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Jul 15, 2019

Researchers develop computer model of ferrofluid motion

Posted by in categories: biotech/medical, computing, nanotechnology

Ferrofluids, with their mesmeric display of shape-shifting spikes, are a favorite exhibit in science shows. These eye-catching examples of magnetic fields in action could become even more dramatic through computational work that captures their motion.

A KAUST research team has now developed a computer model of motion that could be used to design even grander ferrofluid displays. The work is a stepping stone to using to inform the use of ferrofluids in broad range of practical applications, such as medicine, acoustics, radar-absorbing materials and nanoelectronics.

Ferrofluids were developed by NASA in the 1960s as a way to pump fuels in low gravity. They comprise nanoscale magnetic particles of iron-laden compounds suspended in a liquid. In the absence of a magnetic , ferrofluids possess a perfectly smooth surface. But when a magnet is brought close to the ferrofluid, the particles rapidly align with the magnetic field, forming the characteristic spiky appearance. If a magnetic object is placed in the ferrofluid, the spikes will even climb the object before cascading back down.

Jul 15, 2019

The US Army will test armored robotic vehicles in 2020

Posted by in categories: robotics/AI, transportation

The tests are designed to see how soldiers will operate robots in the field.

Jul 15, 2019

Researchers’ deep learning algorithm solves Rubik’s Cube faster than any human

Posted by in categories: information science, mathematics, robotics/AI

Since its invention by a Hungarian architect in 1974, the Rubik’s Cube has furrowed the brows of many who have tried to solve it, but the 3D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine.

DeepCubeA, a learning algorithm programmed by UCI scientists and mathematicians, can find the solution in a fraction of a second, without any specific domain knowledge or in-game coaching from humans. This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state—each of six sides displaying a solid color—which apparently can’t be found through random moves.

For a study published today in Nature Machine Intelligence, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the to the goal state about 60 percent of the time. The algorithm also works on other combinatorial games such as the sliding tile , Lights Out and Sokoban.

Jul 15, 2019

Intel’s Neuromorphic System Hits 8 Million Neurons, 100 Million Coming by 2020

Posted by in categories: computing, neuroscience

Researchers can use the 64-chip Pohoiki Beach system to make systems that learn and see the world more like humans.

Jul 15, 2019

Ebola spreads to largest city yet in DR Congo

Posted by in category: biotech/medical

The Democratic Republic of Congo has confirmed the first case of Ebola in the eastern city of Goma, a major transport hub.

The World Health Organization (WHO) said the case could be a “game-changer” given the city’s population of more than two million.

But the WHO expressed confidence in plans to deal with the diagnosis.

Jul 15, 2019

Free Energy Generator

Posted by in category: energy

Jul 15, 2019

A new ‘mathematically perfect’ material could completely swallow sound

Posted by in category: materials

Researchers have come up with an ‘acoustic metamaterial’ that cancels sound.

Jul 15, 2019

‘Greywater’ Could Help Solve Colorado’s Water Problems. Why Aren’t We All Using It?

Posted by in category: futurism

While greywater use was legalized in 2013, access to it is limited across the state because only Denver, Castle Rock and Pitkin County have adopted a code to regulate systems.

Jul 15, 2019

China #1 in quantum entanglement, teleports object 300 miles

Posted by in categories: quantum physics, robotics/AI, space

Science, Space & Robotics News | Posted: 9 hours, 42 mins ago.

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Jul 15, 2019

Physicists Reverse Time for Tiny Particles Inside a Quantum Computer

Posted by in categories: computing, mathematics, particle physics, quantum physics

Time goes in one direction: forward. Little boys become old men but not vice versa; teacups shatter but never spontaneously reassemble. This cruel and immutable property of the universe, called the “arrow of time,” is fundamentally a consequence of the second law of thermodynamics, which dictates that systems will always tend to become more disordered over time. But recently, researchers from the U.S. and Russia have bent that arrow just a bit — at least for subatomic particles.

In the new study, published Tuesday (Mar. 12) in the journal Scientific Reports, researchers manipulated the arrow of time using a very tiny quantum computer made of two quantum particles, known as qubits, that performed calculations. [Twisted Physics: 7 Mind-Blowing Findings]

At the subatomic scale, where the odd rules of quantum mechanics hold sway, physicists describe the state of systems through a mathematical construct called a wave function. This function is an expression of all the possible states the system could be in — even, in the case of a particle, all the possible locations it could be in — and the probability of the system being in any of those states at any given time. Generally, as time passes, wave functions spread out; a particle’s possible location can be farther away if you wait an hour than if you wait 5 minutes.