VIII. Earth Earns: An Open CoCreative Earthropocene to Astropocene PediaVerse

1. Mind Over Matter and Energy: Quantum, Atomic, Chemical, Astronomic Realms

Terasa, Ivo, et al. Pathways towards truly brain-like computing primitives. MaterialsToday. October, 2023. In this Springer journal, twelve Institute of Materials Science, Kiel University, Germany researchers describe a novel application of AI neural large learning and an avail of animate complex system principles such as Distributed Plasticity: Operation near Criticality, Self-ordered Arrangement, Hierarchy, Modularity, Robustness, and Oscillatory Ensembles. In this regard, the team broaches an innovative synthesis of these methods and features by which to open a 2020s frontier of intentional cocreativity going forward.

Taking inspiration from biological and neural information processing, deep learning and artificial intelligence have made solutions to complex problems more feasible. To explore the capabilities of brain-like hardware computing, a platform with dynamic reconfigurable connections is mandatory. This work addresses this biological motivation and classifies them with respect to several fundamental principles of brain-like computing. The approaches range from interconnected nanogranular networks with dynamically reconfigurable connections and guided redox-wiring to the mimicking of neural action potentials by relaxation-type oscillators that are used as input stimuli. (Abstract excerpt)

The nervous systems of humans, mammals, and even simple living species like invertebrates are well adapted to changing environments. The remarkable interactions with their surroundings are a result of millions of years of evolution. Biological systems can perform cognitive tasks, such as pattern recognition, with low power consumption. Fundamental building blocks leading to such core abilities exploit neurons as central processing units, which are interconnected by synapses to form a complex dynamical three-dimensional network. It is therefore no surprise that attempts have been made to develop artificial information processing systems, to reach the performance and power efficiency of nervous systems. Machine Learning, Neuromorphic Engineering and in materia Computing can be identified as three main development avenues (1, 2)

Thew, Rob, et al. Focus on Quantum Science and Technology Initiatives Around the World. Quantum Science and Technology. November, 2019. Editors from Switzerland, Canada, and Japan post a special collection for this radical worldwide ability to presently treat quantum phenomena as a common dynamic complex, network system which conveys content. Many unique applications with novel features then become possible such as faster computers and internet web.

Quantum physics has been a fascinating field of research for over a century, but is often seen as complex and difficult to understand. Information science was another primary development, but mostly as the reserve of complex and abstract mathematics. These technologies are sometimes seen as the first quantum revolution. Into the 21st century, a shift towards the development of products and applications by industrial companies has occurred, along with governments that realize the significance of these advances. This collection of Perspectives will provide insight into what is now a global pursuit. The first five papers cover established initiatives in Europe, Canada, Japan, Australia, and the USA. Further inputs from the UK and China will appear. So as 2020 approaches, we feel it is time to announce a second quantum revolution. (Summary excerpt.)

Thomas, Jordan, et al.. Quantum teleportation c\oexisting with classical communications in optical fiber.. Optica. 11/12, 2024. Seven Center for Photonic Communication and Computing, Northwestern University researchers describe a vital technical advancement in this regard by showing how both quantum and classical messages can be sent over existing cable networks.

The ability for quantum and conventional networks to operate in the same optical fibers would foster the deployment of quantum network technology. Here we report quantum teleportation over fibers carrying conventional telecommunications traffic. Fidelity is well maintained with an elevated C-band launch power for the single-channel 400-Gbps signal, which could support multiple classical channels with terabits/s aggregate data rates. These results show the feasibility of quantum and classical network applications within a unified fiber infrastructure.

Quantum teleportation is a technique for transferring quantum information from a sender at one location to a receiver some distance away. While teleportation is commonly portrayed as the transfer of physical objects, quantum teleportation only transfers information content.

Tritschler, Ulrich and Helmut Colfen. Self-Assembled Hierarchically Structured Organic-Inorganic Composite Systems. Bioinspiration & Biomimetics. 11/3, 2017. In this journal University of Konstanz, Germany physical chemists seek to intentionally carry forth nature’s hard won, practical solutions to design and build novel, beneficial forms and features. See also in this journal Towards a Theoretical Clarification of Biomeimetics Using Conceptual Tools from Engineering Design by M. Drack, et al (13/1, 2018).

