
III. Ecosmos: A Revolutionary Fertile, Habitable, SolarBioplanet Lifescape1. Quantum Organics in the 21st Century Paparo, Paparo, Giuseppe, et al. Quantum Speedup for Active Learning Agents. Physical Review X. 4/031002, 2014. A team of European systems physicists applies the Projective Simulation method of coauthor Hans Briegel (search) to quantum phenomena which is similarly seen as capable of modifying responses and behaviors by reference to past experience. We note in another venue how it is vital to be able to accord novel events with familiar memory to effectively learn and succeed. One of the defining characteristics of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in any reallife situation is the size and complexity of the corresponding task environment. Even for a moderate task environment, it may simply take too long to rationally respond to a given situation. Here we show that quantum physics can help and provide a significant speedup for active learning as a genuine problem of artificial intelligence. We introduce a large class of quantum learning agents for which we show a quadratic boost in their active learning efficiency over their classical analogues. This result will be particularly relevant for applications involving complex task environments. (Abstract) Rispoli, Matthew, et al. Quantum Critical Behavior at the ManyBodyLocalization Transition. arXiv:1812.06959. While equilibrium quantum systems are said to be well quantified, nonequilibrium phenomena have not yet been. Here seven Harvard University physicists describe how these active phases can be explained by better measurements of their entanglement properties. We cite to record how the arcane quantum realm is being parsed by the same critically poised systems theory as everywhere else. And from the Abstract: Our results unify the system's microscopic structure with its macroscopic quantum critical behavior, and they provide an essential step towards understanding criticality and universality in nonequilibrium systems. Rotter, Ingrid and J. P. Bird. A Review of Progress in the Physics of Open Quantum Systems. Reports on Progress in Physics. 78/114001, 2015. MPI Physics of Complex Systems and SUNY Buffalo scientists survey the 21st century, worldwide revolutionary understanding of this most fundamental microrealm. As yet mostly unnoticed, an arcane, offputting 20th century version has been set aside for the presence of complex networks similar to every other classical macrostage. Sachdev, Subir and Bernhard Keimer. Quantum Criticality. Physics Today. February, 2011. Harvard University and Max Planck Institute physicists are able to deeply glimpse into material realm whose phases of large numbers of particles interact at low enough temperatures that quantum effects produce the title phenomena. An expanded technical version can be found at arxiv:1102.4628. SanchezBurillo, Eduardo, et al. Quantum Navigation and Ranking in Complex Networks. Nature Scientific Reviews. 2/605, 2012. Universidad de Zaragoza, and Universitat Rovira i Virgili, Spain, systems physicists cleverly notice that Google’s PageRank algorithms, in their webwork dynamics, can be similarly found and availed even in quantum realms. An extended reference list offers an entry to this considerable project. Can one now say that every disparate, stratified natural domain seems in fact to be distinguished by such ultimately geneticlike qualities? Complex networks are formal frameworks capturing the interdependencies between the elements of large systems and databases. This formalism allows to use network navigation methods to rank the importance that each constituent has on the global organization of the system. A key example is Pagerank navigation which is at the core of the most used search engine of the World Wide Web. Inspired in this classical algorithm, we define a quantum navigation method providing a unique ranking of the elements of a network. We analyze the convergence of quantum navigation to the stationary rank of networks and show that quantumness decreases the number of navigation steps before convergence. In addition, we show that quantum navigation allows to solve degeneracies found in classical ranks. By implementing the quantum algorithm in real networks, we confirm these improvements and show that quantum coherence unveils new hierarchical features about the global organization of complex systems. (Abstract) Scholes, Gregory, et al. Using Coherence to Enhance Function in Chemical and Biophysical Systems. Nature. 543/647, 2018. As quantum and complexity studies grow and converge in scope and veracity, they are erasing a classical divide so as to reveal a seamless unity (as David Bohm would say) to crossadvise each other. Here some 19 researchers from Harvard to UC Berkeley and onto Canada and Germany draw serious parallels which appear to infuse a natural universe to us vitality. Coherence phenomena arise from interference, or the addition, of wavelike amplitudes with fixed phase differences. Although coherence has been shown to yield transformative ways for improving function, advances have been confined to pristine matter and coherence was considered fragile. However, recent evidence of coherence in chemical and biological systems suggests that the phenomena are robust and can survive in the face of disorder and noise. Here we survey the state of recent discoveries, present viewpoints that suggest that coherence can be used in complex chemical systems, and discuss the role of coherence as a design element in realizing function. (Abstract) Schuld, Maria, et al. Viewpoint: Neural Networks take on Open Quantum Systems. Physics Review Letters. 122/25, 2019. University of KwaZuluNatal, RSA physicists MS, Ilya Sinayskify and Francesco Peruccione comment on articles in this issue such as Neural Network Approach to Dissipative Quantum ManyBody Physics and Quantum Monte Carlo Method with a Neural Network Ansatz for Open Quantum Systems which report ways that this brainbased problemsolving method can similarly apply to nature’s deepest realm. By way of its physical affinity, quantum phenomena can actually possess classical dynamic complexities. See also Machine Learning and the Physical Sciences by Giuseppe Carleo, et al. at arXiv:1903.10563 and The Quest for a Quantum Neural Network by the authors in Quantum Information Processing (13/11, 2014). Simulating a quantum system that exchanges energy with the outside world is difficult, but the necessary computations might be easier with the help of neural networks. These general problem solvers reach their solutions by being adapted or “trained” to capture correlations in realworld data. Physicists are asking if the tools might also be useful in areas ranging from highenergy physics to quantum computing. Four research groups now report on using neural networks to tackle computationally challenging problems such as simulating the behavior of an open manybody quantum system. (Abstract) Schutt, Kristof, et al. QuantumChemical Insights from Deep Tensor Neural Networks. Nature Communications. 