Lifeboat Foundation

Circa 2013

One of the greatest aspirations of the human mind has been to realize machines that surpass its cognitive intelligence. The rapid expansion in computing power, about to exceed the equivalent of the human brain, has yet to produce such a machine. The article by Neftci et al. in PNAS (1) offers a refreshing and humbling reminder that the brain’s cognition does not arise from exacting digital precision in high-performance computing, but rather emerges from an extremely efficient and resilient collective form of computation extending over very large ensembles of sluggish, imprecise, and unreliable analog components. This observation, first made by John von Neumann in his final opus (2), continues to challenge scientists and engineers several decades later in figuring and reproducing the mechanisms underlying brain-like forms of cognitive computing.

Related developments are currently unfolding in collaborative initiatives engaging scientists and engineers, on a grander scale, in advancing neuroscience toward understanding the brain. In parallel with the Human Brain Project in Europe, the Brain Research through Advancing Innovative Neurotechnologies Initiative promises groundbreaking advances in enabling tools for revolutionizing neuroscience by developing nanotechnology to probe brain function at greatly increased spatial and temporal detail. Engineers are poised to contribute even further in revolutionizing such developments in neuroscience. In this regard it is helpful to relate the inquisitive nature of science—analysis—to the constructive power of engineering, synthesis.

Fan speeds clock in over 11000 RPM.

Dynatron rolls out the A38, a robust CPU air cooler for AMD Ryzen Threadripper and EPYC processors.

Researchers at Chalmers University of Technology, Gothenburg, Sweden, have developed a novel type of thermometer that can simply and quickly measure temperatures during quantum calculations with extremely high accuracy. The breakthrough provides a benchmarking tool for quantum computing of great value—and opens up for experiments in the exciting field of quantum thermodynamics.

Key components in quantum computers are coaxial cables and waveguides—structures that guide waveforms and act as the vital connection between the quantum processor and the classical electronics that control it. Microwave pulses travel along the waveguides to the quantum processor, and are cooled down to extremely low temperatures along the way. The waveguide also attenuates and filters the pulses, enabling the extremely sensitive quantum computer to work with stable quantum states.

In order to maximize control over this mechanism, the researchers need to be sure that these waveguides are not carrying noise due to thermal motion of electrons on top of the pulses that they send. In other words, they have to measure the temperature of the electromagnetic fields at the cold end of the microwave waveguides, the point where the controlling pulses are delivered to the computer’s qubits. Working at the lowest possible temperature minimizes the risk of introducing errors in the qubits.

Big Blue has made Qiskit Metal generally available, to let “anyone” try their hand at quantum hardware design.

Pioneering experiment could help design energy-efficient materials.

In a groundbreaking study published in Physical Review Research, a group of University of Chicago scientists announced they were able to turn IBM’s largest quantum computer into a quantum material itself.

They programmed the computer such that it turned into a type of quantum material called an exciton condensate, which has only recently been shown to exist. Such condensates have been identified for their potential in future technology, because they can conduct energy with almost zero loss.

Long but annotated! Most important here is human data for specific treatments due out starting in May or June. And apparently they had a mouse study where they expected a paper due out already but other groups chimed in to help with more testing so there is a delay.

Liz Parrish, CEO of BioViva Science and patient zero of biological rejuvenation with gene therapies, is interviewed by Zora Benhamou on her fresh podcast “HackMyAge”.

Continue reading “Liz Parrish goes deep into gene therapies at the HackMyAge Podcast by Zora (March 2021)” »

By Chuck Brooks

The world of computing has witnessed seismic advancements since the invention of the electronic calculator in the 1960s. The past few years in information processing have been especially transformational. What were once thought of as science fiction fantasies are now technological realties. Classical computing has become more exponentially faster and more capable and our enabling devices smaller and more adaptable.

The Research Group on Synthetic Biology for Biomedical Applications at Pompeu Fabra University in Barcelona, Spain, has designed a cellular device capable of computing by printing cells on paper. For the first time, they have developed a living device that could be used outside the laboratory without a specialist, and it could be produced on an industrial scale at low cost. The study is published in Nature Communications and was carried out by Sira Mogas-Díez, Eva Gonzalez-Flo and Javier Macía.

We currently have many electronic devices available to us such as computers and tablets whose computing power is highly efficient. But, despite their power, they are very limited devices for detecting biological markers, such as those that indicate the presence of a disease. For this reason, a few years ago ‘biological computers’ began to be developed—in other words, living cellular devices that can detect multiple markers and generate complex responses. In them, the researchers leverage biological receptors that allow detecting exogenous signals and, by means of synthetic biology, modify them to emit a response in accordance with the information they detect.

So far, cellular devices have been developed that must operate in the laboratory, for a limited time, under specific conditions, and must be handled by a specialist in molecular biology. Now, a team of researchers from Pompeu Fabra University has developed new technology to ‘print’ cellular devices on paper that can be used outside the laboratory.

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.