Designing bio-inspired, multifunctional organic–inorganic composite materials is one of the most popular current research objectives. This article reviews recent progress in synthesizing organic–inorganic composite materials via various self-assembly techniques and in this context highlights a recently developed bio-inspired synthesis concept for the fabrication of hierarchically structured, organic–inorganic composite materials. This one-step self-organization concept based on simultaneous liquid crystal formation of anisotropic inorganic nanoparticles and a functional liquid crystalline polymer turned out to be simple, fast, scalable and versatile, leading to various (multi-)functional composite materials, which exhibit hierarchical structuring over several length scales. (Abstract excerpt)

Van Anders, Greg, et al. Digital Alchemy for Materials Design: Colloids and Beyond. ACS Nano. 9/10, 2015. A team of University of Michigan materials scientists in coauthor Sharon Glotzer’ Lab describe breakthrough efforts to understand nature’s generative geometries, so as to take evolution forth to new creative, salutary phases. See an earlier entry here under Pablo Damasceno, and a March 2017 posting Digital Alchemist Seeks Rules of Emergence in Quanta Magazine with the subtitle Computational physicist Sharon Glotzer is uncovering the rules by which complex collective phenomena emerge from simple building blocks.

Starting with the early alchemists, a holy grail of science has been to make desired materials by modifying the attributes of basic building blocks. Building blocks that show promise for assembling new complex materials can be synthesized at the nanoscale with attributes that would astonish the ancient alchemists in their versatility. Here we show how to exploit the malleability of the valence of colloidal nanoparticle “elements” to directly and quantitatively link building-block attributes to bulk structure through a statistical thermodynamic framework we term “digital alchemy”. We use this framework to optimize building blocks for a given target structure and to determine which building-block attributes are most important to control for self-assembly, through a set of novel thermodynamic response functions, moduli, and susceptibilities. Moreover, our results give concrete solutions to the more general conceptual challenge of optimizing emergent behaviors in nature and can be applied to other types of matter. As examples, we apply digital alchemy to systems of truncated tetrahedra, rhombic dodecahedra, and isotropically interacting spheres that self-assemble diamond, fcc, and icosahedral quasicrystal structures, respectively. (Abstract)

Velasco-Reyes, J., et al. Piecewise Omnigenous Stellarators.. Physical Review Letters. 122/185101, 2024. We note this entry by Laboratorio Nacional de Fusión, CIEMAT, Madrid, and Princeton Plasma Physics Laboratory researchers to report the latest advances as several mega projects (France, China, UK, USA) achieve more efficient and powerful atomic fusion reactors. See also The Quest to Build a Star on Earth by Raymond Zhong in the NY Times (Nov. 15, 2024).

In magnetic fields, charged particles are confined in the absence of collisions and turbulence. For this reason, the magnetic configuration is close to omnigenity in any candidate stellarator fusion reactor. However, this state imposes constraints on the spatial variation of the magnetic field which, in turn, leads to complicated plasma shapes and coils. This Letter presents a new family of preferred fields that display tokamak-like collisional energy transport while having transitioning particles. This result radically broadens the space of accessible reactor-relevant configurations. (Excerpts)

A New Twist on Stellarator Design Velasco and his colleagues show that rather than dealing with the magnetic surface as a whole, one can divide it into finite modular regions separately. The team’s simulations predict that a “piecewise-optimized” stellarator that reduces charged-particle transport, potentially bringing stellarator energy confinement up to tokamak level. The researchers say that their method which optimizes both confinement and coil simplicity, expands the possible configurations that can be used in a reactor. (Rachei Berkowitz, editor)

Von Lilienfeld, Anatole, et al. Exploring Chemical Compound Space with Quantum-based Machine Learning. Nature Reviews Chemistry. 4/6, 2020. We cite this entry by University of Basel, Berlin and Luxembourg material scientists as an example, largely unawares so far, of humankinder abilities to take over and begin a new physical, elemental and in/organic chemical co-pro-creation.

Rational design of compounds with specific properties requires understanding and fast evaluation of molecular properties throughout the huge set of all potentially stable molecules. Recent melds of quantum-mechanical calculations with machine learning show promise for exploring wide swathes of chemical compound space. We propose that significant progress in the understanding of chemical reactivity can be made through a systematic combination of physical theories, comprehensive data sets of microscopic and macroscopic properties, and modern machine-learning methods. (Abstract excerpt)

Wadkawan, Vinod. Smart Structures. Oxford: Oxford University Press, 2007. As readers know, there is today a burst of books on “nanotechnology” as regnant mind may gain the ability to act upon the molecular and atomic depths of material device and function. This present volume by a Raja Ramanna Fellow at the Bhabha Research Centre, Mumbai, India is notable as a dedicated attempt to first articulate nature’s own method of dynamic self-organization and to then apply it everywhere as a direct, intentional continuation.