8/13890, 2017. Technical University of Berlin and MPI Fritz Haber Institute, Berlin informatics theorists provide another entry to how much quantum phenomena is now commonly treated as a complex dynamic system, akin to all other phases and scales. See also Neural Message Passing for Quantum Chemistry by Justin Gilmer at arXiv:1704.01212. Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable breakthroughs in understanding quantum manybody systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantummechanical observables of molecular systems. We unify concepts from manybody Hamiltonians with purposedesigned deep tensor neural networks, which leads to predictions in compositional and configurational chemical spaces. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantumchemical systems. (Abstract) Shi, Guodong, et al. Reaching Agreement in Quantum Hybrid Networks. Nature Scientific Reports. 7/5989, 2017. We cite this entry by Australian National University, University of Melbourne, and Chinese Academy of Sciences theorists as an example of how, mostly unawares, the 20th century view of quantum arcana has been replaced by not only an informational feature, but in this case, attributed neural, cognitive qualities. As this section tries to document, by these revisions and advances classical and quantum realms are becoming similarly united, and herewith encephalized. We consider a basic quantum hybrid network model consisting of a number of nodes each holding a qubit, for which the aim is to drive the network to a consensus in the sense that all qubits reach a common state. Projective measurements are applied serving as control means, and the measurement results are exchanged among the nodes via classical communication channels. In this way the quantumoperation/classicalcommunication nature of hybrid quantum networks is captured, although coherent states and joint operations are not taken into consideration in order to facilitate a clear and explicit analysis. We show how to carry out centralized optimal path planning for this network with alltoall classical communications, in which case the problem becomes a stochastic optimal control problem with a continuous action space. We show that the qubit states are driven to a consensus almost surely along the proposed PQP algorithm, and that the expected qubit density operators converge to the average of the network’s initial values. (Abstract)
Smolin, Lee.
A Real Ensemble Interpretation of Quantum Mechanics.
Foundations of Physics.
42/10,
2012.
Theoretical physicist and author Lee Smolin, a founding member of the Perimeter Institute, is considered one of the most astute thinkers in both science and society. This article is a latest synopsis of his mission to touch and figure out universe and human. We reprint the full Abstract, and other quotes so its gist can be conveyed. Something is going on beyond quantum realms, which it is difficult to find words for and to metaphorically express. Myriad microsystems tend to make “copies” of themselves, and proceed on to emerge into unique macrocosmic realms. In his writings Smolin has adopted the word “beable,” which Google can’t define, but is traceable to John Bell in a paper cited above. A new ensemble interpretation of quantum mechanics is proposed according to which the ensemble associated to a quantum state really exists: it is the ensemble of all the systems in the same quantum state in the universe. Individual systems within the ensemble have microscopic states, described by beables. Laws for the evolution of the beables of individual systems are given such that their ensemble relative frequencies evolve in a way that reproduces the predictions of quantum mechanics. These laws are highly nonlocal and involve a new kind of interaction between the members of an ensemble that define a quantum state. These include a stochastic process by which individual systems copy the beables of other systems in the ensembles of which they are a member. The probabilities for these copy processes do not depend on where the systems are in space, but do depend on the distribution of beables in the ensemble. Sone, Akira and Sebastian Deffner. Quantum and Classical Ergotropy from Relative Entropies. Entropy. 23/9, 2021. We enter this paper by Center for Nonlinear Studies, LANL and University of Maryland physicists to note the latest theoretical exercises with regard to this open habitable frontier which is now known to be graced by these malleable qualities and much more. See also Quantum Coherence and Ergotropy by Gianluca Francica, et al at arXov:2006.05424. The quantum ergotropy quantifies the maximal amount of work that can be extracted from a quantum state without changing its entropy. Given that the ergotropy can be expressed as the difference of quantum and classical relative entropies of the quantum state with respect to the thermal state, we define the classical ergotropy, which quantifies how much work can be extracted from distributions that are inhomogeneous on the energy surfaces. A unified approach to treat both quantum as well as classical scenarios is provided by geometric quantum mechanics, for which we define the geometric relative entropy. The analysis is concluded with an application of the conceptual insight to conditional thermal states, and the correspondingly tightened maximum work theorem. (Abstract) Spitz, Damiel, et al. Finding Universal Structures in Quantum ManyBody Dynamics via Persistent Homology. arXiv:2001.02616. We cite this entry by Heidelberg University physicists including Jurgen Berges (search) and Anna Wienhard for its report that this widely used mathematical method can be availed even in this deepest domain. Akin to its broad application to neural networks, galactic clusters and more, quantum phenomena are found to be quite amenable. Thus our Organics title and consequent universality is well supported. Inspired by topological data analysis techniques, we introduce persistent homology observables and apply them in a geometric analysis of quantum field theories. As a test case, we consider a twodimensional Bose gas far from equilibrium with a spectrum of dynamical scaling exponents. We find that the persistent homology exponents are inherently linked to the geometry of the system. The approach opens new ways to study quantum manybody dynamics in terms of robust topological structures. (Abstract)
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