CAPTION By evaporating indium gallium arsenide onto a gallium arsenide substrate TUM physicists created nanometer-scale hills, so-called quantum dots. An electron trapped in one of these quantum dots can be used to store information. Hitherto unknown memory loss mechanisms could be switched off by applying a magnetic field. CREDIT Fabian Flassig

Magnetic field helps qubit electrons store information longer

Physicists at the Technical University of Munich, the Los Alamos National Laboratory and Stanford University (USA) have tracked down semiconductor nanostructure mechanisms that can result in the loss of stored information - and halted the amnesia using an external magnetic field. The new nanostructures comprise common semiconductor materials compatible with standard manufacturing processes.

Quantum bits, qubits for short, are the basic logical elements of quantum information processing (QIP) that may represent the future of computer technology. Since they process problems in a quantum-mechanical manner, such quantum supercomputers might one day solve complex problems much more quickly than currently possible, so the hope of researchers.

In principle, there are various possibilities of implementing qubits: photons are an option equally as viable as confined ions or atoms whose states can be altered in a targeted manner using lasers. The key questions regarding their potential use as memory units are how long information can be stored in the system and which mechanisms might lead to a loss of information.

A team of physicists headed by Alexander Bechtold and Professor Jonathan Finley at the Walter Schottky Institute of the Technical University of Munich and the Cluster of Excellence Nanosystems Initiative Munich (NIM) have now presented a system comprising a single electron trapped in a semiconductor nanostructure. Here, the electron's spin serves as the information carrier.

The researchers were able to precisely demonstrate the existence of different data loss mechanisms and also showed that stored information can nonetheless be retained using an external magnetic field.

Electrons trapped in a quantum dot

The TUM physicists evaporated indium gallium arsenide onto a gallium arsenide substrate to form their nanostructure. As a result of the different lattice spacing of the two semiconductor materials strain is produced at the interface between the crystal grids. The system thus forms nanometer-scale "hills" - so-called quantum dots.

When the quantum dots are cooled down to liquid helium temperatures and optically excited, a singe electron can be trapped in each of the quantum dots. The spin states of the electrons can then be used as information stores. Laser pulses can read and alter the states optically from outside. This makes the system ideal as a building block for future quantum computers.

Spin up or spin down correspond to the standard logical information units 0 and 1. But, on top of this come additional intermediate states of quantum mechanical up and down superpositions.

Hitherto unknown memory loss mechanisms

However, there is one problem: "We found out that the strain in the semiconductor material leads to a new and until recently unknown mechanism that results in the loss of quantum information," says Alexander Bechtold. The strain creates tiny electric fields in the semiconductor that influence the nuclear spin orientation of the atomic nuclei.

"It's a kind of piezoelectric effect," says Bechthold. "It results in uncontrolled fluctuations in the nuclear spins." These can, in turn, modify the spin of the electrons, i.e. the stored information. The information is lost within a few hundred nanoseconds.

In addition, Alexander Bechthold's team was able to provide concrete evidence for further information loss mechanisms, for example that electron spins are generally influenced by the spins of the surrounding 100,000 atomic nuclei.

Preventing quantum mechanical amnesia

"However, both loss channels can be switched off when a magnetic field of around 1.5 tesla is applied," says Bechtold. "This corresponds to the magnetic field strength of a strong permanent magnet. It stabilizes the nuclear spins and the encoded information remains intact."

"Overall, the system is extremely promising," according to Jonathan Finley, head of the research group. "The semiconductor quantum dots have the advantage that they harmonize perfectly with existing computer technology since they are made of similar semiconductor material." They could even be equipped with electrical contacts, allowing them to be controlled not only optically using a laser, but also using voltage pulses.

One day powerful quantum supercomputers could be made from molecules like these -- vanadium complexes.

If quantum supercomputers existed, they would revolutionize computing as we know it. Based on fundamental properties of matter, the potential power of these theoretical workhorses would solve problems in a new way, cracking extremely complex spy codes and precisely modeling chemical systems in a snap. This week in ACS Central Science, researchers create cleverly designed molecules to get one step closer to this goal.

Traditional computers rely on transistors that occupy one of two states -- that's what those archetypal zeroes and ones refer to, and each digit is a "bit." Quantum computing would use three states, improving its information storage capacity exponentially. Whereas a small app like "Angry Birds" takes up about 40,000 standard bits, a supercomputer made with just 1,000 quantum bits, or "qubits," could easily and quickly break modern encryption schemes or more precisely model how a pharmaceutical drug candidate would perform in a person. The biggest challenge of quantum supercomputing, however, is making the qubit. Some of the most promising qubits today use electrons, specifically their "spin" state. Spin can have two states, just like a bit, but also a combination of both to form a third state, called "superposition." But very few molecules stay in the superposition state long enough to measure, which makes them difficult to use in computing. One reason is that the interaction of spins on most nuclei can interfere with the electronic ones. To get closer to a real, functional qubit, Danna Freedman and colleagues turned to metal complexes, where most of those problematic nuclear spins were eliminated.