Wan, Kwok-Ho, et al. Quantum Generalization of Feedforward Neural Networks. Npj Quantum Information. 3/36, 2017. We cite this entry by Imperial College London mathematicians to report novel integrations between quantum phenomena and classical complex systems. Of especial note is an amenable employ of cerebral dynamics to nature’s fundamental realm. Why do neural nets so readily apply everywhere, what might this imply about universe and human? See also Topological Networks for Quantum Communication Between Distant Qubits in this journal (Lang, 3/47).

We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically. (Abstract)

Quantum vs. classical: Can these neural networks show some form of quantum
supremacy? The comparison of classical and quantum neural networks is well-defined within our set-up, as the classical networks correspond to a particular parameter regime for the quantum networks. A key type of quantum supremacy is that the quantum network can take and process quantum inputs: it can for example process (+) and (-) differently. Thus, there are numerous quantum tasks it can do that the classical network cannot, including the two examples above. (36)

We often want computers to tell us something about the input data, e.g. if a given image corresponds to a cat or a dog. It seems the human brain learns this by looking at examples whilst getting feedback from a teacher, rather than being given an algorithm. Such an approach to programming is now revolutionising the ability of machines to learn. The approach uses simplified models of the brain: neural nets. Quantum information processing devices are now emerging as the next generation of information processors. One may hope that the neural net approach will be similarly powerful there. We therefore designed quantum neural nets, processing quantum superpositions. The nets work well in two example tasks: compressing data stored in superpositions, and rediscovering a protocol known as quantum teleportation. (Editor comment)

Warth, Benedict, et al. Metabolizing Data in the Cloud. Trends in Biotechnology. Online February, 2017. We cite this note from the Center for Metabolomics and Departments of Chemistry, Molecular and Computational Biology, Immunology and Microbial Science and Chemical Physiology, Scripps Research Institute, La Jolla, CA as an example of this enveloping global sensorium as it proceeds with a deep, interactive informomics learning project.

Cloud-based bioinformatic platforms address the fundamental demands of creating a flexible scientific environment, facilitating data processing and general accessibility independent of a countries’ affluence. These platforms have a multitude of advantages as demonstrated by omics technologies, helping to support both government and scientific mandates of a more open environment. (Abstract)

Wasielewski, Michael, et al. Exploiting Chemsitry and Molecular Systems for Quantum Information Science. Nature Reviews Chemistry. 4/490, 2020. We cite this paper by sixteen chemists from universities across the USA including Birgitta Whaley (UC Berkeley) for both its authorship and how novel integrations across wide realms from deep physical domains to cognitive resources can initiate and enhance a new intentional phase of synthetic chemistry and material procreations. See also Quantum Neuromorphic Computing by Markovic, Danijela Markovic and Julie Grolier at arXiv:2006.15111.

The power of chemistry to prepare new molecules and materials has driven the quest for approaches to solve problems having global societal impact such as renewable energy, healthcare and communication. In the latter case, the intrinsic quantum nature of the electronic, nuclear and spin degrees of freedom in molecules offers intriguing possibilities to advance quantum information science. In this Perspective, which resulted from a Dept. of Energy workshop in November 2018, we discuss how chemical systems and reactions can impact quantum computing, knowledge conveyance and sensing methods. (Abstract)

Wei, Bryan, et al. Complex Shapes Self-Assembled from Single-Stranded DNA Tiles. Nature. 485/623, 2012. Harvard University systems biophysicists find that deoxyribonucleic molecules can be molded by origami-like foldings into a myriad of topological arrays. By avail of its tendency to self-assemble into modular forms, a novel realm of vital nanoscale geometries is thus seen to open. The Letter is accompanied in the same issue by a review “The Importance of Being Modular” by Paul Rothemund and Ebbe Sloth Anderson.

Programmed self-assembly of strands of nucleic acid has proved highly effective for creating a wide range of structures with desired shapes. A particularly successful implementation is DNA origami, in which a long scaffold strand is folded by hundreds of short auxiliary strands into a complex shape. Modular strategies are in principle simpler and more versatile and have been used to assemble DNA or RNA tiles into periodic and algorithmic two-dimensional lattices, extended ribbons and tubes, three-dimensional crystals, polyhedra and simple finite two-dimensional shapes. (623)

Thus, the SST (single-stranded tile) method and DNA origami, and approaches that use multistranded DNA and RNA tiles, logic gates and kinetid hairpins, suggest the presence of a vast design space that remains to be explored for the creation of nucleic acid nanostructures, and more generally for information-directed molecular self-assembly. (626)

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