Lifeboat Foundation

In this work, we carry out KS-MD simulations for a range of elements, temperatures, and densities, allowing for a systematic comparison of three RPP models. While multiple RPP models can be selected, ^7–11 7. J. Vorberger and D. Gericke, “Effective ion–ion potentials in warm dense matter,” High Energy Density Phys. 9, 178 (2013). https://doi.org/10.1016/j.hedp.2012.12.009 8. Y. Hou, J. Dai, D. Kang, W. Ma, and J. Yuan, “Equations of state and transport properties of mixtures in the warm dense regime,” Phys. Plasmas 22, 022711 (2015). https://doi.org/10.1063/1.4913424 9. K. Wünsch, J. Vorberger, and D. Gericke, “Ion structure in warm dense matter: Benchmarking solutions of hypernetted-chain equations by first-principle simulations,” Phys. Rev. E 79, 010201 (2009). https://doi.org/10.1103/PhysRevE.79.010201 10. L. Stanton and M. Murillo, “Unified description of linear screening in dense plasmas,” Phys. Rev. E 91, 033104 (2015). https://doi.org/10.1103/PhysRevE.91.033104 11. W. Wilson, L. Haggmark, and J. Biersack, “Calculations of nuclear stopping, ranges, and straggling in the low-energy region,” Phys. Rev. B 15, 2458 (1977). https://doi.org/10.1103/PhysRevB.15.2458 we choose to compare the widely used Yukawa potential, which accounts for screening by linearly perturbing around a uniform density in the long-wavelength (Thomas–Fermi) limit, a potential constructed from a neutral pseudo-atom (NPA) approach, ^12–15 12. L. Harbour, M. Dharma-wardana, D. D. Klug, and L. J. Lewis, “Pair potentials for warm dense matter and their application to x-ray Thomson scattering in aluminum and beryllium,” Phys. Rev. E 94, 053211 (2016). https://doi.org/10.1103/PhysRevE.94.053211 13. M. Dharma-wardana, “Electron-ion and ion-ion potentials for modeling warm dense matter: Applications to laser-heated or shock-compressed Al and Si,” Phys. Rev. E 86, 036407 (2012). https://doi.org/10.1103/PhysRevE.86.036407 14. F. Perrot and M. Dharma-Wardana, “Equation of state and transport properties of an interacting multispecies plasma: Application to a multiply ionized al plasma,” Phys. Rev. E 52, 5352 (1995). https://doi.org/10.1103/PhysRevE.52.5352 15. L. Harbour, G. Förster, M. Dharma-wardana, and L. J. Lewis, “Ion-ion dynamic structure factor, acoustic modes, and equation of state of two-temperature warm dense aluminum,” Phys. Rev. E 97, 043210 (2018). https://doi.org/10.1103/PhysRevE.97.043210 and the optimal force-matched RPP that is constructed directly from KS-MD simulation data.

Each of the models we chose impacts our physics understanding and has clear computational consequences. For example, success of the Yukawa model reveals the insensitivity to choices in the pseudopotential and screening function and allows for the largest-scale simulations. Large improvements are expected from the NPA model, which makes many fewer assumptions with a modest cost of pre-computing and tabulating forces. (See the Appendix for more details on the NPA model.) The force-matched RPP requires KS-MD data and is therefore the most expensive to produce, but it reveals the limitations of RPPs themselves since they are by definition the optimal RPP.

Using multiple metrics of comparison between RPP-MD and KS-MD including the relative force error, ion–ion equilibrium radial distribution function g (r), Einstein frequency, power spectrum, and the self-diffusion transport coefficient, the accuracy of each RPP model is analyzed. By simulating disparate elements, namely, an alkali metal, multiple transition metals, a halogen, a nonmetal, and a noble gas, we see that force-matched RPPs are valid for simulating dense plasmas at temperatures above fractions of an eV and beyond. We find that for all cases except for low temperature carbon, force-matched RPPs accurately describe the results obtained from KS-MD to within a few percent. By contrast, the Yukawa model appears to systematically fail at describing results from KS-MD at low temperatures for the conditions studied here validating the need for alternate models such as force-matching and NPA approaches at these conditions.

It’s another step on the road to developing quantum information processing applications: A key experiment succeeded in going beyond the previously defined limits for photon applications. Anahita Khodadad Kashi and Prof. Dr. Michael Kues from the Institute of Photonics and the Cluster of Excellence PhoenixD at Leibniz University Hannover (Germany) have demonstrated a novel interference effect. The scientists have thus shown that new color-coded photonic networks can be tapped, and the number of photons involved can be scaled. “This discovery could enable new benchmarks in quantum communication, computational operations of quantum computers as well as quantum measurement techniques and is feasible with existing optical telecommunication infrastructure,” says Kues.

The decisive experiment was successfully performed in the newly established Quantum Photonics Laboratory (QPL) of the Institute of Photonics and the Hannover Centre for Optical Technologies at Leibniz University Hannover. Anahita Khodadad Kashi succeeded in quantum-mechanically interfering independently generated pure photons with different colors, i.e., frequencies. Khodadad Kashi detected a so-called Hong-Ou-Mandel effect.

