Lifeboat Foundation

A world first. New footage from Mars rendered in stunning 4K resolution.

Although the cameras are high quality, the rate at which the rovers can send data back to earth is the biggest challenge. Curiosity can only send data directly back to earth at 32 kilo-bits per second.

Instead, when the rover can connect to the Mars Reconnaissance Orbiter, we get more favourable speeds of 2 Megabytes per second.

Continue reading “WATCH: MARS in 4K!!” »

Yale physicists have developed an error-correcting cat—a new device that combines the Schrödinger’s cat concept of superposition (a physical system existing in two states at once) with the ability to fix some of the trickiest errors in a quantum computation.

It is Yale’s latest breakthrough in the effort to master and manipulate the physics necessary for a useful quantum computer: Correcting the stream of errors that crop up among fragile bits of quantum information, called qubits, while performing a task.

A new study reporting on the discovery appears in the journal Nature. The senior author is Michel Devoret, Yale’s F.W. Beinecke Professor of Applied Physics and Physics. The study’s co-first authors are Alexander Grimm, a former postdoctoral associate in Devoret’s lab who is now a tenure-track scientist at the Paul Scherrer Institute in Switzerland, and Nicholas Frattini, a graduate student in Devoret’s lab.

Honeywell’s quantum computer is ready for companies eager to find out what will be the impact of the next era of computing on their business.

Physicists have long sought to understand the irreversibility of the surrounding world and have credited its emergence to the time-symmetric, fundamental laws of physics. According to quantum mechanics, the final irreversibility of conceptual time reversal requires extremely intricate and implausible scenarios that are unlikely to spontaneously occur in nature. Physicists had previously shown that while time-reversibility is exponentially improbable in a natural environment—it is possible to design an algorithm to artificially reverse a time arrow to a known or given state within an IBM quantum computer. However, this version of the reversed arrow-of-time only embraced a known quantum state and is therefore compared to the quantum version of pressing rewind on a video to “reverse the flow of time.”

In a new report now published in Communications Physics, Physicists A.V. Lebedev and V.M. Vinokur and colleagues in materials, physics and advanced engineering in the U.S. and Russia, built on their previous work to develop a technical method to reverse the temporal evolution of an arbitrary unknown quantum state. The technical work will open new routes for general universal algorithms to send the temporal evolution of an arbitrary system backward in time. This work only outlined the mathematical process of time reversal without experimental implementations.

But have you ever wondered: how well do those maps represent my brain? After all, no two brains are alike. And if we’re ever going to reverse-engineer the brain as a computer simulation—as Europe’s Human Brain Project is trying to do—shouldn’t we ask whose brain they’re hoping to simulate?

Enter a new kind of map: the Julich-Brain, a probabilistic map of human brains that accounts for individual differences using a computational framework. Rather than generating a static PDF of a brain map, the Julich-Brain atlas is also dynamic, in that it continuously changes to incorporate more recent brain mapping results. So far, the map has data from over 24,000 thinly sliced sections from 23 postmortem brains covering most years of adulthood at the cellular level. But the atlas can also continuously adapt to progress in mapping technologies to aid brain modeling and simulation, and link to other atlases and alternatives.

In other words, rather than “just another” human brain map, the Julich-Brain atlas is its own neuromapping API—one that could unite previous brain-mapping efforts with more modern methods.

Materials science researchers, led by electrical engineering professor Shui-Qing “Fisher” Yu, have demonstrated the first electrically injected laser made with germanium tin.

Used as a semiconducting material for circuits on electronic devices, the diode laser could improve micro-processing speed and efficiency at much lower costs.

In tests, the laser operated in pulsed conditions up to 100 kelvins, or 279 degrees below zero Fahrenheit.

Electronic components that can process information with high levels of efficiency are crucial for the development of most contemporary devices and computational tools. Reconfigurable electronics, flexible systems that can change configurations to best utilize available hardware resources, are a possible solution for enhancing processing efficiency.

Researchers at Nanjing University and the National Institute for Materials Science in Japan have recently designed new reconfigurable circuits with advanced shape-morphing and information processing capabilities. These logic and neuromorphic circuits, presented in a paper published in Nature Electronics, were fabricated using 2-D tungsten diselenide, an inorganic compound commonly used in the development of electronics.

“Current mainstream reconfigurable circuits (such as the field programmable gate array, FPGA) are based on traditional silicon circuits, using P-type or N-type field effect transistors with ‘fixed’ electrical characteristics,” Feng Miao, the researcher who led the study, told TechXplore. “For example, PN junction is always reverse-biased, and varying the drain polarity does not add new switching functionalities. Thus, these reconfigurable circuits need to use a lot of transistor resources to build complex circuit structures and eventually realize reconfigurable computing capabilities at the circuit level.”

The life-givers of integrated circuits and quantum devices in silicon are small structures made from patches of foreign atoms called dopants. The dopant structures provide charge carriers that flow through the components of the circuit, giving the components their ability to function. These days the dopant structures are only a few atoms across and so need to be made in precise locations within a circuit and have very well-defined electrical properties. At present manufacturers find it hard to tell in a non-destructive way whether they have made their devices according to these strict requirements. A new imaging paradigm promises to change all that.

The imaging mode called broadband electric force microscopy, developed by Dr. Georg Gramse at Keysight technologies & JKU uses a very sharp probe that sends electromagnetic waves into a silicon chip, to image and localize dopant structures underneath the surface. Dr. Gramse says that because the microscope can use waves with many frequencies it can provide a wealth of previously inaccessible detail about the electrical environment around the dopant structures. The extra information is crucial to predicting how well the devices will ultimately perform.

The imaging approach was tested on two tiny dopant structures made with a templating process which is unique in achieving atomically sharp interfaces between differently doped regions. Dr. Tomas Skeren at IBM produced the world’s first electronic diode (a circuit component which passes current in only one direction) fabricated with this templating process, while Dr. Alex Kölker at UCL created a multilevel 3D device with atomic scale precision.

Artificial molecules could one day form the information unit of a new type of computer or be the basis for programmable substances. The information would be encoded in the spatial arrangement of the individual atoms—similar to how the sequence of base pairs determines the information content of DNA, or sequences of zeros and ones form the memory of computers.

Researchers at the University of California, Berkeley, and Ruhr-Universität Bochum (RUB) have taken a step towards this vision. They showed that atom probe tomography can be used to read a complex spatial arrangement of metal ions in multivariate metal-organic frameworks.

Metal-organic frameworks (MOFs) are crystalline porous networks of multi-metal nodes linked together by organic units to form a well-defined structure. To encode information using a sequence of metals, it is essential to be first able to read the metal arrangement. However, reading the arrangement was extremely challenging. Recently, the interest in characterizing metal sequences is growing because of the extensive information such multivariate structures would be able to offer.