Freedman and colleagues synthesized vanadium complexes with arms made of carbon and sulfur. As long as the system was kept cold, these molecules kept superposition longer than any metal complexes previously reported. They also kept that state for just as long as other bulk materials currently under consideration. These new molecules show that under the right conditions, inorganic complexes can function as viable qubits. In addition, the complexes may prove to be superior to other potential materials because their defined chemical structure could more easily allow the organized design of functional devices. To get a little meta: it's possible that one-day supercomputers made of just a handful of small molecules will be used to make predictions about other molecules.

The paper is be freely available at this link:

The artist's portrayal is an illustration of a nanomagnetic coprocessor solving complex optimization problems and highlights the shape-engineered nanomagnet's two unique energy minimum states -- vortex and single domain. Credit: Illustration by Ryan Wakefield

University of South Florida engineering researchers find nano-scale magnets could supercompute complex functions significantly faster than conventional computer.

Researchers from the University of South Florida College of Engineering have proposed a new form of computing that uses circular nanomagnets to solve quadratic optimization problems orders of magnitude faster than that of a conventional computer. 

A wide range of application domains can be potentially accelerated through this research such as finding patterns in social media, error-correcting codes to Big Data and biosciences. 

In an article published in the current issue of Nature Nanotechnology, "Non Boolean computing with nanomagnets for computer vision applications," authors Sanjukta Bhanja, D.K. Karunaratne, Ravi Panchumarthy, Srinath Rajaram, and Sudeep Sarkar discuss how their work harnessed the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. 

According to the authors, magnets have been used as computer memory/data storage since as early as 1920; they even made an entry into common hardware terminology like multi-"core." The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms.

By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, the research team has created a modeling framework to address the vortex and in-plane single domain in a unified framework and developed a magnetic Hamiltonian which is quadratic in nature. The implemented magnetic system can identify the salient features of a given image with more than 85 percent true positive rate. This form of computing, on average, is 1,528 times faster than IBM ILOG CPLEX (an industry standard software optimizer) with sparse affinity matrices (four neighbor), and 468 times faster with denser (eight neighbor) affinity matrices. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.

The charge density of an electron (in blue) changes its form due to the interaction with photons (in red). © J.M. Harms/MPSD

SuperComputer simulations that predict the light-induced change in the physical and chemical properties of complex systems, molecules, nanostructures and solids usually ignore the quantum nature of light. Scientists of the Max-Planck Institute for the Structure and Dynamics of Matter at CFEL in Hamburg have now shown how the effects of the photons can be properly included in such calculations. This study opens up the possibility to predict and control the change of material properties due to the interaction with light particles from first principles. The study is reported yesterday in the journal Proceedings of the National Academy of Sciences.

The basic building blocks of atoms, molecules and solids are positively charged nuclei and negatively charged electrons. Their mutual interactions determine most physical and chemical properties of matter, such as the electrical conductivity or the absorption of light. The laws that guide this delicate interplay between electrons and nuclei are those of quantum electrodynamics (QED), in which particles interact via the exchange of photons, which are the quanta of light. However, the equations of QED are so complex that in practice scientists have to simplify them to be able to make any prediction for real materials. A very common simplification in quantum chemistry and solid-state physics is to neglect the quantum nature of light. Although this assumption works well for many applications, recent experiments have uncovered situations where the quantum nature of the photons can dramatically change the material properties and give rise to new collective behavior and phenomena.

 The standard simulation techniques usually neglect the photons. In order to simulate such situations on a supercomputer, the theory department of the MPSD, headed by Prof. Angel Rubio, has thus developed a novel theoretical method that also includes the interaction with photons. The basic idea is to treat the full QED system of particles and photons as a quantum fluid. Here the particles are represented by a charge current, and the photons by a classical electromagnetic field that acts on the current in a very complex manner. In their current work, the researchers have shown how this approach can exactly describe the dynamics of an electron that is trapped on a surface and that strongly interacts with photons. “The advantage of this reformulation of the coupled electron-photon problem is that it allows for approximations that treat photons and particles on equal footing.,” says Johannes Flick,  one of the lead authors of the work, “In this way we can come up with new simulation techniques that do not neglect the photons while still being simple enough to be practical," adds Michael Ruggenthaler, second lead author of the article. In a next step after this proof-of-principle, Rubio’s team wants to use the developed technique to investigate complex systems in situations where photons are assumed to play an important role and hence learn how this modifies the properties of materials. This could provide a new way to control and alter chemical reactions in complex systems such as biomolecules and to design new states of matter.

