Lifeboat Foundation

Crucially, the Nissan-NASA partnership is also focusing on batteries that don’t rely on rare metals, like cobalt (of which more than half the global supply is in the Democratic Republic of the Congo, as highlighted in an episode of the New York Times Daily podcast last month), nickel, or manganese.

But getting rid of those metals means finding materials with comparable properties to replace them, which will be no simple task. Here’s where NASA’s computing chops will lend the partnership a much-needed hand. They plan to create an original material informatics platform—that is, a massive database that runs simulations of how various materials interact with one another. When the platform narrows countless options and combinations down to a few prime candidates, researchers can then start testing them.

Nissan has targeted 2028 as the year to roll out its proprietary solid-state batteries. How realistic that timing turns out to be remains to be seen (Toyota is even more ambitious, aiming to have its own vehicles with solid-state batteries on the market by 2025), b ut Nissan is putting its money where its mouth is with plans to open a pilot plant in Japan in 2024. How this plays out will be revelatory, as scaling up manufacturing of solid-state batteries has produced unexpected complications in the past. Encouragingly, startup Solid Power ha s also targeted 2028 for comm ercializing its solid-state batteries.

Elon Musk believes his Neuralink brain chip could help treat morbid obesity. Experts say the billionaire’s dream isn’t as far-fetched as it may seem.

“I don’t think it is any more implausible than other claims for the potential of neurotechnology,” Professor Andrew Jackson, an expert in neural interfaces at Newcastle University, told Insider.

Continue reading “Elon Musk said his Neuralink brain chip could help treat morbid obesity. Scientists say it’s a long shot — but not an impossibility” »

For years, the brain has been thought of as a biological computer that processes information through traditional circuits, whereby data zips straight from one cell to another. While that model is still accurate, a new study led by Salk Professor Thomas Albright and Staff Scientist Sergei Gepshtein shows that there’s also a second, very different way that the brain parses information: through the interactions of waves of neural activity. The findings, published in Science Advances on April 22, 2022, help researchers better understand how the brain processes information.

“We now have a new understanding of how the computational machinery of the brain is working,” says Albright, the Conrad T. Prebys Chair in Vision Research and director of Salk’s Vision Center Laboratory. “The model helps explain how the brain’s underlying state can change, affecting people’s attention, focus, or ability to process information.”

Researchers have long known that waves of electrical activity exist in the brain, both during sleep and wakefulness. But the underlying theories as to how the brain processes information—particularly sensory information, like the sight of a light or the sound of a bell—have revolved around information being detected by specialized brain cells and then shuttled from one neuron to the next like a relay.

Physicists at the University of California, Irvine have demonstrated the use of a hydrogen molecule as a quantum sensor in a terahertz laser-equipped scanning tunneling microscope, a technique that can measure the chemical properties of materials at unprecedented time and spatial resolutions.

This new technique can also be applied to analysis of two-dimensional materials which have the potential to play a role in advanced energy systems, electronics and quantum computers.

Today in Science, the researchers in UCI’s Department of Physics & Astronomy and Department of Chemistry describe how they positioned two bound atoms of hydrogen in between the silver tip of the STM and a sample composed of a flat copper surface arrayed with small islands of copper nitride. With pulses of the laser lasting trillionths of a second, the scientists were able to excite the hydrogen molecule and detect changes in its quantum states at cryogenic temperatures and in the ultrahigh vacuum environment of the instrument, rendering atomic-scale, time-lapsed images of the sample.

Summary: Study reveals the different ways the brain parses information through interactions of waves of neural activity.

Source: Salk Institute.

For years, the brain has been thought of as a biological computer that processes information through traditional circuits, whereby data zips straight from one cell to another. While that model is still accurate, a new study led by Salk Professor Thomas Albright and Staff Scientist Sergei Gepshtein shows that there’s also a second, very different way that the brain parses information: through the interactions of waves of neural activity.

New measurement for W boson is at odds with previous values.

AMD has cut prices on its Ryzen 5,000 CPUs. In some cases, they’ve trimmed price by as much as 25 percent.

Basically all this says is that a basic quantum computer made of a simulation of an infinite quantum computer. So essentially infinite quantum computers could make the internet much more instant.

To parallelise our simulation on a small NISQ machine, we first identify partitions of the system where the effect of one partition upon the other can be summarised by a small amount of information. This is achieved by making Schmidt decompositions across the cut: \(\left|\psi \right\rangle =\mathopsum
olimits_alpha = 1^Dlambda ^alpha \left|phi _L^alpha \right\rangle \left|phi _R^alpha \right\rangle,\) where \(\left|phi _L^alpha \right\rangle\) are an orthonormal set of states to the left of the cut and \(\left|phi _R^alpha \right\rangle\) the same on the right. The λ^α are known as the Schmidt coefficients and D the Schmidt rank or bond order. Retaining λ^α only above some threshold value provides a way to compress representations of a quantum state; the MPS construction can be obtained by applying this procedure sequentially along a spin chain⁴.

If an observation is made on the right-hand-side of such a cut, the effect of the quantum state on the left upon the observation can be summarised by just D variables corresponding to the Schmidt coefficients. This same effect can be achieved by an effective state on a spin chain of length \(log\,_2D\) —see Fig. 1 —which can be parametrised on the quantum circuit by an SU (D²) unitary V_L. This encodes both the Schmidt coefficients λ_α and the orthonormal states \(\left|phi _L^alpha \right\rangle\). The latter does not contribute to observables on the right and so in principle, V_L can be parametrised by just D variational parameters. The precise numerical values must be determined by solving a quantum mechanical problem on the left of the system. Similarly, for observations made to the left of the cut, the effect of the right-hand side can be summarised by a unitary V_R.

Circa 2019

Light is the most energy-efficient way of moving information. Yet, light shows one big limitation: it is difficult to store. As a matter of fact, data centers rely primarily on magnetic hard drives. However, in these hard drives, information is transferred at an energy cost that is nowadays exploding. Researchers of the Institute of Photonic Integration of the Eindhoven University of Technology (TU/e) have developed a ‘hybrid technology’ which shows the advantages of both light and magnetic hard drives.

Ultra-short (femtosecond) light pulses allows data to be directly written in a magnetic memory in a fast and highly energy-efficient way. Moreover, as soon as the information is written (and stored), it moves forward leaving space to empty memory domains to be filled in with new data. This research, published in Nature Communications, promises to revolutionize the process of data storage in future photonic integrated circuits.

Continue reading “Next generation photonic memory devices are ‘light-written,’ ultrafast and energy efficient” »

Circa 2015 This is basically amazing leading to speeds in a computer basically infinite.

Quantum gases of atoms and exciton-polaritons are nowadays a well established theoretical and experimental tool for fundamental studies of quantum many-body physics and suggest promising applications to quantum computing. Given their technological complexity, it is of paramount interest to devise other systems where such quantum many-body physics can be investigated at a lesser technological expense. Here we examine a relatively well-known system of laser light propagating through thermo-optical defocusing media: based on a hydrodynamical description of light as a quantum fluid of interacting photons, we investigate such systems as a valid, room temperature alternative to atomic or exciton-polariton condensates for studies of many-body physics.