, the plastics industry gathers at K, the international trade fair for plastics and rubber in Düsseldorf. The Fraunhofer Institute for Laser Technology ILT will also be attending again and presenting many innovative technologies, such as for joining plastics and metals using ultrashort pulse lasers. From October 19 to 26, you can find the Fraunhofer ILT at the joint Fraunhofer booth SC01 in Hall 7.
K is the world’s largest trade fair for the plastics and rubber industry. As in previous years, the organizers are expecting 3,000 exhibitors and more than...
23.09.2016 | Event News
20.09.2016 | Event News
16.09.2016 | Event News
26.09.2016 | Health and Medicine
26.09.2016 | Power and Electrical Engineering
23.09.2016 | Life Sciences