Oracle today introduced an all-new family of SPARC systems built on the revolutionary 32-core, 256-thread SPARC M7 microprocessor. The systems feature Security in Silicon for advanced intrusion protection and encryption; SQL in Silicon that delivers unparalleled database efficiency; and world record performance spanning enterprise, big data, and cloud applications.

The new SPARC M7 processor-based systems, including the Oracle SuperCluster M7 supercomputer system and SPARC T7 and M7 servers, are designed to seamlessly integrate with existing infrastructure and include fully integrated virtualization and management for cloud. All existing commercial and custom applications will run on SPARC M7 systems unchanged with significant improvements in security, efficiency, and performance. In addition, SPARC M7 is an open platform that developers can utilize to create new software that takes advantage of Security in Silicon and SQL in Silicon capabilities.

Secure cloud infrastructure with the industry’s most advanced security, extreme performance, and a complete suite of efficiency enhancements, tools, and automation that work together to dramatically lower cost and complexity.

Oracle’s new SPARC M7 systems feature:

Security in Silicon, with two key new enhancements in systems design.

Silicon Secured Memory – For the first time, Silicon Secured Memory adds real-time checking of access to data in memory to help protect against malicious intrusion and flawed program code in production for greater security and reliability. Silicon Secured Memory protection is utilized by Oracle Database 12c by default and is simple and easy to turn on for existing applications. Oracle is also making application programming interfaces available for advanced customization.

Hardware-Assisted Encryption – New breakthrough performance with hardware-assisted encryption built into all 32 cores enables uncompromised use without performance penalty. This gives customers the ability to have secure runtime and data for all applications even when combined with wide key usage of AES, DES, SHA, and more. Existing applications that use encryption will be automatically accelerated by this new capability including Oracle, third party, and custom applications.

SQL in Silicon: Adds co-processors to all 32 cores of the SPARC M7 that offload and accelerate important data functions, dramatically improving efficiency and performance of database applications. Critical functions accelerated by these new co-processors include memory de-compression, memory scan, range scan, filtering, and join assist. Offloading these functions to co-processors greatly increases the efficiency of each CPU core, lowers memory utilization, and enables up to 10x better database query performance. Oracle Database 12c In-Memory option fully supports this new capability in the current release. In addition, this new functionality is slated to be available to advanced developers to build the next generation of big data analytics platforms.

World Record Performance: Powered by the world’s fastest microprocessor, Oracle’s new SPARC M7-based systems deliver proven performance superiority with world record results in over 20 benchmarks. In addition to superior performance for database, middleware, Java, and enterprise applications from Oracle and third party ISV’s, the new SPARC M7-based systems achieve incredible performance compared to the competition for big data and cloud workloads. 

“Until now, no computing platform has been able to tackle security without significantly impacting application performance and efficiency,” said John Fowler, executive vice president, Systems, Oracle. “Today Oracle is delivering breakthrough technology for memory intrusion protection and encryption, while accelerating in-memory analytics, databases and Java. Oracle’s SPARC T7 and M7 systems and Oracle SuperCluster M7 are starting a new era in delivering secure computing while increasing efficiency.”

Balanced Design Principles: The new SPARC M7 processor is the design center of the new line of SPARC M7 systems that scale from 32 to 512 cores, 256 to 4,096 threads and up to 8 TB of memory. Oracle’s SPARC M7 chip is a 4.1 GHz 32-core/256-thread processor that addresses the most demanding workloads with a balanced high performance design across all factors of memory, IO, and scalability. In addition, Oracle has improved every other aspect of the design compared to previous generation designs resulting in increased single-thread performance and reduced latency.

Technology That Delivers: Oracle’s new SPARC M7 systems deliver outstanding security and performance as demonstrated by a new world record result for the SPECjEnterprise2010 benchmark for database and Java. Oracle has run this benchmark fully encrypted to demonstrate the levels of security, efficiency, and performance that SPARC M7 delivers. Two SPARC T7-1 servers, fully encrypted, are faster than the second best result from a pair of four-processor IBM Power8 systems, running the same workload unencrypted. Oracle’s SPARC M7 TeraSort benchmark results prove superiority over IBM for running Hadoop, while also utilizing SPARC M7 encryption acceleration with negligible performance impact. One SPARC T7-4 with 128 cores using an AES-256-GCM encrypted file system is 3.8x faster than an unsecure 8-node IBM S822L Power8 cluster with 192 cores. Customers can now run workloads fully encrypted with greater efficiency and without performance penalty.

Available Now: New SuperCluster M7 and SPARC M7-based servers are available now for ordering and delivery.

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