Hong-Ou-Mandel interference is a fundamental effect of quantum optics that forms the basis for many quantum information processing applications—from quantum computing to quantum metrology. The effect describes how two photons behave when they collide on a spatial beam splitter and explains the phenomenon of quantum mechanical interference.

All of which would be nice and handy, but clearly, privacy and ethics are going to be a big issue for people — particularly when a company like Facebook is behind it. Few people in the past would ever have lived a life so thoroughly examined, catalogued and analyzed by a third party. The opportunities for tailored advertising will be total, and so will the opportunities for bad-faith actors to abuse this treasure trove of minute detail about your life.

But this tech is coming down the barrel. It’s still a few years off, according to the FRL team. But as far as it is concerned, the technology and the experience are proven. They work, they’ll be awesome, and now it’s a matter of working out how to build them into a foolproof product for the mass market. So, why is FRL telling us about it now? Well, this could be the greatest leap in human-machine interaction since the touchscreen, and frankly Facebook doesn’t want to be seen to be making decisions about this kind of thing behind closed doors.

Continue reading “Facebook’s upcoming AR wrist controllers will hijack your nerves” »

Progress in the field of integrated circuits is measured by matching, exceeding, or falling behind the rate set forth by Gordon Moore, former CEO and co-founder of Intel, who said the number of electronic components, or transistors, per integrated circuit would double every year. That was more than 50 years ago, and surprisingly his prediction, now called Moore’s Law, came true.

In recent years, it was thought that the pace had slowed; one of the biggest challenges of putting more circuits and power on a smaller chip is managing heat.

A multidisciplinary group that includes Patrick E. Hopkins, a professor in the University of Virginia’s Department of Mechanical and Aerospace Engineering, and Will Dichtel, a professor in Northwestern University’s Department of Chemistry, is inventing a new class of material with the potential to keep chips cool as they keep shrinking in size—and to help Moore’s Law remain true. Their work was recently published in Nature Materials.

TL;DR: Last week, we kicked off a three-part series on the future of human-computer interaction (HCI). In the first post, we shared our 10-year vision of a contextually-aware, AI-powered interface for augmented reality (AR) glasses that can use the information you choose to share, to infer what you want to do, when you want to […].

Following in my recent series on subjects that are all the rage in anti-aging and longevity circles, to help you get a good grasp of the essentials so you can know what all the talk is about, and can make informed judgements rather than just following the herd blindly. This time it is on Metformin. This is a drug widely known as a diabetes drug and it has been in use for a very long time, indeed it is one of the most prescribed drugs there is. Recently it has also been a buzz word in the anti aging/longevity communities following the review of data and with it s mechanism of action, being touted and recommended by a variety of voices in the public domain. But how does it work, and how could it improve longevity? Is it safe? Well, if you want to go into a bit more depth and know all the details, I have put together a video which helps you understand what all the fuss is about. And whatever you are doing, have a great day.

Metformin is very popular in the anti aging paradigm currently so let’s have a look at what it is, what it offers, and what the trade offs are… because, well, it is always wise to have all the data.

Continue reading “Metformin Mechanism Of Action” »

Researchers at the quantum computing firm D-Wave Systems have shown that their quantum processor can simulate the behaviour of an “untwisting” quantum magnet much faster than a classical machine. Led by D-Wave’s director of performance research Andrew King, the team used the new low-noise quantum processor to show that the quantum speed-up increases for harder simulations. The result shows that even near-term quantum simulators could have a significant advantage over classical methods for practical problems such as designing new materials.

The D-Wave simulators are specialized quantum computers known as quantum annealers. To perform a simulation, the quantum bits, or qubits, in the annealer are initialized in a classical ground state and allowed to interact and evolve under conditions programmed to mimic a particular system. The final state of the qubits is then measured to reveal the desired information.

King explains that the quantum magnet they simulated experiences both quantum fluctuations (which lead to entanglement and tunnelling) and thermal fluctuations. These competing effects create exotic topological phase transitions in materials, which were the subject of the 2016 Nobel Prize in Physics.

The debate holds a special interest for neuroscientists; since computer programming has only been around for a few decades, the brain has not evolved any special region to handle it. It must be repurposing a region of the brain normally used for something else.

So late last year, neuroscientists in MIT tried to see what parts of the brain people use when dealing with computer programming. “The ability to interpret computer code is a remarkable cognitive skill that bears parallels to diverse cognitive domains, including general executive functions, math, logic, and language,” they wrote.

Since coding can be learned as an adult, they figured it must rely on some pre-existing cognitive system in our brains. Two brain systems seemed like likely candidates: either the brain’s language system, or the system that tackles complex cognitive tasks such as solving math problems or a crossword. The latter is known as the “multiple demand network.”

With powerful engines, near-photorealistic graphics, and the ability to build incredible, immersive worlds, it’s hard to imagine what the next big technological advance in gaming might be.

Based on a recent tweet by Neuralink co-founder and President Max Hodak, the word might not even apply. In it, he hinted — vaguely, to be fair — that whatever forms of entertainment get programmed into neural implants and brain-computer interfaces will represent a paradigm shift that moves beyond the current terminology.

“We’re gonna need a better term than ‘video game’ once we start programming for more of the sensorium,” Hodak tweeted.